Prognostic prediction and immune infiltration analysis based on lysosome and senescence state identifies MMP12 as a novel therapy target in gastric cancer

• Published in: International immunopharmacology Vol. 143; no. Pt 1; p. 113344
• Main Authors: He, Ke‐Jie, Gong, Guoyu
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 13.10.2024
• Subjects: Chemotherapy response; Copy number variation; Gastric cancer; Immune; MMP12, gene mutation; Prognostic signature; Prognostic signature; Chemotherapy response; MMP12, gene mutation; Copy number variation; Gastric cancer; Immune
• ISSN: 1567-5769; 1878-1705; 1878-1705
• DOI: 10.1016/j.intimp.2024.113344

•Identified a 22-gene prognostic signature related to lysosomes and senescence using TCGA gastric cancer data.•Classified gastric cancers into two subtypes, Cluster 1 and Cluster 2, based on the 22 genes, with Cluster 2 exhibiting worse prognosis.•Cluster 2 displayed widespread dysregulation of lysosomal and senescence pathways, associated with higher clinical stage and activated oncogenic signaling like PI3K-Akt.•MMP12 was downregulated in Cluster 2, and cellular experiments suggested a protective role in gastric cancer. As humans undergo the aging process, they become more vulnerable to various types of cancers, including gastric cancer (GC), which is frequently associated with aging. The senescent phenotype is closely linked to lysosomes, but research on the combined impact of senescence and lysosomes on GC prognosis is scarce. To construct and validate a prognostic model for gastric cancer (GC), we obtained gene expression and clinical data of GC patients from Cancer Genome Atlas (TCGA) databases. We employed Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression for model construction and ConsensusClusterPlus R package for generating cluster heatmaps. The model’s predictive ability was evaluated through Kaplan-Meier survival analysis and ROC curve analysis. Our analysis included an assessment of the senescence and lysosome state using expression profiles and immune infiltration analysis through CIBERSORT methods. Finally, we validated potential gene targets through cellular experiments. “In this research, we discovered two subtypes of gastric cancer (GC), Cluster 1 and Cluster 2. These subtypes are characterized by the presence of lysosomes and senescence, and we have identified distinct molecular features unique to each subtype. We observed that Cluster 2 had a lower survival prognosis compared to Cluster 1. Additionally, we have developed a risk prediction model that takes into consideration the presence of lysosomes and senescence. Patients in the high-risk group, as predicted by our model, experienced shorter survival times. Further analysis included immune infiltration, immune checkpoint, and chemotherapy evaluation of GC patients. We have displayed the frequency of mutations and copy number variations (CNVs) in visual formats. Our cellular experiments demonstrated that the MMP12 gene serves as a protective factor in GC cells.” In conclusion, we have clarified the extensive relationship between lysosomes and senescence in GC and developed a risk signature to forecast the prognosis of GC patients. MMP12 could be a promising protective factor for GC patients and might present a novel concept for anticipating the efficacy of targeted therapies and immunotherapies in GC patients.