Genomics-driven precision medicine for advanced pancreatic ductal carcinoma (PDAC): Early results from the COMPASS trial (NCT02750657).
Bibliographic record
Abstract
211 Background: COMPASS is a prospective study with the primary aim to identify predictive mutational and transcriptional features in advanced PDAC for improved patient stratification and treatment selection. Methods: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy for whole genome sequencing (WGS) and RNA sequencing (RNASeq). Fresh tumor tissue was acquired by image guided percutaneous core needle biopsy of locally advanced primary or metastatic tumors. Laser capture microdissection was performed for all cases to ensure high-resolution genomic analyses. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures. Results: Of 63 patients who underwent a tumor biopsy between December 2015 and June 2017, WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range 19-52 days) from biopsy, meeting the primary feasibility endpoint. Three patients with an ‘unstable’ genomic subtype, including two with a novel ‘duplicator’ phenotype, responded well to m-FOLFIRINOX. Of two cases with the same germline BRCA2 mutation, only the chemotherapy responder had loss of heterozygosity and genomic hallmarks of double stranded break repair deficiency. Approximately 25% of tumors displayed the basal-like RNA expression signature and these were chemotherapy resistant, with tumor shrinkage mainly observed in those with the classical RNA subtype (P = 0.003). Thirty percent of patients had potentially actionable genetic alterations. Conclusions: Prospective comprehensive genomic profiling of advanced PDAC is feasible and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes providing the impetus for further studies. Clinical trial information: NCT02750657.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".