Investigation of the roles of trace elements during hepatitis C virus infection using protein-protein interactions and a shortest path algorithm.

BACKGROUND: Hepatitis is a type of infectious disease that induces inflammation of the liver without pinpointing a particular pathogen or pathogenesis. Type C hepatitis, as a type of hepatitis, has been reported to induce cirrhosis and hepatocellular carcinoma within a very short amount of time. It is a great threat to human health. Some studies have revealed that trace elements are associated with infection with and immune rejection against hepatitis C virus (HCV). However, the mechanism underlying this phenomenon is still unclear. METHODS: In this study, we aimed to expand our knowledge of this phenomenon by designing a computational method to identify genes that may be related to both HCV and trace element metabolic processes. The searching procedure included three stages. First, a shortest path algorithm was applied to a large network, constructed by protein-protein interactions, to identify potential genes of interest. Second, a permutation test was executed to exclude false discoveries. Finally, some rules based on the betweenness and associations between candidate genes and HCV and trace elements were built to select core genes among the remaining genes. RESULTS: 12 lists of genes, corresponding to 12 types of trace elements, were obtained. These genes are deemed to be associated with HCV infection and trace elements metabolism. CONCLUSIONS: The analyses indicate that some genes may be related to both HCV and trace element metabolic processes, further confirming the associations between HCV and trace elements. The method was further tested on another set of HCV genes, the results indicate that this method is quite robustness. GENERAL SIGNIFICANCE: The newly found genes may partially reveal unknown mechanisms between HCV infection and trace element metabolism. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Mining for genes related to choroidal neovascularization based on the shortest path algorithm and protein interaction information.

BACKGROUND: Choroidal neovascularization (CNV) is a serious eye disease that may cause visual loss, especially for older people. Many factors have been proven to induce this disease including age, gender, obesity, and so on. However, until now, we have had limited knowledge on CNV's pathogenic mechanism. Discovering the genes that underlie this disease and performing extensive studies on them can help us to understand how CNV occurs and design effective treatments. METHODS: In this study, we designed a computational method to identify novel CNV-related genes in a large protein network constructed using the protein-protein interaction information in STRING. The candidate genes were first extracted from the shortest paths connecting any two known CNV-related genes and then filtered by a permutation test and using knowledge of their linkages to known CNV-related genes. RESULTS: A list of putative CNV-related candidate genes was accessed by our method. These genes are deemed to have strong relationships with CNV. CONCLUSIONS: Extensive analyses of several of the putative genes such as ANK1, ITGA4, CD44 and others indicate that they are related to specific biological processes involved in CNV, implying they may be novel CNV-related genes. GENERAL SIGNIFICANCE: The newfound putative CNV-related genes may provide new insights into CNV and help design more effective treatments. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

High-concentration atropine induces corneal epithelial cell apoptosis via miR-30c-1/SOCS3.

Atropine is an anticholinergic drug widely used in the field of ophthalmology, but its abuse can cause cytotoxicity to the cornea, resulting in blurred vision. This study used cultured human corneal epithelial cells (HCECs) to investigate the mechanism of high-concentration atropine-induced cytotoxicity. HCECs were treated with different concentrations of atropine. The expression levels of microRNA (miR)-30c-1 and suppressor of cytokine signaling 3 (SOCS3) were manipulated in HCECs treated with 0.1% atropine. Cell counting kit-8 assay and flow cytometry were used to assess the viability and apoptosis of HCECs. The relationship between miR-30c-1 and SOCS3 was obtained from an online database and validated using a dual-luciferase reporter assay and RNA immunoprecipitation method. The effect of atropine on the Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling pathway was also investigated. High-concentration atropine inhibited the viability of HCECs and promoted their apoptosis. Moreover, atropine reduced miR-30c-1 expression and increased SOCS3 expression in a dose-dependent manner. It was found that miR-30c-1 targeted SOCS3. Overexpression of miR-30c-1-reduced atropine-induced HCEC cytotoxicity, whereas upregulation of SOCS3 reversed the effects of miR-30c-1 overexpression. High-concentration atropine inhibited activation of the JAK2/STAT3 signaling pathway via miR-30c-1/SOCS3. High-concentration atropine induces HCEC apoptosis by regulating the miR-30c-1/SOCS3 axis and JAK2/STAT3 signaling pathway.

