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Aggarwal S, Rosenblum C, Gould M, Ziman S, Barshir R, Zelig O, Guan-Golan Y, Iny-Stein T, Safran M, Pietrokovski S, Lancet D. Expanding and Enriching the LncRNA Gene-Disease Landscape Using the GeneCaRNA Database. Biomedicines 2024; 12:1305. [PMID: 38927512 PMCID: PMC11202217 DOI: 10.3390/biomedicines12061305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/04/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
The GeneCaRNA human gene database is a member of the GeneCards Suite. It presents ~280,000 human non-coding RNA genes, identified algorithmically from ~690,000 RNAcentral transcripts. This expands by ~tenfold the ncRNA gene count relative to other sources. GeneCaRNA thus contains ~120,000 long non-coding RNAs (LncRNAs, >200 bases long), including ~100,000 novel genes. The latter have sparse functional information, a vast terra incognita for future research. LncRNA genes are uniformly represented on all nuclear chromosomes, with 10 genes on mitochondrial DNA. Data obtained from MalaCards, another GeneCards Suite member, finds 1547 genes associated with 1 to 50 diseases. About 15% of the associations portray experimental evidence, with cancers tending to be multigenic. Preliminary text mining within GeneCaRNA discovers interactions of lncRNA transcripts with target gene products, with 25% being ncRNAs and 75% proteins. GeneCaRNA has a biological pathways section, which at present shows 131 pathways for 38 lncRNA genes, a basis for future expansion. Finally, our GeneHancer database provides regulatory elements for ~110,000 lncRNA genes, offering pointers for co-regulated genes and genetic linkages from enhancers to diseases. We anticipate that the broad vista provided by GeneCaRNA will serve as an essential guide for further lncRNA research in disease decipherment.
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Affiliation(s)
- Shalini Aggarwal
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
| | - Chana Rosenblum
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
| | - Marshall Gould
- Department of Biological Sciences, University College London, Gower Street, London WC1E 6BT, UK
| | - Shahar Ziman
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
| | - Ruth Barshir
- TAD Center for AI and Data Science, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Ofer Zelig
- LifeMap Sciences Inc., Alameda, CA 94501, USA
| | | | - Tsippi Iny-Stein
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
| | - Marilyn Safran
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
| | - Shmuel Pietrokovski
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
| | - Doron Lancet
- Department of Molecular Genetics, Weizmann Institute of Science, Herzl 234, Rehovot 7610010, Israel (S.Z.)
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Feng Z, Sun N, Noor F, Sun P, Zhang H, Zhong J, Yin W, Fan K, Yang H, Zhang Z, Sun Y, Li H. Matrine Targets BTF3 to Inhibit the Growth of Canine Mammary Tumor Cells. Int J Mol Sci 2023; 25:540. [PMID: 38203709 PMCID: PMC10779273 DOI: 10.3390/ijms25010540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 12/21/2023] [Accepted: 12/28/2023] [Indexed: 01/12/2024] Open
Abstract
The canine mammary tumor model is more suitable for studying human breast cancer, and the safety concentrations of matrine and the biotin-labeled matrine probe were determined in canine primary mammary epithelial cells, and then selected canine mammary tumor cell lines CHMm and CHMp were incubated with matrine, and cell viability was detected by CCK-8. The biotin-labeled matrine probe was used to pull-down the targets of matrine in canine mammary tumor cells, and the targets were screened in combination with activity-based protein profiling (ABPP) and Genecards database, and verified by qPCR and western blot. The results showed that the maximum non-cytotoxic concentrations of matrine and biotin-labeled matrine probe in canine primary mammary epithelial cells were 250 μg/mL and 500 μg/mL, respectively. Matrine and biotin-labeled matrine probe had a proliferation inhibitory effect time-dependently on CHMm and CHMp cells within a safe concentration range, and induced autophagy in cells. Then BTF3 targets were obtained by applying ABPP and Genecards screening. Cellular thermal shift assay (CETSA) findings indicated that matrine could increase the heat stability of BTF3 protein. Pull-down employing biotin-labeled matrine probe with CHMm and CHMp cell lysates revealed that BTF3 protein was detected in the biotin-labeled matrine probe group and that BTF3 protein was significantly decreased by the addition of matrine. The qPCR and western blot findings of CHMm and CHMp cells treated with matrine revealed that matrine decreased the expression of the BTF3 gene and protein with the extension of the action time, and the impact was more substantial at the protein level, respectively.
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Affiliation(s)
- Zijian Feng
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Na Sun
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Fida Noor
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Panpan Sun
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Hua Zhang
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Jia Zhong
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Wei Yin
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Kuohai Fan
- Laboratory Animal Center, Shanxi Agricultural University, Jinzhong 030600, China; (K.F.); (Z.Z.)
| | - Huizhen Yang
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Zhenbiao Zhang
- Laboratory Animal Center, Shanxi Agricultural University, Jinzhong 030600, China; (K.F.); (Z.Z.)
| | - Yaogui Sun
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
| | - Hongquan Li
- Shanxi Key Laboratory for Modernization of TCVM, College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong 030600, China; (Z.F.); (N.S.); (F.N.); (P.S.); (H.Z.); (J.Z.); (W.Y.); (H.Y.); (Y.S.)
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Turley TN, Theis JL, Evans JM, Fogarty ZC, Gulati R, Hayes SN, Tweet MS, Olson TM. Identification of Rare Genetic Variants in Familial Spontaneous Coronary Artery Dissection and Evidence for Shared Biological Pathways. J Cardiovasc Dev Dis 2023; 10:393. [PMID: 37754822 PMCID: PMC10532385 DOI: 10.3390/jcdd10090393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 09/08/2023] [Indexed: 09/28/2023] Open
Abstract
Rare familial spontaneous coronary artery dissection (SCAD) kindreds implicate genetic disease predisposition and provide a unique opportunity for candidate gene discovery. Whole-genome sequencing was performed in fifteen probands with non-syndromic SCAD who had a relative with SCAD, eight of whom had a second relative with extra-coronary arteriopathy. Co-segregating variants and associated genes were prioritized by quantitative variant, gene, and disease-level metrics. Curated public databases were queried for functional relationships among encoded proteins. Fifty-four heterozygous coding variants in thirteen families co-segregated with disease and fulfilled primary filters of rarity, gene variation constraint, and predicted-deleterious protein effect. Secondary filters yielded 11 prioritized candidate genes in 12 families, with high arterial tissue expression (n = 7), high-confidence protein-level interactions with genes associated with SCAD previously (n = 10), and/or previous associations with connective tissue disorders and aortopathies (n = 3) or other vascular phenotypes in mice or humans (n = 11). High-confidence associations were identified among 10 familial SCAD candidate-gene-encoded proteins. A collagen-encoding gene was identified in five families, two with distinct variants in COL4A2. Familial SCAD is genetically heterogeneous, yet perturbations of extracellular matrix, cytoskeletal, and cell-cell adhesion proteins implicate common disease-susceptibility pathways. Incomplete penetrance and variable expression suggest genetic or environmental modifiers.
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Affiliation(s)
- Tamiel N. Turley
- Molecular Pharmacology and Experimental Therapeutics Track, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN 55905, USA;
- Cardiovascular Genetics Research Laboratory, Mayo Clinic, Rochester, MN 55905, USA;
| | - Jeanne L. Theis
- Cardiovascular Genetics Research Laboratory, Mayo Clinic, Rochester, MN 55905, USA;
| | - Jared M. Evans
- Department of Quantitative Health Sciences, Division of Computational Biology, Mayo Clinic, Rochester, MN 55905, USA; (J.M.E.); (Z.C.F.)
| | - Zachary C. Fogarty
- Department of Quantitative Health Sciences, Division of Computational Biology, Mayo Clinic, Rochester, MN 55905, USA; (J.M.E.); (Z.C.F.)
| | - Rajiv Gulati
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA; (R.G.); (S.N.H.); (M.S.T.)
| | - Sharonne N. Hayes
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA; (R.G.); (S.N.H.); (M.S.T.)
| | - Marysia S. Tweet
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA; (R.G.); (S.N.H.); (M.S.T.)
| | - Timothy M. Olson
- Cardiovascular Genetics Research Laboratory, Mayo Clinic, Rochester, MN 55905, USA;
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA; (R.G.); (S.N.H.); (M.S.T.)
- Department of Pediatric and Adolescent Medicine, Division of Pediatric Cardiology, Mayo Clinic, Rochester, MN 55905, USA
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Sun K, Zhang Y, Li Y, Yang P, Sun Y. Biochemical Targets and Molecular Mechanism of Matrine against Aging. Int J Mol Sci 2023; 24:10098. [PMID: 37373246 DOI: 10.3390/ijms241210098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 05/28/2023] [Accepted: 06/01/2023] [Indexed: 06/29/2023] Open
Abstract
The aim of this study is to explore the potential targets and molecular mechanism of matrine (MAT) against aging. Bioinformatic-based network pharmacology was used to investigate the aging-related targets and MAT-treated targets. A total of 193 potential genes of MAT against aging were obtained and then the top 10 key genes (cyclin D1, cyclin-dependent kinase 1, Cyclin A2, androgen receptor, Poly [ADP-ribose] polymerase-1 (PARP1), histone-lysine N-methyltransferase, albumin, mammalian target of rapamycin, histone deacetylase 2, and matrix metalloproteinase 9) were filtered by the molecular complex detection, maximal clique centrality (MMC) algorithm, and degree. The Metascape tool was used for analyzing biological processes and pathways of the top 10 key genes. The main biological processes were response to an inorganic substance and cellular response to chemical stress (including cellular response to oxidative stress). The major pathways were involved in cellular senescence and the cell cycle. After an analysis of major biological processes and pathways, it appears that PARP1/nicotinamide adenine dinucleotide (NAD+)-mediated cellular senescence may play an important role in MAT against aging. Molecular docking, molecular dynamics simulation, and in vivo study were used for further investigation. MAT could interact with the cavity of the PARP1 protein with the binding energy at -8.5 kcal/mol. Results from molecular dynamics simulations showed that the PARP1-MAT complex was more stable than PARP1 alone and that the binding-free energy of the PARP1-MAT complex was -15.962 kcal/mol. The in vivo study showed that MAT could significantly increase the NAD+ level of the liver of d-gal-induced aging mice. Therefore, MAT could interfere with aging through the PARP1/NAD+-mediated cellular senescence signaling pathway.
