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Zhang X, Zhou S, Zhan Y, Mei Z, Qian A, Yuan Y, Zhang X, Fu T, Ma S, Li J. Molecular insights into the proteomic composition of porcine treated dentin matrix. Mater Today Bio 2024; 25:100990. [PMID: 38371466 PMCID: PMC10873736 DOI: 10.1016/j.mtbio.2024.100990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/23/2024] [Accepted: 02/03/2024] [Indexed: 02/20/2024] Open
Abstract
Background Human-treated dentin matrix (hTDM) has recently been studied as a natural extracellular matrix-based biomaterial for dentin pulp regeneration. However, porcine-treated dentin matrix (pTDM) is a potential alternative scaffold due to limited availability. However, there is a dearth of information regarding the protein composition and underlying molecular mechanisms of pTDM.Methods: hTDM and pTDM were fabricated using human and porcine teeth, respectively, and their morphological characteristics were examined using scanning electron microscopy. Stem cells derived from human exfoliated deciduous teeth (SHEDs) were isolated and characterized using flow cytometry and multilineage differentiation assays. SHEDs were cultured in three-dimensional environments with hTDM, pTDM, or biphasic hydroxyapatite/tricalcium phosphate. The expression of odontogenesis markers in SHEDs were assessed using real-time polymerase chain reaction and immunochemical staining. Subsequently, SHEDs/TDM and SHEDs/HA/TCP complexes were transplanted subcutaneously into nude mice. The protein composition of pTDM was analyzed using proteomics and compared to previously published data on hTDM.Results: pTDM and hTDM elicited comparable upregulation of odontogenesis-related genes and proteins in SHEDs. Furthermore, both demonstrated the capacity to stimulate root-related tissue regeneration in vivo. Proteomic analysis revealed the presence of 278 protein groups in pTDM, with collagens being the most abundant. Additionally, pTDM and hTDM shared 58 identical proteins, which may contribute to their similar abilities to induce odontogenesis. Conclusions Both hTDM and pTDM exhibit comparable capabilities in inducing odontogenesis, potentially owing to their distinctive bioactive molecular networks.
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Affiliation(s)
- Xiya Zhang
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Sha Zhou
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Yuzhen Zhan
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Ziyi Mei
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Aizhuo Qian
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Yu Yuan
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Xiaonan Zhang
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Tiwei Fu
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
| | - Shiyong Ma
- Basic Medicine Research and Innovation Center for Novel Target and Therapeutic Intervention, The Ministry of Education, Institute of Life Sciences, Chongqing Medical University, Chongqing, China
| | - Jie Li
- College of Stomatology, Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing Medical University, Chongqing, China
- Chongqing Municipal Key Laboratory of Oral Biomedical Engineering of Higher Education, Chongqing Medical University, Chongqing, China
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Kochuthakidiyel Suresh P, Sekar G, Mallady K, Wan Ab Rahman WS, Shima Shahidan WN, Venkatesan G. The Identification of Potential Drugs for Dengue Hemorrhagic Fever: Network-Based Drug Reprofiling Study. JMIR BIOINFORMATICS AND BIOTECHNOLOGY 2023; 4:e37306. [PMID: 38935956 PMCID: PMC11135182 DOI: 10.2196/37306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 09/30/2022] [Accepted: 03/28/2023] [Indexed: 06/29/2024]
Abstract
BACKGROUND Dengue fever can progress to dengue hemorrhagic fever (DHF), a more serious and occasionally fatal form of the disease. Indicators of serious disease arise about the time the fever begins to reduce (typically 3 to 7 days following symptom onset). There are currently no effective antivirals available. Drug repurposing is an emerging drug discovery process for rapidly developing effective DHF therapies. Through network pharmacology modeling, several US Food and Drug Administration (FDA)-approved medications have already been researched for various viral outbreaks. OBJECTIVE We aimed to identify potentially repurposable drugs for DHF among existing FDA-approved drugs for viral attacks, symptoms of viral fevers, and DHF. METHODS Using target identification databases (GeneCards and DrugBank), we identified human-DHF virus interacting genes and drug targets against these genes. We determined hub genes and potential drugs with a network-based analysis. We performed functional enrichment and network analyses to identify pathways, protein-protein interactions, tissues where the gene expression was high, and disease-gene associations. RESULTS Analyzing virus-host interactions and therapeutic targets in the human genome network revealed 45 repurposable medicines. Hub network analysis of host-virus-drug associations suggested that aspirin, captopril, and rilonacept might efficiently treat DHF. Gene enrichment analysis supported these findings. According to a Mayo Clinic report, using aspirin in the treatment of dengue fever may increase the risk of bleeding complications, but several studies from around the world suggest that thrombosis is associated with DHF. The human interactome contains the genes prostaglandin-endoperoxide synthase 2 (PTGS2), angiotensin converting enzyme (ACE), and coagulation factor II, thrombin (F2), which have been documented to have a role in the pathogenesis of disease progression in DHF, and our analysis of most of the drugs targeting these genes showed that the hub gene module (human-virus-drug) was highly enriched in tissues associated with the immune system (P=7.29 × 10-24) and human umbilical vein endothelial cells (P=1.83 × 10-20); this group of tissues acts as an anticoagulant barrier between the vessel walls and blood. Kegg analysis showed an association with genes linked to cancer (P=1.13 × 10-14) and the advanced glycation end products-receptor for advanced glycation end products signaling pathway in diabetic complications (P=3.52 × 10-14), which indicates that DHF patients with diabetes and cancer are at risk of higher pathogenicity. Thus, gene-targeting medications may play a significant part in limiting or worsening the condition of DHF patients. CONCLUSIONS Aspirin is not usually prescribed for dengue fever because of bleeding complications, but it has been reported that using aspirin in lower doses is beneficial in the management of diseases with thrombosis. Drug repurposing is an emerging field in which clinical validation and dosage identification are required before the drug is prescribed. Further retrospective and collaborative international trials are essential for understanding the pathogenesis of this condition.
