Predictive value of germline <i>ATM</i> mutations in the CCTG PA.7 trial: Gemcitabine (GEM) and nab-paclitaxel (Nab-P) versus GEM, nab-P, durvalumab (D) and tremelimumab (T) as first-line therapy in metastatic pancreatic ductal adenocarcinoma (mPDAC).
Bibliographic record
Abstract
4135 Background: PA.7 evaluated whether combining PD-L1 and CTLA-4 inhibition with GEM and Nab-P increases efficacy. A previous analysis of the PA.7 data demonstrated high plasma based TMB (≥9 mut/Mb) was associated with improved OS in the Gem, Nab-P, D+T arm. DNA repair pathway aberrations beyond mismatch repair have been associated with potential immune sensitivity. We assessed the predictive value of germline ATM mutations in the PA.7 trial. Methods: This randomized phase II study (ClinicalTrials.gov NCT02879318) assessed the efficacy and safety of GEM, Nab-P, D, and T (arm A) vs. GEM and Nab-P (arm B) in patients (pts) with mPDAC (n = 180). The primary endpoint was overall survival (OS). Pre-treatment plasma was sequenced with the Predicine ATLAS next generation assay (600 gene, 2.4 Mb panel). 2-sided alpha set at 0.1. Results: 180 pts were randomized (119 to arm A and 61 to arm B) There was no significant difference in OS (9.8 months in arm A vs. 8.8 months in arm B, p-value 0.72) or PFS (5.5 months and 5.4 months respectively, HR 0.98, p-value 0.91). Plasma analysis was performed on 174/180 pts with available samples. 16/174 (9.2%) pts had germline ATM mutations, 12 in arm A and 4 in arm B. GEM, Nab-P, D+T was associated with improved OS in patients with ATM mutations (HR 0.10, 90% CI 0.03-0.37; median OS 13.9 months vs. 4.9 months) while no activity was seen in pts with ATM Wild Type (HR 0.99, 90% CI 0.73-1.33; median OS 9.79 months vs. 10.2 months); interaction p = 0.014. Germline ATM mutation status was independent of plasma TMB levels (Wilcoxon p = 0.76). Conclusions: Germline ATM mutation appeared predictive of benefit from the addition of dual immune checkpoint inhibitors (D and T) to Gem and Nab-P, with a significant interaction p-value. In addition to previous data from this trial regarding the predictive value of high plasma TMB (≥9 mut/Mb), this data further supports that there may be independent subgroups of PDAC, beyond MSI-H, that may benefit from immunotherapy, and trials evaluating immunotherapy in subgroups of PDAC with these profiles are warranted. Clinical trial information: NCT02879318.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".