Relevant bibliographies by topics / Therapeutic target identification

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  2. Dissertations / Theses
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Academic literature on the topic 'Therapeutic target identification'

Author: Grafiati
Published: 16 November 2024

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Journal articles on the topic "Therapeutic target identification"

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Koscielny, Gautier, Peter An, Denise Carvalho-Silva, Jennifer A. Cham, Luca Fumis, Rippa Gasparyan, Samiul Hasan, et al. "Open Targets: a platform for therapeutic target identification and validation." Nucleic Acids Research 45, no. D1 (November 29, 2016): D985—D994. http://dx.doi.org/10.1093/nar/gkw1055.

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Bajorath, Jürgen. "Identification and validation of therapeutic target proteins." TARGETS 1, no. 2 (August 2002): 45–46. http://dx.doi.org/10.1016/s1477-3627(02)02194-3.

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Hassan, Md Imtaiyaz. "Multi-omics approaches to therapeutic target identification." Briefings in Functional Genomics 22, no. 2 (March 2023): 75. http://dx.doi.org/10.1093/bfgp/elac058.

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Liao, Jianbo, Qinyu Wang, Fengxu Wu, and Zunnan Huang. "In Silico Methods for Identification of Potential Active Sites of Therapeutic Targets." Molecules 27, no. 20 (October 20, 2022): 7103. http://dx.doi.org/10.3390/molecules27207103.

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Target identification is an important step in drug discovery, and computer-aided drug target identification methods are attracting more attention compared with traditional drug target identification methods, which are time-consuming and costly. Computer-aided drug target identification methods can greatly reduce the searching scope of experimental targets and associated costs by identifying the diseases-related targets and their binding sites and evaluating the druggability of the predicted active sites for clinical trials. In this review, we introduce the principles of computer-based active site identification methods, including the identification of binding sites and assessment of druggability. We provide some guidelines for selecting methods for the identification of binding sites and assessment of druggability. In addition, we list the databases and tools commonly used with these methods, present examples of individual and combined applications, and compare the methods and tools. Finally, we discuss the challenges and limitations of binding site identification and druggability assessment at the current stage and provide some recommendations and future perspectives.
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Hu, Yang, Yinteng Wu, Fu Gan, Mingyang Jiang, Dongxu Chen, Mingjing Xie, Yiji Jike, and Zhandong Bo. "Identification of Potential Therapeutic Target Genes in Osteoarthritis." Evidence-Based Complementary and Alternative Medicine 2022 (August 13, 2022): 1–15. http://dx.doi.org/10.1155/2022/8027987.

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Objective. Osteoarthritis (OA), also known as joint failure, is characterized by joint pain and, in severe cases, can lead to loss of joint function in patients. Immune-related genes and immune cell infiltration play a crucial role in OA development. We used bioinformatics approaches to detect potential diagnostic markers and available drugs for OA while initially exploring the immune mechanisms of OA. Methods. The training set GSE55235 and validation set GSE51588 and GSE55457 were obtained from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified by the limma package. Gene set enrichment analysis (GSEA) was performed on the GSE55235 dataset using the cluster profiler package. At the same time, DEGs were analyzed by gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, protein-protein interaction (PPI) analysis was performed on the common DEGs of the three datasets using the STRING database. Proteins with direct linkage were identified as hub genes, and the relation of hub genes was subsequently analyzed using the GOSemSim package. Hub genes’ expression profiles and diagnostic capabilities (ROC curves) were analyzed and validated using three datasets. In addition, we performed RT-qPCR to validate the levels of hub genes. The immune microenvironment was analyzed using the CIBERSORT package, and the relationship between hub genes and immune cells was evaluated. In addition, we used a linkage map (CMAP) database to identify available drug candidates. Finally, the GSEA of hub genes was used to decipher the potential pathways corresponding to hub genes. Results. Three hub genes (CX3CR1, MYC, and TLR7) were identified. CX3CR1 and TLR7 were highly expressed in patients with OA, whereas the expression of MYC was low. The results of RT-qPCR validation were consistent with those obtained using datasets. Among these genes, CX3CR1 and TLR7 can be used as diagnostic markers. It was found that CX3CR1, MYC, and TLR7 affect the immune microenvironment of OA via different immune cells. In addition, we identified a potential drug for the treatment of OA. Altogether, CX3CR1, MYC, and TLR7 affect the immune response of OA through multiple pathways. Conclusion. CX3CR1, MYC, and TLR7 are associated with various immune cells and are the potential diagnostic markers and therapeutic targets for OA.
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Frühwald, M. C., and C. Plass. "Metastatic medulloblastoma—therapeutic success through molecular target identification?" Pharmacogenomics Journal 2, no. 1 (January 2002): 7–10. http://dx.doi.org/10.1038/sj.tpj.6500077.

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Zou, Mingjie, Haiyuan Zhou, Letian Gu, Jingzi Zhang, and Lei Fang. "Therapeutic Target Identification and Drug Discovery Driven by Chemical Proteomics." Biology 13, no. 8 (July 23, 2024): 555. http://dx.doi.org/10.3390/biology13080555.

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Throughout the human lifespan, from conception to the end of life, small molecules have an intrinsic relationship with numerous physiological processes. The investigation into small-molecule targets holds significant implications for pharmacological discovery. The determination of the action sites of small molecules provide clarity into the pharmacodynamics and toxicological mechanisms of small-molecule drugs, assisting in the elucidation of drug off-target effects and resistance mechanisms. Consequently, innovative methods to study small-molecule targets have proliferated in recent years, with chemical proteomics standing out as a vanguard development in chemical biology in the post-genomic age. Chemical proteomics can non-selectively identify unknown targets of compounds within complex biological matrices, with both probe and non-probe modalities enabling effective target identification. This review attempts to summarize methods and illustrative examples of small-molecule target identification via chemical proteomics. It delves deeply into the interactions between small molecules and human biology to provide pivotal directions and strategies for the discovery and comprehension of novel pharmaceuticals, as well as to improve the evaluation of drug safety.
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Traa, Annika, Emily Machiela, Paige D. Rudich, Sonja K. Soo, Megan M. Senchuk, and Jeremy M. Van Raamsdonk. "Identification of Novel Therapeutic Targets for Polyglutamine Diseases That Target Mitochondrial Fragmentation." International Journal of Molecular Sciences 22, no. 24 (December 14, 2021): 13447. http://dx.doi.org/10.3390/ijms222413447.