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Affiliation(s)
| | - Gnanasoundari Sekar
- Department of Biotechnology, Bharathidasan Institute of Technology Campus, Anna University, Tiruchirappalli, India
| | - Kavya Mallady
- Centre for Toxicology and Developmental Research, Sri Ramachandra Institute of Higher Education and Research, Chennai, India
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3
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Zhong J, Xiang D, Ma X. Prediction and analysis of osteoarthritis hub genes with bioinformatics. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:66. [PMID: 36819525 PMCID: PMC9929772 DOI: 10.21037/atm-22-6450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/10/2023] [Indexed: 01/18/2023]
Abstract
Background Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA. Methods The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language "limma" function package under the threshold of log2[fold change (FC)] ≥2 and a P value <0.05. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of the target genes were enriched and analyzed using the database for annotation, visualization, and integrated discovery (DAVID), and a protein-protein interaction (PPI) network was further constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database. The coexpression relationship of the genes in the module was visualized and screened with Cytoscape. Results A total of 27 DEGs were identified, including 9 downregulated genes and 18 upregulated genes. GO signal pathway enrichment analysis showed involvement in hypoxic response, fibrous collagen trimer, and extracellular matrix structural components. KEGG analysis demonstrated associations with protein digestion and absorption, extracellular matrix receptor interaction, and the peroxisome proliferator-activated receptor signal pathway, among several other pathways. A PPI network was obtained through STRING analysis, and the results were imported into Cytoscape software. The 27 DEGs were sequenced by the cytoHubba plug-in by various calculation methods, and 5 hub genes (COL1A1, COL1A2, POSTN, BMP1, and MMP13) were finally selected. These genes were analyzed by PPI again and annotated with GO and KEGG in different colors. Conclusions Bioinformatics technology effectively identified differential genes in the knee cartilage tissue of healthy controls and patients with OA, providing opportunities to further explore the mechanism and treatment of OA on a transcriptional level.
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Affiliation(s)
- Junqing Zhong
- Integration of Traditional Chinese and Western Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Ding Xiang
- Department of Rehabilitation, Tianjin Hospital, Tianjin, China
| | - Xinlong Ma
- Department of Orthopedics, Tianjin Hospital, Tianjin, China
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Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease. Genes (Basel) 2022; 13:genes13050764. [PMID: 35627149 PMCID: PMC9141211 DOI: 10.3390/genes13050764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/04/2022] [Accepted: 04/13/2022] [Indexed: 02/04/2023] Open
Abstract
The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.
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Zhu Z, Wang W, Lin F, Jordan T, Li G, Silverman S, Qiu S, Joy AA, Chen C, Hockley DL, Zhang X, Zhou Q, Postovit LM, Zhang X, Hou Y, Mackey JR, Li B, Wong GKS. Genome profiles of pathologist-defined cell clusters by multiregional LCM and G&T-seq in one triple-negative breast cancer patient. CELL REPORTS MEDICINE 2021; 2:100404. [PMID: 34755126 PMCID: PMC8561166 DOI: 10.1016/j.xcrm.2021.100404] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 03/30/2021] [Accepted: 08/25/2021] [Indexed: 02/06/2023]
Abstract
Pathological examination is the gold standard for cancer diagnosis, and breast tumor cells are often found in clusters. We report a case study on one triple-negative breast cancer (TNBC) patient, analyzing tumor development, metastasis, and prognosis with simultaneous DNA and RNA sequencing of pathologist-defined cell clusters from multiregional frozen sections. The cell clusters are isolated by laser capture microdissection (LCM) from primary tumor tissue, lymphatic vessels, and axillary lymph nodes. Data are reported for a total of 97 cell clusters. A combination of tumor cell-cluster clonality and phylogeny reveals 3 evolutionarily distinct pathways for this patient, each associated with a unique mRNA signature, and each correlated with disparate survival outcomes. Hub gene analysis indicates that extensive downregulation of ribosomal protein mRNA is a potential marker of poor prognosis in breast cancer. Pathologically diverse cell clusters share genomic and transcriptomic profiles Transcriptome-defined clones are more complex than genome-defined clones Three distinct pathways were inferred, each with disparate survival outcomes Lower expression of ribosomal proteins may be an indicator of poor prognosis
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Affiliation(s)
- Zhongyi Zhu
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiwei Wang
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada.,Geneis, Bldg A, 5 Guangshun North Street, Beijing 100102, China
| | - Feng Lin
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Tracy Jordan
- Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada
| | - Guibo Li
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Sveta Silverman
- Department of Pathology and Laboratory Medicine, University of Alberta, Edmonton, AB T6G 2H7, Canada
| | - Si Qiu
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Anil Abraham Joy
- Division of Medical Oncology, Department of Oncology, University of Alberta, Cross Cancer Institute, Edmonton, AB T6G 1Z2, Canada
| | - Chao Chen
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Deanna L Hockley
- Division of Medical Oncology, Department of Oncology, University of Alberta, Cross Cancer Institute, Edmonton, AB T6G 1Z2, Canada
| | - Xi Zhang
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Qing Zhou
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Lynne M Postovit
- Department of Oncology, University of Alberta, Edmonton, AB T6G 2H7, Canada
