Abstract
Introduction
We aimed to determine the prognostic role of long-chain acyl-CoA synthetases (ACSLs)
as a disease marker for kidney clear cell carcinoma (KIRC).
Patients and Methods
The Cancer Genome Atlas (TCGA) data were accessed via open access LinkedOmics database
for KIRC. Provisional datasets were used for analysis as previously described and
gene expression quantification data were downloaded. The corresponding clinical information
of patients also were obtained from the database. Five ACSL family members, ACSL1,
ACSL3, ACSL4, ACSL5, and ACSL6, were investigated in the TCGA-KIRC cohort. Xena browser,
cBioPortal and UALCAN, and Cancer Cell Line Encyclopedia (CCLE) databases were also
used to confirm the results. External validation was performed using patient cohorts
from the Gene Expression Omnibus (GEO-NCBI) database. Finally, the protein–protein
interaction (PPI) was constructed based on the Search Tool for the Retrieval of Interacting
Genes (STRING) database and visualized using Cytoscape software.
Results
Pathological T3-T4 stage tumors had significantly lower ACSL1 mRNA expression (P = .009). Patients with pathologically confirmed metastasis exhibited significantly
lower expression, as well (P = .02). ACSL1 mRNA expression was associated with overall survival (OS) and negatively
correlated with OS time. Univariate and multivariate analyses showed that lower ACSL1
mRNA expression level was associated with mortality. Moreover, ACSL1 mRNA expression
was exhibited significant difference in some VHL gene region mutations and PBRM1_p.R1010
mutation, and negatively correlated with HIF1-alpha mRNA expression (P < .001). Confirmatory analyses and external validation also revealed similar findings.
Conclusion
Lowered ACSL1 mRNA expression is associated with worse tumor histopathology and poor
overall survival in KIRC. It may be used for prognostic marker for KIRC.
Keywords
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Article info
Publication history
Published online: November 22, 2022
Accepted:
November 14,
2022
Received in revised form:
November 7,
2022
Received:
May 7,
2022
Identification
Copyright
© 2022 Elsevier Inc. All rights reserved.
