Cellular Immune and Genomic Biomarkers in NRG-HN003, a Phase I Study Adding Pembrolizumab to Adjuvant Cisplatin and Radiation Therapy (CRT) in Pathologically High-Risk Head and Neck Cancer (HNSCC)
Recommended Citation
Bauman J, Harris J, Uppaluri R, Yao M, Chen J, Jordan R, Geiger JL, Jujjavarapu S, Chakravati A, Phan M, Siddiqui F, Kulkarni A, Upadhyay P, Vujanovic L, Isett B, Sica GL, Reeder C, Le QT, Ferris RL. Cellular Immune and Genomic Biomarkers in NRG-HN003, a Phase I Study Adding Pembrolizumab to Adjuvant Cisplatin and Radiation Therapy (CRT) in Pathologically High-Risk Head and Neck Cancer (HNSCC). Int J Radiat Oncol Biol Phys 2024; 120(2 Suppl):S129-S130.
Document Type
Conference Proceeding
Publication Date
10-1-2024
Publication Title
Int J Radiat Oncol Biol Phys
Abstract
Purpose/Objective(s): NRG HN003 was a phase I study that assessed the safety and recommended phase 2 schedule (RP2S) for adding concurrent and maintenance pembrolizumab to adjuvant CRT in patients with pathologically high-risk, HPV-negative HNSCC. As PD-1/L1 immune checkpoints can be upregulated by HNSCC during chemotherapy and RT, their inhibition may reverse associated immunosuppression. Here, we report the immune and genomic correlates of disease-free survival (DFS). Materials/Methods: All 34 eligible patients treated at RP2S are included in the exploratory biomarker analyses. Only patients with available, relevant biospecimens were included in each analysis, thus n varies by biomarker category. To quantify the in situ immunophenotypic microenvironment, formalin-fixed, paraffin-embedded (FFPE) baseline primary tumor tissue was evaluated by multispectral imaging (n = 34). FFPE tumor cores (n = 24) were also subjected to whole exome sequencing (WES), with somatic variant calls facilitated by germline sequencing of peripheral blood mononuclear cells (PBMC; n = 17). Baseline (n = 20) and post-treatment (n = 16) PBMC were evaluated by spectral flow cytometry characterizing T and natural killer (NK) cells, and monocytes with immune checkpoint (PD-1, LAG-3, TIGIT, TIM-3) and effector markers (CD39, CD69, GZMK, GZMB, IFN-γ) if applicable. DFS rates were estimated by Kaplan-Meier method. Hazard ratios (HR) for biomarker values > vs. ≤ median were estimated by Cox models. All analyses are exploratory. Results: With a median follow-up of 3.1 years, the estimated 2-year DFS for the RP2S population was 59.4% (95% CI = 42.4-76.4). Post-treatment blood memory T and T regulatory (Treg) cells were associated with superior DFS: CD8+ central memory (TCM; HR 0.10; 0.01-0.83); CD8+ effector memory (TEM; HR 0.11; 0.01-0.89); Treg (HR 0.10; 0.01-0.83). Hypothesis-generating numerical associations with DFS included the following baseline tumor biomarkers: PD-L1+ stromal cells at the invasive tumor margin or within all stroma (HR 0.48; 0.16-1.40); PD-L1+ CD3- immune cells within the tumor bed (HR 1.77; 0.63-4.98); disruptive TP53 mutations (1-2 vs. 0 mutations per tumor; HR 2.18; 0.63-7.51). In baseline PBMC, CD8+ TEM (HR 0.44; 0.10-1.86) and CD4+ TCM (HR 0.38; 0.09-1.62); monocytes (HR 0.47; 0.11-1.99); and CD56dim CD16- NK cells (HR 0.48; 0.11-2.04) may be associated with DFS. Analysis of WES as well as immune checkpoint and effector markers is ongoing. Conclusion: In NRG HN003, post-treatment circulating memory T cells and Tregs were associated with improved DFS. This cohort also generated testable hypotheses that baseline PD-L1+ stromal cells and various circulating immune subsets may be protective, while intratumoral PD-L1+ myeloid cells and disruptive TP53 mutations may be adverse in this setting.
Volume
120
Issue
2 Suppl
First Page
S129
Last Page
S130
