Abstract 3888: Molecular profiling of sequential biopsies in patients with metastatic colorectal cancer identifies genomic alterations that evolve during first-line therapy and could have therapeutic implications: A prospective study to identify molecular mechanisms of clinical resistance (QCROC-01: NCT00984048).
Bibliographic record
Abstract
Abstract Therapeutic resistance remains a major obstacle in metastatic colorectal cancer (mCRC) and biomarkers to guide treatment are essential to improving survival and quality of life in mCRC patients. A biopsy-driven prospective study was designed to identify biomarkers and mechanisms of resistance to a standard first-line therapy in patients with mCRC which could be useful in guiding treatment selection (QCROC-01; NCT00984048). We also hoped to recognize molecular changes over time, or resulting from the selection pressure of treatment, which could have implications for subsequent therapy. This study is ongoing and approved at thirteen sites with one-hundred patients enrolled so far. Patients with mCRC receiving FOLFOX (5-fluorouracil, leucovorin and oxaliplatin) with bevacizumab consented to three needle core tumour biopsies at pre-treatment and at the time of resistance. The rate of both patient and physician acceptance of biopsies has steadily risen with time and experience. Serial bloods were also collected for proteomic analysis and circulating tumor DNA. Twenty-five biopsy samples were profiled using exome sequencing (tumor and germ line), RNAseq, low pass genome sequencing and miRNA analysis. Differential gene expression analysis revealed signatures associated with clinical response and resistance when comparing tumours obtained pre- and post-treatment. We detect changes in variant allele fraction including both depletion and enrichment of individual somatic mutations over the course of treatment, the latter of which may indicate subclonal and acquired “driver” mutations that confer therapeutic resistance. A small number of genes show recurrent evidence for changes in clonal enrichment at the time of relapse across multiple patients. These could also represent therapeutic targets for subsequent therapy for these patients, and as such, represent new treatment opportunities. Our findings provide insights into tumor evolution during first-line chemotherapy of mCRC that may hold clues to optimize current first-line therapeutic decision making and identifies potential target pathways for second-line stratification of patients. This study is part of the Canadian Colorectal Cancer Consortium which is a multi-site collaboration funded by the Terry Fox Research Institute and le fonds de recherche du québec - santé. Citation Format: Suzan McNamara, Ryan Morin, Mathilde Couëtoux du Tertre, Rosemary McCloskey, Rebecca Johnston, Daniel Fornika, Benoit Samson, Bernard Lespérance, Thierry Alcindor, Yoo-Joung Ko, Richard Dalfen, Eve St-Hilaire, Lucas Sideris, Felix Couture, Hans Prenen, Sabine Tejpar, Ronald Burkes, André Constantin, Errol Camlioglu, Adriana Aguilar, Adrian Gologan, Benoit Têtu, Celia M. Greenwood, Cyrla Hoffert, Samia Qureshi, Zuanel Diaz, Maud Marques, Micheal Witcher, Thérèse Gagnon-Kugler, Petr Kavan, Gerald Batist. Molecular profiling of sequential biopsies in patients with metastatic colorectal cancer identifies genomic alterations that evolve during first-line therapy and could have therapeutic implications: A prospective study to identify molecular mechanisms of clinical resistance (QCROC-01: NCT00984048). [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3888. doi:10.1158/1538-7445.AM2015-3888
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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 | 0.001 |
| 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) | 0.002 | 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".