Prognostic prediction and immunotherapy response analysis of the fatty acid metabolism-related genes in clear cell renal cell carcinoma

Qinfan Yao; Xiuyuan Zhang; Chunchun Wei; Hongjun Chen; Qiannan Xu; Jianghua Chen; Dajin Chen

doi:10.1016/j.heliyon.2023.e17224

Prognostic prediction and immunotherapy response analysis of the fatty acid metabolism-related genes in clear cell renal cell carcinoma

Heliyon. 2023 Jun 13;9(6):e17224. doi: 10.1016/j.heliyon.2023.e17224. eCollection 2023 Jun.

Authors

Qinfan Yao^{1

2

3

4}, Xiuyuan Zhang^{1

2

3

4}, Chunchun Wei^{1

2

3

4}, Hongjun Chen^{1

2

3

4}, Qiannan Xu^{1

2

3

4}, Jianghua Chen^{1

2

3

4}, Dajin Chen^{1

2

3

4}

Affiliations

¹ Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, China.
² Key Laboratory of Kidney Disease Prevention and Control Technology, Zhejiang Province, China.
³ Institute of Nephropathy, Zhejiang University, China.
⁴ Zhejiang Clinical Research Center of Kidney and Urinary System Disease, China.

Abstract

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.

Keywords: Fatty acid metabolism; Immune features; Prognostic model; Treatment; ccRCC.