| | - Xiuqing Zhang
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Yong Hou
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - John R Mackey
- Division of Medical Oncology, Department of Oncology, University of Alberta, Cross Cancer Institute, Edmonton, AB T6G 1Z2, Canada
| | - Bo Li
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Gane Ka-Shu Wong
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China.,Department of Medicine, University of Alberta, Edmonton, AB T6G 2E1, Canada.,Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada
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6
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PD_BiBIM: Biclustering-based biomarker identification in ESCC microarray data. J Biosci 2021. [DOI: 10.1007/s12038-021-00171-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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7
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Ryan FJ, Carr JM, Furtado JM, Ma Y, Ashander LM, Simões M, Oliver GF, Granado GB, Dawson AC, Michael MZ, Appukuttan B, Lynn DJ, Smith JR. Zika Virus Infection of Human Iris Pigment Epithelial Cells. Front Immunol 2021; 12:644153. [PMID: 33968035 PMCID: PMC8100333 DOI: 10.3389/fimmu.2021.644153] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Accepted: 03/02/2021] [Indexed: 12/13/2022] Open
Abstract
During recent Zika epidemics, adults infected with Zika virus (ZIKV) have developed organ-specific inflammatory complications. The most serious Zika-associated inflammatory eye disease is uveitis, which is commonly anterior in type, affecting both eyes and responding to corticosteroid eye drops. Mechanisms of Zika-associated anterior uveitis are unknown, but ZIKV has been identified in the aqueous humor of affected individuals. The iris pigment epithelium is a target cell population in viral anterior uveitis, and it acts to maintain immune privilege within the anterior eye. Interactions between ZIKV and human iris pigment epithelial cells were investigated with infectivity assays and RNA-sequencing. Primary cell isolates were prepared from eyes of 20 cadaveric donors, and infected for 24 hours with PRVABC59 strain ZIKV or incubated uninfected as control. Cytoimmunofluorescence, RT-qPCR on total cellular RNA, and focus-forming assays of culture supernatant showed cell isolates were permissive to infection, and supported replication and release of infectious ZIKV. To explore molecular responses of cell isolates to ZIKV infection at the whole transcriptome level, RNA was sequenced on the Illumina NextSeq 500 platform, and results were aligned to the human GRCh38 genome. Multidimensional scaling showed clear separation between transcriptomes of infected and uninfected cell isolates. Differential expression analysis indicated a vigorous molecular response of the cell to ZIKV: 7,935 genes were differentially expressed between ZIKV-infected and uninfected cells (FDR < 0.05), and 99% of 613 genes that changed at least two-fold were up-regulated. Reactome and KEGG pathway and Gene Ontology enrichment analyses indicated strong activation of viral recognition and defense, in addition to biosynthesis processes. A CHAT network included 6275 molecular nodes and 24 contextual hubs in the cell response to ZIKV infection. Receptor-interacting serine/threonine kinase 1 (RIPK1) was the most significantly connected contextual hub. Correlation of gene expression with read counts assigned to the ZIKV genome identified a negative correlation between interferon signaling and viral load across isolates. This work represents the first investigation of mechanisms of Zika-associated anterior uveitis using an in vitro human cell model. The results suggest the iris pigment epithelium mounts a molecular response that limits intraocular pathology in most individuals.
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Affiliation(s)
- Feargal J Ryan
- Precision Medicine Theme, South Australian Health & Medical Research Institute, Adelaide, SA, Australia
| | - Jillian M Carr
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - João M Furtado
- Ophthalmology Division, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Yuefang Ma
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - Liam M Ashander
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - Milena Simões
- Ophthalmology Division, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Genevieve F Oliver
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - G Bracho Granado
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - Abby C Dawson
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - Michael Z Michael
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - Binoy Appukuttan
- Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - David J Lynn
- Precision Medicine Theme, South Australian Health & Medical Research Institute, Adelaide, SA, Australia.,Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
| | - Justine R Smith
- Precision Medicine Theme, South Australian Health & Medical Research Institute, Adelaide, SA, Australia.,Flinders University College of Medicine and Public Health, Bedford Park, SA, Australia
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8
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Malik G, Agarwal T, Raj U, Sundararajan VS, Bandapalli OR, Suravajhala P. Hypothetical Proteins as Predecessors of Long Non-coding RNAs. Curr Genomics 2020; 21:531-535. [PMID: 33214769 PMCID: PMC7604745 DOI: 10.2174/1389202921999200611155418] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 04/28/2020] [Accepted: 05/16/2020] [Indexed: 02/07/2023] Open
Abstract
Hypothetical Proteins [HP] are the transcripts predicted to be expressed in an organism, but no evidence of it exists in gene banks. On the other hand, long non-coding RNAs [lncRNAs] are the transcripts that might be present in the 5’ UTR or intergenic regions of the genes whose lengths are above 200 bases. With the known unknown [KU] regions in the genomes rapidly existing in gene banks, there is a need to understand the role of open reading frames in the context of annotation. In this commentary, we emphasize that HPs could indeed be the predecessors of lncRNAs.
