Thèses : « Genomic biomarker »

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Liu, Yiding. « Technologies for Proteomic and Genomic Biomarker Analysis ». Cleveland State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=csu1229461302.

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ZANDA, VALERIA MARIA. « Development of new tools for genomic biomarker investigations ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19712.

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During drug research and development, biomarkers are broadly used to improve the understanding of drug mechanism of action, to investigate drug efficacy and safety, to support the selection of target patient population and to optimize treatment schedule. Among different classes of biomarkers, genomic biomarkers are defined as a measurable DNA or RNA characteristics that are indicator of normal biologic processes, pathogenic processes, and/or response to therapeutic or other intervention. A genomic biomarker can consist, for example, in one or more DNA characteristics such as single nucleotide polymorphisms (SNPs), insertions, deletions or RNA characteristics such as RNA expression levels, RNA processing (splicing and editing) and microRNA levels. The present research aimed at developing new genomics-based tools using non-conventional biological samples that might support biomarker investigations in clinical settings. Concerning DNA biomarkers, Single Nucleotide Polymorphisms (SNP) analysis was validated on DNA extracted from Formalin-Fixed Paraffin-Embedded (FFPE) tissue, from Hematoxylin and Eosin (H&E) stained FFPE slides, and from serum samples. Unconventional samples represent a challenge for genetic analysis due to limitation of biological material and/or the poor quality of the DNA extracted. For example, due to fixation effect and formaldehyde interaction DNA extracted from FFPE samples are characterized by degradation, cross-link, limitation of material, methylol derivatives and PCR inhibitors presence. Therefore before analyzing these samples a method validation is necessary to prove data reliability in accordance with Regulatory Agencies guidelines that encourage the scientific community to perform a fit-for-purpose method validation to support any pharmacogenetic data submission. SNPs were investigated by Real-Time PCR using TaqMan SNP genotyping assays. Polymorphisms in a panel of genes involved in EGFR pathway, which is directly associated with many type of cancer, were evaluated. In particular, each single assay was first validated for accuracy, intra-assay precision (repeatability under the same operating conditions) and ruggedness (reproducibility with different operators, different batches). These parameters were tested first on good quality DNA such as DNA extracted from cell lines and then on real sample to evaluate the non-conventional matrix. On this purpose, the impact of fragmented DNA (FFPE samples) and H&E staining on FFPE samples was evaluated. DNA was extracted from different tissues of 10 commercial donors. DNA genotyping results of unstained FFPE and H&E staining were compared with the genotype obtained from high quality genomic DNA extracted from Fresh Frozen (FF) tissues obtained from the same donors (used as reference samples). Overall, these results demonstrate that SNP genotyping can be performed on archived FFPE tissues providing reliable results. As additional test serum was used as source of DNA to perform SNPs analyses. Serum is usually used to investigate protein biomarker and is generally collected in most of the clinical trials. It has been demonstrated indeed that free circulating DNA is present in serum: in particular, DNA is present in healthy individual at low concentration while levels are higher in cancer patients, in arthritis, hepatitis (Board et al., 2008; Gahana et al., 2008; Gormally et al., 2007). To validate SNPs analysis on serum, two aliquots of whole blood were obtained from 35 healthy volunteers. For each subject one aliquot was used to extract good quality DNA, the other was used to prepare serum prior to DNA extraction. As expected DNA quantity was very low for serum samples. As result, even though DNA was not degraded, genotype analysis was successful only on 70% of the samples. Overall, the validation conducted showed that serum could be used as source of biological material to conduct genetic analyses. However limitation of DNA does not consent to perform a large panel of analysis. These could be further explored in patients since circulating DNA is present at higher levels in several diseases. Part of the present thesis focused also on the validation of methods for KRAS mutation analysis. This gene encodes for a G-protein which plays a key role in the Ras/mitogen-activated protein kinase (MAPK) signaling pathway and located downstream Epidermal Growth Factor Receptor (EGFR) which is involved in colorectal cancer (CRC). KRAS status can predict which patients benefit (KRAS wild-type) or do not benefit (KRAS mutated) from anti-EGFR therapy. Since KRAS analysis is also used for diagnostic analysis, an accurate validation of the method was required. The aim was to compare and validate two different methods for KRAS mutation detection on FFPE tumor specimens, and on H&E stained FFPE which represent an unconventional source of samples for this type of analysis. In particular, DxS ThreraScreen KRAS mutation kit, a Real-Time PCR assay, was compared to the PyroMark KRAS Kit, based on pyrosequencing technology. The DxS ThreraScreen KRAS mutation test kit is able to detect 7 different mutations present in codons 12 and 13 of the KRAS gene while PyroMark KRAS Kit is able to detect 9 KRAS mutations in codon 12-13 and 5 mutations in codon 61. Results from validation showed that both Pyrosequencing assay both DxS ThreraScreen assay are accurate and reproducible. Moreover no impact of degraded DNA obtained from FFPE or influence due to H&E staining was observed in both methods. In conclusion PyroMark KRAS Kit showed advantages such as lower amount of DNA needed for analysis, detection of additional mutations in cod.12/13 and codon 61 than DxS TheraScreen KRAS kit; on the other hand DxS TheraScreen KRAS resulted more sensitive than pyrosequencing assays and less time consuming. This thesis focused also on establishing a simple method to perform gene expression investigation on hair follicles (HF) and to evaluate its applicability in clinical trials. Despite 80% of solid cancers arising from epithelial tissues, blood is still one of the most common peripheral tissues used for biomarkers and pharmacogenomic investigations in oncology. Hair follicles may offer a viable alternative since they can reflect biological response in epithelial tissue, they are easy to collect (non-invasive) and available from most individuals. After the establishment of sample collection and RNA extraction, HFs were collected from 23 health donors to evaluate inter-individual variability of RNA yield and quality. Gene expression analysis was then conducted on the extracted RNA. First it was evaluated a panel of 16 housekeeping genes to assess the feasibility of the analysis. Then it was shown that in HF a panel of epithelial specific genes were expressed. Indeed, Realtime PCR analyses showed that EGFR, Keratin 19 (KRT19), Collagen, Melan-A were expressed in HFs but not in RNA derived from blood. On the opposite, FPR1 and PRF1 genes were expressed only in blood. These results suggest that HF represents a valuable biological source to study pathways active in epithelial tissue. Finally, gene expression analysis was conducted on an in vivo experiment to evaluate if a response to treatment could be observed in HFs. In particular, PD markers of Interferon treatment were investigated after in vivo subministration of Interferon-beta (IFN-β) in Macaca fascicularis. The expression of the known IFN-β responding genes MxA was investigated both in blood and in anagen HFs. Results showed that MxA induction was observed both in blood and HF: gene induction in blood was observed at 6 hours after subministration while in HF at 24 hours probably due to a different IFN-β distribution. These data suggest that gene expression analysis can be carried out in HF samples. However, it is important to highlight that in HF the response had a lower degree of induction and higher variability than in blood. However this preliminary observations need to be further explored in pilot clinical studies to evaluate its applicability. Overall the validation of different genomic analysis on unconventional sampled opens the possibility to conduct biomarker investigations on several clinical trials conducted in the past or to plan new investigations with non invasive methods. In addition, from the deep evaluation of the current guidelines from the Regulatory Agencies (and from the open debate in the scientific community) a proper strategy to validate genomic analytical assays was proposed according to fit-for-purpose criteria.

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Stagni, Camilla. « Genomic analysis in cutaneous melanoma : a tool for predictive biomarker identification and molecular classification ». Doctoral thesis, Università degli studi di Padova, 2017. http://hdl.handle.net/11577/3426683.

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Project 1. Identification of molecular signatures associated with response to MAPK inhibitors. BRAF V600-mutated melanoma benefits from MAPK inhibitors-based therapy. Yet, the onset of resistance impacts long-term efficacy and can even be immediate. In this study, we examined the genetic alterations characterizing melanoma progression to identify predictive factors of response to MAPK inhibitors (MAPKi). Specifically, we evaluated BRAF copy number variation (CNV), BRAF mutant (BRAFmut) allele frequency, PTEN loss or mutations and TERT promoter mutations in pre-treatment melanoma specimens from MAPKi-treated patients (pts) and we analyzed their association with progression free survival (PFS). We also applied a comprehensive unbiased approach, using genome-wide CNV analysis, to identify additional genomic aberrations potentially associated with response to therapy. We found that 65% pts displayed BRAF gains, often supported by chromosome 7 polysomy. In addition, we observed that 64% pts had a balanced BRAF mutant/wild-type allele ratio, while 14% and 23% pts had low and high BRAFmut allele frequency, respectively. Notably, a significantly higher risk of progression was observed in pts with a diploid BRAF status vs. those with BRAF gains (HR = 2.86; 95% CI 1.29‒6.35; p = 0.01) and in pts with low vs. those with a balanced BRAFmut allele percentage (HR = 4.54, 95% CI 1.33‒15.53; p = 0.016). We identified PTEN gene mutations affecting the catalitic and C2 domains in 27% pts. Moreover, we observed a complete PTEN loss in 42% pts, partial loss in 35% pts and no loss in 23% pts. Of note, we found PTEN loss also in pre-treatment samples from pts with long PFS. Sequencing of TERT promoter gene disclosed mutations in 78% pts. The -124C>T and the -146C>T mutations were equally frequent (36%) while the -138-139CC>TT was present only in 5% pts. Fifty-one % pts carried also the neighboring polymorphism rs2853669, which reportedly counteracts the activating effect of the above-mentioned mutations on TERT expression. Upon stratification of the TERT promoter mutant cohort based on presence/absence of the polymorphism, TERTmutant/SNPcarrier pts showed a trend toward better PFS (median PFS 11.5 mo., 95% CI 3.12‒19.88) compared to TERTmutant/SNPnon-carrier pts (median PFS 7 mo., 95% CI 4.27‒9.72). When stratifying based on mutation type, the -146C>T mutation correlated with shorter PFS (median PFS 5.45 mo., 95% CI 2.80‒9.20) compared to the -124C>T one (median PFS 15.2 mo., 95% CI 5.57‒). Genome-wide CNV analysis pointed at chr3p24, chr3p21.2 and chr17p13.1, which are differently alterated between pts with long and short time to disease progression, as regions of potential interest to identify new genes involved in therapeutic resistance. Our data suggest that quantitative analysis of the BRAF gene and sequencing of the TERT promoter gene could be useful to select the melanoma pts who are most likely to benefit from MAPKi therapy. In addition, chromosome 3 and 17 could be regions that warrant further investigation. Conversely, because PTEN loss was present in pre-treatment samples from pts with both short and long PFS, the assessment of PTEN gene status does not seem to provide information about patient responsiveness to treatment. Project 2. Research of molecular biomarkers to classify the acral melanoma. Acral lentiginous melanoma (ALM) is a rare subtype of cutaneous melanoma with specific morphological, epidemiological, and genetic features. Since the genomic landscape of ALM is still incompletely described, we used whole genome CNV analysis to characterize ALM and detail the genomic signatures that differentiate ALM from non-acral melanoma (NAM). We observed that the most strikingly different copy number aberrations were a higher frequency of losses of chromosome 16q24.2-16q24.3 in ALM than in NAM (64.7% vs. 10%) and a lower frequency of gains of chromosome 7q21.2-7q33 in ALM than in NAM (26.5% vs.79.5%). We observed also that ALM more often (than NAM) harbored clusters of breakpoints and isochromosomes. Moreover, in ALM we identified focal amplification of TERT, CCND1, MDM2 and MITF. In NAM, instead, we found only two focal amplifications, involving BRAF and MITF. Focal homozygous copy losses affected especially the CDKN2A and PTEN genes, both in ALM and in NAM, even though they were more frequent in the latter group. In keeping with previous observations that led to classify ALM as a distinct molecular subtype of melanoma, we observed a peculiar genomic landscape in ALM (vs. NAM). Our study provides insights into the molecular characteristics of ALM, which is key to full elucidation of its pathogenesis.
Progetto 1: identificazione di signatures molecolari associate alla risposta al trattamento con inibitori del MAPK pathway. I melanomi portatori di una mutazione nel codone V600 del gene BRAF rispondono agli inibitori del MAPK pathway, ma l’efficacia a lungo termine di questa terapia è limitata dallo sviluppo di resistenza, talvolta immediata. In questo studio, abbiamo esaminato le alterazioni molecolari caratterizzanti la progressione del melanoma al fine di identificare fattori predittivi di risposta/resistenza ai MAPK-inibitori. Nello specifico, su una serie di campioni pretrattamento di pazienti affetti da melanoma, trattati con MAPK-inibitori, abbiamo valutato numero di copie del gene BRAF e percentuale di allele V600-mutato, delezione e mutazioni di PTEN, alterazioni del promotore di TERT, e ne abbiamo analizzato l’associazione con la risposta dei pazienti alla terapia. Inoltre, abbiamo determinato il copy number variation dell’intero genoma dei nostri campioni per individuare ulteriori aberrazioni non note potenzialmente associate con la risposta alla terapia. Abbiamo identificato un numero aumentato di copie (gain) del gene BRAF, spesso dovuto a polisomia del cromosoma 7, nel 65% dei pazienti; l’allele mutato è stato trovato in una percentuale compresa tra il 35% e il 65% nel 64% dei pazienti, inferiore al 35% nel 14% dei pazienti e superiore al 65% nel 23% dei pazienti. Dall’analisi di sopravvivenza, è risultato che i pazienti con BRAF diploide o una percentuale di allele mutato inferiore al 35% presentano un più alto rischio di progressione rispetto a coloro che presentano gain di BRAF (HR=2.86; 95% CI 1.29-6.35; p=0.01) o tra il 35% e il 65% di allele mutato (HR=4.54,CI 1.33-15.53; p=0.016), rispettivamente. L’analisi di PTEN ha rivelato la presenza di mutazioni nel 27% dei pazienti, localizzate a livello dei domini catalitico e C2 della proteina codificata; inoltre, il 42% dei casi valutati mostrava una delezione completa del gene, il 35% una delezione parziale, mentre nel 23% dei pazienti non è stata individuata alcuna aberrazione di PTEN. Da notare, delezioni di PTEN sono emerse sia nei casi di melanoma resistente alla terapia, che in quelli che avevano risposto a lungo. Il sequenziamento del promotore del gene TERT ha permesso l’identificazione di mutazioni nel 78% dei pazienti. Le mutazioni -124C>T e -146C>T mostravano la stessa frequenza (36%) nella nostra coorte, mentre la -138-139CC>TT è stata individuata solo nel 5% dei casi. Il 51% dei pazienti presentava inoltre lo SNP rs2853669, noto per contrastare l’effetto attivante delle mutazioni sull’espressione di TERT. Stratificando la coorte di pazienti mutati in base alla presenza/assenza del polimorfismo, i pazienti TERT mutati/SNP carriers mostravano un trend verso una migliore PFS (PFS mediana 11.5 mesi, 95% CI 3.12-19.88) rispetto ai TERT mutati/SNP non-carriers (PFS mediana 7 mesi, 95% CI 4.27-9.72). La mutazione -146C>T, inoltre, correlava con PFS più breve (PFS mediana 5.45 mesi, 95% CI 2.80-9.20) rispetto alla -124C>T (PFS mediana 15.2 mesi, 95% CI 5.57-). Dall’analisi del copy number variation (CNV) sull’intero genoma, le regioni chr3p24, chr3p21.2 e chr17p13.1 hanno mostrato pattern di alterazioni diverse in pazienti responsivi vs. non-responsivi alle terapie; risultano pertanto regioni di potenziale interesse per l’individuazione di nuovi geni coinvolti nella resistenza alla terapia. I nostri dati suggeriscono dunque che l’analisi quantitativa del gene BRAF e il sequenziamento del promotore di TERT costituiscono un utile strumento di selezione dei pazienti con maggiore probabilità di rispondere alla terapia con MAPK-inibitori, contrariamente alla valutazione dello status di PTEN. L’analisi genome-wide, invece, indica di approfondire lo studio dei cromosomi 3 e 17. Progetto 2: ricerca di marcatori biomolecolari per la classificazione del melanoma acrale. Il melanoma acrale lentigginoso è un raro sottotipo di melanoma cutaneo con specifiche caratteristiche morfologiche, epidemiologiche e genetiche. Poiché il genoma del melanoma acrale non è ancora stato pienamente caratterizzato, ne abbiamo analizzato il CNV per individuare quei caratteri genomici peculiari che lo differenziano dal melanoma non acrale. La nostra analisi genome-wide ha evidenziato una maggiore frequenza di delezioni della regione 16q24.2-16q24.3, gains meno frequenti nella regione 7q21.2-7q33, una più accentuata frammentazione genomica e numerosi isocromosomi come caratteri che distinguono il melanoma acrale dal non acrale. Abbiamo inoltre identificato amplificazioni focali nei geni TERT, CCND1, MDM2 e MITF, più rare nei non acrali, laddove interessavano altri geni, come BRAF e MITF. Delezioni focali sono state individuate soprattutto nei geni CDKN2A e PTEN in entrambi i sottotipi di melanoma, anche se più frequenti nei non acrali. I nostri dati, in accordo con il classificare il melanoma acrale come tipo distinto di melanoma, hanno consentito di delinearne alcune delle peculiarità genomiche, chiave per elucidarne anche la patogenesi.

