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: closed (30 November 2024) | Viewed by 9872

Special Issue Editors


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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

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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

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Keywords

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

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Published Papers (4 papers)

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Research

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22 pages, 4395 KiB  
Article
Combining KPNA2 and FOXM1 Expression as Prognostic Markers and Therapeutic Targets in Hormone Receptor-Positive, HER2-Negative Breast Cancer
by Tsen-Long Yang, Chung-Hsin Tsai, Ying-Wen Su, Yuan-Ching Chang, Fang Lee, To-Yu Huang, Fang-Yi Li and Po-Sheng Yang
Cancers 2025, 17(4), 671; https://doi.org/10.3390/cancers17040671 - 17 Feb 2025
Viewed by 549
Abstract
Background/Objectives: Breast cancer remains the leading malignancy affecting women worldwide, with significant mortality rates. This study aimed to evaluate the prognostic significance of FOXM1 expression specifically in hormone receptor-positive, HER2-negative (HR+HER2-) breast cancer patients with high KPNA2 expression, and to identify potential [...] Read more.
Background/Objectives: Breast cancer remains the leading malignancy affecting women worldwide, with significant mortality rates. This study aimed to evaluate the prognostic significance of FOXM1 expression specifically in hormone receptor-positive, HER2-negative (HR+HER2-) breast cancer patients with high KPNA2 expression, and to identify potential FOXM1-targeted therapeutic strategies for this patient subgroup. Methods: We analyzed RNA sequencing and microarray data from three independent cohorts: Mackay Memorial Hospital patient samples, The Cancer Genome Atlas, and Gene Expression Omnibus databases. The expression levels of KPNA2, FOXM1, CCNB1, and CCNB2 were evaluated, with particular emphasis on stratifying patients based on KPNA2 expression levels. Their associations with clinical outcomes were assessed using Gene Set Enrichment Analysis and survival analyses. Results: While KPNA2 expression showed strong positive correlations with FOXM1, CCNB1, and CCNB2 across all datasets, our analysis revealed a distinct prognostic pattern in HR+HER2- breast cancer patients with high KPNA2 expressions. In this specific subgroup, low FOXM1 expression emerged as a favorable prognostic indicator, despite the generally poor prognosis associated with high KPNA2 levels. Gene Set Enrichment Analysis demonstrated significant enrichment of the G2/M checkpoint pathway in high KPNA2-expressing patients, suggesting potential therapeutic vulnerability to FOXM1 inhibition in this subgroup. Conclusions: This study establishes FOXM1 expression as a critical prognostic marker, specifically in KPNA2-high HR+HER2- breast cancer patients, where low FOXM1 levels correlate with improved survival outcomes. These findings suggest that FOXM1 inhibition could be particularly effective in patients with high KPNA2 expression, offering a novel therapeutic strategy for this specific molecular subtype. Several FOXM1 inhibitors, including thiostrepton and FDI-6, warrant investigation as potential targeted treatments for KPNA2-high HR+HER2- breast cancer patients. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation)
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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
Cited by 1 | Viewed by 1968
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, 1368 KiB  
Review
A Comprehensive Review of TRPS1 as a Diagnostic Immunohistochemical Marker for Primary Breast Carcinoma: Latest Insights and Diagnostic Pitfalls
by Antonia-Carmen Georgescu, Tiberiu-Augustin Georgescu, Simona-Alina Duca-Barbu, Lucian Gheorghe Pop, Daniela Oana Toader, Nicolae Suciu and Dragos Cretoiu
Cancers 2024, 16(21), 3568; https://doi.org/10.3390/cancers16213568 - 23 Oct 2024
Viewed by 2295
Abstract
Background/Objectives: Immunohistochemical expression of TRPS1 (trichorhinophalangeal syndrome type 1) protein is usually used by pathologists to confirm breast origin for triple-negative breast cancers (TNBC) or metastatic carcinomas of unknown primary. However, recent studies have reported TRPS1 expression in a variety of non-breast lesions. [...] Read more.
Background/Objectives: Immunohistochemical expression of TRPS1 (trichorhinophalangeal syndrome type 1) protein is usually used by pathologists to confirm breast origin for triple-negative breast cancers (TNBC) or metastatic carcinomas of unknown primary. However, recent studies have reported TRPS1 expression in a variety of non-breast lesions. This review aims to provide a comprehensive evaluation of TRPS1 expression across various tumor types, highlighting both its diagnostic utility and potential pitfalls that may arise in clinical practice. Methods: A thorough search of the PubMed database on TRPS1 immunoexpression in tumor pathology was conducted. While the gene itself has been known for several decades, most studies regarding its use in immunohistochemistry emerged in the late 2010s. Particular emphasis was placed on case reports and cohort studies that examined the implications of TRPS1 expression in non-breast tissues, as well as variations in the results between commercially available TRPS1 clones, which may influence the staining intensity and specificity. Results: TRPS1 demonstrated a strong diagnostic utility in identifying primary breast lesions, particularly in TNBC cases. However, its expression in a growing number of non-breast cancers, such as lung adenocarcinoma, prostate adenocarcinoma, urothelial carcinoma, ovarian high-grade serous carcinoma, and endometrial adenocarcinoma, as well as up to 96% of synovial sarcomas with SS18-SSX fusion, emphasizes the need for caution when interpreting TRPS1 positivity and suggests a multi-marker approach in order to increase the diagnostic accuracy. Conclusions: While TRPS1 remains a highly sensible immunohistochemical marker for confirming breast primary lesions, pathologists should be aware of its low specificity and incorporate complementary diagnostic methods in order to ensure accurate clinical management. Further research should focus on elucidating the molecular pathways regulating TRPS1 expression in various tumor types, which may better define its clinical utility. Full article
(This article belongs to the Special Issue Breast Cancer Biomarkers and Clinical Translation)
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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 4275
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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