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Affiliation(s)
- Girik Malik
- 1Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave., Boston, MA02115, USA; 2Bioclues.org, Kukatpally, Hyderabad, 500072, India; 3Labrynthe Pvt. Ltd., New Delhi, India; 4NIIT University, NH8, Delhi- Jaipur Highway, District Alwar, Neemrana, Rajasthan 301705, India; 5Hopp Children's Cancer Center [KiTZ], Heidelberg, Germany; 6Division of Pediatric Neuro Oncology, German Cancer Research Center [DKFZ], German Cancer Consortium [DKTK], Heidelberg, Germany; 7Heidelberg University, Medical Faculty, Heidelberg, Germany; 8Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Statue Circle, Jaipur302021, RJ, India
| | - Tanu Agarwal
- 1Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave., Boston, MA02115, USA; 2Bioclues.org, Kukatpally, Hyderabad, 500072, India; 3Labrynthe Pvt. Ltd., New Delhi, India; 4NIIT University, NH8, Delhi- Jaipur Highway, District Alwar, Neemrana, Rajasthan 301705, India; 5Hopp Children's Cancer Center [KiTZ], Heidelberg, Germany; 6Division of Pediatric Neuro Oncology, German Cancer Research Center [DKFZ], German Cancer Consortium [DKTK], Heidelberg, Germany; 7Heidelberg University, Medical Faculty, Heidelberg, Germany; 8Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Statue Circle, Jaipur302021, RJ, India
| | - Utkarsh Raj
- 1Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave., Boston, MA02115, USA; 2Bioclues.org, Kukatpally, Hyderabad, 500072, India; 3Labrynthe Pvt. Ltd., New Delhi, India; 4NIIT University, NH8, Delhi- Jaipur Highway, District Alwar, Neemrana, Rajasthan 301705, India; 5Hopp Children's Cancer Center [KiTZ], Heidelberg, Germany; 6Division of Pediatric Neuro Oncology, German Cancer Research Center [DKFZ], German Cancer Consortium [DKTK], Heidelberg, Germany; 7Heidelberg University, Medical Faculty, Heidelberg, Germany; 8Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Statue Circle, Jaipur302021, RJ, India
| | - Vijayaraghava Seshadri Sundararajan
- 1Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave., Boston, MA02115, USA; 2Bioclues.org, Kukatpally, Hyderabad, 500072, India; 3Labrynthe Pvt. Ltd., New Delhi, India; 4NIIT University, NH8, Delhi- Jaipur Highway, District Alwar, Neemrana, Rajasthan 301705, India; 5Hopp Children's Cancer Center [KiTZ], Heidelberg, Germany; 6Division of Pediatric Neuro Oncology, German Cancer Research Center [DKFZ], German Cancer Consortium [DKTK], Heidelberg, Germany; 7Heidelberg University, Medical Faculty, Heidelberg, Germany; 8Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Statue Circle, Jaipur302021, RJ, India
| | - Obul Reddy Bandapalli
- 1Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave., Boston, MA02115, USA; 2Bioclues.org, Kukatpally, Hyderabad, 500072, India; 3Labrynthe Pvt. Ltd., New Delhi, India; 4NIIT University, NH8, Delhi- Jaipur Highway, District Alwar, Neemrana, Rajasthan 301705, India; 5Hopp Children's Cancer Center [KiTZ], Heidelberg, Germany; 6Division of Pediatric Neuro Oncology, German Cancer Research Center [DKFZ], German Cancer Consortium [DKTK], Heidelberg, Germany; 7Heidelberg University, Medical Faculty, Heidelberg, Germany; 8Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Statue Circle, Jaipur302021, RJ, India
| | - Prashanth Suravajhala
- 1Khoury College of Computer Sciences, Northeastern University, 360 Huntington Ave., Boston, MA02115, USA; 2Bioclues.org, Kukatpally, Hyderabad, 500072, India; 3Labrynthe Pvt. Ltd., New Delhi, India; 4NIIT University, NH8, Delhi- Jaipur Highway, District Alwar, Neemrana, Rajasthan 301705, India; 5Hopp Children's Cancer Center [KiTZ], Heidelberg, Germany; 6Division of Pediatric Neuro Oncology, German Cancer Research Center [DKFZ], German Cancer Consortium [DKTK], Heidelberg, Germany; 7Heidelberg University, Medical Faculty, Heidelberg, Germany; 8Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Statue Circle, Jaipur302021, RJ, India
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9
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Oral lichen planus interactome reveals CXCR4 and CXCL12 as candidate therapeutic targets. Sci Rep 2020; 10:5454. [PMID: 32214134 PMCID: PMC7096434 DOI: 10.1038/s41598-020-62258-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Accepted: 03/12/2020] [Indexed: 01/03/2023] Open
Abstract
Today, we face difficulty in generating new hypotheses and understanding oral lichen planus due to the large amount of biomedical information available. In this research, we have used an integrated bioinformatics approach assimilating information from data mining, gene ontologies, protein–protein interaction and network analysis to predict candidate genes related to oral lichen planus. A detailed pathway analysis led us to propose two promising therapeutic targets: the stromal cell derived factor 1 (CXCL12) and the C-X-C type 4 chemokine receptor (CXCR4). We further validated our predictions and found that CXCR4 was upregulated in all oral lichen planus tissue samples. Our bioinformatics data cumulatively support the pathological role of chemokines and chemokine receptors in oral lichen planus. From a clinical perspective, we suggest a drug (plerixafor) and two therapeutic targets for future research.
