RHBDF2 gene functions are correlated to facilitated renal clear cell carcinoma progression

Abstract

Background The rhomboids are a family of multi-transmembrane proteins, many of which have been implicated in facilitating tumor progression. Little is yet known, however, about rhomboid-associated biomarkers in cancers. An analysis of such biomarkers could yield important insights into the role of the rhomboids in cancer pathology. Methods In this study, we carried out the univariate Cox regression analysis and compared gene expression patterns of several rhomboid genes in 30 types of cancers by using The Cancer Genome Atlas (TCGA) database and the methods delineated in Gene Expression Profiling Interactive Analysis (GEPIA). We then used datasets GSE47032, GSE126964, GSE68417 and 75 paired pathological specimens to verify the influences of the rhomboid genes in cancer progression. Moreover, we carried out Weighted Gene Correlation Network Analysis (WGCNA) to investigate gene-related functions and we exploited potential correlations between rhomboid genes expression and immune cell infiltration in cancer tissues. Furthermore, we constructed gene-knockdown cancer cell lines to investigate rhomboid gene functions. Results We find that kidney renal clear cell carcinoma (KIRC) disease progression is affected by fluctuations in the expression of a number of the rhomboid family of genes and, more specifically, high levels of RHBDF2 gene expression are a good indicator of poor prognosis of the disease, as patients with high RHBDF2 expression levels exhibit less favorable survival rates compared to those with low RHBDF2 levels. Silencing of the RHBDF2 gene in KIRC cell lines leads to significantly diminished cell proliferation and migration; this is in good agreement with the identification of an enhanced presence of a number of cell growth and migration promoting signaling molecules in KIRC tumors. We found that, although high level of RHBDF2 correlated with increased infiltration of lymphocytes in cancer tissues, artificially overexpressed RHBDF2 led to an inhibition of the activity of the infiltrated immune cells through sustaining PD-L1 protein level. Furthermore, we show that RHBDF2 related cell migration and PD-L1 regulation were potentially mediated by EGFR signaling pathway. Conclusions RHBDF2 gene functions are correlated to facilitated renal clear cell carcinoma progression and may serve as a critical prognostic biomarker for the disease.

Transcriptomes reveal microRNAs and mRNAs in different photoperiods influencing cashmere growth in goat

“…The expression level of RHBDF2 gene in skin tissue of cashmere goats was the highest in anagen. The expression of RHBDF2 gene decreased gradually in skin when hair follicles enter into telogen [21]. In our study, the results suggest that high expression of RHBDF2 gene can promote the growth of skin hair follicles.…”

“…Rhomboid proteins are a family of multi-transmembrane proteins. A high level of Rhomboid family member 2 gene (RHBDF2) gene expression is an indicator of disease prognosis [21]. RHBDF2 was found to be involved in epithelial regeneration through epidermal growth factor receptor (EGFR) signal transduction in mouse skin wound healing which can be accelerated by enhancing epidermal growth factor receptor [22,23].…”

Prognostic biomarker NEIL3 and its association with immune infiltration in renal clear cell carcinoma

“…Microarray data of KIRC expression profiling (GSE40435, GSE53757 ( 16 ), GSE68417 ( 17 ) and GSE73731) were obtained from Gene Expression Omnibus (GEO) database ( ) ( 18 ). All gene expression microarray data were normalized using the limma R package.…”

“…Microarray data of KIRC expression profiling (GSE40435, GSE53757 (16), GSE68417 (17) and GSE73731) were obtained from Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm. nih.gov/geo/) (18).…”

The clinical significance of integrin subunit alpha V in cancers: from small cell lung carcinoma to pan-cancer

“…To detect associations between ITGAV expression and tumor immune microenvironment (TME), the relationship between ITGAV expression and immune infiltration levels (using Pearson coefficient) was explored based on the ESTIMATE algorithm [19,[21][22][23] and CIBERSORT algorithm [14,24,25]. Immune checkpoints were promising in the treatment of cancers [26], and thus, the study also evaluated their associations with ITGAV expression to preliminarily assess the immunotherapy potential of ITGAV in SCLC.…”