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Huntington’s disease (HD) is one of at least nine polyglutamine diseases caused by a trinucleotide CAG repeat expansion, all of which lead to age-onset neurodegeneration. Mitochondrial dynamics and function are disrupted in HD and other polyglutamine diseases. While multiple studies have found beneficial effects from decreasing mitochondrial fragmentation in HD models by disrupting the mitochondrial fission protein DRP1, disrupting DRP1 can also have detrimental consequences in wild-type animals and HD models. In this work, we examine the effect of decreasing mitochondrial fragmentation in a neuronal C. elegans model of polyglutamine toxicity called Neur-67Q. We find that Neur-67Q worms exhibit mitochondrial fragmentation in GABAergic neurons and decreased mitochondrial function. Disruption of drp-1 eliminates differences in mitochondrial morphology and rescues deficits in both movement and longevity in Neur-67Q worms. In testing twenty-four RNA interference (RNAi) clones that decrease mitochondrial fragmentation, we identified eleven clones—each targeting a different gene—that increase movement and extend lifespan in Neur-67Q worms. Overall, we show that decreasing mitochondrial fragmentation may be an effective approach to treating polyglutamine diseases and we identify multiple novel genetic targets that circumvent the potential negative side effects of disrupting the primary mitochondrial fission gene drp-1.
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Keerthana N and Koteeswaran K. "Target identification and validation in research." World Journal of Biology Pharmacy and Health Sciences 17, no. 3 (March 30, 2024): 107–17. http://dx.doi.org/10.30574/wjbphs.2024.17.3.0116.

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Target identification is a critical step in biomedical research because it lays the groundwork for the development of new therapies and drugs. Genetic research, including genome-wide association studies (GWAS), genomic sequencing, functional genomics, and data integration, is crucial for understanding disease genetics and potential treatment targets. Transcriptomics and proteomics give data on gene and protein expression, making it easier to identify targets in dysregulated diseases. Target identification is essential for drug discovery, precision medicine, lowering medication attrition, increasing therapeutic efficacy, and, eventually, transforming patient care and drug development. Target validation is a critical stage in drug development because it verifies that revealed molecular targets play a substantial role in disease progression and are therefore suitable for treatment. It employs a range of approaches, including genetic validation, pharmacological validation, and animal model validation. Target validation assures that discovered targets are physiologically relevant, druggable, and have a direct impact on disease processes, thereby reducing pharmaceutical attrition, promoting precision medicine, and hastening therapeutic development. Historically, target identification relied on limited knowledge, typically through candidate-based techniques based on assumptions or prior observations. Target validation experiments looked into how gene knockdown or RNA interference affected illness symptoms. Genomics, proteomics, and functional genomics have all made advances in recent years, as have high-throughput screening and data integration. CRISPR-based technologies and high-throughput sequencing have assisted in the validation of targets. Single-cell validation, machine learning and artificial intelligence, advanced in vitro models like organoids, and patient-derived models will all help to make future assessments of target relevance and treatment responses more precise and individualized. These developments have the potential to dramatically revolutionize research target identification and validation.
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Lin, Chunsheng, Qianqian Tian, Sifan Guo, Dandan Xie, Ying Cai, Zhibo Wang, Hang Chu, Shi Qiu, Songqi Tang, and Aihua Zhang. "Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification." Molecules 29, no. 10 (May 8, 2024): 2198. http://dx.doi.org/10.3390/molecules29102198.

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As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.
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Dissertations / Theses on the topic "Therapeutic target identification"

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Park, Jong Kook. "Target Identification, Therapeutic Application and Maturation Mechanism of microRNAs." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1331096696.

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Cheung, Chi-ho, and 張志豪. "Identification of CD47 as a novel therapeutic target for hepatocellular carcinoma." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46945374.

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Hendley, Rhiannon. "Identification of Lyn kinase as a therapeutic target for tamoxifen resistant breast cancer." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/31462/.

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Tamoxifen has made a significant contribution in decreasing breast cancer related deaths for over 30 years and until recently was the gold standard for treatment of ER positive breast cancer (Fisher et al, 1998). Resistance to tamoxifen is however a considerable issue with cells utilising a number of molecular mechanisms to bypass the growth inhibition caused by blocking ER activity. This move towards an anti-hormone resistant state from an antihormone responsive state is associated with the transition to a much more aggressive phenotype including increased proliferation and also invasiveness. Thus unfortunately, acquisition of tamoxifen resistance is not only associated with a recurrence of breast cancer, but this cancer is also much more aggressive in nature with fewer treatment options available than the initial cancer. This study has identified Lyn kinase as increased in tamoxifen resistant breast cancer cells compared to oestrogen-responsive breast cancer cells. Subsequent removal of Lyn kinase from tamoxifen resistant breast cancer cell lines using RNAi technology led to a significant decrease in cell proliferation, increased apoptosis and also a decrease in migration and invasion. A mechanism has been suggested whereby Lyn kinase is involved in a calcium dependent zinc wave which ultimately leads to the activation of tyrosine kinases. Metastasis to other sites in the body is ultimately responsible for fatalities due to breast cancer and so being able to block its action is key to treating breast cancer in the clinic. Therefore identifying Lyn kinase as a gene target that leads to the advancement of breast cancer to a more aggressive state provides a powerful tool for treating breast cancer in the clinic.
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Paudel, Nirmala. "Computational analysis of biochemical networks for drug target identification and therapeutic intervention design." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90152.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 96-104).
Identification of effective drug targets to intervene, either as single agent therapy or in combination, is a critical question in drug development. As complexity of disease like cancer is revealed, it has become clear that a holistic network approach is needed to identify drug targets that are specially positioned to provide desired leverage on disease phenotypes. In this thesis we develop a computational framework to exhaustively evaluate target behaviors in biochemical network, either as single agent or combination therapies. We present our single target therapy work as a problem of identifying good places to intervene in a network. We quantify a relationship between how interventions at different places in network affect an output of interest. We use this quantitative relationship between target inhibited and output of interest as a metric to compare targets. In network analyzed here, most targets show a sub-linear behavior where a large percentage of targeted molecule needs to be inhibited to see a small change on output. The other key observation is that targets at the top of the network exerted relatively small control compared to the targets at the bottom of the network. In the combination therapy work we study how combination of drug concentrations affect network output of interest compared to when one of the drugs was given alone at equivalent concentrations. By adapting the definitions of additive, synergistic, and antagonistic combination behaviors developed by Ting Chao-Chou (Chou TC, Talalay P (1984), Advances in enzyme regulation 22: 27-55) for our system and systematically perturbing biochemical pathway, we explore the range of combination behaviors for all plausible combination targets. This holistic approach reveals that most target combinations show additive behaviors. Synergistic, and antagonistic behaviors are rare. Even when combinations are classified as synergistic or antagonistic, they show this behavior only in a small range of the inhibitor concentrations. This work is developed in a particular variant of the epidermal growth factor (EGF) receptor pathway for which a detailed mathematical model was first proposed by Schoeberl et al. Computational framework developed in this work is applicable to any biochemical network.
by Nirmala Paudel.
Ph. D.
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BENINI, MONICA. "Identification of the frataxin-specific E3 ligase as a potential therapeutic target for Friedreich’s Ataxia." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2015. http://hdl.handle.net/2108/203003.

