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.     

Use of Genome-Wide Association Studies for Cancer Research and Drug Repositioning

Although genome-wide association studies have identified many risk loci associated with colorectal cancer, the molecular basis of these associations are still unclear. We aimed to infer biological insights and highlight candidate genes of interest within GWAS risk loci. We used an in silico pipeline based on functional annotation, quantitative trait loci mapping of cis-acting gene, PubMed text-mining, protein-protein interaction studies, genetic overlaps with cancer somatic mutations and knockout mouse phenotypes, and functional enrichment analysis to prioritize the candidate genes at the colorectal cancer risk loci. Based on these analyses, we observed that these genes were the targets of approved therapies for colorectal cancer, and suggested that drugs approved for other indications may be repurposed for the treatment of colorectal cancer. This study highlights the use of publicly available data as a cost effective solution to derive biological insights, and provides an empirical evidence that the molecular basis of colorectal cancer can provide important leads for the discovery of new drugs.     

NOGEA: A Network-oriented Gene Entropy Approach for Dissecting Disease Comorbidity and Drug Repositioning

Rapid development of high-throughput technologies has permitted the identification of an increasing number of disease-associated genes (DAGs), which are important for understanding disease initiation and developing precision therapeutics. However, DAGs often contain large amounts of redundant or false positive information, leading to difficulties in quantifying and prioritizing potential relationships between these DAGs and human diseases. In this study, a network-oriented gene entropy approach (NOGEA) is proposed for accurately inferring master genes that contribute to specific diseases by quantitatively calculating their perturbation abilities on directed disease-specific gene networks. In addition, we confirmed that the master genes identified by NOGEA have a high reliability for predicting disease-specific initiation events and progression risk. Master genes may also be used to extract the underlying information of different diseases, thus revealing mechanisms of disease comorbidity. More importantly, approved therapeutic targets are topologically localized in a small neighborhood of master genes in the interactome network, which provides a new way for predicting drug-disease associations. Through this method, 11 old drugs were newly identified and predicted to be effective for treating pancreatic cancer and then validated by in vitro experiments. Collectively, the NOGEA was useful for identifying master genes that control disease initiation and co-occurrence, thus providing a valuable strategy for drug efficacy screening and repositioning. NOGEA codes are publicly available at https://github.com/guozihuaa/NOGEA.     

精神疲劳评价方法研究进展

长时间飞行活动所致的精神疲劳一直是航空航天医学中一个重要的课题。尤其随着我军航空技术的发展,精神疲劳已经成为影响飞行安全的重要原因之一。研究发现,精神疲劳发生时,机体的生理、心理、生化和工作绩效等功能会发生变化。例如,精神疲劳时,脑电图的theta波、delta波和alpha波发生变化、瞳孔直径增大、心率变异性的低频谱功率升高和高频谱功率降低、姿势控制能力下降、反应时延长、临界融合频率降低、血浆中氨基酸等功能性分子水平改变和认知能力的下降等。精神疲劳的客观评定方法就是研究者借助于某些设备来监测到这些变化,并根据这些变化对疲劳状态进行判断。本文将从生理、心理、生化和作业绩效等方面阐述了精神疲劳客观的评定方法,并指出了这些方法的优缺点。最后,本文对精神疲劳评价方法发展趋势做出了初步的判断,即我们应对精神疲劳进行综合量化评定,这样才能更全面准确地评估精神疲劳。     

MEDLINE摘要本地下载与更新及癌基因表达数据的文本挖掘(英文)

近年来对生物医学文献的文本挖掘在功能基因组学研究中得到了广泛开展。为了更好的检索MEDLINE摘要,本文介绍利用Unix文本过滤命令实现了对摘要的自动下载和更新。同时,对癌基因表达数据,如癌的种类,癌基因表达情况,及与p53基因的关联等进行了初步的文本挖掘分析。     

Quantitative Assessment of the Association Between MS Gene Polymorphism and Colorectal Cancer Risk

Accumulating genetic association studies have investigated the risk of colorectal cancer (CRC) in relation to MS gene polymorphism with uncertain conclusions. In the current study, we sought to assess the association between MS gene and CRC. We performed an updated meta-analysis including 18 case-control studies with a total of 10, 303 CRC patients and 15, 389 CRC-free controls to estimate the strength of the association using odds ratios with the corresponding 95 % confidence intervals. Overall, no CRC risk associated with the genotypes of MS gene polymorphism was indicated in our meta-analysis. Similarly, the stratified analysis according to ethnicity and control source did not show any evident association either. The results of our updated meta-analysis suggest that MS gene polymorphism may not serve as a biomarker for the CRC risk. Future large-scale and well-designed studies are required to clarify the association identified in the present meta-analysis.     

