Comprehensive genomic analysis in metastatic pancreatic ductal adenocarcinoma (PDAC).
Bibliographic record
Abstract
285 Background: In the absence of defined tumor molecular subtypes and validated predictive markers, PDAC has been largely treated as a single disease. Recent studies of molecular subtyping in PDAC reveal a complex mutational landscape with data suggesting the presence of genomic and gene expression signatures that may have prognostic and therapeutic significance. These studies predominantly focused on resected PDAC and lack data on metastatic tumors. We aim to explore the clinical utility of whole genome sequencing (WGS) and transcriptome analysis from metastatic biopsy samples in patients (pts) with advanced PDAC. Methods: Pts with incurable advanced cancers undergo tumor biopsy for in-depth WGS and RNA sequencing (RNASeq) as part of an ongoing prospective study (NCT02155621). Comprehensive bioinformatics analysis is performed to identify somatic cancer aberrations, gene expression changes and cellular pathway abnormalities. Here we describe clinical and molecular data on the subset of pts with advanced PDAC. Results: Sixteen PDAC pts have been enrolled; median age 59 years, 8 males (50%), 10 with de novo metastases (63%). Full WGS and RNASeq were completed in 11 pts (1 failed biopsy, 4 had insufficient tumor). KRAS codon 12 and TP53 mutations were present in all but one pt. CDKN2A and SMAD4 were also frequently altered (7 and 4 pts respectively). Gene expression analysis for classical and basal subtypes similar to those recently described (PMID 26343385) identified 3 and 6 pts with classical and basal expression patterns respectively, and 2 pts with mixed expression. Overall survival (OS) was significantly worse for the basal subtype vs all others (median OS 7 vs. 13.9 months (ms), p = 0.017). When separated into 3 subtypes a significant difference was still noted (median OS 7 ms in basal, 19.2 ms in classical and 11.8 ms in mixed subtype, p = 0.032). Conclusions: WGS analysis demonstrated a similar mutation pattern to that described in resectable PDAC, with no novel actionable mutations identified. Gene expression analysis demonstrated the presence of distinct gene expression signatures significantly associated with outcome, despite small pt numbers. These results need to be validated prospectively in larger cohorts. Clinical trial information: NCT02155621.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".