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Friedreich’s ataxia (FRDA) is a rare debilitating, life-shortening, autosomal recessive inherited disease that leads to progressive damage to the nervous system. Onset is usually around the puberty and patients develop a progressive loss of motor coordination, inability to walk, slurred speech, and a cardiac hypertrophy that often leads to premature death. The particular genetic mutation – expansion of an intronic GAA triplet repeat in the FXN gene – leads to reduced expression of the mitochondrial protein frataxin involved in iron-sulfur cluster biogenesis. The subsequent frataxin insufficiency causes mitochondrial dysfunction and oxidative damage with ultimately cell death, particularly in peripheral sensory ganglia. No therapy to prevent or slow down the progression of the disease has been found yet. Since there is an inverse correlation between the amount of residual frataxin and the severity of disease progression, therapeutic approaches aiming at increasing frataxin levels are expected to improve patients’ conditions. We have recently proven the therapeutic relevance of increasing frataxin levels by preventing its degradation. Indeed, we have recently shown that a significant amount of frataxin precursor is degraded by the ubiquitin-proteasome system before its functional mitochondrial maturation and we have described the therapeutic potential of small molecules that promote frataxin accumulation by docking on the frataxin ubiquitination site, thus interfering with its ubiquitination and degradation. In light of these data, inhibition of frataxin E3 ubiquitin ligase, the enzyme responsible for frataxin ubiquitination, could represent another attractive strategy to prevent frataxin degradation. We therefore pursued the identification of such enzyme by performing a functional screening of an E3 ubiquitin ligase small interfering RNA library. HIT2 was identified and validated as a candidate from this screening. Consistently, knockdown of HIT2 promotes frataxin accumulation in cells. Most importantly, silencing of this candidate gene results in frataxin accumulation also in cells derived from FRDA patients, suggesting the therapeutic potential of strategies aimed at inhibiting this E3 enzyme. Additionally, we demonstrated that HIT2 directly interacts with frataxin and its overexpression increased frataxin protein ubiquitination in a catalytic activity-dependent manner, both in cells and in in vitro assay, indicating that this enzyme may actually represent the frataxin E3 ubiquitin ligase. These findings suggest that HIT2 could be a novel important therapeutic target for Friedreich’s ataxia.
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TRICARICO, PAOLA MAURA. "Mevalonate Kinase Deficiency: identification of new therapeutic target, in vitro and in vivo pathogenic study." Doctoral thesis, Università degli Studi di Trieste, 2016. http://hdl.handle.net/11368/2908002.

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Il Difetto di Mevalonato Chinasi (MKD) è una malattia rara autoinfiammatoria autosomica recessiva, causata da mutazioni nel gene MVK che codifica per mevalonato chinasi (MK), enzima chiave della via del mevalonato. Questa via è importante per la produzione di colesterolo, ed anche geranilgeranil pirofosfato e farnesil pirofosfato essenziali per la prenilazione delle proteine. MKD ha fenotipi clinici eterogenei, infatti, si va da una forma lieve, la sindrome iper-IgD (HIDS), ad una forma più grave, la Mevalonica Aciduria (MA). HIDS è caratterizzata da sintomi eterogenei che comprendono febbri ricorrenti, eruzioni cutanee, afte, artralgia, dolori addominali, diarrea e vomito; mentre MA oltre a tutto questo, mostra un fenotipo più grave con coinvolgimento neurologico, ritardo psicomotorio, epatopatia e atassia cerebellare. Più del 50% dei pazienti MA muore durante l'infanzia o nella prima infanzia. Non è tuttora chiara la correlazione tra mutazioni di MVK ed il fenotipo clinico di MKD; infatti a causa della grande eterogeneità genetica e clinica, la correlazione genotipo-fenotipo risulta essere problematica. L’MKD ad oggi è ancora una malattia orfana di trattamento eziologico specifico, sono ancora poco conosciuti i meccanismi patogenetici ed i principali attori coinvolti nella malattia; in particolar modo, non è ancora stata chiarita la patogenesi collegata alle gravi manifestazioni cliniche di MA così come i meccanismi neuro-infiammatori e le interazioni che avvengono tra i diversi tipi cellulari nel sistema nervoso centrale. L'ipotesi patogenetica di MKD ad oggi più accreditata collega il fenotipo infiammatorio con la diminuzione di composti isoprenoidi e del livello di proteine prenilate, causato dal blocco della via del mevalonato. Questa diminuzione di proteine determina attivazione dell’inflammosoma NALP-3, che a sua volta induce l'attivazione ed rilascio di IL-1β. Attualmente, vi è una mancanza di modelli per lo studio dell’MKD. Infatti, il modello biochimico ottenuto in vivo e in vitro mediante somministrazione di inibitori della via del mevalonato (aminobifosfonati o statine) è l'unico modello in grado di mimare le caratteristiche patologiche. L'obiettivo di questo progetto di dottorato è indagare il meccanismo patogenetico del Difetto di Mevalonato Chinasi, ponendo particolare attenzione alla forma più grave, la Mevalonico Aciduria, valutando i meccanismi neuro-apoptotici e neuroinfiammatori tipici di questa sindrome. Per tutti questi motivi, abbiamo eseguito l’analisi dell’esoma di pazienti MKD, per valutare la presenza di eventuali altri geni implicati nelle variazioni fenotipiche; studiato, in modelli biochimici in vitro (ottenuti in cellule neuronali, microgliali e monocitiche), i meccanismi patogenetici di MKD, tra cui l'apoptosi, il danno mitocondriale, lo stress ossidativo e l'infiammazione; abbiamo inoltre valutato l'infiammazione sistemica e la neuro-infiammazione nel modello biochimico in vivo, ottenuto in due diversi ceppi di topi (BALB/C e C57BL/6); infine, abbiamo sviluppato un modello genetico in vitro, utilizzando trasfezione transitoria di due differenti mutazioni tipiche di MKD (I268T associato ad HIDS, e N301T tipico di MA), valutando le basi molecolari della malattia e il meccanismo patologico legato al processo autofagico.
Mevalonate Kinase Deficiency (MKD) is a rare autoinflammatory autosomal recessive inborn disease, caused by mutations in MVK gene that encodes for Mevalonate Kinase (MK) an important enzyme of the mevalonate pathway. Mevalonate pathway is important for the production of cholesterol, geranylgeranyl pyrophosphate and farnesyl pyrophosphate essential for protein prenylation. MKD has heterogeneous clinical phenotypes, with a mild form, Hyper-IgD Syndrome (HIDS), and a severe one, Mevalonic Aciduria (MA). Heterogeneous symptoms including recurrent fevers, cutaneous rash, aphtae, arthralgia, abdominal pain with diarrhoea and vomiting characterize HIDS, while MA shows a more critical neurologic phenotype with psychomotor retardation, hepatopathy and cerebellar ataxia. More than 50% of MA patients die in infancy or early childhood. The correlation between MVK mutations and MKD clinical phenotype is still to be elucidated. Genotype-phenotype correlation is sometimes problematic due to the great genetic and clinical heterogeneity. MKD is also an orphan drug disease and the pathogenic mechanisms as well as the main actors involved in disease’s aetiology are still unknown; especially the pathogenesis of MA clinical manifestations has not been established. Indeed, the neuro-inflammatory mechanisms and the interactions that occur between the different cellular types in the brain have not yet been explained. The most accredited MKD pathogenetic hypothesis is based on the evidence that the mevalonate pathway block induces a decrease in isoprenoid compounds and prenylated proteins, leading to inflammatory phenotypes, caused by the activation of NALP-3 inflammasome that consequently determines IL-1β activation. Currently there is a lack of models for MKD studies. Indeed, the only model able to mimic pathologic features is a biochemical model obtained in vivo and in vitro by administration of mevalonate pathway inhibitors such as aminobisphosphonate or statin. The aim of this PhD project is to investigate the pathogenic mechanism of MKD. Special attention is given to MA, in order to evaluate the neuro-apoptotic and neuro-inflammatoy mechanisms leading to this syndrome. For all these reasons, we performed exome analyse of MKD patients in order to evaluate the presence of eventual other modifiers gene, able to modulate MKD phenotype; we investigated pathogenic mechanisms of MKD, including apoptosis, mitochondrial damage, oxidative stress and inflammation using an in vitro biochemical models (i.e., neuronal, microglia and monocytic cells); we also evaluated systemic inflammation and neuro-inflammation employing an in vivo biochemical model obtained in two different mice strains (BALB/c and C57BL/6); finally, we developed an in vitro genetic model using transient transfection of two different MKD mutations (I268T associated with HIDS, and N301T typical of MA), evaluating the molecular basis of MKD and the pathology mechanism linked to autophagy. The main specific results emerging from this PhD thesis work are: - GRID2 could be a modifier gene of MKD; - biochemical block of mevalonate pathway in neuronal cells caused a balance between apoptosis follows mitochondrial pathway (caspase-9 and caspase-3 dependent) and pyroptosis (caspase-1 dependent); - microglial activation is a direct consequence of mevalonate pathway block, which induces an additional increase of neuronal cell death; - systemic and neuronal inflammations are observed in biochemical in vivo model obtained in two different mice strains; - mevalonate pathway block induced mitochondrial damage, leading to oxidative stress and pro-inflammatory cytokines’ release, which leaded cells to final apoptosis; - MVK mutations cause an alteration in autophagic flux that leads cells to final apoptosis, in in vitro genetic model of MKD in neuronal cells. The findings obtained during the PhD enabled to formulate a new MKD pathogenic hypothesis, based on mitophagy impairment.
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Hoppe, Stephanie [Verfasser], and Martin [Akademischer Betreuer] Müller. "Identification of target T cell epitopes for a therapeutic HPV16 vaccine / Stephanie Hoppe ; Betreuer: Martin Müller." Heidelberg : Universitätsbibliothek Heidelberg, 2019. http://d-nb.info/1177043491/34.

