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

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

doi:10.1038/s41523-025-00740-z

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

NPJ Breast Cancer. 2025 Mar 8;11(1):24. doi: 10.1038/s41523-025-00740-z.

Authors

Brooke M Felsheim^{1

2}, Aranzazu Fernandez-Martinez², Cheng Fan², Adam D Pfefferle^{2

3}, Michele C Hayward², Katherine A Hoadley^{2

3}, Naim U Rashid^{2

4}, Sara M Tolaney⁵, George Somlo⁶, Lisa A Carey^{2

7}, William M Sikov⁸, Charles M Perou^{9

10}

Affiliations

¹ Bioinformatics and Computational Biology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
² Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
³ Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
⁴ Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA.
⁵ Dana-Farber/Harvard Cancer Center, Boston, MA, USA.
⁶ City of Hope Comprehensive Cancer Center, Duarte, CA, USA.
⁷ Division of Hematology-Oncology, Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA.
⁸ Program in Women's Oncology, Women and Infants Hospital of Rhode Island, Warren Alpert Medical School of Brown University, Providence, RI, USA.
⁹ Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. cperou@med.unc.edu.
¹⁰ Department of Genetics, University of North Carolina, Chapel Hill, NC, USA. cperou@med.unc.edu.

Abstract

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.

Abstract

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