Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing.

BACKGROUND

Kidney renal clear cell carcinoma (KIRC), the main histological subtype of renal cell carcinoma, has a high incidence globally. Cell-in-cell structures (CICs), as a cellular biological phenomenon, play pivotal roles in cell competition, immune evasion and tumor progression in the context of KIRC.

METHODS

Data for this study were sourced from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were performed using the clusterProfiler package. Support vector machine-recursive feature elimination (SVM-RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) regression, implemented the caret and glmnet packages in R, were used to select biomarkers. The accuracy of these biomarkers was verified by using the receiver operating characteristic (ROC) curve as well as experiments (CCK-8 assay, wound healing assay, Transwell assay, and quantitative real-time PCR). The CIBERSORT algorithm was applied to explore the association between immune infiltration and the biomarkers. Further analysis explored the association between these biomarkers and clinicopathological characteristics of KIRC. For single-cell data, the Seurat package is used to read the sample data, and the SCTransform function is employed for normalization.

RESULTS

This study identified 1,256 DEGs which enriched in T-cell immune system regulation processes. Five hub genes (, , , , and ) were biomarkers with area under the curve (AUC) values > 0.8, indicating high predictive performance. validation experiments demonstrated that the expressions of all five biomarkers in KIRC cells were elevated, and the knockdown of could inhibit the migration and invasion of KIRC cells. Immune infiltration analysis showed higher proportions of T-cells and macrophages in tumor tissues. and expressions correlated significantly with stage and grade, while , , and were highly expressed in proliferative tumor cells.

CONCLUSION

This study provides new biomarkers for KIRC, offering valuable insights into its developmental mechanisms for the research of CIC in this disease.