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Identification and Characterization of Alcohol-related Hepatocellular Carcinoma Prognostic Subtypes based on an Integrative N6-methyladenosine methylation Model.

ABSTRACT: Background: Alcohol consumption increases the risk of hepatocellular carcinoma (HCC), and associated with a high mortality rate and poor prognosis. N6-methyladenosine (m6A) methylations play key roles in tumorigenesis and progression. However, our current knowledge about m6A in alcohol-related HCC (A-HCC) remains elucidated. Herein, the authors construct an integrative m6A model based on A-HCC subtyping and mechanism exploration workflow. Methods: Based on the m6A expressions of A-HCC and in vivo experiment, different prognosis risk A-HCC subtypes are identified. Meanwhile, multiple interdependent indicators of prognosis including patient survival rate, clinical pathological prognosis and immunotherapy sensitivity. Results: The m6A model includes LRPPRC, YTHDF2, KIAA14219, and RBM15B, classified A-HCC patients into high/low-risk subtypes. The high-risk subtype compared to the low-risk subtype showed phenotypic malignancy, poor prognosis, immunosuppression, and activation of tumorigenesis and proliferation-related pathways, including the E2F target, DNA repair, and mTORC1 signalling pathways. The expression of Immunosuppressive cytokines DNMT1/EZH2 was up-regulated in A-HCC patients, and teniposide may be a potential therapeutic drug for A-HCC. Conclusion: Our model redefined A-HCC prognosis risk, identified potential m6As linking tumour progress and immune regulations and selected possible therapy target, thus promoting understanding and clinical applications about A-HCC.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC8416726 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Purpose: N6-methyladenosine (m6A) RNA methylation has been implicated in various malignancies. This study aimed to identify the m6A methylation regulator-based prognostic signature for hepatocellular carcinoma (HCC) as well as provide candidate targets for HCC treatment. Methods: The least absolute shrinkage and selection operator (LASSO) analyses were performed to identify a risk signature in The Cancer Genome Atlas (TCGA) datasets. The risk signature was further validated in International Cancer Genome Consortium (ICGC) and Pan-Cancer Analysis of Whole Genomes (PCAWG) datasets. Following transfection of short hairpin RNA (shRNA) targeting YTHDF1, the biological activities of HCC cells were evaluated by Cell Counting Kit-8 (CCK-8), wound-healing, Transwell, flow cytometry, and xenograft tumor assays, respectively. The potential mechanisms mediated by YTHDF1 were predicted by overrepresentation enrichment analysis (ORA)/gene set enrichment analysis (GSEA) and validated by Western blotting. Results: Overexpression of m6A RNA methylation regulators was correlated with malignant clinicopathological characteristics of HCC patients. The Cox regression and LASSO analyses identified a risk signature with five m6A methylation regulators (KIAA1429, ZC3H13, YTHDF1, YTHDF2, and METTL3). In accordance with HCC cases in TCGA, the prognostic value of risk signature was also determined in ICGC and PCAWG datasets. Following analyzing the expression and clinical implications in TCGA and Gene Expression Omnibus (GEO), YTHDF1 was chosen for further experimental validation. Knockdown of YTHDF1 significantly inhibited the proliferation, migration, and invasion of HCC cells, as well as enhanced the apoptosis in vitro. Moreover, silencing YTHDF1 repressed the growth of xenograft tumors in vivo. Mechanism investigation indicated that YTHDF1 might promote the aggressive phenotypes by facilitating epithelial-mesenchymal transition (EMT) and activating AKT/glycogen synthase kinase (GSK)-3?/?-catenin signaling. Conclusion: The current study identified a robust risk signature consisting of m6A RNA methylation regulators for HCC prognosis. In addition, YTHDF1 was a potential molecular target for HCC treatment.

Project description:N6‑methyladenosine (m6A) RNA methylation is the most prevalent type of mRNA modification; however, little is known about its function in clear cell renal cell carcinoma (ccRCC). The present study aimed to establish and validate a m6A‑related risk signature as a prognostic factor for patients with ccRCC. Consensus clustering was used to divide patients with ccRCC from The Cancer Genome Atlas (TCGA) cohort (n=489) into three clusters (cluster 1/2/3) based on 19 m6A RNA methylation regulators. In addition, a m6A‑related risk signature was constructed using TCGA data, and its accuracy was validated using data from the International Cancer Genome Consortium (n=91). The prognostic performance of the risk signature was evaluated by Kaplan‑Meier analyses, least absolute shrinkage and selection operator Cox regression, multivariate Cox regression, receiver operating characteristic curves and nomograms. The results revealed that the majority of the 19 m6A RNA methylation regulators were differentially expressed among ccRCC stratified by different clinicopathological features. The cluster 1 group exhibited a higher frequency of metastasis and poorer overall survival compared with the cluster 2/cluster 3 group. The hallmarks of RNA metabolism, transcription misregulation in cancer and regulation of autophagy, were significantly enriched in the cluster 1 group. A m6A‑related risk signature was constructed and validated with high prognostic accuracy for the prediction of 5‑year survival and recurrence (area under the curve, 0.736 and 0.728, respectively). The present study also established robust nomograms for evaluating the risk of mortality and recurrence for patients with ccRCC (c‑index, 0.783 and 0.819, respectively). The dysregulation of hub m6A RNA methylation regulator expression levels and m6A RNA methylation levels were also validated in multiple RCC cells using in vitro experiments. Taken together, the m6A RNA methylation regulators promoted the malignant progression of ccRCC and exhibited good performance in prognostic predictions. These results provided insight into the development of m6A‑targeted treatments for ccRCC.

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Identification and Characterization of Alcohol-related Hepatocellular Carcinoma Prognostic Subtypes based on an Integrative N6-methyladenosine methylation Model.

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