Development of a Cell line Classifier for Precision Subtyping of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) exhibits marked clinical diversity and an absence of established targeted therapies, largely driven by heterogeneous tumor phenotypes and transcriptional profiles across subtypes. This biological variability complicates therapeutic strategies and underscores the unmet need for refined molecular classification systems. While molecular insights into TNBC pathogenesis have expanded, clinical applications remain constrained by insufficiently validated stratification tools. To address this gap, we developed an RNA-seq based classifier specifically optimized for TNBC cell lines, designed to enable refined subtype stratification and mechanistic exploration of molecular drivers.

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Publication Details

Journal
BIO Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/bioconf/202517402024
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of a Cell line Classifier for Precision Subtyping of Triple-Negative Breast Cancer

Hao Huang, Zhiyi Lu, Wenyong Zhu, Zhenchang Wang
BIO Web of Conferences
Cell Image Analysis Techniques
article

Development of a Cell line Classifier for Precision Subtyping of Triple-Negative Breast Cancer

Hao Huang, Zhiyi Lu, Wenyong Zhu, Zhenchang Wang
article en

Abstract

Triple-negative breast cancer (TNBC) exhibits marked clinical diversity and an absence of established targeted therapies, largely driven by heterogeneous tumor phenotypes and transcriptional profiles across subtypes. This biological variability complicates therapeutic strategies and underscores the unmet need for refined molecular classification systems. While molecular insights into TNBC pathogenesis have expanded, clinical applications remain constrained by insufficiently validated stratification tools. To address this gap, we developed an RNA-seq based classifier specifically optimized for TNBC cell lines, designed to enable refined subtype stratification and mechanistic exploration of molecular drivers.

BIO Web of ConferencesVol. 174
State Key Laboratory of Digital Medical Engineering (CN), Southeast University (CN)
Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 92%
Cell Image Analysis Techniques
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