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Slim, Lotfi. "Detection of epistasis in genome wide association studies with machine learning methods for therapeutic target identification." Thesis, Université Paris sciences et lettres, 2020. https://pastel.archives-ouvertes.fr/tel-02895919.

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En offrant une image sans précédent du génome humain, les études d'association pangénomiques (GWAS) expliqueraient pleinement le contexte génétique des maladies complexes. A ce jour, les résultats ont été pour le moins mitigés. Cela peut être partiellement attribué à la méthodologie statistique adoptée, qui ne prend pas souvent en compte l'interaction entre les variants génétiques, ou l'épistasie. La détection d'épistasie à travers des modèles statistiques présente plusieurs défis pour lesquels nous développons dans cette thèse une paire d'outils adéquats. Le premier outil, epiGWAS, utilise l'inférence causale pour détecter les interactions épistatiques entre un SNP cible et le reste du génome. Le deuxième outil, kernelPSI, utilise à la place des méthodes à noyaux pour modéliser l'épistasie entre plusieurs polymorphismes mononucléotidiques (SNPs) voisins. Il tire également partie de l'inférence post-sélection pour effectuer conjointement une sélection au niveau des SNPs et des tests de signification au niveau des gènes. Les outils développés sont - au meilleur de nos connaissances - les premiers à étendre au domains des GWAS des outils puissants d'apprentissage statistique tels que l'inférence causale et l'inférence post-sélection nonlinéaire. En plus des contributions méthodologiques, un accent particulier a été mis sur l'interprétation biologique pour valider nos résultats dans la sclérose en plaques et les variations d'indice de masse corporelle
By offering an unprecedented picture of the human genome, genome-wide association studies (GWAS) have been expected to fully explain the genetic background of complex diseases. So far, the results have been mitigated to say the least. This, among other things, can be partially attributed to the adopted statistical methodology, which does not often take into account interaction between genetic variants, or epistasis. The detection of epistasis through statistical models presents several challenges for which we develop in this thesis a pair of adequate tools. The first tool, epiGWAS, uses causal inference to detect epistatic interactions between a target SNP and the rest of the genome. The second tool, kernelPSI, instead uses kernel methods to model epistasis between nearby single-nucleotide polymorphisms (SNPs). It also leverages post-selection inference to jointly perform SNP-level selection and gene-level significance testing. The developed tools are -- to the best of our knowledge -- the first to extend powerful statistical learning frameworks such as causal inference and nonlinear post-selection inference to GWAS. In addition to the methodological contributions, a special emphasis was placed on biological interpretation to validate our findings in multiple sclerosis and body-mass index variations
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Maule, Francesca. "Identification of Annexin 2A as a fundamental mediator of glioblastoma cell dissemination and potential therapeutic target." Doctoral thesis, Università degli studi di Padova, 2017. http://hdl.handle.net/11577/3422285.

