Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer

Abstract

BackgroundGastric cancer is one of the common malignant tumors of the digestive system worldwide, posing a serious threat to human health. A growing number of studies have demonstrated the important role that lipid droplets play in promoting cancer progression. However, few studies have systematically evaluated the role of lipid droplet metabolism-related genes (LDMRGs) in patients with gastric cancer.MethodsWe identified two distinct molecular subtypes in the TCGA-STAD cohort based on LDMRGs expression. We then constructed risk prediction scoring models in the TCGA-STAD cohort by lasso regression analysis and validated the model with the GSE15459 and GSE66229 cohorts. Moreover, we constructed a nomogram prediction model by cox regression analysis and evaluated the predictive efficacy of the model by various methods in STAD. Finally, we identified the key gene in LDMRGs, ABCA1, and performed a systematic multi-omics analysis in gastric cancer.ResultsTwo molecular subtypes were identified based on LDMRGs expression with different survival prognosis and immune infiltration levels. lasso regression models were effective in predicting overall survival (OS) of gastric cancer patients at 1, 3 and 5 years and were validated in the GEO database with consistent results. The nomogram prediction model incorporated additional clinical factors and prognostic molecules to improve the prognostic predictive value of the current TNM staging system. ABCA1 was identified as a key gene in LDMRGs and multi-omics analysis showed a strong correlation between ABCA1 and the prognosis and immune status of patients with gastric cancer.ConclusionThis study reveals the characteristics and possible underlying mechanisms of LDMRGs in gastric cancer, contributing to the identification of new prognostic biomarkers and providing a basis for future research.

Integrated analysis of single-cell and bulk RNA-sequencing reveals the poor prognostic value of ABCA1 in gastric adenocarcinoma

“…ABCA1 is involved in the progression of various cancers and pathological biological processes, including dyslipidemia, neurological disorders, glaucoma, and diabetes [ 8 ] However, the effect of ABCA1 on the heterogeneous TME of GAC has not been fully elucidated. Nevertheless, Liu et al employed bioinformatics techniques to develop a lipid droplet metabolism model for GAC and revealed that upregulated ABCA1 might contribute to the development of unfavorable clinical characteristics in GAC [ 27 ]. Similarly, Yin et al discovered a correlation between ABCA1 expression and drug metabolism.…”

Progressions of the correlation between lipid metabolism and immune infiltration characteristics in gastric cancer and identification of BCHE as a potential biomarker

“…Inhibiting the activity of CPT1α can decrease FA β- Oxidize, thereby reducing energy supply to tumor cells and exerting anti-tumor effects ( 17 , 18 ). Furthermore, lipid droplets are formed in the endoplasmic reticulum when cellular lipids are excessive ( 19 ), which provide sufficient energy for cancer metastasis ( 20 ).…”