The expression and prognostic significance of PIK3CB in lung adenocarcinoma.

OBJECTIVE: The aim of this study was to explore the expression and prognostic significance of PIK3CB in lung adenocarcinoma (LUAD) and to analyse the possible molecular mechanism that promotes LUAD development. METHODS: Differences of PIK3CB expression at transcriptional level between LUAD and normal tissues were analysed with the Timer and UALCAN databases. Then, immunohistochemical staining was performed to investigate PIK3CB expression at the protein level, and relationships between PIK3CB and clinical characteristics were accessed. Univariate and multivariate Cox regression were performed to identify the independent prognostic risk factors for LUAD. Genetic alterations were analysed using the cBioPortal database. The main coexpressed genes and enrichment pathways of PIK3CB were estimated with the LinkedOmics database. RESULTS: Compared with normal tissues, PIK3CB was higherly expressed in LUAD at the transcriptional level and protein level, respectively. PIK3CB expression was closely related to prognosis of LUAD patients, and PIK3CB protein expression was associated with lymph node metastasis and pathological differentiation, but not related to sex, age, pleural invasion, vascular invasion, tumour site, tumour size or clinical stage. PIK3CB and tumour size were independent risk factors for LUAD patients. The expression of PIK3CB was negatively correlated with AKT1 and AKT2, but there was no significant correlation with AKT3, and strong positive correlations with ARMC8, DNAJC13 and PIK3R4. The main enrichment pathways of PIK3CB and related genes included adherens junctions and the phosphatidylinositol signalling pathways, ErbB signalling pathways, Hedgehog signalling pathways, and C-type lectin receptor signalling pathways. Therefore, we hypothesized that PIK3CB expression did not promote LUAD development through the classical PI3K/AKT pathway. CONCLUSION: High PIK3CB expression was associated with the development of LUAD and worse prognosis. PIK3CB was an independent risk factor for LUAD patients. Therefore, this study provides a reliable reference for the prognostic assessment and targeted therapy for LUAD patients.

Dopamine and dopamine receptor D1 as a novel favourable biomarker for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains one of the most common malignant tumours worldwide. Therefore, the identification and development of sensitivity- genes as novel diagnostic markers and effective therapeutic targets is urgently needed. Dopamine and dopamine receptor D1 (DRD1) are reported to be involved in the progression of various cancers. However, the crucial role of DRD1 in HCC malignant activities remains unclear. METHODS: We enrolled 371 patients with liver hepatocellular carcinoma (LIHC) from The Cancer Genome Atlas (TCGA) to detect the expression and functions of DRD1. The Tumour Immune Estimation Resource (TIMER), UALCAN database, Kaplan-Meier plotter, cBioPortal database, and LinkedOmics database were utilized for the systematic investigation of DRD1 expression and related clinical features, coexpressed genes, functional pathways, mutations, and immune infiltrates in HCC. RESULTS: In this study, we determined that DRD1 expression was decreased in HCC tumour tissues versus normal tissues and that low DRD1 expression indicated a poor prognosis. The significance of DRD1 expression varied among different tumour samples. The somatic mutation frequency of DRD1 in the LIHC cohort was 0.3%. The biological functions of DRD1 were detected and validated, and DRD1 was shown to be involved in various functional activities, including metabolism, oxidation, mitochondrial matrix-related processes and other related signaling pathways. In addition, out study indicated that DRD1 had significant correlations with the infiltration of macrophages, B cells and CD+ T cells in HCC. CONCLUSIONS: These findings demonstrated the rationality of the potential application of DRD1 function as a novel biomarker for HCC diagnosis and a therapeutic target for HCC treatment.

Transcriptome Analysis Reveals IsiA-Regulatory Mechanisms Underlying Iron Depletion and Oxidative-Stress Acclimation in Synechocystis sp. Strain PCC 6803.

