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Alam MS, Sultana A, Sun H, Wu J, Guo F, Li Q, Ren H, Hao Z, Zhang Y, Wang G. Bioinformatics and network-based screening and discovery of potential molecular targets and small molecular drugs for breast cancer. Front Pharmacol 2022; 13:942126. [PMID: 36204232 PMCID: PMC9531711 DOI: 10.3389/fphar.2022.942126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
Accurate identification of molecular targets of disease plays an important role in diagnosis, prognosis, and therapies. Breast cancer (BC) is one of the most common malignant cancers in women worldwide. Thus, the objective of this study was to accurately identify a set of molecular targets and small molecular drugs that might be effective for BC diagnosis, prognosis, and therapies, by using existing bioinformatics and network-based approaches. Nine gene expression profiles (GSE54002, GSE29431, GSE124646, GSE42568, GSE45827, GSE10810, GSE65216, GSE36295, and GSE109169) collected from the Gene Expression Omnibus (GEO) database were used for bioinformatics analysis in this study. Two packages, LIMMA and clusterProfiler, in R were used to identify overlapping differential expressed genes (oDEGs) and significant GO and KEGG enrichment terms. We constructed a PPI (protein–protein interaction) network through the STRING database and identified eight key genes (KGs) EGFR, FN1, EZH2, MET, CDK1, AURKA, TOP2A, and BIRC5 by using six topological measures, betweenness, closeness, eccentricity, degree, MCC, and MNC, in the Analyze Network tool in Cytoscape. Three online databases GSCALite, Network Analyst, and GEPIA were used to analyze drug enrichment, regulatory interaction networks, and gene expression levels of KGs. We checked the prognostic power of KGs through the prediction model using the popular machine learning algorithm support vector machine (SVM). We suggested four TFs (TP63, MYC, SOX2, and KDM5B) and four miRNAs (hsa-mir-16-5p, hsa-mir-34a-5p, hsa-mir-1-3p, and hsa-mir-23b-3p) as key transcriptional and posttranscriptional regulators of KGs. Finally, we proposed 16 candidate repurposing drugs YM201636, masitinib, SB590885, GSK1070916, GSK2126458, ZSTK474, dasatinib, fedratinib, dabrafenib, methotrexate, trametinib, tubastatin A, BIX02189, CP466722, afatinib, and belinostat for BC through molecular docking analysis. Using BC cell lines, we validated that masitinib inhibits the mTOR signaling pathway and induces apoptotic cell death. Therefore, the proposed results might play an effective role in the treatment of BC patients.
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Affiliation(s)
- Md Shahin Alam
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Adiba Sultana
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Hongyang Sun
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Jin Wu
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Fanfan Guo
- Department of Pharmacology, College of Pharmaceutical Science, Soochow University, Suzhou, Jiangsu, China
| | - Qing Li
- Department of Gastroenterology, the First People’s Hospital of Taicang, Taicang Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Haigang Ren
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
| | - Zongbing Hao
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
- *Correspondence: Zongbing Hao, ; Yi Zhang, ; Guanghui Wang,
| | - Yi Zhang
- Department of Pharmacology, College of Pharmaceutical Science, Soochow University, Suzhou, Jiangsu, China
- *Correspondence: Zongbing Hao, ; Yi Zhang, ; Guanghui Wang,
| | - Guanghui Wang
- Laboratory of Molecular Neuropathology, Department of Pharmacology, Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China
- *Correspondence: Zongbing Hao, ; Yi Zhang, ; Guanghui Wang,
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2
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Eskandarzade N, Ghorbani A, Samarfard S, Diaz J, Guzzi PH, Fariborzi N, Tahmasebi A, Izadpanah K. Network for network concept offers new insights into host- SARS-CoV-2 protein interactions and potential novel targets for developing antiviral drugs. Comput Biol Med 2022; 146:105575. [PMID: 35533462 PMCID: PMC9055686 DOI: 10.1016/j.compbiomed.2022.105575] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 04/16/2022] [Accepted: 04/27/2022] [Indexed: 01/08/2023]
Abstract
SARS-CoV-2, the causal agent of COVID-19, is primarily a pulmonary virus that can directly or indirectly infect several organs. Despite many studies carried out during the current COVID-19 pandemic, some pathological features of SARS-CoV-2 have remained unclear. It has been recently attempted to address the current knowledge gaps on the viral pathogenicity and pathological mechanisms via cellular-level tropism of SARS-CoV-2 using human proteomics, visualization of virus-host protein-protein interactions (PPIs), and enrichment analysis of experimental results. The synergistic use of models and methods that rely on graph theory has enabled the visualization and analysis of the molecular context of virus/host PPIs. We review current knowledge on the SARS-COV-2/host interactome cascade involved in the viral pathogenicity through the graph theory concept and highlight the hub proteins in the intra-viral network that create a subnet with a small number of host central proteins, leading to cell disintegration and infectivity. Then we discuss the putative principle of the "gene-for-gene and "network for network" concepts as platforms for future directions toward designing efficient anti-viral therapies.