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ZILIOTTO, Nicole. « Genomic, vessel wall transcriptomic, and plasma proteomic approaches to investigate multiple sclerosis ». Doctoral thesis, Università degli studi di Ferrara, 2019. http://hdl.handle.net/11392/2487975.

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This study was designed to investigate, by several experimental approaches, genes, and proteins associated with multiple sclerosis (MS), an inflammatory and demyelinating disease of the central nervous system (CNS). The study design was aimed to prioritize, by the investigation in patients, potential targets and biomarkers for future mechanistic studies. Through the genomic approach(chpt.10), selected families were investigated by WES for candidate genes from GWAS. The identified low-frequency variants were further investigated in unrelated MS patients. A number of rare and novel mutations were detected, and particularly null variants in the C6orf10 3’ region, in combination with both intra and extra locus low-frequency SNPs. These findings provide the bases for expression studies. The transcriptomic approach (chpt.6) was focused on the internal jugular vein wall, supported by the interaction between vascular and neurodegenerative mechanisms in MS. This original investigation produced a wealth of information on several biological pathways and permitted the combined transcriptome-protein analysis, which provided intriguing biological and clinical hints. Analysis at protein level was conducted in plasma by multiplex assays in relation to clinical MS phenotypes and brain MRI measures, as quantitative and “intermediate” phenotypes evaluating disease progression. Higher CCL18 plasma levels were associated with more severe neurodegenerative features, a noticeable finding(chpt.7). The contribution of adhesion molecules, suggested by the transcriptomic analysis, was similarly explored(chpt.8 and 9). Correlation between plasma levels of specific adhesion molecules in MS patients highlights the leukocyte adhesion process in disease. Increased blood-brain-barrier permeability, a key event in the MS pathophysiology, leads to the irruption of coagulation and hemostasis factors into the CNS, potentially causing an inflammatory response and immune activation. We investigated hemostasis components with main open questions in relation to MS. FXII, the key protease of the coagulation contact activation found deposited in patients’ brain, might participate in adaptive immunity during neuroinflammation. In plasma of MS patients(chpt.4), FXII protein levels were higher than activity, causing a decreased activity/antigen ratio. These findings, corroborated by specifically designed intrinsic thrombin generation assays, might support that FXII contribution in MS is not directly correlated with its “intrinsic” pro-coagulant activity. Negative regulators of hemostasis (TFPI, ADAMTS13, HCII, TM) with anti-inflammatory properties were also studied, which detected specific patterns of correlations (chpt.5 and 11). Positive association of TFPI with TM, observed in MS patients and not in healthy subjects, would imply that endothelium perturbation acts on multiple release mechanisms. In patients, PAI-1, the key fibrinolysis inhibitor, was positively associated with FXII, and negatively associated with HCII, which suggest disease mechanisms influencing their expression in different tissues with implications in fibrin generation/impaired fibrinolysis, important contributors to neuro-inflammation/degeneration. Correlations observed between hemostasis components plasma levels and MRI measures, of interest for brain disease mechanisms, did not overcome correction for multiple comparisons. Extravascular leakage of blood components in MS patients, measured as cerebral microbleeds (CMBs) by MRI, was investigated in relation to plasma levels of hemostasis components. Interestingly, lower ADAMTS13 levels were detected in the MS cohort, in particular in patients with CMBs (chpt.5), who also showed higher VAP-1 levels(chpt.9). These novel findings support the investigation of the plasma protease ADAMTS13, and the amino oxidase/adhesion protein VAP-1, in relation to CMBs. This study provides novel MS disease biomarkers as well as potential drug targets
Questo studio è stato progettato per indagare attraverso diversi approcci sperimentali i geni e le proteine associate alla sclerosi multipla (SM), una malattia infiammatoria e demielinizzante del sistema nervoso centrale (SNC). L’obiettivo era individuare mediante indagini su pazienti, potenziali bersagli e biomarcatori per futuri studi meccanicistici. Mediante l'approccio genomico(cap.10), le famiglie selezionate sono state studiate attraverso WES per geni candidati da GWAS. Gli SNPs identificati a bassa frequenza sono stati ulteriormente studiati in pazienti indipendenti con SM. L’indagine ha rilevato varianti rare e nuove, tra cui le nulle della regione 3' di C6orf10 in combinazione con SNPs a bassa frequenza a livello intra ed extra locus, fornendo le basi per studi di espressione. L'approccio trascrittomico(cap.6) focalizzato sulla parete interna della vena giugulare, era supportato dall'interazione tra i meccanismi vascolari e quelli neurodegenerativi nella SM. Questa indagine ha prodotto una grande quantità di informazioni su diversi percorsi biologici e ha permesso l'analisi combinata trascrittoma-proteine. L'analisi a livello proteico è stata condotta nel plasma mediante saggi multiplex in relazione ai fenotipi clinici di SM e alle misure cerebrali MRI considerate come fenotipi quantitativi e "intermedi" della progressione della malattia. I livelli plasmatici più alti di CCL18 erano associati a caratteristiche neurodegenerative più gravi(cap.7). Il contributo delle molecole di adesione, suggerito dall'analisi trascrittomica, è stato esplorato in modo analogo(cap.8 e 9). La correlazione tra i livelli plasmatici di specifiche molecole di adesione nei pazienti ha evidenziato il processo di adesione dei leucociti nella malattia. L'aumento della permeabilità della barriera emato-encefalica, evento chiave nella fisiopatologia della SM, porta all’irruzione di fattori emostatici nel SNC, causando una risposta infiammatoria e l’attivazione immunitaria. I componenti dell'emostasi con le principali domande aperte in relazione alla SM sono stati investigati. Il FXII, la proteasi attivatrice della coagulazione da contatto trovata depositata nel cervello dei pazienti, potrebbe partecipare all'immunità adattativa durante la neuroinfiammazione. Nel plasma di pazienti(cap.4) i livelli di proteina del FXII erano superiori all'attività, causando un ridotto rapporto attività/antigene. I risultati corroborati dai saggi di generazione intrinseca di trombina, supporterebbero il contributo del FXII nella SM non attraverso la sua attività pro-coagulante. Lo studio di alcuni inibitori dell'emostasi (TFPI, ADAMTS13, HCII, TM) con proprietà antinfiammatorie, ha rivelato specifici schemi di correlazione(cap.5 e 11). L'associazione positiva di TFPI con TM, osservata nei pazienti e non in soggetti sani, implicherebbe che la perturbazione dell'endotelio agisca su più meccanismi di rilascio. Nei pazienti il PAI-1, l'inibitore chiave della fibrinolisi, era associato positivamente al FXII e negativamente all'HCII, suggerendo meccanismi patologici che influenzano la loro espressione in diversi tessuti con implicazioni nella generazione di fibrina e nella compromissione della fibrinolisi. Le correlazioni osservate tra i livelli plasmatici dei componenti dell'emostasi con le misure di MRI, non hanno superato la correzione per confronti multipli. La perdita extravascolare di sangue misurata come micro sanguinamenti cerebrali (MSC) attraverso MRI è stata studiata nei pazienti in relazione ai livelli plasmatici di componenti dell'emostasi. Livelli più bassi di ADAMTS13 sono stati rilevati nella coorte di SM ed in particolare nei pazienti con MSC(cap.5) che mostravano anche livelli più alti di VAP-1(cap.9). Queste nuove scoperte supportano l'analisi della proteasi ADAMTS13 e l’aminossidasi/proteina di adesione VAP-1 in relazione ai MSC. Questo studio fornisce nuovi biomarcatori della SM e potenziali bersagli farmacologici

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Sanavia, Tiziana. « Biomarker lists stability in genomic studies : analysis and improvement by prior biological knowledge integration into the learning process ». Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3422197.

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The analysis of high-throughput sequencing, microarray and mass spectrometry data has been demonstrated extremely helpful for the identification of those genes and proteins, called biomarkers, helpful for answering to both diagnostic/prognostic and functional questions. In this context, robustness of the results is critical both to understand the biological mechanisms underlying diseases and to gain sufficient reliability for clinical/pharmaceutical applications. Recently, different studies have proved that the lists of identified biomarkers are poorly reproducible, making the validation of biomarkers as robust predictors of a disease a still open issue. The reasons of these differences are referable to both data dimensions (few subjects with respect to the number of features) and heterogeneity of complex diseases, characterized by alterations of multiple regulatory pathways and of the interplay between different genes and the environment. Typically in an experimental design, data to analyze come from different subjects and different phenotypes (e.g. normal and pathological). The most widely used methodologies for the identification of significant genes related to a disease from microarray data are based on computing differential gene expression between different phenotypes by univariate statistical tests. Such approach provides information on the effect of specific genes as independent features, whereas it is now recognized that the interplay among weakly up/down regulated genes, although not significantly differentially expressed, might be extremely important to characterize a disease status. Machine learning algorithms are, in principle, able to identify multivariate nonlinear combinations of features and have thus the possibility to select a more complete set of experimentally relevant features. In this context, supervised classification methods are often used to select biomarkers, and different methods, like discriminant analysis, random forests and support vector machines among others, have been used, especially in cancer studies. Although high accuracy is often achieved in classification approaches, the reproducibility of biomarker lists still remains an open issue, since many possible sets of biological features (i.e. genes or proteins) can be considered equally relevant in terms of prediction, thus it is in principle possible to have a lack of stability even by achieving the best accuracy. This thesis represents a study of several computational aspects related to biomarker discovery in genomic studies: from the classification and feature selection strategies to the type and the reliability of the biological information used, proposing new approaches able to cope with the problem of the reproducibility of biomarker lists. The study has highlighted that, although reasonable and comparable classification accuracy can be achieved by different methods, further developments are necessary to achieve robust biomarker lists stability, because of the high number of features and the high correlation among them. In particular, this thesis proposes two different approaches to improve biomarker lists stability by using prior information related to biological interplay and functional correlation among the analyzed features. Both approaches were able to improve biomarker selection. The first approach, using prior information to divide the application of the method into different subproblems, improves results interpretability and offers an alternative way to assess lists reproducibility. The second, integrating prior information in the kernel function of the learning algorithm, improves lists stability. Finally, the interpretability of results is strongly affected by the quality of the biological information available and the analysis of the heterogeneities performed in the Gene Ontology database has revealed the importance of providing new methods able to verify the reliability of the biological properties which are assigned to a specific feature, discriminating missing or less specific information from possible inconsistencies among the annotations. These aspects will be more and more deepened in the future, as the new sequencing technologies will monitor an increasing number of features and the number of functional annotations from genomic databases will considerably grow in the next years.
L’analisi di dati high-throughput basata sull’utilizzo di tecnologie di sequencing, microarray e spettrometria di massa si è dimostrata estremamente utile per l’identificazione di quei geni e proteine, chiamati biomarcatori, utili per rispondere a quesiti sia di tipo diagnostico/prognostico che funzionale. In tale contesto, la stabilità dei risultati è cruciale sia per capire i meccanismi biologici che caratterizzano le malattie sia per ottenere una sufficiente affidabilità per applicazioni in campo clinico/farmaceutico. Recentemente, diversi studi hanno dimostrato che le liste di biomarcatori identificati sono scarsamente riproducibili, rendendo la validazione di tali biomarcatori come indicatori stabili di una malattia un problema ancora aperto. Le ragioni di queste differenze sono imputabili sia alla dimensione dei dataset (pochi soggetti rispetto al numero di variabili) sia all’eterogeneità di malattie complesse, caratterizzate da alterazioni di più pathway di regolazione e delle interazioni tra diversi geni e l’ambiente. Tipicamente in un disegno sperimentale, i dati da analizzare provengono da diversi soggetti e diversi fenotipi (e.g. normali e patologici). Le metodologie maggiormente utilizzate per l’identificazione di geni legati ad una malattia si basano sull’analisi differenziale dell’espressione genica tra i diversi fenotipi usando test statistici univariati. Tale approccio fornisce le informazioni sull’effetto di specifici geni considerati come variabili indipendenti tra loro, mentre è ormai noto che l’interazione tra geni debolmente up/down regolati, sebbene non differenzialmente espressi, potrebbe rivelarsi estremamente importante per caratterizzare lo stato di una malattia. Gli algoritmi di machine learning sono, in linea di principio, capaci di identificare combinazioni non lineari delle variabili e hanno quindi la possibilità di selezionare un insieme più dettagliato di geni che sono sperimentalmente rilevanti. In tale contesto, i metodi di classificazione supervisionata vengono spesso utilizzati per selezionare i biomarcatori, e diversi approcci, quali discriminant analysis, random forests e support vector machines tra altri, sono stati utilizzati, soprattutto in studi oncologici. Sebbene con tali approcci di classificazione si ottenga un alto livello di accuratezza di predizione, la riproducibilità delle liste di biomarcatori rimane ancora una questione aperta, dato che esistono molteplici set di variabili biologiche (i.e. geni o proteine) che possono essere considerati ugualmente rilevanti in termini di predizione. Quindi in teoria è possibile avere un’insufficiente stabilità anche raggiungendo il massimo livello di accuratezza. Questa tesi rappresenta uno studio su diversi aspetti computazionali legati all’identificazione di biomarcatori in genomica: dalle strategie di classificazione e di feature selection adottate alla tipologia e affidabilità dell’informazione biologica utilizzata, proponendo nuovi approcci in grado di affrontare il problema della riproducibilità delle liste di biomarcatori. Tale studio ha evidenziato che sebbene un’accettabile e comparabile accuratezza nella predizione può essere ottenuta attraverso diversi metodi, ulteriori sviluppi sono necessari per raggiungere una robusta stabilità nelle liste di biomarcatori, a causa dell’alto numero di variabili e dell’alto livello di correlazione tra loro. In particolare, questa tesi propone due diversi approcci per migliorare la stabilità delle liste di biomarcatori usando l’informazione a priori legata alle interazioni biologiche e alla correlazione funzionale tra le features analizzate. Entrambi gli approcci sono stati in grado di migliorare la selezione di biomarcatori. Il primo approccio, usando l’informazione a priori per dividere l’applicazione del metodo in diversi sottoproblemi, migliora l’interpretabilità dei risultati e offre un modo alternativo per verificare la riproducibilità delle liste. Il secondo, integrando l’informazione a priori in una funzione kernel dell’algoritmo di learning, migliora la stabilità delle liste. Infine, l’interpretabilità dei risultati è fortemente influenzata dalla qualità dell’informazione biologica disponibile e l’analisi delle eterogeneità delle annotazioni effettuata sul database Gene Ontology rivela l’importanza di fornire nuovi metodi in grado di verificare l’attendibilità delle proprietà biologiche che vengono assegnate ad una specifica variabile, distinguendo la mancanza o la minore specificità di informazione da possibili inconsistenze tra le annotazioni. Questi aspetti verranno sempre più approfonditi in futuro, dato che le nuove tecnologie di sequencing monitoreranno un maggior numero di variabili e il numero di annotazioni funzionali derivanti dai database genomici crescer`a considerevolmente nei prossimi anni.

