Multiomics integration reveals the effect of Orexin A on glioblastoma

Objectives: This study involved a multi-omics analysis of glioblastoma (GBM) samples to elaborate the potential mechanism of drug treatment. Methods: The GBM cells treated with or without orexin A were acquired from sequencing analysis. Differentially expressed genes/proteins/metabolites (DEGs/ DEPs/ DEMs) were screened. Next, combination analyses were conducted to investigate the common pathways and correlations between the two groups. Lastly, transcriptome-proteome-metabolome association analysis was carried out to determine the common pathways, and the genes in these pathways were analyzed through Kaplan-Meier (K-M) survival analysis in public databases. Cell and animal experiments were performed to investigate the anti-glioma activity of orexin A. Results: A total of 1,527 DEGs, 52 DEPs, and 153 DEMs were found. Moreover, the combination analyses revealed that 6, 4, and 1 common pathways were present in the transcriptome-proteome, proteome-metabolome, and transcriptome-metabolome, respectively. Certain correlations were observed between the two data sets. Finally, 11 common pathways were discovered in association analysis, and 138 common genes were screened out in these common pathways. Six genes showed significant differences in terms of survival in both TCGA and CGGA. In addition, orexin A inhibited the proliferation, migration, and invasion of glioma in vitro and in vivo. Conclusion: Eleven common KEGG pathways with six common genes were found among different omics participations, revealing the underlying mechanisms in different omics and providing theoretical basis and reference for multi-omics research on drug treatment.

Molecular Landscape of Tourette's Disorder

Tourette's disorder (TD) is a highly heritable childhood-onset neurodevelopmental disorder and is caused by a complex interplay of multiple genetic and environmental factors. Yet, the molecular mechanisms underlying the disorder remain largely elusive. In this study, we used the available omics data to compile a list of TD candidate genes, and we subsequently conducted tissue/cell type specificity and functional enrichment analyses of this list. Using genomic data, we also investigated genetic sharing between TD and blood and cerebrospinal fluid (CSF) metabolite levels. Lastly, we built a molecular landscape of TD through integrating the results from these analyses with an extensive literature search to identify the interactions between the TD candidate genes/proteins and metabolites. We found evidence for an enriched expression of the TD candidate genes in four brain regions and the pituitary. The functional enrichment analyses implicated two pathways ('cAMP-mediated signaling' and 'Endocannabinoid Neuronal Synapse Pathway') and multiple biological functions related to brain development and synaptic transmission in TD etiology. Furthermore, we found genetic sharing between TD and the blood and CSF levels of 39 metabolites. The landscape of TD not only provides insights into the (altered) molecular processes that underlie the disease but, through the identification of potential drug targets (such as FLT3, NAALAD2, CX3CL1-CX3CR1, OPRM1, and HRH2), it also yields clues for developing novel TD treatments.

EccDNA-oriented ITGB7 expression in breast cancer

Background

Extrachromosomal circular DNA (eccDNA) is omnipresent in cancers and related to the progression of tumors and oncogene amplification. However, its function in breast cancer (BC) is unclear.

Methods

After constructing the DNA library, CLeavage Effects by Circularization for In vitro Reporting of sequencing was performed for eccDNA detection using 1 BC tissue sample. Fastqc was used to evaluate the quality of the original data. Burrows-Wheeler-Alignment Tool was used to compare the original data to the reference genome. A Circle-MAP was subsequently performed to detect eccDNA, and Bedtools was used to annotate the eccDNA genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted by ClusterProfiler. The Genotype-Tissue Expression and the Cancer Genome Atlas databases were used to collect the ribonucleic acid-sequencing data of the BC and normal samples. A Gene Expression Profiling Interactive Analysis, the University of Alabama at Birmingham CANcer data analysis Portal, and Kaplan-Meier survival curves were used to analyze the Cancer Genome Atlas data.