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Affiliation(s)
- Kaiyue Sun
- College of Veterinary Medicine, Shanxi Agricultural University, Taigu, Jinzhong 030801, China
| | - Yingzi Zhang
- College of Veterinary Medicine, Shanxi Agricultural University, Taigu, Jinzhong 030801, China
| | - Yingliang Li
- College of Veterinary Medicine, Shanxi Agricultural University, Taigu, Jinzhong 030801, China
| | - Pengyu Yang
- College of Veterinary Medicine, Shanxi Agricultural University, Taigu, Jinzhong 030801, China
| | - Yingting Sun
- College of Veterinary Medicine, Shanxi Agricultural University, Taigu, Jinzhong 030801, China
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Zhao Q, Pan W, Shi H, Qi F, Liu Y, Yang T, Si H, Si G. Network pharmacology and molecular docking analysis on the mechanism of Baihe Zhimu decoction in the treatment of postpartum depression. Medicine (Baltimore) 2022; 101:e29323. [PMID: 36316904 PMCID: PMC9622608 DOI: 10.1097/md.0000000000029323] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Baihe Zhimu decoction (BZD) has significant antidepressant properties and is widely used to treat mental diseases. However, the multitarget mechanism of BZD in postpartum depression (PPD) remains to be elucidated. Therefore, the aim of this study was to explore the molecular mechanisms of BDZ in treating PPD using network pharmacology and molecular docking. Active components and their target proteins were screened from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The PPD-related targets were obtained from the OMIM, CTD, and GeneCards databases. After overlap, the targets of BZD against PPD were collected. Protein-protein interaction (PPI) network and core target analyses were conducted using the STRING network platform and Cytoscape software. Moreover, molecular docking methods were used to confirm the high affinity between BZD and targets. Finally, the DAVID online tool was used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of overlapping targets. The TCMSP database showed that BZD contained 23 active ingredients in PPD. KEGG analysis showed that overlapping genes were mainly enriched in HIF-1, dopaminergic synapses, estrogen, and serotonergic synaptic signalling pathways. Combining the PPI network and KEGG enrichment analysis, we found that ESR1, MAOA, NR3C1, VEGFA, and mTOR were the key targets of PPD. In addition, molecular docking confirmed the high affinity between BZD and the PPD target. Verified by a network pharmacology approach based on data mining and molecular docking methods, the multi-target drug BZD may serve as a promising therapeutic candidate for PPD, but further in vivo/in vitro experiments are needed.
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Affiliation(s)
- Qiong Zhao
- School of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Wengu Pan
- Department of Kidney transplantation, The second hospital of Shandong University, Jinan, China
| | - Hongshuo Shi
- School of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Fanghua Qi
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Yuan Liu
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Tiantian Yang
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Hao Si
- Ai Kunwei Pharmaceutical Technology Co, Ltd, Shanghai, China
| | - Guomin Si
- School of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
- Department of Traditional Chinese Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
- *Correspondence: Guomin Si, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China (e-mail: )
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Li L, Lu S, Ma C. Anti-proliferative and pro-apoptotic effects of curcumin on skin cutaneous melanoma: Bioinformatics analysis and in vitro experimental studies. Front Genet 2022; 13:983943. [PMID: 36171883 PMCID: PMC9510772 DOI: 10.3389/fgene.2022.983943] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/23/2022] [Indexed: 11/26/2022] Open
Abstract
Objective: To reveal the potential mechanisms of curcumin for the treatment of skin cutaneous melanoma (SKCM) and its identify novel prognostic biomarkers. Methods: We searched the Cancer Genome Atlas and Traditional Chinese Medicine Systems Pharmacology database for the data on SKCM and curcumin. We conducted data analysis using R and online tools. The propagation and migration of SKCM cells were assessed with CCK-8 and scratch wound assays, respectively. We assessed apoptosis by TUNEL assay and western blot. Results: The survival analysis revealed that the mRNA expressions of DPYD, DPYS, LYN, PRKCQ, and TLR1 were significantly related to a favorable overall survival in SKCM patients. Additionally, the mRNA expression level of DPYD was associated with GPI, LYN, PCSK9, PRKCQ, and TLR1 mRNAs. GSEA results showed that the prognostic hub genes were augmented with ultraviolet, apoptosis, and metastasis. Curcumin expressed proliferation and migration of SK-MEL-1 cells (p < 0.05), and induced apoptosis (p < 0.05) significantly. Conclusion: Curcumin may have potential therapeutic effects in SKCM by inhibiting cell proliferation and migration and inducing apoptosis by regulating oxygen-related signaling pathways. The hub genes might be identified as novel biomarkers for SKCM.
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Affiliation(s)
- Long Li
- Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuwen Lu
- Department of Ophthalmology, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China
| | - Chao Ma
- Department of Ophthalmology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- *Correspondence: Chao Ma,
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Hu P, Sun N, Khan A, Zhang X, Sun P, Sun Y, Guo J, Zheng X, Yin W, Fan K, Wang J, Yang H, Li H. Network pharmacology-based study on the mechanism of scutellarin against zearalenone-induced ovarian granulosa cell injury. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2021; 227:112865. [PMID: 34634598 DOI: 10.1016/j.ecoenv.2021.112865] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 09/13/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
Zearalenone(ZEA) is a kind of mycotoxin widely existing in nature, its toxic effects can lead to the reproductive disorders in humans and animals. The aim of this study was to investigate the mechanism of scutellarin against ovarian granulosa cell(GCs) injury induced by ZEA based on network pharmacology, molecular docking method. The results show that 293 drug targets of scutellarin were found from PhamMapper database, and 583 disease targets were selected from Genecards database. Finally, 57 scutellarin targets were obtained for the repair of GCs injury with gene intersection. The protein-protein interaction(PPI), gene ontology(GO) and kyoto encyclopedia of genes and genomes(KEGG) analysis indicated that MAPK signaling pathway was most likely activated by scutellarin. Scutellarin with JNK or Caspase-3 had minimal and negative free binding energy in molecular docking analysis, indicating that they might be the acting targets of scutellarin. Cell viability was significantly decreased in ZEA treated cells. However, GCs viability, the level of estradiol(E2) and progesterone(P4) were significantly increased with addition of scutellarin to ZEA treated cells. Western blot analysis showed that scutellarin significantly reduced the expression of JNK, c-jun and Cleaved-caspasee-3 in GCs compared with ZEA treatment. In conclusion, scutellarin could alleviate the ovarian GCs injury by down-regulating the expression of JNK, c-jun and Cleaved-caspase-3 through the activation of MAPK/JNK signaling pathway. Our results will provide a theoretical foundation for the treatment of reproductive disorders with scutellarin.
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Affiliation(s)
- Panpan Hu
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China; Department of Life Science, Lvliang University, Lishi 033001, Shanxi, People's Republic of China
| | - Na Sun
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Ajab Khan
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Xinyue Zhang
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Panpan Sun
- Laboratory Animal Center, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Yaogui Sun
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Jianzhong Guo
- Department of Veterinary Pathobiology, Schubot Exotic Bird Health Center, Texas A&M University, College Station, TX 77843, USA
| | - Xiaozhong Zheng
- Medical Research Council (MRC) Centre for Inflammation Research, Queen's Medical Research Institute, The University of Edinburgh, Edinburgh EH16 4TJ, UK
| | - Wei Yin
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Kuohai Fan
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Jianzhong Wang
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Huizhen Yang
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China
| | - Hongquan Li
- College of Veterinary Medicine, Shanxi Agricultural University, Taiyuan 030031, Shanxi, People's Republic of China.
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Gubanova NV, Orlova NG, Dergilev AI, Oparina NY, Orlov YL. Glioblastoma gene network reconstruction and ontology analysis by online bioinformatics tools. J Integr Bioinform 2021; 18:jib-2021-0031. [PMID: 34783229 PMCID: PMC8709738 DOI: 10.1515/jib-2021-0031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/18/2021] [Indexed: 12/13/2022] Open
Abstract
Glioblastoma is the most aggressive type of brain tumors resistant to a number of antitumor drugs. The problem of therapy and drug treatment course is complicated by extremely high heterogeneity in the benign cell populations, the random arrangement of tumor cells, and polymorphism of their nuclei. The pathogenesis of gliomas needs to be studied using modern cellular technologies, genome- and transcriptome-wide technologies of high-throughput sequencing, analysis of gene expression on microarrays, and methods of modern bioinformatics to find new therapy targets. Functional annotation of genes related to the disease could be retrieved based on genetic databases and cross-validated by integrating complementary experimental data. Gene network reconstruction for a set of genes (proteins) proved to be effective approach to study mechanisms underlying disease progression. We used online bioinformatics tools for annotation of gene list for glioma, reconstruction of gene network and comparative analysis of gene ontology categories. The available tools and the databases for glioblastoma gene analysis are discussed together with the recent progress in this field.