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Mao Y, Wang Y, Dong L, Zhang Y, Zhang Y, Wang C, Zhang Q, Yang S, Cao L, Zhang X, Li X, Fu Z. Hypoxic exosomes facilitate angiogenesis and metastasis in esophageal squamous cell carcinoma through altering the phenotype and transcriptome of endothelial cells. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2019; 38:389. [PMID: 31488217 PMCID: PMC6727585 DOI: 10.1186/s13046-019-1384-8] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 08/15/2019] [Indexed: 02/06/2023]
Abstract
Background In cancer progression, hypoxia, or low oxygen tension, is a major regulator of tumor aggressiveness and metastasis. However, how cancer cells adapt to the hypoxia and communicate with other mesenchymal cells in microenvironment during tumor development remains to be elucidated. Here, we investigated the involvement of exosomes in modulating angiogenesis and enhancing metastasis in esophageal squamous cell carcinoma (ESCC). Methods Differential centrifugation, transmission electron microscopy and nanoparticle tracking analysis were used to isolate and characterize exosomes. Colony formation and transwell assay were performed to assess the proliferation, migration and invasion of human umbilical vein endothelial cells (HUVECs). The tube formation assay and matrigel plug assay were used to evaluate the vascular formation ability of HUVECs in vitro and in vivo respectively. An in vivo nude mice model was established to detect the regulatory role of exosomes in ESCC progression. Microarray analysis was performed to analyze the transcriptome profiles in HUVECs. Results Exosomes derived from ESCC cells cultured under hypoxia played a better role in promoting proliferation, migration, invasion and tube formation of HUVECs in vitro and in vivo than exosomes from ESCC cells cultured under normoxia. Moreover, hypoxic exosomes significantly enhanced the tumor growth and lung metastasis compared with normoxic exosomes in nude mice models. Interestingly, endothelial cells were programmed by hypoxic and normoxic exosomes from ESCC cells which altered the transcriptome profile of HUVECs. Conclusions Taken together, our data identified an angiogenic role of exosomes from ESCC cells which shed light on the further application of exosomes as valuable therapeutic target for ESCC. Electronic supplementary material The online version of this article (10.1186/s13046-019-1384-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yu Mao
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China.
| | - Yimin Wang
- Department of General Surgery, First Hospital of Qinhuangdao, Hebei Medical University, Qinhuangdao, China
| | - Lixin Dong
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Yunjie Zhang
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Yanqiu Zhang
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Chao Wang
- Department of Thoracic Surgery, First Hospital of Qinhuangdao, Qinhuangdao, China
| | - Qiang Zhang
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Sen Yang
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Liyan Cao
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Xinyuan Zhang
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Xin Li
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Zhanzhao Fu
- Department of Oncology, First Hospital of Qinhuangdao, Wenhua Road No. 258, Haigang District, Qinhuangdao, 066000, Hebei, China.
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11
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Cardona C, Benincore E, Pimentel N, Reyes LH, Patarroyo C, Rodríguez-López A, Martin-Rufian M, Barrera LA, Alméciga-Díaz CJ. Identification of the iduronate-2-sulfatase proteome in wild-type mouse brain. Heliyon 2019; 5:e01667. [PMID: 31193135 PMCID: PMC6517578 DOI: 10.1016/j.heliyon.2019.e01667] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 03/30/2019] [Accepted: 05/02/2019] [Indexed: 01/11/2023] Open
Abstract
Iduronate-2-sulfatase (IDS) is a lysosomal enzyme involved in the metabolism of the glycosaminoglycans heparan (HS) and dermatan (DS) sulfate. Mutations on IDS gene produce mucopolysaccharidosis II (MPS II), characterized by the lysosomal accumulation of HS and DS, leading to severe damage of the central nervous system (CNS) and other tissues. In this study, we used a neurochemistry and proteomic approaches to identify the brain distribution of IDS and its interacting proteins on wild-type mouse brain. IDS immunoreactivity showed a robust staining throughout the entire brain, suggesting an intracellular reactivity in nerve cells and astrocytes. By using affinity purification and mass spectrometry we identified 187 putative IDS partners-proteins, mainly hydrolases, cytoskeletal proteins, transporters, transferases, oxidoreductases, nucleic acid binding proteins, membrane traffic proteins, chaperons and enzyme modulators, among others. The interactions with some of these proteins were predicted by using bioinformatics tools and confirmed by co-immunoprecipitation analysis and Blue Native PAGE. In addition, we identified cytosolic IDS-complexes containing proteins from predicted highly connected nodes (hubs), with molecular functions including catalytic activity, redox balance, binding, transport, receptor activity and structural molecule activity. The proteins identified in this study would provide new insights about IDS physiological role into the CNS and its potential role in the brain-specific protein networks.
