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Yan T, Pang X, Liang B, Meng Q, Wei H, Li W, Liu D, Hu Y. Comprehensive bioinformatics analysis of human cytomegalovirus pathway genes in pan-cancer. Hum Genomics 2024; 18:65. [PMID: 38886862 PMCID: PMC11181644 DOI: 10.1186/s40246-024-00633-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 06/05/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Human cytomegalovirus (HCMV) is a herpesvirus that can infect various cell types and modulate host gene expression and immune response. It has been associated with the pathogenesis of various cancers, but its molecular mechanisms remain elusive. METHODS We comprehensively analyzed the expression of HCMV pathway genes across 26 cancer types using the Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We also used bioinformatics tools to study immune invasion and tumor microenvironment in pan-cancer. Cox regression and machine learning were used to analyze prognostic genes and their relationship with drug sensitivity. RESULTS We found that HCMV pathway genes are widely expressed in various cancers. Immune infiltration and the tumor microenvironment revealed that HCMV is involved in complex immune processes. We obtained prognostic genes for 25 cancers and significantly found 23 key genes in the HCMV pathway, which are significantly enriched in cellular chemotaxis and synaptic function and may be involved in disease progression. Notably, CaM family genes were up-regulated and AC family genes were down-regulated in most tumors. These hub genes correlate with sensitivity or resistance to various drugs, suggesting their potential as therapeutic targets. CONCLUSIONS Our study has revealed the role of the HCMV pathway in various cancers and provided insights into its molecular mechanism and therapeutic significance. It is worth noting that the key genes of the HCMV pathway may open up new doors for cancer prevention and treatment.
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Affiliation(s)
- Tengyue Yan
- Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, Guangxi, 530021, China
| | - Xianwu Pang
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, 530028, China
| | - Boying Liang
- Department of Immunology, School of Basic Medical Sciences, Guangxi Medical University, Nanning, China
| | - Qiuxia Meng
- School of Information and Managent, Guangxi Medical University, Nanning, China
| | - Huilin Wei
- School of Institute of Life Sciences, Guangxi Medical University, Nanning, China
| | - Wen Li
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China
| | - Dahai Liu
- School of Medicine, Foshan University, Foshan, Guangdong, 528000, People's Republic of China.
| | - Yanling Hu
- Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, Guangxi, 530021, China.
- School of Institute of Life Sciences, Guangxi Medical University, Nanning, China.
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2
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Su W, Tian Y, Wei Y, Hao F, Ji J. Key genes and immune infiltration in chronic spontaneous urticaria: a study of bioinformatics and systems biology. Front Immunol 2023; 14:1279139. [PMID: 38045687 PMCID: PMC10693338 DOI: 10.3389/fimmu.2023.1279139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/02/2023] [Indexed: 12/05/2023] Open
Abstract
Background Chronic spontaneous urticaria (CSU) is defined by the spontaneous occurrence of wheals and/or angioedema for >6 weeks. The pathogenesis involves skin mast cells, but the complex causes of their activation remain to be characterized in detail. Objectives To explore disease-driving genes and biological pathways in CSU. Methods Two microarray data sets, e.g., GSE57178 and GSE72540, with mRNA information of skin from CSU patients, were downloaded from the Gene Expression Omnibus (GEO) database. An integrated bioinformatics pipeline including identification of differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction (PPI) network analysis, co-expression and drug prediction analysis, and immune and stromal cells deconvolution analyses were applied to identify hub genes and key drivers of CSU pathogenesis. Results In total, we identified 92 up-regulated and 7 down-regulated genes in CSU lesions. These were significantly enriched in CSU-related pathways such as TNF, NF-κB, and JAK-STAT signaling. Based on PPI network modeling, four genes, i.e., IL-6, TLR-4, ICAM-1, and PTGS-2, were computationally identified as key pathogenic players in CSU. Immune infiltration analyses indicated that dendritic cells, Th2 cells, mast cells, megakaryocyte-erythroid progenitor, preadipocytes, and M1 macrophages were increased in lesional CSU skin. Conclusion Our results offer new insights on the pathogenesis of CSU and suggest that TNF, NF-κB, JAK-STAT, IL-6, TLR-4, ICAM-1, and PTGS-2 may be candidate targets for novel CSU treatments.
