Effects and Prognostic Values of Circadian Genes CSNK1E/GNA11/KLF9/THRAP3 in Kidney Renal Clear Cell Carcinoma via a Comprehensive Analysis

Abstract

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent and deadly types of renal cancer in adults. Recent research has identified circadian genes as being involved in the development and progression of KIRC by altering their expression. This study aimed to identify circadian genes that are differentially expressed in KIRC and assess their role in KIRC progression. In KIRC, there were 553 differentially expressed rhythm genes (DERGs), with 300 up-regulated and 253 down-regulated DERGs. Functional enrichment analyses showed that DERGs were greatly enriched in the circadian rhythm and immune response pathways. Survival analyses indicated that higher expression levels of CSNK1E were related to shorter overall survival of KIRC patients, whereas lower expression levels of GNA11, KLF9, and THRAP3 were associated with shorter overall survival of KIRC patients. Through cell assay verification, the mRNA level of CSNK1E was significantly up-regulated, whereas the mRNA levels of GNA11, KLF9, and THRAP3 were dramatically down-regulated in KIRC cells, which were consistent with the bioinformatics analysis of KIRC patient samples. Age, grade, stage, TM classification, and CSNK1E expression were all shown to be high-risk variables, whereas GNA11, KLF9, and THRAP3 expression were found to be low-risk factors in univariate Cox analyses. Multivariate Cox analyses showed that CSNK1E and KLF9 were also independently related to overall survival. Immune infiltration analysis indicated that the proportion of immune cells varied greatly between KIRC tissues and normal tissue, whereas CSNK1E, GNA11, KLF9, and THRAP3 expression levels were substantially linked with the infiltration abundance of immune cells and immunological biomarkers. Moreover, interaction networks between CSNK1E/GNA11/KLF9/THRAP3 and immune genes were constructed to explore the stream connections. The findings could help us better understand the molecular mechanisms of KIRC progression, and CSNK1E/GNA11/KLF9/THRAP3 might be used as molecular targets for chronotherapy in KIRC patients in the near future.

KLF9 inhibits the proliferation, invasion, and migration of renal cell carcinoma through the SDF‐1/CXCR4 axis

“…Next, the up/down‐regulation of KLF9 expression in RCC cells using pcDNA3.1‐KLF9 and KLF9 siRNA and revealed that KLF9 overexpression inhibited RCC cell proliferation, invasion, and migration, whereas KLF9 knockdown elicited conflicting outcomes. In consistency with our results, the down‐regulation of KLF9 has been identified in RCC tumor tissues and cells and can serve as an independent predictor of RCC prognosis 13 . Besides, Huang et al have highlighted the ability of KLF9 overexpression to suppress the growth and metastasis of RCC via negative interaction with miR‐140‐5p and positive interaction with KCNQ1 14 .…”

“…In consistency with our results, the down-regulation of KLF9 has been identified in RCC tumor tissues and cells and can serve as an independent predictor of RCC prognosis. 13 Besides, Huang et al have highlighted the ability of KLF9 overexpression to suppress the growth and metastasis of RCC via negative interaction with miR-140-5p and positive interaction with KCNQ1. 14 The functional role of KLF9 in cancers is principally dependent on its downstream regulation.…”

“…[6][7][8] Consistently, KLF9 has been identified as a definitive tumor-suppressor of the KLF family in numerous cancer types, such as prostate, pancreatic, breast, and colorectal cancers. [9][10][11][12] Existing studies have demonstrated a correlation between the lower KLF9 expression level with shorter overall survival of kidney renal clear cell carcinoma (KIRC), 13 and the knockdown of KLF9 can radically induce the proliferation-metastasis cascade of RCC cells. 14 However, the molecular mechanism of KLF9 in RCC cell functions remains elusive.…”

Multi-omics analysis of pyroptosis regulation patterns and characterization of tumor microenvironment in patients with hepatocellular carcinoma

“…Continuous variables were compared between the two groups. For normally distributed variables, we used independent t -tests; for non-normally distributed variables, we used the Mann-Whitney rank-sum test ( Li et al, 2022 ). Correlations between different genes were analyzed using the Pearson correlation coefficient calculation.…”

Circadian Genes MBOAT2/CDA/LPCAT2/B4GALT5 in the Metabolic Pathway Serve as New Biomarkers of PACA Prognosis and Immune Infiltration

“…Interestingly, bioinformatics analysis can help us identify differentially expressed rhythm genes, whose expression levels are closely related to the age, sex, stage, and overall survival of cancer patients as molecular markers of tumors. Previous studies have successfully identified differentially expressed rhythm genes in hepatocellular carcinoma, glioma and kidney renal clear cell carcinoma [ 6 , 7 , 8 ], but little is known about differentially expressed rhythm genes in pancreatic cancer.…”