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Affiliation(s)
- Neda Eskandarzade
- Department of Basic Sciences, School of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Abozar Ghorbani
- Nuclear Agriculture Research School, Nuclear Science and Technology Research Institute (NSTRI), Karaj, Iran,Corresponding author
| | - Samira Samarfard
- Berrimah Veterinary Laboratory, Department of Primary Industry and Resources, Berrimah, NT, 0828, Australia
| | - Jose Diaz
- Laboratorio de Dinámica de Redes Genéticas, Centro de Investigación en Dinámica Celular, Universidad Autónoma del Estado de Morelos, Cuernavaca, Mexico
| | - Pietro H. Guzzi
- Department of Medical and Surgical Sciences, Laboratory of Bioinformatics Unit, Italy
| | - Niloofar Fariborzi
- Department of Medical Entomology and Vector Control, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ahmad Tahmasebi
- Institute of Biotechnology, College of Agriculture, Shiraz University, Shiraz, Iran
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3
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Alam MS, Sultana A, Reza MS, Amanullah M, Kabir SR, Mollah MNH. Integrated bioinformatics and statistical approaches to explore molecular biomarkers for breast cancer diagnosis, prognosis and therapies. PLoS One 2022; 17:e0268967. [PMID: 35617355 PMCID: PMC9135200 DOI: 10.1371/journal.pone.0268967] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 05/11/2022] [Indexed: 02/06/2023] Open
Abstract
Integrated bioinformatics and statistical approaches are now playing the vital role in identifying potential molecular biomarkers more accurately in presence of huge number of alternatives for disease diagnosis, prognosis and therapies by reducing time and cost compared to the wet-lab based experimental procedures. Breast cancer (BC) is one of the leading causes of cancer related deaths for women worldwide. Several dry-lab and wet-lab based studies have identified different sets of molecular biomarkers for BC. But they did not compare their results to each other so much either computationally or experimentally. In this study, an attempt was made to propose a set of molecular biomarkers that might be more effective for BC diagnosis, prognosis and therapies, by using the integrated bioinformatics and statistical approaches. At first, we identified 190 differentially expressed genes (DEGs) between BC and control samples by using the statistical LIMMA approach. Then we identified 13 DEGs (AKR1C1, IRF9, OAS1, OAS3, SLCO2A1, NT5E, NQO1, ANGPT1, FN1, ATF6B, HPGD, BCL11A, and TP53INP1) as the key genes (KGs) by protein-protein interaction (PPI) network analysis. Then we investigated the pathogenetic processes of DEGs highlighting KGs by GO terms and KEGG pathway enrichment analysis. Moreover, we disclosed the transcriptional and post-transcriptional regulatory factors of KGs by their interaction network analysis with the transcription factors (TFs) and micro-RNAs. Both supervised and unsupervised learning's including multivariate survival analysis results confirmed the strong prognostic power of the proposed KGs. Finally, we suggested KGs-guided computationally more effective seven candidate drugs (NVP-BHG712, Nilotinib, GSK2126458, YM201636, TG-02, CX-5461, AP-24534) compared to other published drugs by cross-validation with the state-of-the-art alternatives top-ranked independent receptor proteins. Thus, our findings might be played a vital role in breast cancer diagnosis, prognosis and therapies.
