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Discovering master regulators in hepatocellular carcinoma: one novel MR, SEC14L2 inhibits cancer cells
Zhihui Li1, Yi Lou1,2, Guoyan Tian1
1Translational Medicine Center, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang 310015, P.R. China.
Abstract:
Identification of master regulator (MR) genes offers a relatively rapid and efficient way to characterize disease-specific molecular programs. Since strong consensus regarding commonly altered MRs in hepatocellular carcinoma (HCC) is lacking, we generated a compendium of HCC datasets from 21 studies and identified a comprehensive signature consisting of 483 genes commonly deregulated in HCC. We then used reverse engineering of transcriptional networks to identify the MRs that underpin the development and progression of HCC. After cross-validation in different HCC datasets, systematic assessment using patient-derived data confirmed prognostic predictive capacities for most HCC MRs and their corresponding regulons. Our HCC signature covered well-established liver cancer hallmarks, and network analyses revealed coordinated interaction between several MRs. One novel MR, SEC14L2, exerted an anti-proliferative effect in HCC cells and strongly suppressed tumor growth in a mouse model. This study advances our knowledge of transcriptional MRs potentially involved in HCC development and progression that may be targeted by specific interventions.
Insights
Researchers identified key master regulator (MR) genes in hepatocellular carcinoma (HCC) by analyzing 21 studies. A novel MR, SEC14L2, showed potential for targeted HCC therapy by suppressing tumor growth.
Area of Science:
- Genomics
- Cancer Biology
- Bioinformatics
Background:
- Master regulator (MR) gene identification aids in understanding disease-specific molecular programs.
- A lack of consensus on commonly altered MRs in hepatocellular carcinoma (HCC) necessitates comprehensive analysis.
Purpose of the Study:
- To identify commonly deregulated genes and master regulators (MRs) in hepatocellular carcinoma (HCC).
- To assess the prognostic predictive capacity of identified HCC MRs and their regulons.
- To uncover novel MRs for potential therapeutic interventions in HCC.
Main Methods:
- Compiled and analyzed a compendium of 21 HCC datasets.
- Employed reverse engineering of transcriptional networks to identify MRs.
- Validated MRs using cross-validation in HCC datasets and patient-derived data.
Main Results:
- Identified a comprehensive HCC signature of 483 commonly deregulated genes.
- Confirmed prognostic predictive capabilities for most identified HCC MRs and their regulons.
- Discovered a novel MR, SEC14L2, with anti-proliferative effects on HCC cells and tumor suppression in a mouse model.
Conclusions:
- The study provides a comprehensive signature and identifies key MRs involved in HCC development and progression.
- Network analyses revealed coordinated interactions among HCC MRs.
- The novel MR SEC14L2 presents a potential therapeutic target for HCC interventions.
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