Abstract PO-142: Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer
Bibliographic record
Abstract
Abstract Women of African ancestry (WAA) are disproportionately affected by the aggressive triple negative breast cancer (TNBC) subtype that is often associated with high recurrence rates and metastasis. 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. To shed more light on this phenomenon, whole exome sequencing (WES) was performed on 31 formalin-fixed paraffin-embedded TNBC tissues from ancestrally related Barbadian and Nigerian women. We compared these genomics profiles with data from The Cancer Genome Atlas (TCGA) for African American (TCGA-AA), European American (TCGA-EA) women with TNBC. With an average coverage of 382x for tumour samples (n= 31) and 4335x for pooled germline (n=22) non-tumor samples, the most mutated genes in our cohorts include NBPF12, PLIN4, TP53 and BRCA1. For TCGA TNBC cases, these genes had a lower mutation rate, except for TP53 (32% in our cohort; 63% in TCGA-AA; 67% in TCGA-EA). For all altered genes, there were no differences in frequency of mutations between WAA TNBC groups including the TCGA-AA cohort. Additionally, we observed a high frequency of copy number variant alterations in PIK3CA, TP53, FGFR2 and HIF1AN genes. This study provides in-depth insights into the underlying genomic alterations in WAA-TNBC samples and shines light on the importance of inclusion of non-European populations in cancer genomics and biomarker studies. Citation Format: Shawn M. Hercules, Xiyu Liu, Blessing I. Bassey-Archibong, Desiree H.A. Skeete, Suzanne Smith Connell, Adetola Daramola, Adekunbiola A.F. Banjo, Godwin Ebughe, Thomas Agan, Ima-Obong Ekanem, Joe E. Udosen, Christopher Obiorah, Aaron C. Ojule, Michael A. Misauno, Ayuba M. Dauda, Ejike C. Egbujo, Jevon C. Hercules, Amna Ansari, Ian Brain, Christine MacColl, Yili Xu, Yuxin Jin, Sharon Chang, John D. Carpten, André Bédard, Gregory R. Pond, Kim R.M. Blenman, Zarko Manojlovic, Juliet M. Daniel. Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-142.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".