Dataset Information

An Integrated Pan-Cancer Analysis and Structure-Based Virtual Screening of GPR15.

ABSTRACT: G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan G protein-coupled receptors (GPCRs) involving human immunodeficiency virus (HIV) infection, colonic inflammation, and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability to inhibit cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) than in normal tissues. Among 33 cancer types, GPR15 expression was significantly positively correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), and lung adenocarcinoma (LUAD) and significantly negatively correlated with stomach adenocarcinoma (STAD). This study also revealed that commonly upregulated gene sets in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD, and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted structure-based virtual screening. The top eight hit compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provides novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

SUBMITTER: Wang Y

PROVIDER: S-EPMC6940937 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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An Integrated Pan-Cancer Analysis and Structure-Based Virtual Screening of GPR15.

Wang Yanjing Y Wang Xiangeng X Xiong Yi Y Li Cheng-Dong CD Xu Qin Q Shen Lu L Chandra Kaushik Aman A Wei Dong-Qing DQ

International journal of molecular sciences 20191210 24

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan G protein-coupled receptors (GPCRs) involving human immunodeficiency virus (HIV) infection, colonic inflammation, and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability to inhibit cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Geno ...[more]

PMID: 31835584

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Project description:The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.

Project description:Background: The autophagy pathway within the tumour microenvironment can be regulated to inhibit or promote tumour development. In the fight against tumour growth, immunotherapy induces an anti-tumour immune response, whereas autophagy modulates this immune response. A key protein in the autophagy pathway, microtubule-associated protein 1 light chain 3 (MAP1LC3), has recently become a hotspot for tumour research. As a relatively novel member, the function of MAP1LC3C in tumours still need to be investigated. Therefore, the goal of this study was to look into the possible link between MAP1LC3C and immunotherapy for 33 kinds of human malignancies by using pan-cancer analysis. Methods: High-throughput sequencing data from The Cancer Genome Atlas, Genotype-Tissue Expression Project and Cancer Cell Line Encyclopedia databases, combined with clinical data, were used to analyze the expression of MAP1LC3C in 33 types of cancer, as well as patient prognosis and neoplasm staging. Activity scores were calculated using ssGSEA to assess the MAP1LC3C activity in pan-cancer. Associations between MAP1LC3C and the tumour microenvironment, including immune cell infiltration and immunomodulators, were analyzed. Moreover, tumour tissue ImmuneScores and StromalScores were analyzed using the ESTIMATE algorithm. Additionally, associations between MAP1LC3C and tumour mutational burden/microsatellite instability, were investigated. Finally, based on the expression and structure of MAP1LC3C, the United States Food and Drug Administration (FDA)-approved drugs, were screened by virtual screening, molecular docking and NCI-60 drug sensitivity analysis. Results: Our study found that MAP1LC3C was differentially expressed in tumour and normal tissues in 23 of 33 human cancer types, among which MAP1LC3C had prognostic effects in 12 cancer types, and MAP1LC3C expression was significantly correlated with tumour stage in four cancer types. In addition, MAP1LC3C activity in 14 cancer types was consistent with changes in transcription levels. Moreover, MAP1LC3C strongly correlated with immune infiltration, immune modulators and immune markers. Finally, a number of FDA-approved drugs were identified via virtual screening and drug sensitivity analysis. Conclusion: Our study investigated the prognostic and immunotherapeutic value of MAP1LC3C in 33 types of cancer, and several FDA-approved drugs were identified to be highly related to MAP1LC3C and can be potential cancer therapeutic candidates.

Dataset Information

An Integrated Pan-Cancer Analysis and Structure-Based Virtual Screening of GPR15.

Publications

An Integrated Pan-Cancer Analysis and Structure-Based Virtual Screening of GPR15.

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