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Zanjirband, Maryam. « The genomic and functional status of TP53 in ovarian cancer : biomarker for chemotherapy outcome and determinant of response to MDM2 inhibitors ». Thesis, University of Newcastle upon Tyne, 2017. http://hdl.handle.net/10443/3831.

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Background: Mutation and loss of TP53 function is one of the most frequent genetic abnormalities in ovarian cancer. TP53 genomic and functional status have been shown to provide potentially prognostic and predictive value in ovarian cancer; however, the results are controversial and evaluation in the context of a controlled clinical trial with single agent treatment have been lacking. Reactivation of p53 using MDM2-p53 antagonists is a promising therapeutic target for most patients with type I epithelial ovarian cancer and those left from type II harbouring wild-type TP53. BRCA1/2 mutations are present in 70-85% of germline mutations in patients with inherited ovarian cancer, and deficiencies in homologous recombination repair (HRR) account for up to 50% of epithelial ovarian cancer, indicating the possible sensitivity of ovarian cancer patients to PARP inhibitors. MDM2-p53 antagonists and PARP inhibitors are now undergoing clinical trials as targeted therapy for different types of cancer. The effect of RG7388 on its own and in combination with cisplatin, and combined treatment between MDM2-p53 antagonists and PARP inhibitors have not been investigated in ovarian cancer. Hypotheses: 1) Different genomic and functional status of p53 and some of its downstream targets such as p21WAF1, MDM2 and WIP1 can be used as prognostic and predictive biomarkers for the outcome of chemotherapy and overall survival in ovarian cancer. 2) Reactivation of p53 by inhibition of its negative regulator MDM2, using the MDM2-p53 antagonists Nutlin-3 and RG7388, will result in p53-mediated growth arrest and apoptosis in wild-type TP53 ovarian cancer cells, and combination of them with current therapeutic agents or rucaparib increases growth inhibition and/or apoptosis in ovarian cancer cell lines compared to either agent alone. Methods: TP53 was sequenced in 260 ovarian cancer samples from the ICON3 trial using Sanger sequencing and Next Generation Sequencing (NGS) methods. The prognostic value of the expression levels of p53, p21WAF1, MDM2 and WIP1 was investigated using immunohistochemistry (IHC). The effect of MDM2-p53 antagonists, Nutlin-3/RG7112/RG7388, and PARP inhibitor, rucaparib, as single agents and in combination with cisplatin or together were investigated on a panel of ovarian cancer cell lines. Sensitivity was measured by growth inhibition, clonogenic cell survival assay, apoptosis assays including caspase 3/7 activity and flow cytometry. The effect on the p53 molecular pathway and p53-regulated candidate gene expression were investigated by western blotting and Quantitative Reverse-Transcription Polymerase Chain Reaction (qRT-PCR) respectively. Results: Patients from the ICON3 clinical trial treated with carboplatin whose tumours harbour wild-type TP53 had a significantly better overall survival based on both univariate and multivariate analysis compared to those with mutant TP53 regardless of sequencing method. Adding paclitaxel to the platinum-based treatment showed a trend in favour of greater benefit for those with mutant TP53, although this failed to reach statistical significance (p > 0.05). Overexpression of p53 has potential prognostic value for overall survival of ovarian cancer patients. Ovarian cancer cell lines with wild-type TP53 were sensitive to MDM2-p53 antagonists, Nutlin-3/RG7112/RG7388, while those with mutant TP53 were resistant to MDM2 inhibitors. Among the individual cell lines, A2780 and MDAH-2774 were sensitive and other cell lines (IGROV-1, OAW42, CP70, MLH1-corrected CP70+ and SKOV-3) were resistant to rucaparib regardless of BRCA1/BRCA2 status or deficiencies in HRR reported for these cell lines. Combination of Nutlin-3/RG7388 with cisplatin or rucaparib has synergistic and/or dose reduction potential dependent on cell genotype and the type of MDM2-p53 antagonist. Combined treatments using Nutlin-3/RG7388 and cisplatin led to greater levels of p53 stabilisation and upregulation of p21WAF1 and MDM2, and higher expression of p21WAF1 was associated with a greater synergistic effect for growth inhibition. In combination treatment with rucaparib and Nutlin-3/RG7388, rucaparib showed no increase in the effect of MDM2 inhibitors on the p53 pathway, indicating that the mechanism of observed synergy does not involve enhancement of p53 pathway activation by MDM2 inhibitors. Nutlin-3/RG7388 in combination with cisplatin or rucaparib resulted in changes in cell cycle distribution, SubG1 events and caspase 3/7 activity in a cell type, time and compound-dependent manner. The fold changes in expression of candidate genes in response to MDM2 inhibitors were less in A2780 cells than IGROV-1 and OAW42. The balance of activity between growth inhibitory/pro-survival and pro-apoptotic genes dominates a small increase in the expression of several DNA repair genes as an explanation for the synergy observed for treatment with cisplatin and MDM2 inhibitors. Conclusions: The genomic and functional status of TP53 have potentially important prognostic and predictive values in ovarian cancer. Targeting the interaction between MDM2 and p53 using MDM2-p53 antagonists is a promising therapeutic strategy for ovarian cancer patients with wild-type TP53 tumours, and combination treatment with them and cisplatin or rucaparib.

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Pereira, Carolina Ruivo 1986. « Genomic profile of tumorgrafts identifies B2M as a novel tumor suppressor gene in lung cancer ». Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/482055.

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El cáncer de pulmón es la forma más mortal de cáncer en el mundo. Recientemente, el estudio del perfil genómico a larga escala de tumores humanos ha impulsado el desarrollo de drogas que tienen como diana terapéutica genes alterados. Dado que las terapias dirigidas son escasas, el descubrimiento de nuevos genes implicados en cáncer de pulmón con relevancia clínica es crucial. Por eso, este proyecto tuvo como base la secuenciación de exomas y transcriptomas de xenotransplantes de pulmón. La pureza tumoral alcanzada durante el injerto fue fundamental, sobre todo para identificar delecciones homocigóticas y amplificaciones génicas. El gen B2M (β2-microglobulina), encontrado inactivado en 5% de los tumores pulmonares, se caracterizó. Su pérdida genética se correlacionó con bajos niveles de infiltración intratumoral por linfocitos T citotóxicos. Además, la β2-microglobulina se asoció a supervivencia en pacientes tratados con agentes anti-PD1/PD-L1, evidenciando su rol potencial el predecir respuestas a inmunoterapias en neoplasias pulmonares.
Lung cancer is the deadliest form of cancer worldwide. Recently, the large-scale genomic profiling of human tumors has fueled the development of efficient anticancer agents that target the activity of mutated genes. Given that directed therapies are still very scarce, the discovery of novel lung cancer-related genes with potential relevance within the clinical context is imperative. Thus, this project consisted on coupling high-throughput sequencing strategies (exomes and transcriptomes) with the use of lung tumorgrafts. The high tumor purity achieved through the engraftment was crucial, particularly to identify homozygous deletions and gene amplifications. The B2M gene (β2-microglobulin), found to be mutated in 5% of lung tumors, was characterized. Its genetic loss was correlated to lower cytotoxic T-cell intratumoral infiltration, probably impairing the immune-mediated tumor eradication. Moreover, β2-microglobulin was associated with survival in patients treated with anti-PD-1/PD-L1 agents, highlighting a potential role in predicting response to immunologically-based therapies in lung cancer.

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Jiao, Yunlong. « Pronostic moléculaire basé sur l'ordre des gènes et découverte de biomarqueurs guidé par des réseaux pour le cancer du sein ». Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEM027/document.

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Le cancer du sein est le deuxième cancer le plus répandu dans le monde et la principale cause de décès due à un cancer chez les femmes. L'amélioration du pronostic du cancer a été l'une des principales préoccupations afin de permettre une meilleure gestion et un meilleur traitement clinique des patients. Avec l'avancement rapide des technologies de profilage génomique durant ces dernières décennies, la disponibilité aisée d'une grande quantité de données génomiques pour la recherche médicale a motivé la tendance actuelle qui consiste à utiliser des outils informatiques tels que l'apprentissage statistique dans le domaine de la science des données afin de découvrir les biomarqueurs moléculaires en lien avec l'amélioration du pronostic. Cette thèse est conçue suivant deux directions d'approches destinées à répondre à deux défis majeurs dans l'analyse de données génomiques pour le pronostic du cancer du sein d'un point de vue méthodologique de l'apprentissage statistique : les approches basées sur le classement pour améliorer le pronostic moléculaire et les approches guidées par un réseau donné pour améliorer la découverte de biomarqueurs. D'autre part, les méthodologies développées et étudiées dans cette thèse, qui concernent respectivement l'apprentissage à partir de données de classements et l'apprentissage sur un graphe, apportent une contribution significative à plusieurs branches de l'apprentissage statistique, concernant au moins les applications à la biologie du cancer et la théorie du choix social
Breast cancer is the second most common cancer worldwide and the leading cause of women's death from cancer. Improving cancer prognosis has been one of the problems of primary interest towards better clinical management and treatment decision making for cancer patients. With the rapid advancement of genomic profiling technologies in the past decades, easy availability of a substantial amount of genomic data for medical research has been motivating the currently popular trend of using computational tools, especially machine learning in the era of data science, to discover molecular biomarkers regarding prognosis improvement. This thesis is conceived following two lines of approaches intended to address two major challenges arising in genomic data analysis for breast cancer prognosis from a methodological standpoint of machine learning: rank-based approaches for improved molecular prognosis and network-guided approaches for enhanced biomarker discovery. Furthermore, the methodologies developed and investigated in this thesis, pertaining respectively to learning with rank data and learning on graphs, have a significant contribution to several branches of machine learning, concerning applications across but not limited to cancer biology and social choice theory

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Moreira, Elisa Rennó Donnard. « Estudo de variações genômicas para a identificação de biomarcadores personalizados e novos alvos terapêuticos em tumores colorretais ». Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/46/46131/tde-20012015-101640/.

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O câncer colorretal é um dos tipos de tumores mais frequentes no mundo. A atual dificuldade na avaliação correta da resposta ao tratamento torna necessário o desenvolvimento de novas abordagens de detecção tumoral. Atualmente, o sequenciamento genômico em larga escala permite um estudo mais compreensivo das alterações estruturais e de sequência presentes no tumor. A aplicação destas abordagens de maneira personalizada permite o desenvolvimento de biomarcadores tumor específicos que podem facilitar a avaliação de resposta ao tratamento e a presença de doença residual, bem como revelar alterações de sequência em genes capazes de servir de novos alvos terapêuticos. Neste estudo foi desenvolvida uma metodologia eficiente para a identificação de biomarcadores baseados na existência de variações estruturais em genomas de tumores de reto, eliminando a necessidade de sequenciamento do genoma normal do mesmo paciente e diminuindo portanto o custo da abordagem. Os biomarcadores encontrados para cada um dos seis pacientes foram utilizados para avaliar a presença de doença residual após o tratamento através da detecção de DNA tumoral circulante nas amostras de plasma coletadas em momentos diferentes do tratamento. O sequenciamento em baixa cobertura personalizado é portanto uma alternativa viável e promissora para avaliar a resposta ao tratamento em pacientes com tumores de reto. Na segunda parte do estudo, a análise de linhagens celulares de tumores colorretais revelou uma grande quantidade de mutações pontuais somáticas (SNVs e InDels) em genes codificadores para proteínas de superfície celular (surfaceoma). Estas alterações no surfaceoma indicam potenciais novos alvos para drogas e vias regulatórias alteradas neste tipo de tumor. Além disso, estas mutações pontuais também são responsáveis pela geração de epítopos com potencial imunogênico e estes novos epítopos podem ser aplicados como vacinas antitumorais personalizadas e já haviam sido propostos como uma alternativa terapêutica. A presença de novos epítopos, principalmente nas linhagens com elevadas taxas de mutação (resultante da instabilidade de microssatélites e mutações em genes de reparo de DNA tipo mismatch ou POLE), sugerem também um potencial uso de drogas moduladoras do sistema imune em pacientes com tumores que apresentam estas mesmas características. Portanto, o estudo de alterações genômicas em tumores primários e linhagens de câncer colorretal permitiu a detecção de variações estruturais que foram utilizadas como biomarcadores personalizados em pacientes com tumores de reto assim como a identificação de genes contendo mutações pontuais em linhagens celulares de câncer colorretal, que revelam potenciais novos alvos terapêuticos a serem explorados na clínica
Colorectal cancer is one of the more frequent tumor types in the world. To select the appropriate treatment course, it is necessary to develop more precise diagnostic approaches. The current availability of high throughput genome sequencing methods allows for a comprehensive characterization of the structural and sequence alterations present in each tumor. The use of tumor genome sequencing in a personalized setting can result in tumor specific biomarkers that help evaluate response to treatment and the presence of residual disease, improving the clinical management of these patients, and also reveal sequence alterations in genes capable of serving as new therapeutic targets. In this study we developed an efficient bioinformatics pipeline to identify biomarkers based on the existing structural alterations in rectal tumor genomes, eliminating the need to sequence the matched normal genome and therefore reducing the cost for this approach. The biomarkers found for each of the six patients were used to evaluate the presence of residual disease after treatment through the detection of circulating tumor DNA in plasma samples collected at different points during the treatment. Sequencing tumor genomes with low coverage is therefore a viable and promising alternative to follow up rectal cancer patient\'s response to treatment. In the second part of this study, the analysis of colorectal cancer cell lines revealed a large quantity of point mutations (SNVs and InDels) in genes coding for proteins located in the cell surface (surfaceome). These alterations in the surfaceome indicate potential new drug targets and altered pathways in this type of tumor. Furthermore, these point mutations are also responsible for the generation of new epitopes with immunogenic potential and these new epitopes can be applied as personalized tumor vaccines and had previously been proposed as a therapeutic alternative. The presence of new epitopes, especially in the cell lines with elevated mutation rates (resulting from MSI and mutations in DNA mismatch-repair genes or POLE), suggests a potential use of immune checkpoint target drugs in patients with tumors that share these genetic characteristics. With a large-scale bioinformatics approach, we detected new tumor epitopes resulting from point mutations, present in most of the cell lines used. The analysis of gene expression data puts into perspective both the somatic mutations found and which targets are promising as well as the development of therapies based on vaccines derived from tumor epitopes. In conclusion, the study of genomic alterations in primary tumors and colorectal cancer cell lines allowed the detection of structural variations that were used as personalized biomarkers in patients with rectal tumors as well as the identification of genes containing point mutations in colorectal cancer cell lines, that reveal potential new therapeutic targets to be explored in the clinical setting.