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Affiliation(s)
- Natalya V Gubanova
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
| | - Nina G Orlova
- Financial University under the Government of the Russian Federation, 119991 Moscow, Russia.,Moscow State Technical University of Civil Aviation, 125993 Moscow, Russia
| | | | | | - Yuriy L Orlov
- Novosibirsk State University, 630090 Novosibirsk, Russia.,The Digital Health Institute, I.M.Sechenov First Moscow State Medical University of the Russian Ministry of Health, 119991 Moscow, Russia
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Orlov YL, Galieva AG, Orlova NG, Ivanova EN, Mozyleva YA, Anashkina AA. [Reconstruction of gene network associated with Parkinson disease for gene targets search]. BIOMEDIT︠S︡INSKAI︠A︡ KHIMII︠A︡ 2021; 67:222-230. [PMID: 34142529 DOI: 10.18097/pbmc20216703222] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Accumulation of genetic data in the field of Parkinson's disease research culminated in identifying risk factors and confident prediction of the disease occurrence. To find new gene-targets for diagnostics and therapy we have to reconstruct gene network of the disease, to cluster genes in the network, to reveal key (hub) genes with largest number of interactions in the network. Using the on-line bioinformatics tools OMIM, PANTHER, g:Profiler, GeneMANIA, and STRING-DB, we have analyzed the current array of data related to Parkinson's disease, calculated the categories of gene ontologies for a large list of genes, visualized them, and built gene networks containing the identified key objects and their relationships. However, translating the results into biological understanding is still a promising major challenge. The analysis of the genes associated with the disease, the assessment of their place in the gene network (connectivity) allows us to evaluate them as target genes for medicinal effects.
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Affiliation(s)
- Y L Orlov
- Sechenov First Moscow State Medical University of the Russian Ministry of Health (Sechenov University), Moscow, Russia; Novosibirsk State University, Novosibirsk, Russia
| | - A G Galieva
- Novosibirsk State University, Novosibirsk, Russia
| | - N G Orlova
- Financial University under the Government of the Russian Federation, Moscow, Russia
| | - E N Ivanova
- Novosibirsk State University, Novosibirsk, Russia
| | - Y A Mozyleva
- Sechenov First Moscow State Medical University of the Russian Ministry of Health (Sechenov University), Moscow, Russia
| | - A A Anashkina
- Sechenov First Moscow State Medical University of the Russian Ministry of Health (Sechenov University), Moscow, Russia; Engelgardt Institute of Molecular Biology RAS, Moscow, Russia
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Ye M, Luo G, Ye D, She M, Sun N, Lu YJ, Zheng J. Network pharmacology, molecular docking integrated surface plasmon resonance technology reveals the mechanism of Toujie Quwen Granules against coronavirus disease 2019 pneumonia. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2021; 85:153401. [PMID: 33191068 PMCID: PMC7837196 DOI: 10.1016/j.phymed.2020.153401] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 10/03/2020] [Accepted: 10/25/2020] [Indexed: 05/14/2023]
Abstract
BACKGROUND The Coronavirus disease 2019 pneumonia broke out in 2019 (COVID-19) and spread rapidly, which causes serious harm to the health of people and a huge economic burden around the world. PURPOSE In this study, the network pharmacology, molecular docking and surface plasmon resonance technology (SPR) were used to explore the potential compounds and interaction mechanism in the Toujie Quwen Granules (TQG) for the treatment of coronavirus pneumonia 2019. STUDY DESIGN The chemical constituents and compound targets of Lonicerae Japonicae Flos, Pseudostellariae Radix, Artemisia Annua L, Peucedani Radix, Forsythiae Fructus, Scutellariae Radix, Hedysarum Multijugum Maxim, Isatidis Folium, Radix Bupleuri, Fritiliariae Irrhosae Bulbus, Cicadae Periostracum, Poria Cocos Wolf, Pseudobulbus Cremastrae Seu Pleiones, Mume Fructus, Figwort Root and Fritillariae Thunbrgii Bulbus in TQG were searched. The target name was translated to gene name using the UniProt database and then the Chinese medicine-compound-target network was constructed. Protein-protein interaction network (PPI), Gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the core targets were performed in the Metascape to predict its mechanism. The top 34 compounds in the Chinese medicine-compound-target network were docked with SARS-CoV-2 3CL enzyme and SARS--CoV--2 RNA-dependent RNA polymerase (RdRp) and then the 13 compounds with lowest affinity score were docked with angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 Spike protein and interleukin 6 to explore its interaction mechanism. Lastly, SPR experiments were done using the quercetin, astragaloside IV, rutin and isoquercitrin, which were screened from the Chinese medicine-compound-target network and molecular docking. RESULTS The Chinese medicine-compound-target network includes 16 medicinal materials, 111 compounds and 298 targets, in which the degree of PTGS2, TNF and IL-6 is higher compared with other targets and which are the disease target exactly. The result of GO function enrichment analysis included the response to the molecule of bacterial origin, positive regulation of cell death, apoptotic signaling pathway, cytokine-mediated signaling pathway, cytokine receptor binding and so on. KEGG pathway analysis enrichment revealed two pathways: signaling pathway- IL-17 and signaling pathway- TNF. The result of molecular docking showed that the affinity score of compounds including quercetin, isoquercitrin, astragaloside IV and rutin is higher than other compounds. In addition, the SPR experiments revealed that the quercetin and isoquercitrin were combined with SARS-CoV-2 Spike protein rather than Angiotensin-converting enzyme 2, while astragaloside IV and rutin were combined with ACE2 rather than SARS-CoV-2 Spike protein. CONCLUSION TQG may have therapeutic effects on COVID-19 by regulating viral infection, immune and inflammation related targets and pathways, in the way of multi-component, multi-target and multi-pathway.
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Affiliation(s)
- Miaobo Ye
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Guiwen Luo
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Dexiao Ye
- Golden Health (Guangdong) Biotechnology Co, Foshan 528225, China
| | - Mengting She
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Ning Sun
- The State Key Laboratory of Chemical Biology and Drug Discovery, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yu-Jing Lu
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
| | - Jie Zheng
- School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China.
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Zhou HN, Li HY, Xu WH, Wei YY, Yu RX, Wang W, Chen YM. Study on the action mechanism of Wuling Powder on treating osteoporosis based on network pharmacology. Chin J Nat Med 2021; 19:28-35. [PMID: 33516449 DOI: 10.1016/s1875-5364(21)60003-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Indexed: 10/22/2022]
Abstract
Osteoporosis is a health problem to cause global concern. A lot of methods have been used to prevent and treat osteoporosis, but there is still a lack of effective treatment for osteoporosis owing to limited understanding of its mechanism. Therefore, the aim of this present study is to explore the underlying mechanism of Wuling Powder, a traditional Chinese medicine on treating osteoporosis. In this study, we firstly screened and identified the common targets between Wuling Powder and osteoporosis through the related databases, and then explored the relationships among these targets, Wuling Powder and osteoporosis by using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and network analyses. Subsequently, the molecular docking was performed by using systemsDock to evaluate the potential binding relationships between the active components of Wuling Powder and their related targets. The results showed that in total of 14 common targets including CREBBP, ADAM17, GOT1, GAPDH, USP8, ERBB2, EEF1A1, MTOR, RAC1, ETS1, DDX58, GCK, EGF and S100A8 were screened. EGF, ERBB2, MTOR and HIF-1 were the potential therapeutic targets for osteoporosis, and they were also the related targets for predicting active components in Wuling Powder. Taken together, we concluded that Wuling Powder might be used to treat osteoporosis through above these targets.
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Affiliation(s)
- Hao-Nan Zhou
- Graduate School, Guangxi University of Chinese Medicine, Nanning 530000, China
| | - Hao-Yu Li
- Graduate School, Guangxi University of Chinese Medicine, Nanning 530000, China
| | - Wen-Hua Xu
- Graduate School, Guangxi University of Chinese Medicine, Nanning 530000, China
| | - Yan-Yi Wei
- Graduate School, Guangxi University of Chinese Medicine, Nanning 530000, China
| | - Rui-Xin Yu
- Graduate School, Guangxi Medical University, Nanning 530000, China
| | - Wei Wang
- Graduate School, Guangxi University of Chinese Medicine, Nanning 530000, China
| | - Yuan-Ming Chen
- Department of Orthopedics, the Second Affiliated Hospital of Guangxi Medical University, Nanning 530000, China.
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Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations. Sci Rep 2020; 10:4106. [PMID: 32139709 PMCID: PMC7057977 DOI: 10.1038/s41598-020-60456-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 02/10/2020] [Indexed: 12/14/2022] Open
Abstract
Cancer is a comparatively well-studied disease, yet despite decades of intense focus, we demonstrate here using data from The Cancer Genome Atlas that a substantial number of genes implicated in cancer are relatively poorly studied. Those genes will likely be missed by any data analysis pipeline, such as enrichment analysis, that depends exclusively on annotations for understanding biological function. There is no indication that the amount of research - indicated by number of publications - is correlated with any objective metric of gene significance. Moreover, these genes are not missing at random but reflect that our information about genes is gathered in a biased manner: poorly studied genes are more likely to be primate-specific and less likely to have a Mendelian inheritance pattern, and they tend to cluster in some biological processes and not others. While this likely reflects both technological limitations as well as the fact that well-known genes tend to gather more interest from the research community, in the absence of a concerted effort to study genes in an unbiased way, many genes (and biological processes) will remain opaque.
