Comprehensive genomic analysis of metastatic pancreatic ductal adenocarcinoma (mPDAC) reveals a significant proportion of clinical actionable aberrations.
Bibliographic record
Abstract
e15753 Background: Significant progress has been made in the understanding of the genomic landscape of PDAC, but the clinical utility of these data remains uncertain. Methods: As part of the BC Cancer Personalized Oncogenomics (POG) and PanGen studies (NCT02155621, NCT02869802), whole genome analysis and transcriptome sequencing were performed on fresh biopsy and blood sample from 48 mPDAC patients. Genomic findings informed therapy choices including potential eligibility for the CCTG PM.1 molecular basket trial (NCT03297606). Results: Cohort consists of 54.1% male, average age 57.6, 34/48 had ≥2 lines of treatment. 37/48 biopsies were from liver and 27/48 were collected pre-treatment. 8/48 (16.6%) patients had aberrations with strong evidence of clinical actionability. These include 2 germline BRCA2, 1 germline BRCA1, 1 somatic XRCC2 homozygous deletion with strong COSMIC signature 3, all predictive of platinum sensitivity. Patients with XRCC2 deletion and BRCA1 had over 2 years on FOLFIRINOX. Fusions affecting the NRG1 gene were identified in 3/4 patients with KRAS wildtype tumours, which may confer ERRB inhibitor sensitivity. 2/3 NRG1 fusion patients have thus far been treated with the ERBB inhibitor afatinib with radiographic responses noted in both patients. One patient had mismatch repair deficiency, and a high mutational burden, suggestive of immune checkpoint inhibitor sensitivity. Other possible actionable mutations include CCTG PM.1 trial potential eligibility: 4/48 with high homologous recombination defects and 1 germline ATM mutation loss (PARP inhibitor arm), 1/47 ERBB2 amplification (anti-HER2 arm), 2/47 high expression of FGFR1 (Sunitinib arm) and 1/47 with high FLT4 and IGF1R expression (Axitinib arm). Conclusions: More routine use of comprehensive genomic analysis should be considered in mPDAC given finding of high degree of actionability. Importantly, a significant proportion (16.6%) had findings with strong evidence of clinical impact.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".