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Affiliation(s)
- Wenxing Su
- Department of Dermatology, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Dermatology and Plastic Surgery Center, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yu Tian
- Department of Dermatology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Yuqian Wei
- Department of Dermatology, Nantong Third People’s Hospital, Nantong, China
| | - Fei Hao
- Dermatology and Plastic Surgery Center, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiang Ji
- Department of Dermatology, The Second Affiliated Hospital of Soochow University, Suzhou, China
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3
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Long S, Wu B, Yang L, Wang L, Wang B, Yan Y, Jiang J, Yang B, Zhou Q, Shi M, Liang W, Wei W, Li X. Novel tumor necrosis factor-related long non-coding RNAs signature for risk stratification and prognosis in glioblastoma. Front Neurol 2023; 14:1054686. [PMID: 37153654 PMCID: PMC10156969 DOI: 10.3389/fneur.2023.1054686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 03/30/2023] [Indexed: 05/10/2023] Open
Abstract
Background Tumor necrosis factor (TNF) is an inflammatory cytokine that can coordinate tissue homeostasis by co-regulating the production of cytokines, cell survival, or death. It widely expresses in various tumor tissues and correlates with the malignant clinical features of patients. As an important inflammatory factor, the role of TNFα is involved in all steps of tumorigenesis and development, including cell transformation, survival, proliferation, invasion and metastasis. Recent research has showed that long non-coding RNAs (lncRNAs), defined as RNA transcripts >200 nucleotides that do not encode a protein, influence numerous cellular processes. However, little is known about the genomic profile of TNF pathway related-lncRNAs in GBM. This study investigated the molecular mechanism of TNF related-lncRNAs and their immune characteristics in glioblastoma multiforme (GBM) patients. Methods To identify TNF associations in GBM patients, we performed bioinformatics analysis of public databases - The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). The ConsensusClusterPlus, CIBERSORT, Estimate, GSVA and TIDE and first-order bias correlation and so on approaches were conducted to comprehensively characterize and compare differences among TNF-related subtypes. Results Based on the comprehensive analysis of TNF-related lncRNAs expression profiles, we constructed six TNF-related lncRNAs (C1RL-AS1, LINC00968, MIR155HG, CPB2-AS1, LINC00906, and WDR11-AS1) risk signature to determine the role of TNF-related lncRNAs in GBM. This signature could divide GBM patients into subtypes with distinct clinical and immune characteristics and prognoses. We identified three molecular subtypes (C1, C2, and C3), with C2 showing the best prognosis; otherwise, C3 showing the worst prognosis. Moreover, we assessed the prognostic value, immune infiltration, immune checkpoints, chemokines cytokines and enrichment analysis of this signature in GBM. The TNF-related lncRNA signature was tightly associated with the regulation of tumor immune therapy and could serve as an independent prognostic biomarker in GBM. Conclusion This analysis provides a comprehensive understanding of the role of TNF-related characters, which may improve the clinical outcome of GBM patients.
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Affiliation(s)
- Shengrong Long
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bingbing Wu
- Department of Neurosurgery, Yongchuan Hospital of Chongqing Medical University, Chongqing, China
| | - Liu Yang
- Department of Neurosurgery, Central Theater General Hospital of the Chinese People's Liberation Army, Wuhan, China
| | - Lesheng Wang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bo Wang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yu Yan
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Jiazhi Jiang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bin Yang
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Qiangqiang Zhou
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Min Shi
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Wu Liang
- Department of Neurosurgery, The Affiliated Minda Hospital of Hubei University for Nationalities, Enshi, China
| | - Wei Wei
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Wei Wei,
| | - Xiang Li
- Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China
- Brain Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
- Medical Research Institute, Wuhan University, Wuhan, China
- Xiang Li,
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Su R, Zhang H, Zhang L, Khan AR, Zhang X, Wang R, Shao C, Wei X, Xu X. Systemic analysis identifying
PVT1
/
DUSP13
axis for microvascular invasion in hepatocellular carcinoma. Cancer Med 2022; 12:8937-8955. [PMID: 36524545 PMCID: PMC10134337 DOI: 10.1002/cam4.5546] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 10/26/2022] [Accepted: 11/04/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is an independent detrimental risk factor for tumor recurrence and poor survival in hepatocellular carcinoma (HCC). Competitive endogenous RNA (ceRNA) networks play a pivotal role in the modulation of carcinogenesis and progression among diverse tumor types. However, whether the ceRNA mechanisms are engaged in promoting the MVI process in patients with HCC remains unknown. METHODS A ceRNA regulatory network was constructed based on RNA-seq data of patients with HCC from The Cancer Genome Atlas (TCGA) database. In total, 10 hub genes of the ceRNA network were identified using four algorithms: "MCC," "Degree," "Betweenness," and "Stress." Transcriptional expressions were verified by in situ hybridization using clinical samples. Interactions between ceRNA modules were validated by luciferase reporting assay. Logistic regression analysis, correlation analysis, enrichment analysis, promoter region analysis, methylation analysis, and immune infiltration analysis were performed to further investigate the molecular mechanisms and clinical transformation value. RESULTS The ceRNA regulatory network featuring a tumor invasion phenotype consisting of 3 long noncoding RNAs, 3 microRNAs, and 93 mRNAs was constructed using transcriptional data from the TCGA database. Systemic analysis and experimentally validation identified a ceRNA network (PVT1/miR-1258/DUSP13 axis) characterized by lipid regulatory potential, immune properties, and abnormal methylation states in patients with HCC and MVI. Meanwhile, 28 transcriptional factors were identified as potential promotors of PVT1 with 3 transcriptional factors MXD3, ZNF580, and KDM1A promising as therapeutic targets in patients with HCC and MVI. Furthermore, miR-1258 was an independent predictor for MVI in patients with HCC. CONCLUSION The PVT1/DUSP13 axis is significantly associated with MVI progression in HCC patients. This study provides new insight into mechanisms related to lipids, immune phenotypes, and abnormal epigenetics in oncology research.