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Affiliation(s)
- Md. Shahin Alam
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- * E-mail: (MNHM); (MSA)
| | - Adiba Sultana
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- Center for Systems Biology, Soochow University, Suzhou, China
| | - Md. Selim Reza
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
| | - Md Amanullah
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- Department of Respiratory Medicine, Sir Run Run Shaw Hospital and Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Syed Rashel Kabir
- Department of Biochemistry and Molecular Biology, Rajshahi University, Rajshahi, Bangladesh
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh
- * E-mail: (MNHM); (MSA)
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Meng M, Lan T, Tian D, Qin Z, Li Y, Li J, Cao H. Integrative Bioinformatics Analysis Demonstrates the Prognostic Value of Chromatin Accessibility Biomarkers in Clear Cell Renal Cell Carcinoma. Front Oncol 2022; 11:814396. [PMID: 34993155 PMCID: PMC8724435 DOI: 10.3389/fonc.2021.814396] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 11/24/2021] [Indexed: 01/22/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) accounts for 75%–85% of renal cell carcinoma (RCC) and has a poor 5-year survival rate. In recent years, medical advancement has promoted the understanding of the histopathological and molecular characterization of ccRCC; however, the carcinogenesis and molecular mechanisms of ccRCC remain unclear. Chromatin accessibility is an essential determinant of cellular phenotype. This study aimed to explore the potential role of chromatin accessibility in the development and progression of ccRCC. By the combination of open-access genome-wide chromatin accessibility profiles and gene expression profiles in ccRCC, we obtained a total of 13,474 crucial peaks, corresponding to 5,120 crucial genes and 9,185 differentially expressed genes. Moreover, two potential function modules (P2 and G4) that contained 129 upregulated genes were identified via the weighted gene co-expression network analysis (WGCNA). Furthermore, we obtained five independent predictors (FSCN1, SLC17A9, ANKRD13B, ADCY2, and MAPT), and a prognostic model was established based on these genes through the least absolute shrinkage and selection operator-proportional hazards model (LASSO-Cox) analysis. This model can stratify the ccRCC samples into a high-risk and a low-risk group, from which the patients have distinct prognosis. Further analysis demonstrated a completely different immune cell infiltration pattern between these two risk groups. This study also suggested that mast cell resting is associated with the prognosis of ccRCC and could be a target of immunotherapy. Overall, this study indicated that chromatin accessibility plays an essential role in ccRCC. The five prognostic chromatin accessibility biomarkers and the prognostic immune cells can provide a new direction for the treatment of ccRCC.
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Affiliation(s)
- Meng Meng
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,National Supercomputer Center in Guangzhou, Sun Yat-sen University, Guangzhou, China
| | - Tianjun Lan
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Oral & Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Duanqing Tian
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zeman Qin
- Department of Stomatology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yu Li
- Department of Laboratory Medicine, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jinsong Li
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Oral & Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Haotian Cao
- Research Center of Medicine, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Oral & Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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5
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Song K, Farzaneh M. Signaling pathways governing breast cancer stem cells behavior. Stem Cell Res Ther 2021; 12:245. [PMID: 33863385 PMCID: PMC8052733 DOI: 10.1186/s13287-021-02321-w] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Accepted: 03/31/2021] [Indexed: 02/06/2023] Open
Abstract
Breast cancer is the second common cancer and the leading cause of malignancy among females overall. Breast cancer stem cells (BCSCs) are a small population of breast cancer cells that play a critical role in the metastasis of breast cancer to other organs in the body. BCSCs have both self-renewal and differentiation capacities, which are thought to contribute to the aggressiveness of metastatic lesions. Therefore, targeting BCSCs can be a suitable approach for the treatment and metastasis of breast cancer. Growing evidence has indicated that the Wnt, NFκB, Notch, BMP2, STAT3, and hedgehog (Hh) signaling pathways govern epithelial-to-mesenchymal transition (EMT) activation, growth, and tumorigenesis of BCSCs in the primary regions. miRNAs as the central regulatory molecules also play critical roles in BCSC self-renewal, metastasis, and drug resistance. Hence, targeting these pathways might be a novel therapeutic approach for breast cancer diagnosis and therapy. This review discusses known signaling mechanisms involved in the stimulation or prevention of BCSC self-renewal, metastasis, and tumorigenesis.
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Affiliation(s)
- Kai Song
- Xuzhou Vocational College of Bioengineering, Xuzhou, 221006, Jiangsu, China.
| | - Maryam Farzaneh
- Fertility, Infertility and Perinatology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
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6
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Chen B, Sun D, Qin X, Gao XH. Screening and identification of potential biomarkers and therapeutic drugs in melanoma via integrated bioinformatics analysis. Invest New Drugs 2021; 39:928-948. [PMID: 33501609 DOI: 10.1007/s10637-021-01072-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 01/19/2021] [Indexed: 12/15/2022]
Abstract
Melanoma is a highly aggressive malignant skin tumor with a high rate of metastasis and mortality. In this study, a comprehensive bioinformatics analysis was used to clarify the hub genes and potential drugs. Download the GSE3189, GSE22301, and GSE35388 microarray datasets from the Gene Expression Omnibus (GEO), which contains a total of 33 normal samples and 67 melanoma samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) approach analyze DEGs based on the DAVID. Use STRING to construct protein-protein interaction network, and use MCODE and cytoHubba plug-ins in Cytoscape to perform module analysis and identified hub genes. Use Gene Expression Profile Interactive Analysis (GEPIA) to assess the prognosis of genes in tumors. Finally, use the Drug-Gene Interaction Database (DGIdb) to screen targeted drugs related to hub genes. A total of 140 overlapping DEGs were identified from the three microarray datasets, including 59 up-regulated DEGs and 81 down-regulated DEGs. GO enrichment analysis showed that these DEGs are mainly involved in the biological process such as positive regulation of gene expression, positive regulation of cell proliferation, positive regulation of MAP kinase activity, cell migration, and negative regulation of the apoptotic process. The cellular components are concentrated in the membrane, dendritic spine, the perinuclear region of cytoplasm, extracellular exosome, and membrane raft. Molecular functions include protein homodimerization activity, calmodulin-binding, transcription factor binding, protein binding, and cytoskeletal protein binding. KEGG pathway analysis shows that these DEGs are mainly related to protein digestion and absorption, PPAR signaling pathway, signaling pathways regulating stem cells' pluripotency, and Retinol metabolism. The 23 most closely related DEGs were identified from the PPI network and combined with the GEPIA prognostic analysis, CDH3, ESRP1, FGF2, GBP2, KCNN4, KIT, SEMA4D, and ZEB1 were selected as hub genes, which are considered to be associated with poor prognosis of melanoma closely related. Besides, ten related drugs that may have therapeutic effects on melanoma were also screened. These newly discovered genes and drugs provide new ideas for further research on melanoma.
