Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications

Abstract

We performed a comprehensive immuno-genomic analysis of tumor microenvironment immune types (TMITs), which is classified into four groups based on PD-L1+CD8A or PD-L1+cytolytic activity (CYT) expression, across a broad spectrum of solid tumors in order to help identify patients who will benefit from anti- PD-1/PD-L1 therapy. The mRNA sequencing data from The Cancer Genome Atlas (TCGA) of 14 solid cancer types representing 6,685 tumor samples was analyzed. TMIT was classified only for those tumor types that both PD-L1 and CD8A/CYT could prefict mutation and/or neoantigen number. The mutational and neoepitope features of the tumor were compared according to the four TMITs. We found that PD-L1/CD8A/CYT subgroups could not distinguish different mutation and neoantigen numbers in certain tumor types such as glioblastoma multiforme, prostate adenocarcinoma, and head and neck and lung squamous cell carcinoma. For the remaining tumor types, compared with TIMT II (low PD-L1 and CD8A/CYT), TIMT I (high PD-L1 and CD8A/CYT) had a significantly higher number of mutations or neoantigens in bladder urothelial carcinoma, breast and cervical cancer, colorectal, stomach and lung adenocarcinoma, and melanoma. In contrast, TMIT I of kidney clear cell, liver hepatocellular, and thyroid carcinoma were negatively correlated with mutation burden or neoantigen numbers. Our findings show that the TMIT stratification proposed could serve as a favorable approach for tailoring optimal immunotherapeutic strategies in certain tumor types. Going forward, it will be important to test the clinical practicability of TMIT based on quantification of immune infiltrates using mRNA-seq to predict clinical response to these and other immunotherapeutic strategies in more different tumors.

Keywords: Biomarker; Immune checkpoint inhibitors; Mutation burden; Neoantigen.; Tumor microenvironment immune type; mRNA sequencing.

Figure 1

Distribution of mutation burden, neoantigen number, and PD-L1/CD8A/CYT expression across TCGA cancer types. (A) Boxplot distributions of log 2-transformed values of the number of mutations and neoantigens according to TCGA cancer types. (B) Boxplot distributions of log 2-transformed values of expression of PD-L1 and CD8A, and CYT (cytolytic activity, defined as the geometric mean of GZMA and PRF1 expression in RSEM) according to TCGA cancer types. The dashed lines indicate the median values of all tumor samples.

Figure 2

Mutation burden by subgroups of PD-L1/CD8A/CYT expression across TCGA cancer types. Boxplot distributions of log 2-transformed values of the number of somatic mutations between subgroups of PD-L1/CD8A/CYT expression, as defined by RPART cut-off or median value, according to TCGA cancer types (A-N). For some cancer types, the number of mutations differ significantly in certain RPART subgroups: in PD-L1 subgroups for BLCA, BRCA, CESC, COAD, KIRC, LIHC, LUAD, SKCM, and STAD; in CD8A subgroups for BLCA, CESC, COAD, KIRC, LIHC, and LUAD; and in CYT subgroups for BLCA, BRCA, CESC, COAD, LUAD, SKCM, and STAD. P values are calculated by Wilcoxon rank-sum test (*P < 0.05, **P < 0.001). RPART, Recursive Partitioning and Regression Trees.

Figure 3

Neoantigen number by subgroups of PD-L1/CD8A/CYT expression across TCGA cancer types. Boxplot distributions of log 2-transformed values of the number of neoantigens between subgroups of PD-L1/CD8A/CYT expression, as defined by RPART cutoff or median value, according to TCGA cancer types (A-M). For some cancer types, the number of neoantigens differ significantly in certain RPART subgroups: in PD-L1 subgroups for BLCA, BRCA, CESC, KIRC, LUAD, SKCM, STAD, and THCA; in CD8A subgroups for CESC, KIRC, and LUAD; and in CYT subgroups for BLCA, BRCA, CESC, LUAD, SKCM, STAD, and THCA. P values are calculated by Wilcoxon rank-sum test (*P < 0.05, **P < 0.001). COAD was excluded due to insufficient data. RPART, Recursive Partitioning and Regression Trees.

Figure 4

Distribution of TMITs, as well as mutation burden and neoantigen number according to TMIT, across certain cancer types. Proportion of TMITs as defined by PD-L1 and CD8A expression in CESC, COAD, KIRC, LIHC, LUAD (A), and by PD-L1 and CYT expression in BLCA, BRCA, CESC, COAD, LUAD, SKCM, STAD, and THCA (B). Boxplot distributions of log 2-transformed values of the number of mutations/neoantigens according to TMIT, and histogram distributions of TMITs according to mutation/neoantigen status of these cancer types (C-N). P values are calculated by Wilcoxon rank-sum test as compared to TMIT I (*P < 0.05, **P < 0.001). RPART, Recursive Partitioning and Regression Trees; TMIT, tumor microenvironment immune type.

Figure 5

Tailoring cancer immunotherapeutics based on tumor microenvironment immune types (TMITs). The tumor microenvironment has been categorized into four different types based on the expression of PD-L1, and CD8A/CYT: type I (adaptive immune resistance), type II (immunologic ignorance), type III (oncogenic pathway activation), and type IV (immunologic tolerance). The proposed four TMITs are simplistic, but can help us to tailor the most suitable immunotherapeutic strategies. APC, antigen presenting cell; CTL, cytotoxic lymphocyte; IFN, interferon; M2, M2 macrophage; MDSC, myeloid-derived suppressor cell; Th1, T helper 1; Treg, regulatory T cell.