Results

A total of 200 eccDNA genes, including IGTB7, were obtained. About the biological processes (BPs), these 200 genes were mainly enriched in actin cytoskeleton reorganization and axon guidance. Concerning the molecular functions (MFs), these 200 genes were mainly enriched in sodium ion transmembrane transporter activity and metal ion transmembrane transporter activity. As for cellular components (CCs), these 200 genes were mainly enriched in the transcription regulator complex and focal adhesion. ITGB7 was significantly enriched in cell-matrix adhesion and localization within the membrane in the BPs, integrin binding in the MFs, and cell-substrate junction and focal adhesion in the CCs. The 200 eccDNA genes were mainly enriched in the PI3K-Akt signaling pathway and focal adhesion. Notably, ITGB7 was enriched in focal adhesion, ECM-receptor interaction, the PI3K-Akt signaling pathway, and human papillomavirus infection. Besides, ITGB7 was significantly upregulated in BC patients and was associated with the menopause status of the BC patients.

Conclusions

ITGB7 might serve as a prognostic marker for BC patients. ITGB7 has important implications for the individualized clinical treatment of BC patients.

Comparative Transcriptomic Analyses of Different Jujube Cultivars Reveal the Co-Regulation of Multiple Pathways during Fruit Cracking

Fruit cracking is a common physiological disorder in many fruit species. Jujube (Ziziphus jujuba Mill.) is an economically valuable fruit in which fruit cracking seriously affects fruit yield and quality and causes significant economic losses. To elucidate cracking-related molecular mechanisms, the cracking-susceptible cultivars ‘Cuizaohong’ and ‘Jinsixiaozao’ and the cracking-resistant cultivar ‘Muzao’ were selected, and comparative transcriptome analyses of cracking and non-cracking ‘Cuizaohong’ (CC and NC), cracking and non-cracking ‘Jinsixiaozao’ (CJ and NJ), and non-cracking ‘Muzao’ (NM) were conducted. A total of 131 differentially expressed genes (DEGs) were common to the CC vs. NC and CJ vs. NJ comparisons. To avoid passive processes after fruit cracking, we also mainly focused on the 225 gradually downregulated DEGs in the CJ, NJ, and NM samples. The functional annotation of the candidate DEGs revealed that 61 genes related to calcium, the cell wall, the cuticle structure, hormone metabolism, starch/sucrose metabolism, transcription factors, and water transport were highly expressed in cracking fruits. We propose that expression-level changes in these genes might increase the turgor pressure and weaken mechanical properties, ultimately leading to jujube fruit cracking. These results may serve as a rich genetic resource for future investigations on fruit cracking mechanisms in jujube and in other fruit species.

Genomic Heritability and Genome-Wide Association Studies of Plasma Metabolites in Crossbred Beef Cattle

Metabolites, substrates or products of metabolic processes, are involved in many biological functions, such as energy metabolism, signaling, stimulatory and inhibitory effects on enzymes and immunological defense. Metabolomic phenotypes are influenced by combination of genetic and environmental effects allowing for metabolome-genome-wide association studies (mGWAS) as a powerful tool to investigate the relationship between these phenotypes and genetic variants. The objectives of this study were to estimate genomic heritability and perform mGWAS and in silico functional enrichment analyses for a set of plasma metabolites in Canadian crossbred beef cattle. Thirty-three plasma metabolites and 45,266 single nucleotide polymorphisms (SNPs) were available for 475 animals. Genomic heritability for all metabolites was estimated using genomic best linear unbiased prediction (GBLUP) including genomic breed composition as covariates in the model. A single-step GBLUP implemented in BLUPF90 programs was used to determine SNP P values and the proportion of genetic variance explained by SNP windows containing 10 consecutive SNPs. The top 10 SNP windows that explained the largest genetic variation for each metabolite were identified and mapped to detect corresponding candidate genes. Functional enrichment analyses were performed on metabolites and their candidate genes using the Ingenuity Pathway Analysis software. Eleven metabolites showed low to moderate heritability that ranged from 0.09 ± 0.15 to 0.36 ± 0.15, while heritability estimates for 22 metabolites were zero or negligible. This result indicates that while variations in 11 metabolites were due to genetic variants, the majority are largely influenced by environment. Three significant SNP associations were detected for betaine (rs109862186), L-alanine (rs81117935), and L-lactic acid (rs42009425) based on Bonferroni correction for multiple testing (family wise error rate <0.05). The SNP rs81117935 was found to be located within the Catenin Alpha 2 gene (CTNNA2) showing a possible association with the regulation of L-alanine concentration. Other candidate genes were identified based on additive genetic variance explained by SNP windows of 10 consecutive SNPs. The observed heritability estimates and the candidate genes and networks identified in this study will serve as baseline information for research into the utilization of plasma metabolites for genetic improvement of crossbred beef cattle.

