Abstract 1118: The GENIE BPC BRCA Cohort: a real-world repository of standardized clinical and genomic data for young patients with breast cancer
Bibliographic record
Abstract
Abstract Purpose: The first comprehensive analysis of the detailed clinico-genomic landscape of the breast cancer (BC) cohort of the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) Biopharma Collaborative (BPC). Methods: We analyzed 1, 045 BC patients treated at three GENIE-participating institutions. Breast cancer patients in the GENIE registry aged 18-56 at sequencing and with tumor(s) sequenced between 2013 and 2018 were randomly chosen for curation using the PRISSMM framework. Sites of distant metastasis were captured from imaging and pathology reports. A previously published cohort of older patients was used as a point of comparison in identifying age-related differences. Overall survival (OS) was estimated for patients with advanced disease. Results: Clinical and genomic features were compared across the four subtypes HR+/ HER2 - (N=660), HR+/HER2+ (N=138), HR-/HER2+ (N= 74), and TNBC (n = 173). The age distribution was similar across subtypes, HR+/HER2+ had the highest percentage of patients ages 18-39 (HR+/HER2-: 28%, HR+/HER2+: 39%, TNBC: 33%, HR-/HER2+ 35%). The most frequently altered genes in the cohort were TP53 (HR+/HER2-: 33%, HR+/HER2+: 58%, TNBC: 95%, HR-/HER2+ 80%), PIK3CA ( HR+/HER2-: 35%, HR+/HER2+: 33%, TNBC: 8%, HR-/HER2+ 15%), and ERBB2 (HR+/HER2-: 3%, HR+/HER2+: 71%, TNBC: 2%, HR-/HER2+ 84%). Analysis of patients with metastatic disease (n=818) revealed robust associations with OS and TP53 (HR = 1.87, SF = 100%), ERBB2 amplification (HR = 0.61, SF = 98%), MYC (HR = 1.09, SF = 52%), FGFR2 (HR=0.89, SF = 49.3%), MAP3K1 (HR = 0.94, SF = 35%), DDR2 (HR = 1.09, SF = 33%) and ESR1 (HR=1.07, SF = 32.7%). In a comparison of older and younger patients with HR+/HER2- subtype, we found that mutations in TP53 (18-39: 35% vs >60: 22%), GATA3 (18-39: 21% vs >60: 10%), and MAP2K4 (18-39: 10% vs >60: 4%) were significantly (q<0.1) more prevalent among younger patients. Conversely, PIK3CA (18-39: 31% v >60: 48%), CDH1 (18-39: 3% v >60: 21%), and MAP3K1 (18-39: 5% v >60: 12%) showed higher alteration rates in seniors. These trends were consistent at pathway level with higher alteration of p53 (18-39: 44% vs >60: 29%) and PI3K (18-39: 46% vs >60: 62%). In patients with any distant metastases, we calculated the metastatic burden, or the number of distant metastases reported in key sites of interest. Patients with a history of adrenal Metastasis had a higher metastatic burden (49/61, 80.3% with at least 4 distinct sites recorded) than those with no adrenal metastasis recorded (326/764, 42.6% with at least 4 distinct sites recorded). Conclusions: The GENIE BPC cohort provides a comprehensive clinico-genomic dataset enriched with younger patients with BC, providing a valuable source to improve our understanding of age-related clinical and genomic characteristics and their impact on real-world patient outcomes. Citation Format: Evan Seffar, Brooke Mastrogiacomo, Alex Paynter, Protiva Rahman, Jesus Fuentes Antras, Sonya A. Reid, Nikolaus Schultz, Michael J. Hassett, Ben Park, Shawn Sweeney, Walid K. Chatila, Pedram Razavi. The GENIE BPC BRCA Cohort: a real-world repository of standardized clinical and genomic data for young patients with breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1118.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".