Abstract 1377: The role of TIM3 and PD1 blockades in head and neck cancer
Bibliographic record
Abstract
Abstract Background: Our group has recently developed and validated a novel prognostic score for human papillomavirus (HPV+) oropharyngeal cancer called UWO3, which stratifies patients into low risk (immune rich), intermediate risk (immune mixed), and high risk (immune desert) groups. The high-risk immune desert group had a paucity of immune cells, however, that population of lymphocytes expressed high levels of the checkpoint molecule TIM3. To follow up on this, we assessed the therapeutic effect of anti-TIM3 mAb alone and in combination with anti-PD-1 in a syngenic murine HPV+ head and neck cancer model using the mERR. T-cell immunoglobulin mucin 3 (TIM3) and Programmed death 1 (PD-1) are negative immune checkpoint receptors that are expressed on tumor-infiltrating lymphocytes (TIL), play a crucial role in tumor-induced immune suppression. Given the critical role that the tumour microenvironment (TME) has on the prognosis of head and neck squamous cell carcinoma (HNSCC), immune checkpoint inhibitor immunotherapy approaches, specifically anti-PD1 and/or anti-TIM3 antibody therapy, may be very effective treatment strategies and may offer improved survival outcomes. Methods:Immunocompetent C57BL/6 mice were injected in one flank with the syngeneic mouse HPV+ cell line, mEERL (106 cells), for tumour generation. Mice were then treated with either IgG2a isotype control, anti-PD1 (200μg), anti-TIM3 (200 μg) antibodies or a combination of anti-PD-1 and anti-TIM3 were administered via intraperitoneal injection 3 times per week following tumour establishement for 6 weeks (n = 7 mice per arm, total of 28 mice). Tumour volumes were measured every 2 days. Three representative tumors from each treatment group were collected for bulk RNA sequencing, scRNA-seq, and flow cytometry to characterise immune cell populations and transcriptional changes and monitor their impact on the TME of HNSCC. Results:Anti-PD1 and anti-TIM3 both restricted tumour growth by size and weight relative to the IgG2a control (p<0.01, linear mixed model [lmm]). The combination of anti-PD1 and anti-TIM3 was more effective than either monotherapy alone (p<0.05, lmm). RNA sequencing analysis revealed differential abundance in CCL6, CCL9, CFD, and MAP3K5 transcripts relative to control for anti-PD1, anti-TIM3, and combination checkpoint inhibition. Conclusion:Targeting both PD-1 and TIM3 enhanced the anti-tumor immune response in HPV+ head and neck tumours, providing further support for dual targeting of these molecules for more effective cancer immunotherapy. Our results suggest that immune checkpoint inhibitor therapy (PD1 and TIM3 blockades) could be a promising treatment strategy for HPV+ HNSCC, and the expression of these immune checkpoint molecules could serve as a predictive biomarker of patient outcome in HPV+ HNSCC. Citation Format: Mushfiq Shaikh, Amir Karimi, Peter Zeng, Harrison Pan, John Barrett, Anthony Nichols. The role of TIM3 and PD1 blockades in head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1377.
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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 | 0.001 |
| 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".