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Brown, Margaret M. « Application of genomic techniques to development of biomarkers for the aquatic environment ». Thesis, Glasgow Caledonian University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.443169.

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Tcherveniakov, Peter Alexandrov. « Genomic biomarkers of recurrence in stage I non-small cell lung cancer ». Thesis, University of Leeds, 2015. http://etheses.whiterose.ac.uk/11903/.

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Objective: Lung cancer is the leading cause of cancer-related mortality worldwide. Disease stage still remains the best prognostic factor for patients with localized non-small cell lung cancer. The TNM staging system, however, does not address the heterogeneity of this disease. Sub-classification and identification of distinct prognostic sub-groups within each stage may allow the optimization of clinical trial design and potentially improve outcome. This is a retrospective pilot study, in which we attempt to identify genomic biomarkers predictive of recurrence in stage I lung cancer by analysing copy number (CN) data obtained by next-generation sequencing. Materials and Methods: Ninety eight patients with stage I NSCLC, who underwent elective radical surgery were identified from a tissue bank of 323 tumour samples. Their demographic and surgical data, including their recurrence status were collected and an extensive database compiled. The cases were split into two cohorts depending on their histology (adenocarcinoma vs. squamous cell carcinoma). Formalin-fixed paraffin-embedded blocks were retrieved from the local pathology archive and DNA was extracted from macrodissected tumour tissue using the QiAmp DNA microkit. DNA libraries were prepared and samples were sequenced using Illumina Genome Analyzer II. The frequency of CN gain and loss along the entire genome was compared between the recurrent and non-recurrent cancers. Results: Comparative whole genome maps of the recurrent and non-recurrent cohort did not show any significant differences. Attempts to distinguish the recurrent from the non-recurrent cohorts with previously published algorithms, based on whole genome CN variation were also unsuccessful. However, a newly devised logistic regression model based on pan-genomic assessment of CN variation was able to differentiate recurrent from non-recurrent cancers in both histological subtypes. Conclusion: Although no single chromosomal region was associated with cancer recurrence, the two groups were distinguishable with an algorithm that assesses total genomic change. Analysis of a larger cohort will be required for validation.

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Huang, Jie. « Whole-genome sequencing-based association studies of cardiovascular biomarkers ». Thesis, University of Cambridge, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708994.

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Guan, Xiaojing. « Genomic and biochemical analysis of oxidative stress in birds with diverse longevities ». Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/27827.

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The relationship among oxidative stress, mitochondrial DNA integrity, and longevity continues to be without a general consensus. Here, we hypothesize that short- and long-lived birds, including the budgerigar (Melopsittacus undulatus), guineafowl (Numida meleagris), quail (Corturnix japonica), and turkey (Meleagris gallopavo) differ in oxidative stress measured by blood markers and that this difference correlates with mitochondrial genomic integrity both within and among species. In preliminary studies and to establish a reference and standard for the search for single nucleotide polymorphisms (SNPs), we used a combination of experimental and in silico tools for genome analysis to screen selected regions of the chicken (Gallus gallus) mitochondrial genome (mtGenome) for SNPs. A total of 113 SNPs was identified which formed 17 haplotypes. The length of the turkey mtGenome sequence developed was 16,967 bp in length, while that of the budgie was 18,193 bp. Annotation of both sequences revealed a total of 13 genes and 24 RNA (22 tRNA and 2 rRNA). Within the budgie mtGenome sequence, a duplicated control region was observed, and there was an additional nucleotide in the NADH dehydrogenase subunit 3 sequence of both the turkey and budgie. The total number of SNPs within the D-loop and 16S rRNA in each of the four species ranged from zero in the quail to 22 in the budgie. The new mtGenome sequences revealed that the turkey was most closely related to the chicken and quail, and the budgie was closest to kakabo (Strigops habroptilus). Oxidative stress, estimated by biomarkers thiobarbiturate acid reacting substance (TBARS), plasma uric acid (PUA), and glutathione (GSH) and at 10, 30, 55, and 80 wks-of-age within each species, was not consistent. The level of GSH was highest in guineafowl, but lowest in budgie. While PUA, an antioxidant, exhibited a significantly (P<0.05) decrease as birds grew order, TBARS, a lipid peroxidation index, increased with age. In general, oxidant and antioxidant status appeared to vary among species and to be significantly affected by age, unlike mutations in the mtDNA which remained the same in younger and older birds. This primary findings and discoveries of this dissertation research include the large scale SNP discovery in previously described and novel avian mtGenomes including the chicken and turkey, the two main poultry species, and the determination that oxidative stress in birds appears to vary with age but that this does not affect mitochondrial DNA variation. Recent evidence of work in mice appears to support results described in this dissertation that mitochondrial DNA mutations do not increase with age, the central paradigm of the â Free Radical Theory of Agingâ . The dissertation also described resources and data that will be a foundation for the use of birds, especially the budgie, as a model for testing this theory that remains of interest to both agricultural and biomedical sciences.
Ph. D.

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Dreder, Abdouladeem. « Machine learning based approaches for identifying sarcopenia-related genomic biomarkers in ageing males ». Thesis, Northumbria University, 2017. http://nrl.northumbria.ac.uk/36184/.

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Sexual dimorphism of skeletal muscle can occur due to age and many of these age-related changes in skeletal muscle appear to be influenced by gender. In humans, the muscle mass peaks in the second decade while loss of muscle mass (sarcopenia) starts between the third and the fifth decade of life. In system biology, the function of genes still needs to be understood and understanding gene function remains a significant challenge. Several machine learning and computational techniques have been used to understand. However, these previous attempts have not produced enough interpretation of the impact of age on skeletal muscle mass across both gender. Although there are several thousands of genes, very few differentially expressed genes play an active role in understanding the age and gender differences. The core aim of this thesis is to uncover new biomarkers that can contribute towards the prevention of sarcopenia progress in humans according to the gene expression levels of skeletal muscle tissues. The main contributions are the development of machine learning methods based on majority voting of multi-evaluation methods and multi-feature selection methods in order to analyse microarray data and identify subsets of genes related to muscle mass loss in ageing males and females. Previously, statistical methods were used to find important genes related to the impact of age on muscle mass loss. Multi-filter and multi- wrapper based systems are proposed in this thesis to identify different and common sarcopenia-related genes in males and females based on human skeletal muscle. Genes are first sorted using three different evaluation methods (t-test, Entropy and Receiver operating characteristic). Then, important genes are obtained using majority voting based on the principle that combining multiple models can improve the generalization of the system. Experiments were conducted on three different microarray gene expression datasets and results have indicated a significant increase in classification accuracy up to 10% associated with sarcopenia when compared with existing systems.

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Owoka, Temitayo Olajumoke. « Investigating HLXB9 as a biomarker in cancer ». Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/14446.

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A biomarker is a measurable biological characteristic that can be evaluated as an indicator of normal (physiological) or abnormal (pathogenic) processes. In cancer research, there remains a need for the identification of new biomarkers that can be used to close the gaps in the current understanding of cancer development, progression and treatment. HLXB9 is a homeobox gene located at 7q36. It encodes a transcription factor important in embryonic development. Its accurate regulation is significant in the organogenesis of the endodermal germ layer particularly in the development of the pancreas. After development, its expression is downregulated in the majority of adult tissues. Recently, aberrant expression of HLXB9 has been found in certain cancers such as hepatocellular carcinoma, testicular cancer, pancreatic cancer and leukaemia. The location of genes and chromosomes in the nuclei of healthy human cells has been shown to be non-random, therefore understanding the mechanisms that regulate nuclear genome organisation is important in understanding of cancer biology in cases where genes are relocated. The nuclear localisation of genes as a biomarker of tumour development in cancer is a relatively new but promising field in cancer research. Previous research by our group found overexpression of HLXB9 corresponded to an altered positioning of this gene in the nucleus of paediatric leukaemia patients harbouring the translocation t(7;12)(q36;p13). In this project, HLXB9 was evaluated as a biomarker in cancer development. In the first study, a new dual colour probe for the detection of the t(7;12)(q36; p13) was validated by fluorescence in situ hybridisation (FISH) in leukaemia patient samples previously described as harbouring the translocation. The expression of HLXB9 was then analysed by RT-PCR in 48 patients diagnosed with various haematological disorders. 25% of patients analysed expressed HLXB9. Additionally, HLXB9 expression in leukaemia was found in patients with normal copies of chromosome 7 suggesting HLXB9 expression can occur independently of chromosome 7 abnormalities. An attempt was made to evaluate the link between HLXB9 expression and its nuclear localisation in these patients. Four online databases were interrogated to identify cancer types and subtypes that exhibit differential HLXB9 expression. HLXB9 expression was not altered in the majority of cancer cases investigated. However, aberrant HLXB9 expression was found in cancer types not previously reported as showing differential HLXB9 expression such as kidney cancer, lung cancer and endometrial cancer. The identification of aberrant expression of HLXB9 in these cancer types provides a new avenue for research into understanding cancer development and progression in these tumour types. Finally, the expression of HLXB9 was analysed in four breast cancer cell lines by quantitative RT-PCR and immunofluorescence. Additionally, the prognostic significance of HLXB9 expression was evaluated in publicly available breast cancer survival databases (Kaplan Meier plotter and BreastMark). Altogether, the findings emerging from this thesis work show that, although the potential for HLXB9 to be used as biomarker is appealing, further work is required to confirm the value of this biological parameter in the diagnosis, prognosis and progression of cancer.

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Alshammari, Nawal. « Genetic biomarkers in uveal melanoma : an exploration using high-resolution array comparative genomic hybridization ». Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/16803/.

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Uveal melanomas (UM) are aggressive ocular tumours of adults that are typically characterized by chromosomal aberrations such as loss of 1p, 3, 6q, and gain 6p, and 8q. Of these monosomy 3 (M3) and 8q+ are powerful predictors of prognosis. The relationship of changes affecting chromosome 6 is however more ambivalent, having been linked to both good and poor prognosis, and yet both regions have not been well defined, which suggest the presence of one or more oncogenes in 6p and tumour suppressor gene in 6q. Therefore, different chromosome 6 alterations may have a variable impact on the prognosis of UM, and ultimately contain genes that contribute to the development and metastasis of this disease. It is likely that these changes can act as moderators to the tumour outcome. Although UM disseminates haematogenous with high propensity for the liver, and hepatic involvement reported in over 90% of patients, infrequently some patients will however initially present with metastases in sites other than the liver. The aim of this thesis was to address both central issues. Firstly to better understand how genetic biomarkers identify UM that will metastasize, and whether they can be used to further subtype UM. Secondly to see if potential driver genes could be identified that may lead both to an improved understanding of UM metastasis and how to treat it. The approach taken was to use customised high-resolution aCGH. Which, because it was specifically designed for UM, was hoped to identify recurrent focal SCNA that could have been missed by previous studies using lower resolution and unfocussed approaches, such as chromosomal CGH, classical karyotyping, or even BAC arrays. Altogether 137 primary UM were analysed, and as part of a small pilot study possible drivers were further investigated using IHC.

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Prabhulkar, Shradha V. « Development of Micro Immunosensors to Study Genomic and Proteomic Biomarkers Related to Cancer and Alzheimer's Disease ». FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/467.

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A report from the National Institutes of Health defines a disease biomarker as a "characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." Early diagnosis is a crucial factor for incurable disease such as cancer and Alzheimer’s disease (AD). During the last decade researchers have discovered that biochemical changes caused by a disease can be detected considerably earlier as compared to physical manifestations/symptoms. In this dissertation electrochemical detection was utilized as the detection strategy as it offers high sensitivity/specificity, ease of operation, and capability of miniaturization and multiplexed detection. Electrochemical detection of biological analytes is an established field, and has matured at a rapid pace during the last 50 years and adapted itself to advances in micro/nanofabrication procedures. Carbon fiber microelectrodes were utilized as the platform sensor due to their high signal to noise ratio, ease and low-cost of fabrication, biocompatibility, and active carbon surface which allows conjugation with bio-recognition moieties. This dissertation specifically focuses on the detection of 3 extensively validated biomarkers for cancer and AD. Firstly, vascular endothelial growth factor (VEGF) a cancer biomarker was detected using a one-step, reagentless immunosensing strategy. The immunosensing strategy allowed a rapid and sensitive means of VEGF detection with a detection limit of about 38 pg/mL with a linear dynamic range of 0–100 pg/mL. Direct detection of AD-related biomarker amyloid beta (Aβ) was achieved by exploiting its inherent electroactivity. The quantification of the ratio of Aβ1-40/42 (or Aβ ratio) has been established as a reliable test to diagnose AD through human clinical trials. Triple barrel carbon fiber microelectrodes were used to simultaneously detect Aβ1-40 and Aβ1-42 in cerebrospinal fluid from rats within a detection range of 100nM to 1.2μM and 400nM to 1μM respectively. In addition, the release of DNA damage/repair biomarker 8-hydroxydeoxyguanine (8-OHdG) under the influence of reactive oxidative stress from single lung endothelial cell was monitored using an activated carbon fiber microelectrode. The sensor was used to test the influence of nicotine, which is one of the most biologically active chemicals present in cigarette smoke and smokeless tobacco.

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Sohiya, Yotsukura. « Computational Framework for the Dissection of Cancer Genomic Architecture and its Association in Different Biomarkers ». 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/217149.

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Findlay, John Mitchell. « Precision staging and management of Barrett's oesophagus and oesophageal cancer : genomic, imaging and pathological biomarkers ». Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/38037/.

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Barrett’s oesophagus and oesophageal cancer represent two of the most important and challenging oesophageal disease processes globally, combining increasing incidences with high morbidity treatments, often with poor clinical outcomes. A major contributory factor is that disease susceptibility, progression and response to therapy are largely unpredictable, due to inherent biological complexity and variability. At present, just staging groups are used routinely as thresholds for guiding the use of therapies such as ablation, resection, and oncological therapies. However, these represent blunt tools that do not necessarily reflect patients’ experiences, or appropriately select from the range of treatments available. The aim of this thesis was to explore the potential of genomic, imaging, and pathological biomarkers in guiding more tailored and personalised therapy. The first half of this thesis explores the role of genomic markers. The first results chapter describes the identification of new loci and gene pathways associated with susceptibility to Barrett’s oesophagus, dysplasia and oesophageal adenocarcinoma, by further replication and analysis of a genome-wide association study. In addition, all reported genomic markers of these endpoints were identified and criticised by systematic review, and synthesised by meta-analysis. Validation of these was then attempted, and lessons for markers and future research drawn. The second results chapter describes a similar appraisal and synthesis of genomic markers of oesophageal cancer prognosis, response to therapy, and stage. The third describes the first next generation sequencing study performed in oesophageal adenocarcinoma (and indeed any gastrointestinal cancer as far as the author is aware), before and after neoadjuvant chemotherapy. Using whole exome sequencing a new model of genomic tumour response was developed, and the implications for biomarkers explored. The second half of this thesis follows a large cohort of patients with oesophageal cancer, from nearly 1000 undergoing staging, to more than 300 undergoing neoadjuvant chemotherapy, restaging and resection. In the fourth results chapter, the first application of decision theory to cancer staging identified the potential for routine imaging data to personalise and optimise oesophageal cancer staging. In the following chapter, positron emission tomography-computed tomography was found to be more sensitive for identifying disease progression during neoadjuvant chemotherapy than computed tomography alone. Two factors were identified that could stratify risk of progression to incurable disease, including that encountered at surgery. These included 18F-FDG avid nodes, with new concepts of metabolic nodal stage and response developed in conjunction with predictive models. Thereafter, a number of conventional and experimental metrics of metabolic tumour response were compared and refined as predictors of pathological response. Existing metrics of metabolic tumour response were found to be suboptimal, and these new concepts and classifications of metabolic nodal stage and response were found to have independent utility for clinical practice. Again, predictive models were generated. Finally, the prognostic utilities of these markers were explored. Metabolic tumour response was found to be an imperfect surrogate of pathological response. However, metabolic nodal response demonstrated independent utility in identifying patients at high risk of early recurrence and death, both when used before surgery and afterwards. Indeed, a number of analyses demonstrated the additive utility of considering the primary tumour and nodal metastases as separate entities. Finally, prognostic models were generated, and a simple risk score was generated, using the four independent prognostic markers identified to stratify prognosis.

