KCNN4 is a potential prognostic marker and critical factor affecting the immune status of the tumor microenvironment in kidney renal clear cell carcinoma

Abstract

Background: The tumor microenvironment (TME) has emerged as a crucial factor in cancer development and progression. Recent findings have indicated that tumor-infiltrating immune cells (TICs) in the TME may predict cancer prognosis and response to treatment. Herein, we sought to identify critical modulators of the kidney renal clear cell carcinoma (KIRC) TME.Methods: KIRC datasets from The Cancer Genome Atlas (TCGA) were analyzed using the ESTIMATE algorithm to determine the ImmuneScore and StromalScore. By profiling the differentially expressed genes (DEGs) in the ImmuneScore and StromalScore, we finally identified the immune-and stromal-related DEGs of the cases, through which we then performed intersection analysis to determine the immunerelated genes (IRGs). Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify critical IRGs and construct a prognostic model. The CIBERSORT algorithm was used to calculate the relative content of 22 immune cell types. Finally, the datasets from the Gene Expression Omnibus (GEO) database were analyzed to validate results from the above analyses.Experimental validation was used on KIRC tissues by quantitative polymerase chain reaction (qPCR) and western blot.Results: We found that the ImmuneScore was negatively correlated with patients' prognosis. Intersection analysis of the ImmuneScore and StromalScore identified 118 IRGs that were enriched in immune-related functions. Following IRGs screening by Cox and LASSO regression analyses, six genes were identified and used to construct a KIRC prognostic model. Intersection analysis of these six genes and protein-protein interaction (PPI) were performed and obtained the most critical gene: Potassium Calcium-Activated Channel Subfamily N Member 4 (KCNN4). Further analysis showed that KCNN4 expression was higher in tumor samples relative to normal controls, and was negatively correlated with prognosis. CIBERSORT analysis revealed significant correlation between KCNN4 expression and multiple types of TICs, demonstrating that KCNN4 may affect KIRC prognosis by influencing the TME immune status. Ultimately, the GEO datasets and validation experiments confirmed that KCNN4 was highly expressed in tumor tissues compared to the corresponding normal tissues.

KCNN4 is a Potential Biomarker for Predicting Cancer Prognosis and an Essential Molecule that Remodels Various Components in the Tumor Microenvironment: A Pan-Cancer Study

“…Herein, we found significant correlations between KCNN4 and immune scores as well as stromal scores in four tumor types in the increased-risk group, whereas KCNN4 expression was associated with immune and stromal scores of the SKCM in the decreased-risk group. Collectively, the above results suggest that KCNN4 may participate in remodeling the TME, which is consistent with results reported in a previous study (Brown et al, 2018;Chimote et al, 2018;Chen et al, 2021). Interestingly, we discovered that KCNN4 expression was correlated with various TIC subtypes and macrophages are the most frequently occurring cell types in different cancers.…”

A Novel Prognostic Signature Associated With the Tumor Microenvironment in Kidney Renal Clear Cell Carcinoma

“…Univariate and multifactorial Cox regression analyses combined with clinicopathological parameters showed this prognostic signature to be an independent prognostic factor for KIRC patients. When we compared our risk prognostic signature with the prognostic models developed by Yang et al ( 17 ), Chen et al ( 18 ), and Zhu et al ( 19 ), the overall performance of our signature was better than these three signatures.…”

“…We also established a nomogram to better predict the prognosis of KIRC patients, and the concordance index (C-index) and DCA were used to evaluate the performance of the nomogram. To demonstrate the superior performance of the signature developed in this study, we compared the signature with three recently published prediction models (17)(18)(19).…”

Clinical Eosinophil-Associated Genes can Serve as a Reliable Predictor of Bladder Urothelial Cancer

“…As the ninth most common cancer in the world, BLCA with high recurrence and high invasiveness poses a great threat to the health of all human beings (Cumberbatch et al, 2018). Cisplatin-based chemotherapy is the universal treatment for locally advanced or metastatic BLCA in the clinic currently (von der Maase et al, 2005), however, the efficacy is usually unsatisfactory due to the physical condition of the patients and various adverse reactions (Chen et al, 2021). In recent years, immunotherapy has developed rapidly, with a variety of ICIs appearing and being used to treat advanced BLCA (Chism, 2017).…”