Comprehensive analysis of m6 A methylome and transcriptome by Nanopore sequencing in clear cell renal carcinoma.

N6 -methyladenosine (m6 A) is the most prevalent epigenetic modification on eukaryotic messenger RNAs. Recent studies have focused on elucidating the key role of m6 A modification patterns in tumor progression. However, the relationship between m6 A and transcriptional regulation remains elusive. Nanopore technology enables the quantification of m6 A levels at each genomic site. In this study, a pair of tumor tissues and adjacent normal tissues from clear cell renal cell carcinoma (ccRCC) surgical samples were collected for Nanopore direct RNA sequencing. We identified 9644 genes displaying anomalous m6 A modifications, with 5343 genes upregulated and 4301 genes downregulated. Among these, 5224 genes were regarded as dysregulated genes, encompassing abnormal regulation of both m6 A modification and RNA expression. Gene Set Enrichment Analysis revealed an enrichment of these genes in pathways related to renal system progress and fatty acid metabolic progress. Furthermore, the χ2 test demonstrated a significant association between the levels of m6 A in dysregulated genes and their transcriptional expression levels. Additionally, we identified four obesity-associated genes (FTO, LEPR, ADIPOR2, and NPY5R) among the dysregulated genes. Further analyses using public databases revealed that these four genes were all related to the prognosis and diagnosis of ccRCC. This study introduced the novel approach of employing conjoint analysis of m6 A modification and RNA expression based on Nanopore sequencing to explore potential disease-related genes. Our work demonstrates the feasibility of the application of Nanopore sequencing technology in RNA epigenetic regulation research and identifies new potential therapeutic targets for ccRCC.

Small molecule NMD and MDM2 inhibitors synergistically trigger apoptosis in HeLa cells.

The nonsense-mediated mRNA decay (NMD) pathway and the p53 pathway, linked to tumorgenesis, are also promising targets for cancer treatment. NMD plays an important role in RNA quality control, while the p53 pathway is involved in cancer suppression. However, their individual and combined effects on cervical cancer are poorly understood. In this study, we evaluated the impacts of NMD inhibitor, Mouse double minute 2 homolog (MDM2) inhibitor, and their combination on cell apoptosis, cell cycle, and p53 target genes in human papillomavirus-18-positive HeLa cells. Our findings revealed that XR-2 failed to activate p53 or induce apoptosis in HeLa cells, whereas SMG1 (serine/threonine-protein kinase 1) inhibitor repressed cell proliferation at high concentrations. Notably, the combination of these 2 agents significantly inhibited cell proliferation, arrested the cell cycle, and triggered cell apoptosis. Mechanistically, MDM2 inhibitor and NMD inhibitor likely exert a synergistically through the truncated E6 protein. These results underscore the potential of employing a combination of MDM2 inhibitor and NMD inhibitor as a promising candidate for the clinical treatment of human papillomavirus-infected tumors.

Integrative analyses of multi-omics data constructing tumor microenvironment and immune-related molecular prognosis model in human colorectal cancer.

The increasing prevalence and incidence of colorectal cancer (CRC), particularly in young adults, underscore the imperative to comprehend its fundamental mechanisms, discover novel diagnostic and prognostic markers, and enhance therapeutic strategies. Here, we integrated multi-omics data, including gene expression, somatic mutation data and DNA methylation data, to unravel the intricacies of tumor microenvironment (TME) in CRC and search for novel prognostic markers. By calculating the immune score for each patient from the expression profile, we delineated the differential immune cell fraction, constructed an immune-related multi-omics atlas, and identified molecular characteristics. The entire colorectal dataset (n = 343) was randomly divided into training (n = 249) and testing datasets (n = 94). We screened 144 immune-related genes, 6 mutant genes, and 38 methylation probes associated with overall survival (OS). These makers were then incorporated into a 10-gene prognostic model using Lasso and Cox regression in the training dataset, and the model's performance was evaluated in an independent validation dataset. The model exhibited satisfactory results (average concordance index [C-index] = 0.77), with the average 1-year, 3-year, and 5-year AUCs being 0.79, 0.76, and 0.76 in the training dataset and 0.74, 0.80, and 0.90 in the testing dataset. Furthermore, the prognostic model demonstrated applicability in guiding chemotherapy for CRC patients and exhibited a degree of pan-cancer utility in risk stratification. In conclusion, our integrated analysis of multi-omics data revealed immune-related genetic and epigenetic characteristics of the TME. We propose an integrative prognostic model that can stratify risk and guide chemotherapy for CRC patients. The generalizability of the model in risk stratification across different cancer types was validated in Pan-Cancer cohort.