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Affiliation(s)
- Carolina Cardona
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Eliana Benincore
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Natalia Pimentel
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Luis H Reyes
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia.,Process and Product Design Group (GDPP), Department of Chemical Engineering, Universidad de los Andes, Bogotá, Colombia
| | - Camilo Patarroyo
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Alexander Rodríguez-López
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia.,Chemistry Department, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - M Martin-Rufian
- Central Services Research Support, Proteomics Unit, Universidad de Malaga, Spain
| | - Luis Alejandro Barrera
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia.,Clínica de Errores Innatos del Metabolismo, Hospital Universitario San Ignacio, Bogotá, Colombia
| | - Carlos J Alméciga-Díaz
- Institute for the Study of Inborn Errors of Metabolism, School of Sciences, Pontificia Universidad Javeriana, Bogotá, Colombia
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12
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Lie S, Rochet E, Segerdell E, Ma Y, Ashander LM, Shadforth AMA, Blenkinsop TA, Michael MZ, Appukuttan B, Wilmot B, Smith JR. Immunological Molecular Responses of Human Retinal Pigment Epithelial Cells to Infection With Toxoplasma gondii. Front Immunol 2019; 10:708. [PMID: 31118929 PMCID: PMC6506780 DOI: 10.3389/fimmu.2019.00708] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 03/15/2019] [Indexed: 11/13/2022] Open
Abstract
Ocular toxoplasmosis is the commonest clinical manifestation of infection with obligate intracellular parasite, Toxoplasma gondii. Active ocular toxoplasmosis is characterized by replication of T. gondii tachyzoites in the retina, with reactive inflammation. The multifunctional retinal pigment epithelium is a key target cell population for T. gondii. Since the global gene expression profile is germane to understanding molecular involvements of retinal pigment epithelial cells in ocular toxoplasmosis, we performed RNA-Sequencing (RNA-Seq) of human cells following infection with T. gondii tachyzoites. Primary cell isolates from eyes of cadaveric donors (n = 3), and the ARPE-19 human retinal pigment epithelial cell line, were infected for 24 h with GT-1 strain T. gondii tachyzoites (multiplicity of infection = 5) or incubated uninfected as control. Total and small RNA were extracted from cells and sequenced on the Illumina NextSeq 500 platform; results were aligned to the human hg19 reference sequence. Multidimensional scaling showed good separation between transcriptomes of infected and uninfected primary cell isolates, which were compared in edgeR software. This differential expression analysis revealed a sizeable response in the total RNA transcriptome-with significantly differentially expressed genes totaling 7,234 (28.9% of assigned transcripts)-but very limited changes in the small RNA transcriptome-totaling 30 (0.35% of assigned transcripts) and including 8 microRNA. Gene ontology and pathway enrichment analyses of differentially expressed total RNA in CAMERA software, identified a strong immunologic transcriptomic signature. We conducted RT-qPCR for 26 immune response-related protein-coding and long non-coding transcripts in epithelial cell isolates from different cadaveric donors (n = 3), extracted by a different isolation protocol but similarly infected with T. gondii, to confirm immunological activity of infected cells. For microRNA, increases in miR-146b and miR-212 were detected by RT-qPCR in 2 and 3 of these independent cell isolates. Biological network analysis in the InnateDB platform, including 735 annotated differentially expressed genes plus 2,046 first-order interactors, identified 10 contextural hubs and 5 subnetworks in the transcriptomic immune response of cells to T. gondii. Our observations provide a solid base for future studies of molecular and cellular interactions between T. gondii and the human retinal pigment epithelium to illuminate mechanisms of ocular toxoplasmosis.
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Affiliation(s)
- Shervi Lie
- Eye and Vision Health, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
| | - Elise Rochet
- Eye and Vision Health, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
| | - Erik Segerdell
- Department of Biostatistics, Oregon Health and Sciences University, Portland, OR, United States
| | - Yuefang Ma
- Eye and Vision Health, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
| | - Liam M. Ashander
- Eye and Vision Health, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
| | - Audra M. A. Shadforth
- Queensland Eye Institute, Brisbane, QLD, Australia
- School of Biomedical Science, Queensland University of Technology, Brisbane, QLD, Australia
| | - Timothy A. Blenkinsop
- Departments of Cell, Developmental and Regenerative Biology, and Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Michael Z. Michael
- Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
| | - Binoy Appukuttan
- Eye and Vision Health, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
- Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
| | - Beth Wilmot
- Department of Biostatistics, Oregon Health and Sciences University, Portland, OR, United States
| | - Justine R. Smith
- Eye and Vision Health, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
- Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Adelaide, SA, Australia
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13
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Lu Y, Wang X, Dong H, Wang X, Yang P, Han L, Wang Y, Zheng Z, Zhang W, Zhang L. Bioinformatics analysis of microRNA expression between patients with and without latent tuberculosis infections. Exp Ther Med 2019; 17:3977-3988. [PMID: 30988779 PMCID: PMC6447890 DOI: 10.3892/etm.2019.7424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 03/06/2019] [Indexed: 12/14/2022] Open
Abstract
Tuberculosis (TB) is a globally prevalent infectious disease. The mechanisms of latent TB infection (LTBI) remain to be fully elucidated and may provide novel approaches for diagnosis. As therapeutic targets and molecular diagnostic markers, microRNAs (miRs) have been studied and utilized in various diseases. In the present study, the differentially expressed miRs (DEMs) in LTBI were screened and analyzed to determine the underlying mechanisms and identify potential biomarkers, thereby contributing to the diagnosis of LTBI. The GSE25435 and GSE29190 datasets from Gene Expression Omnibus were selected for analysis. The 2 datasets were analyzed individually using the Bioconductor package to screen the DEMs with specific cut-off criteria [P<0.01 and |log (fold change)|≥1]. Target gene prediction and interaction network construction were performed using Targetscan, the Search Tool for the Retrieval of Interacting Genes and Proteins and Cytoscape individually, and were merged using the latter tool. The hub genes were finally selected based on their degree of connectivity (DC). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the KEGG and GENCLIP. A total of 144 DEMs were identified from the 2 datasets. By exploring the overlapping miRs in the two datasets, Homo sapiens (hsa)-miR-29a and hsa-miR-15b were identified to be decreased, while hsa-miR-576-5p, hsa-miR-500 and hsa-miR-155 were identified to be upregulated. hsa-miR-500a-3p and hsa-miR-29a-3p, as well as 4 genes, namely cell division cycle (CDC)42, actin α1, skeletal muscle (ACTA1), phosphatase and tensin homolog (PTEN) and fos proto-oncogene (FOS), were selected as the key factors in this regulatory network. A total of 9 signaling pathways, including phosphoinositide-3 kinase (PI3K)/AKT and 11 biological processes, were identified to be associated with LTBI. In conclusion, the present analysis identified hsa-miR-500a-3p and hsa-miR-29a-3p, as well as CDC42, ACTA1, PTEN and FOS, as the most promising biomarkers and therapeutic candidates for LTBI. The PI3K/AKT signaling pathway is the key signaling pathway implicated in LTBI, and an in-depth investigation of the efficiency of PI3K/AKT signaling inhibitors may be used to prevent a chronic state of infection in LTBI.
