Academic literature on the topic 'Predictive DNA typing'
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Journal articles on the topic "Predictive DNA typing"
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Li, Xin, Xuan Zhang, Xiangyu Lin, Liting Cai, Yan Wang, and Zhiqiang Chang. "Classification and Prognosis Analysis of Pancreatic Cancer Based on DNA Methylation Profile and Clinical Information." Genes 13, no. 10 (October 21, 2022): 1913. http://dx.doi.org/10.3390/genes13101913.
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Pancreatic adenocarcinoma (PAAD) has a poor prognosis with high individual variation in the treatment response among patients; however, there is no standard molecular typing method for PAAD prognosis in clinical practice. We analyzed DNA methylation data from The Cancer Genome Atlas database, which identified 1235 differentially methylated DNA genes between PAAD and adjacent tissue samples. Among these, 78 methylation markers independently affecting PAAD prognosis were identified after adjusting for significant clinical factors. Based on these genes, two subtypes of PAAD were identified through consistent clustering. Fourteen specifically methylated genes were further identified to be associated with survival. Further analyses of the transcriptome data identified 301 differentially expressed cancer driver genes between the two PAAD subtypes and the degree of immune cell infiltration differed significantly between the subtypes. The 14 specific genes characterizing the unique methylation patterns of the subtypes were used to construct a Bayesian network-based prognostic prediction model for typing that showed good predictive value (area under the curve value of 0.937). This study provides new insight into the heterogeneity of pancreatic tumors from an epigenetic perspective, offering new strategies and targets for personalized treatment plan evaluation and precision medicine for patients with PAAD.
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Titov, Sergei E., Evgeniya S. Kozorezova, Pavel S. Demenkov, Yulia A. Veryaskina, Irina V. Kuznetsova, Sergey L. Vorobyev, Roman A. Chernikov, Ilya V. Sleptsov, Nataliya I. Timofeeva, and Mikhail K. Ivanov. "Preoperative Typing of Thyroid and Parathyroid Tumors with a Combined Molecular Classifier." Cancers 13, no. 2 (January 11, 2021): 237. http://dx.doi.org/10.3390/cancers13020237.
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In previous studies, we described a method for detecting and typing malignant tumors of the thyroid gland in fine-needle aspiration biopsy samples via analysis of a molecular marker panel (normalized HMGA2 mRNA level; normalized microRNA-146b, -221, and -375 levels; mitochondrial-to-nuclear DNA ratio; and BRAFV600E mutation) in cytological preparations by quantitative PCR. In the present study, we aimed to estimate the specificity of the typing of different thyroid tumors by the proposed method. Fine-needle aspiration cytological preparations from 278 patients were used. The histological diagnosis was known for each sample. The positive and negative predictive values of the method assessed in this study were, respectively, 100% and 98% for papillary thyroid carcinoma (n = 63), 100% and 100% for medullary thyroid carcinoma (n = 19), 43.5% and 98% for follicular carcinoma (n = 15), and 86% and 100% for Hürthle cell carcinoma (n = 6). Thus, we demonstrate that the diagnostic panel, including the analysis of microRNA expression, mRNA expression, the BRAFV600E mutation, and the mitochondrial-to-nuclear DNA ratio, allows the highly accurate identification of papillary thyroid carcinoma, medullary thyroid carcinoma, and Hürthle cell carcinoma but not malignant follicular tumors (positive predictive value was below 50%).
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Titov, Sergei E., Evgeniya S. Kozorezova, Pavel S. Demenkov, Yulia A. Veryaskina, Irina V. Kuznetsova, Sergey L. Vorobyev, Roman A. Chernikov, Ilya V. Sleptsov, Nataliya I. Timofeeva, and Mikhail K. Ivanov. "Preoperative Typing of Thyroid and Parathyroid Tumors with a Combined Molecular Classifier." Cancers 13, no. 2 (January 11, 2021): 237. http://dx.doi.org/10.3390/cancers13020237.
