Abstract PR-17: Genomic and transcriptomic characterization of pancreatic cancer patients on the PASS-01 trial
Bibliographic record
Abstract
Abstract Overall survival for patients with advanced PDAC remains less than 1 year. Biomarkers are needed to select chemotherapy regimens, either alone or in combination with novel agents. PASS-01 compared mFOLFIRINOX and Gemcitabine/nab-Paclitaxel in a phase II randomised control trial while prospectively exploring tissue, liquid and organoid biospecimens to interrogate putative biomarkers of chemotherapy response and resistance. Methods PASS-01 was conducted across 6 sites in North America. Patients with de novo metastatic disease and a lesion amenable to core biopsy were included. Cases with germline pathogenic variants in BRCA1/2 or PALB2 were excluded. Up to 6 core biopsies were obtained with priorities for clinical diagnosis, patient derived organoids (PDOs), and whole genome and transcriptome sequencing (WGTS). WGTS were performed at a single site following laser capture microdissection. WGS reports were clinically (CAP) accredited and annotated mutations, copy number alterations, mutational signatures, TMB and structural variant patterns. KRAS allelic states were documented with major imbalances in mutant KRAS (KRASmaj) defined as mutant: WT copy number >3. Transcriptomic subtypes (classical vs. basal-like) were classified as previously described (Moffitt et al., 2015). WGTS results were discussed at a molecular tumor board with PDO pharmacotyping to determine best second line options. Results: 160 patients were included in the intention to treat population, of these WGS was available in 127 (79%) and additional NGS reports in 20 (13%). RNA-seq was successful in 119 (74%) and the basal-like subtype accounted for 29% and was associated with inferior outcomes. KRASm were evident in 91% and KRASG12D represented 45%. Tumor suppressors TP53, CDKN2A and SMAD4 were lost in 81%, 76% and 39% respectively. MTAP deletion was present in 40%, largely synonymous with CDKN2A deletions. Commonly co-altered genes in the dataset included epigenetic regulators (ARID1A, KMT2C, KDM6A) and TGFBR2. KRASmaj was present in 30% of cases and polyploid tumors in 50%. 50% of basal-like PDAC harboured KRASmaj compared to 22% of classical PDAC, p<0.01. Dominant signatures (SBS) included age related SBS1, 5 and 8. Additionally, we saw a prevalence of SBS17 and APOBEC SBS2/13, signatures which occurred more frequently compared to a similarly characterised resected cohort. Unstable genotypes were present in 24% with somatic-HRD evident in 3%. Of KRASWT PDAC, 58% harboured class I-II BRAF variants. KRAS WT PDAC had fewer co-mutations and in one case where an NGS report did not find a driver, a novel fusion in SLC4A4-RASGRF2 was identified. 28 molecular tumor boards took place throughout the trial influencing 50% obtaining a 2nd-line treatment. Conclusion: The PASS-01 cohort exhibits a heterogeneous group of genotypes and molecular subgroups. Certain mutational processes are more evident in advanced compared to resected PDAC. The impact of subgroups on survival and chemotherapy response is ongoing with a planned data lock on July 15th. Results will be presented at the meeting. Citation Format: Grainne M O'Kane, Gunho Jang, Trevor J Pugh, Julie Wilson, Stephanie Ramotar, Daniel A King, Dan Laheru, Ken H Yu, Kimberly J Perez, Amber Habowski, Erica S Tsang, Robert C Grant, Andrew J Aguirre, Raymond W-J Jang, Craig E Devoe, Eileen M O'Reilly, Anna Dodd, Brian M Wolpin, Xiang Y Ye, Elizabeth M Jaffee, David Tuveson, Steven Gallinger, Jennifer J Knox, Faiyaz Notta. Genomic and transcriptomic characterization of pancreatic cancer patients on the PASS-01 trial [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr PR-17.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".