Drug Repositioning through Systematic Mining of Gene Coexpression Networks in Cancer

Gene coexpression network analysis is a powerful “data-driven” approach essential for understanding cancer biology and mechanisms of tumor development. Yet, despite the completion of thousands of studies on cancer gene expression, there have been few attempts to normalize and integrate co-expression data from scattered sources in a concise “meta-analysis” framework. We generated such a resource by exploring gene coexpression networks in 82 microarray datasets from 9 major human cancer types. The analysis was conducted using an elaborate weighted gene coexpression network (WGCNA) methodology and identified over 3,000 robust gene coexpression modules. The modules covered a range of known tumor features, such as proliferation, extracellular matrix remodeling, hypoxia, inflammation, angiogenesis, tumor differentiation programs, specific signaling pathways, genomic alterations, and biomarkers of individual tumor subtypes. To prioritize genes with respect to those tumor features, we ranked genes within each module by connectivity, leading to identification of module-specific functionally prominent hub genes. To showcase the utility of this network information, we positioned known cancer drug targets within the coexpression networks and predicted that Anakinra, an anti-rheumatoid therapeutic agent, may be promising for development in colorectal cancer. We offer a comprehensive, normalized and well documented collection of >3000 gene coexpression modules in a variety of cancers as a rich data resource to facilitate further progress in cancer research.     

DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules

Background  

Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differentially expressed genes between two conditions, the field of differential coexpression analysis is still relatively new. More specifically, there is so far no sensitive and untargeted method to identify gene modules (also known as gene sets or clusters) that are differentially coexpressed between two conditions. Here, sensitive and untargeted means that the method should be able to construct de novo modules by grouping genes based on shared, but subtle, differential correlation patterns.     

Lack of association between 14-3-3 beta gene (YWHAB) polymorphisms and sporadic Creutzfeldt-Jakob disease (CJD)

14-3-3 proteins are highly abundant in brain tissue. The presence of 14-3-3 at elevated levels in the cerebrospinal fluid has been considered as a biomarker for sporadic Creutzfeldt-Jakob disease (CJD). Recent studies showed that 14-3-3 beta protein interacts with the N-terminal amino acids 1–38 and with the central hydrophobic amino acids 106–126 of prion protein. This interaction may indicate a role of 14-3-3 beta in the biological function of PrP and in the pathogenesis of prion disease. An association between the polymorphisms of 14-3-3 beta gene (YWHAB) and prion disease has not been reported previously. In order to investigate whether YWHAB polymorphisms are associated with sporadic CJD in the Korean population, we compared genotype distribution and allele frequencies of six YWHAB polymorphisms in 244 sporadic CJD patients and 219 healthy Koreans. Of six polymorphisms identified, four single nucleotide polymorphisms (SNPs) were known previously (c.60A>C, c.685-120G>A, c.685-89G>A, 92G>A) and two SNPs were novel (c.185T>A and c.377A>C). Two novel polymorphisms were identified within 3′-untranslated region of exon 6. We could not find significant differences in genotype and allele frequencies of the six YWHAB polymorphisms between the controls and sporadic CJD patients. These results indicate that these six YWHAB polymorphisms are not associated with the genetic susceptibility to sporadic CJD. This is the first genetic association study of YWHAB in sporadic CJD.     

Network-based analysis reveals novel gene signatures in the peripheral blood of patients with sporadic nonsyndromic thoracic aortic aneurysm

Thoracic aortic aneurysm (TAA), a serious cardiovascular disease that causes morbidity and mortality worldwide. At present, few biomarkers can accurately diagnose the appearance of TAA before dissection or rupture. Our research has the intention to investigate the developing applicable biomarkers for TAA promising clinically diagnostic biomarkers or probable regulatory targets for TAA. In our research, we built correlation networks utilizing the expression profile of peripheral blood mononuclear cell obtained from a public microarray data set (GSE9106). Furthermore, we chose the turquoise module, which has the strongest significance with TAA and was further analyzed. Fourteen genes that overlapped with differentially expressed proteins in the medial aortic layer were obtained. Subsequently, we verified the results applying quantitative polymerase chain reaction (Q-PCR) to our clinical specimen. In general, the Q-PCR results coincide with the majority of the expression profile. Fascinatingly, a notable change occurred in CLU, DES, MYH10, and FBLN5. In summary, using weighted gene coexpression analysis, our study indicates that CLU, DES, MYH10, and FBLN5 were identified and validated to be related to TAA and might be candidate biomarkers or therapeutic targets for TAA.     

