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Cancers
Special Issues
Breast Cancer Biomarkers and Clinical Translation
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Breast Cancer Biomarkers and Clinical Translation

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 4194

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,

Breast cancer represents the second most common cancer in women, 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” 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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Published Papers (2 papers)

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Research

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24 pages, 1679 KiB  
Article
Secondary Transcriptomic Analysis of Triple-Negative Breast Cancer Reveals Reliable Universal and Subtype-Specific Mechanistic Markers
by Naomi Rapier-Sharman, Mauri Dobbs Spendlove, Jenna Birchall Poulsen, Amanda E. Appel, Rosana Wiscovitch-Russo, Sanjay Vashee, Norberto Gonzalez-Juarbe and Brett E. Pickett
Cancers 2024, 16(19), 3379; https://doi.org/10.3390/cancers16193379 - 2 Oct 2024
Viewed by 780
Abstract
Background/Objectives: Breast cancer is diagnosed in 2.3 million women each year and kills 685,000 (~30% of patients) worldwide. The prognosis for many breast cancer subtypes has improved due to treatments targeting the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth [...] Read more.
Background/Objectives: Breast cancer is diagnosed in 2.3 million women each year and kills 685,000 (~30% of patients) worldwide. The prognosis for many breast cancer subtypes has improved due to treatments targeting the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). In contrast, patients with triple-negative breast cancer (TNBC) tumors, which lack all three commonly targeted membrane markers, more frequently relapse and have lower survival rates due to a lack of tumor-selective TNBC treatments. We aim to investigate TNBC mechanistic markers that could be targeted for treatment. Methods: We performed a secondary TNBC analysis of 196 samples across 10 publicly available bulk RNA-sequencing studies to better understand the molecular mechanism(s) of disease and predict robust mechanistic markers that could be used to improve the mechanistic understanding of and diagnostic capabilities for TNBC. Results: Our analysis identified ~12,500 significant differentially expressed genes (FDR-adjusted p-value < 0.05), including KIF14 and ELMOD3, and two significantly modulated pathways. Additionally, our novel findings include highly accurate mechanistic markers identified using machine learning methods, including CIDEC (97.1% accuracy alone), CD300LG, ASPM, and RGS1 (98.9% combined accuracy), as well as TNBC subtype-differentiating mechanistic markers, including the targets PDE3B, CFD, IFNG, and ADM, which have associated therapeutics that can potentially be repurposed to improve treatment options. We then experimentally and computationally validated a subset of these findings. Conclusions: The results of our analyses can be used to better understand the mechanism(s) of disease and contribute to the development of improved diagnostics and/or treatments for TNBC. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation)
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Review

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15 pages, 1733 KiB  
Review
Advances in Early Breast Cancer Risk Profiling: From Histopathology to Molecular Technologies
by Carlo Pescia, Elena Guerini-Rocco, Giuseppe Viale and Nicola Fusco
Cancers 2023, 15(22), 5430; https://doi.org/10.3390/cancers15225430 - 15 Nov 2023
Cited by 7 | Viewed by 2909
Abstract
Early breast cancer (BC) is the definition applied to breast-confined tumors with or without limited involvement of locoregional lymph nodes. While risk stratification is essential for guiding clinical decisions, it can be a complex endeavor in these patients due to the absence of [...] Read more.
Early breast cancer (BC) is the definition applied to breast-confined tumors with or without limited involvement of locoregional lymph nodes. While risk stratification is essential for guiding clinical decisions, it can be a complex endeavor in these patients due to the absence of comprehensive guidelines. Histopathological analysis and biomarker assessment play a pivotal role in defining patient outcomes. Traditional histological criteria such as tumor size, lymph node involvement, histological type and grade, lymphovascular invasion, and immune cell infiltration are significant prognostic indicators. In addition to the hormone receptor, HER2, and—in specific scenarios—BRCA1/2 testing, molecular subtyping through gene expression profiling provides valuable insights to tailor clinical decision-making. The emergence of “omics” technologies, applicable to both tissue and liquid biopsy samples, has broadened our arsenal for evaluating the risk of early BC. However, a pressing need remains for standardized methodologies and integrated pathological models that encompass multiple analytical dimensions. In this study, we provide a detailed examination of the existing strategies for early BC risk stratification, intending to serve as a practical guide for histopathologists and molecular pathologists. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation)
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