Abstract
Breast cancers are heterogeneous and largely classified using immunohistochemistry of estrogen receptor expression. However, research suggests RNA-based subtyping, including intrinsic (luminal vs. non-luminal) and TP53-based subtypes, may offer additional etiologic insight. TP53 mutant tumors, often more aggressive and non-luminal, are common among women of African descent. We examined possible heterogeneity for RNA-based luminal/non-luminal and TP53 subtypes among women of west African ancestry. We analyzed 595 invasive breast cancer cases and 2096 controls in the Ghana Breast Health Study. RNA was extracted from formalin-fixed paraffin-embedded tumor samples and profiled via nCounter® Breast Cancer 360™. Tumors were classified as luminal (N = 278) vs. non-luminal (N = 282) and TP53 wildtype-like (N = 324) vs. mutant-like (N = 271) using the PAM50 assay and a validated RNA signature, respectively. Case–control odds ratios and 95% confidence intervals were estimated using polytomous logistic regression. Etiologic heterogeneity was assessed in case-only analyses. Higher parity was more protective for luminal than non-luminal tumors (p-heterogeneity =.05). Older age at menarche and alcohol use ≥6 months were associated with elevated risk of luminal, but not non-luminal tumors (p-heterogeneity =.01). Similar trends were observed for TP53 wildtype-like tumors, though not statistically significant. Cross-classification of PAM50/TP53 showed that higher parity, older age at menarche, and alcohol use ≥6 months were more strongly associated with luminal/TP53 wildtype-like than other subtypes. RNA-based breast cancer subtyping suggests TP53 refines breast cancer etiologic heterogeneity in a sub-Saharan African population. The high prevalence of aggressive, mostly TP53-mutant tumors in this population underscores the need for further studies to clarify etiologic heterogeneity.
| Original language | English |
|---|---|
| Pages (from-to) | 2890-2899 |
| Number of pages | 10 |
| Journal | International Journal of Cancer |
| Volume | 158 |
| Issue number | 11 |
| DOIs | |
| Publication status | Accepted/In press - 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Nanostring
- breast cancer
- etiologic heterogeneity
- gene expression
- risk factors
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