Ring Finger Protein 125 Is an Anti-Proliferative Tumor Suppressor in Hepatocellular Carcinoma

DNA methylation biomarker panels for differentiating various liver adenocarcinomas, including hepatocellular carcinoma, cholangiocarcinoma, colorectal liver metastases and pancreatic adenocarcinoma liver metastases

BACKGROUND

DNA methylation biomarkers are one of the most promising tools for the diagnosis and differentiation of adenocarcinomas of the liver, which are among the most common malignancies worldwide. Their differentiation is important because of the different prognoses and treatment options. This study aimed to validate previously identified DNA methylation biomarkers that successfully differentiate between liver adenocarcinomas, including the two most common primary liver cancers, hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), as well as two common metastatic liver cancers, colorectal liver metastases (CRLM) and pancreatic ductal adenocarcinoma liver metastases (PCLM), and translate them to the methylation-sensitive high-resolution melting (MS-HRM) and digital PCR (dPCR) platforms.

METHODS

Our study included a cohort of 149 formalin-fixed, paraffin-embedded tissue samples, including 19 CRLMs, 10 PCLMs, 15 HCCs, 15 CCAs, 15 colorectal adenocarcinomas (CRCs), 15 pancreatic ductal adenocarcinomas (PDACs) and their paired normal tissue samples. The methylation status of the samples was experimentally determined by MS-HRM and methylation-specific dPCR. Previously determined methylation threshold were adjusted according to dPCR data and applied to the same DNA methylation array datasets (provided by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)) used to originally identify the biomarkers for the included cancer types and additional CRLM projects. The sensitivities, specificities and diagnostic accuracies of the panels for individual cancer types were calculated.

RESULTS

In the dPCR experiment, the DNA methylation panels identified HCC, CCA, CRC, PDAC, CRLM and PCLM with sensitivities of 100%, 66.7%, 100%, 86.7%, 94.7% and 80%, respectively. The panels differentiate between HCC, CCA, CRLM, PCLM and healthy liver tissue with specificities of 100%, 100%, 97.1% and 94.9% and with diagnostic accuracies of 100%, 94%, 97% and 93%, respectively. Reevaluation of the same bioinformatic data with new additional CRLM projects demonstrated that the lower dPCR methylation threshold still effectively differentiates between the included cancer types. The bioinformatic data achieved sensitivities for HCC, CCA, CRC, PDAC, CRLM and PCLM of 88%, 64%, 97.4%, 75.5%, 80% and 84.6%, respectively. Specificities between HCC, CCA, CRLM, PCLM and healthy liver tissue were 98%, 93%, 86.6% and 98.2% and the diagnostic accuracies were 94%, 91%, 86% and 98%, respectively. Moreover, we confirmed that the methylation of the investigated promoters is preserved from primary CRC and PDAC to their liver metastases.

CONCLUSIONS

The cancer-specific methylation biomarker panels exhibit high sensitivities, specificities and diagnostic accuracies and enable differentiation between primary and metastatic adenocarcinomas of the liver using methylation-specific dPCR. High concordance was achieved between MS-HRM, dPCR and bioinformatic data, demonstrating the successful translation of bioinformatically identified methylation biomarkers from the Illumina Infinium HumanMethylation450 BeadChip (HM450) and lllumina MethylationEPIC BeadChip (EPIC) platforms to the simpler MS-HRM and dPCR platforms.

Identification of the Shared Gene Signatures of HCK, NOG, RNF125 and Biological Mechanism in Pediatric Acute Lymphoblastic Leukaemia and Pediatric Sepsis

The shared mechanisms between pediatric acute lymphoblastic leukaemia (ALL) and pediatric sepsis are currently unclear. This study was aimed to explore the shared key genes of pediatric ALL and pediatric sepsis. The datasets involved were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between disease and control samples in GSE13904 and GSE79533 were intersected. The least absolute shrinkage and selection operator (LASSO) and the boruta analyses were performed in GSE13904 and GSE79533 separately based on shared DEGs, and shared key genes were obtained by taking the intersection of sepsis-related key genes and ALL-related key genes. Three shared key genes (HCK, NOG, RNF125) were obtained, that have a good diagnostic value for both sepsis and ALL. The correlation between shared key genes and differentially expressed immune cells was higher in GSE13904 and conversely, the correlation of which was lower in GSE79533. Suggesting that the sharing key genes had a different impact on the immune environment in pediatric ALL and pediatric sepsis. We make the case that this study provides a new perspective to study the relationship between pediatric ALL and pediatric sepsis.