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In previous studies, we described a method for detecting and typing malignant tumors of the thyroid gland in fine-needle aspiration biopsy samples via analysis of a molecular marker panel (normalized HMGA2 mRNA level; normalized microRNA-146b, -221, and -375 levels; mitochondrial-to-nuclear DNA ratio; and BRAFV600E mutation) in cytological preparations by quantitative PCR. In the present study, we aimed to estimate the specificity of the typing of different thyroid tumors by the proposed method. Fine-needle aspiration cytological preparations from 278 patients were used. The histological diagnosis was known for each sample. The positive and negative predictive values of the method assessed in this study were, respectively, 100% and 98% for papillary thyroid carcinoma (n = 63), 100% and 100% for medullary thyroid carcinoma (n = 19), 43.5% and 98% for follicular carcinoma (n = 15), and 86% and 100% for Hürthle cell carcinoma (n = 6). Thus, we demonstrate that the diagnostic panel, including the analysis of microRNA expression, mRNA expression, the BRAFV600E mutation, and the mitochondrial-to-nuclear DNA ratio, allows the highly accurate identification of papillary thyroid carcinoma, medullary thyroid carcinoma, and Hürthle cell carcinoma but not malignant follicular tumors (positive predictive value was below 50%).
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Martí-Carreras, Joan, and Piet Maes. "BKTyper—Web Application for VP1 and NCCR Polyoma BK Typing." Proceedings 50, no. 1 (June 9, 2020): 25. http://dx.doi.org/10.3390/proceedings2020050025.
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Human polyoma BK virus (BKV) prevalence has been increasing due to the introduction of more potent immunosuppressive agents, mostly in immunocompromised patients. BKV has been linked mostly to polyomavirus-associated hemorrhagic cystitis, and polyomavirus-associated nephropathy. BKV is a circular double stranded DNA virus (cdsDNA) with an average genome size of 5100 bp and an average GC content of 40%. Its genome codifies for five proteins: VP1, VP2, VP3, Angio gene, and the antigen T (which includes an event of alternative splicing, yielding a short and a large antigen T transcript). Additionally, it contains the non-coding control region (NCCR), known to be highly repetitive and to vary in number, length, and location of the repeats. Subtyping of BKV has been mainly studied in VP1 and the NCCR. Subtyping and subgrouping of BKV is conducted routinely in diagnostic assays and in epidemiological studies. Recently, Morel et al. published (Journal of Clinical Microbiology 2017; 55, 4) a strategy to subtype BKV through 100 bp VP1 amplicon. NCCR diversity is more complex than VP1, as it is configured by five repeat blocks (O, P, Q, R, and S). NCCR blocks can vary in number and length, resulting in a gradient of infectivity and replication. Rearranged NCCR have been linked to diverse patient etiologies, although any specific arrangement has failed to correlate with disease outcome or to have any predictive value. Due to the high abundance of BKV individuals and the clinical implications for human health that may represent BKV typing, a reliable, automatic, and free typing tool would be of great interest. Here, BKTyper is presented, a whole genome genotyper for polyoma BKV, based on a VP1 typing by Morel’s algorithm and NCCR block identification. BKTyper can accept both whole BKV genome or regions of interest in fasta format to generate the typing profile and phylogenetic analysis.
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Rietveld, MJH, JC van der Valk, IL Bongers, TM Stroet, PE Slagboom, and DI Boomsma. "Zygosity diagnosis in young twins by parental report." Twin Research 3, no. 3 (June 1, 2000): 134–41. http://dx.doi.org/10.1375/twin.3.3.134.
