cimb-logo

Journal Browser

Journal Browser

Gene Expression and Regulation in Cancer

A special issue of Current Issues in Molecular Biology (ISSN 1467-3045). This special issue belongs to the section "Molecular Medicine".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1136

Special Issue Editor


E-Mail Website
Guest Editor
Department of Medical Genetics, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Medykow 18 Street, 40-752 Katowice, Poland
Interests: molecular mechanisms; cell therapy; mesenchymal stem cells; tissue regeneration; drug delivery; epithelial-to-mesenchymal transition; microRNA; molecular cancer biology; metastasis; personalized medicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Gene expression programs shape virtually every hallmark of cancer, influencing tumor initiation, progression, therapeutic resistance, and metastatic behavior. This Special Issue will highlight recent advances in understanding how transcriptional, epigenetic, and post-transcriptional mechanisms drive oncogenic phenotypes across tumor types. We welcome studies on regulatory networks controlling EMT, stemness, tumor microenvironment interactions, non-coding RNAs, splicing factors, isoform switching, and emerging therapeutic strategies targeting gene regulation. This Special Issue will provide an integrative view of how dysregulated gene expression can be leveraged for improved diagnostics and treatment in cancer.

Best regards,

Dr. Karolina Bajdak-Rusinek
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. Current Issues in Molecular Biology 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 2200 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 gene expression
  • oncogenic regulatory mechanisms
  • gene regulation targeted therapy
  • tumor phenotypes
  • cancer diagnostics and treatment

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 1619 KB  
Article
Ensemble Machine Learning on Bulk RNA-Seq Identifies 17-Gene Signature Predicting Neoadjuvant Chemotherapy Response in Breast Cancer
by Stelios Lamprou, Styliana Georgiou, Triantafyllos Stylianopoulos and Chrysovalantis Voutouri
Curr. Issues Mol. Biol. 2026, 48(1), 94; https://doi.org/10.3390/cimb48010094 - 16 Jan 2026
Cited by 1 | Viewed by 875
Abstract
Predicting neoadjuvant chemotherapy response in breast cancer remains critical for optimizing treatment strategies, yet robust predictive biomarkers are lacking. This study implemented an ensemble machine learning approach to identify a gene expression signature predicting pathological complete response (pCR) versus residual disease (RD) using [...] Read more.
Predicting neoadjuvant chemotherapy response in breast cancer remains critical for optimizing treatment strategies, yet robust predictive biomarkers are lacking. This study implemented an ensemble machine learning approach to identify a gene expression signature predicting pathological complete response (pCR) versus residual disease (RD) using bulk RNA-sequencing data from GSE163882 (138 RD, 80 pCR). We employed TMM normalization with differential expression analysis (250 genes, FDR < 0.05, |log2FC| ≥ 1), ensemble feature selection across five classifiers (Random Forest, Gradient Boosting, SVM, k-NN, and Neural Network) with 10-fold repeated cross-validation, and stacked ensemble development. Consensus selection identified a 17-gene signature consistently ranked across algorithms. The stacked ensemble achieved 0.97 AUC post-testing on hold-out test data. External validation on the independent GSE240671 cohort (37 pCR, 25 RD) following ComBat batch correction achieved ROC AUC of 0.78 and PR AUC of 0.85 with isotonic calibration, demonstrating balanced accuracy of 0.71 and 0.86 sensitivity for pCR detection. Pathway enrichment revealed associations with cell cycle regulation (E2F3, MKI67), DNA repair (BRCA2), and transcriptional control (MED1), with six priority genes (MED1, BRCA2, E2F3, PITPNB, H1-1, and FARP2) showing established breast cancer relevance. This externally validated 17-gene signature provides a biologically grounded tool for NAC response prediction in precision oncology. Full article
(This article belongs to the Special Issue Gene Expression and Regulation in Cancer)
Show Figures

Figure 1

Back to TopTop