Integrated the analysis of single-cell and bulk RNA-sequencing to predict renal cell carcinoma by identifying signature based on Mitophagy-related Genes

Background The features of resistance to mitophagy contribute significantly to invasion, malignancy and cell survival. But the mechanism of mitophagy in clear cell renal cell carcinoma (ccRCC) remains unclear It is valuable to estimate mitophagy molecular characters as a clinical factor for prognosis and immune phenotypes in ccRCC. Methods Clinical data of ccRCC patients, including genome and transcriptome data, were downloaded from The Cancer Gene Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database. The differentially expressed genes (DEGs) of patient clusters determined by mitophagy gene expression and univariate Cox regression analysis were identified and used to classify patient clusters for constructing mitophagy scores via PCA analysis. Immune cell infiltration and immune cell function were analyzed by ssGSEA algorithm and TIDE algorithm. Results Based on the expression of mitophagy marker genes, ccRCC patients were divided into three mitophagy clusters with different gene expression patterns, prognosis and immune niches. 1,356 DEGs of mitophagy clusters related with prognosis were screened out for building mitophagy score. ccRCC patients with high mitophagy scores have better prognosis. Meanwhile, lower mitophagy patients with high expressed several immune-checkpoint proteins and had high immunophenoscore after immune-checkpoint blockers treatment, indicating better responsiveness to immune therapy. Conclusions mitophagy features are tightly correlated with ccRCC prognosis and immune responsiveness. mitophagy score built here is able to predict the prognosis and immune features of ccRCC patients and be indicative for immunotherapy.