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Glioblastoma multiforme (GBM) is the most devastating tumor of the brain, characterized by an almost inevitable tendency to recur after intensive treatments and a fatal prognosis. Indeed, despite recent technical improvements in GBM surgery, the complete eradication of cancer cell disseminated outside the tumor mass still remains a crucial issue for glioma patients management. In my PhD project, we identified Annexin 2A (ANXA2) as an important intracellular cytoskeletal protein expressed also on the surface of various types of cancer cells. Initially, we show that ANXA2 is over-expressed in IV grade GBM at various levels when compared to lower stage tumors. More importantly, we demonstrated that low/absent expression of ANXA2 identifies a subgroup of GBM patients endowed with better prognosis, suggesting that ANXA2 expression can be considered as an independent prognostic factor in glioma. We then analyzed the transcriptional changes associated to different levels of ANXA2 expression. In particular, we generated a series of ANXA2 dependent transcriptional signatures based on the comparison between ANXA2hi versus ANXA2lo expressing GBM patients from the TCGA and GSE13041 datasets (719 differentially expressed genes in common between the two cohorts), modulated transcripts after ANXA2 neutralization by specific antibody (855 differentially expressed genes) and the expression profiles of ANXA2 silenced cells respect to relative controls (3592 differentially expressed genes) in our primary GBM cell cultures. Interestingly, Gene Set Enrichment Analysis (GSEA) on the three different signatures obtained, revealed a negative enrichment of cell migration and mesenchymal transition related genes. These data strongly suggested the important role played by ANXA2 in GBM cell behavior and aggressiveness, allowing us to further setup strategies to specifically modulate its functions and dependent intracellular signaling. For this reason, we further analyzed ANXA2 functional activity in vitro in primary GBM cell cultures, demonstrating as ANXA2 is a major sustainer of GBM cell aggressiveness by regulating cellular invasion and motility together with cancer cell proliferation and differentiation status. Moreover, based on gene expression data of ANXA2 neutralized cells, we were able to test the prognostic potential of an ANXA2down signature in multiple cancer datasets, demonstrating that expression of genes regulated by ANXA2 fluctuations predict cancer patients outcome by themselves. Finally, we then functionally mapped an ANXA2-dependent gene signature (TCGA and GSE13041 datasets analysis) by exploiting the Connectivity Map bioinformatic tool in order to identify compounds and approved drugs able to revert this signature of GBM aggressiveness. The compounds, significantly predicted to be able to counteract the ANXA2-dependent transcriptional signature, were analyzed for their ability to inhibit GBM cell invasion in vitro in primary GBM cultures. Finally, we applied ANXA2 dependent transcriptional signatures, previously generated from our primary GBM cells, to the QUADrATiC tool, which was allowed the exploration of a larger database of reference cell lines and perturbagens.
Il Glioblastoma Multiforme (GBM) è il tumore cerebrale più aggressivo, caratterizzato da una prognosi infausta e dall’inevitabile tendenza a ricadere anche in seguito ad un trattamento intensivo. Nonostante i recenti miglioramenti tecnici nella chirurgia del GBM, la sua completa rimozione rimane ad oggi uno dei maggiori problemi legati all’insuccesso terapeutico di questi pazienti. Questo studio si focalizza sulla caratterizzazione di annessina 2A (ANXA2), proteina presente in diversi compartimenti delle cellule normali e ritrovata anche sulla superficie di diversi tipi di cellule tumorali. Con lo sviluppo di questo progetto, abbiamo dimostrato che ANXA2 è espressa ad alti livelli nei gliomi di IV grado rispetto ai gliomi di grado minore e che una bassa/nulla espressione di ANXA2 identifica un sottogruppo di pazienti caratterizzati da una prognosi migliore, suggerendo come l’espressione di ANXA2 possa essere considerata un fattore prognostico indipendente nei gliomi. Successivamente, con lo scopo di analizzare i cambiamenti trascrizionali associati ai differenti livelli di espressione di ANXA2, abbiamo generato una signature trascrizionale ANXA2-dipendente utilizzando i dati provenienti dai dataset pubblici TCGA e GSE13041 e basata sul confronto tra pazienti esprimenti alti livelli di ANXA2 e pazienti esprimenti bassi livelli di questa proteina (719 geni differenzialmente espressi in comune tra le due coorti). Sono state quindi generate due signature ANXA2-dipendenti basate rispettivamente sui trascritti modulati in seguito alla neutralizzazione di ANXA2 con anticorpo specifico (855 geni differenzialmente espressi) e tramite silenziamento (3592 geni differenzialmente espressi), in colture primarie di GBM. L’analisi di gene set enrichment (GSEA) condotta sulle tre signature, ha rivelato un arricchimento negativo di geni legati ai processi di migrazione cellulare e transizione epitelio-mesenchimale. Questi dati hanno fortemente suggerito l’importante ruolo svolto da ANXA2 nel comportamento e nell’aggressività delle cellule di GBM, portandoci pertanto a programmare differenti strategie per modulare le sue funzioni e le vie di segnale intracellulare ad essa correlate. Per questo motivo, è stata condotta una serie di analisi funzionali in vitro in cellule primarie di GBM, dimostrando come ANXA2 sia un principale mediatore dell’aggressività di questo tumore attraverso la regolazione di processi quali motilità cellulare, proliferazione e differenziamento. Inoltre, basandoci sul profilo d’espressione genica di cellule di GBM in cui abbiamo inibito la funzione di ANXA2, abbiamo validato il potenziale prognostico di una signature “ANXA2down” (basata sui geni maggiormente down-regolati in cellule di GBM trattate con anticorpo neutralizzante ANXA2) in diversi dataset pubblici, dimostrando come l’espressione di geni regolati dai livelli di ANXA2 sia in grado di predire l’andamento dei pazienti. Infine, la signature precedentemente generata dai dataset TCGA e GSE13041 è stata mappata funzionalmente utilizzando il tool bioinformatico Connectivity Map con lo scopo di identificare composti in grado di revertire tale signature. I composti identificati sono stati analizzati successivamente per la loro abilità di inibire il processo di invasione in vitro in colture primarie di GBM. Inoltre, le signature ANXA2-dipendenti, ottenute dalle precedenti analisi (cellule inibite/silenziate per ANXA2), sono state applicate al tool QUADrATiC. Ciò ha permesso di approfondire i risultati grazie all’utilizzo di un database più ampio che si basa sullo studio di un numero maggiore di composti approvati in numerose linee cellulari.
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Cole, Clare Louise. "Identification of OATP1B3 as a potential therapeutic target in Recessive Dystrophic Epidermolysis Bullosa Associated Squamous Cell Carcinoma." Thesis, University of Dundee, 2011. https://discovery.dundee.ac.uk/en/studentTheses/20729995-be96-4f29-80b8-53da131c6fd8.

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Epidermolysis Bullosa encompasses a group of inherited heterogeneous diseases involving trauma induced blistering of the skin. Recessive Dystrophic Epidermolysis Bullosa (RDEB) is one of the most debilitating variants of the disease and patients are predisposed to developing aggressive cutaneous Squamous Cell Carcinoma (SCC). Unlike SCC in the general population, the primary cause of RDEB associated SCC is not UV-radiation. SCC in RDEB patients has poor prognosis due to a high frequency of recurrence and metastasis. 70% of all severe generalized RDEB patients die from SCC by the age of 45, compared to only 1.25% of all patients with UV-induced SCC in the general population (Fine et al. 2008), making SCC the leading cause of death in these RDEB patients. The aim of this investigation was to identify therapeutic targets for RDEB associated SCC. Global gene expression studies identified 36 candidate genes which were differentially regulated in RDEB SCC (n=4) compared with non-RDEB SCC (n=5) primary keratinocyte cultures. The validation of these genes by qRT-PCR in replicate cultures of RDEB SCC (n=3), non-RDEB SCC (n=3) keratinocytes and normal human keratinocytes as a control, deduced 5 genes to be significantly differentially regulated. Of particular interest, is the over-expression of SLCO1B3 by 6.25 fold in RDEB SCC keratinocytes (p = 0.035). SLCO1B3 encodes the organic anion transporter OATP1B3, which is normally exclusively expressed on the basolateral membrane of hepatocytes. qRT-PCR revealed the mRNA expression level of SLCO1B3 is reduced in RDEB SCC keratinocyte cultures when COL7A1, the causal gene mutated in RDEB, is re-expressed, suggesting that COL7A1 which encodes the Type VII Collagen protein and is secreted into the extracellular matrix, may suppress the transcription of SLCO1B3. Immunofluorescent staining of RDEB SCC keratinocytes and tissue identified OATP1B3 expression, whilst qRT-PCR using mRNA isolated from freshly frozen skin and SCC tissue samples from both RDEB and non-RDEB individuals identified increased SLCO1B3 mRNA expression in RDEB SCC in vivo. Over expression of SLCO1B3 and increased activity of OATP1B3 is associated with breast, colon and pancreatic cancer and is a known transporter of chemotherapeutic agents, such as Methotrexate and Paclitaxel. These observations have led to speculation that, as a transporter over expressed in cancer and capable of introducing drugs into cells, OATP1B3 represents a potential therapeutic target. Preliminary results from a cell viability assay suggest that exposing RDEB SCC cells to Microcystin-LR specifically reduces cell viability in a SLCO1B3 dependent manner. This supports the conclusion that SLCO1B3 represents a viable RDEB SCC specific therapeutic target and provides a pathway which can be exploited to deliver anti-cancer drugs directly to tumour cells whilst reducing the systemic toxicity of these agents.
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Books on the topic "Therapeutic target identification"

