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Molecular Signatures of Therapy: Biomarkers Predicting Response and Relapse in Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 2319

Special Issue Editor

Dr. Antonis Giakountis

E-Mail Website
Guest Editor
Department of Biochemistry & Biotechnology, School of Health Sciences, University of Thessaly, 41335 Larissa, Greece
Interests: lncRNA-mediated transcriptional regulation; RNA–chromatin interactions; chromatin architecture; transcriptional and epigenetic regulation in cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue of Cancers, dedicated to advancing our understanding of how molecular biomarkers can anticipate therapeutic outcomes and forewarn disease relapse. Precision oncology increasingly depends on refined biomarkers that not only stratify patients before treatment, but also monitor residual disease, early recurrence, and evolving resistance.

This Special Issue invites original research articles and reviews that focus on:

  • Predictive biomarkers: molecular signatures (genomic, transcriptomic, proteomic, epigenetic) that indicate the likelihood of response to targeted therapies, immunotherapies, or conventional modalities.
  • Therapy-induced dynamics: changes in biomarker profiles during treatment (for example, via liquid biopsy, circulating tumour DNA, exosomes, immune signatures) that reflect early response, emerging resistance, or minimal residual disease.
  • Mechanisms of relapse: molecular and cellular drivers of disease recurrence, including persistence of residual clones, tumour evolution under treatment pressure, microenvironmental adaptations, and immune escape.
  • Strategies for relapse-prediction and monitoring: assays and models for timely detection of recurrence (biomarker-based surveillance, imaging-biomarker integration, multi-omics longitudinal profiling) and their translation into clinical protocols.
  • Translational and clinical implementation: biomarker-guided clinical trials, companion diagnostics, integration of biomarkers into therapeutic decision-making and relapse prevention frameworks, and real-world evidence supporting biomarker utility.

We welcome contributions across all cancer types and therapeutic modalities and particularly encourage multi-disciplinary studies that bridge molecular discovery with clinical application. All submitted manuscripts will undergo rigorous peer review to ensure the highest scientific quality and relevance to the field.

Join us in building a timely and impactful collection that brings together biomarker science with actionable clinical insight—helping to bring the next generation of precision therapy and relapse-prevention strategies into practice.

Dr. Antonis Giakountis
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 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. Cancers is an international peer-reviewed open access semimonthly 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 2900 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

  • molecular biomarkers
  • therapeutic response
  • disease relapse
  • precision oncology
  • liquid biopsy
  • predictive biomarkers
  • multi-omics integration
  • minimal residual disease
  • translational oncology

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

Published Papers (2 papers)

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Research

27 pages, 5804 KB  
Article
Disparities in Tumor Microenvironment Between Primary and Metastatic Colorectal Cancer: Impact on Immune Infiltration and Survival
by Ewelina Dziąg-Dudek, Aleksandra Semeniuk-Wojtaś, Magdalena Modzelewska, Arkadiusz Lubas, Letycja Róg, Barbara Górnicka and Rafał Stec
Cancers 2026, 18(4), 566; https://doi.org/10.3390/cancers18040566 - 9 Feb 2026
Viewed by 735
Abstract
Background/Objectives: In recent years, growing evidence that the tumor microenvironment (TME) plays crucial roles in the progression and treatment responses of various cancers has emerged. Unfortunately, we still do not fully understand the mechanisms through which the TME influences cancer development. Therefore, the [...] Read more.
Background/Objectives: In recent years, growing evidence that the tumor microenvironment (TME) plays crucial roles in the progression and treatment responses of various cancers has emerged. Unfortunately, we still do not fully understand the mechanisms through which the TME influences cancer development. Therefore, the aim of this study is to assess the impact of the TME on the clinical course of the disease, comparing primary and metastatic tumors. Materials and Methods: This retrospective study included 30 colorectal cancer patients for which tissue samples from primary and metastatic tumors were available for immunohistochemistry. A multiple Cox proportional hazards regression analysis was performed to characterize differences between the microenvironments of primary and metastatic tumors, as well as between lesions diagnosed at different times after resection. Results: Immune cell infiltration was higher in metastatic than primary tumors. Statistically significant differences were observed only in the central part of the tumor, while cell infiltration at the periphery had no prognostic significance. In the multivariate analysis, a positive correlation was revealed between the expression of Programmed Death-Ligand 1 (PD-L1) on primary tumor cells (TCs) and survival (HR: 5.43; 95% CI: 1.89–15.61; p = 0.0017). Conclusions: Primary and metastatic tumors differ regarding their tumor microenvironment. As such, the tumor immune status should be considered as a key factor when selecting a therapeutic strategy, as well as for post-treatment surveillance. Full article
(This article belongs to the Special Issue Molecular Signatures of Therapy: Biomarkers Predicting Response and Relapse in Cancer)
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17 pages, 1996 KB  
Article
AdhesionScore: A Prognostic Predictor of Breast Cancer Patients Based on a Cell Adhesion-Associated Gene Signature
by Catarina Esquível, Rogério Ribeiro, Ana Sofia Ribeiro, Pedro G. Ferreira and Joana Paredes
Cancers 2025, 17(23), 3731; https://doi.org/10.3390/cancers17233731 - 21 Nov 2025
Cited by 1 | Viewed by 1120
Abstract
Background: Aberrant or loss of cell adhesion drives invasion and metastasis, key hallmarks of cancer progression. In this work, we hypothesized that a gene signature related to cell adhesion could predict breast cancer prognosis. Methods: Highly variant genes were tested for association with [...] Read more.
Background: Aberrant or loss of cell adhesion drives invasion and metastasis, key hallmarks of cancer progression. In this work, we hypothesized that a gene signature related to cell adhesion could predict breast cancer prognosis. Methods: Highly variant genes were tested for association with overall survival using Cox regression. Adhesion-related genes were identified through gene ontology analysis and multivariate Cox regression, with AIC selection, defined the prognostic signature. The AdhesionScore was then calculated as a weighted sum of gene expression, with risk stratification assessed by Kaplan–Meier and log-rank tests. Results: We found that the AdhesionScore was a significant independent predictor of poor survival in three large independent datasets, as it provided a robust stratification of patient prognosis in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (HR: 2.65; 95% CI: 2.33–3.0, p = 2.34 × 10−51), The Cancer Genome Atlas (TCGA) (HR: 3.46; 95% CI: 2.35–5.09, p = 3.50 × 10−10), and the GSE96058 (HR: 2.83; 95% CI: 2.20–3.65, p = 6.29 × 10−16) datasets. The 5-year risk of death in the high-risk group was 32.41% for METABRIC, 27.8% for TCGA, and 17.54% for GSE96058 datasets. Consistently, HER2-enriched and triple-negative breast carcinomas (TNBC) cases showed higher AdhesionScores than luminal subtypes, indicating an association with aggressive tumor biology. Conclusions: We have developed, for the first time, a molecular signature based on cell adhesion, as well as an associated AdhesionScore that can predict patient prognosis in invasive breast cancer, with potential clinical application. We developed a novel adhesion-based molecular signature, the AdhesionScore, that robustly predicts prognosis in breast cancer across independent cohorts, highlighting its potential clinical utility for patient risk stratification. Full article
(This article belongs to the Special Issue Molecular Signatures of Therapy: Biomarkers Predicting Response and Relapse in Cancer)
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