Construction of a Cancer Stem Cell related Histone Acetylation Regulatory Genes Prognostic Model for Hepatocellular Carcinoma via Bioinformatics Analysis: Implications for Tumor Chemotherapy and Immunity

BACKGROUND

Cancer stem cells (CSC) play an important role in the development of Liver Hepatocellular Carcinoma (LIHC). However, the regulatory mechanisms between acetylation- associated genes (HAGs) and liver cancer stem cells remain unclear.

OBJECTIVE

To identify a set of histone acetylation genes (HAGs) with close associations to liver cancer stem cells (LCSCs), and to construct a prognostic model that facilitates more accurate prognosis assessments for LIHC patients.

METHODS

LIHC expression data were downloaded from the public databases. Using mRNA expression- based stemness indices (mRNAsi) inferred by One-Class Logistic Regression (OCLR), Differentially Expressed Genes (DEGs) (mRNAsi-High VS. mRNAsi-Low groups) were intersected with DEGs (LIHC VS. normal samples), as well as histone acetylation-associated genes (HAGs), to obtain mRNAsi-HAGs. A risk model was constructed employing the prognostic genes, which were acquired through univariate Cox and Least Shrinkage and Selection Operator (LASSO) regression analyses. Subsequently, independent prognostic factors were identified via univariate and multivariate Cox regression analyses and then a nomogram for prediction of LIHC survival was developed. Additionally, immune infiltration and drug sensitivity analysis were performed to explore the relationships between prognostic genes and immune cells. Finally, the expressions of selected mRNAsi-HAGs were validated in the LIHC tumor sphere by quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) assay and western blot analysis.

RESULTS

Among 13 identified mRNAsi-HAGs, 3 prognostic genes (HDAC1, HDAC11, and HAT1) were selected to construct a risk model (mRNAsi-HAGs risk score = 0.02 * HDAC1 + 0.09 * HAT1 + 0.05 * HDAC11). T-stage, mRNAsi, and mRNAsi-HAGs risk scores were identified as independent prognostic factors to construct the nomogram, which was proved to predict the survival probability of LIHC patients effectively. We subsequently observed strongly positive correlations between mRNAsi-HAGs risk score and tumor-infiltrating T cells, B cells and macrophages/monocytes. Moreover, we found 8 drugs (Mitomycin C, IPA 3, FTI 277, Bleomycin, Tipifarnib, GSK 650394, AICAR and EHT 1864) had significant correlations with mRNAsi-HAGs risk scores. The expression of HDAC1 and HDAC11 was higher in CSC-like cells in the tumor sphere.

CONCLUSION

This study constructed a mRNAsi and HAGs-related prognostic model, which has implications for potential immunotherapy and drug treatment of LIHC.

Long non-coding RNAs influence aging process of sciatic nerves in SD rats

OBJECTIVES

To investigate the long non-coding RNAs (lncRNAs) changes in the sciatic nerve (SN) in Sprague Dawley (SD) rats during aging.

METHODS

Eighteen healthy SD rats were selected at the age of 1 month (1M) and 24 months (24M) and SNs were collected. High-throughput transcriptome sequencing and bioinformatics analysis were performed. Protein-protein interaction (PPI) networks and competing endogenous RNA (ceRNA) networks were established according to differentially expressed genes (DEGs).

RESULT

As the length of lncRNAs increased, its proportion to the total number of lncRNAs decreased. A total of 4079 DElncRNAs were identified in Con vs. 24M. GO analysis was primarily clustered in nerve and lipid metabolism, extracellular matrix, and vascularization-related fields. There were 17 nodes in the PPI network of the target genes of up-regulating genes including Itgb2, Lox, Col11a1, Wnt5a, Kras, etc. Using quantitative RT-PCR, microarray sequencing accuracy was validated. There were 169 nodes constructing the PPI network of down-regulated target genes, mainly including Col1a1, Hmgcs1, Hmgcr. CeRNA interaction networks were constructed

CONCLUSION

Lipid metabolism, angiogenesis, and ECM fields might play an important role in the senescence process in SNs. Col3a1, Serpinh1, Hmgcr, and Fdps could be candidates for nerve aging research.

