Tumor-infiltrating immune cells have been linked to prognosis and response to immunotherapy; however, the levels of distinct immune cell subsets and the signals that draw them into a tumor, such as the expression of antigen presenting machinery genes, remain poorly characterized. Here, we employ a gene expression-based computational method to profile the infiltration levels of 24 immune cell populations in 19 cancer types. We compare cancer types using an immune infiltration score and a T cell infiltration score and find that clear cell renal cell carcinoma (ccRCC) is among the highest for both scores. Using immune infiltration profiles as well as transcriptomic and proteomic datasets, we characterize three groups of ccRCC tumors: T cell enriched, heterogeneously infiltrated, and non-infiltrated. We observe that the immunogenicity of ccRCC tumors cannot be explained by mutation load or neo-antigen load, but is highly correlated with MHC class I antigen presenting machinery expression (APM). We explore the prognostic value of distinct T cell subsets and show in two cohorts that Th17 cells and CD8+ T/Treg ratio are associated with improved survival, whereas Th2 cells and Tregs are associated with negative outcomes. Investigation of the association of immune infiltration patterns with the subclonal architecture of tumors shows that both APM and T cell levels are negatively associated with subclone number. Our analysis sheds light on the immune infiltration patterns of 19 human cancers and unravels mRNA signatures with prognostic utility and immunotherapeutic biomarker potential in ccRCC.

Recent clinical trials have demonstrated a clear survival advantage in advanced head and neck squamous cell carcinoma (HNSCC) patients treated with immune checkpoint blockade. These emerging results reveal that HNSCC is one of the most promising frontiers for immunotherapy research. However, further progress in head and neck immuno-oncology will require a detailed understanding of the immune infiltrative landscape found in these tumors. We leveraged transcriptome data from 280 tumors profiled by The Cancer Genome Atlas (TCGA) to comprehensively characterize the immune landscape of HNSCC in order to develop a rationale for immunotherapeutic strategies in HNSCC and guide clinical investigation. We find that both HPV ⁺ and HPV ^– HNSCC tumors are among the most highly immune-infiltrated cancer types. Strikingly, HNSCC had the highest median Treg/CD8 ⁺ T cell ratio and the highest levels of CD56 ^dim NK cell infiltration, in our pan-cancer analysis of the most immune-infiltrated tumors. CD8 ⁺ T cell infiltration and CD56 ^dim NK cell infiltration each correlated with superior survival in HNSCC. Tumors harboring genetic smoking signatures had lower immune infiltration and were associated with poorer survival, suggesting these patients may benefit from immune agonist therapy. These findings illuminate the immune landscape of HPV ⁺ and HPV ^– HNSCC. Additionally, this landscape provides a potentially novel rationale for investigation of agents targeting modulators of Tregs (e.g., CTLA-4, GITR, ICOS, IDO, and VEGFA) and NK cells (e.g., KIR, TIGIT, and 4-1BB) as adjuncts to anti–PD-1 in the treatment of advanced HNSCC.

Treatment with immune checkpoint inhibitors (ICI) has demonstrated clinical benefit for a wide range of cancer types. Because only a subset of patients experience clinical benefit, there is a strong need for biomarkers that are easily accessible across diverse practice settings. Here, in a retrospective cohort study of 1714 patients with 16 different cancer types treated with ICI, we show that higher neutrophil-to-lymphocyte ratio (NLR) is significantly associated with poorer overall and progression-free survival, and lower rates of response and clinical benefit, after ICI therapy across multiple cancer types. Combining NLR with tumor mutational burden (TMB), the probability of benefit from ICI is significantly higher (OR = 3.22; 95% CI, 2.26-4.58; P < 0.001) in the NLR low/TMB high group compared to the NLR high/TMB low group. NLR is a suitable candidate for a cost-effective and widely accessible biomarker, and can be combined with TMB for additional predictive capacity.

Renal cell carcinoma stands out as one of the most immune-infiltrated tumors in pan-cancer comparisons. Features of the tumor microenvironment heavily affect disease biology and may affect responses to systemic therapy. With evolving frontline options in the metastatic setting, several immune checkpoint blockade regimens have emerged as efficacious, and there is growing interest in characterizing features of tumor biology that can reproducibly prognosticate patients and/or predict the likelihood of their deriving therapeutic benefit. Herein, we review pertinent characteristics of the tumor microenvironment with dedicated attention to candidate prognostic and predictive signatures as well as possible targets for future drug development.Significance: Tumor microenvironment features broadly characterizing angiogenesis and inflammatory signatures have shown striking differences in response to immune checkpoint blockade and antiangiogenic agents. Integration of stromal and immune biomarkers may hence produce predictive and prognostic signatures to guide management with existing regimens as well as future drug development.