For several decades, cancers have demonstrably been one of the most frequent causes of death worldwide. In addition to genetic causes, cancer can also be caused by epigenetic gene modifications. Frequently, tumor suppressor genes are epigenetically inactivated due to hypermethylation of their CpG islands, actively contributing to tumorigenesis. Since CpG islands are usually localized near promoters, hypermethylation of the promoter can have a major impact on gene expression. In this study, the potential tumor suppressor gene Receptor Interacting Serine/Threonine Protein Kinase 3 (RIPK3) was examined for an epigenetic regulation and its gene inactivation in melanomas. A hypermethylation of the RIPK3 CpG island was detected by bisulfite pyrosequencing and was accompanied by a correlated loss of its expression. In addition, an increasing RIPK3 methylation rate was observed with increasing tumor stage of melanomas. For further epigenetic characterization of RIPK3, epigenetic modulation was performed using a modified CRISPR/dCas9 (CRISPRa activation) system targeting its DNA hypermethylation. We observed a reduced fitness of melanoma cells by (re-)expression and demethylation of the RIPK3 gene using the epigenetic editing-based method. The tumor suppressive function of RIPK3 was evident by phenotypic determination using fluorescence microscopy, flow cytometry and wound healing assay. Our data highlight the function of RIPK3 as an epigenetically regulated tumor suppressor in melanoma, allowing it to be classified as a biomarker.

Background: The kidney’s tubular system relies on cell polarity and tight junctions to maintain structure and function and disruptions contribute to diseases like cancer. Loss of tight junction proteins such as Claudins can actively contribute to tumorigenesis. Results: We aimed to identify biomarkers for renal carcinoma, after kidney transplantation and conventional kidney tumors. We identified the epigenetic silencing of the Claudin 10 gene isoform B (CLDN10B) through DNA hypermethylation in renal cancers, including clear cell (ccRCC), papillary (pRCC) and post-transplantation renal carcinoma (PT-ccRCC). In contrast, CLDN10A was hypomethylated in ccRCC and pRCC. Differential methylation of the isoforms discriminates RCC from other malignancies. The epigenetic alteration of CLDN10B significantly correlated with reduced patient survival and advanced tumor staging. CLDN10B overexpression or induction significantly inhibited migration, cell cycle progression, and cellular growth. Using a CRISPR-based epigenetic editing tool reactivated CLDN10B to its endogenous level using VP160 and TET1 by promoter demethylation and significantly demonstrated its tumor-suppressive effects in 2D and 3D cell models. Conclusion: Our findings suggest that CLDN10B acts as a tumor suppressor, and its epigenetic regulation may represent a therapeutic target for RCC. Ultimately, understanding CLDN10B’s regulation and function could provide new insights into renal cancer treatment.

Studying epigenetic changes in cancer development can reveal the role of tumor suppressor genes and their regulation by DNA methylation. CpG islands, found in promoter regions, are of particular interest, as their hypermethylation can silence tumor suppressor gene expression. Here, we present a practical analysis pipeline for wet-lab biologists with the aim of identify novel epigenetically regulated tumor suppressors using freely available online tools. Bioinformatic platforms such as the R2 Genomics Analysis and Visualization Platform enable analysis of genomic organization, CpG islands, and regulatory elements. Differential methylation and gene expression analyses are based on datasets including TCGA, using tools such as MethSurv, TCGA Wanderer, and GEPIA2 to correlate DNA methylation with gene expression. This bioinformatic step is the basis for the tumor suppressor verification in the wet-lab. Using this pipeline, we identified CLDN10 and GJB2 as potential tumor suppressors in melanoma. Experimentally, our approach includes DNA methylation analysis based on DNA bisulfite conversion, combined bisulfite restriction analysis (CoBRA), pyrosequencing for specific CpG methylation quantification, and RT-PCR for RNA expression quantification. We verify these results in primary tumors, metastases, and cell line models. This approach supports efficient identification of novel epigenetically regulated tumor suppressors, providing practical research guidelines.