Abstract PO-079: The impact of statin use on anti-PD-1 monotherapy for recurrent head and neck squamous cell carcinoma
Bibliographic record
Abstract
Abstract While anti-PD-1 monoclonal antibody (mAb) therapy has become standard of care for the treatment of recurrent head and neck squamous cell carcinoma (HNSCC), a majority of patients do not benefit from this immunotherapy. Metabolic changes in the tumor microenvironment may contribute to PD-1 resistance by affecting the tumor microenvironment (TME). Using matrix-assisted laser desorption ionization (MALDI) mass-spectrometry imaging (MSI), we examined the metabolic landscape of a syngeneic murine MEER HNSCC model upon anti-PD1 therapy. We validated the findings in a clinical dataset of patients with HNSCC who were treated with anti-PD-1 mAb monotherapy. Using MEER tumors treated with anti-PD-1 therapy or control and MEER PD-1 resistant tumors treated with anti-PD-1 or control antibodies, we investigated the metabolism in the TME. Tumors were harvested from the mice after 10 days of treatment, slow frozen over liquid nitrogen immediately after resection, and sections were cut onto glass slides. The slides were then subjected to MALDI-MSI on a Bruker SolariX XR 12T Hybrid QqFT-ICR mass spectrometer. Discriminant analysis results showed that 2-Lysophosphatidylcholine and many intermediates in the lipid metabolism pathway were significantly enriched in the anti-PD-1 treated parental tumors compared to the untreated group. While analysis of the PD-1-resistant treated versus untreated tumors showed differential enrichment of a wide variety of metabolites involved in multiple metabolic pathways, the results were notable for greater enrichment of cholesterol in the treated PD-1 resistant tumors. This suggested cholesterol metabolism (that can be targeted by statins) may impact response to anti-PD1. Therefore, we assessed prevalence of statin use and its impact on oncologic outcomes in a single-center retrospective cohort of N=48 patients treated with anti-PD-1 mAb monotherapy. In n=28 patients who previously failed platinum therapy, statin use was associated with a significantly reduced overall survival (p=0.0064) and reduced progression free survival (p=0.0142). From within the monotherapy patient cohort, n=23 patients underwent multiplex imaging to characterize the intratumoral immune profile immediately prior to treatment initiation. Interestingly, patients on statin treatment had a lower mean ratio of CD8+ T-cells to T-regs of 1.14, compared to 2.27 in non-statin users, though not statistically significant (p=0.37). The mean neutrophil to lymphocyte ratio (NLR) in patients just prior to treatment with anti-PD-1 mAb monotherapy was significantly lower in patients on statins with a mean NLR of 5.96 compared to 12.54 in patients who were not receiving statins (p=0.047). These findings suggest a more immunosuppressive tumor landscape in patients who are receiving statins at the time of their anti-PD-1 therapy. Further studies using the MEER mouse model are in progress to validate these findings, but preliminary tumor volume results indicate that statin treatment in combination with anti-PD-1 therapy attenuates the mAb therapy’s tumor effect. Citation Format: Chareeni Kurukulasuriya, Abdulkader Yassin-Kassab, William Andrews, Maureen Kane, Greg Delgoffe, Dan Zandberg, Nicole Scheff, R. Alex Harbison, Umamaheswar Duvvuri. The impact of statin use on anti-PD-1 monotherapy for recurrent head and neck squamous cell carcinoma [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-079.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".