Identification of potential crucial genes and molecular mechanisms in glioblastoma multiforme by bioinformatics analysis

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor of the adult central nervous system and is associated with poor prognosis. The present study aimed to identify the hub genes in GBM in order to improve the current understanding of the underlying mechanism of GBM. The RNA-seq data were downloaded from The Cancer Genome Atlas database. The edgeR package in R software was used to identify differentially expressed genes (DEGs) between two groups: Glioblastoma samples and normal brain samples. Gene Ontology (GO) functional enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using Database for Annotation, Visualization and Integrated Discovery software. Additionally, Cytoscape and Search Tool for the Retrieval of Interacting Genes/Proteins tools were used for the protein-protein interaction network, while the highly connected modules were extracted from this network using the Minimal Common Oncology Data Elements plugin. Next, the prognostic significance of the candidate hub genes was analyzed using UALCAN. In addition, the identified hub genes were verified by reverse transcription-quantitative (RT-q) PCR. In total, 1,483 DEGs were identified between GBM and control samples, including 954 upregulated genes and 529 downregulated genes (P<0.01; fold-change >16) and these genes were involved in different GO terms and signaling pathways. Furthermore, CDK1, BUB1, BUB1B, CENPA and GNG3 were identified as key genes in the GBM samples. The UALCAN tool verified that higher expression level of CENPA was relevant to poorer overall survival rates. In conclusion, CDK1, BUB1, BUB1B, CENPA and GNG3 were found to be potential biomarkers for GBM. Additionally, ‘cell cycle’ and ‘γ-aminobutyric acid signaling’ pathways may serve a significant role in the pathogenesis of GBM.

Identification of Key Players Involved in CoCl2 Hypoxia Induced Pulmonary Artery Hypertension in vitro

Background

The proliferation of human pulmonary artery smooth muscle cells (HPASMCs) induced by hypoxia was considered as the main cause of pulmonary arterial hypertension (PAH). This study aimed to explore potential genes and long non-coding RNAs (lncRNAs) involved in the mechanism of hypoxia-induced PAH.

Methods

CoCl₂ was utilized to induce hypoxia in HPASMCs, and then cell proliferation, apoptosis, and expression of hypoxia-inducible factors (HIF)-1α were determined. Meanwhile, the RNA isolated from CoCl₂-treated cells and control cells were sequenced and differentially expressed genes/lncRNA (DEGs/DELs) were screened, followed by protein-protein interaction (PPI) construction, functional enrichment analyses, and lncRNA-target prediction. Finally, the expression of key genes and lncRNAs were validated using quantitative real-time PCR and western blotting.

Results

CoCl₂ treatment could significantly increase the expression of HIF-1α and the proliferation of HPASMCs. A total of 360 DEGs and 57 DELs were identified between CoCl₂ treated and control cells. Functional enrichment analysis showed that up-regulated DEGs and DELs’ targets, including LDHA, PFKP, and VEGFA, were significantly enriched in biological processes related to hypoxia or oxygen levels, and the downregulated DEGs and DELs’ targets were significantly enriched in extracellular-matrix-related biological processes. In addition, LDHA, PFKP, and VEGFA exhibited a strong relationship with miR-100HG and TSPEAR-AS2 in lncRNA-target network. The protein level of LDHA, PFKP, and VEGFA were all increased.

Conclusion

LDHA, PFKP, VEGFA, and lncRNA miR-100HG and TSPEAR-AS2 probably played crucial roles in the pathogenesis of CoCl₂ hypoxia-induced-HAP, which might serve as promising therapeutic targets for PAH.