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Affiliation(s)
- Bo Chen
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
- Medical Research Center, Liaoning Key Laboratory of Research and Application of Animal Models for Environmental and Metabolic Diseases, Shengjing Hospital of China Medical University, Shenyang, China
| | - Donghong Sun
- Department of Dermatology, The First Hospital of China Medical University, No. 155 Nanjing North Street, Shenyang, 110001, Liaoning Province, China
| | - Xiuni Qin
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
- Medical Research Center, Liaoning Key Laboratory of Research and Application of Animal Models for Environmental and Metabolic Diseases, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xing-Hua Gao
- Department of Dermatology, The First Hospital of China Medical University, No. 155 Nanjing North Street, Shenyang, 110001, Liaoning Province, China.
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7
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Hong Z, Wang Q, Hong C, Liu M, Qiu P, Lin R, Lin X, Chen F, Li Q, Liu L, Wang C, Chen D. Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer. J Cancer 2021; 12:740-753. [PMID: 33403032 PMCID: PMC7778540 DOI: 10.7150/jca.48245] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 11/04/2020] [Indexed: 12/24/2022] Open
Abstract
Breast cancer (BC), with complex tumorigenesis and progression, remains the most common malignancy in women. We aimed to explore some novel and significant genes with unfavorable prognoses and potential pathways involved in BC initiation and progression via bioinformatics methods. BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002, which included a total of 651 BC tissues and 44 normal breast tissues, were obtained from the Gene Expression Omnibus (GEO) database, and 124 differentially expressed genes (DEGs) were identified between BC tissues and normal breast tissues via R software and an online Venn diagram tool. Database for Annotation, Visualization and Integration Discovery (DAVID) software showed that 65 upregulated DEGs were mainly enriched in the regulation of the cell cycle, and Search Tool for the Retrieval of Interacting Genes (STRING) software identified the 39 closest associated upregulated DEGs in protein-protein interactions (PPIs), which validated the high expression of genes in BC tissues by the Gene Expression Profiling Interactive Analysis (GEPIA) tool. In addition, 36 out of 39 BC patients showed significantly worse outcomes by Kaplan-Meier plotter (KM plotter), and an additional Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that seven genes (cyclin E2 (CCNE2), cyclin B1 (CCNB1), cyclin B2 (CCNB2), mitotic checkpoint serine/threonine kinase B (BUB1B), dual-specificity protein kinase (TTK), cell division cycle 20 (CDC20), and pituitary tumor transforming gene 1 (PTTG1)) were markedly enriched in the cell cycle pathway. Analysis of the clinicopathological characteristics of hub genes revealed that seven cell cycle-related genes (CCRGs) were significantly highly expressed in four BC subtypes (luminal A, luminal B, HER2-positive and triple-negative (TNBC)), and except for the CCNE2 gene, high expression levels were significantly associated with tumor pathological grade and stage and metastatic events of BC. Furthermore, genetic mutation analysis indicated that genetic alterations of CCRGs could also significantly affect BC patients' prognosis. A quantitative real-time polymerase chain reaction (qRT-PCR) assay found that the seven CCRGs were significantly differentially expressed in BC cell lines. Integration of published multilevel expression data and a bioinformatics computational approach were used to predict and construct a regulation mechanism: a transcription factor (TF)-microRNA (miRNA)-messenger RNA (mRNA) regulation network. The present work is the first to construct a regulatory network of TF-miRNA-mRNA in BC for CCRGs and provides new insights into the molecular mechanism of BC.