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Alentorn, Agusti. « Caractérisation génomique et génétique des gliomes diffus de bas grade de l’adulte ». Thesis, Paris 11, 2014. http://www.theses.fr/2014PA11T011.

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La caractérisation moléculaire multidimensionnelle des tumeurs et des tumeurs gliales en particulier est une étape importante pour l’identification de biomarqueurs (diagnostique, pronostique, théranostique et/ou de prédisposition), pour l’identification de cibles thérapeutiques et pour une meilleure compréhension de l’oncogénèse moléculaire.Nos travaux ont permis de confirmer et de consolider certaines données de la littérature comme par exemple : (i) la valeur pronostique favorable de la codélétion 1p/19q, (ii) la valeur pronostique favorable de la mutation IDH, (iii) le caractère mutuellement exclusive des mutations TP53 et de la codélétion 1p/19q et (iv) la rareté des altérations génétiques du PDGFRA dans les gliomes de bas grade (GDBG). De manière plus originale, nous avons identifié plusieurs sous-groupes génomiques de GDBG pertinents sur le plan clinico-biologique, notamment au sein des GDBG non 1p/19q codélétés : (i) 19q-délété ; (ii) 11p-délété, (iii) 7-gagné, (iv) 19-gagné et (v) inclassés. La perte du bras chromosomique 19q annule la valeur pronostique favorable de la mutation IDH dans les GDBG non 1p/19q codélétés. Nous avons également identifié des mutations géniques originales dans les GDBG (i.e. mutation TEP1 et RNF40) qui renforcent le rôle des télomères et du remodelage de la chromatine au sein des GDBG.Enfin, nous nous sommes concentrés sur la caractérisation des GDBG 11p-délétés qui sont de phénotype majoritairement astrocytaire et de moins bon pronostic. Ces GDBG surexpriment des gènes des cellules immunitaires (les GIM -Glioma infiltrating microglia-, les macrophages de type 1, les macrophages de type 2) et sont infiltrés par des cellules macrophagiques et microgliales. Ce microenvironnement dérégulé peut constituer une cible thérapeutique au sein des GDBG 11p-délétés. En conclusion, nos travaux participent à la dissection clinico-moléculaire des GDBG et à préciser la biologie d’un sous-type de GDBG caractérisé la perte du bras chromosomique 11p
Multildimensional molecular characterization of tumors and more specifically of gliomas is of pivotal importance to identify: (i) new biomarkers (i.e. diagnostic, prognostic, theranostic or predisposing), (ii) new therapeutic targets and (iii) to improve our understanding of molecular oncogenesis.Our work has confirmed and consolidated previous data published in the literature, for example that: (i) 1p/19q co-deletion is associated with better prognosis, (ii) IDH mutation is associated with better prognosis, (iii) TP53 mutations and 1p/19q codeletion are mutually exclusive and (iv) PDGFRA is rarely altered, at genomic level, in low-grade gliomas (LGG).More originally, we have identified several genomic groups, with clinical and biological relevances, in LGG and more specifically in LGG without 1p/19q co-deletion: (i) 19q-deleted, (ii) 11p-deleted, (iii) 7-gained, (iv) 19-gained and (v) unclassified. Interestingly, 19q deletion abrogates the positive prognostic value of IDH mutation in LGG without 1p/19q codeletion.We have also identified new recurrent somatic gene mutations in LGG (i.e. TEP1 and RNF40 mutations), supporting the critical role of telomeres and chromatin remodelling in LGG.Finally, we have characterized further 11p-deleted LGG that exhibit mostly astrocytic phenotype and poor prognosis. This subgroup includes LGG overexpressing genes of inflammatory/immune cells (GIM -Glioma infiltrating microglia-, M1 macrophages and M2 macrophages) and infiltrated by macrophagic/microglial cells. This peculiar microenvironment detected in 11p-deleted LGG might be used as a therapeutic target. In conclusion, our work participates to characterize clinico-biological portrait of LGG and to describe a singular genomic subgroup of LGG characterized by 11p loss

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Hindocha, Sandip. « Identification of biomarkers and whole genome scanning in Dupuytren's Disease ». Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/identification-of-biomarkers-and-whole-genome-scanning-in-dupuytrens-disease(465cbe01-f3d6-4b1a-9e48-ff3c0c42f5c8).html.

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Background: Dupuytren’s Disease (DD) is a common fibroproliferative disease of unknown origin affecting the hand. The hypotheses of this thesis are; i) DD is a complex polygenic disease and ii) the cells that comprise DD tissue may be derived not only from fascia but also from fat and dermis. On this basis, the overall aims of this thesis were to: ia) estimate the level of penetrance in a UK DD population; ib) present the largest DD family available to date (from Iceland) and attempt linkage analysis following whole genomic scanning; ii) observe stem cell markers as potential biomarkers in DD fascia, fat and skin compared to appropriate controls. Methods: Patients diagnosed with DD (n = 135) were randomly selected from hospitals in the UK. One family was identified in Reykjavik, Iceland. Family pedigrees were compiled for each patient and subsequently analysed to calculate a revised sibling recurrence risk ratio (λs) and estimate the level of penetrance. Members of the Icelandic family from whom DNA was available were genotyped using the Affymetrix 6.0 SNP chip and linkage analysis performed to identify susceptible genetic regions for DD. Biopsies of DD patients (n=9) with digital fixed flexion deformity were taken at operation from the diseased cord, nodule, peri-nodular fat, distant palmar fat and skin. Fluorescence Activated Cell Sorting (FACS), immunohistochemistry and Quantitative Real Time Polymerase Chain reaction (QRT-PCR) were used to identify expression of five mesenchymal (CD’s 13, 29, 44, 90, 166) and two haematopoietic (CD’s 34,117) stem cell markers. Results: ia) The DD status of 1156 relatives of the 135 probands was established. Patients with a family history had a greater severity of disease than those who did not (p<0.05). Despite published studies pointing towards DD being a polygenic disease, DD appears to show a near autosomal pattern of inheritance with variable penetrance (estimated penetrance level: 18%). The revised sibling recurrence risk ratio for the UK, λs=6.2. ib) The Icelandic family had 25 affected members. The pedigree approximated autosomal dominance. Results identified 8 candidate genes with susceptibility loci over 3 chromosomes (GRK4, ADD1, SH3BP2 on chromosome 4; SGCZ on chromosome 8; NAV2, MRGPRX1, SAAL1, MYOD1 on chromosome 11).ii) There was a significantly higher expression of selected stem cell markers in DD tissue over control: CD13 protein expression was increased in all DD tissue compared to controls (p=0.02), while CD44 was significantly over expressed in the cord and nodule (p=0.02). CD34 in the skin was also significantly enhanced (p=0.008). The mean number of positive cells expressing the stem cell markers was significantly greater in DD cord tissue compared to healthy carpal tunnel fascia (p= 0.003).Conclusions: ia) DD appears to show a near autosomal pattern of inheritance with variable penetrance (estimated at 18%), and the sibling recurrence risk ratio was revised. These calculations provide a more up to date evaluation of familial aggregation and more accurate estimates for complex bio-informatic DD models. ib) A large DD pedigree has been identified and a whole genome scan has found 8 potential candidate genes within susceptibility loci on chromosomes 4, 8 and 11. ii) The analysis of stem cell markers in various DD tissue components questions the previously proposed origin of abnormal DD fibroblasts from the fascia alone and suggests that the surrounding palmar fat and skin are also involved in DD pathobiology. Future work may involve functional analysis of these stem cell markers and potential use as biomarkers.

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Prabakaran, Sudhakaran. « A systems-based functional genomics approach to understand schizophrenia and to identify disease biomarkers ». Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613268.

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Appari, Mahesh [Verfasser]. « Genome-wide screening of biomarkers in androgen insensitivity syndrome (AIS) / Mahesh Appari ». Kiel : Universitätsbibliothek Kiel, 2009. http://d-nb.info/1019866764/34.

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Durda, Jon Peter. « The Cardiovascular Epidemiology and Genome-Wide Associations of Biomarkers of Innate and Adaptive Immunity : sCD163 and sIL2RA ». ScholarWorks @ UVM, 2017. http://scholarworks.uvm.edu/graddis/788.

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Cardiovascular disease (CVD) is a major cause of morbidity and mortality in the U.S. and worldwide. Atherosclerosis, the buildup of plaque in the arteries, is a common cause of CVD. For many years, research in atherosclerosis was focused on lipid metabolism and the accumulation of low-density lipoprotein in the arteries. While this research set public health guidelines for lipid management, lipid concentration was not the only factor influencing atherosclerosis and CVD events. Many scientists, as far back as the 1850’s recognized the role of inflammation in the progression of atherosclerotic disease. The continuous low levels of immune activation in the body contribute to atherosclerosis. Research in animal models and epidemiologic studies have shown the involvement of both the innate and the adaptive immune systems in plaque development and to elucidate the roles of monocytes and T cells. In addition to animal studies and epidemiologic research, CVD and atherosclerotic research has extended to genetic analysis in the search for associations with risk factors and outcomes. The first chapter is a review of the literature studying the immune system’s involvement in atherosclerosis. Beginning with an examination of the impact of CVD and atherosclerosis, the basic pathophysiology, and the involvement of the innate and adaptive immune systems through animal models and epidemiology. Some of the significant cohort studies in CVD and genome wide association studies are also discussed. Chapter 2 examines the associations of soluble interleukin 2 receptor alpha (sIL-2Rα) with clinical events in the Cardiovascular Health Study and genetic variants. Interleukin 2 (IL-2) and its receptor regulate both tolerance and immunity, IL-2 induces the proliferation and differentiation of T cells, part of the adaptive immune system. The results showed an association between sIL-2Rα and CVD events. The genome-wide association study found 52 variants to be significantly associated with sIL-2Rα in European Americans. Chapter 3 assesses the involvement of the innate immune system in atherosclerosis through the associations of soluble CD163 (sCD163). CD163 is a marker of macrophage activation, specifically associated with M2 macrophages. In CHS, sCD163 levels were analyzed for associations with cardiovascular events and genetic variants. sCD163 was found to be associated with CVD risk factors and with cardiovascular events. In a genome-wide association study six variants in European Americans and three variants in African Americans were found to be significant. Chapter 4 summarizes the results and discusses some bench to bedside translational science already seen in atherosclerosis treatment and prevention. Continued investigation of markers of T-cell and monocyte differentiation in animal models and cohort studies may lead to opportunities for the prevention of atherosclerosis and/or treatment through an increased understanding of the biology and genetics of the innate and adaptive immune.

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Ståhl, Patrik L. « Methods for Analyzing Genomes ». Doctoral thesis, KTH, Genteknologi, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-12407.

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The human genome reference sequence has given us a two‐dimensional blueprint of our inherited code of life, but we need to employ modern‐day technology to expand our knowledge into a third dimension. Inter‐individual and intra‐individual variation has been shown to be larger than anticipated, and the mode of genetic regulation more complex. Therefore, the methods that were once used to explain our fundamental constitution are now used to decipher our differences. Over the past four years, throughput from DNA‐sequencing platforms has increased a thousand‐fold, bearing evidence of a rapid development in the field of methods used to study DNA and the genomes it constitutes. The work presented in this thesis has been carried out as an integrated part of this technological evolution, contributing to it, and applying the resulting solutions to answer difficult biological questions. Papers I and II describe a novel approach for microarray readout based on immobilization of magnetic particles, applicable to diagnostics. As benchmarked on canine mitochondrial DNA, and human genomic DNA from individuals with cystic fibrosis, it allows for visual interpretation of genotyping results without the use of machines or expensive equipment. Paper III outlines an automated and cost‐efficient method for enrichment and titration of clonally amplified DNA‐libraries on beads. The method uses fluorescent labeling and a flow‐cytometer to separate DNA‐beads from empty ones. At the same time the fraction of either bead type is recorded, and a titration curve can be generated. In paper IV we combined the highly discriminating multiplex genotyping of trinucleotide threading with the digital readout made possible by massively parallel sequencing. From this we were able to characterize the allelic distribution of 88 obesity related SNPs in a population of 462 individuals enrolled at a childhood obesity center. Paper V employs the throughput of present day DNA sequencingas it investigates deep into sun‐exposed skin to find clues on the effects of sunlight during the course of a summer holiday. The tumor suppressor p53 gene was targeted, only to find that despite its well‐documented involvement in the disease progression of cancers, an estimated 35,000 novel sun‐induced persistent p53 mutations are added and phenotypically tolerated in the skin of every individual every year. The last paper, VI, describes a novel approach for finding breast cancer biomarkers. In this translational study we used differential protein expression profiles and sequence capture to select and enrich for 52 candidate genes in DNA extracted from ten tumors. Two of the genes turned out to harbor protein‐altering mutations in multiple individuals.

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Li, Yichao. « Algorithmic Methods for Multi-Omics Biomarker Discovery ». Ohio University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1541609328071533.

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Ansari, Morad. « Analysis of biomarkers for complex human diseases ». Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4505.

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The aims of this study were to analyse known and potential biomarkers of common and genetically complex human disorders and to identify genetic and environmental variation associated with plasma biomarker concentrations. Two groups of protein biomarkers were analysed. First, plasma complement factor H (CFH) was selected as a potential biomarker for age-related macular degeneration (AMD), since common variants in the CFH gene show strong association with this disorder. Secondly, two isoforms of amyloid-β (Aβ40 and Aβ42) were selected as biomarkers for Alzheimer disease (AD) since Aβ deposits are major constituents of the amyloid plaques characteristic of this disorder. Physiological and anthropometric measurements and samples of human and genomic DNA were collected from a population sample of 1,021 individuals from the Croatian island of Vis. Quantitative determination of plasma Aβ40 and Aβ42 concentrations was performed using enzyme-linked immunosorbent assays. Heritabilities and significant covariate effects were estimated for each trait in the Croatian data set. Genome-wide linkage and association analyses were conducted for the biomarker traits. A novel finding was the genome-wide significant association between a CFH and several polymorphisms close to and within the CFH gene. The strongest association was with an intronic SNP within CFH, which explained 28% of the total trait variance (P < 10-50). The association was also replicated in a Dutch sample set. A SNP haplotype was identified which accounted for a higher proportion of the phenotypic variance. Conditional haplotype analysis showed that the effect of this haplotype on plasma CFH concentration was independent of the CFH Y402H variant, and significantly stronger than a deletion of the adjacent CFHR3/CFHR1 which was already known to affect AMD susceptibility. Genetic analysis of 382 AMD cases and 201 controls was consistent with the CFH Y402H variant being the strongest AMD susceptibility locus. Variation in plasma CFH concentration was found to explain up to 1.8% of the variation in susceptibility to AMD with an odds 2.1 (95% C.I. 1.3-3.4, P = 0.003). SNPs that were strongly associated with a CFH concentration also influenced AMD susceptibility (P < 0.05) independently of the CFH Y402H polymorphism. Functional analysis of genomic regions associated with plasma CFH is needed to identify the causal variants. Associations were observed between plasma Aβ40 concentration and several novel candidate loci, spanning regions of approximately 0.2 Mb, on chromosomes 9 and X. Similarly, novel associations with plasma Aβ42 were found in several regions, each spanning 0.2-0.4 Mb, on chromosomes 2, 5, 9, 15 and 20. The proportion of the phenotypic variance in plasma Aβ42 explained by these putative associations ranged between 1.8 and 2.8%. However, none of the associated SNPs was significant after correction for multiple testing, therefore replication is required. Finally, attempts were made to identify and quantitate new protein biomarkers of disease in human plasma using mass spectrometry. Development and optimisation of techniques was initially undertaken to deplete high-abundance plasma proteins and improve signal:noise ratio. This allowed the assessment of downstream proteomic approaches including MALDI-TOF mass spectrometry (MS), capillary electrophoresis (CE) and ion exchange chromatography (IEC), each with the potential for large-scale quantitation of plasma proteins. Although the analysis of single protein analytes, using CE and IEC proved promising, the results highlighted the difficulty associated with MALDI-TOF and protein ionisation techniques in analysing complex mixtures such as plasma.

