Abstract P6-19-01: Evaluation of multiple transcriptomic gene risk signatures in male breast cancer
Bibliographic record
Abstract
Abstract Introduction: Male breast cancer (MBC) is a rare disease accounting for less than 1% of all breast cancers (BC) and 1% of all cancers in males. The clinical management is largely extrapolated from female BC. Several multigene assays are increasingly used to guide clinical treatment decisions in female BC, however there is little data on the utility of these tests in MBC. Methods: Here we present the gene expression results of 380 M0, ER+ve, HER2-ve MBCs enrolled in the Part 1 (retrospective joint analysis) International Male Breast Cancer Program of 1483 patients diagnosed between 1990-2010 (Cardoso et al. Annals of Oncology, 2018). Using a custom Nanostring™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDx® and Mammaprint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by Bayani and Yao et al (npjBreast Cancer, 2017). Survival outcomes by risk classification were analyzed using Cox models with time-dependent covariates when the proportional hazard assumption was not met and adjusted for clinical and treatment variables. Results: Prosigna-like risk scores identified 99 (26.1%) as low-risk, 159 (41.8%) as intermediate-risk, and 122 (32.1%) as high-risk. Using the TAILORx cut-off (25) for OncotypeDx-like risk of recurrence scoring, 158 (41.6%) were identified as low-risk, while 222 (58.4%) were identified as high-risk. MammaPrint-like results identified 175 (46.1%) as low-risk and 205 (53.9%) as high-risk. Overall, patients classified as high-risk had higher grade, more nodal involvement, larger tumors, and more frequently treated with chemotherapy than low-risk patients. Survival analyses demonstrated clear clinical utility for each test, showing patients at high-risk with poor relapse-free survival (RFS) as compared to patients classified as low-risk: Prosigna-like RFS at 3-years (HR=2.20, 95% CI, 1.28-3.80); Oncotype-like RFS at 3-years (HR=1.92, 95% CI, 1.17-3.17); MammaPrint-like RFS (HR=1.51, 95% CI, 1.00-2.27); with similar findings for distant relapse-free survival (DRFS) and overall survival (OS). Across outcomes and all gene signatures, patients with concordant Low/Low risk classification had better prognosis than those with concordant High/High risk classification. PAM50 intrinsic subtyping identified 147 (38.7%) as Luminal A, 57 (15.0%) as Luminal B, 80 (21.1%) as Her2-enriched and 96 (25.3%) as Basal-like; showing overall 34.5% concordance to clinic-pathological subtyping by central pathology (95% CI, 29.7%-39.5%). Comparison between the tests in the MBC cohort and a comparable cohort of female BC from the Tamoxifen Exemestane Adjuvant Multinational (TEAM) trial processed in the same way will be presented. Conclusion: Common transcriptomic assays designed to assess residual risk, validated in female BC, provide similar information in male BC patients. Not surprisingly, disagreement between test results at the individual patient level was observed. To our knowledge, this is the largest study of MBC assayed to generate risk scores of the current commercial BC tests to demonstrate their clinical utility and their differences and similarity to female BC. This work has been funded by the Breast Cancer Research Foundation (BCRF). Citation Format: Bayani J, Poncet C, Yao CQ, Crozier C, Anouk N, Piper T, Cunningham C, Sobol M, Aebi S, Benstead K, Bogler O, Dal Lago L, Fraser J, Hilbers FH, Hedenfalk I, Korde L, Linderholm B, Martens J, Middleton L, Murray M, Kelly C, Nilsson C, Nowaczyk M, Peeters S, Peric A, Porter P, Schröder C, Rubio IT, Ruddy KJ, van Asperen C, Van Den Weyngaert D, van Deurzen C, van Leeuwen-Stok E, Vermeij J, Winer E, Boutros PC, Giordano SH, Cardoso F, Bartlett JM. Evaluation of multiple transcriptomic gene risk signatures in male breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-19-01.
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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 | 0.001 | 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) | 0.003 | 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".