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Nanda H, Ponnusamy N, Odumpatta R, Jeyakanthan J, Mohanapriya A. Exploring genetic targets of psoriasis using genome wide association studies (GWAS) for drug repurposing. 3 Biotech 2020; 10:43. [PMID: 31988837 PMCID: PMC6954159 DOI: 10.1007/s13205-019-2038-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 12/23/2019] [Indexed: 12/26/2022] Open
Abstract
Psoriasis is a chronic inflammatory disease causing itching in the body and pain in the joints. Currently, no permanent cure is available at a commercial level for this disease. Genome wide association studies (GWAS) provide a deeper insight that helps in better understanding this disease and further possible cure of this disease. The major goal of the present study is to identify potent genetic targets of psoriasis disease using GWAS approach and identify drugs for repurposing. The methods used include GWAS catalogue, GeneAnalytics, canSAR protein annotation tool, VarElect, Drug bank, Proteomics database, ProTox software. By exploring GWAS catalogue, 126 psoriasis associated genes (PAG) were identified. 68 genes found to be druggable were obtained from canSAR protein annotation tool. Localization results depict that maximum genes are present in cytoplasmic cellular components. The superpathways obtained from GeneAnalytics resulted in involvement of these genes in the immune system, Jak/Stat pathway, Th17 and Wnt pathways. Two genes Interleukin 13 (IL13) and POLI are Food and Drug Administration (FDA) approved targets. Small compounds for these targets were analysed for drug-likeliness, toxicity and mutagenecity properties. The FDA approved drug pandel was found to possess desirable properties. The medications used for psoriasis causes mild to severe side effects and does not work well always. Hence we propose drug repurposing strategy to use existing drugs for new therapies. Therefore, the drug pandel could be explored further and repurposed to treat psoriasis.
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Affiliation(s)
- Harshit Nanda
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India
| | - Nirmaladevi Ponnusamy
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India
| | - Rajasree Odumpatta
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India
| | - Jeyaraman Jeyakanthan
- Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu 630004 India
| | - Arumugam Mohanapriya
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu 632014 India
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Shen GH, Song Y, Yao Y, Sun QF, Jing B, Wu J, Li SY, Liu SQ, Li HC, Yuan C, Liu GY, Li JB, Liu XY, Wang HY. Downregulation of DLGAP1-Antisense RNA 1 Alleviates Vascular Endothelial Cell Injury Via Activation of the Phosphoinositide 3-kinase/Akt Pathway Results from an Acute Limb Ischemia Rat Model. Eur J Vasc Endovasc Surg 2019; 59:98-107. [PMID: 31744785 DOI: 10.1016/j.ejvs.2019.06.032] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 06/26/2019] [Accepted: 06/28/2019] [Indexed: 12/13/2022]
Abstract
OBJECTIVE This study aimed to investigate the effect of long non-coding RNA (lncRNA) DLGAP1 antisense RNA 1 (DLGAP1-AS1) on vascular endothelial cell (VEC) injury via the phosphoinositide 3-kinase (PI3K)/Akt pathway in rat models of acute lower limb ischaemia-reperfusion (I/R). METHODS Differentially expressed lncRNAs related to I/R were screened using the gene expression omnibus database. Acute lower limb I/R models were induced in male Wistar rats, in which the regulatory mechanisms of DLGAP1-AS1 silencing were analysed after the treatment of small interfering RNA (siRNA) against DLGAP1-AS1 or an inhibitor of the PI3K/Akt pathway. The relationship between DLGAP1-AS1 and the PI3K/Akt pathway was analysed. The levels of tumour necrosis factor (TNF)-α and vascular cell adhesion molecule-1 (VCAM-1), as well as malondialdehyde (MDA) concentration and creatine kinase (CK) activity, were measured. The number of circulating endothelial cells (CECs) and apoptosis of VECs were identified. RESULTS Microarray based analysis indicated that DLGAP1-AS1 was highly expressed in I/R, which was further confirmed by detection of expression in rat models of acute lower limb I/R. Notably, the treatment of siRNA against DLGAP1-AS1 led to the activation of the PI3K/Akt pathway. In response to siRNA against DLGAP1-AS1, the levels of TNF-α and VCAM-1 were decreased, and MDA concentration and CK activity was downregulated. Reduced CEC numbers and suppressed VEC apoptosis were also observed. CONCLUSION DLGAP1-AS1 silencing could further suppress the oxidative stress, exert an anti-apoptosis effect, and reduce inflammatory reaction, whereby VEC injury is alleviated by activation of the PI3K/Akt pathway in rats with acute lower limb I/R.
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Affiliation(s)
- Guang-Hui Shen
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Ye Song
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Ye Yao
- Department of Cardiac Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Qing-Feng Sun
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Bao Jing
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Jia Wu
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Shi-Yong Li
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Si-Qi Liu
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Hao-Cheng Li
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Chao Yuan
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Gao-Yan Liu
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Jing-Bo Li
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Xin-Yu Liu
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China
| | - Hai-Yang Wang
- Department of Vascular Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China.
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Li K, Li H, Xu W, Liu W, Du Y, He JF, Ma C. Research on the Potential Mechanism of Gypenosides on Treating Thyroid-Associated Ophthalmopathy Based on Network Pharmacology. Med Sci Monit 2019; 25:4923-4932. [PMID: 31268042 PMCID: PMC6621796 DOI: 10.12659/msm.917299] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Thyroid-associated ophthalmopathy is the commonest orbital disease in adults. However, shortcomings still exist in treatments. The aim of this study was to identify the efficacy and potential mechanism of gypenosides in the treatment of thyroid-associated ophthalmopathy. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was screened for active compounds of gypenosides, and targets were predicted using Swiss Target Prediction. The targets of thyroid-associated ophthalmopathy were obtained from Online Mendelian Inheritance in Man, Comparative Toxicogenomic Database and GeneCards Human gene database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome Pathways were determined based on the common targets. Protein-protein interaction (PPI) network was constructed to further understand of relationship among target genes, compounds and proteins. Molecular docking was performed to investigate the binding ability between gypenosides and hub genes. A total of 70 targets for gypenosides and 804 targets for thyroid-associated ophthalmopathy were obtained with 8 common targets identified. GO analysis and KEGG pathway analysis revealed that the hub genes were enriched in JAK-STAT, while Reactome pathways analysis indicated genes enriched in interleukin pathways. PPI network showed STAT1, STAT3, and STAT4 were at the center. Additionally, molecular docking indicated that STAT1 and STAT3 display good binding forces with gypenosides. This study indicates that target genes mainly enriched in JAK-STAT signaling pathway, particularly in STATs, which can be combined with gypenosides. This may suggest that gypenosides have curative effect on thyroid-associated ophthalmopathy via the JAK-STAT pathway.
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Affiliation(s)
- Kaijun Li
- Department of Ophthalmology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)
| | - Haoyu Li
- Guangxi University of Chinese Medicine, Nanning, Guangxi, China (mainland)
| | - Wenhua Xu
- Guangxi University of Chinese Medicine, Nanning, Guangxi, China (mainland)
| | - Wei Liu
- Department of Ophthalmology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)
| | - Yi Du
- Department of Ophthalmology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)
| | - Jian-Feng He
- Department of Ophthalmology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)
| | - Chao Ma
- Department of Ophthalmology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (mainland)
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Chen K, Ma Y, Wu S, Zhuang Y, Liu X, Lv L, Zhang G. Construction and analysis of a lncRNA‑miRNA‑mRNA network based on competitive endogenous RNA reveals functional lncRNAs in diabetic cardiomyopathy. Mol Med Rep 2019; 20:1393-1403. [PMID: 31173240 DOI: 10.3892/mmr.2019.10361] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 02/19/2019] [Indexed: 11/06/2022] Open
Abstract
Diabetic cardiomyopathy (DCM) is a major cause of mortality in patients with diabetes, particularly those with type 2 diabetes. Long non‑coding RNAs (lncRNAs), including terminal differentiation‑induced lncRNA (TINCR), myocardial infarction‑associated transcript (MIAT) and H19, serve a key role in the regulation of DCM. MicroRNAs (miRNAs/miRs) can inhibit the expression of mRNA at the post‑transcriptional level, whereas lncRNAs can mask the inhibitory effects of miRNAs on mRNA. Together, miRNAs and lncRNAs form a competitive endogenous non‑coding RNA (ceRNA) network that regulates the occurrence and development of various diseases. However, the regulatory role of lncRNAs in DCM is unclear. In this study, a background network containing mRNAs, miRNAs and lncRNAs was constructed using starBase and a regulatory network of DCM was screened using Cytoscape. A functional lncRNA, X‑inactive specific transcript (XIST), was identified in the disease network and the main miRNAs (miR‑424‑5p and miR‑497‑5p) that are regulated by XIST were further screened to obtain the ceRNA regulatory network of DCM. In conclusion, the results of this study revealed that lncRNAs may serve an important role in DCM and provided novel insights into the pathogenesis of DCM.
