Spatial features of specific CD103+CD8+ tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer
Guanqun Yang, Siqi Cai, Mengyu Hu, Chaozhuo Li, Liying Yang, Wei Zhang, Jujie Sun, Fenghao Sun, Ligang Xing, Xiaorong Sun
Abstract
Abstract Background Tissue-resident memory T (T RM ) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of T RM cells but we know little about it. Methods Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of T RM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a T RM -based spatial immune signature (T RM -SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). Results The density of T RM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of T RM cell subsets was defined, including T RM1 (PD-1 − Tim-3 − T RM ), T RM2 (PD-1 + Tim-3 − T RM ), T RM3 (PD-1 − Tim-3 + T RM ) and T RM4 (PD-1 + Tim-3 + T RM ). The cytotoxicity of T RM2 was the strongest while that of T RM4 was the weakest. Compare with T RM1 and T RM2 , T RM3 and T RM4 had better infiltration and stronger interaction with cancer cells. The T RM -SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63–3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of T RM cells. Conclusions These findings reveal a significant heterogeneity in the functional status and spatial distribution of T RM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating T RM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.