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Affiliation(s)
- Zhipeng Hong
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China.,Department of Breast Surgery and General Surgery, The Affiliated Union Hospital of Fujian Medical University, Fuzhou, Fujian Province, 350001, P. R. China.,Breast Cancer Institute, Fujian Medical University, Fuzhou, Fujian Province, 350001, P.R. China
| | - Qinglan Wang
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Chengye Hong
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Meimei Liu
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Pengqin Qiu
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Rongrong Lin
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Xiaolan Lin
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Fangfang Chen
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Qiuhuang Li
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Lingling Liu
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
| | - Chuan Wang
- Department of Breast Surgery and General Surgery, The Affiliated Union Hospital of Fujian Medical University, Fuzhou, Fujian Province, 350001, P. R. China.,Breast Cancer Institute, Fujian Medical University, Fuzhou, Fujian Province, 350001, P.R. China
| | - Debo Chen
- Department of Breast Surgery, Affiliated Quanzhou First Hospital of Fujian Medical University, Quanzhou, Fujian Province, 362000, P. R. China
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Dai FF, Bao AY, Luo B, Zeng ZH, Pu XL, Wang YQ, Zhang L, Xian S, Yuan MQ, Yang DY, Liu SY, Cheng YX. Identification of differentially expressed genes and signaling pathways involved in endometriosis by integrated bioinformatics analysis. Exp Ther Med 2019; 19:264-272. [PMID: 31853298 PMCID: PMC6909483 DOI: 10.3892/etm.2019.8214] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 10/11/2019] [Indexed: 12/11/2022] Open
Abstract
Endometriosis is a common gynecological disease characterized by the presence and growth of endometrial tissue outside the uterus, including the pelvis and abdominal cavity. This condition causes various clinical symptoms, such as non-menstrual pelvic pain, dysmenorrhea and infertility, seriously affecting the health and quality of life of women. To date, the specific mechanism and the key molecules of endometriosis remain uncertain. The purpose of the present study was to elucidate the mechanisms involved in the development and persistence of the disease. A number of mRNA expression profile datasets (namely GSE11691, GSE23339, GSE25628 and GSE78851) were downloaded from the Gene Expression Omnibus (GEO) database. These gene expression profiles were normalized, and the differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis. A total of 103 DEGs were screened upon excluding the genes that exhibited inconsistency of expression (P<0.05). Furthermore, the Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and construction of protein-protein interaction networks of DEGs were performed using online software. The results revealed that the DEGs were closely associated with cell migration, adherens junction and hypoxia-inducible factor signaling. In addition, immunohistochemical assay results were found to be consistent with the bioinformatics results. The present study may help us understand underlying molecular mechanisms and the development of endometriosis, which has a great clinical significance for early diagnosis of the disease.
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Affiliation(s)
- Fang-Fang Dai
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China.,Department of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China
| | - An-Yu Bao
- Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Bing Luo
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Zi-Hang Zeng
- Department of Oncology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China
| | - Xiao-Li Pu
- Department of Obstetrics and Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000, P.R. China
| | - Yan-Qing Wang
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Li Zhang
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Shu Xian
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Meng-Qin Yuan
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Dong-Yong Yang
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Shi-Yi Liu
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Yan-Xiang Cheng
- Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
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9
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Malvia S, Bagadi SAR, Pradhan D, Chintamani C, Bhatnagar A, Arora D, Sarin R, Saxena S. Study of Gene Expression Profiles of Breast Cancers in Indian Women. Sci Rep 2019; 9:10018. [PMID: 31292488 PMCID: PMC6620270 DOI: 10.1038/s41598-019-46261-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Accepted: 06/25/2019] [Indexed: 02/06/2023] Open
Abstract
Breast cancer is the most common cancer among women globally. In India, the incidence of breast cancer has increased significantly during the last two decades with a higher proportion of the disease at a young age compared to the west. To understand the molecular processes underlying breast cancer in Indian women, we analysed gene expression profiles of 29 tumours and 9 controls using microarray. In the present study, we obtained 2413 differentially expressed genes, consisting of overexpressed genes such as COL10A1, COL11A1, MMP1, MMP13, MMP11, GJB2, and CST1 and underexpressed genes such as PLIN1, FABP4, LIPE, AQP7, LEP, ADH1A, ADH1B, and CIDEC. The deregulated pathways include cell cycle, focal adhesion and metastasis, DNA replication, PPAR signaling, and lipid metabolism. Using PAM50 classifier, we demonstrated the existence of molecular subtypes in Indian women. In addition, qPCR validation of expression of metalloproteinase genes, MMP1, MMP3, MMP11, MMP13, MMP14, ADAMTS1, and ADAMTS5 showed concordance with that of the microarray data; wherein we found a significant association of ADAMTS5 down-regulation with older age (≥55 years) of patients. Together, this study reports gene expression profiles of breast tumours from the Indian subcontinent, throwing light on the pathways and genes associated with the breast tumourigenesis in Indian women.
