Epigenetics-targeted drugs: current paradigms and future challenges

Signal Transduction and Targeted Therapy, Journal Year: 2024, Volume and Issue: 9(1)

Published: Nov. 26, 2024

Epigenetics governs a chromatin state regulatory system through five key mechanisms: DNA modification, histone RNA remodeling, and non-coding regulation. These mechanisms their associated enzymes convey genetic information independently of base sequences, playing essential roles in organismal development homeostasis. Conversely, disruptions epigenetic landscapes critically influence the pathogenesis various human diseases. This understanding has laid robust theoretical groundwork for developing drugs that target epigenetics-modifying pathological conditions. Over past two decades, growing array small molecule targeting such as methyltransferase, deacetylase, isocitrate dehydrogenase, enhancer zeste homolog 2, have been thoroughly investigated implemented therapeutic options, particularly oncology. Additionally, numerous epigenetics-targeted are undergoing clinical trials, offering promising prospects benefits. review delineates epigenetics physiological contexts underscores pioneering studies on discovery implementation drugs. include inhibitors, agonists, degraders, multitarget agents, aiming to identify practical challenges avenues future research. Ultimately, this aims deepen epigenetics-oriented strategies further application settings.

Language: Английский

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Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 21, 2024

The druggable proteome refers to proteins that can bind small molecules with appropriate chemical affinity, inducing a favorable clinical response. Predicting through screening and in silico modeling is imperative for drug design. To contribute this field, we developed an accurate predictive classifier cancer-driving using amino acid composition descriptors of protein sequences 13 machine learning linear non-linear classifiers. optimal was achieved the support vector method, utilizing 200 tri-amino descriptors. high performance model evident from area under receiver operating characteristics (AUROC) 0.975 ± 0.003 accuracy 0.929 0.006 (threefold cross-validation). prediction enhanced multi-omics approaches, including target-disease evidence score, shortest pathways cancer hallmarks, structure-based ligandability assessment, unfavorable prognostic analysis, oncogenic variome. Additionally, performed repurposing analysis identify drugs highest affinity capable targeting best predicted proteins. As result, identified 79 key ligandability, 23 them demonstrated significance across 16 TCGA PanCancer types: CDKN2A, BCL10, ACVR1, CASP8, JAG1, TSC1, NBN, PREX2, PPP2R1A, DNM2, VAV1, ASXL1, TPR, HRAS, BUB1B, ATG7, MARK3, SETD2, CCNE1, MUTYH, CDKN2C, RB1, SMARCA4. Moreover, prioritized 11 clinically relevant these This strategy effectively predicts prioritizes biomarkers, therapeutic targets, in-depth studies trials. Scripts are available at https://github.com/muntisa/machine-learning-for-druggable-proteins .

Language: Английский

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Epigenomic Echoes—Decoding Genomic and Epigenetic Instability to Distinguish Lung Cancer Types and Predict Relapse

Epigenomes, Journal Year: 2025, Volume and Issue: 9(1), P. 5 - 5

Published: Feb. 5, 2025

Genomic and epigenomic instability are defining features of cancer, driving tumor progression, heterogeneity, therapeutic resistance. Central to this process epigenetic echoes, persistent dynamic modifications in DNA methylation, histone modifications, non-coding RNA regulation, chromatin remodeling that mirror underlying genomic chaos actively influence cancer cell behavior. This review delves into the complex relationship between these illustrating how they collectively shape genome, affect repair mechanisms, contribute evolution. However, dynamic, context-dependent nature changes presents scientific ethical challenges, particularly concerning privacy clinical applicability. Focusing on lung we examine specific patterns function as biomarkers for distinguishing subtypes monitoring disease progression relapse.

Language: Английский

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Global analysis of actionable genomic alterations in thyroid cancer and precision-based pharmacogenomic strategies

Frontiers in Pharmacology, Journal Year: 2025, Volume and Issue: 16

Published: April 14, 2025

Introduction Thyroid cancer, a prevalent endocrine malignancy, has an age-standardized incidence rate of 9.1 per 100,000 people and mortality 0.44 as 2024. Despite significant advances in precision oncology driven by large-scale international consortia, gaps persist understanding the genomic landscape thyroid cancer its impact on therapeutic efficacy across diverse populations. Methods To address this gap, we performed comprehensive data mining silico analyses to identify pathogenic variants driver genes, calculate allele frequencies, assess deleteriousness scores global populations, including African, Amish, Ashkenazi Jewish, East South Asian, Finnish non-Finnish European, Latino, Middle Eastern groups. Additionally, pharmacogenomic profiling, drug prescription, clinical trial were analyzed prioritize targeted strategies. Results Our analysis examined 56,622 40 cancer-driver genes 76,156 human genomes, identifying 5,001 known predicted oncogenic variants. Enrichment revealed critical pathways such MAPK, PI3K-AKT-mTOR, p53 signaling, underscoring their roles pathogenesis. High-throughput validation strategies confirmed actionable alterations RET, BRAF, NRAS, KRAS, EPHA7. Ligandability assessments identified these proteins promising targets. Furthermore, our findings highlight potential inhibitors, vandetanib, dabrafenib, selumetinib, for improving treatment outcomes. Discussion This study underscores significance integrating insights with disparities treatment. The identification population-specific targets provides foundation advancing oncology. Future efforts should focus underrepresented developing prevention strategies, fostering collaboration ensure equitable access testing innovative therapies. These initiatives have transform care align broader goals personalized medicine.

Language: Английский

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The Future of Pharmacogenomics: Integrating Epigenetics, Nutrigenomics, and Beyond

Journal of Personalized Medicine, Journal Year: 2024, Volume and Issue: 14(12), P. 1121 - 1121

Published: Nov. 27, 2024

Pharmacogenomics (PGx) has revolutionized personalized medicine by empowering the tailoring of drug treatments based on individual genetic profiles. However, complexity response mechanisms necessitates integration additional biological and environmental factors. This article explores integrating epigenetics, nutrigenomics, microbiomes, protein interactions, exosomes, metabolomics with PGx to enhance medicine. In addition discussing these scientific advancements, we examine regulatory ethical challenges translating multi-omics into clinical practice, including considerations data privacy, oversight, equitable access. By framing factors within context Medication Adherence, Appropriateness, Adverse Events (MA3), aim refine therapeutic strategies, improve efficacy, minimize adverse effects, goal improving approach potential benefit patients, healthcare providers, payers, system as a whole enabling more precise effective treatments.

Language: Английский

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Editorial: Cancer genetics and epigenetics: theranostic targets and mechanisms

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: July 26, 2024

Keywords: cancers, epigenetics, genetics, cancer theranostics, mechanisms, tumor biomarkers, mutations

Language: Английский

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Worldwide analysis of actionable genomic alterations in lung cancer and targeted pharmacogenomic strategies

Heliyon, Journal Year: 2024, Volume and Issue: 10(17), P. e37488 - e37488

Published: Sept. 1, 2024

Language: Английский

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