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AbstractThis study reports on zygosity determination in twins of childhood age. Parents responded to questionnaire items dealing with twin similarity in physical characteristics and frequency of mistaking one twin for another by parents, relatives and strangers. The accuracy of zygosity diagnosis was evaluated across twins aged 6, 8, and 10 and across parents. In addition, it was examined whether the use of multiple raters and the use of longitudinal data lead to an improvement of zygosity assignment. Complete data on zygosity questions and on genetic markers or blood profiles were available for 618 twin pairs at the age of 6 years. The method used was predictive discriminant analyses. Agreement between zygosity assigned by the replies to the questions and zygosity determined by DNA markers/blood typing was around 93%. The accuracy of assignment remained constant across age and parents. Analyses of data provided by both parents and collected over multiple ages did not result in better prediction of zygosity. Details on the discriminant function are provided. Twin Research (2000) 3, 134–141.
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Melsheimer, Peter, R. Klaes, M. v. Knebel Doeberitz, and G. Bastert. "Prospective clinical study comparing DNA flow cytometry and HPV typing as predictive tests for persistence and progression of CIN I/II." Cytometry 46, no. 3 (2001): 166–71. http://dx.doi.org/10.1002/cyto.1101.
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Almeida, Nalvo F., Shuangchun Yan, Rongman Cai, Christopher R. Clarke, Cindy E. Morris, Norman W. Schaad, Erin L. Schuenzel, et al. "PAMDB, A Multilocus Sequence Typing and Analysis Database and Website for Plant-Associated Microbes." Phytopathology® 100, no. 3 (March 2010): 208–15. http://dx.doi.org/10.1094/phyto-100-3-0208.
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Although there are adequate DNA sequence differences among plant-associated and plant-pathogenic bacteria to facilitate molecular approaches for their identification, identification at a taxonomic level that is predictive of their phenotype is a challenge. The problem is the absence of a taxonomy that describes genetic variation at a biologically relevant resolution and of a database containing reference strains for comparison. Moreover, molecular evolution, population genetics, ecology, and epidemiology of many plant-pathogenic and plant-associated bacteria are still poorly understood. To address these challenges, a database with web interface was specifically designed for plant-associated and plant-pathogenic microorganisms. The Plant-Associated Microbes Database (PAMDB) comprises, thus far, data from multilocus sequence typing and analysis (MLST/MLSA) studies of Acidovorax citrulli, Pseudomonas syringae, Ralstonia solanacearum, and Xanthomonas spp. Using data deposited in PAMDB, a robust phylogeny of Xanthomonas axonopodis and related bacteria has been inferred, and the diversity existing in the Xanthomonas genus and in described Xanthomonas spp. has been compared with the diversity in P. syringae and R. solanacearum. Moreover, we show how PAMDB makes it easy to distinguish between different pathogens that cause almost identical diseases. The scalable design of PAMDB will make it easy to add more plant pathogens in the future.
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Roth, A. D., S. Tejpar, P. Yan, R. Fiocca, D. Dietrich, G. Bodoky, R. Labianca, D. Cunningham, E. Van Cutsem, and F. Bosman. "Tissue biomarkers (BIOM) in colon cancer (COC): The translational study on the randomized phase III trial comparing infused irinotecan/5-fluorouracil (5-FU)/folinic acid (FA) to 5-FU/FA in stage II-III COC patients (pts)." Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 4022. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.4022.
