ArticleCancer research2025
Genomic Analysis Reveals Racial and Age-Related Differences in the Somatic Landscape of Breast Cancer and the Association with Socioeconomic Factors.
Article in Cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Identifying Locally Recurrent Versus Second Primary Breast Cancer: Genomic Versus Clinical Criteria from Carolina Breast Cancer Study Phase III.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Trial
- Engineered artificial antigen-presenting cells for tumor immunotherapy: Design strategies, clinical applications, and translational challenges.Materials today. Bio · 2026Review
- Bridging the gap: ctDNA, genomics, and equity in breast cancer care.NPJ breast cancer · 2025Review
- Tumor Mutational Landscape and Its Correlation With Histopathological Characteristics in Breast Cancer.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Cancer genomics consortia have identified somatic drivers of breast cancer subtypes. However, these studies have predominantly included older, non-Black women, and the related socioeconomic status (SES) data are limited. Increased representation and depth of social data are crucial for understanding how health inequity is intertwined with somatic landscapes. Here, we conducted targeted sequencing on primary tumors from the Carolina Breast Cancer Study (N = 357; 52% Black; 47% <50) and compared the results with The Cancer Genome Atlas (N = 948; 18% Black; 27% <50). Race (Black vs. non-Black), age, and SES were evaluated in association with mutations, copy number alterations, and aneuploidy using generalized linear models. Pathway dysfunction was also assessed by aggregating mutation and copy number alterations. Adjusting for age, Black participants (N = 350) were significantly more likely to have TP53 and FAT1 mutations and less likely to have PIK3CA, CDH1, DDR2, and GATA3 mutations than non-Black participants. Younger participants had more GATA3 alterations and fewer KMT2C, PTEN, MAP3K1, and CDH1 alterations. Black participants had significant enrichment for MYC (8q) and PIK3CA (3q26) amplifications and higher total aneuploidy, but age was not associated with copy number variation. SES was associated with different patterns of alteration in Black versus non-Black women. Overall, Black participants showed modest differences in TP53, PIK3CA, and other alterations that further varied by SES. Race is a social construct, and varying distributions of etiologic factors across social strata may predispose Black, young, and low SES women to cancer subtypes characterized by these alterations. Significance: The collection and analysis of DNA sequencing with comprehensive socioeconomic factor associations in a large Black breast cancer patient cohort could help uncover mechanisms by which social conditions contribute to tumor biology.
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