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posted on 14.07.2021, 05:48 authored by Tianli Cheng, Jing Zhang, Danni Liu, Guorong Lai, Xiaoping Wen

Immune checkpoint inhibitors (ICIs) significantly improve the survival of patients with non-small-cell lung cancer (NSCLC), but only some patients obtain clinical benefits. Predictive biomarkers for ICIs can accurately identify people who will benefit from immunotherapy. Lipid metabolism signaling plays a key role in the tumor microenvironment (TME) and immunotherapy. Hence, we aimed to explore the association between the mutation status of the lipid metabolism pathway and the prognosis of patients with NSCLC treated with ICIs. We downloaded the mutation data and clinical data of a cohort of patients with NSCLC who received ICIs. Univariate and multivariate Cox regression models were used to analyze the association between the mutation status of the lipid metabolism signaling and the prognosis of NSCLC receiving ICIs. Additionally, The Cancer Genome Atlas (TCGA)–NSCLC cohort was used to explore the relationships between the different mutation statuses of lipid metabolism pathways and the TME. Additionally, we found that patients with high numbers of mutations in the lipid metabolism pathway had significantly enriched macrophages (M0- and M1-type), CD4 + T cells (activated memory), CD8 + T cells, Tfh cells and gamma delta T cells, significantly increased expression of inflammatory genes [interferon-γ (IFNG), CD8A, GZMA, GZMB, CXCL9, and CXCL10] and enhanced immunogenic factors [neoantigen loads (NALs), tumor mutation burden (TMB), and DNA damage repair pathways]. In the local-NSCLC cohort, we found that the group with a high number of mutations had a significantly higher tumor mutation burden (TMB) and PD-L1 expression. High mutation status in the lipid metabolism pathway is associated with significantly prolonged progression-free survival (PFS) in NSCLC, indicating that this marker can be used as a predictive indicator for patients with NSCLC receiving ICIs.

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