Microorganisms in nature are commonly exposed to various stresses in parallel. The isiA gene encodes an iron stress-induced chlorophyll-binding protein which is significantly induced under iron starvation and oxidative stress. Acclimation of oxidative stress and iron deficiency was investigated using a regulatory mutant of the Synechocystis sp. strain PCC 6803. In this study, the ΔisiA mutant grew more slowly in oxidative-stress and iron depletion conditions compared to the wild-type (WT) counterpart under the same conditions. Thus, we performed transcriptome sequencing (RNA-seq) analysis of the WT strain and the ΔisiA mutant under double-stress conditions to obtain a comprehensive view of isiA-regulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed significant differences between the WT strain and ΔisiA mutant, mainly related to photosynthesis and the iron-sulfur cluster. The deletion of isiA affects the expression of various genes that are involved in cellular processes and structures, such as photosynthesis, phycobilisome, and the proton-transporting ATPase complex. Weighted gene coexpression network analysis (WGCNA) demonstrated three functional modules in which the turquoise module was negatively correlated with superoxide dismutase (SOD) activity. Coexpression network analysis identified several hub genes of each module. Cotranscriptional PCR and reads coverage using the Integrative Genomics Viewer demonstrated that isiA, isiB, isiC, ssl0461, and dfp belonged to the isi operon. Three sRNAs related to oxidative stress were identified. This study enriches our knowledge of IsiA-regulatory mechanisms under iron deficiency and oxidative stress.IMPORTANCE This study analyzed the impact of isiA deletion on the transcriptomic profile of Synechocystis The isiA gene encodes an iron stress-induced chlorophyll-binding protein, which is significantly induced under iron starvation. The deletion of isiA affects the expression of various genes that are involved in photosynthesis and ABC transporters. WGCNA revealed three functional modules in which the blue module was correlated with oxidative stress. We further demonstrated that the isi operon contained the following five genes: isiA, isiB, isiC, ssl0461, and dfp by cotranscriptional PCR. Three sRNAs were identified that were related to oxidative stress. This study enhances our knowledge of IsiA-regulatory mechanisms under iron deficiency and oxidative stress.

Transcriptome dynamics of developing maize leaves and genomewide prediction of cis elements and their cognate transcription factors.

Maize is a major crop and a model plant for studying C4 photosynthesis and leaf development. However, a genomewide regulatory network of leaf development is not yet available. This knowledge is useful for developing C3 crops to perform C4 photosynthesis for enhanced yields. Here, using 22 transcriptomes of developing maize leaves from dry seeds to 192 h post imbibition, we studied gene up- and down-regulation and functional transition during leaf development and inferred sets of strongly coexpressed genes. More significantly, we developed a method to predict transcription factor binding sites (TFBSs) and their cognate transcription factors (TFs) using genomic sequence and transcriptomic data. The method requires not only evolutionary conservation of candidate TFBSs and sets of strongly coexpressed genes but also that the genes in a gene set share the same Gene Ontology term so that they are involved in the same biological function. In addition, we developed another method to predict maize TF-TFBS pairs using known TF-TFBS pairs in Arabidopsis or rice. From these efforts, we predicted 1,340 novel TFBSs and 253 new TF-TFBS pairs in the maize genome, far exceeding the 30 TF-TFBS pairs currently known in maize. In most cases studied by both methods, the two methods gave similar predictions. In vitro tests of 12 predicted TF-TFBS interactions showed that our methods perform well. Our study has significantly expanded our knowledge on the regulatory network involved in maize leaf development.

Identifying the Prognostic Risk Factors of Synaptojanin 2 and Its Underlying Perturbations Pathways in Hepatocellular Carcinoma.

Synaptojanin 2 (SYNJ2) regulates cell proliferation and apoptosis via dephosphorylating plasma membrane phosphoinositides. Aim of this study is to first seek the full-scale expression levels and potential emerging roles of SYNJ2 in hepatocellular carcinoma (HCC). We systematically analyzed SYNJ2 mRNA expression and protein levels in HCC tissues based on large-scale data and in-house immunohistochemistry (IHC). The clinical significance and risk factors for SYNJ2-related HCC cases were identified. A nomogram of prognosis was created and its performance was validated by concordance index (C-index) and shown in calibration plots. Based on the identified differentially coexpressed genes (DCGs) of SYNJ2, enriched annotations and potential pathways were predicted, and the protein interacting networks were mapped. Upregulated SYNJ2 in 3,728 HCC and 3,203 non-HCC tissues were verified and in-house IHC showed higher protein levels of SYNJ2 in HCC tissues. Pathologic T stage was identified as a risk factor. Upregulated mRNA levels and mutated SYNJ2 might cause a poorer outcome. The C-index of the nomogram model constructed by SYNJ2 level, age, gender, TNM classification, grade, and stage was evaluated as 0.643 (95%CI = 0.619-0.668) with well-calibrated plots. A total of 2,533 DCGs were extracted and mainly functioned together with SYNJ2 in metabolic pathways. Possible transcriptional axis of CTCF/POLR2A-SYNJ2/INPP5B (transcription factor-target) in metabolic pathways was discovered based on ChIP-seq datasets. In summary, transcriptional regulatory axis CTCF/POLR2A-SYNJ2 might influence SYNJ2 expression levels. Increased SYNJ2 expression level could be utilized for predicting HCC prognosis and potentially accelerates the occurrence and development of HCC via metabolic perturbations pathways.