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Affiliation(s)
- Renyi Su
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China
| | - Huizhong Zhang
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China
| | - Lincheng Zhang
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China
| | - Abdul Rehman Khan
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China
| | - Xuanyu Zhang
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital Zhejiang University School of Medicine Hangzhou China
| | - Rui Wang
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
| | - Chuxiao Shao
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Lishui Hospital Zhejiang University School of Medicine Lishui China
| | - Xuyong Wei
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China
| | - Xiao Xu
- Institute of Organ Transplantation, Zhejiang University Hangzhou China
- Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China
- Westlake Laboratory of Life Sciences and Biomedicine Hangzhou China
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5
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Ping S, Gong R, Lei K, Qing G, Zhang G, Chen J. Development and validation of a ferroptosis-related lncRNAs signature to predict prognosis and microenvironment for melanoma. Discov Oncol 2022; 13:125. [PMID: 36371574 PMCID: PMC9653531 DOI: 10.1007/s12672-022-00581-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 10/25/2022] [Indexed: 11/13/2022] Open
Abstract
Ferroptosis plays an important role in cancer. However, studies about ferroptosis-related lncRNAs (FRLs) in skin cutaneous melanoma (SKCM) are scarce. Moreover, the relationship between prognostic FRLs and tumor microenvironment (TME) in melanoma remains unclear. This study investigates the potential prognostic value of FRLs and their association with TME in SKCM. The RNA-sequencing data of SKCM were downloaded from The Cancer Genome Atlas (TCGA) database. Melanoma patients were randomly divided into training and testing groups in a 1:1 ratio. A signature composed of 19 FRLs was developed by the least absolute shrinkage and selection operator (LASSO) regression analysis to divide patients into a low-risk group with a better prognosis and a high-risk group with a poor prognosis. Multivariate Cox regression analysis suggested that the risk score was an independent prognostic factor. The Area Under Curve (AUC) value of the risk score reached 0.768 in the training group and 0.770 in the testing group. Subsequent analysis proved that immune-related signaling pathways were significantly enriched in the low-risk group. The tumor immune cell infiltration analysis demonstrated that melanoma in the high-risk group tended to be immunologically "cold". We identified a novel FRLs signature which could accurately predict the prognosis of patients with melanoma.
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Affiliation(s)
- Shuai Ping
- Department of Gastroenterology, Tumor Immunology and Cytotherapy, Medical Research Center, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Huangdao District, Qingdao, 266000 China
| | - Ruining Gong
- Department of Gastroenterology, Tumor Immunology and Cytotherapy, Medical Research Center, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Huangdao District, Qingdao, 266000 China
| | - Ke Lei
- Tumor Immunology and Cytotherapy, Medical Research Center, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Huangdao District, Qingdao, 266000 China
| | - Gong Qing
- Department of Gastroenterology, Tumor Immunology and Cytotherapy, Medical Research Center, The Affiliated Hospital of Qingdao University, No. 1677 Wutaishan Road, Huangdao District, Qingdao, 266000 China
| | - Guangheng Zhang
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430077 China
| | - Jianghai Chen
- Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022 Hubei China
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6
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Wang W, Lu Z, Wang M, Liu Z, Wu B, Yang C, Huan H, Gong P. The cuproptosis-related signature associated with the tumor environment and prognosis of patients with glioma. Front Immunol 2022; 13:998236. [PMID: 36110851 PMCID: PMC9468372 DOI: 10.3389/fimmu.2022.998236] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 08/03/2022] [Indexed: 12/29/2022] Open
Abstract
