Abstract P2-05-12: Signatures of endocrine resistance in the tamoxifen and exemestane adjuvant multinational trial (TEAM)-UK cohort
Bibliographic record
Abstract
Abstract Introduction: There are a number of commercially-available tests to stratify risk for women diagnosed with early breast cancer. While such "Generation I" tests are increasingly being used, a consensus is growing that these tests are moderately accurate in assessing risk. Moreover, Generation I tests fail to direct more personalized treatment. There exists, therefore, a clear need for more informative "Generation II" tests that have theranostic targets. To this end, we have performed an mRNA abundance-based analysis using the UK cohort of the TEAM trial to identify signatures of endocrine resistance, from which pathways for putative therapeutic intervention may be identified. Methods: RNA extracted from 790 patients in the UK-TEAM cohort were profiled using a 165-gene NanoString codeset. The gene list was compiled from targets that comprise many of the existing risk assessment tests, in addition to genes known to be of importance for breast cancer pathogenesis. Signal intensities were normalized using the R statistical environment; 336 different combinations of preprocessing methods were assessed and the most optimal method selected using unbiased criteria. Results: Univariate survival analysis revealed a number of significantly prognostic candidates. Using inter-gene correlation and consensus clustering, we identified five gene clusters. Not surprisingly, these clusters included a strong proliferation, hormone signalling and cell migration component. Derivation of risk scores using Cox proportional hazards model, with the inclusion of age and nodal status, generated a signature identifying patients with differences in distant relapse-free survival (DRFS). Moreover, the composition of the gene-list made it possible to characterize the patients into their intrinsic subtypes and to determine their relative risk for recurrence relative to assessment tools available today. The added value of subtyping and the gene clusters identified in this discovery cohort will be discussed. Conclusions: The impact of test-guided therapy using multi-parametric tests is increasingly being felt in the clinic, and is reshaping modern health-care economics. A successful Generation II multi-parametric test will better discriminate those that are truly at high risk for recurrence following endocrine therapy and offer potential therapeutic options for intervention for those who would not benefit from current modalities. Citation Format: Jane Bayani, Mary Anne Quintayo, Cindy Q Yao, Syed Haider, Cassandra Brookes, Paul C Boutros, John MS Bartlett, Daniel W Rea. Signatures of endocrine resistance in the tamoxifen and exemestane adjuvant multinational trial (TEAM)-UK cohort [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 P2-05-12.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".