Analysis of Volatile Compounds in Exhaled Breath Condensate in Patients with Severe Pulmonary Arterial Hypertension

Background

An important challenge to pulmonary arterial hypertension (PAH) diagnosis and treatment is early detection of occult pulmonary vascular pathology. Symptoms are frequently confused with other disease entities that lead to inappropriate interventions and allow for progression to advanced states of disease. There is a significant need to develop new markers for early disease detection and management of PAH.

Methodolgy and Findings

Exhaled breath condensate (EBC) samples were compared from 30 age-matched normal healthy individuals and 27 New York Heart Association functional class III and IV idiopathic pulmonary arterial hypertenion (IPAH) patients, a subgroup of PAH. Volatile organic compounds (VOC) in EBC samples were analyzed using gas chromatography/mass spectrometry (GC/MS). Individual peaks in GC profiles were identified in both groups and correlated with pulmonary hemodynamic and clinical endpoints in the IPAH group. Additionally, GC/MS data were analyzed using autoregression followed by partial least squares regression (AR/PLSR) analysis to discriminate between the IPAH and control groups. After correcting for medicaitons, there were 62 unique compounds in the control group, 32 unique compounds in the IPAH group, and 14 in-common compounds between groups. Peak-by-peak analysis of GC profiles of IPAH group EBC samples identified 6 compounds significantly correlated with pulmonary hemodynamic variables important in IPAH diagnosis. AR/PLSR analysis of GC/MS data resulted in a distinct and identifiable metabolic signature for IPAH patients.

Conclusions

These findings indicate the utility of EBC VOC analysis to discriminate between severe IPAH and a healthy population; additionally, we identified potential novel biomarkers that correlated with IPAH pulmonary hemodynamic variables that may be important in screening for less severe forms IPAH.     

Identification and functional analysis of spermatogenesis-associated gene modules in azoospermia by weighted gene coexpression network analysis

Nonobstructive azoospermia (NOA) or testicular failure is the most severe form of male infertility. A variety of conditions, both acquired and congenital, can cause azoospermia. However, in a large number of azoospermia patients who are classified as idiopathic cases, the etiology remains poorly understand mainly due to the lack of knowledge of all the genetic causes and molecular mechanisms responsible for spermatogenesis failure. Identification of the key gene modules and pathways-related spermatogenesis failure might help to reveal the mechanisms of idiopathic azoospermia. Therefore, the expression patterns of spermatogenesis-associated genes in NOA were analyzed by weighted gene coexpression network analysis (WGCNA) based on two public microarray data sets (GSE45885 and GSE45887), which included 51 samples and 32,321 genes. We identified a module (turquoise) that was significantly related to the Johnsen score of the testicular samples. In addition, the results of function and pathway enrichment analyses based on the online bioinformatics database Metascape revealed that genes in the turquoise module were mainly related to the process of spermatogenesis and spermatid development. To further identify spermatogenesis-associated genes, a microarray data set (GSE926) of murine testis at different developmental time points was analyzed by WGCNA. The blue module in GSE926 was significantly related to the time of murine testis development. The overlap study and k-core analysis based on protein–protein interaction network revealed that spermatogenesis- and spermatid development–associated genes, including glyceraldehyde-3-phosphate dehydrogenase, ADAM metallopeptidase domain 2, transition protein 1, testis-specific serine kinase 2, transition protein 2, and germ cell-associated 1 (GSG1), were further identified in the selected modules. The expression profile of GSG1 in human testis was chosen for further study using immunochemistry staining. Taken together, these screened gene modules and pathways provided a more detailed genetic and molecular mechanism underlying spermatogenesis failure occurrence and holds promise as potential diagnosis biomarkers and therapeutic targets.     

