Background: ceRNAs have emerged as pivotal players in the regulation of gene expression and play a crucial role in the physiology and development of various cancers. Nevertheless, the function and underlying mechanisms of ceRNAs in esophageal cancer (EC) are still largely unknown. Methods: In this study, profiles of DEmRNAs, DElncRNAs, and DEmiRNAs between normal and EC tumor tissue samples were obtained from the Cancer Genome Atlas database using the DESeq package in R by setting the adjusted P2 as the cutoff. The ceRNA network (ceRNet) was initially constructed to reveal the interaction of these ceRNAs during carcinogenesis based on the bioinformatics of miRcode, miRDB, miRTarBase, and TargetScan. Then, independent microarray data of GSE6188, GSE89102, and GSE92396 and correlation analysis were used to validate molecular biomarkers in the initial ceRNet. Finally, a least absolute shrinkage and selection operator logistic regression model was built using an oncogenic ceRNet to diagnose EC more accurately. Results: We successfully constructed an oncogenic ceRNet of EC, crosstalk of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1. In addition, the risk-score model −0.0053*log₂(CADM2)+0.0168*log₂(SERPINE1)-0.0073*log₂(ADAMTS9-AS2)+0.0905*log₂(PVT1)+0.0047*log₂(hsa-miR372)–0.0193*log₂(hsa-miR145), (log₂[gene count]) could improve diagnosis of EC with an AUC of 0.988. Conclusion: We identified two novel pairs of ceRNAs in EC and its role of diagnosis. The pairs of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1 were likely potential carcinogenic mechanisms of EC, and their joint detection could improve diagnostic accuracy.

Background: The molecular complexity of colorectal cancer poses a significant challenge to the clinical implementation of accurate risk stratification. There is still an urgent need to find better biomarkers to enhance established risk stratification and guide risk-adapted treatment decisions. Methods: we systematically analyzed cancer dependencies of 17 colorectal cancer cells and 513 other cancer cells based on genome-scale CRISPR-Cas9 knockout screens to identify colorectal cancer-specific fitness genes. A regression model was built using colorectal cancer-specific fitness genes, which was validated in other three independent cohorts. 30 published gene expression signatures were also retrieved. Findings: We defined a total of 1828 genes that were colorectal cancer-specific fitness genes and identified a 22 colorectal cancer-specific fitness gene (CFG22) score. A high CFG22 score represented unfavorable recurrence and mortality rates, which was validated in three independent cohorts. Combined with age, and TNM stage, the CFG22 model can provide guidance for the prognosis of colorectal cancer patients. Analysis of genomic abnormalities and infiltrating immune cells in the CFG22 risk stratification revealed molecular pathological difference between the subgroups. Besides, drug analysis found that CFG22 high patients were more sensitive to clofibrate. Interpretation: The CFG22 model provided a powerful auxiliary prediction tool for identifying colorectal cancer patients with high recurrence risk and poor prognosis, optimizing precise treatment and improving clinical efficacy.

Background: HCC is one of the most prevalent and deadliest malignancies worldwide, with a poor prognosis. Altered histone modifications have been shown to play a significant role in HCC. However, the biological roles and clinical relevance of specific histone modifications, such as the asymmetric dimethylation on arginine 3 of histone H4 (H4R3me2a), remain poorly understood in HCC. Methods: In this study, immunohistochemical staining was performed to assess histone H4R3me2a modification in 32 pairs of HCC tissues and corresponding adjacent nontumor liver tissues. Cellular-level experiments and subcutaneous xenograft models in nude mice were used to investigate the effects of silencing protein arginine methyltransferase 1 (PRMT1) with shRNA or pharmacologically blocking PRMT1 activity on HCC cell proliferation, migration, and invasion. RNA-seq analysis combined with Chip-qPCR validation was employed to explore the regulatory mechanism of PRMT1 on SOX18 expression. The downstream target of SOX18 was identified using the JASPAR database and a dual-luciferase reporter system. Results: The level of histone H4R3me2a modification was significantly elevated in HCC tissues and closely associated with poor prognosis in patients with HCC. Silencing PRMT1 or pharmacologically inhibiting its activity effectively suppressed the proliferation, migration, and invasion of HCC cells. Mechanistically, PRMT1 was found to regulate SOX18 expression by modulating histone H4R3me2a modification in the SOX18 promoter region. LOXL1 was identified as a downstream target of the transcription factor SOX18. Conclusions: This study revealed the clinical relevance of histone H4R3me2a modification in HCC and demonstrated that PRMT1 promotes malignant behavior in HCC cells by modulating H4R3me2a modification in the SOX18 promoter region. The findings elucidate the role and molecular mechanism of PRMT1-mediated histone H4R3me2a modification in HCC progression and highlight the potential clinical applications of PRMT1 inhibitors. These results may provide new insights into the treatment of HCC.