Low Levels of TRIM28-Interacting KRAB-ZNF Genes Associate with Cancer Stemness and Predict Poor Prognosis of Kidney Renal Clear Cell Carcinoma Patients.
Patrycja CzerwinskaAndrzej Adam MackiewiczPublished in: Cancers (2021)
Krüppel-associated box zinc finger (KRAB-ZNF) proteins are known to regulate diverse biological processes, such as embryonic development, tissue-specific gene expression, and cancer progression. However, their involvement in the regulation of cancer stemness-like phenotype acquisition and maintenance is scarcely explored across solid tumor types, and to date, there are no data for kidney renal clear cell cancer (KIRC). We have harnessed The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database transcriptomic data and used several bioinformatic tools (i.e., GEPIA2, GSCALite, TISIDB, GSEA, CIBERSORT) to verify the relation between the expression and genomic alterations in KRAB-ZNFs and kidney cancer, focusing primarily on tumor dedifferentiation status and antitumor immune response. Our results demonstrate a significant negative correlation between KRAB-ZNFs and kidney cancer dedifferentiation status followed by an attenuated immune-suppressive response. The transcriptomic profiles of high KRAB-ZNF-expressing kidney tumors are significantly enriched with stem cell markers and show a depletion of several inflammatory pathways known for favoring cancer stemness. Moreover, we show for the first time the prognostic role for several KRAB-ZNFs in kidney cancer. Our results provide new insight into the role of selected KRAB-ZNF proteins in kidney cancer development. We believe that our findings may help better understand the molecular basis of KIRC.
Keyphrases
- papillary thyroid
- stem cells
- gene expression
- poor prognosis
- squamous cell
- immune response
- lymph node metastasis
- chronic kidney disease
- emergency department
- epithelial mesenchymal transition
- end stage renal disease
- squamous cell carcinoma
- childhood cancer
- young adults
- transcription factor
- artificial intelligence
- peritoneal dialysis
- big data