The high incidence of hepatocellular carcinoma(HCC)recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapi...The high incidence of hepatocellular carcinoma(HCC)recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies.Over the past few decades,the emergence of transcriptome analysis tools,including real-time quantitative reverse transcription PCR,microarrays,and RNA sequencing,has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures.In recent years,the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment,which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets.In the present article,we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains:primary cancer cells;carcinogenic stimuli;and tumor microenvironment.We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics,surveillance,and treatment of HCC recurrence.展开更多
Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression.High levels of variation or noise can disrupt robust gene expression and result in tremendo...Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression.High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors.In this work,we showed evidence from single-cell RNA sequencing data analysis that microRNAs(miRNAs)can reduce gene expression noise at the mRNA level in mouse cells.We identified that the miRNA expression level,number of targets,target pool abundance,and miRNA-target interaction strength are the key features contributing to noise repression.miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner.By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits,we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations.Together,through the integrated analysis of single-cell RNA and miRNA expression profiles,we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.展开更多
基金Linkou Chang Gung Memorial Hospital,Taiwan,No.CORPG3L0271,No.CORPG3L0281,No.CMRPG3K2292,and No.CORPG3L0301Ministry of Science and Technology,No.MOST111-2314-B-182A-126.
文摘The high incidence of hepatocellular carcinoma(HCC)recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies.Over the past few decades,the emergence of transcriptome analysis tools,including real-time quantitative reverse transcription PCR,microarrays,and RNA sequencing,has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures.In recent years,the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment,which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets.In the present article,we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains:primary cancer cells;carcinogenic stimuli;and tumor microenvironment.We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics,surveillance,and treatment of HCC recurrence.
基金This work has been supported by the National Science Foundation of China(Grant Nos.61773230 and 61721003)XZ is supported in part by the Chan Zuckerberg Initiative(CZI)Human Cell Atlas(HCA)project.
文摘Isogenic cells growing in identical environments show cell-to-cell variations because of the stochasticity in gene expression.High levels of variation or noise can disrupt robust gene expression and result in tremendous consequences for cell behaviors.In this work,we showed evidence from single-cell RNA sequencing data analysis that microRNAs(miRNAs)can reduce gene expression noise at the mRNA level in mouse cells.We identified that the miRNA expression level,number of targets,target pool abundance,and miRNA-target interaction strength are the key features contributing to noise repression.miRNAs tend to work together in cooperative subnetworks to repress target noise synergistically in a cell type-specific manner.By building a physical model of post-transcriptional regulation and observing in synthetic gene circuits,we demonstrated that accelerated degradation with elevated transcriptional activation of the miRNA target provides resistance to extrinsic fluctuations.Together,through the integrated analysis of single-cell RNA and miRNA expression profiles,we demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.
