[Shared functional modules for nasopharyngeal and oral squamous cell carcinoma identified by network analysis of transcriptomes].

Although nasopharyngeal carcinoma (NPC) and oral squamous cell carcinoma (OSCC) are highly correlated clinical diseases, the underling molecular mechanisms to link the two diseases remain largely unknown. The aim of this study is to identify the shared functional modules for NPC and OSCC by using large-scale transcriptomic data. Gene expression profile datasets of NPC and OSCC were obtained from the GEO database. A total of 1279 differentially expressed genes (DEGs) of NPC and 1293 DEGs of OSCC were identified by fold change and empirical Bayes method, and 278 DEGs were common to these two diseases. These overlapped genes were translated into a primary network consisting of 1290 nodes (genes) and 1766 edges. The primary network was then decomposed into 15 compacted modules (subnets) with high modularity by Newman's algorithm. Topological analysis of these modules identified a total of 58 hub genes, most of which (e.g., PCNA, CDK1, STAT1, CCL5, and MMP1) have been proved to be associated with NPC and/or OSCC, while the rest (e.g., MELK, NME1, RACGAP1, INHBA, and NID1) might be novel risk genes for the two diseases. Further bioinformatics analysis of KEGG databases revealed that these modules are involved in multiple pathogenic biological pathways for either NPC or OSCC (e.g., p53 signaling pathway, ECM-receptor interaction, focal adhesion, and cell cycle). This study demonstrates that NPC and OSCC have similar molecular bases, and the identified pleiotropic modules may shape the complicated molecular interplays underlying the two clinically correlated diseases.

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data.

Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene-gene interactions involved in these susceptible pathways with their protein-protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer's disease, non-alcoholic fatty liver disease, and Huntington's disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer's disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer's disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.

[Identification of gene functional modules shared by cancers based on biclustering].

Pleiotropy is a common phenomenon in the genetics of cancers, which is rarely systematically evaluated. A novel idea for identifying shared gene functional modules using biclustering was proposed in this paper to explore the common molecular mechanisms among cancers and the relationships between different types of cancers. Gene expression datasets for 20 cancers were obtained. And genes differentially expressing in at least two types of cancers were selected using both moderated t-statistic and fold change to construct a 10417 × 20 matrix (gene-cancer matrix). 22 gene clusters shared by cancers were found by using the biclustering method. Further, Gene Ontology (GO)-based enrichment analysis identified 17 gene functional modules (Bonferroni corrected P < 0.05). The involved biological processes primarily included regulation of chromatids separation during mitosis, cell differentiation, immune and inflammatory response, and collagen fibril organization. These modules undertook molecular functions of ATP binding and microtubule motor activity, MHC class II receptor activity, endopeptidase inhibitor activity and so on. And their activity sites were mostly located in cytoskeleton, chromosome, MHC protein complex, intermediate filament, fibrillar collagen and so on. The network constructed based on these modules indicates that gastric cancer, ovarian adenocarcinoma, cervical cancer and mesothelioma were highly relevant to each other. However, the molecular mechanisms of two hematologic malignancies (acute myeloid leukemia and multiple myeloma) seem very different from other cancers. It can be seen that gene functional modules shared by cancers are associated with many biological mechanisms, and similarities among cancers are probably attributed to cellular origin and shared carcinogenic mechanisms. The proposed method for analysis of pleiotropy in this paper will help understand the common molecular mechanisms for complex human diseases.

A meta-analysis of the association between TNF-α -308G>A polymorphism and type 2 diabetes mellitus in Han Chinese population.