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Affiliation(s)
- Shreshtha Malvia
- Tumour Biology Division, ICMR-National Institute of Pathology, New Delhi, 110029, India
| | | | - Dibyabhaba Pradhan
- Bioinformatics Cell, ICMR-National Institute of Pathology, New Delhi, 110029, India
| | | | - Amar Bhatnagar
- Department of Cancer Surgery, Safdarjung Hospital, New Delhi, 110029, India
| | - Deepshikha Arora
- Department of Pathology, Indraprastha Apollo Hospital, New Delhi, 110076, India
| | - Ramesh Sarin
- Department of Surgery, Indraprastha Apollo Hospital, New Delhi, 110076, India
| | - Sunita Saxena
- Tumour Biology Division, ICMR-National Institute of Pathology, New Delhi, 110029, India.
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Identification of core genes and clinical roles in pregnancy-associated breast cancer based on integrated analysis of different microarray profile datasets. Biosci Rep 2019; 39:BSR20190019. [PMID: 31171715 PMCID: PMC6591572 DOI: 10.1042/bsr20190019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 05/06/2019] [Accepted: 05/31/2019] [Indexed: 12/18/2022] Open
Abstract
More women are delaying child-birth. Thus, the diagnosis of pregnancy-associated breast cancer (PABC) will continue to increase. The aim of this study was to identify core candidate genes of PABC, and the relevance of the genes on the prognosis of PABC. GSE31192 and GSE53031 microarray profile datasets were downloaded from the Gene Expression Omnibus database and differentially expressed genes were analyzed using the R package and GEO2R tool. Then, Gene Ontology and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Moreover, the Search Tool for the Retrieval of Interacting Genes and the Molecular Complex Detection Cytoscape software plug-in were utilized to visualize protein–protein interactions and to screen candidate genes. A total of 239 DEGs were identified in PABC, including 101 up-regulated genes mainly enriched in fatty acid activation and the fibroblast growth factor signaling pathway, while 138 down-regulated genes particularly involved in activation of DNA fragmentation factor and apoptosis-induced DNA fragmentation. Fourteen hub genes with a high degree of connectivity were selected, including CREB1, ARF3, UBA5, SIAH1, KLHL3, HECTD1, MMP9, TRIM69, MEX3C, ASB6, UBE2Q2, FBXO22, EIF4A3, and PXN. Overall survival (OS) analysis of core candidate genes was performed using the Gene Expression Profiling Interactive Analysis and UALCAN websites. High ASB6 expression was associated with worse OS of PABC patients. Molecular subtypes and menopause status were also associated with worse OS for PABC patients. In conclusion, ASB6 could be a potential predictor and therapeutic target in patient with PABC.
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11
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Wang S, Yu ZH, Chai KQ. Identification of CFTR as a novel key gene in chromophobe renal cell carcinoma through bioinformatics analysis. Oncol Lett 2019; 18:1767-1774. [PMID: 31423244 PMCID: PMC6607225 DOI: 10.3892/ol.2019.10476] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 05/30/2019] [Indexed: 12/25/2022] Open
Abstract
Chromophobe renal cell carcinoma (chRCC), the third most common histological subtype of RCC, comprises 5–7% of all RCC cases. The aim of the present study was to identify potential biomarkers for chRCC and to examine the underlying mechanisms. A total of 4 profile datasets were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs were performed with the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed to predict hub genes. Hub gene expression within chRCC across multiple datasets, as well as overall survival, were investigated by utilizing the Oncomine platform and UALCAN dataset, separately. A total of 266 DEGs (88 upregulated genes and 168 downregulated genes) were identified from 4 profile datasets. Integrating the results from the PPI network, Oncomine platform and survival analysis, CFTR was screened as a key factor in the prognosis of chRCC. GO and KEGG analysis revealed that 266 DEGs were mainly enriched in 17 terms and 9 pathways. The present study identified key genes and potential molecular mechanisms underlying the development of chRCC, and CFTR may be a potential prognostic biomarker and novel therapeutic target for chRCC.