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Affiliation(s)
- Yang Lu
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Xinmin Wang
- Department of Urinary Surgery, The First Affiliated Hospital, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Hongchang Dong
- Department of Biochemistry, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Xiaofang Wang
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Pu Yang
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Ling Han
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Yingzi Wang
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Zhihong Zheng
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Wanjiang Zhang
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
| | - Le Zhang
- Department of Pathophysiology, The Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Medical College of Shihezi University, Shihezi, Xinjiang 832000, P.R. China
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14
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Tiwari P, Saxena A, Gupta N, Medicherla KM, Suravajhala P, Mathur SK. Systems Genomics of Thigh Adipose Tissue From Asian Indian Type-2 Diabetics Revealed Distinct Protein Interaction Hubs. Front Genet 2019; 9:679. [PMID: 30671081 PMCID: PMC6331691 DOI: 10.3389/fgene.2018.00679] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 12/07/2018] [Indexed: 12/13/2022] Open
Abstract
We performed a systematic analysis of genes implicated in thigh subcutaneous adipose tissue of Asian Indian Type 2 Diabetes Mellitus (AIT2DM) and created a phenome-interactome network. This analysis was performed on 60 subjects specific to limb thigh fat by integrating phenotypic traits and similarity scores associated with AIT2DM. Using a phenotypic attribute, a contextual neighbor was identified across all the traits, viz. body mass index (BMI) statistics, adipocyte size, lipid parameters, homeostatic model assessment- insulin resistance (HOMA-IR), HOMA-ß. In this work, we have attempted to characterize transcription signatures using the phenome-interactome maps where each of the traits under study including the intermediary phenotypes has a distinct set of genes forming the hubs. Furthermore, we have identified various clinical, biochemical, and radiological parameters which show significant correlation with distinct hubs. We observed a number of novel pathways and genes including those that are non-coding RNAs implicated in AIT2DM.We showed that they appear to be associated with pathways, viz. tyrosine kinase JAK2, NOTCH thereby recruiting signaling molecules such as STAT5 and Src family kinases on the cell surface regulated them and our analyses comprising significant hubs suggest that thigh subcutaneous adipose tissue plays a role in pathophysiology of AIT2DM.
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Affiliation(s)
- Pradeep Tiwari
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur, India.,Department of Endocrinology, Sawai Man Singh Medical College and Hospital, Jaipur, India.,Department of Chemistry, School of Basic Sciences, Manipal University Jaipur, Jaipur, India
| | - Aditya Saxena
- Department of Biotechnology, Institute of Applied Sciences and Humanities, GLA University, Mathura, India
| | - Nidhi Gupta
- Department of Biotechnology, The IIS University, Jaipur, India
| | - Krishna Mohan Medicherla
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur, India
| | - Prashanth Suravajhala
- Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur, India
| | - Sandeep Kumar Mathur
- Department of Chemistry, School of Basic Sciences, Manipal University Jaipur, Jaipur, India
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15
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Agrin has a pathological role in the progression of oral cancer. Br J Cancer 2018; 118:1628-1638. [PMID: 29872149 PMCID: PMC6008410 DOI: 10.1038/s41416-018-0135-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 04/26/2018] [Accepted: 05/09/2018] [Indexed: 12/27/2022] Open
Abstract
Background The extracellular matrix modulates the hallmarks of cancer. Here we examined the role of agrin—a member of this matrix—in progression of oral squamous cell carcinoma (OSCC). Methods We evaluated the immunohistochemical expression of agrin in OSCC and dysplasias. Benign lesions were used as control. In subsequent experiments, we investigated whether the silencing of agrin interferes with tumour expansion both in vitro as well as in vivo. To gain insights into the role of agrin, we identified its protein network (interactome) using mass spectrometry-based proteomics and bioinformatics. Finally, we evaluated the clinical relevance of agrin interactome. Results Agrin was elevated in malignant and premalignant lesions. Further, we show that agrin silencing interferes with cancer cell motility, proliferation, invasion, colony and tumour spheroid formation, and it also reduces the phosphorylation of FAK, ERK and cyclin D1 proteins in OSCC cells. In orthotopic model, agrin silencing reduces tumour aggressiveness, like vascular and neural invasion. From a clinical perspective, agrin contextual hubs predict a poor clinical prognosis related with overall survival. Conclusions Altogether, our results demonstrate that agrin is a histological marker for the progression of oral cancer and is a strong therapeutic target candidate for both premalignant and OSCC lesions.
