Clinical-genomic determinants of immune checkpoint blockade response in head and neck squamous cell carcinoma
Cristina Valero, … , Timothy A. Chan, Luc G.T. Morris
Cristina Valero, … , Timothy A. Chan, Luc G.T. Morris
Published August 10, 2023
Citation Information: J Clin Invest. 2023;133(19):e169823. https://doi.org/10.1172/JCI169823.
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Clinical Research and Public Health Immunology Oncology

Clinical-genomic determinants of immune checkpoint blockade response in head and neck squamous cell carcinoma

Abstract

BACKGROUND Recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is generally an incurable disease, with patients experiencing median survival of under 10 months and significant morbidity. While immune checkpoint blockade (ICB) drugs are effective in approximately 20% of patients, the remaining experience limited clinical benefit and are exposed to potential adverse effects and financial costs. Clinically approved biomarkers, such as tumor mutational burden (TMB), have a modest predictive value in HNSCC.METHODS We analyzed clinical and genomic features, generated using whole-exome sequencing, in 133 ICB-treated patients with R/M HNSCC, of whom 69 had virus-associated and 64 had non-virus-associated tumors.RESULTS Hierarchical clustering of genomic data revealed 6 molecular subtypes characterized by a wide range of objective response rates and survival after ICB therapy. The prognostic importance of these 6 subtypes was validated in an external cohort. A random forest-based predictive model, using several clinical and genomic features, predicted progression-free survival (PFS), overall survival (OS), and response with greater accuracy than did a model based on TMB alone. Recursive partitioning analysis identified 3 features (systemic inflammatory response index, TMB, and smoking signature) that classified patients into risk groups with accurate discrimination of PFS and OS.CONCLUSION These findings shed light on the immunogenomic characteristics of HNSCC tumors that drive differential responses to ICB and identify a clinical-genomic classifier that outperformed the current clinically approved biomarker of TMB. This validated predictive tool may help with clinical risk stratification in patients with R/M HNSCC for whom ICB is being considered.FUNDING Fundación Alfonso Martín Escudero, NIH R01 DE027738, US Department of Defense CA210784, The Geoffrey Beene Cancer Research Center, The MSKCC Population Science Research Program, the Jayme Flowers Fund, the Sebastian Nativo Fund, and the NIH/NCI Cancer Center Support Grant P30 CA008748.

Authors

Cristina Valero, Mahdi Golkaram, Joris L. Vos, Bin Xu, Conall Fitzgerald, Mark Lee, Shannon Kaplan, Catherine Y. Han, Xin Pei, Reith Sarkar, Lillian A. Boe, Abhinav Pandey, Elizabeth S. Koh, Charlotte L. Zuur, David B. Solit, Traci Pawlowski, Li Liu, Alan L. Ho, Diego Chowell, Nadeem Riaz, Timothy A. Chan, Luc G.T. Morris

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Figure 2

The genomic landscape of V-negative, HPV-positive, and EBV-positive HNSCC.

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The genomic landscape of V-negative, HPV-positive, and EBV-positive HNSC...
(A) Each column represents a unique sample. V-negative tumors are shown on the left and HPV-positive and EBV-positive tumors on the right. The top bar chart represents the TMB in mutations/Mbp per sample; the EBV-positive sample marked with an asterisk was microsatellite unstable. Below that, a stacked bar chart shows the proportion of the total mutational load attributed to COSMIC signatures (23) associated with APOBEC activity, smoking, or aging. Oncoprints show the top 15 most frequently mutated genes (listed on the left), the variant type (box color), the total proportion of samples with a mutation in that gene (percentage on the right), and the Q value per gene (bar chart on the right). Tracks below the oncoprints show mutations in the TERT promoter region; an individual tumor’s causative virus (in V-positive tumors only); the primary tumor site; the proportion of LOH at the HLA locus (51); and the tumors’ best objective response. Ins, insertion; Del, deletion; Sig., signature; val, value.(B) Box plots show (from left to right) the TMB, the sum of insertions and deletions per exome, and the total number of clonal mutations per exome in V-negative, HPV-positive, and EBV-positive tumors. The clonal mutational load was available for 124 samples. P values were calculated using a Kruskal-Wallis test. (C) Box plots show the contribution of an SBS signature associated with smoking (SBS 4) and APOBEC activity (SBS 2) in V-negative, HPV-positive, and EBV-positive tumors (n = 133). P values were calculated using a Kruskal-Wallis test. (D) Stacked bar chart shows the proportion of diploidy (blue, mean copy number [CN] of 1.5–2.5) and hyperploidy (yellow, mean CN >2.5) in V-negative, HPV-positive, and EBV-positive tumors (n = 133). The P value was calculated using a Fisher’s exact test with Freeman-Halton extension. (E) Box plots show the sample tumor purity estimates derived from FACETS in V-negative, HPV-positive, and EBV-positive tumors (n = 133). The P value was calculated using a Kruskal-Wallis test.