TY - JOUR
T1 - A unique regulated cell death-related classification regarding prognosis and immune landscapes in non-small cell lung cancer
AU - Su, Wei
AU - Hong, Ting
AU - Feng, Baijie
AU - Yang, Zhou
AU - Lei, Guang
N1 - Publisher Copyright:
Copyright © 2023 Su, Hong, Feng, Yang and Lei.
PY - 2023
Y1 - 2023
N2 - Regulated cell death (RCD) contributes to reshaping the tumor immune microenvironment and participating in the progression of non-small cell lung cancer (NSCLC); however, related mechanisms have not been fully disclosed. Here, we identified 5 subclusters of NSCLC based on consensus clustering of 3429 RCD-associated genes in the TCGA database and depicted the genomic features and immune landscape of these clusters. Importantly, the clusters provided insights into recognizing tumor microenvironment (TME) and tumor responses to immunotherapy and chemotherapy. Further, we established and validated an RCD-Risk model based on RCD-associated genes, which strongly predicted the prognosis, TME, and immunotherapy outcomes in NSCLC patients. Notably, tissue microarray staining confirmed that the expression of LDLRAD3, a core gene in RCD-Risk model, correlated with poor survival. In conclusion, we developed a novel RCD classification system and RCD-Risk model of NSCLC, serving as a robust and promising predictor for prognosis and immunotherapy benefit of individual NSCLC patients.
AB - Regulated cell death (RCD) contributes to reshaping the tumor immune microenvironment and participating in the progression of non-small cell lung cancer (NSCLC); however, related mechanisms have not been fully disclosed. Here, we identified 5 subclusters of NSCLC based on consensus clustering of 3429 RCD-associated genes in the TCGA database and depicted the genomic features and immune landscape of these clusters. Importantly, the clusters provided insights into recognizing tumor microenvironment (TME) and tumor responses to immunotherapy and chemotherapy. Further, we established and validated an RCD-Risk model based on RCD-associated genes, which strongly predicted the prognosis, TME, and immunotherapy outcomes in NSCLC patients. Notably, tissue microarray staining confirmed that the expression of LDLRAD3, a core gene in RCD-Risk model, correlated with poor survival. In conclusion, we developed a novel RCD classification system and RCD-Risk model of NSCLC, serving as a robust and promising predictor for prognosis and immunotherapy benefit of individual NSCLC patients.
KW - immune checkpoint inhibitors
KW - immunotherapy
KW - non-small cell lung cancer
KW - regulated cell death
KW - tumor microenvironment
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U2 - 10.3389/fimmu.2023.1075848
DO - 10.3389/fimmu.2023.1075848
M3 - Article
C2 - 36817452
AN - SCOPUS:85148773565
SN - 1664-3224
VL - 14
SP - 1075848
JO - Frontiers in immunology
JF - Frontiers in immunology
ER -