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Hallczuk, Howard. Therapeutic Target Identification : Validation and Drug Discovery for Traumatic Brain Injury: Mild Traumatic Brain Injury. Independently Published, 2021.

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Popescu, Bogdan Florin Gh, Yong Guo, and Claudia Francesca Lucchinetti. Multiple Sclerosis: Pathology. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199937837.003.0081.

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The pathology of MS consists of areas of focal demyelination, known as plaques or lesions, characterized by inflammation, gliosis, and relative axonal preservation. Recent neuropathological studies have established that white matter lesions are heterogenous with respect to the targets of injury and mechanisms of demyelination, highlighting the need for the identification of surrogate clinical and/or paraclinical markers that would correlate with immunopatterns in the general MS population and for the design of novel therapeutic strategies specifically tailored to each immunopattern. Recent neuropathological studies have also shown the cortex is an early target of the MS disease process, and that inflammatory cortical demyelination may be driven by meningeal inflammation.
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Drouin-Ouellet, Janelle, and Roger A. Barker. Disease-Modifying Therapies in Neurodegenerative Disorders. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190233563.003.0016.

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The recent identification of the genetic basis of many neurodegenerative disorders (NDDs), coupled with a greater understanding of their pathophysiology, has enabled better therapeutic strategies to be identified and tried. This includes approaches that target critical specific nodes in the disease pathways, for example, agents that modulate levels of mutant huntingtin in Huntington’s disease. In addition to these highly specific targeted therapies, there is also a growing realization that more generic lifestyle therapies influencing whole brain health may also have merit in treating these conditions-such as diet and exercise. This chapter explores the different approaches and agents used to try to modify the course of a range of NDDs, and highlights their progress relative to the clinic and the patients suffering with these currently incurable conditions.
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Modern CNS Drug Discovery : Novel Therapeutics for Psychiatric and Neurological Diseases: From Target Identification to Regulatory Approval. Springer International Publishing AG, 2024.

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Lazarov, Amit, Adva Segal, and Yair Bar-Haim. Cognitive Training and Technology in the Treatment of Children and Adolescents. Edited by Thomas H. Ollendick, Susan W. White, and Bradley A. White. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190634841.013.47.

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Cognitive training approaches in the treatment of pediatric psychopathology rely on the identification of specific aberrant cognitive processes that could be targeted for rectification via training. Such processes include threat-related attention and interpretation, working memory, and emotion recognition, among others. A selective review is given of mental processes that have been identified as potential targets for psychological treatment and the technologies that could be harnessed for such therapeutic targeting. Implementation of cognitive training procedures in the treatment of children, adolescents, and adults is described, and their clinical efficacy is evaluated. Recent technologies harnessed for the implementation of cognitive training protocols, such as eye-tracking, virtual reality, and neuromodulation, are described and their potential applications in novel therapeutic procedures and in improvement of extant cognitive training protocols are discussed.
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Hwang, Young-Hwan, and York Pei. Autosomal dominant polycystic kidney disease management. Edited by Neil Turner. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0309_update_001.

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Management of patients with autosomal dominant polycystic kidney disease (ADPKD) currently comprises non-specific measures including promotion of healthy lifestyle, optimization of blood pressure control, and modification of cardiovascular risk factors. A high water intake of 3–4 L per day in patients with glomerular filtration rate greater than 30 mL/min/1.73 m2 may decrease the risk of kidney stones, but its potential benefit in reducing renal cyst growth is presently unproven. Maintenance of a target blood pressure of 130/80 mmHg is recommended by expert clinical guidelines though this is unlikely to slow cyst growth. It is unclear whether pharmacological blockade of the renin–angiotensin axis confers an extrarenal protective effect. Recognition of the variable clinical presentations of cyst infection, cyst haemorrhage, or nephrolithiasis is important for early diagnosis and optimal management of these complications. Most patients with ADPKD do well on dialysis and after transplantation. Nephrectomy may be needed to make space for a donor kidney, or if kidney size or infection is an issue after end-stage renal failure is reached. Recent advances in ADPKD have led to the identification of multiple potential therapeutic targets with more than 10 clinical trials completed or currently in progress. Given the promising results of the TEMPO trial, tolvaptan may well be the first disease-modifying drug to be approved for clinical use. Several other classes of drugs (e.g. somatostatin analogues, triptolide, metformin, and glucosylceramide synthase inhibitors) with good long-term safety profiles are promising candidates which may be repurposed for this disease. In the future, identifying patients with different risks of renal disease progression by their genotype and/or kidney volume will likely assume an important role for the clinical management of ADPKD.
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Beyer, Chad E., and Stephen M. Stahl, eds. Next Generation Antidepressants. Cambridge University Press, 2010. http://dx.doi.org/10.1017/9780511778414.

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The World Health Organization defines depression as a primary contributor to the global burden of disease and predicts it will become the second leading cause of death by 2020. The need to develop effective therapies has never been so pressing. Current antidepressant drugs have several limitations. This 2010 book looks at the future of mood-disorder research, covering the identification of new therapeutic targets, establishing new preclinical models, new medicinal chemistry opportunities, and fostering greater understanding of genetic influences. These strategies are likely to help build a better picture of the disease process, and lead to new opportunities for patient stratification and treatment. The ultimate goal for this strand of research is to develop more personalized and effective treatments for this chronic and debilitating condition. This is essential reading for all those involved in psychopharmacologic drug development, and mental health clinicians seeking a preview of discoveries soon to influence their practice.
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Book chapters on the topic "Therapeutic target identification"

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Zhou, Yu, and James D. Marks. "Identification of Target and Function Specific Antibodies for Effective Drug Delivery." In Therapeutic Antibodies, 145–60. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-554-1_7.

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Vinci, Maria, Carol Box, Miriam Zimmermann, and Suzanne A. Eccles. "Tumor Spheroid-Based Migration Assays for Evaluation of Therapeutic Agents." In Target Identification and Validation in Drug Discovery, 253–66. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-311-4_16.

