Data source and cleaning
The ccRCC RNA-Seq data were obtained from TCGA database via the Data transfer tool. Samples information and clinical data which consist of gender, age, clinical TNM stage, histopathological grade, survival time, etc. were directly collected from the website. Then, two gene expression matrices of COUNT and FPKM (Fragments Per Kilobase of exon model per Million mapped)) and one clinical information table were constructed through R software (version: 64 4.0.3). Meanwhile, Yusenko renal datasets from the Oncomine (https://www.oncomine.org/) database and GSE126864 from GEO (Gene Expression Omnibus) database were also analyzed in this study. The analytical procedures were shown in Additional file 1: Fig. S1.
Establishment of immune infiltration landscape
CIBERSORTx is an online tool to accurately infer cell type abundance from RNA profiles of intact tissues [20]. This study conducted CIBERSORTx analysis online (https://cibersortx.stanford.edu/) according to the following parameters:
sigmatrix: LM22.update-gene-symbols.txt, perm: 500, verbose: TRUE, rmbatchBmode: TRUE
,
QN
:
FALSE
From calculation results of CIBERSORTx, 609 samples were selected with p ≤ 0.05 and each sample was equipped with the relative proportion matrix of 22 immune cell types. Then R packages “pheatmap”, “barplot” and “vioplot” were installed in R software to establish the immune infiltration landscape.
Identification of survival-associated immune cells
On basis of the proportions of 22 immune cells, Kaplan–Meier (K-M) analysis of overall survival rate was performed. Among K-M survival analysis, the cut-off was set as the upper and lower quartiles and statistically significant means that p-values were less than 0.05. Univariate survival analysis was used to verify the prognostic predictive effect of known factors, such as age, gender, T stage, M stage, etc. Additionally, this study created a multivariate model which was adjusted for those factors whose hazard ratio (HR) > 1. By setting the cut-off as the median of relative proportion, 537 samples were distributed into high and low groups. Then the proportion of each immune cell was added as a new binary variable for survival analysis.
Identification of key genes related to immune infiltration
Among genes that are highly expressed in tumors, this study searched for genes that are closely related to the high degree of immune-infiltration of immune cells. Also, the same method was used to identify the low expressed key genes. R package “VennDiagram [21]” was installed on R software to visualize these results. The receiver operating characteristic (ROC) curve of each key gene was used to assess the capability of distinguishing from patients for healthy individuals according to areas under this curve (AUC).
Construction of RUFY4 co-expression network
The cBioPortal offers researchers online assistance for studying multidimensional cancer genomics data [22]. To construct the co-expression network of RUFY4, genes with a Spearman correlation index > 0.55 were added to co-expression network.
Functional enrichment analysis
This study carried out functional classification and annotation of immune-associated genes on the website DAVID [23] by the methods of GO and KEGG analysis. The cut-off of p-value was 0.05. R packages “ggplot2” were used to visualize the top 10 terms of GO analysis and KEGG pathway analysis. Then, Cytoscape [24] was also applied to construct the pathway cross-talk network via a “Cluego” plug-in. Gene set enrichment analysis (GSEA) was performed by Windows desktop program v4.1.0. The GSEA result of RUFY4 was therefore conducted on all known genes ranked by enrichment scores from most positive and most negative. 1000 random sample permutations were carried out.
Prediction of immunotherapy response
ImmuCellAI was used to predict the response of Immune checkpoint blockade (ICB) therapy with the ICB response prediction being checked based on gene expression matrix [25]. This study conducted ICB prediction analysis online (http://bioinfo.life.hust.edu.cn/ImmuCellAI#!/analysis) based on the compositions and proportions of immune cells of patients in TCGA.
Cell culture and reagents
The human renal cell carcinoma cell line A498, 786O, CAKI, OSRC and control cell line HK2 were obtained from the American Type Culture Collection (ATCC, USA). Cells were cultured in with Dulbecco's modified eagle medium (DMEM, Gibco, USA) supplemented with 10 percent fetal bovine serum (FBS, Gibco, USA) and were cultured in the incubator at 37 °C, 5% carbon dioxide.
