Abstract P1-05-27: Evaluation of the Oncomine focus and comprehensive assays for therapeutic stratification in early hormone receptor positive breast cancers
Bibliographic record
Abstract
Abstract Large-scale sequencing initiatives have revealed a wealth of common and novel variants as well as copy-number aberrations, across different solid tumours and hematological malignancies. The growing list of variants/aberrations can sometimes be matched to specific therapeutics. Such “actionable mutations/changes” hold promise for personalized treatment, as treatments could be tailored to molecular abnormalities, rather than disease site. In breast cancer, women with hormone positive early breast cancer continue to experience improved survival on adjuvant anti-hormone therapy, but even today, a significant number of women continue to progress. Therefore there is not only a need to identify those women for whom current therapies are insufficient, but to identify alternative therapeutic interventions. The ThermoFisher Scientific Oncomine™ Focus and Oncomine™ Comprehensive Assays (OFA and OCA) are based on the Ion Torrent™ next-generation sequencing platform and Ion AmpliSeq™ library preparation technology, coupled to the Oncomine™ Knowledgebase, for target selection, variant calling, and data annotations. Both panels interrogate the most referenced oncology biomarker variants that are matched to curated published evidence from clinical trials supporting the matching of driver genetic variants with relevant potential clinical therapeutic options. The ability to identify SNVs, CNVs and fusion events in a single assay provides an unprecedented approach to maximizing the molecular information to be derived from a single tumour sample. To explore the value of the Oncomine™ assays in early invasive breast cancers, we have performed a pilot study to assess the reproducibility and accuracy of the OFA and OCA from nucleic acids extracted from formalin-fixed paraffin embedded tissues. In addition to the sequencing and copy-number data generated by these assays, we will compare these results to copy-number information generated using the Oncoscan® (Affymetrix)copy-number assay as well as information derived by Multiplex Ligation-dependent Probe Amplification-based panels (MRC-Holland) and Fluorescent in situ Hybridization (FISH). Our preliminary analyses of 35 invasive breast cancers by Oncoscan® identified the frequent whole chromosomal gains of 2, 3, 5, 7, 18, 19 and 20; gains of 1q, 7p, 8q, 11p, 16p, 17q; losses at 1p, 8p, 11q, 13, 16q, 17p and chromosome 18. High level amplifications were also identified for breast cancer related genes such as ERBB2, CCND1, MYC, FGFR1; in addition to the frequent losses of TP53, RB1, CDKN2A. Copy-number changes were confirmed by locus-specific FISH and MLPA. Data generated from the OFA and OCA from these same samples will be compared to the other platform findings and provide a snapshot of the mutational landscape of early breast cancers across these pan-cancer panels. Having established the robustness and accuracy of the assays, the applicability of the OCA in the context of improved stratification for breast cancers for prognostic and predictive tests will be discussed. Citation Format: Bayani J, Crozier C, Zhang NX, Amemiya Y, Quintayo MA, Yan FJ, Dion D, Mccormack S, Yaffe M, Seth A, Feilotter H, Bartlett JMS. Evaluation of the Oncomine focus and comprehensive assays for therapeutic stratification in early hormone receptor positive breast cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-27.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".