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Genetic and Epigenetic Analyses in Cancer
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Genetic and Epigenetic Analyses in Cancer

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 957

Special Issue Editor

Prof. Dr. Jing Gong

E-Mail Website
Guest Editor
College of Informatics, Huazhong Agricultural University, Wuhan, China
Interests: genetics and bioinformatics; multiomics data analysis; biological artificial intelligence

Special Issue Information

Dear Colleagues,

Cancer, as a complex and multifactorial disease, involves profound alterations at both the genetic and epigenetic levels in its pathogenesis. The genetic foundation of cancer encompasses processes such as gene mutations, gene recombination, chromosomal instability, and genetic susceptibility. These genetic alterations can affect critical cellular processes, including proliferation, apoptosis, differentiation, and metabolism, thereby driving cancer progression. Epigenetic mechanisms, including DNA methylation, histone modifications, and non-coding RNA regulation, provide new insights into the onset and development of complex diseases. Both genetic and epigenetic changes play essential roles in the initiation, progression, and drug resistance of cancer, collectively influencing the disease course. Investigating the roles of these alterations in cancer can enhance our understanding of its complexity and pave the way for more effective therapeutic strategies.

We invite the submission of original research articles, reviews, and opinion pieces on the latest discoveries, theoretical advances, or clinical applications in cancer genetics and epigenetics for this Special Issue. We also seek to explore the interplay between genetic and epigenetic mechanisms in cancer. In particular, we encourage studies that integrate multi-omics approaches, such as combining genetic data with epigenomic, transcriptomic, and proteomic profiles. Our goal is to highlight how genetic and epigenetic analyses can unlock novel cancer biomarkers and therapeutic opportunities.

Prof. Dr. Jing Gong
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • epigenetics
  • genetic mutations
  • chromosomal instability
  • DNA methylation
  • histone modifications
  • non-coding rnas
  • multi-omics
  • transcriptomics
  • proteomics
  • drug resistance in cancer
  • cancer biomarkers
  • therapeutic targets in cancer

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Published Papers (2 papers)

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19 pages, 2974 KiB  
Article
Epigenetic Inactivation of RIPK3-Dependent Necroptosis Augments Cisplatin Chemoresistance in Human Osteosarcoma
by Aditya Sharma, Daniel Pettee, Christine Mella, Catherine Hord, Maximilian Brockwell, Samantha Hardy, Hope C. Ball, Fayez F. Safadi and Steven J. Kuerbitz
Int. J. Mol. Sci. 2025, 26(8), 3863; https://doi.org/10.3390/ijms26083863 - 18 Apr 2025
Viewed by 246
Abstract
Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents. Unfortunately, drug resistance limits the efficacy of chemotherapeutic treatment and compromises therapeutic outcomes in a substantial proportion of cases. Aberrant CpG island methylation-associated transcriptional silencing contributes to chemoresistance in pediatric [...] Read more.
Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents. Unfortunately, drug resistance limits the efficacy of chemotherapeutic treatment and compromises therapeutic outcomes in a substantial proportion of cases. Aberrant CpG island methylation-associated transcriptional silencing contributes to chemoresistance in pediatric solid tumors. Here, using whole-genome DNA methylation screening on 16 human primary OS specimens, we identify receptor interacting protein kinase-3 (RIPK3), a molecular regulator of the necroptosis programmed cell death pathway, as a gene target of aberrant CpG methylation and demonstrate its role in human OS chemoresistance. We validated these findings via enforced expression and DsiRNA silencing, and evaluated the role of RIPK3 in cisplatin chemosensitivity and necroptosis activation through MLKL phosphorylation. We found that CpG island methylation results in RIPK3 silencing in primary human OS samples and cell lines. Enforced RIPK3 expression significantly enhanced cisplatin cytotoxicity in OS cells and DsiRNA knockdown reversed the cisplatin-sensitive phenotype. In cells with enforced RIPK3 expression, cisplatin treatment significantly increased phosphorylation of both RIPK3 and its target, MLKL, indicative of induction of necroptosis. Here, we identify RIPK3 as an important mediator of chemoresistance in OS and a potential pharmacologic target to improve chemotherapy efficacy in drug-resistant tumors. Full article
(This article belongs to the Special Issue Genetic and Epigenetic Analyses in Cancer)
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12 pages, 2075 KiB  
Article
SurvDB: Systematic Identification of Potential Prognostic Biomarkers in 33 Cancer Types
by Zejun Wu, Congcong Min, Wen Cao, Feiyang Xue, Xiaohong Wu, Yanbo Yang, Jianye Yang, Xiaohui Niu and Jing Gong
Int. J. Mol. Sci. 2025, 26(6), 2806; https://doi.org/10.3390/ijms26062806 - 20 Mar 2025
Viewed by 411
Abstract
The identification of cancer prognostic biomarkers is crucial for predicting disease progression, optimizing personalized therapies, and improving patient survival. Molecular biomarkers are increasingly being identified for cancer prognosis estimation. However, existing studies and databases often focus on single-type molecular biomarkers, deficient in comprehensive [...] Read more.
The identification of cancer prognostic biomarkers is crucial for predicting disease progression, optimizing personalized therapies, and improving patient survival. Molecular biomarkers are increasingly being identified for cancer prognosis estimation. However, existing studies and databases often focus on single-type molecular biomarkers, deficient in comprehensive multi-omics data integration, which constrains the comprehensive exploration of biomarkers and underlying mechanisms. To fill this gap, we conducted a systematic prognostic analysis using over 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Our study integrated nine types of molecular biomarker-related data: single-nucleotide polymorphism (SNP), copy number variation (CNV), alternative splicing (AS), alternative polyadenylation (APA), coding gene expression, DNA methylation, lncRNA expression, miRNA expression, and protein expression. Using log-rank tests, univariate Cox regression (uni-Cox), and multivariate Cox regression (multi-Cox), we evaluated potential biomarkers associated with four clinical outcome endpoints: overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI). As a result, we identified 4,498,523 molecular biomarkers significantly associated with cancer prognosis. Finally, we developed SurvDB, an interactive online database for data retrieval, visualization, and download, providing a comprehensive resource for biomarker discovery and precision oncology research. Full article
(This article belongs to the Special Issue Genetic and Epigenetic Analyses in Cancer)
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