A metabolomic and proteomic study to elucidate the molecular mechanisms of immunotherapy resistance in patients with oesophageal squamous cell carcinoma

Gao,Lijuan; Chen,Yongshun

doi:10.3892/br.2023.1619

A metabolomic and proteomic study to elucidate the molecular mechanisms of immunotherapy resistance in patients with oesophageal squamous cell carcinoma

Authors:
- Lijuan Gao
- Yongshun Chen
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Affiliations: Department of Clinical Oncology, Renmin Hospital of Wuhan University, Wuhan University First Clinical College, Wuhan, Hubei 430060, P.R. China
Published online on: April 6, 2023 https://doi.org/10.3892/br.2023.1619
Article Number: 36

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Abstract

Systemic chemotherapy, the standard first‑line treatment option for patients with advanced oesophageal squamous cell carcinoma (OSCC), results in a median survival of ~1 year. Immune checkpoint inhibitors are a breakthrough oncology treatment option; however, most patients with advanced OSCC develop primary and acquired resistance to programmed death receptor‑1 (PD‑1) monoclonal antibody, severely affecting their prognosis. Therefore, there is an urgent need to investigate the molecular mechanism underlying resistance to treatment. The present study aimed to explore the mechanism of resistance to PD‑1 monoclonal antibody. Plasma samples were collected from patients with OSCC treated with immunotherapy, who achieved pathological response/partial response (CR/PR) or stable disease/progressive disease (SD/PD) after the fourth treatment cycle. TM‑widely targeted metabolomics, widely targeted lipidomics, and DIA proteomics assays were performed. Differential metabolites were screened based on fold change (FC) ≥1.5 or ≤0.67 and a VIP ≥1; differential proteins were screened based on FC >1.5 or <0.67 and P<0.05. The identified metabolites were annotated and mapped using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. The differential proteins were annotated to the Gene Ontology and KEGG pathway databases. A correlation network diagram was drawn using differential expressed proteins and metabolites with (Pearson correlation coefficient) r>0.80 and P<0.05. Finally, 197 and 113 differential metabolites and proteins were screened, respectively, in patients with CR/PR and SD/PD groups. The KEGG enrichment analysis revealed that all of these metabolites and proteins were enriched in cholesterol metabolism and in the NF‑κB and phospholipase D signalling pathways. The present study is the first to demonstrate that PD‑1 inhibitor resistance may be attributed to cholesterol metabolism or NF‑κB and phospholipase D signalling pathway activation. This finding suggests that targeting these signalling pathways may be a promising novel therapeutic approach in OSCC which may improve prognosis in patients undergoing immunotherapy.

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