Abstract 541: PARP and autophagy inhibition synergy in small cell lung cancer
Bibliographic record
Abstract
Abstract Purpose: Small cell lung cancer (SCLC) is a high-grade neuroendocrine carcinoma comprising 15% of lung cancers. First-line treatment with platinum and etoposide chemotherapy—and radiotherapy for limited stage disease—produces good initial response, but most patients suffer treatment-resistant relapse within 2 years. The median survival is under 10 months, with immunotherapy increasing this by about 2 months. This regimen has changed minimally in 3 decades, fueling a need for more effective therapies. Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) effectively induce DNA damage in SCLC and have shown potential in this setting, but response is variable, so we aimed to identify mechanisms through which SCLC may be sensitized to PARPi therapy. Methods: CRISPR dropout screens were conducted using the Toronto KnockOut v1 (TKOv1) CRISPR library in the SBC5 and H82 SCLC cell lines, with the PARPi, olaparib, as the selection pressure. DNA sequencing was performed at days 25 and 35 for SBC5 and days 28 and 39 for H82. Top hits were identified by gene dropout in the olaparib condition versus the control, with a false discovery rate (FDR) cutoff of 0.05. Gene ontology analysis was used to identify critical pathways. Stable shRNA knockdown cell lines were generated using lentiviral transduction and validated by Western blot. Cells were treated with olaparib and assayed for viability with CellTiter-Glo 2.0. In wild-type cell lines, therapeutic mTOR activation with MHY1485 was validated by Western blot and therapeutic autophagy inhibition with chloroquine (CQ) or GNS561 was validated by Western blot after 3 hours starvation in EBSS medium. Efficacy of autophagy inhibitors alone and in combination with PARPi was assayed by cell viability, and SynergyFinder+ was used to quantify synergism of the combination. Results: CRISPR screening identified mTOR pathway regulators, including components of the TSC and GATOR1 complexes, and gene ontology analysis indicated downregulation of TOR signaling and upregulation of autophagy as key pathways which confer PARPi sensitivity when lost. TSC1/2 knockdown cell lines exhibit reduced viability after PARPi treatment. MHY1485 treatment blocked autophagy as indicated by LC3B-II accumulation, but combination therapy with MHY1485 and olaparib was antagonistic due to proliferative effects of MHY1485. CQ or GNS561 treatment also blocked autophagy, and SCLC cell lines had varying sensitivity to these agents as monotherapies. Autophagy inhibition synergized with PARPi, sensitizing SCLC cell lines to PARPi therapy. Conclusions: TSC1/2 knockdown sensitizes SCLC cell lines to PARPi in concordance with our model that mTOR downregulation promotes autophagy and cell survival after PARPi therapy. While mTOR upregulation was antagonistic with PARPi and promoted cell growth, autophagy inhibitors were a superior therapeutic approach, synergizing with PARPi in vitro. Citation Format: Tony Yu, Ranya Barayan, Lifang Song, Vidhyasagar Venkatasubramanian, Sree N. Nair, Vivek Philip, Benjamin H. Lok. PARP and autophagy inhibition synergy in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 541.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".