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<p>Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous disease that remains challenging to target with traditional therapies and to predict risk. We provide a comprehensive characterization of 238 stage II-III TNBC tumors with paired RNA and DNA sequencing data from the CALGB 40603 (Alliance) clinical trial, along with 448 stage II-III TNBC tumors with paired RNA and DNA data from three additional datasets. We identify DNA mutations associated with RNA-based subtypes, specific <i>TP53</i> missense mutations compatible with potential neoantigen activity, and a consistently highly altered copy number landscape. We train exploratory multi-modal elastic net models of TNBC patient overall survival to determine the added impact of DNA-based features to RNA and clinical features. We find that mutations and copy number show little to no prognostic value, while RNA expression features, including signatures of T cell and B cell activity, along with stage, improve stratification of TNBC survival risk.</p>

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Prognostic and molecular multi-platform analysis of CALGB 40603 (Alliance) and public triple-negative breast cancer datasets

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月8日

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  • Brooke M. Felsheim,
  • Aranzazu Fernandez-Martinez,
  • Cheng Fan,
  • Adam D. Pfefferle,
  • Michele C. Hayward,
  • Katherine A. Hoadley,
  • Naim U. Rashid,
  • Sara M. Tolaney,
  • George Somlo,
  • Lisa A. Carey,
  • William M. Sikov,
  • Charles M. Perou

摘要

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous disease that remains challenging to target with traditional therapies and to predict risk. We provide a comprehensive characterization of 238 stage II-III TNBC tumors with paired RNA and DNA sequencing data from the CALGB 40603 (Alliance) clinical trial, along with 448 stage II-III TNBC tumors with paired RNA and DNA data from three additional datasets. We identify DNA mutations associated with RNA-based subtypes, specific TP53 missense mutations compatible with potential neoantigen activity, and a consistently highly altered copy number landscape. We train exploratory multi-modal elastic net models of TNBC patient overall survival to determine the added impact of DNA-based features to RNA and clinical features. We find that mutations and copy number show little to no prognostic value, while RNA expression features, including signatures of T cell and B cell activity, along with stage, improve stratification of TNBC survival risk.