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Affiliation(s)
- Kai Chen
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Yunci Ma
- Nanfang Hospital, Southern Medical University/The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong 510000, P.R. China
| | - Shaoyu Wu
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Yuxin Zhuang
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Xin Liu
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Lin Lv
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
| | - Guohua Zhang
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
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Xiang SY, Zhao J, Lu Y, Chen RM, Wang Y, Chen Y, Long B, Zhu LP, Yao PF, Xu YF, Chen JH. Network pharmacology-based identification for therapeutic mechanism of Ling-Gui-Zhu-Gan decoction in the metabolic syndrome induced by antipsychotic drugs. Comput Biol Med 2019; 110:1-7. [PMID: 31085379 DOI: 10.1016/j.compbiomed.2019.05.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 04/29/2019] [Accepted: 05/06/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND The metabolic syndrome (MetS) is a common side effect of second-generation antipsychotic drugs (SGAs), leading to poor prognosis in patients with mental illness. The traditional Chinese herbal formula Ling-Gui-Zhu-Gan decoction (LGZGD) is a clinically validated remedy for SGAs-induced MetS, but its underlying mechanism remains unclear. METHODS A network pharmacology-based analysis was performed to explore predicted plasma-absorbed components, putative therapeutic targets, and main pathways involved in LGZGD bioactivity. We constructed a target interaction network between the predicted targets of LGZGD and the known targets of MetS, after which we extracted major hubs using topological analysis. Thereafter, the maximum value of "edge betweenness" of all interactions was defined as a bottleneck, which suggested its importance in connecting all targets in the network. Finally, a pathway enrichment analysis of major hubs was used to reveal the biological functions of LGZGD. RESULTS This approach identified 120 compounds and 361 candidate targets of LGZGD. According to the data generated in this study, the interaction between JUN and APOA1 plays a vital role in the treatment of SGAs-induced MetS using LGZGD. Interestingly, JUN was a putative target of LGZGD and APOA1 is one of the known targets of both MetS and SGAs (olanzapine and clozapine). LGZGD was significantly associated with several pathways including PI3K-Akt signaling, insulin resistance, and MAPK signaling pathway. CONCLUSIONS LGZGD might inhibit JUN and thereby increases the expression of APOA1 to maintain metabolic homeostasis via some vital pathways.
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Affiliation(s)
- Si-Ying Xiang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Jing Zhao
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Ying Lu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Ru-Meng Chen
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Yan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Yi Chen
- Department of Nephrology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, PR China
| | - Bin Long
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Li-Ping Zhu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Pei-Fen Yao
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China
| | - Yi-Feng Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China.
| | - Jian-Hua Chen
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China.
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Soreq L, Rose J, Soreq E, Hardy J, Trabzuni D, Cookson MR, Smith C, Ryten M, Patani R, Ule J. Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging. Cell Rep 2017; 18:557-570. [PMID: 28076797 PMCID: PMC5263238 DOI: 10.1016/j.celrep.2016.12.011] [Citation(s) in RCA: 269] [Impact Index Per Article: 38.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 10/04/2016] [Accepted: 12/02/2016] [Indexed: 02/06/2023] Open
Abstract
Gene expression studies suggest that aging of the human brain is determined by a complex interplay of molecular events, although both its region- and cell-type-specific consequences remain poorly understood. Here, we extensively characterized aging-altered gene expression changes across ten human brain regions from 480 individuals ranging in age from 16 to 106 years. We show that astrocyte- and oligodendrocyte-specific genes, but not neuron-specific genes, shift their regional expression patterns upon aging, particularly in the hippocampus and substantia nigra, while the expression of microglia- and endothelial-specific genes increase in all brain regions. In line with these changes, high-resolution immunohistochemistry demonstrated decreased numbers of oligodendrocytes and of neuronal subpopulations in the aging brain cortex. Finally, glial-specific genes predict age with greater precision than neuron-specific genes, thus highlighting the need for greater mechanistic understanding of neuron-glia interactions in aging and late-life diseases.
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Affiliation(s)
- Lilach Soreq
- Institute of Neurology, University College London, London WC1N 3BG, UK; The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | | | | | - Jamie Rose
- MRC Edinburgh Brain Bank, Academic Neuropathology, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Eyal Soreq
- The Computational, Cognitive and Clinical NeuroImaging Laboratory, Division of Brain Sciences, Imperial College, London SW7 2AZ, UK
| | - John Hardy
- Institute of Neurology, University College London, London WC1N 3BG, UK; Reta Lila Weston Institute of Neurological Studies, UCL ION, 1 Wakefield Street, London WC1N 1PJ, UK
| | - Daniah Trabzuni
- Institute of Neurology, University College London, London WC1N 3BG, UK; Departments of Genetics, King Faisal Specialist Hospital and Research Centre. Riyadh 12713, Saudi Arabia
| | - Mark R Cookson
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Colin Smith
- MRC Edinburgh Brain Bank, Academic Neuropathology, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Mina Ryten
- Institute of Neurology, University College London, London WC1N 3BG, UK; Department of Medical and Molecular Genetics, King's College London, Guy's Hospital, Great Maze Pond, London SE1 9RT, UK
| | - Rickie Patani
- Institute of Neurology, University College London, London WC1N 3BG, UK; The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK; Reta Lila Weston Institute of Neurological Studies, UCL ION, 1 Wakefield Street, London WC1N 1PJ, UK; Euan MacDonald Centre for MND, University of Edinburgh, Edinburgh EH8 9YL, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 1TN, UK.
| | - Jernej Ule
- Institute of Neurology, University College London, London WC1N 3BG, UK; The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
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Calderón-González KG, Hernández-Monge J, Herrera-Aguirre ME, Luna-Arias JP. Bioinformatics Tools for Proteomics Data Interpretation. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 919:281-341. [PMID: 27975225 DOI: 10.1007/978-3-319-41448-5_16] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Biological systems function via intricate cellular processes and networks in which RNAs, metabolites, proteins and other cellular compounds have a precise role and are exquisitely regulated (Kumar and Mann, FEBS Lett 583(11):1703-1712, 2009). The development of high-throughput technologies, such as the Next Generation DNA Sequencing (NGS) and DNA microarrays for sequencing genomes or metagenomes, have triggered a dramatic increase in the last few years in the amount of information stored in the GenBank and UniProt Knowledgebase (UniProtKB). GenBank release 210, reported in October 2015, contains 202,237,081,559 nucleotides corresponding to 188,372,017 sequences, whilst there are only 1,222,635,267,498 nucleotides corresponding to 309,198,943 sequences from Whole Genome Shotgun (WGS) projects. In the case of UniProKB/Swiss-Prot, release 2015_12 (December 9, 2015) contains 196,219,159 amino acids that correspond to 550,116 entries. Meanwhile, UniProtKB/TrEMBL (release 2015_12 of December 9 2015) contains 1,838,851,8871 amino acids corresponding to 555,270,679 entries. Proteomics has also improved our knowledge of proteins that are being expressed in cells at a certain time of the cell cycle. It has also allowed the identification of molecules forming part of multiprotein complexes and an increasing number of posttranslational modifications (PTMs) that are present in proteins, as well as the variants of proteins expressed.
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Affiliation(s)
- Karla Grisel Calderón-González
- Departamento de Biología Celular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav-IPN), Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, C.P. 07360, Ciudad de México, Mexico
| | - Jesús Hernández-Monge
- Instituto de Física, Universidad Autónoma de San Luis Potosí, Av. Manuel Nava 6, Zona Universitaria, C.P. 78290, San Luis Potosí, S.L.P., Mexico
| | - María Esther Herrera-Aguirre
- Departamento de Biología Celular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav-IPN), Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, C.P. 07360, Ciudad de México, Mexico
| | - Juan Pedro Luna-Arias
- Departamento de Biología Celular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav-IPN), Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, C.P. 07360, Ciudad de México, Mexico.
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20
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Momparler RL, Côté S, Momparler LF, Idaghdour Y. Inhibition of DNA and Histone Methylation by 5-Aza-2'-Deoxycytidine (Decitabine) and 3-Deazaneplanocin-A on Antineoplastic Action and Gene Expression in Myeloid Leukemic Cells. Front Oncol 2017; 7:19. [PMID: 28261562 PMCID: PMC5309231 DOI: 10.3389/fonc.2017.00019] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/31/2017] [Indexed: 12/26/2022] Open
Abstract
Epigenetic alterations play an important role in the development of acute myeloid leukemia (AML) by silencing of genes that suppress leukemogenesis and differentiation. One of the key epigenetic changes in AML is gene silencing by DNA methylation. The importance of this alteration is illustrated by the induction of remissions in AML by 5-aza-2′-deoxycytidine (5-AZA-CdR, decitabine), a potent inhibitor of DNA methylation. However, most patients induced into remission by 5-AZA-CdR will relapse, suggesting that a second agent should be sought to increase the efficacy of this epigenetic therapy. An interesting candidate for this purpose is 3-deazaneplanocin A (DZNep). This analog inhibits EZH2, a histone methyltransferase that trimethylates lysine 27 histone H3 (H3K27me3), a marker for gene silencing. This second epigenetic silencing mechanism also plays an important role in leukemogenesis as shown in preclinical studies where DZNep exhibits potent inhibition of colony formation by AML cells. We reported previously that 5-AZA-CdR in combination with DZNep exhibits a synergistic antineoplastic action against human HL-60 AML cells and the synergistic activation of several tumor suppressor genes. In this report, we showed that this combination also induced a synergistic activation of apoptosis in HL-60 cells. The synergistic antineoplastic action of 5-AZA-CdR plus DZNep was also observed on a second human myeloid leukemia cell line, AML-3. In addition, 5-AZA-CdR in combination with the specific inhibitors of EZH2, GSK-126, or GSK-343, also exhibited a synergistic antineoplastic action on both HL-60 and AML-3. The combined action of 5-AZA-CdR and DZNep on global gene expression in HL-60 cells was investigated in greater depth using RNA sequencing analysis. We observed that this combination of epigenetic agents exhibited a synergistic activation of hundreds of genes. The synergistic activation of so many genes that suppress malignancy by 5-AZA-CdR plus DZNep suggests that epigenetic gene silencing by DNA and histone methylation plays a major role in leukemogenesis. Targeting DNA and histone methylation is a promising approach that merits clinical investigation for the treatment of AML.