Background Copper ions are essential for cellular physiology. Cuproptosis is a novel method of copper-dependent cell death, and the cuproptosis-based signature for glioma remains less studied. Methods Several glioma datasets with clinicopathological information were collected from TCGA, GEO and CGGA. Robust Multichip Average (RMA) algorithm was used for background correction and normalization, cuproptosis-related genes (CRGs) were then collected. The TCGA-glioma cohort was clustered using ConsensusClusterPlus. Univariate Cox regression analysis and the Random Survival Forest model were performed on the differentially expressed genes to identify prognostic genes. The cuproptosis-signature was constructed by calculating CuproptosisScore using Multivariate Cox regression analysis. Differences in terms of genomic mutation, tumor microenvironment, and enrichment pathways were evaluated between high- or low-CuproptosisScore. Furthermore, drug response prediction was carried out utilizing pRRophetic. Results Two subclusters based on CRGs were identified. Patients in cluster2 had better clinical outcomes. The cuproptosis-signature was constructed based on CuproptosisScore. Patients with higher CuproptosisScore had higher WHO grades and worse prognosis, while patients with lower grades were more likely to develop IDH mutations or MGMT methylation. Univariate and Multivariate Cox regression analysis demonstrated CuproptosisScore was an independent prognostic factor. The accuracy of the signature in prognostic prediction was further confirmed in 11 external validation datasets. In groups with high-CuproptosisScore, PIK3CA, MUC16, NF1, TTN, TP53, PTEN, and EGFR showed high mutation frequency. IDH1, TP53, ATRX, CIC, and FUBP1 demonstrated high mutation frequency in low-CuproptosisScore group. The level of immune infiltration increased as CuproptosisScore increased. SubMap analysis revealed patients with high-CuproptosisScore may respond to anti-PD-1 therapy. The IC50 values of Bexarotene, Bicalutamide, Bortezomib, and Cytarabine were lower in the high-CuproptosisScore group than those in the low-CuproptosisScore group. Finally, the importance of IGFBP2 in TCGA-glioma cohort was confirmed. Conclusion The current study revealed the novel cuproptosis-based signature might help predict the prognosis, biological features, and appropriate treatment for patients with glioma.
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7
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Hephzibah Cathryn R, Udhaya Kumar S, Younes S, Zayed H, George Priya Doss C. A review of bioinformatics tools and web servers in different microarray platforms used in cancer research. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 131:85-164. [PMID: 35871897 DOI: 10.1016/bs.apcsb.2022.05.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Over the past decade, conventional lab work strategies have gradually shifted from being limited to a laboratory setting towards a bioinformatics era to help manage and process the vast amounts of data generated by omics technologies. The present work outlines the latest contributions of bioinformatics in analyzing microarray data and their application to cancer. We dissect different microarray platforms and their use in gene expression in cancer models. We highlight how computational advances empowered the microarray technology in gene expression analysis. The study on protein-protein interaction databases classified into primary, derived, meta-database, and prediction databases describes the strategies to curate and predict novel interaction networks in silico. In addition, we summarize the areas of bioinformatics where neural graph networks are currently being used, such as protein functions, protein interaction prediction, and in silico drug discovery and development. We also discuss the role of deep learning as a potential tool in the prognosis, diagnosis, and treatment of cancer. Integrating these resources efficiently, practically, and ethically is likely to be the most challenging task for the healthcare industry over the next decade; however, we believe that it is achievable in the long term.
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Affiliation(s)
- R Hephzibah Cathryn
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - S Udhaya Kumar
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Salma Younes
- Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar
| | - Hatem Zayed
- Department of Biomedical Sciences, College of Health and Sciences, Qatar University, QU Health, Doha, Qatar
| | - C George Priya Doss
- Laboratory of Integrative Genomics, Department of Integrative Biology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India.
