Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer
Bibliographic record
Abstract
PURPOSE: Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that disproportionately affects women of African ancestry (WAA) and is often associated with poor survival. Although there is a high prevalence of TNBC across West Africa and in women of the African diaspora, there has been no comprehensive genomics study to investigate the mutational profile of ancestrally related women across the Caribbean and West Africa. METHODS: This multisite cross-sectional study used 31 formalin-fixed paraffin-embedded (FFPE) samples from Barbadian and Nigerian TNBC participants. High-resolution whole exome sequencing (WES) was performed on the Barbadian and Nigerian TNBC samples to identify their mutational profiles and comparisons were made to African American, European American and Asian American sequencing data obtained from The Cancer Genome Atlas (TCGA). Whole exome sequencing was conducted on tumors with an average of 382 × coverage and 4335 × coverage for pooled germline non-tumor samples. RESULTS: Variants detected at high frequency in our WAA cohorts were found in the following genes NBPF12, PLIN4, TP53 and BRCA1. In the TCGA TNBC cases, these genes had a lower mutation rate, except for TP53 (32% in our cohort; 63% in TCGA-African American; 67% in TCGA-European American; 63% in TCGA-Asian). For all altered genes, there were no differences in frequency of mutations between WAA TNBC groups including the TCGA-African American cohort. For copy number variants, high frequency alterations were observed in PIK3CA, TP53, FGFR2 and HIF1AN genes. CONCLUSION: This study provides novel insights into the underlying genomic alterations in WAA TNBC samples and shines light on the importance of inclusion of under-represented populations in cancer genomics and biomarker studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".