OBJECTIVE: A meta-analysis was applied to evaluate the associations between tumor necrosis factor-α (TNF-α) -308G>A (rs1800629) polymorphism and type 2 diabetes mellitus (T2DM). METHODS: Hardy-Weinberg equilibrium (HWE) was employed to test genetic equilibrium among the genotypes of the selected literature. Power analysis was performed with the Power and Sample Size Calculation (PS) program. A fixed or random effect model was used on the basis of heterogeneity. Publication bias was quantified and examined with the Begg's funnel plot test and Egger's linear regression test. The meta-analysis was performed with Review Manager 5.1 and Stata 11.0. RESULTS: There were 10 studies including 1425 T2DM patients and 1116 healthy control subjects involved in this meta-analysis. No significant publication bias was found in the studies. The pooled ORs (95% CIs) for TNF-α -308G>A of A vs. G allele and GA+AA vs. GG genotype were 1.63 (1.17-2.25) and 1.47 (1.17-1.85), respectively. CONCLUSION: This meta-analysis result suggested that TNF-α -308G>A polymorphism was strongly associated with T2DM risk, and A allele at this locus might be a susceptibility allele for the development of T2DM in Han Chinese population.

Postoperative complications in patients with cochlear implants and impacts of nursing intervention.

CONCLUSION: This study shows that cochlear implantation is relatively safe surgery with few major complications and within acceptable limits. However, close follow-up observation and effective medical and nursing intervention could alleviate further complications and thus become key elements for promoting recovery of patients undergoing such surgery. OBJECTIVES: Cochlear implantation has become an effective method for curing patients disabled by profound hearing loss in China. However, full exploration of the associated complications remains to be completed. The objective of this study was thus to analyse the postoperative complications in patients with cochlear implants (CIs) in order to design improved measures for clinical and nursing interventions. METHODS: A retrospective study of 262 patients receiving CIs at the Department of Otorhinolaryngology/Head and Neck Surgery, Chinese People's Liberation Army General Hospital, Beijing, China from March 1997 to December 2006 was conducted. RESULTS: Among 262 patients, 4 cases (1.5%) had 1 or more major complications requiring substantial medical or nursing interventions, including 1 case of cerebrospinal fluid (CSF) otorrhoea accompanied by meningitis, 2 cases of facial nerve paresis and 1 case of perforation of tympanic membrane. Forty cases (15.3%) had some form of minor complication that settled spontaneously or easily with conventional treatments and nursing, of which dizziness and vomiting was the most frequent (4.2%), followed by CSF gusher without otorrhoea and/or induced meningitis (2.7%), tinnitus (1.9%) and facial nerve partially exposed without paralysis (1.5%). Eleven cases (4.2%) had some symptoms associated with installation of the cochlear device. Except for one patient who had no response after implantation because his auditory nerves were underdeveloped, all the patients who received appropriate treatment and nursing intervention had a favourable prognosis.

[Audiological and genetic studies on 130 infants with hearing loss].

OBJECTIVE: To investigate the genetic etiologies in the 0- 3-years-old infants with hearing loss and to analyze the interaction between genetics and environmental factors. METHODS: Total of 130 infants were performed detailed audiological evaluation as well as the detection of the popular deafness gene mutations in GJB2 gene, SLC26A4 and mtDNA12SrRNA. Of them, 84 cases were performed the computer tomography or magnetic resonance imaging examinations. RESULTS: Of the 130 cases, 54 infants were diagnosed as large vestibular aqueduct syndrome, while seven of 130 were as auditory neuropathy and the others were diagnosed as sensorineural hearing loss. Considering of the risks of etiologies for hearing loss, 85 of them had the experiences of the high risk factors at birth (65.4%, 85/130), while 23 of them had the exposure of aminoglycoside antibiotics, and 13 had the family history background as well as two cases were from the consanguineous families. In the causative genes screening, 42 infants were caused by the mutations of SLC26A4 gene (32.3%), but 14 infants found the mutations in GJB2 gene (4.6%), and no infants carried the mutation in mtDNA 12SrRNA 1555G and 1494T points in our studies. CONCLUSIONS: In our studies, about 36.9% infants hearing loss cases can be found the mutations in SLC26A4 and GJB2 genes. It is essential to put the idea into the hearing evaluation combined with genetic testing for the diagnoses of hearing loss. It is also helpful for exploring the etiologies of hearing loss and performing the target genetic consulting for decreasing the prevalence of deafness in the future.

