Classification of Hepatocellular Carcinoma Based on N6-Methylandenosine–Related lncRNAs Profiling

Yin, Lu; Zhou, Liuzhi; Gao, Shiqi; Feng, Yina; Zhu, Hong-Jian; Xiang, Jingjing; Xu, Ruochen

doi:10.3389/fmolb.2022.807418

Cited by 12 publications

(14 citation statements)

References 38 publications

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“…Tumor purity is inversely proportional to the ratio of infiltrating immune cells (Yin et al, 2022). The relative ratios of infiltrating immune cells in each tumor sample were analyzed using the "preprocessCore", "limma", and "e1071" packages.…”

Section: Tumor Immune Microenvironment and Gene Set Enrichment Analysismentioning

confidence: 99%

Classification of stomach adenocarcinoma based on fatty acid metabolism-related genes frofiling

Liu¹,

Tao²,

Lin³

et al. 2022

Front. Mol. Biosci.

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Background: Fatty acid metabolism (FAM)-related genes play a key role in the development of stomach adenocarcinoma (STAD). Although immunotherapy has led to a paradigm shift in STAD treatment, the overall response rate of immunotherapy for STAD is low due to heterogeneity of the tumor immune microenvironment (TIME). How FAM-related genes affect TIME in STAD remains unclear.Methods: The univariate Cox regression analysis was performed to screen prognostic FAM-related genes using transcriptomic profiles of the Cancer Genome Atlas (TCGA)-STAD cohort. Next, the consensus clustering analysis was performed to divide the STAD cohort into two groups based on the 13 identified prognostic genes. Then, gene set enrichment analysis (GSEA) was carried out to identify enriched pathways in the two groups. Furthermore, we developed a prognostic signature model based on 7 selected prognostic genes, which was validated to be capable in predicting the overall survival (OS) of STAD patients using the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses. Finally, the “Estimation of STromal and Immune cells in MAlignant Tumours using Expression data” (ESTIMATE) algorithm was used to evaluate the stromal, immune, and ESTIMATE scores, and tumor purity of each STAD sample.Results: A total of 13 FAM-related genes were identified to be significantly associated with OS in STAD patients. Two molecular subtypes, which we named Group 1 and Group 2, were identified based on these FAM-related prognostic genes using the consensus clustering analysis. We showed that Group 2 was significantly correlated with poor prognosis and displayed higher programmed cell death ligand 1 (PD-L1) expressions and distinct immune cell infiltration patterns. Furthermore, using GSEA, we showed that apoptosis and HCM signaling pathways were significantly enriched in Group 2. We constructed a prognostic signature model using 7 selected FAM-related prognostic genes, which was proven to be effective for prediction of STAD (HR = 1.717, 95% CI = 1.105–1.240, p < 0.001). After classifying the patients into the high- and low-risk groups based on our model, we found that patients in the high-risk group tend to have more advanced T stages and higher tumor grades, as well as higher immune scores. We also found that the risk scores were positively correlated with the infiltration of certain immune cells, including resting dendritic cells (DCs), and M2 macrophages. We also demonstrated that elevated expression of gamma-glutamyltransferase 5 (GGT5) is significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and increased immune cell infiltration, suggesting that STAD patients with high GGT5 expression in the tumor tissues might have a better response to immunotherapy.Conclusion: FAM-related genes play critical roles in STAD prognosis by shaping the TIME. These genes can regulate the infiltration of various immune cells and thus are potential therapeutic targets worthy of further investigation. Furthermore, GGT5 was a promising marker for predicting immunotherapeutic response in STAD patients.

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Section: Tumor Immune Microenvironment and Gene Set Enrichment Analysismentioning

confidence: 99%

Classification of stomach adenocarcinoma based on fatty acid metabolism-related genes frofiling

Liu¹,

Tao²,

Lin³

et al. 2022

Front. Mol. Biosci.

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“…Patients with advanced metastatic and/or recurrent HCCs have failed to gain benefit over the long term from standard HCC treatments such as surgical resection and liver transplantation (3). Therefore, it is crucial to explore novel molecularly-targeted therapies and new prognostic factors for HCC patients (4)(5)(6). Very, recently, multiple personalized molecular subtypes of HCC have been reported.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics analysis and experimental verification of the prognostic and biological significance mediated by fatty acid metabolism related genes for hepatocellular carcinoma

Zhu

Zhu²,

Chen³

et al. 2022

Front. Oncol.

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BackgroundLiver cancer is among the leading causes of death related to cancer around the world. The most frequent type of human liver cancer is hepatocellular carcinoma (HCC). Fatty acid (FA) metabolism is an emerging hallmark that plays a promoting role in numerous malignancies. This study aimed to discover a FA metabolism-related risk signature and formulate a better model for HCC patients’ prognosis prediction.MethodsWe collected mRNA expression data and clinical parameters of patients with HCC using the TCGA databases, and the differential FA metabolism-related genes were explored. To create a risk prognostic model, we carried out the consensus clustering as well as univariate and multivariate Cox regression analyses. 16 genes were used to establish a prognostic model, which was then validated in the ICGC dataset. The accuracy of the model was performed using receiver operating characteristic (ROC) analyses, decision curve analysis (DCA) and nomogram. The immune cell infiltration level of risk genes was evaluated with single-sample GSEA (ssGSEA) algorithm. To reflect the response to immunotherapy, immunophenoscore (IPS) was obtained from TCGA-LIHC. Then, the expression of the candidate risk genes (p < 0.05) was validated by qRT-PCR, Western blotting and single-cell transcriptomics. Cellular function assays were performed to revealed the biological function of HAVCR1.ResultsAccording to the TCGA-LIHC cohort analysis, the majority of the FA metabolism-related genes were expressed differentially in the HCC and normal tissues. The prognosis of patients with high-risk scores was observed to be worse. Multivariate COX regression analysis confirmed that the model can be employed as an independent prognosis factor for HCC patients. Furthermore, ssGSEA analysis revealed a link between the model and the levels of immune cell infiltration. Our model scoring mechanism also provides a high predictive value in HCC patients receiving anti-PDL1 immunotherapy. One of the FA metabolism-related genes, HAVCR1, displays a significant differential expression between normal and HCC cell lines. Hepatocellular carcinoma cells (Huh7, and HepG2) proliferation, motility, and invasion were all remarkably inhibited by HAVCR1 siRNA.ConclusionOur study identified a novel FA metabolism-related prognostic model, revealing a better potential treatment and prevention strategy for HCC.

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“…Studies have shown that NRAV and AL031985.3 were highly expressed in HCC tissues, modified by m6A, and were associated with prognosis [ 49 , 50 ]. However, the mechanism by which m6A modifies these two lncRNAs remains unclear.…”

Section: Discussionmentioning

confidence: 99%

Analysis of the role of m6A and lncRNAs in prognosis and immunotherapy of hepatocellular carcinoma

Liu

2022

Heliyon

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Classification of Hepatocellular Carcinoma Based on N6-Methylandenosine–Related lncRNAs Profiling

Cited by 12 publications

References 38 publications

Classification of stomach adenocarcinoma based on fatty acid metabolism-related genes frofiling

Classification of stomach adenocarcinoma based on fatty acid metabolism-related genes frofiling

Bioinformatics analysis and experimental verification of the prognostic and biological significance mediated by fatty acid metabolism related genes for hepatocellular carcinoma

Analysis of the role of m6A and lncRNAs in prognosis and immunotherapy of hepatocellular carcinoma

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