A regulatory gene network related to the porcine umami taste receptor (TAS1R1/TAS1R3)

Taste perception plays an important role in the mediation of food choices in mammals. The first porcine taste receptor genes identified, sequenced and characterized, TAS1R1 and TAS1R3, were related to the dimeric receptor for umami taste. However, little is known about their regulatory network. The objective of this study was to unfold the genetic network involved in porcine umami taste perception. We performed a meta‐analysis of 20 gene expression studies spanning 480 porcine microarray chips and screened 328 taste‐related genes by selective mining steps among the available 12 320 genes. A porcine umami taste‐specific regulatory network was constructed based on the normalized coexpression data of the 328 genes across 27 tissues. From the network, we revealed the ‘taste module’ and identified a coexpression cluster for the umami taste according to the first connector with the TAS1R1/TAS1R3 genes. Our findings identify several taste‐related regulatory genes and extend previous genetic background of porcine umami taste.     

Key modules and hub genes identified by coexpression network analysis for revealing novel biomarkers for larynx squamous cell carcinoma

Larynx squamous cell carcinoma (LSCC) is the second most aggressive head and neck squamous cell carcinoma. Numerous genes have been identified to be aberrantly expressed during the development of LSCC. However, currently, researchers focus more on the individual molecule and downstream genes, leaving the coexpression among genes and key upstream disease driver genes unexploited. In this study, we applied weighted gene coexpression analysis (WGCNA) to decipher potential hub genes driving the development of LSCC. After downloading of LSCC microarray profile from gene expression omnibus, different expression analysis was performed, which was used to conduct functional enrichment analysis. Then, we applied WGCNA to highlight the hub genes which were relevant to the carcinogenesis and progression. A total of 2858 differentially expressed genes were identified in LSCC samples compared with adjacent non-neoplastic tissues. WGCNA revealed three LSCC set-specific modules having significant Kyoto Encyclopedia of Genes and Genomes enrichment effect, including pink, cyan, and black module. Nine hub genes were identified to be crucial in LSCC onset and progression, which may assist clinical decisions and serve as potential targets for LSCC treatment.     

Identification of Novel Endo- β-1, 4-glucanase Isoforms from Bursaphelenchus Species (Nemtoda: Aphelenchoididae)

Bursaphelenchus xylophilus has been recognized as a causal pathogen of pine wilt disease (PWD). In order to identify relevant molecular biomarkers, we selected a variable region of endo-β-1, 4-glucanase (β 14-gcn) which was cloned from the cDNA of B. xylophilus and B. mucronatus. We then identified three novel β14-gcn isoforms: Bm-β 14-gcn and Bm-β 14-gcni from B. mucronatus, and Bx-β 14-gcn from B. xylophilus. Bm-β 14-gcn and Bx-β 14-gcn were found to be identical, whereas Bm-β 14-gcni was unique to B. mucronatus. These isoforms are Bursaphelenchus-specific and may be employed as molecular markers for the diagnosis of PWD. Our phylogenetic analysis showed that these β 14-gcns from Bursaphelenchus species were associated most closely with fungal β 14-gcns.     

Differential coexpression networks in bronchiolitis and emphysema phenotypes reveal heterogeneous mechanisms of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with multiple molecular mechanisms. To investigate and contrast the molecular processes differing between bronchiolitis and emphysema phenotypes of COPD, we downloaded the GSE69818 microarray data set from the Gene Expression Omnibus (GEO), which based on lung tissues from 38 patients with emphysema and 32 patients with bronchiolitis. Then, weighted gene coexpression network analysis (WGCNA) and differential coexpression (DiffCoEx) analysis were performed, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis (KEGG) analysis. Modules and hub genes for bronchiolitis and emphysema were identified, and we found that genes in modules linked to neutrophil degranulation, Rho protein signal transduction and B cell receptor signalling were coexpressed in emphysema. DiffCoEx analysis showed that four hub genes (IFT88, CCDC103, MMP10 and Bik) were consistently expressed in emphysema patients; these hub genes were enriched, respectively, for functions of cilium assembly and movement, proteolysis and apoptotic mitochondrial changes. In our re‐analysis of GSE69818, gene expression networks in relation to emphysema deepen insights into the molecular mechanism of COPD and also identify some promising therapeutic targets.