Databases, patients and cell linesThe experimental database utilized in this study was the KIRC cohort. Clinical information and the RNA-seq data (KIRC, N = 72, T = 532) of this cohort were obtained from the TCGA website (https://portal.gdc.cancer.gov/). External validation databases included the International Cancer Genome Consortium (ICGC) database (RECA-EU, N = 45, T = 91. http://dcc.icgc.org) and the GEO database (GSE40435, N = 101, T = 101. https://www.ncbi.nlm.nih.gov/geo/). Table 1 displayed the clinical data from each database. The expression levels of SHC1 in tissues and cell lines were obtained from the GTEx website (https://gtexportal.org/home/) and the CCLE website (https://sites.broadinstitute.org/ccle).Table 1 Summary of the clinical characteristics of ccRCC patients.Tissue samples were collected from nine ccRCC patients recruited from Ningbo Urology and Nephrology Hospital (NBUNH). This study was approved by the Ethics Committee of NBUNH and written informed consent was obtained from all included patients. The 786-O, ACHN, OS-RC-2 and HK-2 cell lines were purchased from the National Collection of Authenticated Cell Cultures (Shanghai, China). ACHN and HK-2 cells were cultured using DMEM (HyClone, Logan, Utah, USA), while 786-O and OS-RC-2 cells were cultured with RPMI-1640 medium (HyClone). All cells were cultured in a CO2 incubator at a constant temperature of 37 °C.mRNA expression levels and immunohistochemistry in tissues and cell linesThe R packages of “ggplot2” and “ggpubr” were applied to draw boxplots, comparing the mRNA expression levels of SHC1 in the experimental cohort and external databases. The R packages of “plyr” and “ggpubr” were used to map the expression levels of SHC1 in different human normal tissues and in various tumor cell lines. The R package of “GOplot” was used to graph the expression of SHC1 in ccRCC cell lines. The Human Protein Atlas website (https://www.proteinatlas.org/) was utilized to validate the protein expression level of SHC1.For clinical samples or cells, total RNA was extracted by E.Z.N.A.® Total RNA Kit (Omega Bio-Tek, Norcross, GA, USA). A total of 1 µg RNA was reverse-transcribed into cDNA using ABScript II RT Master Mix (ABclonal, Woburn, USA). Real-time quantitative polymerase chain reaction (RT-qPCR) was performed on a 7500 real-time PCR system with 2X Universal SYBR Green Fast qPCR Mix (ABclonal, Woburn, USA) according to the manufacturer’s instructions. The primer sequences utilized were as follows: The forward primer for SHC1 was 5ʹ-GAACAAGCTGAGTGGAGGCG-3ʹ and the reverse primer was 5ʹ-CCATGTACCGAACCAAGTAGGAA-3ʹ. The forward and reverse primers for GAPDH were 5ʹ-GGAAGCTTGTCATCAATGGAAATC-3ʹ and 5ʹ-TGATGACCCTTTTGGCTCCC-3ʹ, respectively. Relative gene expression was normalized to that of GAPDH and the 2−ΔΔCt method was used to calculate the relative expression levels of SHC1.Western blot and cell culturesLysis was performed using RIPA buffer (Cat#R0010, Solarbio) containing 1% protease inhibitor PMSF for 5 min on ice. The lysate was subsequently centrifuged at 12,000 rpm for 10 min. The protein concentration was determined using the BCA method. Equal protein concentrations (25 µg) were separated on a 12% SDS-PAGE. The proteins were then transferred onto PVDF membranes (Millipore, Billerica, MA) and blocked for 1.5 h with 5% (w/v) non-fat dry milk at room temperature. Membranes were incubated with rabbit SHC1 (Cat#ab33770, Abcam) and rabbit GAPDH (Cat#5714s, CST) antibodies, respectively, at 4 °C overnight. Next, the membranes were washed three times with TBST, after which they were probed with Goat Anti-rabbit HRP-coupled secondary antibody (Cat#BA1055, Boster) for 1.5 h at room temperature. Finally, protein bands were visualized using an enhanced chemiluminescence reagent (Cat#180810-45, Advansta) and analyzed by Tannon GIS software.Clinical relevanceAccording to the clinical information and expression data from TCGA, the R package of “ComplexHeatmap” was used to create heatmaps and subsequently compare differences in traditional clinicopathological parameters between the high and low SHC1 expression groups. Univariate and multivariate Cox regression analyses were conducted using the “survival” package to assess the independence of SHC1 from traditional clinical factors. The survival rates of the SHC1 high- and low-expression groups were graphed using the “survival” and “survivminer” packages. A nomogram was constructed using the ‘regplot’ and ‘rms’ packages to display the association between SHC1 expression and other clinical parameters for predicting 1-, 3-, 5-, and 8-year overall survival (OS).Function and pathway analysisBased on the criteria of a |Pearson correlation coefficient|> 0.50 and P < 0.001, we identified 164 genes related to SHC1. Supplementary 1 provides further details. The R packages of “clusterProfiler”, “org.Hs.eg.db”, “enrichplot”, “ggplot2”, “R.Utls” and “pathview” were used to analyze and plot pathways via gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). For gene set enrichment analysis, we searched MSigDB gene sets (http://software.broadinstitute.org/gsea/msigdb/index.jsp) of “c5.go.v7.4.symbols.gmt” and “c2.cp.kegg.v7.4.symbols.gmt” to study the situation in KIRC for various functions in different SHC1 expression groups.Tumor immune infiltrationTo analyze tumor immune infiltration, we utilized two different methods to confirm our findings. The CIBERSORT algorithm was employed to examine the relationship between SHC1 expression and 22 kinds of immune cells, visualized through a bar diagram. The ssGSEA algorithm could comprehensively quantified the relative abundance of immune cell types, pathways, functions, and checkpoints in each patient based on 29 immune gene sets (infiltration scores of 16 immune cells and activity of 13 immune-related pathways). The GSVA package was used to compare the differences between the high and low SHC1 expression groups.Prediction of immune escape and immune responseBox plots were used to illustrate the relationship between SHC1 expression and immune checkpoints. The TIDE database (http://tide.dfci.harvard.edu) was employed to evaluate immune escape. To explore potential immune functions in high- and low-SHC1 expression groups, expression matrices were uploaded to the TIDE website. Additionally, immune phenotype scores from the TCIA (https://tcia.at/) were used to evaluate the immune properties of two immune checkpoint inhibitors (ICIs): CTLA4 and PD1, under varying expression levels of SHC1.Statistical analysisAll statistical analyses were performed by R software version v4.1.1 (https://www.r-project.org/). A P value < 0.05 was considered to be statistically significant. We have marked * to clarify the different values, where * means P < 0.05, ** means P < 0.01, and *** means P < 0.001.Ethics approval and consent to participateThe study was conducted in accordance with the Declaration of Helsinki. It was approved by the Ethics Committee of the Ningbo Urology and Nephrology Hospital (No.2023020). Written informed consent has been obtained from the patient(s) to publish this paper.
