In this study, we analyzed the clinical significance of ferroptosis-related genes (FRGs) in 32 cancer types in the GSCA database. We detected a 2-82% mutation rate among 36 FRGs. In clear cell renal cell carcinoma (ccRCC; n=539) tissues from the The Cancer Genome Atlas database, 30 of 36 FRGs were differentially expressed (up- or down-regulated) compared to normal kidney tissues (n=72). Consensus clustering analysis identified two clusters of FRGs based on similar co-expression in ccRCC tissues. We then used LASSO regression analysis to build a new survival model based on five risk-related FRGs (CARS, NCOA4, FANCD2, HMGCR, and SLC7A11). Receiver operating characteristic curve analysis confirmed good prognostic performance of the new survival model with an area under the curve of 0.73. High FANCD2, CARS, and SLC7A11 expression and low HMGCR and NCOA4 expression were associated with high-risk ccRCC patients. Multivariate analysis showed that risk score, age, stage, and grade were independent risk factors associated with prognosis in ccRCC. These findings demonstrate that this five risk-related FRG-based survival model accurately predicts prognosis in ccRCC patients, and suggest FRGs are potential prognostic biomarkers and therapeutic targets in several cancer types.

Emerging evidence has shown that the PIM serine/threonine kinase family, including PIM1, PIM2 and PIM3, is associated with tumour progression towards metastasis. PIM1, an attractive molecular target, has been identified as a potential prognostic biomarker for haematological and epithelial malignancies. However, to date, the potential regulatory roles and molecular mechanisms by which PIM1 affects the development and progression of cancers, including clear-cell renal-cell carcinoma (ccRCC), remain largely unknown. Herein, we present the first evidence that PIM1 is aberrantly overexpressed in human ccRCC tissues and cell lines and positively correlated with human ccRCC progression. In our study, depletion of PIM1 attenuated ccRCC cell proliferation, colony formation, migration, invasion and angiogenesis, suggesting that PIM1 expression may be a cancer-promoting event in ccRCC. Mechanistically, we observed that PIM1 could interact with Smad2 or Smad3 in the nucleus and subsequently phosphorylate Smad2 and Smad3 to induce the expression of transcription factors, including ZEB1, ZEB2, Snail1, Snail2 and Twist, to promote epithelial-mesenchymal transition (EMT). In addition, PIM1-mediated phosphorylation of c-Myc activates the expression of the above transcription factors to synergistically promote EMT but does not activate Smads. Collectively, our results demonstrate that aberrant expression of PIM1 contributes to ccRCC development and progression. Moreover, our data reveal a potential molecular mechanism in which PIM1 mediates crosstalk between signalling pathways, including different Smad proteins and c-Myc, which target downstream transcription factors (ZEB1, ZEB2, Snail1, Snail2 and Twist) to trigger EMT. Together, our data suggest that PIM1 may be a potential therapeutic target for ccRCC patients.

The purpose of this study was to investigate the genetic variation, gene expression differences, and clinical significance of SUMOylation regulators in pan-cancers. Based on previous studies, we gained a better understanding of the biological process of SUMOylation and the status of current research. In the present study, we employed a wide range of bioinformatics methods. We used genetic variation and mRNA expression data in the Cancer Genome Atlas (TCGA) to construct a panoramic view of the single nucleotide variants, copy number variants, and gene expression changes in SUMOylation regulators in various tumors. Subsequently, we used the String website and the Cytoscape tool to construct the PPI network between these regulators. We used the GSCALite website to determine the relationship between these regulators and cancer pathways and drug sensitivity. We constructed images of co-expression between these regulators using the R programming language. Using clinical data from TCGA, we performed hazard ratio analysis for these regulators in pan-cancer. Most importantly, we used these regulators to successfully establish risk signatures related to patient prognosis in multiple tumors. Finally, in KIRC, we conducted gene-set enrichment analysis (GSEA) of the five molecules in its risk signatures. We found that these five molecules are involved in multiple cancer pathways. In short, we have comprehensively interpreted the detailed biological process of SUMOylation at the genetic level for the first time, successfully constructed multiple risk signatures, and conducted GSEA in KIRC. We believe that these findings provide credible and valuable information that is relevant for future clinical diagnoses and scientific research.

Introduction: Papillary renal cell carcinoma (pRCC) is an important subtype of kidney cancer with a problematic pathological classification and highly variable clinical behavior. In this review, we summarize the current progression on pRCC in molecular level. Our findings highlight the need for molecular markers to accurately subtype PRCC and may lead to the development of more targeted agents and better patient stratification in clinical trials for pRCC. Areas covered：This review highlights the need for molecular markers to accurately subtype PRCC and may lead to the development of more targeted agents and better patient stratification in clinical trials for pRCC. Expert commentary: There are mainly two subtypes of pRCC based on histology. However, little is known about the genetic characterization of the sporadic forms of papillary renal cell carcinoma and there are currently no standard forms of therapy for patients with advanced disease. Both MET inhibitors and immunotherapy may be effective in advanced pRCC treatment. Therefore understanding the molecular basis of pRCC and identifying the main goal of treatment is crucial for the selection of the best strategy