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Lin Y, Zhou X, Peng W, Wu J, Wu X, Chen Y, Cui Z. Expression and clinical implications of basic leucine zipper ATF-like transcription factor 2 in breast cancer. BMC Cancer 2021; 21:1062. [PMID: 34565331 PMCID: PMC8474811 DOI: 10.1186/s12885-021-08785-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 09/15/2021] [Indexed: 12/28/2022] Open
Abstract
Background Basic leucine zipper ATF-like transcription factor 2 (BATF2) has been reported to participate in the occurrence and development of some malignancies. Herein, we aimed to explore the expression pattern and clinical implications of BATF2 in breast cancer (BC). Methods We assessed the differences in BATF2 mRNA expression between cancerous and noncancerous tissues in BC using GEPIA and UALCAN data and in BATF2 protein expression pattern using Human Protein Atlas (HPA) data. BATF2 co-expression networks were analyzed in Coexpedia. The association between the differentially expressed BATF2 mRNA and BC prognosis was assessed using UALCAN, OSbrca, and GEPIA databases. In external validations, BATF2 protein expression in BC tissues was quantitated using a tissue microarray and immunohistochemistry (IHC) analysis, and BATF2 mRNA expression in serum and serum-derived exosomes of BC patients using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results No difference in the BATF2 mRNA expression level was found between cancerous and noncancerous tissues in BC based on databases. There were low-to-moderate levels of increases in BATF2 protein expressions in BC cases from the HPA cohort. BATF2 mRNA expression was negatively correlated with androgen receptor (AR) and positively correlated with BRCA2 DNA repair associated (BRCA2), marker of proliferation Ki-67 (Mki67), and tumor protein p53 (TP53) expressions. Generally, BATF2 mRNA exhibited a non-significant association with BC prognosis; yet the subgroup analyses showed that triple-negative breast cancer (TNBC) patients with high BATF2 mRNA expressions had a longer overall survival (OS). Our IHC analysis revealed a positive rate of BATF2 protein expression of 46.90%, mainly located in the nucleus of cancer cells in BC, and the OS of BC patients with high BATF2 protein expressions was prolonged. The positive rates of BATF2 mRNA expressions in the serum and exosomes were 45.00 and 41.67%, respectively. Besides, the AUCs of serum and exosomal BATF2 mRNA for BC diagnosis were 0.8929 and 0.8869, respectively. Conclusions BC patients exhibit low-to-moderate expressions in BATF2 mRNA expression levels in cancerous tissues. The high BATF2 protein expression can be a potential indicator of a better BC prognosis. Serum and exosomal BATF2 mRNA levels also serve as promising noninvasive biomarkers for BC diagnosis. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08785-6.
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Affiliation(s)
- Yingying Lin
- Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory, Fujian Medical University Cancer Hospital, No. 420 Fuma Road, Jin'an District, Fuzhou, 350014, Fujian Province, China
| | - Xusheng Zhou
- Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory, Fujian Medical University Cancer Hospital, No. 420 Fuma Road, Jin'an District, Fuzhou, 350014, Fujian Province, China
| | - Wei Peng
- Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory, Fujian Medical University Cancer Hospital, No. 420 Fuma Road, Jin'an District, Fuzhou, 350014, Fujian Province, China
| | - Jing Wu
- Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory, Fujian Medical University Cancer Hospital, No. 420 Fuma Road, Jin'an District, Fuzhou, 350014, Fujian Province, China
| | - Xiufeng Wu
- Department of Breast Surgical Oncology, Fujian Medical University Cancer Hospital, Fuzhou, Fujian, China.
| | - Yan Chen
- Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory, Fujian Medical University Cancer Hospital, No. 420 Fuma Road, Jin'an District, Fuzhou, 350014, Fujian Province, China.
| | - Zhaolei Cui
- Laboratory of Biochemistry and Molecular Biology Research, Department of Clinical Laboratory, Fujian Medical University Cancer Hospital, No. 420 Fuma Road, Jin'an District, Fuzhou, 350014, Fujian Province, China.
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Huang K, Yue X, Zheng Y, Zhang Z, Cheng M, Li L, Chen Z, Yang Z, Bian E, Zhao B. Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma. Front Oncol 2021; 11:726745. [PMID: 34540695 PMCID: PMC8446619 DOI: 10.3389/fonc.2021.726745] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 08/16/2021] [Indexed: 12/29/2022] Open
Abstract
Glioma is well known as the most aggressive and prevalent primary malignant tumor in the central nervous system. Molecular subtypes and prognosis biomarkers remain a promising research area of gliomas. Notably, the aberrant expression of mesenchymal (MES) subtype related long non-coding RNAs (lncRNAs) is significantly associated with the prognosis of glioma patients. In this study, MES-related genes were obtained from The Cancer Genome Atlas (TCGA) and the Ivy Glioblastoma Atlas Project (Ivy GAP) data sets of glioma, and MES-related lncRNAs were acquired by performing co-expression analysis of these genes. Next, Cox regression analysis was used to establish a prognostic model, that integrated ten MES-related lncRNAs. Glioma patients in TCGA were divided into high-risk and low-risk groups based on the median risk score; compared with the low-risk groups, patients in the high-risk group had shorter survival times. Additionally, we measured the specificity and sensitivity of our model with the ROC curve. Univariate and multivariate Cox analyses showed that the prognostic model was an independent prognostic factor for glioma. To verify the predictive power of these candidate lncRNAs, the corresponding RNA-seq data were downloaded from the Chinese Glioma Genome Atlas (CGGA), and similar results were obtained. Next, we performed the immune cell infiltration profile of patients between two risk groups, and gene set enrichment analysis (GSEA) was performed to detect functional annotation. Finally, the protective factors DGCR10 and HAR1B, and risk factor SNHG18 were selected for functional verification. Knockdown of DGCR10 and HAR1B promoted, whereas knockdown of SNHG18 inhibited the migration and invasion of gliomas. Collectively, we successfully constructed a prognostic model based on a ten MES-related lncRNAs signature, which provides a novel target for predicting the prognosis for glioma patients.