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Sundaramurthy, Gopinath. « A Probabilistic Approach for Automated Discovery of Biomarkers using Expression Data from Microarray or RNA-Seq Datasets ». University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1459528594.

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Kuntala, Prashant Kumar. « Optimizing Biomarkers From an Ensemble Learning Pipeline ». Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1503592057943043.

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Ramli, Siti Roszilawati Binti Verfasser], Michael [Akademischer Betreuer] [Hust et Michael [Akademischer Betreuer] Steinert. « Whole Genome Analysis and Biomarker Identification of Leptospira spp. / Siti Roszilawati Binti Ramli ; Michael Hust, Michael Steinert ». Braunschweig : Technische Universität Braunschweig, 2019. http://d-nb.info/1183254989/34.

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Nowak, Christoph. « Insulin Resistance : Causes, biomarkers and consequences ». Doctoral thesis, Uppsala universitet, Molekylär epidemiologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-316891.

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The worldwide increasing number of persons affected by largely preventable diseases like diabetes demands better prevention and treatment. Insulin is required for effective utilisation of circulating nutrients. Impaired responsiveness to insulin (insulin resistance, IR) is a hallmark of type 2 diabetes and independently raises the risk of heart attack and stroke. The pathophysiology of IR is incompletely understood. High-throughput measurement of large numbers of circulating biomarkers may provide new insights beyond established risk factors. The aims of this thesis were to (i) use proteomics, metabolomics and genomics methods in large community samples to identify biomarkers of IR; (ii) assess biomarkers for risk prediction and insights into aetiology and consequences of IR; and (iii) use Mendelian randomisation analysis to assess causality. In Study I, analysis of 80 circulating proteins in 70-to-77-year-old Swedes identified cathepsin D as a biomarker for IR and highlighted a tentative causal effect of IR on raised plasma tissue plasminogen activator levels. In Study II, nontargeted fasting plasma metabolomics was used to discover 52 metabolites associated with glycaemic traits in non-diabetic 70-year-old men. Replication in independent samples of several thousand persons provided evidence for a causal effect of IR on reduced plasma oleic acid and palmitoleic acid levels. In Study III, nontargeted metabolomics in plasma samples obtained at three time points during an oral glucose challenge in 70-year-old men identified associations between a physiologic measure of IR and concentration changes in medium-chain acylcarnitines, monounsaturated fatty acids, bile acids and lysophosphatidylethanolamines. Study IV provided evidence in two large longitudinal cohorts for causal effects of type 2 diabetes and impaired insulin secretion on raised coronary artery disease risk. In conclusion, the Studies in this thesis provide new insights into the pathophysiology and adverse health consequences of IR and illustrate the value of combining traditional epidemiologic designs with recent molecular techniques and bioinformatics methods. The results provide limited evidence for the role of circulating proteins and small molecules in IR and require replication in separate studies and validation in experimental designs.

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Murat, Katarzyna. « Bioinformatics analysis of epigenetic variants associated with melanoma ». Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17220.

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The field of cancer genomics is currently being enhanced by the power of Epigenome-wide association studies (EWAS). Over the last couple of years comprehensive sequence data sets have been generated, allowing analysis of genome-wide activity in cohorts of different individuals to be increasingly available. Finding associations between epigenetic variation and phenotype is one of the biggest challenges in biomedical research. Laboratories lacking dedicated resources and programming experience require bioinformatics expertise which can be prohibitively costly and time-consuming. To address this, we have developed a collection of freely available Galaxy tools (Poterlowicz, 2018a), combining analytical methods into a range of convenient analysis pipelines with graphical user-friendly interface.The tool suite includes methods for data preprocessing, quality assessment and differentially methylated region and position discovery. The aim of this project was to make EWAS analysis flexible and accessible to everyone and compatible with routine clinical and biological use. This is exemplified by my work undertaken by integrating DNA methylation profiles of melanoma patients (at baseline and mitogen-activated protein kinase inhibitor MAPKi treatment) to identify novel epigenetic switches responsible for tumour resistance to therapy (Hugo et al., 2015). Configuration files are publicly published on our GitHub repository (Poterlowicz, 2018b) with scripts and dependency settings also available to download and install via Galaxy test toolshed (Poterlowicz, 2018a). Results and experiences using this framework demonstrate the potential for Galaxy to be a bioinformatics solution for multi-omics cancer biomarker discovery tool.

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Fragkogianni, Stamatina. « Genome-wide expression profiling of human circulating monocytes and macrophages identifies diagnostic and prognostic signatures for cancer outcomes ». Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28836.

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Background: Breast and endometrial cancers are the most common gynaecological cancers in women in the UK. Early detection of tumours is crucial for improving patient survival rates. In breast cancer, mammography is the most reliable screening method for asymptomatic patients; however, its sensitivity is limited by breast density. Currently, there are no early screening assays for endometrial cancer. Thus, there is an urgent need to identify clinical biomarkers for improved non-invasive diagnosis of breast and endometrial cancer. Macrophages are abundant in the tumour microenvironment and their density has been associated with poor prognosis in breast cancer and decreased survival in endometrial cancer. Monocytes are precursors of macrophages and recent studies have shown an association with pro-tumoral functions. The aim of this study has been to examine the transcriptional profiles of human circulating monocytes and tumour associated macrophages (TAMs) in order to investigate their biological relevance and potential as biomarkers for cancer detection and prognosis. Methods: RNA-sequencing was performed on purified monocytes (22 healthy individuals, 21 breast cancer, 16 endometrial cancer samples), as well as purified normal macrophages, TAMs from breast tissue (4 breast cancer, 4 healthy breast) and endometrium tissue (5 endometrial cancer, 9 healthy endometrium). Results: A shift in the transcriptional profile of monocytes in cancer compared to controls was observed. Given these cancer-associated alterations circulating monocytes from cancer patients were called “Tumour Educated Monocytes” (TEMo). A TEMo-derived 13-gene signature was extracted that detected cancer, yielding an accuracy of 94%, a positive predictive value (PPV) of 92% and a negative predictive value (NPV) of 97%. External validation confirmed the ability of the signature to accurately identify cancer patients with perfect accuracy. Transcriptome profiling of TAMs revealed a significantly altered gene expression profile when compared to normal tissue resident macrophages. Furthermore, comparison of TAMs between breast and endometrial cancer also revealed differences suggesting that different tumour microenvironments induce different gene expression profiles in TAMs. Functional analysis of significant genes in breast cancer revealed similar biological pathways to those of murine studies suggesting that TAMs in humans and mice may have similar functions. A gene list of transmembrane receptors has been extracted by comparing breast cancer TAMs with publicly available datasets that could serve as markers for their identification. Finally, exploratory analysis identified a subset of 49 genes associated with recurrence-free and overall survival in publicly available datasets. Conclusion: To my knowledge this is the first genome-wide profiling study of human circulating monocytes and TAMs in breast and endometrial cancer. It provides evidence that monocytes and TAMs can alter their expression profile in the presence of cancer and, using bioinformatics tools I was able to identify biomarkers for diagnosis and prognosis of breast and endometrial cancer.

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Sahadevan, Sudeep [Verfasser]. « Application of knowledge discovery and data mining methods in livestokc genomics for hypothesis generation and identification of biomarker candidates influencing meat quality traits in pigs / Sudeep Sahadevan ». Bonn : Universitäts- und Landesbibliothek Bonn, 2014. http://d-nb.info/1077268890/34.

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Nikolayeva, Iryna. « Network and machine learning approaches to dengue omics data ». Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCB032/document.

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Les 20 dernières années ont vu l'émergence de technologies de mesure puissantes, permettant l'analyse omique de diverses maladies. Ils fournissent souvent des moyens non invasifs pour étudier l'étiologie des maladies complexes nouvellement émergentes, telles que l'infection de la dengue, transmise par les moustiques. Ma thèse se concentre sur l'adaptation et l'application d'approches utilisant des réseaux d'interaction de gènes et l'apprentissage automatique pour l'analyse de données génomiques et transcriptomiques. La première partie va au-delà d'une analyse pangénomique précédemment publiée de 4 026 personnes en appliquant une analyse de réseaux d'interaction pour trouver des groupes de gènes qui interagissent dans un réseau d'interactions fonctionnelles et qui, pris ensemble, sont associés à la dengue sévère. Dans cette partie, j'ai d'abord recalculé les valeurs-p d'association des polymorphismes séquencés, puis j'ai travaillé sur le mapping des polymorphismes à des gènes fonctionnellement apparentés, et j'ai enfin exploré différentes bases de données de voies métaboliques et d'interactions génétiques pour trouver des groupes de gènes qui, pris ensemble, sont associés à la dengue sévère. La deuxième partie de ma thèse dévoile une approche théorique pour étudier un biais dans les algorithmes de recherche de réseau actifs. Mon analyse théorique suggère que le meilleur score de sous-réseaux d'une taille donnée devrait être normalisé en fonction de la taille, selon l'hypothèse selon laquelle il s'agit d'un échantillon d'une distribution de valeur extrême, et non un échantillon de la distribution normale, comme c'est généralement le cas dans la littérature. Je propose alors une solution théorique à ce biais. La troisième partie présente un nouvel outil de recherche de sous-réseaux que j'ai co-conçu. Son modèle sous-jacent et l'algorithme évite le biais de taille trouvé dans les méthodes existantes et génère des résultats facilement compréhensibles. Je présente une application aux données transcriptomiques de la dengue. Dans la quatrième et dernière partie, je décris l'identification d'un biomarqueur qui détecte la sévérité de la dengue à l'arrivée à l'hôpital en utilisant une nouvelle approche d'apprentissage automatique. Cette approche combine la régression monotone bidimensionnelle avec la sélection des variables. Le modèle sous-jacent va au-delà des approches linéaires couramment utilisées, tout en permettant de contrôler le nombre de transcrits dans le biomarqueur. Le petit nombre de transcrits accompagné de leur représentation visuelle maximisent la compréhension et l'interprétation du biomarqueur par les professionnels de la biomédecine. Je présente un biomarqueur à 18 gènes qui permet de distinguer, à leur arrivée à l'hôpital, les patients qui vont développer des symptômes de dengue sévères de ceux qui auront une dengue non sévère. Ce biomarqueur a une performance prédictive élevée et robuste. La performance prédictive du biomarqueur a été confirmée sur deux ensembles de données qui ont tous deux utilisé différentes technologies transcriptomiques et différents sous-types de cellules sanguines
The last 20 years have seen the emergence of powerful measurement technologies, enabling omics analysis of diverse diseases. They often provide non-invasive means to study the etiology of newly emerging complex diseases, such as the mosquito-borne infectious dengue disease. My dissertation concentrates on adapting and applying network and machine learning approaches to genomic and transcriptomic data. The first part goes beyond a previously published genome-wide analysis of 4,026 individuals by applying network analysis to find groups of interacting genes in a gene functional interaction network that, taken together, are associated to severe dengue. In this part, I first recalculated association p-values of sequences polymorphisms, then worked on mapping polymorphisms to functionally related genes, and finally explored different pathway and gene interaction databases to find groups of genes together associated to severe dengue. The second part of my dissertation unveils a theoretical approach to study a size bias of active network search algorithms. My theoretical analysis suggests that the best score of subnetworks of a given size should be size-normalized, based on the hypothesis that it is a sample of an extreme value distribution, and not a sample of the normal distribution, as usually assumed in the literature. I then suggest a theoretical solution to this bias. The third part introduces a new subnetwork search tool that I co-designed. Its underlying model and the corresponding efficient algorithm avoid size bias found in existing methods, and generates easily comprehensible results. I present an application to transcriptomic dengue data. In the fourth and last part, I describe the identification of a biomarker that detects dengue severity outcome upon arrival at the hospital using a novel machine learning approach. This approach combines two-dimensional monotonic regression with feature selection. The underlying model goes beyond the commonly used linear approaches, while allowing controlling the number of transcripts in the biomarker. The small number of transcripts along with its visual representation maximize the understanding and the interpretability of the biomarker by biomedical professionals. I present an 18-gene biomarker that allows distinguishing severe dengue patients from non-severe ones upon arrival at the hospital with a unique biomarker of high and robust predictive performance. The predictive performance of the biomarker has been confirmed on two datasets that both used different transcriptomic technologies and different blood cell subtypes

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Arloth, Janine [Verfasser], et John [Akademischer Betreuer] Parsch. « Expression quantitative trait loci as possible biomarkers on depression : candidate gene and genome-wide approaches / Janine Arloth. Betreuer : John Parsch ». München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2014. http://d-nb.info/1075457041/34.

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Chapman, M. H. « Whole genome RNA expression profiling for the identification of novel biomarkers in the diagnosis and prognosis of biliary tract cancer ». Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1310148/.

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Biliary tract cancer (BTC) is difficult to diagnose, in part related to the lack of reliable tumour markers. The aim of this project was to use whole genome RNA expression profiling in order to identify novel biomarkers for diagnosis and prognosis in biliary tract cancer. Chapter 1 summarises clinical aspects of BTC as well as current diagnostic and prognostic tests. Chapter 2 addresses the identification of circulating tumour cells for the diagnosis of BTC. It includes details of a study investigating measurement of circulating cytokeratin 19 fragments (CYFRA 21-1), demonstrating that CYFRA 21-1 is a more specific, but less sensitive diagnostic marker than CA19-9, and predicts a poor prognosis in BTC. Chapter 3 investigates the potential for using RNA isolated from archived formalin fixed, paraffin embedded (FFPE) surgical and explanted liver tissues from patients with primary sclerosing cholangitis (PSC) with and without cholangiocarcinoma, for use in whole genome RNA expression analysis. We demonstrate that, although technically possible, the rarity of samples and RNA degradation that occurs as a result of the tissue processing, are such that further evaluation using these materials is not feasible at this time. Chapter 4 addresses and validates methodology for isolating RNA from samples of biliary brushings taken at the time of endoscopic retrograde cholangiopancreatography (ERCP). We demonstrate that RNA isolated from biliary brushings is of low quantity and degraded, and that this degradation occurs in vivo. However, we demonstrate that such RNA is still useful for downstream applications such as quantitative real time PCR and is therefore suitable for whole genome RNA expression analysis using microarray technology. Chapter 5 describes the methods and results obtained from using whole genome RNA expression analysis using microarray of RNA isolated from ERCP biliary brushings. The results are presented as a shortlist of candidate genes requiring further validation. Chapter 6 provides results of qPCR studies performed in order to validate the gene expression profile identified by microarray. A selection of candidate genes are investigated using TaqMan Array and SYBR Green qPCR and demonstrate a high correlation with the pattern of expression shown by microarray. Chapter 7 investigates whether a selection of the genes identified in malignant biliary brushings are similarly upregulated in fresh frozen surgical resection material from patients with benign and malignant biliary diseases. In addition, we provide evidence for gene translation and upregulation at the protein level by immunohistochemistry for a selection of the protein products. Chapter 8 discusses the main conclusions drawn from the work as well as potential future studies.