Identification of genes associated with renal cell carcinoma using gene expression profiling analysis.

Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults and accounts for ~80% of all kidney cancer cases. However, the pathogenesis of RCC has not yet been fully elucidated. To interpret the pathogenesis of RCC at the molecular level, gene expression data and bio-informatics methods were used to identify RCC associated genes. Gene expression data was downloaded from Gene Expression Omnibus (GEO) database and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in RCC patients compared with controls. In addition, a regulatory network was constructed using the known regulatory data between transcription factors (TFs) and target genes in the University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) and the regulatory impact factor of each TF was calculated. A total of 258,0427 pairs of DCGs were identified. The regulatory network contained 1,525 pairs of regulatory associations between 126 TFs and 1,259 target genes and these genes were mainly enriched in cancer pathways, ErbB and MAPK. In the regulatory network, the 10 most strongly associated TFs were FOXC1, GATA3, ESR1, FOXL1, PATZ1, MYB, STAT5A, EGR2, EGR3 and PELP1. GATA3, ERG and MYB serve important roles in RCC while FOXC1, ESR1, FOXL1, PATZ1, STAT5A and PELP1 may be potential genes associated with RCC. In conclusion, the present study constructed a regulatory network and screened out several TFs that may be used as molecular biomarkers of RCC. However, future studies are needed to confirm the findings of the present study.

Genes Frequently Coexpressed with Hoxc8 Provide Insight into the Discovery of Target Genes.

Identifying Hoxc8 target genes is at the crux of understanding the Hoxc8-mediated regulatory networks underlying its roles during development. However, identification of these genes remains difficult due to intrinsic factors of Hoxc8, such as low DNA binding specificity, context-dependent regulation, and unknown cofactors. Therefore, as an alternative, the present study attempted to test whether the roles of Hoxc8 could be inferred by simply analyzing genes frequently coexpressed with Hoxc8, and whether these genes include putative target genes. Using archived gene expression datasets in which Hoxc8 was differentially expressed, we identified a total of 567 genes that were positively coexpressed with Hoxc8 in at least four out of eight datasets. Among these, 23 genes were coexpressed in six datasets. Gene sets associated with extracellular matrix and cell adhesion were most significantly enriched, followed by gene sets for skeletal system development, morphogenesis, cell motility, and transcriptional regulation. In particular, transcriptional regulators, including paralogs of Hoxc8, known Hox co-factors, and transcriptional remodeling factors were enriched. We randomly selected Adam19, Ptpn13, Prkd1, Tgfbi, and Aldh1a3, and validated their coexpression in mouse embryonic tissues and cell lines following TGF-ß2 treatment or ectopic Hoxc8 expression. Except for Aldh1a3, all genes showed concordant expression with that of Hoxc8, suggesting that the coexpressed genes might include direct or indirect target genes. Collectively, we suggest that the coexpressed genes provide a resource for constructing Hoxc8-mediated regulatory networks.

Genome-Wide Detection of Gene Coexpression Domains Showing Linkage to Regions Enriched with Polymorphic Retrotransposons in Recombinant Inbred Mouse Strains.

Although gene coexpression domains have been reported in most eukaryotic organisms, data available to date suggest that coexpression rarely concerns more than doublets or triplets of adjacent genes in mammals. Using expression data from hearts of mice from the panel of AxB/BxA recombinant inbred mice, we detected (according to window sizes) 42-53 loci linked to the expression levels of clusters of three or more neighboring genes. These loci thus formed "cis-expression quantitative trait loci (eQTL) clusters" because their position matched that of the genes whose expression was linked to the loci. Compared with matching control regions, genes contained within cis-eQTL clusters showed much greater levels of coexpression. Corresponding regions showed: (1) a greater abundance of polymorphic elements (mostly short interspersed element retrotransposons), and (2) significant enrichment for the motifs of binding sites for various transcription factors, with binding sites for the chromatin-organizing CCCTC-binding factor showing the greatest levels of enrichment in polymorphic short interspersed elements. Similar cis-eQTL clusters also were detected when we used data obtained with several tissues from BxD recombinant inbred mice. In addition to strengthening the evidence for gene expression domains in mammalian genomes, our data suggest a possible mechanism whereby noncoding polymorphisms could affect the coordinate expression of several neighboring genes.