Transcriptional and epigenetic landscape of Ca2+-signaling genes in hepatocellular carcinoma

Calcium (Ca2+) signaling has a major role in regulating a wide range of cellular mechanisms, including gene expression, proliferation, metabolism, cell death, muscle contraction, among others. Recent evidence suggests that ~ 1600 genes are related to the Ca2+ signaling. Some of these genes' expression is altered in several pathological conditions, including different cancer types, and epigenetic mechanisms are involved. However, their expression and regulation in hepatocellular carcinoma (HCC) and the liver are barely known. Here, we aimed to explore the expression of genes involved in the Ca2+-signaling in HCC, liver regeneration, and hepatocyte differentiation, and whether their expression is regulated by epigenetic mechanisms such as DNA methylation and histone posttranslational modifications (HPM). Results show that several Ca2+-signaling genes' expression is altered in HCC samples; among these, a subset of twenty-two correlate with patients' survival. DNA methylation correlates with eight of these genes' expression, and Guadecitabine, a hypomethylating agent, regulates the expression of seven down-regulated and three up-regulated genes in HepG2 cells. The down-regulated genes displayed a marked decrease of euchromatin histone marks, whereas up-regulated genes displayed gain in these marks. Additionally, the expression of these genes is modulated during liver regeneration and showed similar profiles between in vitro differentiated hepatocytes and liver-derived hepatocytes. In conclusion, some components of the Ca2+-signaling are altered in HCC and displayed a correlation with patients' survival. DNA methylation and HMP are an attractive target for future investigations to regulate their expression. Ca2+-signaling could be an important regulator of cell proliferation and differentiation in the liver.

A MicroRNA-Based Network Provides Potential Predictive Signatures and Reveals the Crucial Role of PI3K/AKT Signaling for Hepatic Lineage Maturation

Background

Functions of miRNAs involved in tumorigenesis are well reported, yet, their roles in normal cell lineage commitment remain ambiguous. Here, we investigated a specific "transcription factor (TF)-miRNA-Target" regulatory network during the lineage maturation of biliary tree stem cells (BTSCs) into adult hepatocytes (hAHeps).

Method

Bioinformatic analysis was conducted based on our RNA-seq and microRNA-seq datasets with four human hepatic-lineage cell lines, including hBTSCs, hepatic stem cells (hHpSCs), hepatoblasts (hHBs), and hAHeps. Short time-series expression miner (STEM) analysis was performed to reveal the time-dependent dynamically changed miRNAs and mRNAs. GO and KEGG analyses were applied to reveal the potential function of key miRNAs and mRNAs. Then, the miRDB, miRTarBase, TargetScan, miRWalk, and DIANA-microT-CDS databases were adopted to predict the potential targets of miRNAs while the TransmiR v2.0 database was used to obtain the experimentally supported TFs that regulate miRNAs. The TCGA, Kaplan-Meier Plotter, and human protein atlas (HPA) databases and more than 10 sequencing data, including bulk RNA-seq, microRNA-seq, and scRNA-seq data related to hepatic development or lineage reprogramming, were obtained from both our or other published studies for validation.

Results

STEM analysis showed that during the maturation from hBTSCs to hAHeps, 52 miRNAs were downwardly expressed and 928 mRNA were upwardly expressed. Enrichment analyses revealed that those 52 miRNAs acted as pluripotency regulators for stem cells and participated in various novel signaling pathways, including PI3K/AKT, MAPK, and etc., while 928 mRNAs played important roles in liver-functional metabolism. With an extensive sorting of those key miRNAs and mRNAs based on the target prediction results, 23 genes were obtained which not only functioned as the targets of 17 miRNAs but were considered critical for the hepatic lineage commitment. A "TF-miRNA-Target" regulatory network for hepatic lineage commitment was therefore established and had been well validated by various datasets. The network revealed that the PI3K/AKT pathway was gradually suppressed during the hepatic commitment.