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Affiliation(s)
- Richard L Momparler
- Département de Pharmacologie, Université de Montréal, Montreal, QC, Canada; Centre de recherche, Service d'hématologie/oncologie, CHU-Saint-Justine, Montréal, QC, Canada
| | - Sylvie Côté
- Centre de recherche, Service d'hématologie/oncologie, CHU-Saint-Justine , Montréal, QC , Canada
| | - Louise F Momparler
- Centre de recherche, Service d'hématologie/oncologie, CHU-Saint-Justine , Montréal, QC , Canada
| | - Youssef Idaghdour
- Department of Biology, New York University Abu Dhabi , Abu Dhabi , United Arab Emirates
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21
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Li H, Jiang X, Zhu S, Sui L. Identification of personalized dysregulated pathways in hepatocellular carcinoma. Pathol Res Pract 2017; 213:327-332. [PMID: 28215647 DOI: 10.1016/j.prp.2017.01.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 01/11/2017] [Accepted: 01/19/2017] [Indexed: 11/27/2022]
Abstract
INTRODUCTION Hepatocellular carcinoma (HCC) is the most common liver malignancy, and ranks the fifth most prevalent malignant tumors worldwide. In general, HCC are detected until the disease is at an advanced stage and may miss the best chance for treatment. Thus, elucidating the molecular mechanisms is critical to clinical diagnosis and treatment for HCC. The purpose of this study was to identify dysregulated pathways of great potential functional relevance in the progression of HCC. MATERIALS AND METHODS Microarray data of 72 pairs of tumor and matched non-tumor surrounding tissues of HCC were transformed to gene expression data. Differentially expressed genes (DEG) between patients and normal controls were identified using Linear Models for Microarray Analysis. Personalized dysregulated pathways were identified using individualized pathway aberrance score module. RESULTS 169 differentially expressed genes (DEG) were obtained with |logFC|≥1.5 and P≤0.01. 749 dysregulated pathways were obtained with P≤0.01 in pathway statistics, and there were 93 DEG overlapped in the dysregulated pathways. After performing normal distribution analysis, 302 pathways with the aberrance probability≥0.5 were identified. By ranking pathway with aberrance probability, the top 20 pathways were obtained. Only three DEGs (TUBA1C, TPR, CDC20) were involved in the top 20 pathways. CONCLUSION These personalized dysregulated pathways and overlapped genes may give new insights into the underlying biological mechanisms in the progression of HCC. Particular attention can be focused on them for further research.
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Affiliation(s)
- Hong Li
- Department of Oncology, Weihai Central Hospital, Weihai, 264400, Shandong, PR China
| | - Xiumei Jiang
- Department of Oncology, Weihai Central Hospital, Weihai, 264400, Shandong, PR China
| | - Shengjie Zhu
- Department of Oncology, Weihai Central Hospital, Weihai, 264400, Shandong, PR China
| | - Lihong Sui
- Department of Oncology, Weihai Central Hospital, Weihai, 264400, Shandong, PR China.
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22
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Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, Stein TI, Nudel R, Lieder I, Mazor Y, Kaplan S, Dahary D, Warshawsky D, Guan-Golan Y, Kohn A, Rappaport N, Safran M, Lancet D. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. ACTA ACUST UNITED AC 2016; 54:1.30.1-1.30.33. [PMID: 27322403 DOI: 10.1002/cpbi.5] [Citation(s) in RCA: 2104] [Impact Index Per Article: 263.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It automatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. VarElect's capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. © 2016 by John Wiley & Sons, Inc.
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Affiliation(s)
- Gil Stelzer
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.,These authors contributed equally to the paper
| | - Naomi Rosen
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.,These authors contributed equally to the paper
| | - Inbar Plaschkes
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.,LifeMap Sciences Ltd, Tel Aviv, Israel
| | - Shahar Zimmerman
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Michal Twik
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Simon Fishilevich
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Tsippi Iny Stein
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Ron Nudel
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | | | | | | | - Dvir Dahary
- LifeMap Sciences Ltd, Tel Aviv, Israel.,Toldot Genetics Ltd, Hod Hasharon, Israel
| | | | | | - Asher Kohn
- LifeMap Sciences Inc, Marshfield, Massachusetts
| | - Noa Rappaport
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Marilyn Safran
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Doron Lancet
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.,Corresponding author
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23
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Li RH, Zhang AM, Li S, Li TY, Wang LJ, Zhang HR, Li P, Jia XJ, Zhang T, Peng XY, Liu MD, Wang X, Lang Y, Xue WL, Liu J, Wang YY. Multiple differential expression networks identify key genes in rectal cancer. Cancer Biomark 2016; 16:435-44. [PMID: 27062700 DOI: 10.3233/cbm-160582] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Rectal cancer is an important contributor to cancer mortality. OBJECTIVE The objective of this paper is to identify key genes across three phenotypes (fungating, polypoid and polypoid & small-ulcer) of rectal cancer based on multiple differential expression networks (DENs). METHODS Differential interactions and non-differential interactions were evaluated according to Spearman correlation coefficient (SCC) algorithm, and were selected to construct DENs. Topological analysis was performed for exploring hub genes in largest components of DENs. Key genes were denoted as intersections between nodes of DENs and rectal cancer associated genes from Genecards. Finally, we utilized hub genes to classify phenotypes of rectal cancer on the basis of support vector machines (SVM) methodology. RESULTS We obtained 19 hub genes and total 12 common key genes of three largest components of DENs, and EGFR was the common element. The SVM results revealed that hub genes could classify phenotypes, and validated feasibility of DEN methods. CONCLUSIONS We have successfully identified significant genes (such as EGFR and UBC) across fungating, polypoid and polypoid & small-ulcer phenotype of rectal cancer. They might be potential biomarkers for classification, detection and therapy of this cancer.
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Affiliation(s)
- Ri-Heng Li
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Ai-Min Zhang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Shuang Li
- Department of Blood Transfusion, Neimenggu Xinganleague People's Hospital, Wulanhaote, Inner Mongolia, China
| | - Tian-Yang Li
- Clinical Medical College of Hebei University, Baoding, Hebei, China
| | - Lian-Jing Wang
- Clinical Medical College of Hebei University, Baoding, Hebei, China
| | - Hao-Ran Zhang
- Clinical Medical College of Hebei University, Baoding, Hebei, China
| | - Ping Li
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Xiong-Jie Jia
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Tao Zhang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Xin-Yu Peng
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Min-Di Liu
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Xu Wang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Yan Lang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Wei-Lan Xue
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Jing Liu
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
| | - Yan-Yan Wang
- Department of Gastrointestinal Surgery, Affiliated Hospital of Hebei University, Baoding, Hebei, China
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Fishilevich S, Zimmerman S, Kohn A, Iny Stein T, Olender T, Kolker E, Safran M, Lancet D. Genic insights from integrated human proteomics in GeneCards. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw030. [PMID: 27048349 PMCID: PMC4820835 DOI: 10.1093/database/baw030] [Citation(s) in RCA: 102] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Accepted: 02/23/2016] [Indexed: 11/15/2022]
Abstract
GeneCards is a one-stop shop for searchable human gene annotations (http://www.genecards.org/). Data are automatically mined from ∼120 sources and presented in an integrated web card for every human gene. We report the application of recent advances in proteomics to enhance gene annotation and classification in GeneCards. First, we constructed the Human Integrated Protein Expression Database (HIPED), a unified database of protein abundance in human tissues, based on the publically available mass spectrometry (MS)-based proteomics sources ProteomicsDB, Multi-Omics Profiling Expression Database, Protein Abundance Across Organisms and The MaxQuant DataBase. The integrated database, residing within GeneCards, compares favourably with its individual sources, covering nearly 90% of human protein-coding genes. For gene annotation and comparisons, we first defined a protein expression vector for each gene, based on normalized abundances in 69 normal human tissues. This vector is portrayed in the GeneCards expression section as a bar graph, allowing visual inspection and comparison. These data are juxtaposed with transcriptome bar graphs. Using the protein expression vectors, we further defined a pairwise metric that helps assess expression-based pairwise proximity. This new metric for finding functional partners complements eight others, including sharing of pathways, gene ontology (GO) terms and domains, implemented in the GeneCards Suite. In parallel, we calculated proteome-based differential expression, highlighting a subset of tissues that overexpress a gene and subserving gene classification. This textual annotation allows users of VarElect, the suite’s next-generation phenotyper, to more effectively discover causative disease variants. Finally, we define the protein–RNA expression ratio and correlation as yet another attribute of every gene in each tissue, adding further annotative information. The results constitute a significant enhancement of several GeneCards sections and help promote and organize the genome-wide structural and functional knowledge of the human proteome. Database URL: http://www.genecards.org/
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Affiliation(s)
- Simon Fishilevich
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Shahar Zimmerman
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Asher Kohn
- LifeMap Sciences Ltd., Tel Aviv 69710, Israel
| | - Tsippi Iny Stein
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Tsviya Olender
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Eugene Kolker
- CDO Analytics, Seattle Children's Hospital, Seattle, WA 98101 USA Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, WA 98101 USA Data-Enabled Life Sciences Alliance (DELSA), Seattle, Washington, 98101, USA Departments of Biomedical Informatics and Medical Education and Pediatrics, University of Washington School of Medicine, Seattle, WA 98109, USA Department of Chemistry and Chemical Biology, Northeastern University College of Science, Boston, MA 02115 USA
| | - Marilyn Safran
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Doron Lancet
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 7610001, Israel
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Cha EY, Jeong HE, Kim WY, Shin HJ, Kim HS, Shin JG. Brief introduction to current pharmacogenomics research tools. Transl Clin Pharmacol 2016. [DOI: 10.12793/tcp.2016.24.1.13] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Eun-Young Cha
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Hye-Eun Jeong
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Woo-Young Kim
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Ho Jung Shin
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Ho-Sook Kim
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
- Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan 47392, Korea
| | - Jae-Gook Shin
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
- Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan 47392, Korea
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Wong YH, Wu CC, Lai HY, Jheng BR, Weng HY, Chang TH, Chen BS. Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data. BMC SYSTEMS BIOLOGY 2015; 9 Suppl 6:S4. [PMID: 26679092 PMCID: PMC4674888 DOI: 10.1186/1752-0509-9-s6-s4] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Molecular signaling of angiogenesis begins within hours after initiation of a stroke and the following regulation of endothelial integrity mediated by growth factor receptors and vascular growth factors. Recent studies further provided insights into the coordinated patterns of post-stroke gene expressions and the relationships between neurodegenerative diseases and neural function recovery processes after a stroke. RESULTS Differential protein-protein interaction networks (PPINs) were constructed at 3 post-stroke time points, and proteins with a significant stroke relevance value (SRV) were discovered. Genes, including UBC, CUL3, APP, NEDD8, JUP, and SIRT7, showed high associations with time after a stroke, and Ingenuity Pathway Analysis results showed that these post-stroke time series-associated genes were related to molecular and cellular functions of cell death, cell survival, the cell cycle, cellular development, cellular movement, and cell-to-cell signaling and interactions. These biomarkers may be helpful for the early detection, diagnosis, and prognosis of ischemic stroke. CONCLUSIONS This is our first attempt to use our theory of a systems biology framework on strokes. We focused on 3 key post-stroke time points. We identified the network and corresponding network biomarkers for the 3 time points, further studies are needed to experimentally confirm the findings and compare them with the causes of ischemic stroke. Our findings showed that stroke-associated biomarker genes at different time points were significantly involved in cell cycle processing, including G2-M, G1-S and meiosis, which contributes to the current understanding of the etiology of stroke. We hope this work helps scientists reveal more hidden cellular mechanisms of stroke etiology and repair processes.
