Identification of the potential novel biomarkers as susceptibility gene for Wilms tumor

Background Wilms tumor (WT) is the most common malignant renal tumor in children. The aim of this study was to identify potential susceptibility gene of WT for better prognosis. Methods Weighted gene coexpression network analysis is used for the detection of clinically important biomarkers associated with WT. Results In the study, 59 tissue samples from National Cancer Institute were pretreated for constructing gene co-expression network, while 224 samples also downloaded from National Cancer Institute were used for hub gene validation and module preservation analysis. Three modules were found to be highly correlated with WT, and 44 top hub genes were identified in these key modules eventually. In addition, both the module preservation analysis and gene validation showed ideal results based on other dataset with 224 samples. Meanwhile, Functional enrichment analysis showed that genes in module were enriched to sister chromatid cohesion, cell cycle, oocyte meiosis. Conclusion In summary, we established a gene co-expression network to identify 44 hub genes are closely to recurrence and staging of WT, and 6 of these hub genes was closely related to the poor prognosis of patients. Our findings revealed that those hub genes may be used as potential susceptibility gene for clinical diagnosis and prognosis of this tumor.

Identification of key immune regulatory genes in HIV–1 Progression

In the last few decades, application of DNA microarray technology has sprung up as a powerful technique for discovering stage specific changes in expression pattern of a disease progression. Human Immunodeficiency Virus (HIV) infection causes Acquired Immunodeficiency Syndrome (AIDS) which is one of the most devastating diseases affecting humankind. Here, we have proposed a framework to examine the difference among microarray gene expression data of uninfected and three different HIV–1 infection stages using module preservation statistics. Initially, we detected differentially expressed genes among all the stages and identified coexpression modules by using topological overlap as a dissimilarity measure. To examine relationship among co-expression modules, we have compiled a module eigenegene network for each sample category which models similarity among all coexpression modules. To further examine the network, we have found clusters in it which are termed as ‘meta-modules’. Different module preservation statistics with two composite statistics: “Zsummary” and “MedianRank” are utilized to examine changes in structure of coexpression modules. We have applied our proposed methodology to discover modular changes between uninfected and acute samples, acute and chronic samples, chronic and AIDS samples. We have found several interesting results on preservation characteristics of gene modules across different stages. Some genes are identified to be preserved in a pair of stages while alter their characteristics across other stages. We further validated the obtained results using permutation test and classification techniques. Biological significance of the obtained modules have been examined using gene ontology and pathway based analysis. Additionally, we have detected key immune regulatory hub genes in the associated protein-protein interaction networks (PPINs) of the differentially expressed genes (DEGs) using twelve topological and centrality analysis methods. Moreover, we have analyzed the key immune regulatory genes which interacts with HIV-1 proteins inside the preserved and perturbed meta-modules across different HIV-1 stages and thus likely to act as potential biomarkers in HIV–1 progression.

Identification of the potential biomarkers in patients with glioma: a weighted gene co-expression network analysis

Glioma is the most common brain tumor with high mortality. However, there are still challenges for the timely and accurate diagnosis and effective treatment of the tumor. One hundred and twenty-one samples with grades II, III and IV from the Gene Expression Omnibus database were used to construct gene co-expression networks to identify hub modules closely related to glioma grade, and performed pathway enrichment analysis on genes from significant modules. In gene co-expression network constructed by 2345 differentially expressed genes from 121 gene expression profiles for glioma, we identified the black and blue modules that associated with grading. The module preservation analysis based on 118 samples indicates that the two modules were replicable. Enrichment analysis showed that the extracellular matrix genes were enriched for blue module, while cell division genes were enriched for black module. According to survival analysis, 21 hub genes were significantly up-regulated and one gene was significantly down-regulated. What’s more, IKBIP, SEC24D, and FAM46A are the genes with little attention among the 22 hub genes. In this study, IKBIP, SEC24D, and FAM46A related to glioma were mentioned for the first time to the current knowledge, which might provide a new idea for us to study the disease in the future. IKBIP, SEC24D and FAM46A among the 22 hub genes identified that are related to the malignancy degree of glioma might be used as new biomarkers to improve the diagnosis, treatment and prognosis of glioma.

Identifying conserved molecular mechanisms of thermo-acclimation in symbiotic organisms

Seawater temperature rise in French Polynesia has repeatedly resulted in symbiosis breakdown between giant clam (Tridacna maxima) and dinoflagellates (Symbiodinium spp.), particularly in small individuals. Herein, we explored the physiological and gene expression responses of the clam hosts and their photosynthetically active symbionts over a 65-day experiment in which clams were exposed to either normal or environmentally relevant elevated seawater temperatures. These data were combined with publicly available data for both free-living Symbiodinium (clades C1 and F) and Symbiodinium spp. in hospite with the coral Pocillopora damicornis. Gene module preservation analysis revealed that the function of the symbionts' photosystem II was impaired at high temperatures, and this response was conserved across all holobionts and Symbiodinium clades examined. Similarly, activation of the phytohormone abscisic acid signaling and epigenetics modulation appeared to be a key response mechanisms for symbionts in hospite with giant clams exposed to high temperatures and also distinguish thermo-tolerant from thermo-sensitive Symbiodinium C1 phenotypes.

A scalable permutation approach reveals replication and preservation patterns of gene coexpression modules

Gene coexpression network modules provide a framework for identifying shared biological functions. Analysis of topological preservation of modules across datasets is important for assessing reproducibility, and can reveal common function between tissues, cell types, and species. Although module preservation statistics have been developed, heuristics have been required for significance testing. However, the scale of current and future analyses requires accurate and unbiased p-values, particularly to address the challenge of multiple testing. Here, we developed a rapid and efficient approach (NetRep) for assessing module preservation and show that module preservation statistics are typically non-normal, necessitating a permutation approach. Quantification of module preservation across brain, liver, adipose, and muscle tissues in a BxH mouse cross revealed complex patterns of multi-tissue preservation with 52% of modules showing unambiguous preservation in one or more tissues and 25% showing preservation in all four tissues. Phenotype association analysis uncovered a liver-derived gene module which harboured housekeeping genes and which also displayed adipose and muscle tissue specific association with body weight. Taken together, our study presents a rapid unbiased approach for testing preservation of gene network topology, thus enabling rigorous assessment of potentially conserved function and phenotype association analysis.