Conclusion

A total of 17 miRNAs act as suppressors during hepatic maturation mainly by regulating 23 targets and modulating the PI3K/AKT signaling pathway. The regulatory network uncovers possible signatures and guidelines enabling us to identify or obtain the functional hepatocytes for future study.

Modulatory effect of photobiomodulation on stem cell epigenetic memory: a highlight on differentiation capacity

Differentiation potential of stem cells into various lineages makes these cells as promising sources to treat multiple diseases. In this regard, the use of different strategies and protocols to increase differentiation capacity is highly demanded. Low-level laser therapy, a relatively noninvasive technique, has the capacity to accelerate the healing of numerous injuries and a portion of restorative capacity could be correlated with the stem cell activation and differentiation. Several mechanisms have been diagnosed to participate in orientation of stem cells to functional mature cells. Among them, the status of DNA methylation orchestrates the maintenance of tissue-specific gene expression during the differentiation procedure. DNA methylation is a momentous event in embryogenesis and functional maturation. This review article highlighted the potency of laser irradiation (low-level intensities) in the differentiation of stem cells by modulation of methylation. The analysis of these modalities could help us to understand the underlying mechanisms participating in the therapeutic effects of photobiomodulation.

Investigation mechanisms between normal, developing and regenerating livers for regenerative liver drug design

Aim: A systematic multimolecule drug design procedure is proposed for promoting hepatogenesis and liver regeneration. Materials & methods: Genome-wide microarray data including three hepatic conditions are obtained from the GEO database (GSE15238). System modeling and big data mining methods are used to construct real genome-wide genetic-and-epigenetic networks (GWGENs). Then, we extracted the core GWGENs by applying principal network projection on real GWGENs of normal, developing and regenerating livers, respectively. After that, we investigated the significant signal pathways and epigenetic modifications in the core GWGENs to identify potential biomarkers as drug targets. Result & conclusion: A multimolecule drug consisting of sulmazole, clofibrate, colchicine, furazolidone, nadolol, eticlopride and felbinac is proposed to target on novel biomarkers for promoting hepatogenesis and liver regeneration.

DNA methylation dynamic of bone marrow hematopoietic stem cells after allogeneic transplantation

BACKGROUND

Allogeneic hematopoietic stem cell transplantation (AHSCT) is a curative therapeutic approach for different hematological malignancies (HMs), and epigenetic modifications, including DNA methylation, play a role in the reconstitution of the hematopoietic system after AHSCT. This study aimed to explore global DNA methylation dynamic of bone marrow (BM) hematopoietic stem and progenitor cells (HSPCs) from donors and their respective recipients affected by acute myeloid leukemia (AML), acute lymphoid leukemia (ALL) and Hodgkin lymphoma (HL) during the first year after transplant.

METHODS

We measured DNA methylation profile by Illumina HumanMethylationEPIC in BM HSPC of 10 donors (t0) and their matched recipients at different time points after AHSCT, at day + 30 (t1), + 60 (t2), + 120 (t3), + 180 (t4), and + 365 (t5). Differential methylation analysis was performed by using R software and CRAN/Bioconductor packages. Gene set enrichment analysis was carried out on promoter area of significantly differentially methylated genes by clusterProfiler package and the mSigDB genes sets.

RESULTS

Results show significant differences in the global methylation profile between HL and acute leukemias, and between patients with mixed and complete chimerism, with a strong methylation change, with prevailing hyper-methylation, occurring 30 days after AHSCT. Functional analysis of promoter methylation changes identified genes involved in hematopoietic cell activation, differentiation, shaping, and movement. This could be a consequence of donor cell "adaptation" in recipient BM niche. Interestingly, this epigenetic remodeling was reversible, since methylation returns similar to that of donor HSPCs after 1 year. Only for a pool of genes, mainly involved in dynamic shaping and trafficking, the DNA methylation changes acquired after 30 days were maintained for up to 1 year post-transplant. Finally, preliminary data suggest that the methylation profile could be used as predictor of relapse in ALL.

