Angiotensin-converting enzyme inhibitor prescription is associated with decreased progression-free survival (PFS) and overall survival (OS) in patients with lung cancers treated with PD-1/PD-L1 immune checkpoint blockers.
Bibliographic record
Abstract
e20512 Background: Angiotensin converting enzyme (ACE) inhibitors are used to treat hyperblood pressure and congestive heart failure. Preclinical evidence show that ACE has a role in both innate and adaptive responses thus suggesting a capacity of ACE to promote antitumor immunity. Interaction between ACE inhibitors and Immune checkpoint blockers (ICB) has not been investigated in cancer patients (pts). Our study evaluated the effect of ACE inhibitors in Non Small cell lung cancer (NSCLC) pts treated with PD-1/PD-L1 inhibitors. Methods: We conducted a retrospective multicohort retrospective analysis of pts treated with PD-1/PD-L1 inhibitors for NSCLC at Dijon Cancer Center, and at the University of Montreal Hospital. ACE inhibitors groups were defined as pts treated with ACE inhibitors given during the treatment with ICB. PFS and OS were compared between both groups among all pts. Statistical analyses were performed using the Kaplan-Meier method and Cox univariate analysis. Multivariate Cox regression analyses was used to adjust for classical prognostic factors. Tumor RNA sequencing were performed and CIBERSORT was used to estimate immune cell infiltration in ACE inhibitors group and None ACE inhibitors group. Results: Among 283 pts included (177 pts from Dijon, and 106 pts from Montreal), 27 (10%) received ACE inhibitors. ACE inhibitors group did not differ from None ACE inhibitors group for main clinical prognostic characteristics. However, ACE inhibitors group are more frequently treated with statin, beta blocker and metformin. ACE inhibitors group had shorter median PFS compared to None ACE inhibitors group : 2.5 vs. 3.8 months, p = 0.02 (HR = 1.7 IC95% 1.1-2.5 p = 0.02 Cox Univariate). The negative impact of ACE inhibitors group was maintained after multivariate analyses adjusting for risk factors (HR = 1.9 IC95% 1.1-3.5 p = 0.02 for PFS and HR = 2.3 IC95% 1.2-4.4 p = 0.01 for OS). RNA sequencing and CIBERSORT analysis underlines that ACE inhibitors group has lower M1 macrophage, activated Mast cells, NK cells and memory activated T cells thus suggesting an immunosuppressive state. Conclusions: ACE inhibitors prescription concomitant to the PD-1/PD-L1 inhibitors treatment impairs the outcome in patients with advanced NSCLC pts. This reduction is independent of classical prognostic factors. Biological date underlines an immunosuppressive state in ACE inhibitors group. These data should be validated in larger cohort.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".