A quantitative trait GWAS on lens thickness identifies novel risk loci on PTPRM in the narrow angle individuals susceptible to PACG

PURPOSE

PACG is one of the leading causes of blindness where lens thickness is a major risk factor for narrow-angle individuals. To our knowledge, no literature has been reported on candidate gene for lens thickness as a quantitative trait (QT). Here, we performed a genome-wide association analysis on lens thickness in the narrow-angle individuals.

MATERIALS AND METHODS

We conducted a genome-wide association study (GWAS) in the narrow angle individuals to investigate comprehensive genetic insights on lens thickness.

RESULTS

 In QT-GWAS, we identified 145 genome-wide suggestive significant loci in the discovery cohort. Subsequently, we observed 13 SNPs that showed statistical significance around the region of PTRRM. Regional association analysis for top significant genotyped variants identified PTPRM as the most likely candidate for increased LT. Integrative bioinformatic analyses confirmed that the associated genomic region has potential regulatory roles for modulating transcription as enhancers. In the replication cohort, the sentinel genotype SNP was further associated significantly (P-value =0.000448) with high LT individuals. In both cohorts, the T allele of rs1941137 in the PTPRM gene indicates as a risk allele for the increased LT.

CONCLUSION

In this study, we discovered evidence of a genomic association between chromosomal areas around the PTPRM and increased lens thickness, resulting in a narrow angle. The regulatory components corresponding to PTPRM variations might have a role in the thicker lens. We report that the genomic region near PTPRM, a gene of potential interest, is associated with increased lens thickness.

A Study Against Colon Cancer Mechanism of Xanthium Sibiricum Herba Based on Computer Simulation and Bioinformatics

INTRODUCTION

Cancer is one of the leading causes of death worldwide, accounting for nearly one in six deaths in 2020. As a folk medicine, Xanthium sibiricum Herba (XSH) has been used many times in clinical practice for the treatment of various diseases. With the increasing number of cancer patients, there is a clinical need to find effective anti-cancer drugs.

AIM

This study aims to explores the bioactivity and the anti-cancer mechanism of XSH.

METHODS

In this study, bioinformatics, network pharmacology, molecular docking, molecular dynamics simulation techniques, and apoptosis assay were used to explore the bioactivity and the anti-cancer mechanism of XSH.

RESULTS

Finally, seven active ingredients in XSH after the screening were obtained, the two most active compounds were β-sitosterol and aloe-emodin, and good anti-cancer activity of XSH was predicted.

DISCUSSION

Four core targets were obtained from the PPI network map, namely Caspase-3 (CASP3), Transcription factor AP-1 (JUN), Myc proto-oncogene protein (MYC), and cellular tumor antigen p53 (TP53). GO and KEGG analyses showed that the mechanism of XSH anti-cancer is mainly related to the apoptosis process, and the main signaling pathways are enriched in the p53 signaling pathway, Apoptosis, and MAPK signaling. The molecular docking and molecular dynamics simulation results showed that CASP3, JUN, MYC, and TP53 had a high affinity with β-sitosterol and aloe-emodin. Bioinformatics analyses demonstrated the importance of core targets. Apoptosis assay showed that XSH could significantly promote the apoptosis of cancer cells, and inhibit their proliferation and migration, especially colon cancer cells.

CONCLUSION

This study uncovered the main active components, bioactivities, and potential targets of XSH, and further revealed the multi-component, multi-target, and multi-pathway mechanism of XSH for cancer treatment and promoting apoptosis.

Identification of PSMB9 and CXCL13 as immune-related diagnostic markers for rheumatoid arthritis by machine learning

BACKGROUND

Rheumatoid arthritis (RA) is a chronic inflammatory disease that causes significant physical and psychological damage. Although researchers have gained a better understanding of the mechanisms of RA, there are still difficulties in diagnosing and treating RA. We applied a data mining approach based on machine learning algorithms to explore new RA biomarkers and local immune cell status.