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Cheung, Atwood K., and Feng Cong. "Finding a Needle in a Haystack. Identification of Tankyrase, a Novel Therapeutic Target of the Wnt Pathway Using Chemical Genetics." In Concepts and Case Studies in Chemical Biology, 249–64. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2014. http://dx.doi.org/10.1002/9783527687503.ch17.

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Garg, Aakriti, Ruchika Sharma, Santanu Kaity, and Anoop Kumar. "Identification of Bioactive Lipid Drug Targets by Computational Techniques." In Therapeutic Platform of Bioactive Lipids, 143–62. New York: Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003301608-10.

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Watson, Geoffrey Alan, Kirsty Taylor, and Lillian L. Siu. "Innovation and Advances in Precision Medicine in Head and Neck Cancer." In Critical Issues in Head and Neck Oncology, 355–73. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63234-2_24.

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AbstractThe clinical utility of precision medicine through molecular characterization of tumors has been demonstrated in some malignancies, especially in cases where oncogenic driver alterations are identified. Next generation sequencing data from thousands of patients with head and neck cancers have provided vast amounts of information about the genomic landscape of this disease. Thus far, only a limited number of genomic alterations have been druggable, such as NTRK gene rearrangements in salivary gland cancers (mainly mammary analogue secretory carcinoma), NOTCH mutations in adenoid cystic cancers, HRAS mutations in head and neck squamous cell cancers, and even a smaller number of these have reached regulatory approval status. In order to expand the scope of precision medicine in head and neck cancer, additional evaluation beyond genomics is necessary. For instance, there is increasing interest to perform transcriptomic profiling for target identification. Another advance is in the area of functional testing such as small interfering RNA and drug libraries on patient derived cell cultures. Liquid biopsies to detect specific tumor clones or subclones, or viral sequences such as HPV, are of great interest to enable non-invasive tracking of response or resistance to treatment. In addition, precision immuno-oncology is a tangible goal, with a growing body of knowledge on the interactions between the host immunity, the tumor and its microenvironment. Immuno-oncology combinations that are tailored to immunophenotypes of the host-tumor-microenvironment triad, personalized cancer vaccines, and adoptive cell therapies, among others, are in active development. Many therapeutic possibilities and opportunities lie ahead that ultimately will increase the reality of precision medicine in head and neck cancer.
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Calabretta, Raffaella, and Marcus Hacker. "Cardiotoxicity of Targeted Therapies: Imaging of Heart Does Matter." In Beyond Becquerel and Biology to Precision Radiomolecular Oncology: Festschrift in Honor of Richard P. Baum, 139–45. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-33533-4_12.

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AbstractMolecular targeted therapies are characterized by blocking essential biochemical pathways or mutant proteins that are required for cancer cell growth and survival. Targeted cancer therapeutics are amongst the major treatment options for cancer today. These treatments are more selective for cancer cells and improve the quality of life for cancer patients undergoing therapy. Nevertheless, cardiotoxicity is a frequent side effect in targeted therapies, frequently described as myocardial dysfunction and heart failure. Cardiotoxicity includes also any subsequent functional or structural heart injury, with a possible accelerated development of cardiovascular diseases. Early identification of patients at risk for cardiotoxicity from cancer target therapies and the early diagnosis of CV complications related to cancer treatments are crucial. Anamnesis and risk stratification are the first steps of the diagnostic process to detect myocardial toxicity. Electrocardiography, cardiac biomarkers, and cardiac imaging modalities (echocardiography, CMR, PET, conventional imaging, and cardiac CT) are essential for a cardiotoxicity screening.
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Singh, Ankita, Shafaque Zahra, Simran Arora, Fiza Hamid, and Shailesh Kumar. "In Silico Identification of tRNA Fragments, Novel Candidates for Cancer Biomarkers, and Therapeutic Targets." In Methods in Molecular Biology, 379–92. New York, NY: Springer US, 2024. http://dx.doi.org/10.1007/978-1-0716-3886-6_21.

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Mathie, Alistair, Samuel R. Bourne, Rachel Forfar, Walter E. Perfect, and Emma L. Veale. "The Contribution of Genetic Sequencing Information to the Identification and Functional Characterization of Two-Pore Domain Potassium (K2P) Channels as Viable Therapeutic Targets." In Ion Channels as Targets in Drug Discovery, 199–220. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-52197-3_6.

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Wild, G. E., J. Hasan, M. J. Ropeleski, K. A. Waschke, C. Cossette, L. Dufresne, B. Q. H. Le, and A. B. R. Thomson. "Application of recombinant DNA technology to the identification of novel therapeutic targets in inflammatory bowel disease." In Trends in Inflammatory Bowel Disease Therapy 1999, 234–51. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-011-4002-7_24.

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Aoki, Masahiro, and Makoto Mark Taketo. "Use of Genetically Engineered Mouse Models in Identification and Validation of Therapeutic Targets for Colon Cancer." In Targeting the Wnt Pathway in Cancer, 143–63. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-8023-6_7.

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Conference papers on the topic "Therapeutic target identification"

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Loscalzo, Joseph. "Network Approach to Drug Target Identification and Drug Combinations: Implications for cGMP-based Therapeutics." In cGMP: Generators, Effectors and Therapeutic Implications. ScienceOpen, 2024. http://dx.doi.org/10.14293/cgmp.24000049.v1.

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Enfield, Katey S. S., Erin A. Marshall, Christine Anderson, Kevin W. Ng, Sara Rahmati, Zhaolin Xu, Calum E. MacAulay, et al. "Abstract A26: Identification of a novel therapeutic target in lung adenocarcinoma." In Abstracts: Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; January 8-11, 2018; San Diego, CA. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1557-3265.aacriaslc18-a26.

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Chengzhang, Li, and Xu Jiucheng. "Identification of Potentially Therapeutic Target Genes in Ovarian Cancer via Bioinformatic Approach." In 2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB). IEEE, 2021. http://dx.doi.org/10.1109/icbcb52223.2021.9459203.

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Tomioka, Y., Y. Hagihara, K. Tanigawa, T. Suetsugu, K. Mizuno, N. Seki, and H. Inoue. "Identification of Therapeutic Target Molecules for Lung Adenocarcinoma Based on MicroRNA Analysis." In American Thoracic Society 2024 International Conference, May 17-22, 2024 - San Diego, CA. American Thoracic Society, 2024. http://dx.doi.org/10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a4941.

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T, Suresh, S. Kaliappan, H. Mohammed Ali, and Bura Vijay Kumar. "AI - Driven Drug Discovery and Therapeutic Target Identification for Rare Genetic Diseases." In 2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC). IEEE, 2024. http://dx.doi.org/10.1109/assic60049.2024.10507989.

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Hoppe, Stephanie, Jan Winter, Renata Blatnik, Julia Schessner, Lisa Dressler, Alina Steinbach, Hadeel Khallouf, Martin Wuehl, Alexandra Klevenz, and Angelika B. Riemer. "Abstract B31: Identification of target T cell epitopes for a therapeutic HPV16 vaccine." In Abstracts: AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/2326-6074.tumimm14-b31.

