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Unraveling Tumor Heterogeneity: Quantitative Insights from Single-cell RNA Sequencing Analysis in Breast Cancer Subtypes

Senra, Daniela et al · Cognizant Communication Corp · 2025

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Background and objectives: Tumors are complex systems characterized by variations across genetic, transcriptomic, phenotypic, and microenvironmental levels. This study introduced a novel framework for quantifying cancer cell heterogeneity using single-cell RNA sequencing data. The framework comprised several scores aimed at uncovering the complexities of key cancer traits, such as metastasis, tumor progression, and recurrence. Methods: This study leveraged publicly available single-cell transcriptomic data from three human breast cancer subtypes: estrogen receptor-positive, human epidermal growth factor receptor 2-positive, and triple-negative. We employed a quantitative approach, analyzing copy number alterations (CNAs), entropy, transcriptomic heterogeneity, and diverse protein-protein interaction networks (PPINs) to explore critical concepts in cancer biology. Results: We found that entropy and PPIN activity related to the cell cycle could distinguish cell clusters with elevated mitotic activity, particularly in aggressive breast cancer subtypes. Additionally, CNA distributions varied across cancer subtypes. We also identified positive correlations between the CNA score, entropy, and the activities of PPINs associated with the cell cycle, as well as those linked to basal and mesenchymal cell lines. Conclusions: This study addresses a gap in the current understanding of breast cancer heterogeneity by presenting a novel quantitative approach that offers deeper insights into tumor biology, surpassing traditional marker-based methods. Fil: Senra, Daniela. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina Fil: Guisoni, Nara Cristina. Universidad Nacional de La Plata. Centro Regional de Estudios Genómicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Argentina de la Empresa; Argentina

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APA 7

Senra, D. E. A. (2025). Unraveling Tumor Heterogeneity: Quantitative Insights from Single-cell RNA Sequencing Analysis in Breast Cancer Subtypes. http://hdl.handle.net/11336/267060

MLA

Senra, Daniela et al. "Unraveling Tumor Heterogeneity: Quantitative Insights from Single-cell RNA Sequencing Analysis in Breast Cancer Subtypes." 2025. http://hdl.handle.net/11336/267060.

Chicago

Senra, Daniela et al. 2025. "Unraveling Tumor Heterogeneity: Quantitative Insights from Single-cell RNA Sequencing Analysis in Breast Cancer Subtypes.". http://hdl.handle.net/11336/267060.

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Senra, D. E. A. 2025, Unraveling Tumor Heterogeneity: Quantitative Insights from Single-cell RNA Sequencing Analysis in Breast Cancer Subtypes, Cognizant Communication Corp, available at: http://hdl.handle.net/11336/267060 [Accessed 28 Jun. 2026].

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Título
Unraveling Tumor Heterogeneity: Quantitative Insights from Single-cell RNA Sequencing Analysis in Breast Cancer Subtypes
Autor / colaboradores
Senra, Daniela et al
Editorial
Cognizant Communication Corp
Año de publicación
2025
ISSN
1052-2166
ISSN
1052-2166
Idioma
eng

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