METHODS

We extracted six RA synovial microarray datasets from the GEO database and used bioinformatics to obtain differentially expressed genes (DEGs) and associated functional enrichment pathways. In addition, we identified potential RA diagnostic markers by machine learning strategies and validated their diagnostic ability for early RA and established RA, respectively. Next, CIBERSORT and ssGSEA analyses explored alterations in synovium-infiltrating immune cell subpopulations and immune cell functions in the RA synovium. Moreover, we examined the correlation between biomarkers and immune cells to understand their immune-related molecular mechanisms in the pathogenesis of RA.

RESULTS

We obtained 373 DEGs (232 upregulated and 141 downregulated genes) between RA and healthy controls. Enrichment analysis revealed a robust correlation between RA and immune response. Comprehensive analysis indicated PSMB9, CXCL13, and LRRC15 were possible potential markers. PSMB9 (AUC: 0.908, 95% CI:0.853-0.954) and CXCL13 (AUC: 0.890, 95% CI:0.836-0.937) also showed great diagnostic ability in validation dataset. Infiltrations of 16 kinds of the immune cell were changed, with macrophages being the predominant infiltrating cell type. Most proinflammatory pathways in immune cell function were activated in RA. The correlation analysis found the strongest positive correlation between CXCL13 and plasma cells, PSMB9, and macrophage M1.

CONCLUSIONS

There is a robust correlation between RA and local immune response. The immune-related CXCL13 and PSMB9 were identified as potential diagnostic markers for RA based on a machine learning approach. Further in-depth exploration of the target genes and associated immune cells can deepen the understanding of RA pathophysiological processes and provide new insights into diagnosing and treating RA.

UCEasy: A software package for automating and simplifying the analysis of ultraconserved elements (UCEs)

Background

The use of Ultraconserved Elements (UCEs) as genetic markers in phylogenomics has become popular and has provided promising results. Although UCE data can be easily obtained from targeted enriched sequencing, the protocol for in silico analysis of UCEs consist of the execution of heterogeneous and complex tools, a challenge for scientists without training in bioinformatics. Developing tools with the adoption of best practices in research software can lessen this problem by improving the execution of computational experiments, thus promoting better reproducibility.

New information

We present UCEasy, an easy-to-install and easy-to-use software package with a simple command line interface that facilitates the computational analysis of UCEs from sequencing samples, following the best practices of research software. UCEasy is a wrapper that standardises, automates and simplifies the quality control of raw reads, assembly and extraction and alignment of UCEs, generating at the end a data matrix with different levels of completeness that can be used to infer phylogenetic trees. We demonstrate the functionalities of UCEasy by reproducing the published results of phylogenomic studies of the bird genus Turdus (Aves) and of Adephaga families (Coleoptera) containing genomic datasets to efficiently extract UCEs.

MiR-17-5p and MKL-1 modulate stem cell characteristics of gastric cancer cells

Effectively targeting cancer stem cells to treat cancer has great therapeutic prospects. However, the effect of microRNA miR-17/MKL-1 on gastric cancer stem cells has not been studied yet. This study preliminarily explored the mechanism of miR-17/MKL-1 in gastric cancer stem cells. Many previous reports have indicated that microRNA and EMT regulated cancer stem cell characteristics, and miR-17 and MKL-1 were involved as a critical gene in migration and invasion in the EMT pathway. Through RT-PCR, Western Blot, flow cytometry, immunofluorescence, sphere formation xenograft tumor assays and drug resistance, the role of miR-17-5p and MKL-1 on promoting stem cell-like properties of gastric cancer were verified in vivo and vitro. Next, MKL-1 targets CD44, EpCAM, and miR -17-5p promoter verified by luciferase assay and ChIP. Besides, the TCGA database analysis found that both miR-17-5p and MKL-1 increased in gastric cancer, and the prognostic survival of the MKL-1 high expression group was reduced. It is found that MKL-1 promotes expression by targeting miR-17, CD44 and EpCAM promoters. Besides, the TCGA database analysis found that both miR-17-5p and MKL-1 increased in gastric cancer, and the prognostic survival of the MKL-1 high expression group was reduced. These findings reveal new regulatory signaling pathways for gastric cancer stem cells, thus it give new insights on potential early diagnosis and/or molecular therapy for gastric cancer.

Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches

Cartilage destruction in rheumatoid arthritis (RA) occurs primarily in the pannus-cartilage interface. The close contact of the synovium-cartilage interface implicates crosstalk between synovial fibroblasts and chondrocytes. The aim of this study is to explore the differentially expressed genes and novel microRNA regulations potentially implicated in the dysregulated cartilage homeostasis in joint destruction of RA. Total RNAs were extracted from human primary cultured normal and RA chondrocytes for RNA and small RNA expression profiling using next-generation sequencing. Using systematic bioinformatics analyses, we identified 463 differentially expressed genes in RA chondrocytes were enriched in biological functions related to altered cell cycle process, inflammatory response and hypoxic stimulation. Moreover, fibroblast growth factor 9 (FGF9), kynureninase (KYNU), and regulator of cell cycle (RGCC) were among the top dysregulated genes identified to be potentially affected in the RA joint microenvironment, having similar expression patterns observed in arrays of clinical RA synovial tissues from the Gene Expression Omnibus database. Additionally, among the 31 differentially expressed microRNAs and 10 candidate genes with potential microRNA-mRNA interactions in RA chondrocytes, the novel miR-140-3p-FGF9 interaction was validated in different microRNA prediction databases, and proposed to participate in the pathogenesis of joint destruction through dysregulated cell growth in RA. The findings provide new perspectives for target genes in the management of cartilage destruction in RA.

The Role of Deleterious Substitutions in Crop Genomes

Populations continually incur new mutations with fitness effects ranging from lethal to adaptive. While the distribution of fitness effects of new mutations is not directly observable, many mutations likely either have no effect on organismal fitness or are deleterious. Historically, it has been hypothesized that a population may carry many mildly deleterious variants as segregating variation, which reduces the mean absolute fitness of the population. Recent advances in sequencing technology and sequence conservation-based metrics for inferring the functional effect of a variant permit examination of the persistence of deleterious variants in populations. The issue of segregating deleterious variation is particularly important for crop improvement, because the demographic history of domestication and breeding allows deleterious variants to persist and reach moderate frequency, potentially reducing crop productivity. In this study, we use exome resequencing of 15 barley accessions and genome resequencing of 8 soybean accessions to investigate the prevalence of deleterious single nucleotide polymorphisms (SNPs) in the protein-coding regions of the genomes of two crops. We conclude that individual cultivars carry hundreds of deleterious SNPs on average, and that nonsense variants make up a minority of deleterious SNPs. Our approach identifies known phenotype-altering variants as deleterious more frequently than the genome-wide average, suggesting that putatively deleterious variants are likely to affect phenotypic variation. We also report the implementation of a SNP annotation tool BAD_Mutations that makes use of a likelihood ratio test based on alignment of all currently publicly available Angiosperm genomes.

Epigenetic repression of male gametophyte-specific genes in the Arabidopsis sporophyte

Tissue formation, the identity of cells, and the functions they fulfill, are results of gene regulation. The male gametophyte of plants, pollen, is outstanding in this respect as several hundred genes expressed in pollen are not expressed in the sporophyte. How pollen-specific genes are down-regulated in the sporophyte has yet to be established. In this study, we have performed a bioinformatics analysis of publicly available genome-wide epigenetics data of several sporophytic tissues. By combining this analysis with DNase I footprinting data, we assessed means by which the repression of pollen-specific genes in the Arabidopsis sporophyte is conferred. Our findings show that, in seedlings, the majority of pollen-specific genes are associated with histone-3 marked by mono- or trimethylation of Lys-27 (H3K27me1/H3K27me3), both of which are repressive markers for gene expression in the sporophyte. Analysis of DNase footprint profiles of pollen-specific genes in the sporophyte displayed closed chromatin proximal to the start codon. We describe a model of two-staged gene regulation in which a lack of nucleosome-free regions in promoters and histone modifications in open reading frames repress pollen-specific genes in the sporophyte.

Human Endogenous Retroviruses (HERVs) and Autoimmune Rheumatic Disease: Is There a Link?