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Affiliation(s)
- Yung-Hao Wong
- Laboratory of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Chia-Chou Wu
- Laboratory of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Hsien-Yong Lai
- Institution Review Board, Christian Mennonite Hospital, Hualien 970, Taiwan
| | - Bo-Ren Jheng
- Laboratory of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Hsing-Yu Weng
- Graduate Institute of Clinical Medicine, Taipei Medical University, Taipei 110, Taiwan
| | - Tzu-Hao Chang
- Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei 110, Taiwan
| | - Bor-Sen Chen
- Laboratory of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
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Yu S, Yi H, Wang Z, Dong J. Screening key genes associated with congenital heart defects in Down syndrome based on differential expression network. INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL PATHOLOGY 2015; 8:8385-8393. [PMID: 26339408 PMCID: PMC4555736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Accepted: 06/23/2015] [Indexed: 06/05/2023]
Abstract
BACKGROUND Down syndrome (DS) is the most common viable chromosomal disorder with intellectual impairment and several other developmental abnormalities. Forty to fifty percent of newborns with DS have some form of congenital heart defects (CHD). The genome of CHD in DS has already been obtained, but the underlying genomic or gene expression variation that contributes to the manifestation of a CHD in DS is still unknown. OBJECTIVE This study was aimed to analyze key genes of patients with CHD in DS. METHODS Differential expression network (DEN) approach was employed to analyze the dyeregulated genes and pathways in this study. First, the differentially expressed genes (DEGs) between CHD in DS and normal subjects were screened based on the microarray expression data. Next, the differential interactions were identified using spearman correlation coefficients of edges in different conditions. The DEN was then constructed combining both DEGs and differential interactions, and HUB genes were gained by degree centrality analysis of DEN. Meanwhile, disease genes included in the DEN were also ascertained. RESULTS When analyzing gene expression values in different conditions, no DEGs were identified. While, a total of 984 gene pairs with significant differential expression were identified. Finally, the DEN was constructed only using differential edges in our study. In this network, eight HUB genes were identified, and thereinto four genes (UBC, APP, HUWE1 and SRC) were both HUB genes and disease genes. CONCLUSIONS DEN approach should be taken as a useful complement to traditional differential genes methods. We provide several potential underlying biomarkers for CHD in DS.
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Affiliation(s)
- Shan Yu
- Department of Obstetrics, Jinan Maternity and Child Care Hospital Jinan 250001, Shandong Province, P.R. China
| | - Huani Yi
- Department of Obstetrics, Jinan Maternity and Child Care Hospital Jinan 250001, Shandong Province, P.R. China
| | - Zhimin Wang
- Department of Obstetrics, Jinan Maternity and Child Care Hospital Jinan 250001, Shandong Province, P.R. China
| | - Juan Dong
- Department of Obstetrics, Jinan Maternity and Child Care Hospital Jinan 250001, Shandong Province, P.R. China
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Rappaport N, Twik M, Nativ N, Stelzer G, Bahir I, Stein TI, Safran M, Lancet D. MalaCards: A Comprehensive Automatically-Mined Database of Human Diseases. ACTA ACUST UNITED AC 2014; 47:1.24.1-19. [PMID: 25199789 DOI: 10.1002/0471250953.bi0124s47] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Systems medicine provides insights into mechanisms of human diseases, and expedites the development of better diagnostics and drugs. To facilitate such strategies, we initiated MalaCards, a compendium of human diseases and their annotations, integrating and often remodeling information from 64 data sources. MalaCards employs, among others, the proven automatic data-mining strategies established in the construction of GeneCards, our widely used compendium of human genes. The development of MalaCards poses many algorithmic challenges, such as disease name unification, integrated classification, gene-disease association, and disease-targeted expression analysis. MalaCards displays a Web card for each of >19,000 human diseases, with 17 sections, including textual summaries, related diseases, related genes, genetic variations and tests, and relevant publications. Also included are a powerful search engine and a variety of categorized disease lists. This unit describes two basic protocols to search and browse MalaCards effectively.
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Affiliation(s)
- Noa Rappaport
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
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Kariya Y, Honma M, Suzuki H. Systems-based understanding of pharmacological responses with combinations of multidisciplinary methodologies. Biopharm Drug Dispos 2013; 34:489-507. [DOI: 10.1002/bdd.1865] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2013] [Accepted: 10/06/2013] [Indexed: 12/25/2022]
Affiliation(s)
- Yoshiaki Kariya
- Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine; The University of Tokyo; 113-8655 Tokyo Japan
| | - Masashi Honma
- Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine; The University of Tokyo; 113-8655 Tokyo Japan
| | - Hiroshi Suzuki
- Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine; The University of Tokyo; 113-8655 Tokyo Japan
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Ullah M, Stich S, Häupl T, Eucker J, Sittinger M, Ringe J. Reverse differentiation as a gene filtering tool in genome expression profiling of adipogenesis for fat marker gene selection and their analysis. PLoS One 2013; 8:e69754. [PMID: 23922792 PMCID: PMC3724870 DOI: 10.1371/journal.pone.0069754] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2013] [Accepted: 06/11/2013] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND During mesenchymal stem cell (MSC) conversion into adipocytes, the adipogenic cocktail consisting of insulin, dexamethasone, indomethacin and 3-isobutyl-1-methylxanthine not only induces adipogenic-specific but also genes for non-adipogenic processes. Therefore, not all significantly expressed genes represent adipogenic-specific marker genes. So, our aim was to filter only adipogenic-specific out of all expressed genes. We hypothesize that exclusively adipogenic-specific genes change their expression during adipogenesis, and reverse during dedifferentiation. Thus, MSC were adipogenic differentiated and dedifferentiated. RESULTS Adipogenesis and reverse adipogenesis was verified by Oil Red O staining and expression of PPARG and FABP4. Based on GeneChips, 991 genes were differentially expressed during adipogenesis and grouped in 4 clusters. According to bioinformatic analysis the relevance of genes with adipogenic-linked biological annotations, expression sites, molecular functions, signaling pathways and transcription factor binding sites was high in cluster 1, including all prominent adipogenic genes like ADIPOQ, C/EBPA, LPL, PPARG and FABP4, moderate in clusters 2-3, and negligible in cluster 4. During reversed adipogenesis, only 782 expressed genes (clusters 1-3) were reverted, including 597 genes not reported for adipogenesis before. We identified APCDD1, CHI3L1, RARRES1 and SEMA3G as potential adipogenic-specific genes. CONCLUSION The model system of adipogenesis linked to reverse adipogenesis allowed the filtration of 782 adipogenic-specific genes out of total 991 significantly expressed genes. Database analysis of adipogenic-specific biological annotations, transcription factors and signaling pathways further validated and valued our concept, because most of the filtered 782 genes showed affiliation to adipogenesis. Based on this approach, the selected and filtered genes would be potentially important for characterization of adipogenesis and monitoring of clinical translation for soft-tissue regeneration. Moreover, we report 4 new marker genes.