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Guillemette, Shawna S. « Investigating Tumor Suppressors in the DNA Damage Response : Caretakers of the Genome and Biomarkers to Predict Therapeutic Response : A Dissertation ». eScholarship@UMMS, 2014. https://escholarship.umassmed.edu/gsbs_diss/712.

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Our genome is constantly challenged by sources that cause DNA damage. To repair DNA damage and maintain genomic stability eukaryotes have evolved a complex network of pathways termed the DNA damage response (DDR). The DDR consists of signal transduction pathways that sense DNA damage and mediate tightly coordinated reactions to halt the cell cycle and repair DNA with a collection of different enzymes. In this manner, the DDR protects the genome by preventing the accumulation of mutations and DNA aberrations that promote cellular transformation and cancer development. Loss of function mutations in DDR genes and genomic instability occur frequently in many tumor types and underlie numerous cancer-prone hereditary syndromes such as Fanconi Anemia (FA). My thesis research applies candidate-based and unbiased experimental approaches to investigate the role of several tumor suppressor genes (TSGs) in the DDR. My dissertation will first describe a novel function for the breast and ovarian cancer tumor suppressor and FA-associated gene FANCJ in the DDR to ultraviolet (UV) irradiation. In response to UV irradiation FANCJ supports checkpoint induction, the arrest of DNA synthesis, and suppresses UV induced point mutations. Suggesting that FANCJ could suppress UV induced cancers, in sequenced melanomas from multiple databases I found somatic mutations in FANCJ previously associated with breast/ovarian cancer and FA syndrome. The second part of my dissertation will describe an RNA interference screen to identify genes modulating cellular sensitivity to the chemotherapeutic drug cisplatin. The hereditary breast/ovarian cancer tumor suppressor BRCA2 is essential for DNA repair, thus BRCA2 mutant ovarian cancer cells are initially sensitive to cisplatin chemotherapy that induces DNA damage. However, drug resistance develops and remains a major problem in the clinic. My screen identified the chromatin remodeling factor CHD4 as a potent modulator of cisplatin sensitivity and predictor of response to chemotherapy in BRCA2 mutant cancers. Taken together, my investigations highlight the important contribution of the DDR and the role they play in tumorigenesis and predicting therapeutic response.

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Guillemette, Shawna S. « Investigating Tumor Suppressors in the DNA Damage Response : Caretakers of the Genome and Biomarkers to Predict Therapeutic Response : A Dissertation ». eScholarship@UMMS, 2004. http://escholarship.umassmed.edu/gsbs_diss/712.

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Our genome is constantly challenged by sources that cause DNA damage. To repair DNA damage and maintain genomic stability eukaryotes have evolved a complex network of pathways termed the DNA damage response (DDR). The DDR consists of signal transduction pathways that sense DNA damage and mediate tightly coordinated reactions to halt the cell cycle and repair DNA with a collection of different enzymes. In this manner, the DDR protects the genome by preventing the accumulation of mutations and DNA aberrations that promote cellular transformation and cancer development. Loss of function mutations in DDR genes and genomic instability occur frequently in many tumor types and underlie numerous cancer-prone hereditary syndromes such as Fanconi Anemia (FA). My thesis research applies candidate-based and unbiased experimental approaches to investigate the role of several tumor suppressor genes (TSGs) in the DDR. My dissertation will first describe a novel function for the breast and ovarian cancer tumor suppressor and FA-associated gene FANCJ in the DDR to ultraviolet (UV) irradiation. In response to UV irradiation FANCJ supports checkpoint induction, the arrest of DNA synthesis, and suppresses UV induced point mutations. Suggesting that FANCJ could suppress UV induced cancers, in sequenced melanomas from multiple databases I found somatic mutations in FANCJ previously associated with breast/ovarian cancer and FA syndrome. The second part of my dissertation will describe an RNA interference screen to identify genes modulating cellular sensitivity to the chemotherapeutic drug cisplatin. The hereditary breast/ovarian cancer tumor suppressor BRCA2 is essential for DNA repair, thus BRCA2 mutant ovarian cancer cells are initially sensitive to cisplatin chemotherapy that induces DNA damage. However, drug resistance develops and remains a major problem in the clinic. My screen identified the chromatin remodeling factor CHD4 as a potent modulator of cisplatin sensitivity and predictor of response to chemotherapy in BRCA2 mutant cancers. Taken together, my investigations highlight the important contribution of the DDR and the role they play in tumorigenesis and predicting therapeutic response.

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Pettersson, Fredrik. « A multivariate approach to computational molecular biology ». Doctoral thesis, Umeå : Univ, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-609.

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Maroilley, Tatiana. « Génétique et Génomique de la capacité immunitaire chez le porc : approches eQTL et étude de biomarqueurs sanguins ». Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLV097/document.

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Une meilleure compréhension des mécanismes de résistance aux agents pathogènes couplée à une caractérisation de la capacité immune devient un axe de recherche prioritaire en élevage. L’objectif global de la thèse est d’exploiter des informations de phénotypage, de génétique et de génomique pour étudier l’architecture génétique de la capacité immune chez le porc et contribuer à l’identification de marqueurs génétiques et de biomarqueurs sanguins prédictifs de variations de niveaux de paramètres immuns. Le projet s’articule autour de trois axes complémentaires et les résultats obtenus sont basés sur l’exploitation des jeux de données issus des projets IMMOPIG et SUS_FLORA financés par l’ANR, pour lesquels des cohortes de 450 et 560 porcelets ont été prélevés à 60 jours d’âge, trois semaines après une vaccination contre Mycoplasma hyopneumoniae.Nous avons analysé le déterminisme génétique de l’expression des gènes dans le sang par une analyse eGWAS (génotypage 60K SNP et transcriptome du sang pour 242 animaux) validée pour partie par une étude de la régulation spécifique d’allèles (ASE) des transcrits (RNA-Seq sur 38 animaux). Les résultats d’eGWAS mettent en évidence de multiples associations locales (n=2839) et à distance (n=1752) entre des polymorphes SNP et des variations de transcription, réparties sur l’ensemble des chromosomes. Les analyses ASE confirment l’importance du contrôle génétique en cis, avec une régulation allélique trouvée pour 763 gènes. Les fonctions biologiques associées sont notamment reliées au processing des ARN et à l’immunité. La région du complexe majeur d’histocompatibilité a été trouvée particulièrement riche en eQTL et ASE. L’ensemble de ces données a permis d’établir, pour le porc, une première cartographie des eQTL et gènes soumis à ASE dans le sang.Nous avons étudié les co-variations entre des paramètres immunitaires et le transcriptome du sang pour 243 individus. Les paramètres immunitaires incluent la numération formule sanguine, la caractérisation de sous-populations cellulaires par cytomètre de flux, des dosages sériques (protéine C réactive, haptoglobine, anticorps spécifiques anti Mycoplasma hyopneumoniae), des dosages de réponse suite à des stimulations in vitro du sang total (phagocytose, cytokines IL1b, IL2, IL6, IL8, IL10, TNFa, INFg). Nous avons confirmé l’héritabilité de nombreux paramètres immuns et identifié des covariations avec des profils géniques, offrant des hypothèses sur des biomarqueurs candidats.Nous avons également conduit une analyse fonctionnelle sur quatre animaux de 70 jours d’âge pour caractériser et comparer les profils de transcrits du sang et de trois tissus lymphoïdes associés au tube digestif (ganglion mésentérique, plaques de Peyer jéjunales et iléales). Les données RNA-Seq ont mis en évidence des différentiels d’expression entre les tissus, ce nombre étant plus limité entre les deux types de plaques de Peyer. De manière tout à fait intéressante, parmi les fonctions biologiques enrichies par les gènes différentiellement exprimés entre les deux plaques de Peyer, sont identifiées les voies de différenciation lymphocytaires Th1 et Th2, en cohérence avec une surabondance de lymphocytes B dans les plaques de Peyer iléales.L’ensemble de ces résultats apporte des informations nouvelles pour avancer dans la compréhension du déterminisme génétique des variations de paramètres immunitaires chez le porc, la recherche de polymorphismes causaux de ces variations et l’identification de biomarqueurs sanguins pertinents pour phénotyper la compétence immunitaire
A better understanding of the mechanisms for resistance to pathogens along with the characterization of the immune capacity has become a priority for research in breeding. The overall objective of this PhD project was to use phenotyping, genetic and genomic information to study the genetic architecture of the immune capacity in the pig and to contribute to the identification of genetic markers and blood biomarkers that predict variations of immune parameter levels. The study was focused on three complementary axes and the results obtained were based on the use of data collected as part of the IMMOPIG and SUS_FLORA projects financed by the ANR, for which 450 and 560 piglet cohorts were sampled at 60 days of age, three weeks after vaccination against Mycoplasma hyopneumoniae.We analyzed the genetic determinism of gene expression in the blood using an eGWAS (60K SNP genotyping and blood transcriptome for 242 animals) confirmed in part by an allele specific expression (ASE) of transcripts (RNA-Seq on 38 animals). The eGWAS results showed multiple local (n=2839) and distant associations between the SNP polymorphisms and transcription variations, spread over all the chromosomes. The ASE analyses confirmed the cis genetic control of gene expression, with allele regulation being found for 763 genes. The biological functions associated were notably associated with RNA processing and immunity. The region of the major histocompatibility complex was found particularly rich in eQTL signals and genes with ASE in the blood.We studied the co-variations between immune parameters and blood transcriptomes for 243 individuals. The immune parameters included the blood count, cell subpopulation characterization by flow cytometry, serum assays (reactive C protein, haptoglobin, antibodies specific for Mycoplasma hyopneumoniae), immune response after in vitro stimulation of peripheral blood (phagocytosis, IL1b, IL2, IL6, IL8, IL10, TNFa, INFg cytokines). We confirmed the heritability of numerous immune parameters and identified covariations with gene profiles, providing hypotheses on biomarker candidates.We also led a functional analysis on four animals at 70 days-of-age in order to characterize and compare the transcriptome profiles of peripheral blood and three gut-associated lymphoid tissues (mesenteric lymph nodes, jejunal and ileal Payer’s patches). The RNA-Seq data showed differential expression between tissues; this number was more limited between the two types of Peyer’s patches. Interestingly, among the biological functions enriched by the differentially expressed genes between the Peyer’s patches, we identified the Th1 and Th2 lymphocyte differentiation pathways, which was in agreement with an over-abundance of B lymphocytes in the ileal Peyer’s patches.Together these results provide new information on the understanding of the genetic determinism of immune parameter variations in the pig, the search for causal polymorphisms of these variations and the identification of relevant blood biomarkers for phenotyping immune competence

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Saman, Sadik [Verfasser], Jürgen [Akademischer Betreuer] Brockmöller et Tim [Akademischer Betreuer] Beissbarth. « Identifizierung genetischer Biomarker für die Wirksamkeit von Oxaliplatin:Kandidatengen-bezogene und Genom-weite Analysen / Sadik Saman. Gutachter : Jürgen Brockmöller ; Tim Beissbarth. Betreuer : Jürgen Brockmöller ». Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2014. http://d-nb.info/1063776198/34.

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Gay-Bellile, Mathilde. « Etude de l'instabilité génomique et du statut des télomères dans le cancer du sein ». Thesis, Université Clermont Auvergne‎ (2017-2020), 2017. http://www.theses.fr/2017CLFAS001.

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Dans le cancer du sein, la recherche de nouveaux biomarqueurs, permettant de prédire la réponse thérapeutique et de déterminer le pronostic d’une patiente, est importante pour adapter au mieux les traitements mais aussi pour améliorer la compréhension des phénomènes physiopathologiques. Nous nous sommes particulièrement intéressés aux cancers du sein traités par chimiothérapie néoadjuvante. Nous avons étudié, dans des biopsies tumorales réalisées avant traitement et dans des résidus tumoraux, à la fois les paramètres télomériques et la réparation des lésions d’ADN puisque ces 2 mécanismes, lorsqu’ils sont dysfonctionnels, sont à l’origine d’une forte instabilité génomique. Nous avons corrélés ces paramètres à la réponse à la chimiothérapie néoadjuvante et à la survie des patientes. Dans un 1er temps, nous avons montré que des télomères courts, une surexpression de la télomérase (TERT) et une sous-expression d’une protéine impliquée dans différents mécanismes de réparation de l’ADN, ERCC1, sont des marqueurs de mauvais pronostic. La dysfonction simultanée des télomères et des mécanismes de réparation de l’ADN peut contribuer de façon synergique à la progression tumorale et à la résistance thérapeutique. Nous avons ensuite étudié une population de tumeurs du sein triple négatives. Nous avons montré que des télomères courts sont associés aux tumeurs les plus agressives et les plus résistantes. De plus, une résistance thérapeutique est retrouvée associée à une instabilité génomique plus importante. Nous avons enfin analysé les altérations génomiques caractéristiques permettant d’identifier le statut BRCA1-like. Le profil BRCA1-like est corrélé à une résistance thérapeutique et à une forte instabilité génomique.Enfin, nous avons réalisé une étude plus fondamentale visant à identifier les mécanismes à l’origine de la réactivation de la télomérase dans le cancer du sein. Nous avons démontré que la surexpression de TERT, dans le cancer du sein, n’est pas liée à la présence de mutations somatiques activatrices mais plutôt à celle de gain du locus TERT. Ces gains sont associés à une résistance thérapeutique et un risque de rechute plus important. Enfin, la présence de gain de TERT combinée à la surexpression de MYC, permet de définir un sous groupe de très mauvais pronostique et pourrait être utilisé pour évaluer le risque de récidives. Les paramètres télomériques et l’instabilité génomique semblent donc être des biomarqueurs prédictifs de la réponse à la chimiothérapie néoadjuvante dans le cancer du sein triple négatif. Ces paramètres ont également une forte valeur pronostique dans le cancer du sein en général et pourraient être utilisés cliniquement comme biomarqueurs utiles au choix des traitements
In breast cancer, discovering new biomarkers, that can predict therapeutic response and prognosis, is important to find the best therapeutic options and improve our understanding of physiopathology. Our particular interest is in breast cancer treated by neoadjuvant chemotherapy (NCT). In pre-NCT biopsies and post-NCT tumors, we studied both telomeric parameters and DNA damage repair (DDR), because when these are dysfunctional, both result in high genomic instability. We correlated these parameters to neoadjuvant chemotherapy response and patient outcomes. First, we demonstrated that short telomeres, high telomerase (TERT) expression and low expression of ERCC1 (a protein involved in a number of DNA repair mechanisms) are markers of poor prognosis. Telomere and DDR dysfunction can contribute synergistically to tumor progression and chemoresistance. We then studied a triple negative breast cancer population. We demonstrated that short telomeres were associated with tumor aggressiveness and chemoresistance. Chemoresistance was also associated with high genomic instability. We analyzed genomic alterations specific to BRCA1-like status and demonstrated that BRCA1-like profile correlated with chemoresistance and high genomic instability. Finally, we performed a comprehensive study of telomerase reactivation in breast cancer. We demonstrated that high TERT expression in breast cancer is not associated with somatic enhancer mutations but more probably to TERT locus gains. These gains were correlated to chemoresistance and increased risk of relapse. TERT gain, combined with high MYC expression, was able to isolate a subgroup with a very poor prognosis, and this could be used to evaluate risk of relapse. Telomeric parameters and genomic instability seem to be predictive biomarkers for neoadjuvant chemotherapy response in triple negative breast cancer. These parameters also have strong prognostic value in breast cancer and could be used clinically as biomarkers for tailoring treatment

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Ustunkar, Gurkan. « An Integrative Approach To Structured Snp Prioritization And Representative Snp Selection For Genome-wide Association Studies ». Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612871/index.pdf.