Autoimmune rheumatic diseases, such as RA and SLE, are caused by genetic, hormonal and environmental factors. Human Endogenous Retroviruses (HERVs) may be triggers of autoimmune rheumatic disease. HERVs are fossil viruses that began to be integrated into the human genome some 30-40 million years ago and now make up 8% of the genome. Evidence suggests HERVs may cause RA and SLE, among other rheumatic diseases. The key mechanisms by which HERVS are postulated to cause disease include molecular mimicry and immune dysregulation. Identification of HERVs in RA and SLE could lead to novel treatments for these chronic conditions. This review summarises the evidence for HERVs as contributors to autoimmune rheumatic disease and the clinical implications and mechanisms of pathogenesis are discussed.

Differential expression profiling and functional analysis of microRNAs through stage I-III papillary thyroid carcinoma

OBJECTIVE

To elucidate the mechanisms undergoing the pathogenesis of PTC, this study try to find stage specific microRNAs (miRNAs) using microarray chip in stage I, II and III papillary thyroid carcinoma (PTC) tissues as well predict miRNAs binding target genes and their molecular functions.

METHODS

PTC specimens of stage I, II, and III and their paired adjacent non-tumor tissue (one patient for each stage) were collected. The expressions of miRNAs were examined using miRNA microarray chip. The most significant changed miRNAs from microarray were verified by using quantitative RT-PCR. The Potential miRNAs regulating target genes and their preliminary biological functions were forecasted with variety function prediction software.

RESULTS

Ten miRNAs exhibited sequential up regulation expression profiles and five miRNAs performed sequential down regulation throughout stage I to III (p<0.05). After normalization, Fifteen miRNAs showed significant different compared to adjacent non-tumor tissues (p<0.05). Among of them, the most significant up regulation and down regulation miRNAs were miR-146b-5p and miR-335, respectively. Both of them were verified with qRT-PCR. 34 target genes for miR-146-5p and 36 target genes for miR-335 was predicted.

CONCLUSION

MicroRNA profile assay successfully detected a branch of differential expression miRNAs between PTC and normal tissue. Some of them also showed stage specific. Biological function analysis showed that target genes were involved in five aspects including cell proliferation, differentiation, apoptosis, cycle, and signaling transduction pathway, suggesting the regulatory role of abnormal expression of critical miRNAs in the pathogenesis of PTC.

The microRNA Transcriptome of Human Cytomegalovirus (HCMV)

The purpose of the present study was to characterize the microRNA transcriptome (miRNAome) of the human cytomegalovirus (HCMV or HHV5). We used deep sequencing and real time PCR (qPCR) together with bioinformatics to analyze the pattern of small RNA expression in cells infected with low-passage isolates of HCMV as well as in plasma and amniotic fluid. We report here on the discovery of four new precursors and ten new miRNAs as well as eleven microRNA-offset-RNAs (moRs) that are all encoded by HCMV. About eighty percent of the total HCMV reads were perfectly mapped to HCMV miRNAs, strongly suggestive of their important biological role that in large remains still to be defined and characterized. Taken altogether, the results of this study demonstrate the power and usefulness of the combined bioinformatics/biological approach in discovering additional important members of HCMV- encoded small RNAs and can be applied to the study of other viruses as well.

The -omics Era- Toward a Systems-Level Understanding of Streptomyces

Streptomyces is a group of soil bacteria of medicinal, economic, ecological, and industrial importance. It is renowned for its complex biology in gene regulation, antibiotic production, morphological differentiation, and stress response. In this review, we provide an overview of the recent advances in Streptomyces biology inspired by -omics based high throughput technologies. In this post-genomic era, vast amounts of data have been integrated to provide significant new insights into the fundamental mechanisms of system control and regulation dynamics of Streptomyces.

Comparative analyses of plant transcription factor databases

Transcription factors (TFs) are proteinaceous complex, which bind to the promoter regions in the DNA and affect transcription initiation. Plant TFs control gene expressions and genes control many physiological processes, which in turn trigger cascades of biochemical reactions in plant cells. The databases available for plant TFs are somewhat abundant but all convey different information and in different formats. Some of the publicly available plant TF databases may be narrow, while others are broad in scopes. For example, some of the best TF databases are ones that are very specific with just one plant species, but there are also other databases that contain a total of up to 20 different plant species. In this review plant TF databases ranging from a single species to many will be assessed and described. The comparative analyses of all the databases and their advantages and disadvantages are also discussed.