Theranostics 2017; 7(14):3585-3594. doi:10.7150/thno.21471
Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications
1. Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangzhou, People's Republic of China;
2. Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, People's Republic of China;
3. Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, United States;
4. Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.
* These authors contributed equally to this work.
Chen YP, Zhang Y, Lv JW, Li YQ, Wang YQ, He QM, Yang XJ, Sun Y, Mao YP, Yun JP, Liu N, Ma J. Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications. Theranostics 2017; 7(14):3585-3594. doi:10.7150/thno.21471. Available from http://www.thno.org/v07p3585.htm
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: Tumor microenvironment immune type, Immune checkpoint inhibitors, Biomarker, mRNA sequencing, Mutation burden, Neoantigen.