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Greenblatt, Sarah M., Pierre-Jacques J. Hamard, Takashi Asai, Na Man, Concepcion Martinez-Caja, Fan Liu, and Stephen Nimer. "Abstract 3340: Identification of CARM1/PRMT4 as a novel therapeutic target for AML." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-3340.

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Silvestre, David C., Amelie Brisson, Bérengère Marty-Prouvost, David Gentien, Damarys Loew, Florent Dingli, Virginie Maire, et al. "Abstract B164: Identification and validation of PRMT1 as a therapeutic target in breast cancer." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; November 5-9, 2015; Boston, MA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1535-7163.targ-15-b164.

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Wu, Pei-Yu, Tong-You Wade Wei, Ting-Jung Wu, and Ming-Daw Tsai. "Abstract 3123: Identification of TIFA as a novel therapeutic target in acute myeloid leukemia." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-3123.

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Buchner, Maike V., Eugene Park, Lars Klemm, Huimin Geng, Dragana Kopanja, Pradip Raychaudhuri, and Markus Müschen. "Abstract 484: Identification of FOXM1 as therapeutic target in Philadelphia chromosome-positive acute lymphoblastic leukemia." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-484.

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Reports on the topic "Therapeutic target identification"

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Hong, Waun K., and David J. Stewart. PROSPECT (Profiling of Resistance Patterns & Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax and Therapeutic Target Identification). Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada488128.

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Hong, Wuan K. PROSPECT (Profiling of Resistance Patterns & Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax and Therapeutic Target Identification. Fort Belvoir, VA: Defense Technical Information Center, June 2009. http://dx.doi.org/10.21236/ada509995.

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Hong, Wuan K. PROSPECT: Profiling of Resistance Patterns & Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax and Therapeutic Target Identification. Fort Belvoir, VA: Defense Technical Information Center, June 2012. http://dx.doi.org/10.21236/ada581682.

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Allen, J. Rapid Computational Identification of Therapeutic Targets for Pathogens. Office of Scientific and Technical Information (OSTI), March 2023. http://dx.doi.org/10.2172/1961765.

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Shiang, Christine. Identification of Novel Therapeutic Targets for Triple-Negative Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, December 2012. http://dx.doi.org/10.21236/ada571316.

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Jongens, Thomas A. Examination of the mGluR-mTOR Pathway for the Identification of Potential Therapeutic Targets to Treat Fragile X. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada612771.

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Shpigel, Nahum Y., Ynte Schukken, and Ilan Rosenshine. Identification of genes involved in virulence of Escherichia coli mastitis by signature tagged mutagenesis. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7699853.bard.

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Mastitis, an inflammatory response of the mammary tissue to invading pathogenic bacteria, is the largest health problem in the dairy industry and is responsible for multibillion dollar economic losses. E. coli are a leading cause of acute mastitis in dairy animals worldwide and certainly in Israel and North America. The species E. coli comprises a highly heterogeneous group of pathogens, some of which are commensal residents of the gut, infecting the mammary gland after contamination of the teat skin from the environment. As compared to other gut microflora, mammary pathogenic E. coli (MPEC) may have undergone evolutionary adaptations that improve their fitness for colonization of the unique and varied environmental niches found within the mammary gland. These niches include competing microbes already present or accompanying the new colonizer, soluble and cellular antimicrobials in milk, and the innate immune response elicited by mammary cells and recruited immune cells. However, to date, no specific virulence factors have been identified in E. coli isolates associated with mastitis. The original overall research objective of this application was to develop a genome-wide, transposon-tagged mutant collection of MPEC strain P4 and to use this technology to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. In the course of the project we decided to take an alternative genome-wide approach and to use whole genomes bioinformatics analysis. Using genome sequencing and analysis of six MPEC strains, our studies have shown that type VI secretion system (T6SS) gene clusters were present in all these strains. Furthermore, using unbiased screening of MPEC strains for reduced colonization, fitness and virulence in the murine mastitis model, we have identified in MPEC P4-NR a new pathogenicity island (PAI-1) encoding the core components of T6SS and its hallmark effectors Hcp, VgrG and Rhs. Next, we have shown that specific deletions of T6SS genes reduced colonization, fitness and virulence in lactating mouse mammary glands. Our long-term goal is to understand the molecular mechanisms of host-pathogen interactions in the mammary gland and to relate these mechanisms to disease processes and pathogenesis. We have been able to achieve our research objectives to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. The project elucidated a new basic concept in host pathogen interaction of MPEC, which for the best of our knowledge was never described or investigated before. This research will help us to shed new light on principles behind the infection strategy of MPEC. The new targets now enable prevalence and epidemiology studies of T6SS in field strains of MPEC which might unveil new geographic, management and ecological risk factors. These will contribute to development of new approaches to treat and prevent mastitis by MPEC and perhaps other mammary pathogens. The use of antibiotics in farm animals and specifically to treat mastitis is gradually precluded and thus new treatment and prevention strategies are needed. Effective mastitis vaccines are currently not available, structural components and effectors of T6SS might be new targets for the development of novel vaccines and therapeutics.
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8

Matthews, Lisa, Guanming Wu, Robin Haw, Timothy Brunson, Nasim Sanati, Solomon Shorser, Deidre Beavers, Patrick Conley, Lincoln Stein, and Peter D'Eustachio. Illuminating Dark Proteins using Reactome Pathways. Reactome, October 2022. http://dx.doi.org/10.3180/poster/20221027matthews.

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Diseases are often the consequence of proteins or protein complexes that are non-functional or that function improperly. An active area of research has focused on the identification of molecules that can interact with defective proteins and restore their function. While 22% percent of human proteins are estimated to be druggable, less than fifteen percent are targeted by FDA-approved drugs, and the vast majority of untargeted proteins are understudied or so-called "dark" proteins. Elucidation of the function of these dark proteins, particularly those in commonly drug-targeted protein families, may offer therapeutic opportunities for many diseases. Reactome is the most comprehensive, open-access pathway knowledgebase covering 2585 pathways and including 14246 reactions, 11088 proteins, 13984 complexes, and 1093 drugs. Placing dark proteins in the context of Reactome pathways provides a framework of reference for these proteins facilitating the generation of hypotheses for experimental biologists to develop targeted experiments, unravel the potential functions of these proteins, and then design drugs to manipulate them. To this end, we have trained a random forest with 106 protein/gene pairwise features collected from multiple resources to predict functional interactions between dark proteins and proteins annotated in Reactome and then developed three scores to measure the interactions between dark proteins and Reactome pathways based on enrichment analysis and fuzzy logic simulations. Literature evidence via manual checking and systematic NLP-based analysis support predicted interacting pathways for dark proteins. To visualize dark proteins in the context of Reactome pathways, we have also developed a new website, idg.reactome.org, by extending the Reactome web application with new features illustrating these proteins together with tissue-specific protein and gene expression levels and drug interactions.
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