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4022 Background and Aims: PETACC 3 is a large adjuvant trial with 3,005 COC pts. The value of BIOM in COC in adjuvant setting is still a matter of debate because of lack of large data sets. We took advantage of PETACC 3 to assess P53, SMAD4, thymidylate synthetase (TS), telomerase (HTERT) expressions, UGT1A1 genotype, KRAS and BRAF mutations, microsatellite instability (MSI), 18q and 8p LOH with regard to their prognostic and predictive value and their individual interactions on a very large homogeneous cohort of COC pts. In addition we investigated the association between UGT1A1 genotype and occurrence of diarrhoea and Gd 4 neutropenia. Methods: 1,564 formalin fixed paraffin embedded (FFPE) tissue blocks of PETACC 3 pts were prospectively collected and 5–20μ sections cut. DNA from normal (Nor) and tumoral (Tu) tissue was extracted after section microdissection. P53, SMAD4, TS and HTERT were assessed by immunohistochemistry (IHC); MSI was typed with 10 markers, KRAS exon 2 and BRAF exon 15 mutations by allele specific real time PCR on Tu DNA; 18q and 8p LOH by typing multiple SNPs by pyrosequencing on Nor/Tu DNA; UGT1A1 genotypes by PCR and fragment sizing on Nor DNA. Prognostic/predictive value of each BIOM is analysed by Cox regression for disease free survival and by logistic regression for specific toxicity. Associations between any 2 categorized BIOM and between each BIOM and each known prognostic variable are tested by chi-square tests. Results: DNA of 1405 pts was extracted and successfully analyzed in 97.1% for KRAS, 98.6% for BRAF, 94% for 18q LOH, 93.6% for MSI, 86% for UGT1A1, 8p LOH is still ongoing. Of 1530 pts slides IHC analysis was successful in 94.5% for P53, 94.2% for SMAD4, 82.9% for TS, 53.9% for HTERT. The clinical database was made available in Nov 06 and statistical analysis started on Dec 11th 2006. Conclusion: This is the largest multicenter centrally coordinated tissue BIOM study performed in COC to date. The high success rate of analysis shows that large prospective BIOM studies can be performed on routine FFPE material. Final results on the prognostic/predictive value of each molecular BIOM will be available at the meeting. No significant financial relationships to disclose.
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Chapman, Rebecca, David R. Ghasemi, Pierre LeBlond, Hendrik Witt, Jacques Grill, John-Paul Kilday, Piergiorgio Modena, et al. "EPEN-24. Biological markers of ependymoma in children and adolescents (BIOMECA): Systematic comparison of methods for the precise evaluation of biomarkers for ependymoma diagnosis and prognostication." Neuro-Oncology 24, Supplement_1 (June 1, 2022): i44. http://dx.doi.org/10.1093/neuonc/noac079.160.
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Abstract The identification and validation of prognostic and diagnostic biomarkers is a key element of The SIOP Ependymoma II trial, realised through the Biomarkers of Ependymoma in Children and Adolescents study (BIOMECA). BIOMECA aims to identify and validate biomarkers for prediction of outcome whilst enhancing stratification for the next generation of ependymoma trials. We outline our findings from the first 147 consecutive BIOMECA cases (posterior fossa, PF=111; supratentorial, ST=32; spinal, SP=4). We compared various methods for biomarker assessment, across six European laboratories to determine key analysis methods. Methods included: methylation-based classification (EPIC 850K DNA methylation array) (n=141); immunohistochemistry (IHC) for nuclear p65-RELA (n=32), H3K27me3 (n=115), and Tenascin-C (TNC) (n=147); copy number (CN) analysis by FISH, MLPA (1q, CDKN2A) (n=147), and MIP (molecular inversion probe) and DNA methylation array (1q, CDKN2A, 6q, 11q, 13q, 22q) (n=141); analysis of ZFTA- and YAP1-fusions by RT-PCR, sequencing, Nanostring assays and break-apart FISH (n=32). Using DNA methylation-based classification, 91% (n=101/111) of PF cases classified as PF ependymoma group A (PFA) and 69% (n=22/32) of ST cases as ST ependymoma, ZFTA fusion-positive (ZFTA). Most PFAs demonstrated inter-centre agreement for loss of H3K27me3, and were TNC positive, representing surrogate markers for PFA identification. Combinations of p65-RELA IHC, FISH analysis, and RNA-based methods were suitable to identify ZFTA- and YAP1- fused ST ependymomas. Predictive CN alterations were identified by high-resolution, quantitative MIP technology.The integration of histopathology assessment and molecular typing is now critical as the updated 2021 WHO CNS5 classification of ependymomas lists seven molecularly distinct entities. This study highlights the importance of evaluating different methods in a prospective trial cohort. Here, advanced molecular techniques represent powerful tools for the classification of ependymoma entities (DNA methylation array) and for the detection of CN alterations (MIP) and specific fusions, enabling the correct classification and identification of prognostic markers.
