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Computational Cancer Genomics and Molecular Profile in Breast Cancer

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 1016

Special Issue Editors


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Guest Editor
Faculdade de Medicina de Ribeirão Preto (FMRP), Universidade de São Paulo, Sao Paulo, Brazil
Interests: breast cancer; computational biology; molecular profiling; predictive and prognostic factors

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Guest Editor
Dipartimento di Scienze e Tecnologie (DST), Università degli Studi del Sannio, Benevento, Italy
Interests: computational statistics; computational inference; cancer genomics; transcriptomics

Special Issue Information

Dear Colleagues,

Breast cancer is a highly prevalent disease worldwide. Current developments in molecular biology have brought new insights into the nature of this disease, and it is clear that breast cancer is not a unique illness but probably a myriad of entities with distinct biological and clinical behaviors. Such diversity impairs therapeutic strategies, and treating breast cancer patients remains challenging. Computational biology is a powerful field that integrates computer science, mathematics, and statistics to solve complex problems, such as molecular and genomic information from high-throughput technologies. The use of such tools enables a better characterization of breast cancer diversity and has demonstrated that this approach is a successful strategy in the development of more accurately targeted therapies, optimizing cancer treatment, and reducing undesired side effects. Original research, systematic reviews, and new protocols or methodologies of analysis using computational strategies to analyze molecular and genomic data from breast cancer samples—in particular when integrating them with clinical applications—are welcome.

Dr. Daniel Guimarães Tiezzi
Dr. Stefano Maria Pagnotta
Guest Editors

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Keywords

  • breast cancer
  • computational biology
  • genomics
  • molecular biology

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Published Papers (1 paper)

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Research

14 pages, 1527 KB  
Article
The HER2MtGx Metagene Score as a Reliable Tool to Select HER2 Breast Cancer Patients for Neoadjuvant Targeted Therapy
by Daniel Guimarães Tiezzi, Isabela Panzeri Carlotti Buzatto, Willian Abraham da Silveira, Anna Clara Monti, Fabiana de Oliveira Buono, Juliana Meola, Omero Benedicto Poli-Neto and Stefano Maria Pagnotta
Int. J. Mol. Sci. 2025, 26(24), 11809; https://doi.org/10.3390/ijms262411809 - 6 Dec 2025
Viewed by 694
Abstract
The cHER2+ breast cancer subtype is characterized by the overexpression of the HER2 oncoprotein based on immunohistochemistry (IHC)/or by ERBB2 gene amplification using in situ hybridization (ISH) techniques. Targeted therapies are significantly changing cancer treatment outcomes. However, not all patients benefit from it [...] Read more.
The cHER2+ breast cancer subtype is characterized by the overexpression of the HER2 oncoprotein based on immunohistochemistry (IHC)/or by ERBB2 gene amplification using in situ hybridization (ISH) techniques. Targeted therapies are significantly changing cancer treatment outcomes. However, not all patients benefit from it due to misclassification or intrinsic mechanisms of resistance. Identifying predictive factors of response to therapy is thus crucial for optimizing treatment protocol. In addition, with the development of effective antibody–drug conjugates for targeting HER2-low subtypes, enhancing the HER2 molecular classification is crucial. In this study, a comprehensive analysis of publicly available datasets (TCGA, METABRIC, I-SPY, NOAH and CHER-LOB trials) has been considered. We present a metagene expression score (HER2MtGx 31-gene assay) based on the most informative genes associated with each molecular profile. HER2MtGx scores represent three linear subspaces associated with the HER2, Luminal and Basal-like profiles (STAT). In the METABRIC cohort, the scores are useful to discriminate against the HER2-enriched phenotype and this classification is significantly associated with long-term survival in cHER2+ patients (HR = 1.76; 95%CI = 1.09–2.86). In terms of response to neoadjuvant chemo/target therapy including I-SPY, NOAH, and CHER-LOB trials, the metagene scores are associated with the pathological response to therapy (OR = 2.26; 95%CI = 1.74–2.98). The HER2MtGx assay is a reliable tool for selecting patients for HER2-targeted therapy. Full article
(This article belongs to the Special Issue Computational Cancer Genomics and Molecular Profile in Breast Cancer)
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