Abstract P5-10-02: A copy number aberration driven endocrine response gene signature stratifies risk in estrogen receptor positive breast cancer
Bibliographic record
Abstract
Abstract Background: Many prognostic gene signatures have been developed for estrogen receptor positive (ER+) breast cancer (BC); however, most have been solely based on mRNA expression data without integrated information on underlying primary drivers such as genomic aberrations. We therefore coupled gene expression and copy number aberration (CNA) in an attempt to improve upon prognostic signatures for ER+ BC. Methods: mRNA expression based discovery was conducted between 172/59 ER+ BC with low/high Ki67 levels after neoadjuvant aromatase inhibition and significant genes (significance analysis of microarray, q-value less than 0.05) were screened by correlation (Mann-Whitney-Wilcoxon test P less than 0.05) with CNA using Agilent comparative genomic hybridization array. Further interrogation on prognosis of relapse-free survival (RFS) by univariate survival analysis (P less than 0.05) in patients treated with adjuvant endocrine monotherapy from a public data set produced a Copy Number Aberration Driven Endocrine Response (CADER) signature consisting of treatment sensitive/resistant genes. MetaCore (GeneGo Inc) pathway analysis was conducted for enriched pathways. We subsequently applied Nanostring nCounter technology to formalin fixed archival tumor RNA from 620 ER+ adjuvant tamoxifen treated BC (UBC TAM-series) for CADER gene profiling. Patients in multiple independent public data sets and the TAM-series were classified into treatment sensitive defined by up-regulated sensitive gene centroid and down-regulated resistant gene centroid by the median cutoffs, treatment resistant defined with the reverse pattern and indeterminate otherwise. CADER risk stratifications were associated with patient survival outcomes in public cohorts and the TAM-series. The Kaplan-Meier (KM) analysis and Cox models were used for survival analysis. Published PAM50 intrinsic subtypes and subtype based risk of relapse (ROR-S) assignments were used (Nielsen CCR 16:5222, 2010). Results: A 54-gene CADER signature, 27 resistant/27 sensitive genes, was derived. Pathway analysis indicated that CADER was enriched with sensitive genes of cell survival functions while resistant genes were largely drivers of cell cycle progression. CADER stratifications were significantly prognostic of relapse free survival (RFS) in all public cohorts (log rank test P=0.05 for all) and in the UBC TMA-series (P=0.0001, BC specific survival and RFS). CADER showed an additional value (likelihood ratio test P=0.05) in all cohorts when both standard clinical variables and ROR-S were incorporated in multivariate Cox models. CADER were highly concordant with intrinsic subtypes and ROR-S (p=0.0001) in all data sets. However, CADER may stratify risk within ROR-S medium risk patients (P=0.002 METABRIC; P=0.003 and 0.036 in TAM-series for BC specific survival and RFS). Conclusions: We have developed a signature that is prognostic of long-term survival in postmenopausal BC, further splits risk within ROR-S medium risk group and identifies some highly resistant BC in presence of ROR-S and clinical variables (see Ellis et. al. abstract for evaluation of a CADER single sample predictor in the MA12 Phase 3 clinical trial). Citation Format: Jingqin Luo, Li-Wei Chang, Yu Tao, Jeremy Hoog, Samuel Leung, Torsten O Nielsen, Matthew J Ellis. A copy number aberration driven endocrine response gene signature stratifies risk in estrogen receptor positive breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P5-10-02.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".