Abstract PO-078: Tissue-resident memory CD8+ T cells correlate with anti-PD-1 response in head and neck cancer and expand upon cDC1 activation in tumor-draining lymph nodes to overcome PD-1 resistance
Bibliographic record
Abstract
Abstract Introduction: Tumor infiltrating tissue-resident memory CD8+ T (TRM) cells correlate with immunotherapy response against several solid tumor types. Recent data from neoadjuvant immunotherapy studies highlight CD8+ TRM cells as early responders in head and neck squamous carcinoma (HNSCC). Here, we defined anti-tumor CD8+ TRM cell representation in neoadjuvant anti-PD1 clinical trial HNSCC tumors and examined their development in anti-PD1 responsive and resistant HNSCC mouse models. Methods: CD8+ CD103+ TRM cells were quantified using CODEX (CO-detection by inDEXing) in tumor tissue microarray cores from 28 HNSCC patients treated with neoadjuvant anti-PD1 on a previously reported clinical trial (NCT02296684). Anti-PD1 sensitive MOC1 and isogenic anti-PD1 resistant MOC1-esc1 cells were engineered to express ovalbumin derived SIINFEKL peptide (OVA). OVA-specific CD8+ TRM induction and activation from endogenous T cells and following OT-1 adoptive transfer was evaluated in orthotopic (buccal) MOC1/MOC1esc1-OVA tumor bearing mice by ELISA and flow cytometry employing SIINFEKL-H2Kbdextramers. In vitro OVA-directed T cell activity was evaluated using co-culture of OT-1 T cells and MOC1/MOC1OVA/MOC1esc1OVA cells, OVA peptide, or IL-2. OT-1 CD8+ T cells were transferred into MOC1OVA or MOC1-esc1OVA-bearing mice and the dynamics of TRM development were evaluated using flow cytometry. Conventional Dendritic cells 1 (cDC1s) from tumor-draining lymph nodes (TDLNs) were cocultured with OT-1 cells and evaluated for antigen-specific TRM development. Results: CD8+ CD103+ TRM cells were more frequent in baseline tumors that developed pathological tumor response following neoadjuvant pembrolizumab compared to baseline nonresponding tumors (p=0.011). In mouse orthotopic models, MOC1-esc1OVA cells maintained in vivo PD-1 resistance despite eliciting SIINFEKL dextramer+ antigen-specific T cells in the tumors that expanded in response to PD-1 blockade. Further characterization of these tumor antigen specific T cells showed that compared to MOC1OVA, MOC1-esc1OVA had reduced CD69 and CD103 expression (MOC1OVA, Average 17.55% (14.1-19.4%); MOC1-esc1OVA, Average 11.84% (9.42-15.8%); p=0.025) and reduced response to SIINFEKL restimulation (MOC1OVA, Average 1093.3 pg/mL (860.6-1240.9 pg/mL); MOC1-esc1OVA, Average 533.3 pg/mL (254.5-749.0 pg/mL); p=0.006). A time course analysis in vivo showed that OVA-specific TRM cells were generated in TDLN and migrated into tumor. Compared to MOC1-OVA, MOC1-esc1OVA TDLN cDC1s had reduced CD40 expression and fewer TRM cells. Anti-CD40 blocking monoclonal antibodies reduced OVA-specific TRM cells in MOC1OVA while CD40 agonist antibodies increased antitumor TRMs and reduced PD1-resistant tumor growth compared to the control IgG groups. Conclusion: These findings highlight TRM CD8_+ T cells as a correlate of PD-1 blockade response in HNSCC patient tissues and mouse models and delineate cDC1 CD40 function in the TDLN as critical for effective antitumor TRM development. Citation Format: Michihisa Kono, Shin Saito, Geoff Ivison, Ayano Kondo, Aaron Mayer, Jonathan D. Schoenfeld, Ann Marie Egloff, Ravindra Uppaluri. Tissue-resident memory CD8+ T cells correlate with anti-PD-1 response in head and neck cancer and expand upon cDC1 activation in tumor-draining lymph nodes to overcome PD-1 resistance [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-078.
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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) | 0.005 | 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".