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Cancers
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Cancer Epigenetic Biomarkers: 2nd Edition
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Cancer Epigenetic Biomarkers: 2nd Edition

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

Deadline for manuscript submissions: 22 October 2025 | Viewed by 825

Special Issue Editor

Prof. Dr. Fabio Coppedè

E-Mail Website
Guest Editor
Department of Translational Research and of New Surgical and Medical Technologies, University of Pisa, 56126 Pisa, Italy
Interests: cancer genetics; cancer epigenetics; DNA methylation; cancer biomarkers; pharmacoepigenetics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the second edition of “Cancer Epigenetic Biomarkers”, available at https://www.mdpi.com/journal/cancers/special_issues/CEB.

Cancer represents one of the most threatening human diseases, with millions of diagnosed novel cases and deaths occurring worldwide every year. The global aging of the population and the increased exposure to environmental carcinogens, coupled with the adoption of lifestyle behaviors, such as smoking, poor diets, and scarce physical activity, account for the majority of cancers in both developed and less-developed countries.

It is also well ascertained that genetic, epigenetic, and cytogenetic modifications occur within cancer cells and tissue, many of which are driven by environmental exposures and are responsible for the acquisition of the malignant phenotype. Particularly, it is now clear that hundreds of genes change their expression in the multistep process of carcinogenesis as a consequence of epigenetic events, including promoter hypermethylation, histone tail modifications, chromatin remodeling, or interference mechanisms mediated by non-coding RNA molecules.

Some of these epigenetic marks are gathering increasing interest in the clinical setting as valid diagnostic or prognostic biomarkers of the disease, as well as response predictors to therapy. This Special Issue will focus on the most recent advances in cancer epigenetics, as well as on the discovery and utility of cancer epigenetic biomarkers.

Prof. Dr. Fabio Coppedè
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 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. 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

  • cancer
  • biomarker
  • epigenetics
  • DNA methylation
  • miRNA
  • diagnostic biomarkers
  • pharmacoepigenetics
  • epigenetic drugs

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Published Papers (1 paper)

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Research

17 pages, 1077 KiB  
Article
Accurate Diagnosis of High-Risk Pulmonary Nodules Using a Non-Invasive Epigenetic Biomarker Test
by Pei-Hsing Chen, Tung-Ming Tsai, Tzu-Pin Lu, Hsiao-Hung Lu, Dorian Pamart, Aristotelis Kotronoulas, Marielle Herzog, Jacob Vincent Micallef, Hsao-Hsun Hsu and Jin-Shing Chen
Cancers 2025, 17(6), 916; https://doi.org/10.3390/cancers17060916 - 7 Mar 2025
Viewed by 658
Abstract
Background/Objectives: Accurate non-invasive tests to improve early detection and diagnosis of lung cancer are urgently needed. However, no regulatory-approved blood tests are available for this purpose. We aimed to improve pulmonary nodule classification to identify malignant nodules in a high-prevalence patient group. Methods: [...] Read more.
Background/Objectives: Accurate non-invasive tests to improve early detection and diagnosis of lung cancer are urgently needed. However, no regulatory-approved blood tests are available for this purpose. We aimed to improve pulmonary nodule classification to identify malignant nodules in a high-prevalence patient group. Methods: This study involved 806 participants with undiagnosed nodules larger than 5 mm, focusing on assessing nucleosome levels and histone modifications (H3.1 and H3K27Me3) in circulating blood. Nodules were classified as malignant or benign. For model development, the data were randomly divided into training (n = 483) and validation (n = 121) datasets. The model’s performance was then evaluated using a separate testing dataset (n = 202). Results: Among the patients, 755 (93.7%) had a tissue diagnosis. The overall malignancy rate was 80.4%. For all datasets, the areas under curves were as follows: training, 0.74; validation, 0.86; and test, 0.79 (accuracy range: 0.80–0.88). Sensitivity showed consistent results across all datasets (0.91, 0.95, and 0.93, respectively), whereas specificity ranged from 0.37 to 0.64. For smaller nodules (5–10 mm), the model recorded accuracy values of 0.76, 0.88, and 0.85. The sensitivity values of 0.91, 1.00, and 0.94 further highlight the robust diagnostic capability of the model. The performance of the model across the reporting and data system (RADS) categories demonstrated consistent accuracy. Conclusions: Our epigenetic biomarker panel detected non-small-cell lung cancer early in a high-risk patient group with high sensitivity and accuracy. The epigenetic biomarker model was particularly effective in identifying high-risk lung nodules, including small, part-solid, and non-solid nodules, and provided further evidence for validation. Full article
(This article belongs to the Special Issue Cancer Epigenetic Biomarkers: 2nd Edition)
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