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Single Nucleotide Polymorphisms (SNPs) are the most frequent genomic variations and the main basis for genetic differences among individuals and many diseases. As genotyping millions of SNPs at once is now possible with the microarrays and advanced sequencing technologies, SNPs are becoming more popular as genomic biomarkers. Like other high-throughput research techniques, genome wide association studies (GWAS) of SNPs usually hit a bottleneck after statistical analysis of significantly associated SNPs, as there is no standardized approach to prioritize SNPs or to select representative SNPs that show association with the conditions under study. In this study, a java based integrated system that makes use of major public databases to prioritize SNPs according to their biological relevance and statistical significance has been constructed. The Analytic Hierarchy Process, has been utilized for objective prioritization of SNPs and a new emerging methodology for second-wave analysis of genes and pathways related to disease associated SNPs based on a combined p-value approach is applied into the prioritization scheme. Using the subset of SNPs that is most representative of all SNPs associated with the diseases reduces the required computational power for analysis and decreases cost of following association and biomarker discovery studies. In addition to the proposed prioritization system, we have developed a novel feature selection method based on Simulated Annealing (SA) for representative SNP selection. The validity and accuracy of developed model has been tested on real life case control data set and produced biologically meaningful results. The integrated desktop application developed in our study will facilitate reliable identification of SNPs that are involved in the etiology of complex diseases, ultimately supporting timely identification of genomic disease biomarkers, and development of personalized medicine approaches and targeted drug discoveries.

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D'AMICO, FRANCA. « Studio dell'espressione dei geni del metabolismo degli androgeni e caratterizzazione del profilo citogenetico per la ricerca di biomarcatori genomici in linee primarie di carcinoma della prostata ». Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2008. http://hdl.handle.net/2108/680.

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Obiettivi principali di questa tesi di dottorato sono lo studio dell’espressione genica e del profilo citogenetico, basato sulla tecnologia dei microarrays, per l’identificazione di potenziali biomarcatori genomici quali geni candidati per la comprensione della patogenesi molecolare del tumore della prostata, in linee primarie ottenute da campioni di carcinoma prostatico dopo rimozione chirurgica e lo studio degli eventuali geni differenzialmente espressi nelle colture primarie in linfociti estratti da sangue periferico di pazienti affetti da carcinoma prostatico e non trattati farmacologicamente, allo scopo di verificare se l’espressione differenziale è riscontrata anche nel sangue. E’ stato costruito un array a bassa densità costituito da 205 geni (“androchip”) selezionati sulla base del loro provato o potenziale ruolo nella cancerogenesi del carcinoma prostatico relazionati al pathway degli androgeni. E’ stata osservata un’alterata espressione dei geni coinvolti nella progressione verso l’androgeno indipendenza (BCL2, CALR e VIM) e nel contempo una diminuzione del gene PKC-beta, marcatore delle fasi iniziali della progressione del tumore. Inoltre è stato riscontrato un elevato aumento dell’espressione del gene NQO1. Questo gene è in grado di trasformare un farmaco anti tumorale, il β-lapacone, nella sua forma attiva e pertanto potrebbe essere un gene chiave nelle scelte terapeutiche da parte dei clinici. D’altro canto, dopo gli esperimenti di a-CGH non si è riscontrata alcuna anomalia a carico del corredo genomico delle linee primarie analizzate ad eccezione della perdita del cromosoma Y riscontrata in una linea primaria su dieci analizzate, prima con la piattaforma a BAC e confermata con la piattaforma Agilent a oligonucleotidi. Per quanto riguarda lo studio dei biomarcatori nel sangue di pazienti affetti da carcinoma prostatico, sono stati analizzati i geni NQO1, PKC-beta, BCL2 e ERBB2. Nel complesso i nostri dati hanno mostrato una effettiva variazione dell’espressione dei quattro geni esaminati. in particolare abbiamo riscontrato, in alcuni pazienti, una diminuzione dell’espressione di PCK-beta, gene ipo-espresso nelle primissime fasi della malattia e un aumento di espressione del gene ERBB2, gene correlato ad androgeno indipendenza e metastasi. In conclusione, questo lavoro ha portato all’individuazione di marcatori di prognosi sfavorevole in linee primarie ottenute da pazienti con carcinoma prostatico e all’identificazione e alla conferma del potenziale ruolo del gene ERBB2 come marcatore di prognosi nel sangue.
The aims of this study where to investigate expression profiles of genes related to androgen signaling and to screen genomic alterations in primary epithelial cultures derived from tissue explanted from patients undergoing radical prostatectomy to better understanding the rule of androgen pathway and of genomic copy number changes in the development and progression of prostate cancer. Moreover, we investigated expression profiles of selected genes (NQO1, PKC-beta, BCL2 e ERBB2) in circulating blood cells of prostate cancer patients to discover new biomarkers for diagnostic purposes. To carry out these aims we developed a low density home made oligonucleotide-array composed of 205 genes selected on the basis of their proved or potential role in prostate cancerogenesis related to androgen signalling (“AndroChip”), and we carried out array-based comparative genomic hibridization (aCGH) on primary epithelial cultures derived from tissue explanted from patients undergoing radical prostatectomy. After microarray experiments, considering only genes resulted significant in all primary cancer cell lines and whose differential expression had a threeshold>±1,5, we identified a total of 15 genes. In summary, we observed differential expression of genes (BCL2, CALR e VIM) able to confer androgen- independent growth and down regulation of PKC-beta gene that may be down-regulated at an early stage in the pathogenesis of prostate cancer. Moreover, we found over expression of NQO1 gene. High levels of NQO1 gene expression have been observed in many cancers as compared to normal tissues of the same origin. NQO1 bioactivates an anti-cancer agent, Beta-lapachone and so this gene could be exploitable target for the treatment of cancer cells that overexpress this enzyme. After aCGH experiment, we did not reveal genomic imbalances in 9 of the 10 samples examined. In one semple we detected the loss of the Y chromosome. These results demonstrate that no specific genomic biomarkers are detectable for early stage prostatic cancer. Moreover, we studied NQO1, PKC-beta, BCL2 e ERBB2 expression by RT-PCR real-time in peripheral blood mononuclear cell fraction samples of 7 patients with prostate cancer. All thogether, our results showed an differential expression profiles of examinated genes. In particular, we found down regulation of PCK-beta and up regulation of ERBB2. In conclusion, this study allowed to identify prognosis biomarkers in primary cell lines and confirmed that ERBB2 gene can be use as prognosis marker in blood.

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UDALI, SILVIA. « Genome-wide DNA methylation profiles by high-throughput techniques in alcohol-related hepatocellular carcinoma : identification of epigenetic signatures in liver tissue and peripheral blood cells DNA as potentially useful biomarkers of disease ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/41782.

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DNA methylation is the major epigenetic feature of eukaryotic cell DNA and consists in the covalent binding of a methyl group to the 5’ carbon of a cytosine in a CpG dinucleotide sequence and acts regulating gene expression. Methyl-transfer reactions occur within one-carbon metabolism pathway that takes place principally in the liver: hepatic tissue that is, therefore, to be considered among the most interesting target tissues for DNA methylation analysis. Moreover alcohol, a major risk factor for hepatic cancer, is known to disturb one-carbon metabolism but the mechanisms underlying the alcohol-related liver carcinogenesis are still incompletely understood. We, therefore, designed this study to investigate DNA methylation profiles in alcohol-related hepatocellular carcinoma (HCC) by high-throughput techniques for genome-wide analysis. Main scope of the present project was to define a possible role for DNA methylation in the development of non-viral alcohol-related HCC in DNA obtained either from liver tissue and peripheral blood mononuclear cells (PBMCs) with the final goal of identifying potentially useful epigenetic biomarkers for HCC from an easily accessible DNA source, namely PBMCs. The methylation status and the transcriptional levels of all the annotated genes were assessed on liver HCC tissue compared to homologous non-neoplastic tissue using a genome-wide, array-based approach in eight patients undergoing curative surgery. The merging of DNA methylation and gene expression data allowed identifying hypermethylated and transcriptional repressed genes among which six genes belonging to retinol metabolism (ADH1A, ADH1B, ADH6, CYP3A43, CYP4A22 and RDH16). Among other hypermethylated-repressed genes, was detected a key gene of one-carbon metabolism, SHMT1, ESR1, a transcription factor with an hormone-binding domain involved in cell cycle regulation, and hepcidin, a liver peptide hormone involved in iron homeostasis were also identified as epigenetically regulated through DNA methylation inducing transcriptional repression. Interestingly, the gene expression analysis on RNA extracted from buffy coat of HCC patients, alcoholic patients without liver cancer and healthy subjects revealed that transcriptional repression of RDH16 was significantly associated with hepatic cancer. Moreover, the down-regulation of RDH16, SHMT1 and ESR1 was associated to chronic alcohol intake compared to controls. These findings suggest that expression profiles of specific genes obtained from PBMCs may be useful biomarkers for HCC.

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Hassan, Aamir Ul. « Integration of Genome Scale Data for Identifying New Biomarkers in Colon Cancer : Integrated Analysis of Transcriptomics and Epigenomics Data from High Throughput Technologies in Order to Identifying New Biomarkers Genes for Personalised Targeted Therapies for Patients Suffering from Colon Cancer ». Thesis, University of Bradford, 2017. http://hdl.handle.net/10454/17419.

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Colorectal cancer is the third most common cancer and the leading cause of cancer deaths in Western industrialised countries. Despite recent advances in the screening, diagnosis, and treatment of colorectal cancer, an estimated 608,000 people die every year due to colon cancer. Our current knowledge of colorectal carcinogenesis indicates a multifactorial and multi-step process that involves various genetic alterations and several biological pathways. The identification of molecular markers with early diagnostic and precise clinical outcome in colon cancer is a challenging task because of tumour heterogeneity. This Ph.D.-thesis presents the molecular and cellular mechanisms leading to colorectal cancer. A systematical review of the literature is conducted on Microarray Gene expression profiling, gene ontology enrichment analysis, microRNA and system Biology and various bioinformatics tools. We aimed this study to stratify a colon tumour into molecular distinct subtypes, identification of novel diagnostic targets and prediction of reliable prognostic signatures for clinical practice using microarray expression datasets. We performed an integrated analysis of gene expression data based on genetic, epigenetic and extensive clinical information using unsupervised learning, correlation and functional network analysis. As results, we identified 267-gene and 124-gene signatures that can distinguish normal, primary and metastatic tissues, and also involved in important regulatory functions such as immune-response, lipid metabolism and peroxisome proliferator-activated receptors (PPARs) signalling pathways. For the first time, we also identify miRNAs that can differentiate between primary colon from metastatic and a prognostic signature of grade and stage levels, which can be a major contributor to complex transcriptional phenotypes in a colon tumour.

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Jeschke, Jana [Verfasser], et Andreas [Akademischer Betreuer] Winterpacht. « Utilization of Genome-wide DNA Methylation Changes in Breast Cancer for Identification of Biomarkers for Prognosis and Mechanisms of Tumorigenesis / Jana Jeschke. Betreuer : Andreas Winterpacht ». Erlangen : Universitätsbibliothek der Universität Erlangen-Nürnberg, 2013. http://d-nb.info/1033029882/34.

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Martínez, Enguita David. « Identification of personalized multi-omic disease modules in asthma ». Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15987.

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Asthma is a respiratory syndrome associated with airflow limitation, bronchial hyperresponsiveness and inflammation of the airways in the lungs. Despite the ongoing research efforts, the outstanding heterogeneity displayed by the multiple forms in which this condition presents often hampers the attempts to determine and classify the phenotypic and endotypic biological structures at play, even when considering a limited assembly of asthmatic subjects. To increase our understanding of the molecular mechanisms and functional pathways that govern asthma from a systems medicine perspective, a computational workflow focused on the identification of personalized transcriptomic modules from the U-BIOPRED study cohorts, by the use of the novel MODifieR integrated R package, was designed and applied. A feature selection of candidate asthma biomarkers was implemented, accompanied by the detection of differentially expressed genes across sample categories, the production of patient-specific gene modules and the subsequent construction of a set of core disease modules of asthma, which were validated with genomic data and analyzed for pathway and disease enrichment. The results indicate that the approach utilized is able to reveal the presence of components and signaling routes known to be crucially involved in asthma pathogenesis, while simultaneously uncovering candidate genes closely linked to the latter. The present project establishes a valuable pipeline for the module-driven study of asthma and other related conditions, which can provide new potential targets for therapeutic intervention and contribute to the development of individualized treatment strategies.

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Fung, P. L. « The GENVABO study : genetic variants as biomarkers of jaw osteonecrosis associated with bisphosphonates : a large, multicentre genome-wide association study and detailed analyses of clinical phenotype ». Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1472795/.

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Osteonecrosis of the jaw (ONJ) is a potentially severe adverse effect of bisphosphonates. It can cause persistent pain and infection to the jawbones, and is currently considered incurable. ONJ occurs in a subset of individuals exposed to bisphosphonates (≤7%). Although a number of clinical risk factors, such as dentoalveolar surgery and dental infection, can increase the risk of ONJ development, there remains a number of patients who do not present with these clinical risk factors. Therefore, a genetic predisposition has been proposed. Genome-wide association studies (GWAS), widely performed in pharmacogenomics and successful in other drug side effects, have also been attempted in bisphosphonates-associated ONJ. However, possibly due to small cohort sizes (≤30 cases), these studies failed to detect any significant genetic risk factors. The aim of this thesis is to present the results of a large, multicentre GWAS, coupled with detailed analyses of clinical phenotype. 393 ONJ cases were recruited from 23 clinical centres worldwide. All cases were thoroughly phenotyped and adjudicated by specialist multidisciplinary teams. Random effects logistic regressions (Stata v12.1) were used for clinical risk factor analyses. All samples were genotyped using Illumina® Human1M Omni Express Beadchip (1,072,820 probes) and were compared with 2,554 genetically-matched population controls from publicly available sources. Genotype statistical analysis was performed in PLINK. Risk factors including advanced age, longer bisphosphonates duration, other cancers and use of steroids were found statistically significant (p < 0.05). With extreme phenotyping, i.e. non-surgery triggered ONJ cases versus the population controls, for the first time, a genome-wide significant single nucleotide polymorphism was identified: rs12440268 at TJP1 gene (p=1.21E-8). Individuals positive for this marker were nearly three times more likely to develop ONJ than those negative for it (OR=2.66). TJP1 encodes protein at the tight junctions, which maintain epithelial integrity. Its polymorphism may contribute to ONJ pathogenesis through impaired mucosal healing.

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