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Affiliation(s)
- Sheng Wang
- The Second Clinical Medical College, Zhejiang Chinese Medicine University, Hangzhou, Zhejiang 310053, P.R. China.,Department of Oncology, Tongde Hospital of Zhejiang, Hangzhou, Zhejiang 310053, P.R. China
| | - Zhi-Hong Yu
- Department of Oncology, Tongde Hospital of Zhejiang, Hangzhou, Zhejiang 310053, P.R. China
| | - Ke-Qun Chai
- Department of Oncology, Tongde Hospital of Zhejiang, Hangzhou, Zhejiang 310053, P.R. China
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12
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Prospective molecular mechanism of COL5A1 in breast cancer based on a microarray, RNA sequencing and immunohistochemistry. Oncol Rep 2019; 42:151-175. [PMID: 31059074 PMCID: PMC6549075 DOI: 10.3892/or.2019.7147] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 04/16/2019] [Indexed: 12/11/2022] Open
Abstract
Breast cancer (BC) has a complex etiology and pathogenesis, and is the most common malignant tumor type in females, in USA in 2018, yet its relevant molecular mechanisms remain largely unknown. The collagen type V α-1 chain (COL5A1) gene is differentially expressed in renal and ovarian cancer. Using bioinformatics methods, COL5A1 was determined to also be a significant gene in BC, but its association with BC has not been sufficiently reported. COL5A1 microarray and relevant clinical data were collected from the Gene Expression Omnibus, The Cancer Genome Atlas and other databases to summarize COL5A1 expression in BC and its subtypes at the mRNA and protein levels. All associated information was comprehensively analyzed by various software. The clinical significance of the mutation was obtained via the cBioPortal. Furthermore, Gene Ontology functional annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were also performed to investigate the mechanism of COL5A1 in BC. Immunohistochemistry was also conducted to detect and confirm COL5A1 expression. It was determined that COL5A1 was highly expressed in BC tissues, compared with normal tissues at the mRNA level [standard mean difference, 0.84; 95% confidence interval (CI), 0.60-1.07; P=0.108]. The area under the summary receiver operator characteristic curve for COL5A1 was 0.87 (95% CI, 0.84-0.90). COL5A1 expression was altered in 32/817 (4%) sequenced samples. KEGG analysis confirmed the most notable pathways, including focal adhesion, extracellular matrix-receptor interaction and regulation of the actin cytoskeleton. Immunohistochemical detection was used to verify the expression of COL5A1 in 136 selected cases of invasive BC tissues and 55 cases of adjacent normal tissues, while the rate of high expression of COL5A1 in BC was up to 90.4%. These results indicated that COL5A1 is highly expressed at the mRNA and protein levels in BC, and the prognosis of patients with BC with high COL5A1 expression may be reduced; therefore, COL5A1 may be used independently or combined with other detection factors in BC diagnosis.
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13
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Wang K, Li L, Fu L, Yuan Y, Dai H, Zhu T, Zhou Y, Yuan F. Integrated Bioinformatics Analysis the Function of RNA Binding Proteins (RBPs) and Their Prognostic Value in Breast Cancer. Front Pharmacol 2019; 10:140. [PMID: 30881302 PMCID: PMC6405693 DOI: 10.3389/fphar.2019.00140] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 02/06/2019] [Indexed: 02/06/2023] Open
Abstract
Background and Purpose: Breast cancer is one of the leading causes of death among women. RNA binding proteins (RBPs) play a vital role in the progression of many cancers. Functional investigation of RBPs may contribute to elucidating the mechanisms underlying tumor initiation, progression, and invasion, therefore providing novel insights into future diagnosis, treatment, and prognosis. Methods: We downloaded RNA sequencing data from the cancer genome atlas (TCGA) by UCSC Xena and identified relevant RBPs through an integrated bioinformatics analysis. We then analyzed biological processes of differentially expressed genes (DEGs) by DAVID, and established their interaction networks and performed pathway analysis through the STRING database to uncover potential biological effects of these RBPs. We also explored the relationship between these RBPs and the prognosis of breast cancer patients. Results: In the present study, we obtained 1092 breast tumor samples and 113 normal controls. After data analysis, we identified 90 upregulated and 115 downregulated RBPs in breast cancer. GO and KEGG pathway analysis indicated that these significantly changed genes were mainly involved in RNA processing, splicing, localization and RNA silencing, DNA transposition regulation and methylation, alkylation, mitochondrial gene expression, and transcription regulation. In addition, some RBPs were related to histone H3K27 methylation, estrogen response, inflammatory mediators, and translation regulation. Our study also identified five RBPs associated with breast cancer prognosis. Survival analysis found that overexpression of DCAF13, EZR, and MRPL13 showed worse survival, but overexpression of APOBEC3C and EIF4E3 showed better survival. Conclusion: In conclusion, we identified key RBPs of breast cancer through comprehensive bioinformatics analysis. These RBPs were involved in a variety of biological and molecular pathways in breast cancer. Furthermore, we identified five RBPs as a potential prognostic biomarker of breast cancer. Our study provided novel insights to understand breast cancer at a molecular level.
