Involvement of erbB4 and tumor marker genes in renal carcinoma regulatory network

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics

Objective

This study aimed to delineate the clear cell renal cell carcinoma (ccRCC) intrinsic subtypes through unsupervised clustering of radiomics and transcriptomics data and to evaluate their associations with clinicopathological features, prognosis, and molecular characteristics.

Methods

Using a retrospective dual-center approach, we gathered transcriptomic and clinical data from ccRCC patients registered in The Cancer Genome Atlas and contrast-enhanced computed tomography images from The Cancer Imaging Archive and local databases. Following the segmentation of images, radiomics feature extraction, and feature preprocessing, we performed unsupervised clustering based on the "CancerSubtypes" package to identify distinct radiotranscriptomic subtypes, which were then correlated with clinical-pathological, prognostic, immune, and molecular characteristics.

Results

Clustering identified three subtypes, C1, C2, and C3, each of which displayed unique clinicopathological, prognostic, immune, and molecular distinctions. Notably, subtypes C1 and C3 were associated with poorer survival outcomes than subtype C2. Pathway analysis highlighted immune pathway activation in C1 and metabolic pathway prominence in C2. Gene mutation analysis identified VHL and PBRM1 as the most commonly mutated genes, with more mutated genes observed in the C3 subtype. Despite similar tumor mutation burdens, microsatellite instability, and RNA interference across subtypes, C1 and C3 demonstrated greater tumor immune dysfunction and rejection. In the validation cohort, the various subtypes showed comparable results in terms of clinicopathological features and prognosis to those observed in the training cohort, thus confirming the efficacy of our algorithm.

Conclusion

Unsupervised clustering based on radiotranscriptomics can identify the intrinsic subtypes of ccRCC, and radiotranscriptomic subtypes can characterize the prognosis and molecular features of tumors, enabling noninvasive tumor risk stratification.

Low expression of PDK1 inhibits renal cell carcinoma cell proliferation, migration, invasion and epithelial mesenchymal transition through inhibition of the PI3K-PDK1-Akt pathway

As the most commonly occurring form of primary renal tumor, renal cell carcinoma (RCC) is a malignancy accompanied by a high mortality rate. 3-phosphoinositide-dependent protein kinase 1 (PDK1) has been established as a protein target and generated considerable interest in both the pharmaceutical and academia industry. The aim of the current study was to investigate the effect of si-PDK1 on the RCC cell apoptosis, proliferation, migration, invasion and epithelial mesenchymal transition (EMT) in connection with the PI3K-PDK1-Akt pathway. Microarray analysis from the GEO database was adopted to identify differentially expressed genes (DEGs) related to RCC, after which the positive expression of the PDK1 protein in tissue was determined accordingly. The optimal silencing si-RNA was subsequently selected and RCC cell lines 786-O and A498 were selected and transfected with either a si-PDK1 or activator of the PI3K-PDK1-Akt pathway for grouping purposes. The mRNA and protein expressions of PDK1, the PI3K-PDK1-Akt pathway-, EMT- and apoptosis-related genes were then evaluated. The effect of si-PDK1 on cell proliferation, apoptosis, invasion and migration was then analyzed. Through microarray analysis of GSE6344, GSE53757, GSE14762 and GSE781, PDK1 was examined. PDK1 was determined to be highly expressed in RCC tissues. Si-PDK1 exhibited marked reductions in relation to the mRNA and protein expression of PDK1, PI3K, AKT as well as Vimentin while elevated mRNA and protein expressions of E-cadherin were detected, which ultimately suggested that cell migration, proliferation and invasion had been inhibited coupled with enhanced levels of cell apoptosis. While a notable observation was made highlighting that the PI3K-PDK1-Akt pathway antagonized the effect of PDK1 silencing. Taken together, the key observations of this study provide evidence suggesting that high expressions of PDK1 are found in RCC, while highlighting that silencing PDK1 could inhibit RCC cell proliferation, migration, invasion and EMT by repressing the PI3K-PDK1-Akt pathway.