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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 "Cancer Biomarkers".

Deadline for manuscript submissions: 20 February 2026 | Viewed by 2794

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 Oncology, 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 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.

Publisher’s Notice

The Special Issue, together with its publications, has been shifted from Section Clinical Research to Section Cancer Biomarkers on 14 November 2025. The publications remain available in the regular issues in which they were originally published. The Editorial Office confirms that these articles adhered to MDPI's standard editorial process (https://www.mdpi.com/editorial_process).

Keywords

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

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Published Papers (3 papers)

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Research

17 pages, 931 KB  
Article
Tissue Microarray-Based Digital Spatial Profiling of Benign Breast Lobules and Breast Cancers: Feasibility, Biological Coherence, and Cross-Platform Benchmarks
by Mark E. Sherman, Jodi C. Carter, Robert A. Vierkant, Melody Stallings-Mann, Laura Pacheco-Spann, Stacey J. Winham, Celine M. Vachon, Chen Wang, Matthew R. Jensen, Melissa A. Troester, Amy C. Degnim, E. Aubrey Thompson, Jennifer Kachergus, Ji Shi and Derek C. Radisky
Cancers 2025, 17(23), 3797; https://doi.org/10.3390/cancers17233797 - 27 Nov 2025
Viewed by 309
Abstract
Background: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements [...] Read more.
Background: Discovering risk biomarkers in small benign breast disease (BBD) biopsies is constrained by scarce tissue and microanatomic heterogeneity of terminal duct lobular units (TDLUs). We tested whether tissue-sparing tissue microarray (TMA)–based Digital Spatial Profiling (DSP) can deliver reproducible, biologically coherent protein measurements across benign lobules and breast cancers (BCs), and how well DSP aligns with standard immunoassays. Methods: We performed a pilot using tissues from the Mayo Clinic BBD cohort using TMAs representing four contexts: terminal duct lobular units (TDLUs) from BBD biopsies preceding BC and matched BBD-controls, subsequent BCs, and BC-associated TDLUs. We profiled 79 proteins by DSP (37 retained after QC) and benchmarked against chromogenic IHC and OPAL immunofluorescence. Reproducibility was evaluated using intraclass correlation coefficients (ICCs), cross-platform agreement (weighted kappa), marker correlations, and mixed-effects models with false-discovery-rate (FDR) control. Results: We analyzed 368 BBD-TDLU cores (88 cases; 88 controls), 204 BC cores and 110 BC-associated TDLU cores. ICCs were highest in BC tissues, and lower in BC-associated TDLUs and BBD-TDLUs. Agreement was slight–to-fair in TDLUs but moderate (ER/PR) to substantial (BCL2) in BC. DSP recapitulated expected immunologic correlations (CD45 with T-cell, B-cell, and macrophage markers) and tissue-type gradients (BC > BC-associated TDLUs > BBD-TDLUs). Exploratory case–control differences in BBD-TDLUs did not persist after FDR control. Conclusions: TMA-based DSP is feasible in archival breast tissues and yields biologically coherent, cross-platform-benchmarked profiles that are particularly robust in BC, while conserving scarce TDLUS and clarifying current limits of single-marker risk stratification from benign lobules. These data provide a foundation for refined sampling and expanded panels in future TDLU-focused studies. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation: 2nd Edition)
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12 pages, 904 KB  
Article
Decline of PD-L1 Immunoreactivity with Storage Duration in Formalin-Fixed Paraffin-Embedded Breast Cancer Specimens: Implications for Diagnostic Accuracy and Immunotherapy Eligibility in Triple-Negative Breast Cancer
by Keiko Yanagihara, Koji Nagata, Tamami Yamakawa, Sena Kato, Miki Tamura and Masato Yoshida
Cancers 2025, 17(19), 3103; https://doi.org/10.3390/cancers17193103 - 23 Sep 2025
Viewed by 940
Abstract
Backgrounds: Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is a critical predictive biomarker for immune checkpoint inhibitor (ICI) therapy in triple-negative breast cancer (TNBC). However, prolonged storage of formalin-fixed paraffin-embedded (FFPE) tissue may reduce antigenicity, potentially leading to false-negative results. False-negative results may [...] Read more.
Backgrounds: Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is a critical predictive biomarker for immune checkpoint inhibitor (ICI) therapy in triple-negative breast cancer (TNBC). However, prolonged storage of formalin-fixed paraffin-embedded (FFPE) tissue may reduce antigenicity, potentially leading to false-negative results. False-negative results may lead to the inappropriate selection of ICI therapy. We investigated the effect of FFPE storage duration on PD-L1 immunoreactivity. Methods: We retrospectively analyzed 63 TNBC cases with PD-L1 testing using the 22C3 pharmDx assay at diagnosis and repeated IHC on the same FFPE blocks after varying storage durations (<1, 1–2, 2–3, ≥3 years). PD-L1 positivity was defined as Combined Positive Score (CPS) ≥ 10. Associations with clinicopathologic features, pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC), and survival were evaluated. Results: At diagnosis, 41 patients (65.1%) were PD-L1–positive. In the PD-L1–positive group, decreased staining was observed in 0%, 11%, 13%, and 50% of cases for <1, 1–2, 2–3, and ≥3 years of storage, respectively (p = 0.015). PD-L1 positivity correlated with higher Ki67 and nuclear grade. pCR was achieved in 33% of PD-L1–positive vs. 0% of PD-L1–negative NAC patients (p = 0.0527). Survival analysis showed a non-significant trend toward shorter recurrence-free and overall survival in PD-L1–positive patients. Conclusions: Prolonged FFPE storage, particularly beyond three years, significantly reduces PD-L1 immunoreactivity. Testing on recent specimens is recommended to avoid false-negative results that may impact ICI eligibility. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation: 2nd Edition)
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17 pages, 1251 KB  
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
Cited by 1 | Viewed by 1173
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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