Whole genome and transcriptome profiling in advanced pancreatic cancer patients on the COMPASS trial
Bibliographic record
Abstract
Integrated whole genome and transcriptome sequencing can unveil distinct molecular subgroups in pancreatic cancer (PDAC). The COMPASS trial (NCT02750657) enrolled 268 patients with advanced PDAC; patients were given either modified (m) FOLFIRINOX or Gemcitabine-nab-paclitaxel (GnP) as per physicians choice. Median follow-up is 52 months and median overall survival in those receiving mFOLFIRINOX is 10.6 months and 8.4 months for GnP. KRAS specific mutants and allelic states alone are not prognostic; however basal-like PDAC are more likely to harbour major imbalances in mutant KRAS (KRASmaj). In the presence of KRASmaj, pre-existing type II DM is more common. Distinct prognostic cohorts include homologous-recombination deficient PDAC, predictive of mFOLFIRINOX response. Basal-like PDAC and patients exhibiting evidence of systemic inflammation as annotated using the Gustave Roussy Immune Score are unique poor prognostic cohorts. The latter associates with low CD8 T cell infiltration while basal-like PDAC documents an inflamed tumour microenvironment. The COMPASS trial is a prospective observational study seeking to establish biomarkers in advanced pancreatic cancer through in-depth profiling prior to commencing chemotherapy. Here, the authors report the final data for the complete cohort of 268 patients enrolled in the COMPASS trial.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".