This study aimed to characterize tumor microenvironment (TME) profile to predict clinical outcomes of cancer immunotherapy and to identify potential cellular mechanisms driving immunotherapy response and resistance.
This study analyzed single-cell or RNA sequencing data of 396 immunotherapy-treated patients from the phase II IMvigor210 trial and Gene Expression Omnibus, and also included 4,547 patients from The Cancer Genome Atlas. Using unsupervised hierarchical clustering, we combined immune checkpoints, human leukocyte antigens, and immune cells to construct a novel TME classification.
The clustering in IMvigor210 trial resulted in three immune subtypes, with the greatest overall survival (OS) benefit in Immune-Active Class (HR 0.69; 95% CI 0.56 to 0.84; P < 0.001), which was validated in TCGA cohort across multiple cancers (HR 0.86; 95% CI 0.80 to 0.92; P < 0.0001). The three immune subtypes exhibited distinct metabolic patterns, especially in the hypoxia signaling pathway; patients in Immune-Active Class had lowest hypoxia score (P<0.0001). Further single-cell profiling revealed that in patients who did not respond to immunotherapy, M2 macrophages increased after treatment but there was no significant difference in natural killer (NK) cells between pre- and post- immunotherapy treatment. Conversely, among responders, M2 macrophages showed little change but NK cells significantly increased after immunotherapy. Among non-responders, M2 macrophages had higher expression of hypoxia signature after treatment, but this change in responders was not evident. In agreement, IMvigor210 data showed longer OS in patients with low versus high M2 macrophages (HR 0.58; 95% CI 0.42 to 0.80; P < 0.001), and in patients with high versus low NK cells (HR 0.74; 95% CI 0.56 to 0.97; P = 0.03).
This study developed novel TME-based subtypes to facilitate cancer immunotherapy delivery. Additionally, M2 macrophages might induce immunotherapy resistance by causing NK cell exclusion or dysfunction via hypoxia-related pathways.
Herui Yao.
This work was supported by the National Science and Technology Major Project (grant number 2020ZX09201021); the National Natural Science Foundation of China (grant numbers 81572596, 81972471, U1601223); the Natural Science Foundation of Guangdong Province (grant number 2017A030313828); the Guangzhou Science and Technology Major Program (grant number 201704020131); the Sun Yat-Sen University Clinical Research 5010 Program (grant number 2018007); the Sun Yat-Sen Clinical Research Cultivating Program (grant number SYS-C-201801); the Guangdong Science and Technology Department (grant number 2017B030314026); and the Special Funds for the Cultivation of Guangdong College Students’ Scientific and Technological Innovation (grant number pdjh2019a0212); National Students’ Innovation and Entrepreneurship training program (grant number 201910571001); and Guangdong Medical University College Students’ Innovation Experiment Project (grant number ZZZF001).
All authors have declared no conflicts of interest.