[Correlation between phonetically balanced maximum and pure tone auditory threshold among 106 auditory neuropathy patients].

OBJECTIVE: To estimate correlation between phonetically balanced maximum (PB max) and pure tone auditory threshold in auditory neuropathy (AN) patients. METHODS: One hundred and six AN patients were identified using multiple criteria including PB max, a metric for speech recognition, pure tone auditory threshold, acoustic emission test, distortion products otoacoustic emission (DPOAE) and auditory brainstem response (ABR). SPSS statistical software was used to estimate the Pearson's correlation between PB max and pure tone auditory threshold and to test whether pure tone auditory threshold, or auditory configuration had a significant impact on PB max. RESULTS: Even the patients had the same or similar values for pure tone auditory threshold or auditory configuration, varied values of PB max were found in two hundreds and twelve ears for 106 patients. Analysis of the data for 106 patients revealed a negative correlation (r = -0. 602, P <0. 01) between PB max and pure tone auditory threshold, i. e. hearing loss at a mild relates to a lower PB max. By using analysis of variance (ANOVA) method, it was found that both pure tone auditory threshold and auditory configuration had a significant (P <0.01) impact on the patients' PB max. CONCLUSIONS: This analysis implicated the promise and potential of pure tone auditory threshold and auditory configuration for predicting PB max of the AN patients, and improving the diagnosis of AN.

[Analysis of diffuse large B-cell lymphoma heterogeneity based on coupled two-way clustering].

Microarray technology has proposed a powerful tool in dealing with the heterogeneity of disease. Currently, many methods in the field are based on traditional hierarchical clustering to discover subtypes of disease using a large number of genes on microarray.However, they did not considered that large unrelated noise (genes)may mask significant partitions and correlations of disease samples. To avoid the shortcoming, this paper presented a heterogeneous analysis based on coupled two-way clustering (HCTWC) to search interesting gene signature and find the natural partitions of disease samples. The method was applied to diffuse large B-cell lymphoma (DLBCL) microarray dataset. By identifying significant gene signature, we were able to discover the two new subtypes of DLBCL with survival rate 55% and 25% respectively. The results showed that HCTWC had the potential to be a powerful tool for solving the heterogeneity of disease on gene expression profile.

Peeling off the hidden genetic heterogeneities of cancers based on disease-relevant functional modules.

Discovering molecular heterogeneities in phenotypically defined disease is of critical importance both for understanding pathogenic mechanisms of complex diseases and for finding efficient treatments. Recently, it has been recognized that cellular phenotypes are determined by the concerted actions of many functionally related genes in modular fashions. The underlying modular mechanisms should help the understanding of hidden genetic heterogeneities of complex diseases. We defined a putative disease module to be the functional gene groups in terms of both biological process and cellular localization, which are significantly enriched with genes highly variably expressed across the disease samples. As a validation, we used two large cancer datasets to evaluate the ability of the modules for correctly partitioning samples. Then, we sought the subtypes of complex diffuse large B-cell lymphoma (DLBCL) using a public dataset. Finally, the clinical significance of the identified subtypes was verified by survival analysis. In two validation datasets, we achieved highly accurate partitions that best fit the clinical cancer phenotypes. Then, for the notoriously heterogeneous DLBCL, we demonstrated that two partitioned subtypes using an identified module ("cellular response to stress") had very different 5-year overall rates (65% vs. 14%) and were highly significantly (P < 0.007) correlated with the clinical survival rate. Finally, we built a multivariate Cox proportional-hazard prediction model that included 4 genes as risk predictors for survival over DLBCL. The proposed modular approach is a promising computational strategy for peeling off genetic heterogeneities and understanding the modular mechanisms of human diseases such as cancers.