Abstract P5-03-05: Distinct molecular differences between African American/Black and White women with Triple Negative Breast Cancer
Bibliographic record
Abstract
Abstract Introduction: Triple-negative breast cancer (TNBC) is an aggressive disease that lacks well-defined molecular targets. It accounts for 15-20% of all breast cancers and disproportionately affects women of color due to both limited access to treatment and genetic variation. Recent studies identified BRCA1(or 2) and the PIK3CA/AKT1/PTEN axis as targets for treatment, but these studies neglected to account for genetic variations between race. Here, we present molecular differences between African American/Black (AA) and White (W) women with TNBC to highlight the importance of accounting for race to develop effective therapy and improve long-term outcomes. Methods: This study utilized the TCGA Firehose Legacy Breast Carcinoma dataset on cBioPortal. Subjects with breast cancer and negative ER, PR, and HER2 scores were stratified into AA (n=32) and W (n=69) subgroups. Data was analyzed to compare the most altered genes, copy number variation (CNV), and survival rates between the subgroups. The logrank test was used to obtain the hazard rate. The GISTIC2 model was used to assess CNV and G-scores (G; amplitude of aberration x frequency of occurrence). Results: The main genetic differences were in PIK3CA and BRCA1(or 2) genes. PIK3CA was detected as one of the ten most altered genes in TNBC, but this alteration was found in less than 10% of the TNBC cases. Of the 10%, PIK3CA was altered in 19% of W and 9% of AA subgroup. BRCA1(2) were altered in 10%(7%) of W but 0%(3%) of AA. Additionally, structural differences in chromosomes contributed to different survival outcomes. Both groups had co-amplification in 8q, but a significant hazard rate difference (z = 5.32, p < 0.001) was found for the W compared to the AA for the MYC gene. Further, the W had significantly higher amplification at 3q (G = 0.8 in W; 0.45 in AA). It is important to note that the PIK3CA gene lies in the 3q.26 region, meaning this gene is amplified significantly in the W subgroup. The AA group had a significant deletion at 8p.23 (G=0.5 in W; 0.8 in AA). Deletion of 8p causes MYC amplification, a targetable alteration. Conclusion: Our analysis reveals critical differences between AA and W subgroups with TNBC. Thus, it is clear that targeting the PIK3CA or BRCA1(2) gene benefits the W more than the AA population. To alleviate the disproportionate burden that AA women with TNBC face, more effort must be geared to find solutions specific to the AA subgroup. A greater sample size will help determine whether MYC amplification is unique to the AA subgroup, and if so, it could be targeted to improve outcomes of AA women with TNBC. Nevertheless, more data and research is needed to understand causes and decrease the rate of disparate outcomes in patients with TNBC. Citation Format: So Hyeon Park, Roy Khalife, Evan White, Anthony Magliocco. Distinct molecular differences between African American/Black and White women with Triple Negative Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-03-05.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".