Abstract B81: Gene expression analysis demonstrates prognostic subtypes in metastatic pancreatic ductal adenocarcinoma (PDAC)
Bibliographic record
Abstract
Abstract 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 [1-4] reveal a complex mutational landscape with data suggesting the presence of genomic and gene expression signatures that may have prognostic and therapeutic significance. However, most of these PDAC datasets consisted of resected tumors, cell lines or xenografts and lack data on metastatic tumors. The aim of this study is to evaluate gene signatures using whole genome sequencing (WGS) and transcriptome (RNA-Seq) data from metastatic biopsy samples in patients with advanced PDAC. Methods: Patients with incurable advanced cancers undergo fresh tumor biopsies for indepth WGS and RNA sequencing as part of an ongoing prospective study (NCT02155621). DNA and RNA extraction and library construction were performed according to standard protocols. Paired-end reads were generated on an Illumina HiSeq2500 sequencer. RNA-Seq expression values were converted into centile expression ranks against the TCGA PDAC dataset. Centile distributions for genes in published signatures were compared by pairwise Wilcoxon-Mann-Whitney tests using one-sided p=0.1 as the significance cutoff. Survival analysis was performed using the Kaplan-Meier method. Results: Molecular data is available for 12 patients with metastatic PDAC; median age 63 years, 6 males, 8 with de novo metastatic disease (67%). 10 tumor samples (83%) were obtained from liver biopsies; average tumor content was 41% (range 24-51%). The average number of structural variants per sample was 125 (range 40-271). Rearrangement-based subtypes [3] were distributed as follows: stable (n=3), locally rearranged (n=1), scattered (n=7) and unstable (n=1). 1 patient harbored a germline BRCA1 185delAG founder mutation but had a stable genotype. Gene expression analysis for classical and basal subtypes similar to those recently described [4] identified 3 and 7 patients with classical and basal expression patterns respectively. Gene signatures were undetermined for 2 patients, where no significant difference in expression of classical or basal signature genes was noted. At median follow-up of 16.7 months, 8 patients had died. Median overall survival was 19.1 vs 7 months in patients with classical and basal subtypes respectively (p=0.078). Conclusion: Despite small patient numbers, gene expression analysis demonstrated the presence of distinct signatures in metastatic PDAC, with a trend towards worse outcomes for patients with a basal expression subtype. Future challenges include prospective validation in larger cohorts, standardization of RNA data acquisition and analysis, and better definition of prognostic and predictive signatures that may be of clinical utility in metastatic PDAC. References 1. Collison E, et al. Nat Med. 2011 [PMID: 21460848] 2. Biankin A, et al. Nature. 2012 [PMID: 23103869] 3. Waddell N, et al. Nature. 2015 [PMID: 25719666] 4. Moffitt R, et al. Nat Genet. 2015 [PMID: 26343385] Citation Format: Hui-li Wong, Joanna M. Karasinska, Martin Jones, Peter Eirew, Kasmintan Schrader, Howard Lim, Yaoqing Shen, Steven Jones, Stephen Yip, Janessa Laskin, Marco Marra, David F. Schaeffer, Daniel J. Renouf.{Authors}. Gene expression analysis demonstrates prognostic subtypes in metastatic pancreatic ductal adenocarcinoma (PDAC). [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B81.
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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 | 0.001 | 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 | 0.000 |
| 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".