A six-mRNA signature model for the prognosis of head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC), one of the most common cancers with high morbidity and mortality rates worldwide, has a poor prognosis. The transcriptome sequencing data of 500 patients with HNSCC in the TCGA dataset were assessed to find biomarkers associated with HNSCC prognosis so as to improve the prognosis of patients with HNSCC. The patients were divided into the training and testing sets. A model of six mRNAs (FRMD5, PCMT1, PDGFA, TMC8, YIPF4, ZNF324B) that could predict patient prognosis was identified in the training set using the Cox regression analysis. According to this model, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier analysis showed that the high-risk group showed significantly shorter overall survival time compared with the low-risk group in both training and testing sets. The receiver operating characteristic analysis further confirmed high sensitivity and specificity for the model, which was more accurate compared with some known biomarkers in predicting HNSCC prognosis. Moreover, the model was applicable to patients of different ages, genders, clinical stages, tumor locations, smoking history, and human papillomavirus (HPV) status, as well as to microarray dataset. This model could be used as a novel biomarker for the prognosis of HNSCC and a significant tool for guiding the clinical treatment of HNSCC. The risk score acquired from the model might contribute to improving outcome prediction and management for patients with HNSCC, indicating its clinical significance.

Melanoma long non-coding RNA signature predicts prognostic survival and directs clinical risk-specific treatments.

BACKGROUND: Various studies have demonstrated that the Breslow thickness, tumor ulceration and mitotic index could serve as prognostic markers in patients with cutaneous melanoma. Recently, however, as these clinicopathological biomarkers lack efficient interpretation of endogenous mechanism of melanoma, the emphasis on the prognosis of melanoma has transformed to molecular tumor markers. OBJECTIVE: This study was designed to identify survival-related long non-coding RNAs (lncRNAs), and based on the different expressions of these lncRNAs, clinical risk-specific diagnosis and adjuvant therapy could be employed on melanoma patients, especially patients in the early course of disease or patients with a Breslow thickness no more than 2mm. METHODS: The clinical information and corresponding RNA expression data were obtained from The Cancer Genome Atlas dataset and Gene Expression Omnibus dataset (GSE65904). All samples were categorized into one training dataset and two validation datasets. Cox proportional hazard regression analysis was then used to identify survival-related lncRNAs and risk assessment signature was constructed in training dataset. Kaplan-Meier method was used to estimate the utility of this signature in predicting the duration of survival of patients both in the training dataset and two validation datasets. Meanwhile receiver operating characteristic analyses were used to evaluate the predictive effectiveness of this signature in two validation datasets. RESULTS: It was found that the signature was effective while used for risk stratification, and Kaplan-Meier analyses indicated that the duration of survival of patients in high-risk groups were significantly shorter than that of low-risk groups. Moreover, areas under the receiver operating characteristic curve were 0.711 (95% confidence interval: 0.618-0.804) and 0.698 (95% confidence interval: 0.614-0.782) when this signature was used to predict the patients' duration of survival in two validation datasets respectively, indicating the superior specificity and sensitivity of this signature. CONCLUSION: We identified a four-lncRNA prognostic signature with the ability of risk stratification for melanoma patients. Risk score acquired from this signature, combining with differential diagnosis and differential adjuvant therapy, could potentially improve the prognosis quality of life for patients, especially patients in the early course of disease or patients with a Breslow thickness no more than 2mm.

Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan-Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC = 0.752, 95% confidence intervals (CI): 0.651-0.854) and the microarray dataset (AUC = 0.714, 95%CI: 0.615-0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs.

Therapeutic effect of atropine 1% in children with low myopia.

PURPOSE: To evaluate the efficacy of topical atropine 1% in promoting unaided visual acuity, reducing myopia, and slowing the progression of ocular axial elongation in Chinese children with low myopia. METHODS: Children with low myopia were randomly assigned to one of two groups, receiving either atropine 1% (treatment group) or placebo eyedrops (control group) once nightly for 1 year. After instillation of 3 drops of cyclopentolate 1%, unaided visual acuity, cycloplegic refraction, and ocular axial length were tested and recorded at baseline (2 weeks after atropine or vehicle eyedrops), 3 months, 6 months, 9 months, and 1 year. RESULTS: A total of 132 children 7-12 years of age with a refractive error of spherical equivalent -0.50 D to -2.00 were included. After 1 year, the mean unaided visual acuity in the treatment group was 0.31 ± 0.16 logMAR; in the control group, 0.66 ± 0.15 logMAR, (P < 0.0001). After treatment for 1 year, there was a decrease of 0.32 ± 0.22 D from baseline in the treatment group and an increase of -0.85 ± 0.31 D in the control group (P < 0.0001). The axial elongation in the treatment group was -0.03 ± 0.07 mm; in the control group, 0.32 ± 0.15 mm (P < 0.0001). CONCLUSIONS: In this study cohort, topical atropine1% reduced the degree of low myopia and slowed the progression of ocular axial elongation in children.