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16
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Dong H, Zhang S, Wei Y, Liu C, Wang N, Zhang P, Zhu J, Huang J. Bioinformatic analysis of differential expression and core GENEs in breast cancer. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2018; 11:1146-1156. [PMID: 31938209 PMCID: PMC6958129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 12/22/2017] [Indexed: 06/10/2023]
Abstract
Breast cancer (BRCA) is one of the most common malignancies in women. The gene expression profile of GSE103512 from the GEO database was downloaded in order to find key genes involved in the occurrence and development of BRCA. 75 samples, including 65 cancer and 10 normal samples, were included in this analysis. Differentially expressed genes (DEGs) between BRCA patients and health people were chosen using R tool. We next performed gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) was utilized to visualize protein-protein interaction (PPI) of these DEGs. The related genes and medicines specific to hub genes were predicted by CBioportal. We screened a total of 357 DEGs including 77 up-regulated and 280 down-regulated. A series of BRCA related GO terms and pathways were identified by analysis of these DEGs. Insulin-like growth factor 1 (IGF1); epidermal growth factor receptor (EGFR); v-jun avian sarcoma virus 17 oncogene homolog (JUN) and Estrogen Receptor 1 (ESR1) of the DEGs were screened by construction of the PPI network and the degree of connectivity. IGF1 and ESR1 were finally selected as potential hub genes and treatment targets of BRCA. In conclusion, this bioinformatics analysis demonstrated that DEGs and hub genes, such as IGF1, might regulate the development of gastric cancer. These DEGs could be used as new biomarkers for diagnosis and to guide the combination medicine of BRCA.
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Affiliation(s)
- Hongchang Dong
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of MedicineShihezi, Xinjiang, China
| | - Shuai Zhang
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of MedicineShihezi, Xinjiang, China
| | - Yu Wei
- The First Affiliated Hospital of Medical College of Shihezi UniversityShihezi, Xinjiang, China
| | - Chunyan Liu
- The First Affiliated Hospital of Medical College of Shihezi UniversityShihezi, Xinjiang, China
| | - Na Wang
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of MedicineShihezi, Xinjiang, China
| | - Pan Zhang
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of MedicineShihezi, Xinjiang, China
| | - Jingling Zhu
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of MedicineShihezi, Xinjiang, China
| | - Jin Huang
- The Key Laboratory of Xinjiang Endemic & Ethnic Diseases and Department of Biochemistry, Shihezi University School of MedicineShihezi, Xinjiang, China
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17
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Thakur Z, Dharra R, Saini V, Kumar A, Mehta PK. Insights from the protein-protein interaction network analysis of Mycobacterium tuberculosis toxin-antitoxin systems. Bioinformation 2017; 13:380-387. [PMID: 29225431 PMCID: PMC5712783 DOI: 10.6026/97320630013380] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 12/11/2017] [Accepted: 12/11/2017] [Indexed: 12/19/2022] Open
Abstract
Protein-protein interaction (PPI) network analysis is a powerful strategy to understand M. tuberculosis (Mtb) system level physiology in the identification of hub proteins. In the present study, the PPI network of 79 Mtb toxin-antitoxin (TA) systems comprising of 167 nodes and 234 edges was investigated. The topological properties of PPI network were examined by 'Network analyzer' a cytoscape plugin app and STRING database. The key enriched biological processes and the molecular functions of Mtb TA systems were analyzed by STRING. Manual curation of the PPI data identified four proteins (i.e. Rv2762c, VapB14, VapB42 and VapC42) to possess the highest number of interacting partners. The top 15% hub proteins were identified in the PPI network by employing two statistical measures, i.e. betweenness and radiality by employing cytohubba. Insights gained from the molecular protein models of VapC9 and VapC10 are also documented.
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Affiliation(s)
- Zoozeal Thakur
- Centre for Biotechnology, Maharshi Dayanand University (MDU), Rohtak-124001 (Haryana), India
| | - Renu Dharra
- Centre for Biotechnology, Maharshi Dayanand University (MDU), Rohtak-124001 (Haryana), India
| | - Vandana Saini
- Toxicology & Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University (MDU), Rohtak-124001 (Haryana), India
| | - Ajit Kumar
- Toxicology & Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University (MDU), Rohtak-124001 (Haryana), India
| | - Promod K. Mehta
- Centre for Biotechnology, Maharshi Dayanand University (MDU), Rohtak-124001 (Haryana), India
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18
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Muetze T, Goenawan IH, Wiencko HL, Bernal-Llinares M, Bryan K, Lynn DJ. Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks. F1000Res 2016; 5:1745. [PMID: 27853512 PMCID: PMC5105880 DOI: 10.12688/f1000research.9118.2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/26/2016] [Indexed: 01/21/2023] Open
Abstract
Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such
contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (
http://apps.cytoscape.org/apps/chat).
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Affiliation(s)
- Tanja Muetze
- EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia
| | - Ivan H Goenawan
- EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia
| | - Heather L Wiencko
- Animal and Bioscience Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Meath, Ireland
| | - Manuel Bernal-Llinares
- EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia
| | - Kenneth Bryan
- EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia
| | - David J Lynn
- EMBL Australia Biomedical Informatics Group, Infection & Immunity Theme, South Australian Medical and Health Research Institute, Adelaide, Australia; School of Medicine, Flinders University, Bedford Park, Australia
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