自杀基因在肿瘤基因治疗中的应用

自杀基因治疗肿瘤近年来在国内外研究较多并已取得了明显的疗效。目前发现的自杀基因包括：单纯疱疹病毒胸苷激酶基因、胞嘧啶脱氨酶基因、水痘带状疱疹病毒胸苷激酶基因、硝基还原酶基因、大肠杆菌GPT基因和DEO基因等。     

癌症的miRNA基因治疗

MiRNAs是一种内源非编码小RNA,具有进化上的保守性,在各物种中广泛分布.MiRNAs的作用是反向调节其靶基因的mRNA,研究发现在所有的人类癌症细胞中,miRNA的表达都有异常,即miRNA在肿瘤的形成、生长和扩散过程中发挥重要的作用.本文重点介绍了几种癌症的miRNA治疗方法,为将来的miRNA基因治疗奠定了基础.此外,还简要介绍了相关的基因传递系统及目前面临的挑战.     

Quantitative Assessment of the Effect of Cytochrome P450 2C9 Gene Polymorphism and Colorectal Cancer

CYP2C9 enzyme activity is involved in the metabolism of substances related to colorectal cancer (CRC), and it is functionally linked to a genetic polymorphism. Two allelic variants of the CYP2C9 gene, namely CYP2C9*2 and CYP2C9*3, differ from wild-type CYP2C9*1 by single amino acid substitutions. These mutated alleles encode enzymes with altered properties that are associated with impaired metabolism. In the past decade, a number of case-control studies have been carried out to investigate the relationship between the CYP2C9 polymorphism and CRC susceptibility, but the results were conflicting. To investigate this inconsistency, we performed a meta-analysis of 13 studies involving a total of 20,879 subjects for CYP2C9*2 and *3 polymorphisms to evaluate the effect of CYP2C9 on genetic susceptibility for CRC. Overall, the summary odds ratio of CRC was 0.94 (95%CI: 0.87–1.03, P = 0.18) and 1.00 (95%CI: 0.86–1.16, P = 0.99) for CYP2C9 *2 and *3 carriers, respectively. No significant results were observed in heterozygous and homozygous when compared with wild genotype for these polymorphisms. In the stratified analyses according to ethnicity, sample size, diagnostic criterion, HWE status and sex, no evidence of any gene-disease association was obtained. Our result suggest that the *2, *3 polymorphisms of CYP2C9 gene are not associated with CRC susceptibility.     

Cancer Stem Cell-Related Gene Periostin: A Novel Prognostic Marker for Breast Cancer

We investigated the expression status of periostin in breast cancer stem cells and its clinical implications in order to lay a foundation for managing breast cancer. CD44+/CD24−/line- tumor cells (CSC) from clinical specimens were sorted using flow cytometry. Periostin expression status was detected in CSC cells and 1,086 breast cancer specimens by Western blot and immunohistochemistry staining, with the CSC ratio determined by immunofluorescence double staining. The relationship between the periostin protein and clinico-pathological parameters and prognosis was subsequently determined. As a result, CSC cells are more likely to generate new tumors in mice and cell microspheres that are deficient in NOD/SCID compared to the control group. Periostin protein was expressed higher in CSC cells compared to the control cells and was found to be related to CSC chemotherapy resistance. Moreover, periostin expression was found to be related to the CSC ratio in 1,086 breast cancer specimens (P = 0.001). In total, 334 (30.76%) of the 1,086 breast cases showed high periostin expression. After universal and Spearman regression correlation analysis, periostin was observed to be related to histological grade, CSC ratio, lymph node metastasis, tumor size, and triple-negative breast cancer (all P<0.05). Furthermore, periostin was shown to attain a significantly more distant bone metastasis and worse disease-specific survival than those with none or low-expressed periostin protein (P = 0.001). In the Cox regression test, periostin protein was detected as an independent prognostic factor (P = 0.001). In conclusion, periostin was found to be related to the CSC and an independent prognostic factor for breast cancer. It is also perhaps a potential target to breast cancer.     

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

Bladder cancer is the second most common cancer of the urogenital tract and novel therapeutic approaches that can reduce recurrence and progression are needed. The tumor microenvironment can significantly influence tumor development and therapy response. It is therefore often desirable to grow tumor cells in the organ from which they originated. This protocol describes an orthotopic model of bladder cancer, in which MB49 murine bladder carcinoma cells are instilled into the bladder via catheterization. Successful tumor cell implantation in this model requires disruption of the protective glycosaminoglycan layer, which can be accomplished by physical or chemical means. In our protocol the bladder is treated with trypsin prior to cell instillation. Catheterization of the bladder can also be used to deliver therapeutics once the tumors are established. This protocol describes the delivery of an adenoviral construct that expresses a luciferase reporter gene. While our protocol has been optimized for short-term studies and focuses on gene delivery, the methodology of mouse bladder catheterization has broad applications.