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Affiliation(s)
- Kebing Huang
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Xiaoyu Yue
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Yinfei Zheng
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Zhengwei Zhang
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Meng Cheng
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Lianxin Li
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Zhigang Chen
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Zhihao Yang
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Erbao Bian
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
| | - Bing Zhao
- Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.,Cerebral Vascular Disease Research Center, Anhui Medical University, Hefei, China
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10
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Zhong C, Wu K, Wang S, Long Z, Yang T, Zhong W, Tan X, Wang Z, Li C, Lu J, Mao X. Autophagy-related circRNA evaluation reveals hsa_circ_0001747 as a potential favorable prognostic factor for biochemical recurrence in patients with prostate cancer. Cell Death Dis 2021; 12:726. [PMID: 34294687 PMCID: PMC8298711 DOI: 10.1038/s41419-021-04015-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 06/25/2021] [Accepted: 07/08/2021] [Indexed: 01/18/2023]
Abstract
Prostate cancer (PCa) is a common high-incidence malignancy in men, some of whom develop biochemical recurrence (BCR) in the advanced stage. However, there are currently no accurate prognostic indicators of BCR in PCa. The aim of our study was to identify an autophagy-related circular RNA prognostic factor of BCR for patients with PCa. In this study, immunochemistry revealed that the classic autophagy marker MAP1LC3B was positively correlated with Gleason score. Least absolute shrinkage and selector operator regression were conducted to develop a novel prognostic model with tenfold cross-validation and an L1 penalty. Five autophagy-related circRNA signatures were included in the prognostic model. Patients with PCa were ultimately divided into high- and low-risk groups, based on the median risk score. Patients with PCa, who had a high risk score, were more likely to develop BCR in a shorter period of time. Univariate and multivariate Cox regression analyses demonstrated that the risk score was an independent variable for predicting BCR in PCa. In addition, a prognostic nomogram integrated with the risk score and numerous clinicopathological parameters was developed to accurately predict 3- and 5-year BCR of patients with PCa. Finally, the hsa_circ_0001747 signature was selected for further experimental verification in vitro and in vivo, which showed that downregulated hsa_circ_0001747 might facilitate PCa via augmenting autophagy. Our findings indicate that the autophagy-related circRNA signature hsa_circ_0001747 may serve as a promising indicator for BCR prediction in patients with PCa.
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Affiliation(s)
- Chuanfan Zhong
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Kaihui Wu
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Shuo Wang
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Zining Long
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Taowei Yang
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Weibo Zhong
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Xiao Tan
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | | | - Chuanyin Li
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| | - Jianming Lu
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| | - Xiangming Mao
- Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
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11
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Politi FAS, Bueno RV, Zeoly LA, Fantatto RR, Eloy JDO, Chorilli M, Coelho F, Guido RVC, Chagas ACDS, Furlan M. Anthelmintic activity of a nanoformulation based on thiophenes identified in Tagetes patula L. (Asteraceae) against the small ruminant nematode Haemonchus contortus. Acta Trop 2021; 219:105920. [PMID: 33861973 DOI: 10.1016/j.actatropica.2021.105920] [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: 09/22/2020] [Revised: 02/02/2021] [Accepted: 04/07/2021] [Indexed: 11/25/2022]
Abstract
The synthesis of thiophenic compounds, previously identified in Tagetes patula, revealed that 4-(5'-(hydroxymethyl)-[2,2'-bithiophene]-5-yl)but-3-yn-1-ol), or simply Thio1, has a pronounced in vitro anthelmintic effect against Haemonchus contortus, showing 100% efficacy in the egg hatch and larval development tests presenting EC50 = 0.1731 mg.mL-1 and EC50 = 0.3243 mg.mL-1, respectively. So, this compound was selected to preparation of a nanostructured formulation to be orally administered to Santa Inês sheep. In general, from the fecal egg count reduction test (FECRT), it was observed that the product kept the parasitic load in the digestive tract of the hosts stable, with eggs per gram of faeces (EPG) counts having a mean value < 3,000 (EPGmean = 2167.1, efficacy = 36,45%), thus protecting the animals from health risks caused by a massive nematode infestation. To better understand the mode of action of this thiophene derivative, in silico molecular modeling studies were carried out with the glutamate-activated chloride channel (GluCl), a well-known molecular target of anthelmintic compounds. Based on the affinity score (GlideScore = -5.7 kcal.mol-1) and the proposed binding mode, Thio1 could be classified as a potential GluCl ligand, justifying the promising results observed in the anthelmintic assays.