RNF125, transcriptionally regulated by NFATC2, alleviates osteoarthritis via inhibiting the Wnt/β-catenin signaling pathway through degrading TRIM14

Osteoarthritis (OA) is a chronic joint disease characterized by the progressive degradation of articular cartilage. In this study, as determined by histological staining, the cartilage surface of the OA rats was damaged, defective and broken, and chondrocytes and proteoglycan were reduced. While moderate physical exercise showed protective effects on the cartilage. Besides, RNA-seq was performed to select a target protein and RNF125 (an E3 ubiquitin ligase) was decreased in the cartilage tissues of OA rats and increased after physiological exercise. However, the precise role of RNF125 in OA is still unknown. This work aimed to investigate the involvement and underlying mechanism of RNF125 in OA pathogenesis. Our results defined that adenovirus-mediated overexpression of RNF125 inhibited the degradation of extracellular matrix of chondrocytes induced by IL-1β, as revealed by increased chondrocyte viability, upregulated COL2A1 and ACAN levels, and downregulated MMP1, MMP13 and ADAMTS5 levels, which was abrogated by NR4A2 knockdown. In vivo, RNF125 relieved OA, manifested as reduced cartilage injury and increased chondrocytes. Mechanically, NFATC2 bound to the RNF125 promoter and directly regulated RNF125 transcription, as illustrated by luciferase reporter, Ch-IP and DNA pull-down assays. Furthermore, RNF125 overexpression inhibited the nuclear translocation of β-catenin, thus suppressing activation of the Wnt/β-catenin signaling pathway. Also, RNF125 as E3 ubiquitin ligase led to the ubiquitination and degradation of TRIM14 protein, and TRIM14 overexpression efficiently reversed the effects of RNF125 overexpression on OA progression. Totally, this study provides new insights into OA pathogenesis regulated by RNF125. RNF125 may be a novel biomarker for OA therapy.

Exploring tumor-normal cross-talk with TranNet: Role of the environment in tumor progression

There is a growing awareness that tumor-adjacent normal tissues used as control samples in cancer studies do not represent fully healthy tissues. Instead, they are intermediates between healthy tissues and tumors. The factors that contribute to the deviation of such control samples from healthy state include exposure to the tumor-promoting factors, tumor-related immune response, and other aspects of tumor microenvironment. Characterizing the relation between gene expression of tumor-adjacent control samples and tumors is fundamental for understanding roles of microenvironment in tumor initiation and progression, as well as for identification of diagnostic and prognostic biomarkers for cancers. To address the demand, we developed and validated TranNet, a computational approach that utilizes gene expression in matched control and tumor samples to study the relation between their gene expression profiles. TranNet infers a sparse weighted bipartite graph from gene expression profiles of matched control samples to tumors. The results allow us to identify predictors (potential regulators) of this transition. To our knowledge, TranNet is the first computational method to infer such dependencies. We applied TranNet to the data of several cancer types and their matched control samples from The Cancer Genome Atlas (TCGA). Many predictors identified by TranNet are genes associated with regulation by the tumor microenvironment as they are enriched in G-protein coupled receptor signaling, cell-to-cell communication, immune processes, and cell adhesion. Correspondingly, targets of inferred predictors are enriched in pathways related to tissue remodelling (including the epithelial-mesenchymal Transition (EMT)), immune response, and cell proliferation. This implies that the predictors are markers and potential stromal facilitators of tumor progression. Our results provide new insights into the relationships between tumor adjacent control sample, tumor and the tumor environment. Moreover, the set of predictors identified by TranNet will provide a valuable resource for future investigations.

RNF125 attenuates hepatocellular carcinoma progression by downregulating SRSF1-ERK pathway

Hepatocellular carcinoma (HCC) is one of the most deadly malignant cancers worldwide. Research into the crucial genes responsible for maintaining the aggressive behaviour of cancer cells is important for the clinical treatment of HCC. The purpose of this study was to determine whether the E3 ubiquitin ligase Ring Finger Protein 125 (RNF125) plays a role in the proliferation and metastasis of HCC. RNF125 expression in human HCC samples and cell lines was investigated using TCGA dataset mining, qRT‒PCR, western blot, and immunohistochemistry assays. In addition, 80 patients with HCC were studied for the clinical value of RNF125. Furthermore, the molecular mechanism by which RNF125 contributes to hepatocellular carcinoma progression was determined with mass spectrometry (MS), coimmunoprecipitation (Co-IP), dual-luciferase reporter assays, and ubiquitin ladder assays. We found that RNF125 was markedly downregulated in HCC tumour tissues, which was associated with a poor prognosis for patients with HCC. Moreover, the overexpression of RNF125 inhibited HCC proliferation and metastasis both in vitro and in vivo, whereas the knockdown of RNF125 exerted antithetical effects. Mechanistically, mass spectrometry analysis revealed a protein interaction between RNF125 and SRSF1, and RNF125 accelerated the proteasome-mediated degradation of SRSF1, which impeded HCC progression by inhibiting the ERK signalling pathway. Furthermore, RNF125 was detected to be the downstream target of miR-103a-3p. In this study, we identified that RNF125 is a tumour suppressor in HCC and inhibits HCC progression by inhibiting the SRSF1/ERK pathway. These findings provide a promising treatment target for HCC.