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Volante, Marco, Alfred K. Lam, Mauro Papotti, and Giovanni Tallini. "Molecular Pathology of Poorly Differentiated and Anaplastic Thyroid Cancer: What Do Pathologists Need to Know?" Endocrine Pathology 32, no. 1 (February 4, 2021): 63–76. http://dx.doi.org/10.1007/s12022-021-09665-2.
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AbstractThe molecular characterization of poorly and anaplastic thyroid carcinomas has been greatly improved in the last years following the advent of high throughput technologies. However, with special reference to genomic data, the prevalence of reported alterations is partly affected by classification criteria. The impact of molecular pathology in these tumors is multifaceted and bears diagnostic, prognostic, and predictive implications although its use in the clinical practice is not completely assessed. Genomic profiling data claim that genetic alterations in poorly differentiated and anaplastic thyroid carcinomas include “Early” and “Late” molecular events, which are consistent with a multi-step model of progression. “Early” driver events are mostly RAS and BRAF mutations, whereas “Late” changes include above all TP53 and TERT promoter mutations, as well as dysregulation of gene involved in the cell cycle, chromatin remodeling, histone modifications, and DNA mismatch repair. Gene fusions are rare but represent relevant therapeutic targets. Epigenetic modifications are also playing a relevant role in poorly differentiated and anaplastic thyroid carcinomas, with altered regulation of either genes by methylation/deacetylation or non-coding RNAs. The biological effects of epigenetic modifications are not fully elucidated but interfere with a wide spectrum of cellular functions. From a clinical standpoint, the combination of genomic and epigenetic data shows that several molecular alterations affect druggable cellular pathways in poorly differentiated and anaplastic thyroid carcinomas, although the clinical impact of molecular typing of these tumors in terms of predictive biomarker testing is still under exploration.
Dissertations / Theses on the topic "Predictive DNA typing"
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Bardan, Felicia. "New forensic DNA profiling techniques for human identification." Thesis, 2019. http://hdl.handle.net/2440/120161.
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Highly degraded biological samples are commonly encountered in missing persons cases, historical human remains, war graves, mass disasters and various forensic casework. As biological tissue degrades, DNA becomes progressively fragmented and chemical modifications can occur, complicating successful standard short tandem repeat typing. Alternative genotyping strategies such as single nucleotide polymorphism typing and the emergence of massively parallel sequencing to examine ancestry and phenotype SNPs have ushered in a new era of forensic intelligence testing for problematic samples. Despite showing promise, a number of technical concerns still exist for the use of these strategies in forensic investigation. The research presented in this thesis explores, develops and assesses alternative techniques using both traditional and new technologies for the retrieval of forensic intelligence data from highly degraded samples. I develop new techniques for the screening and genotyping of highly degraded DNA and generate a new dataset of ancestry data from an Australian population for use in analysing historical samples. Issues relating to the implementation of these technologies are discussed, including laboratory workflow, data analysis and interpretation, ethics, and the need for standard guidelines for forensic laboratories to adopt in their methodology. Specifically, in this thesis I use: • A SNP typing strategy based on conventional techniques and equipment to develop a screening tool that estimates sample degradation and presumptive broad biological profile for the triage of forensic samples – Chapter 2 • Emerging target enrichment and massively parallel sequencing technologies for the generation of ancestry and phenotype data for forensic investigation – Chapter 3 • Techniques developed and assessed in Chapter 2 and 3 to analyse a set of degraded DNA and forensic casework samples, demonstrating the utility of the methods to genotype and provide forensic intelligence data for challenging samples – Chapter 4 • mtDNA and autosomal SNP analysis to construct the first Australian reference population database for ancestry testing of historical human remains – Chapter 5. In essence, my research aimed to explore techniques to improve the genetic assessment of highly degraded and compromised forensic samples, and to build on current knowledge concerning the implementation of such techniques in forensic investigations.Thesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 2019