Background: Clear cell renal cell carcinoma (ccRCC) is a common urinary cancer. Although diagnostic and therapeutic approaches for ccRCC have been improved, the survival outcomes of patients with advanced ccRCC remain unsatisfactory. Fatty acid metabolism (FAM) has been increasingly recognized as a critical modulator of cancer development. However, the significance of the FAM in ccRCC remains unclear. Herein, we explored the function of a FAM-related risk score in the stratification and prediction of treatment responses in patients with ccRCC.
Methods: First, we applied an unsupervised clustering method to categorize patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets into subtypes and retrieved FAM-related genes from the MSigDB database. We discern differentially expressed genes (DEGs) among different subtypes. Then, we applied univariate Cox regression analysis followed by least absolute shrinkage and selection operator (LASSO) linear regression based on DEGs expression to establish a FAM-related risk score for ccRCC.
Results: We stratified the three ccRCC subtypes based on FAM-related genes with distinct overall survival (OS), clinical features, immune infiltration patterns, and treatment sensitivities. We screened nine genes from the FAM-related DEGs in the three subtypes to establish a risk prediction model for ccRCC. Nine FAM-related genes were differentially expressed in the ccRCC cell line ACHN compared to the normal kidney cell line HK2. High-risk patients had worse OS, higher genomic heterogeneity, a more complex tumor microenvironment (TME), and elevated expression of immune checkpoints. This phenomenon was validated in the ICGC cohort.
Conclusion: We constructed a FAM-related risk score that predicts the prognosis and therapeutic response of ccRCC. The close association between FAM and ccRCC progression lays a foundation for further exploring FAM-related functions in ccRCC.
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http://dx.doi.org/10.1016/j.heliyon.2023.e17224 | DOI Listing |
Ren Fail
December 2024
Renal Division, Department of Internal Medicine, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Aims: To investigate the potential mechanisms of fatty acid metabolism (FAM)-related genes in IgA nephropathy (IgAN) and to explore its immune cell infiltration characteristic.
Methods: Datasets for IgAN and FAM-related genes were obtained from GEO and MSigDB database, respectively. We employed differential expression analysis and WGCNA to identify common genes.
Front Immunol
October 2024
Jiangxi Provincial Key Laboratory of Cell Precision Therapy, School of Basic Medical Sciences, Jiujiang University, Jiujiang, Jiangxi, China.
Background: Aberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited.
Methods: We developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA).
Cancer Manag Res
October 2024
Department of Oncology, Jining, 272000, People's Republic of China.
Aging (Albany NY)
May 2024
Department of Gastroenterology, Strategic Support Force Medical Center, Beijing 100101, China.
Background: Fatty acid metabolism (FAM) contributes to tumorigenesis and tumor development, but the role of FAM in the progression of stomach adenocarcinoma (STAD) has not been comprehensively clarified.
Methods: The expression data and clinical follow-up information were obtained from The Cancer Genome Atlas (TCGA). FAM pathway was analyzed by gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) methods.
J Biochem Mol Toxicol
April 2024
Department of Gastrointestinal Surgery, Tianjin First Central Hospital, Nankai District, Tianjin, China.
To analyze the expression profile of fatty acid metabolism (FAM)-related genes, identify a prognostic signature, and evaluate its clinical value for gastric cancer (GC) patients. The mRNA expression profiles of 493 FAM-related genes were obtained from TCGA database. Differentially expressed genes (DEGs) between cancer and non-cancer samples were identified, and their relationships with overall survival (OS) of GC patients were evaluated.
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