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Cancers
Special Issues
Breast Cancer Biomarkers and Clinical Translation: 2nd Edition
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Breast Cancer Biomarkers and Clinical Translation: 2nd Edition

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

Deadline for manuscript submissions: 30 August 2025 | Viewed by 461

Special Issue Editors

Dr. Cristian Scatena

E-Mail Website
Guest Editor
1. Division of Pathology, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
2. Department of Laboratory Medicine, Pisa University Hospital, 56126 Pisa, Italy
Interests: pathology; tumour microenvironment; molecular genetics; breast cancer
Special Issues, Collections and Topics in MDPI journals
Dr. Carmine De Angelis

E-Mail Website
Guest Editor
Medical Oncology, Department of Clinical Medicine and Surgery, University Federico II, 80131 Naples, Italy
Interests: breast cancer; resistance; targeted therapy; biomarkers
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a continuation of our previous Special Issue titled “Breast Cancer Biomarkers and Clinical Translation” (https://www.mdpi.com/journal/cancers/special_issues/2A01G15270).

Breast cancer represents the second most common cancer in women, with its high mortality rate causing millions of cancer-related deaths annually. Thus, discovering and optimizing biomarkers that can improve breast cancer diagnosis, prognosis and therapeutic outcomes are needed. Diagnostic biomarkers are required for accurate diagnosis or to improve breast cancer risk prediction, including factors that integrate radiologic imaging and molecular pathology. Prognostic biomarkers provide information regarding the risk of recurrence and survival. Predictive biomarkers are tools for selecting patients who may benefit from specific therapy regimens. Translational research builds the bridge between discovering biomarkers in preclinical studies and testing their application in the clinical setting.

This Special Issue on “Breast Cancer Biomarkers and Clinical Translation: 2nd Edition” will provide a portrait of the current knowledge on novel biomarkers at the genomic, transcriptomic, proteomic, and immunologic levels and therapeutic strategies, together with advanced experimental approaches, in the management of breast cancer patients, thanks to a collection of high-level manuscripts in this field of research. Authors are welcome to submit original research articles, short communications of preliminary, but significant, experimental results and review articles (either systematic or comprehensive).

Dr. Cristian Scatena
Dr. Carmine De Angelis
Guest Editors

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

  • breast cancer diagnosis
  • cancer risk
  • cell reprogramming
  • biomarkers
  • resistance
  • precision therapy

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

Published Papers (1 paper)

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Research

17 pages, 1251 KiB  
Article
Skeletal Muscle Density as a Predictive Marker for Pathologic Complete Response in Triple-Negative Breast Cancer Treated with Neoadjuvant Chemoimmunotherapy
by Han Song Mun, Sung Hun Kim, Jieun Lee, Se Jun Park, Ahwon Lee, Jun Kang, Woo-Chan Park, Soo Youn Bae, Byung Ok Choi, Ji Hyun Hong, Soon Nam Oh and Kabsoo Shin
Cancers 2025, 17(11), 1768; https://doi.org/10.3390/cancers17111768 - 25 May 2025
Viewed by 286
Abstract
Background: The predictive value of muscle-related indicators in triple-negative breast cancer (TNBC) patients undergoing neoadjuvant chemotherapy (NAC) remains unclear. This study aimed to evaluate the association between the skeletal muscle density (SMD) and clinical variables related to the physical reserve with respect [...] Read more.
Background: The predictive value of muscle-related indicators in triple-negative breast cancer (TNBC) patients undergoing neoadjuvant chemotherapy (NAC) remains unclear. This study aimed to evaluate the association between the skeletal muscle density (SMD) and clinical variables related to the physical reserve with respect to its impact on the pathologic complete response (pCR). Methods: We retrospectively analyzed TNBC patients who underwent NAC at Seoul St. Mary’s Hospital, Catholic University of Korea, from March 2021 to March 2024, via receiving paclitaxel/carboplatin followed by doxorubicin/cyclophosphamide, with or without pembrolizumab. Muscle indices were assessed from CT measurements of the entire cross-sectional muscle area at the L3 level using commercial deep learning software (ClariMetabo version 1.03). Results: A total of 144 patients were included, where 102 received chemoimmunotherapy (NACIT) and 42 received chemotherapy alone (NACT). A higher SMD was significantly associated with a younger age, lower BMI, and fewer comorbidities. In the NACIT group, patients in the high-SMD group (n = 68) demonstrated a higher relative dose intensity (p = 0.003) and improved pCR rates (63.2% vs. 44.1%, p = 0.066) compared with the low-SMD group (n = 34). The multivariable regression analysis identified a higher SMD (per 5-unit increment: OR = 1.67, p = 0.003) and increased PD-L1 combined positive score (per 10-unit increment: OR = 1.38, p = 0.019) as independent predictors of a pCR. The event-free survival was significantly longer in the high-SMD group (p = 0.017) and among patients that achieved a pCR (p < 0.001). In the NACT group, the SMD was not associated with a pCR or survival. Conclusions: The CT-measured SMD reflected the physical reserve in the TNBC patients that received NAC. Alongside the CPS, SMD may serve as a predictive marker for NACIT efficacy. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation: 2nd Edition)
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