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12
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Zhang K, Ping L, Du T, Liang G, Huang Y, Li Z, Deng R, Tang J. A Ferroptosis-Related lncRNAs Signature Predicts Prognosis and Immune Microenvironment for Breast Cancer. Front Mol Biosci 2021; 8:678877. [PMID: 34164433 PMCID: PMC8215711 DOI: 10.3389/fmolb.2021.678877] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/25/2021] [Indexed: 01/10/2023] Open
Abstract
Background: Ferroptosis, a regulated cell death which is driven by the iron-dependent peroxidation of lipids, plays an important role in cancer. However, studies about ferroptosis-related Long non-coding RNAs (lncRNAs) in breast cancer (BC) are limited. Besides, the prognostic role of ferroptosis-related lncRNAs and their relationship to immune microenvironment in breast cancer remain unclear. This study aimed to explore the potential prognostic value of ferroptosis-related lncRNAs and their relationship to immune microenvironment in breast cancer. Methods: RNA-sequencing data of female breast cancer patients were downloaded from TCGA database. 937 patients were randomly separated into training or validation cohort in 2:1 ratio. Ferroptosis-related lncRNAs were screened by Pearson correlation analysis with 239 reported ferroptosis-related genes. A ferroptosis-related lncRNAs signature was constructed with univariate and multivariate Cox regression analyses in the training cohort, and its prognostic value was further tested in the validation cohort. Results: An 8-ferroptosis-related-lncRNAs signature was developed by multivariate Cox regression analysis to divide patients into two risk groups. Patients in the high-risk group had worse prognosis than patients in the low-risk group. Multivariate Cox regression analysis showed the risk score was an independent prognostic indicator. Receiver operating characteristic curve (ROC) analysis proved the predictive accuracy of the signature. The area under time-dependent ROC curve (AUC) reached 0.853 at 1 year, 0.802 at 2 years, 0.740 at 5 years in the training cohort and 0.791 at 1 year, 0.778 at 2 years, 0.722 at 5 years in the validation cohort. Further analysis demonstrated that immune-related pathways were significantly enriched in the high-risk group. Analysis of the immune cell infiltration landscape showed that breast cancer in the high-risk group tended be immunologically “cold”. Conclusion: We identified a novel ferroptosis-related lncRNA signature which could precisely predict the prognosis of breast cancer patients. Ferroptosis-related lncRNAs may have a potential role in the process of anti-tumor immunity and serve as therapeutic targets for breast cancer.
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Affiliation(s)
- Kaiming Zhang
- Department of Breast Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Liqin Ping
- Department of Medical Oncology, State Key Laboratory of On cology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Tian Du
- Department of Breast Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Gehao Liang
- Department of Breast Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Yun Huang
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Zhiling Li
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Rong Deng
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Jun Tang
- Department of Breast Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
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13
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Sun Z, Jing C, Xiao C, Li T. An autophagy-related long non-coding RNA prognostic signature accurately predicts survival outcomes in bladder urothelial carcinoma patients. Aging (Albany NY) 2021; 12:15624-15637. [PMID: 32805727 PMCID: PMC7467376 DOI: 10.18632/aging.103718] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 07/06/2020] [Indexed: 12/16/2022]
Abstract
In this study, we analyzed the prediction accuracy of an autophagy-related long non-coding RNA (lncRNA) prognostic signature using bladder urothelial carcinoma (BLCA) patient data from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses showed significant correlations between five autophagy-related lncRNAs, LINC02178, AC108449.2, Z83843.1, FAM13A-AS1 and USP30-AS1, and overall survival (OS) among BCLA patients. The risk scores based on the autophagy-related lncRNA prognostic signature accurately distinguished high- and low-risk BCLA patients that were stratified according to age; gender; grade; and AJCC, T, and N stages. The autophagy-related lncRNA signature was an independent prognostic predictor with an AUC value of 0.710. The clinical nomogram with the autophagy-related lncRNA prognostic signature showed a high concordance index of 0.73 and accurately predicted 1-, 3-, and 5-year survival times among BCLA patients in the high- and low-risk groups. The lncRNA-mRNA co-expression network contained 77 lncRNA-mRNA links among 5 lncRNAs and 49 related mRNAs. Gene set enrichment analysis showed that cancer- and autophagy-related pathways were significantly enriched in the high-risk group, and immunoregulatory pathways were enriched in the low-risk group. These findings demonstrate that an autophagy-related lncRNA signature accurately predicts the prognosis of BCLA patients.
