Abstract A050: Enhancing immune checkpoint inhibitor efficacy by targeting neurotrophic receptor tyrosine kinase 1 signaling in immune resistant non-small cell lung cancer patients
Bibliographic record
Abstract
Abstract Introduction: The FDA’s approval of immune checkpoint inhibitors (ICI) in 2015 drastically changed the survival of late-stage non-small cell lung cancer (NSCLC) patients. However, only about 30% of NSCLC patients respond to treatment, while the other 70% are immune resistant. Through an analysis of 424 NSCLC patients at Atrium Wake Forest, we have identified a loss-of-function mutation in Neurotrophic Receptor Tyrosine Kinase 1 (NTRK1) as a biomarker for response to ICI. We hypothesize that by treating wild-type immune-resistant tumors with Entrectinib, we can mimic the effect of the mutation in NTRK1 and induce immune responses. Methods: To identify biomarkers, we collected genomic sequencing data and comprehensive clinical characteristics on 424 NSCLC patients who received ICI or chemo-ICI treatment at Atrium Health Wake Forest Baptist. To determine the role of NTRK1 in vivo, we implanted LL/2-scramble (wild-type NTRK1) or LL/2-shNTRK1, which diminished NTRK1, into C57/B6 mice. The animals were injected with either IgG or Anti-PD1. To determine if we could mimic the effect of a mutation in NTRK1, C57/B6 mice were inoculated with LL2-wildtype NTRK1 and treated with either a) IgG, b) Entrectinib, c) Anti-PD-1, or d) Anti-PD-1 + Entrectinib. All in vivo experiments had tumor growth monitored, and a flow cytometry panel was performed at the endpoint to understand the immune responses. Bulk RNA-Sequencing was performed on cell cultures and tumors. Results: Mice given the LL/2-shNTRK1 responded to Anti-PD-1 treatment and had a significant increase in CD4+ stem-like effector T cells in the spleen and tumor-draining lymph nodes. Animals that were inoculated with the LL/2 cell lines and treated with Anti-PD-1 + Entrectinib also responded. Mice treated with Anti-PD-1 + Entrectinib were found to have a significant increase in CD4+ stem-like effector T cells as well. RNA-Sequencing revealed that in the mutant cell line LL/2-shNTRK1 and LL/2 tumors treated with Anti-PD-1 + Entrectinib, there was a significant upregulation of C3 production. Conclusion: Our studies demonstrate that the loss of NTRK1 function, through either genetic ablation or enzymatic inhibition combined with Anti-PD-1, provides a potent treatment for immune-resistant NSCLC tumors. Citation Format: Margaret R Smith, Yuezhu Wang, Caroline B. Dixon, Ralph D'Agostino, Yin Liu, George C. Oliver, Lance D Miller, Umit Topaloglu, Michael D Chan, Micahel Farris, Jing Su, Kathryn F Mileham, Wencheng Li, Jason M. Grayson, Thomas Lycan, Fei Xing. Enhancing immune checkpoint inhibitor efficacy by targeting neurotrophic receptor tyrosine kinase 1 signaling in immune resistant non-small cell lung cancer patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A050.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".