CONCLUSIONS

Overall, these data provide insights into the DNA methylation changes of HSPCs after transplantation and a new framework to investigate epigenetics of AHSCT and its outcomes.

DNA methylation: an epigenetic mark of cellular memory

DNA methylation is a stable epigenetic mark that can be inherited through multiple cell divisions. During development and cell differentiation, DNA methylation is dynamic, but some DNA methylation patterns may be retained as a form of epigenetic memory. DNA methylation profiles can be useful for the lineage classification and quality control of stem cells such as embryonic stem cells, induced pluripotent cells and mesenchymal stem cells. During cancer initiation and progression, genome-wide and gene-specific DNA methylation changes occur as a consequence of mutated or deregulated chromatin regulators. Early aberrant DNA methylation states occurring during transformation appear to be retained during tumor evolution. Similarly, DNA methylation differences among different regions of a tumor reflect the history of cancer cells and their response to the tumor microenvironment. Therefore, DNA methylation can be a useful molecular marker for cancer diagnosis and drug treatment.

DNA methylation dynamics in cellular commitment and differentiation

DNA methylation is an essential epigenetic modification for mammalian development and is crucial for the establishment and maintenance of cellular identity. Traditionally, DNA methylation has been considered as a permanent repressive epigenetic mark. However, the application of genome-wide approaches has allowed the analysis of DNA methylation in different genomic contexts, revealing a more dynamic regulation than originally thought, as active DNA methylation and demethylation occur during cell fate commitment and terminal differentiation. Recent data provide insights into the contribution of different epigenetic factors, and DNA methylation in particular, to the establishment of cellular memory during embryonic development and the modulation of cell type-specific gene regulation programs to ensure proper differentiation. This review summarizes published data regarding DNA methylation changes along lineage specification and differentiation programs. We also discuss the current knowledge about DNA methylation alterations occurring in physiological and pathological conditions such as aging and cancer.

DeGNServer: deciphering genome-scale gene networks through high performance reverse engineering analysis

Analysis of genome-scale gene networks (GNs) using large-scale gene expression data provides unprecedented opportunities to uncover gene interactions and regulatory networks involved in various biological processes and developmental programs, leading to accelerated discovery of novel knowledge of various biological processes, pathways and systems. The widely used context likelihood of relatedness (CLR) method based on the mutual information (MI) for scoring the similarity of gene pairs is one of the accurate methods currently available for inferring GNs. However, the MI-based reverse engineering method can achieve satisfactory performance only when sample size exceeds one hundred. This in turn limits their applications for GN construction from expression data set with small sample size. We developed a high performance web server, DeGNServer, to reverse engineering and decipher genome-scale networks. It extended the CLR method by integration of different correlation methods that are suitable for analyzing data sets ranging from moderate to large scale such as expression profiles with tens to hundreds of microarray hybridizations, and implemented all analysis algorithms using parallel computing techniques to infer gene-gene association at extraordinary speed. In addition, we integrated the SNBuilder and GeNa algorithms for subnetwork extraction and functional module discovery. DeGNServer is publicly and freely available online.

Patterning and shaping the endoderm in vivo and in culture

The definitive endoderm (DE) was first defined as the innermost germ layer found in all metazoan embryos. During development, it gives rise to a vast array of specialized epithelial cell types lining the respiratory and digestive systems, and contributes to associated organs such as thyroid, thymus, lungs, liver, and pancreas. In the adult, the DE provides a protective barrier against the environment and assumes many essential functions including digestion, nutrient absorption, and glucose homeostasis. Since general endoderm formation and patterning have been reviewed recently in a comprehensive manner [1], we will only provide a brief summary of how extracellular signals and downstream transcription factors control endoderm patterning. We will then focus on emerging work addressing the chromatin remodeling events occurring during endoderm organ specification and discuss how these molecular tools can be used to engineer endodermal organs in vitro.