Dataset Information

Comprehensive transcriptome profiling of BET inhibitor-treated HepG2 cells.

ABSTRACT: Hepatocellular carcinoma (HCC) is the most common primary liver cancer and poor prognosis. Emerging evidence suggests that epigenetic alterations play a crucial role in HCC, suggesting epigenetic inhibition as a promising therapeutic approach. Indeed, the bromodomain and extra-terminal (BET) inhibitors inhibit the proliferation and invasion of various cancers but still lack a strong mechanistic rationale. Here, we identified the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) in human HCC cell line HepG2 treated with the BET inhibitors, JQ1, OTX015, or ABBV-075. We analyzed the correlation between DEmRNAs and DElncRNAs in common for the three inhibitors based on their expression profiles and performed functional annotation pathway enrichment analysis. Most of these shared DEmRNAs and DElncRNAs, including some novel transcripts, were downregulated, indicating decreased proliferation/adhesion and increased apoptosis/inflammation. Our study suggests that BET proteins play a crucial role in regulating cancer progression-related genes and provide a valuable resource for novel putative biomarkers and therapeutic targets in HCC.

SUBMITTER: Baek M

PROVIDER: S-EPMC9053788 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Comprehensive transcriptome profiling of BET inhibitor-treated HepG2 cells.

Baek Mina M Chai Jin Choul JC Choi Hae In HI Yoo Eunyoung E Binas Bert B Lee Young Seek YS Jung Kyoung Hwa KH Chai Young Gyu YG

PloS one 20220429 4

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and poor prognosis. Emerging evidence suggests that epigenetic alterations play a crucial role in HCC, suggesting epigenetic inhibition as a promising therapeutic approach. Indeed, the bromodomain and extra-terminal (BET) inhibitors inhibit the proliferation and invasion of various cancers but still lack a strong mechanistic rationale. Here, we identified the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) in ...[more]

PMID: 35486664

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Project description:Background: Sepsis, as a clinical emergency, usually causes multiorgan dysfunction and can lead to high mortality. Establishment of specific and sensitive biomarkers for early diagnosis is critical to identify patients who would benefit from targeted therapy. In this study, we investigated this syndrome by analyzing the transcriptome of peripheral blood mononuclear cells (PBMCs) from patients with sepsis and identified sepsis-specific biomarkers. Methods: In this study, a total of 87 patients with sepsis and 40 healthy controls from a prospective multicenter cohort were enrolled. Samples from 44 subjects (24 patients with sepsis and 20 healthy controls) were sequenced and the remaining patients were included in the validation group. Using high-throughput sequencing, a gene expression profile of PBMCs from patients with sepsis was generated to elucidate the pathophysiology of sepsis and identify sepsis-specific biomarkers. Results: Principal component analysis (PCA) and unsupervised hierarchical cluster analysis showed that patients with sepsis separated from healthy controls. A total of 1639 differentially expressed genes (DEGs) were identified (|log2 fold change|>2, adjusted P value <0.05) between these two groups, with 1278 (78.0%) upregulated and 361 (22.0%) downregulated in patients with sepsis. Gene Ontology (GO) analysis of the upregulated DEGs identified 194 GO terms that were clustered into 27 groups, and analysis of the downregulated DEGs identified 20 GO terms that were clustered into 4 groups. Four unique genes were identified that could be predictive of patients with sepsis. External validation of the four genes using quantitative real-time polymerase chain reaction (qRT-PCR) was consistent with the results of mRNA sequencing, revealing their potential in sepsis diagnosis. Conclusions: The transcriptome characteristics of PBMCs, which were significantly altered in sepsis patients, provide new insights into sepsis pathogenesis. The four identified gene expression changes differentiated patients with sepsis from healthy subjects, which could serve as a convenient tool contributing to sepsis diagnosis.

Dataset Information

Comprehensive transcriptome profiling of BET inhibitor-treated HepG2 cells.

Publications

Comprehensive transcriptome profiling of BET inhibitor-treated HepG2 cells.

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