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Affiliation(s)
- Mujib Ullah
- Tissue Engineering Laboratory & Berlin-Brandenburg Center for Regenerative Therapies, Department of Rheumatology and Clinical Immunology, Charité-University Medicine Berlin, Berlin, Germany
| | - Stefan Stich
- Tissue Engineering Laboratory & Berlin-Brandenburg Center for Regenerative Therapies, Department of Rheumatology and Clinical Immunology, Charité-University Medicine Berlin, Berlin, Germany
| | - Thomas Häupl
- Tissue Engineering Laboratory & Berlin-Brandenburg Center for Regenerative Therapies, Department of Rheumatology and Clinical Immunology, Charité-University Medicine Berlin, Berlin, Germany
| | - Jan Eucker
- Department of Hematology and Oncology, Charité-University Medicine Berlin, Berlin, Germany
| | - Michael Sittinger
- Tissue Engineering Laboratory & Berlin-Brandenburg Center for Regenerative Therapies, Department of Rheumatology and Clinical Immunology, Charité-University Medicine Berlin, Berlin, Germany
| | - Jochen Ringe
- Tissue Engineering Laboratory & Berlin-Brandenburg Center for Regenerative Therapies, Department of Rheumatology and Clinical Immunology, Charité-University Medicine Berlin, Berlin, Germany
- * E-mail:
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Douville C, Carter H, Kim R, Niknafs N, Diekhans M, Stenson PD, Cooper DN, Ryan M, Karchin R. CRAVAT: cancer-related analysis of variants toolkit. Bioinformatics 2013; 29:647-8. [PMID: 23325621 PMCID: PMC3582272 DOI: 10.1093/bioinformatics/btt017] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2012] [Revised: 11/19/2012] [Accepted: 01/08/2013] [Indexed: 11/13/2022] Open
Abstract
SUMMARY Advances in sequencing technology have greatly reduced the costs incurred in collecting raw sequencing data. Academic laboratories and researchers therefore now have access to very large datasets of genomic alterations but limited time and computational resources to analyse their potential biological importance. Here, we provide a web-based application, Cancer-Related Analysis of Variants Toolkit, designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis. Cancer-Related Analysis of Variants Toolkit provides predictive scores for germline variants, somatic mutations and relative gene importance, as well as annotations from published literature and databases. Results are emailed to users as MS Excel spreadsheets and/or tab-separated text files. AVAILABILITY http://www.cravat.us/
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Affiliation(s)
- Christopher Douville
- Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
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Abstract
The HUGO Gene Nomenclature Committee (HGNC) assigns approved gene symbols to human loci. There are currently over 33,000 approved gene symbols, the majority of which represent protein-coding genes, but we also name other locus types such as non-coding RNAs, pseudogenes and phenotypic loci. Where relevant, the HGNC organise these genes into gene families and groups. The HGNC website http://www.genenames.org/ is an online repository of HGNC-approved gene nomenclature and associated resources for human genes, and includes links to genomic, proteomic and phenotypic information. In addition to this, we also have dedicated gene family web pages and are currently expanding and generating more of these pages using data curated by the HGNC and from information derived from external resources that focus on particular gene families. Here, we review our current online resources with a particular focus on our gene family data, using it to highlight our new Gene Symbol Report and gene family data downloads.
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Stelzer G, Dalah I, Stein TI, Satanower Y, Rosen N, Nativ N, Oz-Levi D, Olender T, Belinky F, Bahir I, Krug H, Perco P, Mayer B, Kolker E, Safran M, Lancet D. In-silico human genomics with GeneCards. Hum Genomics 2012; 5:709-17. [PMID: 22155609 PMCID: PMC3525253 DOI: 10.1186/1479-7364-5-6-709] [Citation(s) in RCA: 159] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org). This human gene compendium was created to help to introduce order into the increasing chaos of information flow. As a consequence of viewing details and deep links related to specific genes, users have often requested enhanced capabilities, such that, over time, GeneCards has blossomed into a suite of tools (including GeneDecks, GeneALaCart, GeneLoc, GeneNote and GeneAnnot) for a variety of analyses of both single human genes and sets thereof. In this paper, we focus on inhouse and external research activities which have been enabled, enhanced, complemented and, in some cases, motivated by GeneCards. In turn, such interactions have often inspired and propelled improvements in GeneCards. We describe here the evolution and architecture of this project, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.
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Affiliation(s)
- Gil Stelzer
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 76100, Israel.
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Abstract
Technological Omics breakthroughs, including next generation sequencing, bring avalanches of data which need to undergo effective data management to ensure integrity, security, and maximal knowledge-gleaning. Data management system requirements include flexible input formats, diverse data entry mechanisms and views, user friendliness, attention to standards, hardware and software platform definition, as well as robustness. Relevant solutions elaborated by the scientific community include Laboratory Information Management Systems (LIMS) and standardization protocols facilitating data sharing and managing. In project planning, special consideration has to be made when choosing relevant Omics annotation sources, since many of them overlap and require sophisticated integration heuristics. The data modeling step defines and categorizes the data into objects (e.g., genes, articles, disorders) and creates an application flow. A data storage/warehouse mechanism must be selected, such as file-based systems and relational databases, the latter typically used for larger projects. Omics project life cycle considerations must include the definition and deployment of new versions, incorporating either full or partial updates. Finally, quality assurance (QA) procedures must validate data and feature integrity, as well as system performance expectations. We illustrate these data management principles with examples from the life cycle of the GeneCards Omics project (http://www.genecards.org), a comprehensive, widely used compendium of annotative information about human genes. For example, the GeneCards infrastructure has recently been changed from text files to a relational database, enabling better organization and views of the growing data. Omics data handling benefits from the wealth of Web-based information, the vast amount of public domain software, increasingly affordable hardware, and effective use of data management and annotation principles as outlined in this chapter.
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Affiliation(s)
- Arye Harel
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
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Nguyen VPKH, Hanna G, Rodrigues N, Pizzuto K, Yang E, Van Slyke P, Kim H, Chen SH, Dumont DJ. Differential proteomic analysis of lymphatic, venous, and arterial endothelial cells extracted from bovine mesenteric vessels. Proteomics 2010; 10:1658-72. [PMID: 20186751 DOI: 10.1002/pmic.200900594] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Differential protein profiling by 2-D PAGE is generally useful in biomarker discovery, proteome analysis and routine sample preparation prior to analysis by MS. The goal of this study was to compare 2-D PAGE-resolved protein profile of lymphatic endothelial cells to those of venous, and arterial endothelial cells isolated from lymphatic and blood vessels of bovine mesentery (bm). Three 2-D PAGE electrophoretograms were produced for each of the three cell types and quantitatively analyzed. Protein identification by LC-MS/MS was performed to identify 39 proteins found to be present at statistically significantly different levels in the three cell types (p<0.05). Most of the 39 proteins have not been previously reported in EC proteomic studies of 2-D PAGE electrophoretograms. Three proteins, HSPA1B (HSP70 family member), HSPB1 (HSP27 family member), and UBE2D3 (a member of E2 ubiquitin-conjugating enzymes) found to be at highest levels in bm arterial endothelial cells, bm venous endothelial cells, and bm lymphatic endothelial cells, respectively, were validated by immunoblotting with appropriate antibodies. The lack of substantial overlap between our results and those of other groups' comparative studies are discussed. Functional implications of differences in levels of various proteins identified in the three cell types are also discussed.
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Affiliation(s)
- Vicky P K H Nguyen
- Molecular and Cellular Biology Research, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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Safran M, Dalah I, Alexander J, Rosen N, Iny Stein T, Shmoish M, Nativ N, Bahir I, Doniger T, Krug H, Sirota-Madi A, Olender T, Golan Y, Stelzer G, Harel A, Lancet D. GeneCards Version 3: the human gene integrator. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2010; 2010:baq020. [PMID: 20689021 PMCID: PMC2938269 DOI: 10.1093/database/baq020] [Citation(s) in RCA: 1045] [Impact Index Per Article: 74.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73 000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards’ unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene’s functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite. Database URL:www.genecards.org
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Affiliation(s)
- Marilyn Safran
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
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Re-annotation is an essential step in systems biology modeling of functional genomics data. PLoS One 2010; 5:e10642. [PMID: 20498845 PMCID: PMC2871057 DOI: 10.1371/journal.pone.0010642] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2009] [Accepted: 04/14/2010] [Indexed: 11/19/2022] Open
Abstract
One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data.
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Stelzer G, Inger A, Olender T, Iny-Stein T, Dalah I, Harel A, Safran M, Lancet D. GeneDecks: paralog hunting and gene-set distillation with GeneCards annotation. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2010; 13:477-87. [PMID: 20001862 DOI: 10.1089/omi.2009.0069] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Sophisticated genomic navigation strongly benefits from a capacity to establish a similarity metric among genes. GeneDecks is a novel analysis tool that provides such a metric by highlighting shared descriptors between pairs of genes, based on the rich annotation within the GeneCards compendium of human genes. The current implementation addresses information about pathways, protein domains, Gene Ontology (GO) terms, mouse phenotypes, mRNA expression patterns, disorders, drug relationships, and sequence-based paralogy. GeneDecks has two modes: (1) Paralog Hunter, which seeks functional paralogs based on combinatorial similarity of attributes; and (2) Set Distiller, which ranks descriptors by their degree of sharing within a given gene set. GeneDecks enables the elucidation of unsuspected putative functional paralogs, and a refined scrutiny of various gene-sets (e.g., from high-throughput experiments) for discovering relevant biological patterns.
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Affiliation(s)
- Gil Stelzer
- Departments of Molecular Genetics, Weizmann Institute of Science , Rehovot 76100, Israel.
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