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Affiliation(s)
- Ke Wang
- Clinical Laboratory, Yongchuan People's Hospital of Chongqing, Chongqing, China
| | - Ling Li
- Clinical Laboratory, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Liang Fu
- Clinical Laboratory, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Yongqiang Yuan
- Clinical Laboratory, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Hongying Dai
- Clinical Laboratory, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Tianjin Zhu
- Clinical Laboratory, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Yuxi Zhou
- Yidu Cloud (Beijing) Technology Co., Ltd., Beijing, China
| | - Fang Yuan
- Yidu Cloud (Beijing) Technology Co., Ltd., Beijing, China
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14
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Huang W, Li H, Cheng C, Ren C, Chen T, Jiang X, Cheng K, Luo P, Hu C. Analysis of the transcriptome data in Litopenaeus vannamei reveals the immune basis and predicts the hub regulation-genes in response to high-pH stress. PLoS One 2018; 13:e0207771. [PMID: 30517152 PMCID: PMC6281221 DOI: 10.1371/journal.pone.0207771] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2018] [Accepted: 11/06/2018] [Indexed: 11/18/2022] Open
Abstract
Soil salinization erodes the farmlands and poses a serious threat to human life, reuse of the saline-alkali lands as cultivated resources becomes increasingly prominent. Pacific white shrimp (Litopenaeus vannamei) is an important farmed aquatic species for the development and utilization of the saline-alkali areas. However, little is known about the adaptation mechanism of this species in terms of high-pH stress. In the present study, a transcriptome analysis on the gill tissues of L. vannamei in response to high-pH stress (pH 9.3 ± 0.1) was conducted. After analyzing, the cyclic nucleotide gated channel-Ca2+ (CNGC-Ca2+) and patched 1 (Ptc1) were detected as the majority annotated components in the cAMP signaling pathway (KO04024), indicating that the CNGC-Ca2+ and Ptc1 might be the candidate components for transducing and maintaining the high-pH stress signals, respectively. The immunoglobulin superfamily (IgSF), heat shock protein (HSP), glutathione s-transferase (GST), prophenoloxidase/phenoloxidase (proPO/PO), superoxide dismutase (SOD), anti-lipopolysaccharide factor (ALF) and lipoprotein were discovered as the major transcribed immune factors in response to high-pH stress. To further detect hub regulation-genes, protein-protein interaction (PPI) networks were constructed; the genes/proteins "Polymerase (RNA) II (DNA directed) polypeptide A" (POLR2A), "Histone acetyltransferase p300" (EP300) and "Heat shock 70kDa protein 8" (HSPA8) were suggested as the top three hub regulation-genes in response to acute high-pH stress; the genes/proteins "Heat shock 70kDa protein 4" (HSPA4), "FBJ murine osteosarcoma viral oncogene homolog" (FOS) and "Nucleoporin 54kDa" (NUP54) were proposed as the top three hub regulation-genes involved in adapting endurance high-pH stress; the protein-interactions of "EP300-HSPA8" and "HSPA4-NUP54" were detected as the most important biological interactions in response to the high-pH stress; and the HSP70 family genes might play essential roles in the adaptation of the high-pH stress environment in L. vannamei. These findings provide the first insight into the molecular and immune basis of L. vannamei in terms of high-pH environments, and the construction of a PPI network might improve our understanding in revealing the hub regulation-genes in response to abiotic stress in shrimp species and might be beneficial for further studies.
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Affiliation(s)
- Wen Huang
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- South China Sea Bio-Resource Exploitation and Utilization Collaborative Innovation Center, Guangzhou, China
| | - Hongmei Li
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chuhang Cheng
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chunhua Ren
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- South China Sea Bio-Resource Exploitation and Utilization Collaborative Innovation Center, Guangzhou, China
| | - Ting Chen
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- South China Sea Bio-Resource Exploitation and Utilization Collaborative Innovation Center, Guangzhou, China
| | - Xiao Jiang
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- South China Sea Bio-Resource Exploitation and Utilization Collaborative Innovation Center, Guangzhou, China
| | | | - Peng Luo
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- * E-mail: (CH); (PL)
| | - Chaoqun Hu
- CAS Key Laboratory of Tropical Marine Bio-resources and Ecology (LMB), Guangdong Provincial Key Laboratory of Applied Marine Biology (LAMB), South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
- South China Sea Bio-Resource Exploitation and Utilization Collaborative Innovation Center, Guangzhou, China
- University of Chinese Academy of Sciences, Beijing, China
- * E-mail: (CH); (PL)
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