Mutational landscape of triple-negative breast cancer in African American women

African American (AA) women have the highest incidence of triple-negative breast cancer (TNBC) among all racial groups, but are underrepresented in cancer genomic studies. In 462 AA women with TNBC, we characterized the tumor mutational landscape by whole-exome sequencing and RNA sequencing. We unveiled a high-resolution mutational portrait of TNBC in AA women reminiscent of that in Asian and non-Hispanic white women, with no evidence of associations of mutational features with African ancestry. We also made some distinctive discoveries, including an almost complete dominance of TP53 mutations, low frequency of PIK3CA mutations and mutational signature-based subtypes with etiologic and prognostic significance. These findings do not support major racial differences in TNBC biology at the level of somatic mutations. Our study contributes considerably to diversifying the knowledge base of breast cancer genomics and provides insights into the disease etiology, disparities and therapeutic vulnerability of TNBC in AA women.

Authors

Institutions

Publication Details

Journal
Nature Genetics
Published
2025-08-26
DOI
https://doi.org/10.1038/s41588-025-02322-y
Citations
3
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
2.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mutational landscape of triple-negative breast cancer in African American women

Qiuyin Cai, Maureen Sanderson, Elisa V. Bandera, Chi‐Chen Hong et al.
3 citations
Nature Genetics
Cancer Genomics and Diagnostics
2.81
article

Mutational landscape of triple-negative breast cancer in African American women

Qiuyin Cai, Maureen Sanderson, Elisa V. Bandera, Chi‐Chen Hong, Mark D. Long, Song Yao, Lei Wei, Christine B. Ambrosone, Peter N. Fiorica, Zarko Manojlovic, Jie Ping, Qiang Hu, Gary Zirpoli, Kazuaki Takabe, Qianqian Zhu, Yuxin Jin, Mollie E. Barnard, Thaer Khoury, Naomi Y. Ko, David W. Craig, Rochelle Payne Ondracek, Mitsuko Murakami, John D. Carpten, Jianmin Wang, Wei Zheng, Jian‐Hong Chen, Jirong Long, Song Liu, Julie R. Palmer, W. Davis, Shipra Gandhi
article en
3 citations

Abstract

African American (AA) women have the highest incidence of triple-negative breast cancer (TNBC) among all racial groups, but are underrepresented in cancer genomic studies. In 462 AA women with TNBC, we characterized the tumor mutational landscape by whole-exome sequencing and RNA sequencing. We unveiled a high-resolution mutational portrait of TNBC in AA women reminiscent of that in Asian and non-Hispanic white women, with no evidence of associations of mutational features with African ancestry. We also made some distinctive discoveries, including an almost complete dominance of TP53 mutations, low frequency of PIK3CA mutations and mutational signature-based subtypes with etiologic and prognostic significance. These findings do not support major racial differences in TNBC biology at the level of somatic mutations. Our study contributes considerably to diversifying the knowledge base of breast cancer genomics and provides insights into the disease etiology, disparities and therapeutic vulnerability of TNBC in AA women.

Nature GeneticsVol. 57(9)
Rutgers, The State University of New Jersey (US), Boston University (US), Meharry Medical College (US), Boston Medical Center (US), Roswell Park Comprehensive Cancer Center (US), City of Hope (US), Rutgers Cancer Institute (US), Vanderbilt University Medical Center (US)
Breast Cancer Research Foundation, National Cancer Institute
Openalex Percentile: Top 9%
Cancer Genomics and Diagnostics
2.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.