KCNN4 may weaken anti-tumor immune response via raising Tregs and diminishing resting mast cells in clear cell renal cell carcinoma

Abstract

Background Studies over the past decade have shown that competitive endogenous RNA (ceRNA) plays an essential role in the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). Meanwhile, immune checkpoint blocker is gradually moving towards the first-line treatment of ccRCC. Hence, it’s urgent to develop a new prediction model for the efficiency of immunotherapy. At present, there is no study to reveal the effect of ceRNA network on the efficiency of immunotherapy for ccRCC. Methods To systematically analyze the effect of ceRNA hub genes in ccRCCon immune response, we constructed prognosis models based on ceRNAs and immune cells, respectively. We constructed ceRNA network using hypergeometric distribution test and correlation analysis with R script based on The Cancer Genome Atlas (TCGA) database. We then applied the Cibersort algorithm to simulate the infiltration overview of immune cells in kidney renal clear carcinoma (KIRC) samples. Prognosis-related immune cells were screened and a predictive model of these cells was constructed. Prognosis-related immune cells and ceRNA hub genes were performed with co-expression analysis. Finally, qRT-PCR and immunofluorescence assays were performed to validate the results. Results The construction of ceRNA related prognosis model contained 8 hub genes, including RELT, MYO9B, KCNN4, SIX1, OTOGL, MALAT1, hsa-miR-130b-3p, and hsa-miR-21-5p. The area under the receiver operating characteristic curve (AUC) was 0.77 at 5 years. For the construction of immune cells prognosis model, 3 immune cells (T cells regulatory, Macrophages, Mast cells resting) were adopted, and the AUC was 0.65 at 5 years. We then merged the two models by correlation analysis and co-expression analysis. Finally, we found that KCNN4 positively correlates with T cells regulatory (Tregs) and negatively correlates with mast cells resting significantly. Furthermore, higher expression of KCNN4 may lead to a higher potential for immune evasion and lower efficiency for immune checkpoint inhibitors (ICIs). Conclusions Generally, this is the first study to assess the prognostic value of immune related ceRNA hub genes in ccRCC, and KCNN4 was finally demonstrated to be a key regulatory factor with strong correlation with Tregs and mast cells resting.

Identification of molecular characteristics of FUT8 and alteration of core fucosylation in kidney renal clear cell cancer

“…High density of CD20-defined B-cells indicated a poor-prognosis subset of RCC [ 48 ]. Mast cells might be diminished in KIRC which resulted in a weaken anti-tumor immune response [ 49 ]. The NK cells in KIRC were revealed to be correlated with the expression of TACC3 which was discerned as an autonomous risk element influencing prognosis [ 50 ].…”

Identification of the Prognostic Biomarkers CBX6 and CBX7 in Bladder Cancer

“…Mechanistically, RCC attracts mast cells by modulating PI3K AKT GSK AM signalling, resulting in a poor prognosis [ 43 ]. Reduction in ccRCC resting mast cells hampers anticancer immune responses [ 44 ]. Tumors having a greater infiltration of CD8+ T cells, M1 macrophages, and CD20+ cells had a better prognosis than those infiltrated with M0/M2 macrophages and high immunological checkpoint protein expression [ 45 ].…”

Predicting prognosis and immunotherapeutic response of clear cell renal cell carcinoma

“…KCNN4 influences tumor microenvironment by remodeling tumor-infiltrating immune cell profiles (Chen et al, 2022a). It may regulate immune response via raising Tregs and diminishing resting mast cells in ccRCC, which may cause the differential clinical outcomes (Cui et al, 2022).…”

“…Chromosomal losses of 9p21.3 and 10q23.31, human endogenous retroviruses (ERVE-4, ERV4700, ERV2282, ERV3382), transcriptions of ADAMTS14, PARP1, KCNN4, RUFY4, MUC20, LAG3 and PDCD1 which previously shown to associate with ICB response were included in the univariate analysis (Smith et al, 2019;Braun et al, 2020;Wu et al, 2021;Xue et al, 2022a;Chen et al, 2022b;Cui et al, 2022;Hagiwara et al, 2022;Miao et al, 2022). Transcriptions of CDKN2A, CDKN2B, CDKN2B_AS1, and MTAP were included because these genes are located at 9p21.3, and they are also potential tumor suppressors (Girgis et al, 2012).…”

“…However, In-frame insertions and deletions, missense mutations, and other alterations are not included in the two studies. Chromosomal losses of 9p21.3 and 10q23.31, human endogenous retroviruses (ERVE-4, ERV4700, ERV2282, and ERV3382), transcriptions of ADAMTS14, PARP1, KCNN4, RUFY4, MUC20, LAG3, and PDCD1 were also shown to associate with ICB response (Smith et al, 2019;Braun et al, 2020;Wu et al, 2021;Xue et al, 2022a;Chen et al, 2022b;Cui et al, 2022;Hagiwara et al, 2022;Miao et al, 2022). These biomarkers require further validation in multivariate analyses (Wu et al, 2021).…”