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Genetic Biomarkers in Cancer: From Discovery to Clinical Application
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Genetic Biomarkers in Cancer: From Discovery to Clinical Application

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".

Deadline for manuscript submissions: 5 June 2026 | Viewed by 1408

Special Issue Editor

Dr. Evangelos Koustas

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Guest Editor
Oncology Department, General Hospital Evangelismos, Ipsilantou 45-47, 106 76 Athens, Greece
Interests: cancer; tumor biology; biomarkers; cancer therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Genetic biomarkers play a pivotal role in the advancement of precision oncology, enabling early cancer detection, prognosis, and personalized treatment strategies. This review explores the journey of genetic biomarker development, from initial discovery through genomic and transcriptomic profiling to their validation and integration into clinical practice. Key technologies such as next-generation sequencing and bioinformatics tools have accelerated biomarker identification, revealing critical mutations, gene expression patterns, and epigenetic alterations linked to tumorigenesis. Despite significant progress, challenges persist in translating biomarkers from bench to bedside, including issues of reproducibility, cost, and regulatory approval. Notable successes, such as BRCA1/2 in breast cancer and EGFR mutations in non-small-cell lung cancer, highlight the transformative potential of genetic biomarkers in guiding targeted therapies and improving patient outcomes. Continued interdisciplinary collaboration and innovation are essential for expanding the clinical utility of genetic biomarkers across diverse cancer types.

Dr. Evangelos Koustas
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 250 words) can be sent to the Editorial Office for assessment.

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. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). 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

  • cancer
  • tumor biology
  • biomarkers
  • cancer therapy
  • targeted therapy

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Published Papers (1 paper)

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Research

34 pages, 2111 KB  
Article
In Silico Characterization of Pathogenic ESR2 Coding and UTR Variants as Oncogenic Potential Biomarkers in Hormone-Dependent Cancers
by Hakeemah Al-Nakhle, Zainab Almoerifi, Layan Alharbi, Mashael Alayoubi and Rawan Alharbi
Genes 2025, 16(10), 1144; https://doi.org/10.3390/genes16101144 - 26 Sep 2025
Viewed by 868
Abstract
Background: The ESR2 gene encodes Estrogen Receptor-β1 (ERβ1), a putative tumor suppressor in hormone-dependent malignancies. Although ERβ biology has been studied extensively at the expression level, the functional impact of nonsynonymous SNPs (nsSNPs) and untranslated-region (UTR) variants in ESR2 remains underexplored. Methods [...] Read more.
Background: The ESR2 gene encodes Estrogen Receptor-β1 (ERβ1), a putative tumor suppressor in hormone-dependent malignancies. Although ERβ biology has been studied extensively at the expression level, the functional impact of nonsynonymous SNPs (nsSNPs) and untranslated-region (UTR) variants in ESR2 remains underexplored. Methods: We retrieved variants from Ensembl and performed an integrative in silico assessment using PredictSNP, I-Mutant, MUpro, HOPE, MutPred2, and CScape for pathogenicity, oncogenicity and structural stability; STRING/KEGG/GO for pathway context; RegulomeDB and polymiRTS for regulatory effects; and cBioPortal for pan-cancer clinical outcomes (breast (BRCA), endometrial (UCEC), and ovarian (OV)). We evaluated effects of nsSNPs on ERβ1 stability, ligand-binding/DNA-binding domains, co-factor recruitment, and post-transcriptional regulation. Results: Across tools, 93 missense nsSNPs were consistently predicted to be deleterious. Notably, several variants were found to destabilize ERβ1, particularly within the ligand-binding domains (LBD) and DNA-binding domains (DBD). Putative oncogenic drivers R198P and D154N showed high CScape scores and very low population frequencies, consistent with pathogenicity. Several substitutions were predicted to impair coactivator binding and disrupt interactions with key transcriptional partners, including JUN, NCOA1, and SP1. At the post-transcriptional level, rs139004885 was predicted to disrupt miRNA binding, while 3′UTR rs4986938 showed strong regulatory potential and comparatively high population frequency; by contrast, most other identified SNPs were rare. Clinically, pan-cancer survival analyses indicated worse overall survival (OS) in BRCA for ESR2-Altered cases (HR ≈ 2.25; q < 0.001), but better OS in UCEC (HR ≈ 0.24; q ≈ 0.014) and OV (HR ≈ 0.29; q < 0.001), highlighting a tumor-type-specific association. Conclusions: This integrative analysis prioritizes high-impact ESR2 variants that likely impair ERβ1 structure and shows context-dependent clinical effects. Despite their generally low frequency (except for rs4986938), prospective validation linking variant class to ERβ expression and survival outcomes is needed to support biomarker development and therapeutic applications. Full article
(This article belongs to the Special Issue Genetic Biomarkers in Cancer: From Discovery to Clinical Application)
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