RNA interference
Small interfering RNA for RUFY4 was transfected in 786O and CAKI cell lines using Lipofectamine 6000 (Beyotime, China), respectively. The siRNA sequences for RUFY4 (GenePharma, China) were followings:
siRNA#1:5′–3′ CAAGGUCACCAAAGACCUAAG
siRNA#2:5′–3′ GGAGAAUCCACAAGUGCAAAC
siRNA#3:5′–3′ GCAGAGGGUCAGAGAACAACA
Cell lysates and total RNA were collected 72 h after the transfection to verify knockdown efficiency by western blot and qPCR.
Tissue samples
16 pairs of human ccRCC tissues and adjacent normal tissues were collected from Department of Urology, Union Hospital, Tongji Medical College (Wuhan, China) in 2020. This process had fully informed consent of the patients. And this study was approved by the Institutional Review Board of Huazhong University of Science and Technology. The license number of the ethical review for the study was S1892.
RNA isolation and real-time PCR analysis
The Magzol reagent (Thermo, Massachusetts, USA) was used to extract total RNA of tissues and cell lysates. 500 ng of total RNA from tissue and cell were applied for reverse transcription. qPCR analysis was conducted (LightCycler 480II; Roche, Basel, Switzerland) with the Hieff® qPCR SYBR Green Master Mix (11201ES03, Yeasen, China). Samples were normalized by Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH).
-
GAPDH
:
-
Forward 5′-CCAGAACATCATCCCTGCCT-3′
Reverse 5′-CCTGCTTCACCACCTTCTTG-3′
-
RUFY4
:
-
Forward 5′-ACGCCAAGAAGACATCCTGG-3′
Reverse 5′-CTCTGACCCTCTGCAACCAG-3′
Western blotting assays
The protein of cells and tissues was extracted by radio-immunoprecipitation assay (RIPA) protein lysis buffer (Beyotime, China) with protease inhibitor cocktail (Beyotime, China) and Phenylmethanesulfonylfluoride (PMSF, Beyotime, China). 30 µg of protein was subjected to sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) gel. The proteins were then separated by gel electrophoresis and transferred to polyvinylidene fluoride (PVDF, Roche, Basel, Switzerland) membranes. 5% nonfat dried skimmed milk was used to block the membranes for 1.5 h at room temperature. Then, the membranes were incubated overnight with primary antibodies.
RUFY4, LS‑C307570 LSBio, USA, dilution 1:2000
PDL1, A1645 ABclonal, China, dilution 1:1000
β-actin, AC026 ABclonal, China, dilution 1:100,000
Finally, the membranes were washed and incubated in blocking buffer with secondary antibodies (Anti-Rabbit AS014 ABclonal, China; Anti-Mouse AS003 ABclonal, China) for 2 h before detection.
Cell viability assays
Each 96‐well plate was plated with 2000 cells. The proliferation rate of cells was detected using the cell counting kit (CCK-8, Yeasen, China). 110 μL CCK8 solution (10 μL CCK8:100 μL medium) were added to each well and the 96-well plate was incubated in dark for 1 h. Cell viability was assessed at 0, 24, 48, 72 and 96 h upon treatments by NanoDrop 2000 spectrophotometer (NanoDrop Technologies, USA) at 450 nm.
Transwell assays
For migration and invasion assays, cells were cultured in serum-free medium for 24 h. Then, cells were plated in the top chamber of transwell chamber (REF3422, Corning, USA) and cells were allowed to invade through the Matrigel (Corning, USA, dilution 1:8) or not. With or without Matrigel were used for invasion and migration assay. After 24 h, cells invading the lower surface of the chamber membrane were fixed in 100% methanol. Then, cells were stained with 0.05% crystal violet and 10 fields were randomly photographed for counting. More details were described in previous study [26].