Abstract

Only a small fraction of patients with cancer receiving immune checkpoint therapy (ICT) respond, which is associated with tumor immune microenvironment (TIME) subtypes and tumor-infiltrating lymphocytes (TILs). To examine whether germline variants of natural killer (NK) cells, a key component of the immune system, are associated with TIME subtypes, the abundance of TILs, response to ICT, clinical outcomes, and cancer risk. This genetic association study explored TIME subtypes and examined the association of the germline genomic information of patients with cancer with TIME subtypes, abundance of TILs, response to ICT, prognosis, and cancer risk. Clinical information, tumor RNA sequencing, and whole-exome sequencing (WES) data of paired normal samples of patients with 13 common cancers (n = 5883) were obtained from the Cancer Genome Atlas. The WES data of individuals with no cancer (n = 4500) were obtained from the database of Genotypes and Phenotypes. Data collection and analysis took place in March 2017. Associations between the number of germline defective genes in NK cells and survival time and the abundance of TILs. Based on tumor RNA sequencing data, tumors were stratified into TIME-rich, TIME-intermediate, and TIME-poor subtypes. Tumors of TIME-rich subtype had more TILs (TIL-NK cells in TIME-rich head and neck squamous cell carcinoma [HNSC] tumors: t = 4.85; 95% CI of the difference, 0.01-0.03; P = 2.19 × 10-6) compared with TIME-intermediate HNSC tumors (t = 3.70; 95% CI of the difference, 0.01-0.03; P < .001), better prognosis (patients with HNSC: hazard ratio, 0.65; 95% CI, 0.41-1.02; P = .054) compared with TIME-intermediate and TIME-poor subtypes, and better ICT response (patients with melanoma: odds ratio [OR], 4.45; 95% CI, 0.99-27.08; P = .04). Patients with TIME-rich tumors had significantly fewer inherited defective genes in NK cells than patients with TIME-intermediate and TIME-poor tumors (patients with HNSC: OR, 0.49; 95% CI, 0.26-1.07; P = .005). Similarly, patients with cancer had significantly more inherited defective genes in NK cells than individuals with no cancer (patients with HNSC: OR, 19.09; 95% CI, 4.30-315.96; P = 6.21 × 10-4). Among 11 of 13 common cancers, the number of heritable defective genes in NK cells was significantly negatively associated with survival (patients with HNSC: hazard ratio, 1.77; 95% CI, 1.18-2.66; P = .005), abundance of TILs (patients with HNSC: R = -0.25; 95% CI, -0.65-2.17; P = 0.02), and response to ICT (patients with melanoma: OR, 4.45; 95% CI, 0.99-27.08; P = .04). These results suggest that individuals who have more inherited defective genes in NK cells had a higher risk of developing cancer and that these inherited defects were associated with TIME subtypes, recruitment of TILs, ICT response, and clinical outcomes. The findings have implications for identifying individuals at risk for developing cancer of many types based on germline variants of NK cells and for improving existing ICT and chimeric antigen receptor-T cell therapy by adoptive transfer of healthy NK cells to patients with TIME-intermediate and TIME-poor tumors.

Highlights

  • Over the past 2 decades, classification of tumors based on genomics has resulted in identifying distinct tumor molecular subtypes for cancer types, thereby providing a framework to study the molecular mechanisms of cancer

  • Among 11 of 13 common cancers, the number of heritable defective genes in natural killer (NK) cells was significantly negatively associated with survival, abundance of tumor-infiltrating lymphocytes (TILs), and response to Immune checkpoint therapy (ICT)

  • Association of Germline Variants in Natural Killer Cells With Clinical Outcomes and Cancer Risk. These results suggest that individuals who have more inherited defective genes in NK cells had a higher risk of developing cancer and that these inherited defects were associated with tumor immune microenvironment (TIME) subtypes, recruitment of TILs, ICT response, and clinical outcomes

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Summary

Introduction

Over the past 2 decades, classification of tumors based on genomics has resulted in identifying distinct tumor molecular subtypes for cancer types, thereby providing a framework to study the molecular mechanisms of cancer. In most patients, ICT has failed to have its intended effect.[1,2] It has been thought that an understanding of tumor-infiltrating lymphocytes (TILs) and the tumor immune microenvironment (TIME) could provide insights into ICT resistance and might thereby improve existing immunotherapies.[3,4] with the advance of cancer immunotherapy, there is a strong interest in stratifying tumors into TIME subtypes. This stratification could provide better insights into the underlying molecular mechanisms for TILs and response to ICT as well as help to improve current immunotherapy. There is no consensus about how to study TIMEs, and we lack efficient tools to stratify TIMEs

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