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Integrated multi-omics analysis of the clinical relevance and potential regulatory mechanisms of splicing factors in hepatocellular carcinoma.

ABSTRACT: Splicing factors (SFs) have been increasingly documented to perturb the genome of cancers. However, little is known about the alterations of SFs in hepatocellular carcinoma (HCC). This study comprehensively delineated the genomic and epigenomic characteristics of 404 SFs in HCC based on the multi-omics data from the Cancer Genome Atlas database. The analysis revealed several clinically relevant SFs that could be effective biomarkers for monitoring the onset and prognosis of HCC (such as, HSPB1, DDX39A, and NELFE, which were the three most significant clinically relevant SFs). Functional enrichment analysis of these indicators showed the enrichment of pathways related to splicing and mRNA processes. Furthermore, the study found that SF copy number variation is common in HCC and could be a typical characteristic of hepato-carcinogenesis; the complex expression regulation of SFs was significantly affected by copy number variant and methylation. Several SFs with significant mutation patterns were identified (such as, RNF213, SF3B1, SPEN, NOVA1, and EEF1A1), and the potential regulatory network of SFs was constructed to identify their potential mechanisms for regulating clinically relevant alternative splicing events. Therefore, this study established a foundation to uncover the broad molecular spectrum of SFs for future functional and therapeutic studies of HCC.

SUBMITTER: Zhao YJ

PROVIDER: S-EPMC8806902 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Integrated multi-omics analysis of the clinical relevance and potential regulatory mechanisms of splicing factors in hepatocellular carcinoma.

Zhao Yu-Jia YJ Wu Lin-Yong LY Pang Jin-Shu JS Liao Wei W Chen Yu-Ji YJ He Yun Y Yang Hong H

Bioengineered 20211201 1

Splicing factors (SFs) have been increasingly documented to perturb the genome of cancers. However, little is known about the alterations of SFs in hepatocellular carcinoma (HCC). This study comprehensively delineated the genomic and epigenomic characteristics of 404 SFs in HCC based on the multi-omics data from the Cancer Genome Atlas database. The analysis revealed several clinically relevant SFs that could be effective biomarkers for monitoring the onset and prognosis of HCC (such as, HSPB1, ...[more]

PMID: 34288818

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Project description:BackgroundGlycosylation plays an essential role in driving the progression and treatment resistance of hepatocellular carcinoma (HCC). However, its function in regulating the acquisition and maintenance of the cancer stemness-like phenotype in HCC remains largely unknown. There is also very little known about how CAD and other potential glycosylation regulators may influence stemness. This study explores the relationship between glycosylation and stemness in HCC.MethodsGene set variance analysis (GSVA) was used to assess the TCGA pan-cancer enrichment in glycosylation-related pathways. Univariate, LASSO, and multivariate COX regression were then used to identify prognostic genes in the TCGA-LIHC and construct a prognostic signature. HCC patients were classified into high- and low-risk subgroups based on the signature. The relationship between gene expression profiles and stemness was confirmed using bulk and single-cell RNA-sequencing data. The role of CAD and other genes in regulating the stemness of HCC was also validated by RT-qPCR, CCK-8, and colony formation assay. Copy number variation (CNV), immune infiltration, and clinical features were further analyzed in different subgroups and subsequent gene expression profiles. Sensitive drugs were also screened.ResultsIn the pan-cancer analysis, HCC was shown to have specific glycosylation alterations. Five genes, CAD, SLC51B, LGALS3, B3GAT3, and MT3, identified from 572 glycosylation-related genes, were used to construct a gene signature and predict HCC patient survival in the TCGA cohort. The results demonstrated a significant positive correlation between patients in the high-risk group and both elevated gene expression and HCC dedifferentiation status. A significant reduction in the stemness-related markers, CD24, CD44, CD20, FOXM1, and EpCAM, was found after the knockdown of CAD and other genes in HepG2 and Huh7 cells. Frequent mutations increased CNVs, immune-suppressive responses, and poor prognosis were also associated with the high-risk profile. The ICGC-LIRI-JP cohort confirmed a similar relationship between glycosylation-related subtypes and stemness. Finally, 84 sensitive drugs were screened for abnormal glycosylation of HCC, and carfilzomib was most highly correlated with CAD.ConclusionsGlycosylation-related molecular subtypes are associated with HCC stemness and disease prognosis. These results provide new directions for further research on the relationship between glycosylation and stemness phenotypes.

Project description:BackgroundHepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and the development of accurate predictive models for prognosis and drug sensitivity remains challenging.MethodsWe integrated laboratory data and public cohorts to conduct a multi-omics analysis of HCC, which included bulk RNA sequencing, proteomic analysis, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics sequencing (ST-seq), and genome sequencing. We constructed a tumor purity (TP) and tumor microenvironment (TME) prognostic risk model. Proteomic analysis validated the TP-TME-related signatures. Joint analysis of scRNA-seq and ST-seq revealed characteristic clusters associated with TP high-risk subtypes, and immunohistochemistry confirmed the expression of key genes. We conducted functional enrichment analysis, transcription factor activity inference, cell-cell interaction, drug efficacy analysis, and mutation information analysis to identify a novel subtype of HCC.ResultsOur analyses constructed a robust HCC prognostic risk prediction model. The patients with TP-TME high-risk subtypes predominantly exhibit hypoxia and activation of the Wnt/beta-catenin, Notch, and TGF-beta signaling pathways. Furthermore, we identified a novel subtype, XPO1+Epithelial. This subtype expresses signatures of the TP risk subtype and aligns with the biological behavior of high-risk patients. Additional analyses revealed that XPO1+Epithelial is influenced primarily by fibroblasts via ligand-receptor interactions, such as FN1-(ITGAV+ITGB1), and constitute a significant component of the TP-TME subtype. Moreover, XPO1+Epithelial interact with monocytes/macrophages, T/NK cells, and endothelial cells through ligand-receptor pairs, including MIF-(CD74+CXCR4), MIF-(CD74+CD44), and VEGFA-VEGFR1R2, respectively, thereby promoting the recruitment of immune-suppressive cells and angiogenesis. The ST-seq cohort treated with Tyrosine Kinase Inhibitors (TKIs) and Programmed Cell Death Protein 1 (PD-1) presented elevated levels of TP and TME risk subtype signature genes, as well as XPO1+Epithelial, T-cell, and endothelial cell infiltration in the treatment response group. Drug sensitivity analyses indicated that TP-TME high-risk subtypes, including sorafenib and pembrolizumab, were associated with sensitivity to multiple drugs. Further exploratory analyses revealed that CTLA4, PDCD1, and the cancer antigens MSLN, MUC1, EPCAM, and PROM1 presented significantly increase expression levels in the high-risk subtype group.ConclusionsThis study constructed a robust prognostic model for HCC and identified novel subgroups at the single-cell level, potentially assisting in the assessment of prognostic risk for HCC patients and facilitating personalized drug therapy.

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Integrated multi-omics analysis of the clinical relevance and potential regulatory mechanisms of splicing factors in hepatocellular carcinoma.

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Integrated multi-omics analysis of the clinical relevance and potential regulatory mechanisms of splicing factors in hepatocellular carcinoma.

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