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Affiliation(s)
- Zhuolun Sun
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, China.,Equal contribution
| | - Changying Jing
- The Second Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.,Equal contribution
| | - Chutian Xiao
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, China
| | - Tengcheng Li
- Department of Urology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, China
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14
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Role of Bioinformatics in Biological Sciences. Adv Bioinformatics 2021. [DOI: 10.1007/978-981-33-6191-1_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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15
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Kaufmann J, Wentzensen N, Brinker TJ, Grabe N. Large-scale in-silico identification of a tumor-specific antigen pool for targeted immunotherapy in triple-negative breast cancer. Oncotarget 2019; 10:2515-2529. [PMID: 31069014 PMCID: PMC6493464 DOI: 10.18632/oncotarget.26808] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 02/15/2019] [Indexed: 12/16/2022] Open
Abstract
Since the advent of cetuximab, clinical cancer treatment has evolved from the standard, relatively nonspecific chemo- and radiotherapy with significant cytotoxic side effects towards immunotherapeutic approaches with selective, target-mechanism-based effects. Antibody therapies as the most successful form of cancer immunotherapy led to approved treatments for specific cancer types with increased patient survival. Thus, the identification of tumor antigens with high immunogenicity is in central focus now. In this study, we applied computational methods to comprehensively discover overexpressed molecular targets with high therapeutic relevance for clinical, immunotherapeutic cancer treatment in triple-negative breast cancer (TNBC). By actively modeling potential negative side effects utilizing expression data of 29 different, normal human tissues, we were able to develop a highly-specific coverage of TNBC patients with RNA targets. We identified here more than 400 potential tumor-specific antigens suitable for targeted therapy, including several already identified as potential targets for TNBC and other solid tumors. A specific cocktail of MAGEB4, CT83, TLX3, ACTL8, PRDM13 achieved almost 94% patient coverage in TNBC. Overall, these results show that our approach can identify and prioritize TNBC targets suitable for targeted therapy. Therefore, our method has the potential to lead to new and more effective immunotherapeutic cancer treatment.
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Affiliation(s)
- Jessica Kaufmann
- Hamamatsu Tissue Imaging and Analysis Center (TIGA), BIOQUANT, University of Heidelberg, Heidelberg, Germany.,Medical Oncology Department, Universitätsklinik Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Nicolas Wentzensen
- National Cancer Institute, Division of Cancer Epidemiology & Genetics, Clinical Genetics Branch, NCI Shady Grove, Bethesda, Maryland, USA
| | - Titus J Brinker
- National Center for Tumor Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Dermatology, University Hospital Heidelberg, Heidelberg, Germany
| | - Niels Grabe
- Hamamatsu Tissue Imaging and Analysis Center (TIGA), BIOQUANT, University of Heidelberg, Heidelberg, Germany.,Medical Oncology Department, Universitätsklinik Heidelberg, National Center for Tumor Diseases (NCT), Heidelberg, Germany
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16
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Chávez-Fumagalli MA, Lage DP, Tavares GSV, Mendonça DVC, Dias DS, Ribeiro PAF, Ludolf F, Costa LE, Coelho VTS, Coelho EAF. In silico Leishmania proteome mining applied to identify drug target potential to be used to treat against visceral and tegumentary leishmaniasis. J Mol Graph Model 2018; 87:89-97. [PMID: 30522092 DOI: 10.1016/j.jmgm.2018.11.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 11/12/2018] [Accepted: 11/28/2018] [Indexed: 12/11/2022]
Abstract
New therapeutic strategies against leishmaniasis are desirable, since the treatment against disease presents problems, such as the toxicity, high cost and/or parasite resistance. As consequence, new antileishmanial compounds are necessary to be identified, as presenting high activity against Leishmania, but low toxicity in mammalian hosts. In the present study, a Leishmania proteome mining strategy was developed, in order to select new drug targets with low homology to human proteins, but that are considered relevant for the parasite' survival. Results showed a hypothetical protein, which was functionally annotated as a glucosidase-like protein, as presenting such characteristics. This protein was associated with the metabolic network of the N-Glycan biosynthesis pathway in Leishmania, and two specific inhibitors - acarbose and miglitol - were predicted to be potential targets against it. In this context, miglitol [1-(2-Hydroxyethyl)-2-(hydroxymethyl)piperidine-3,4,5-triol] was tested against stationary promastigotes and axenic amastigotes of the Leishmania amazonensis and L. infantum species, and results showed high values of antileishmanial inhibition against both parasite species. Miglitol showed also efficacy in the treatment of Leishmania-infected macrophages; thus denoting its potential use as an antileishmanial candidate. In conclusion, this work presents a new drug target identified by a proteome mining strategy associated with bioinformatics tools, and suggested its use as a possible candidate to be applied in the treatment against disease.
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Affiliation(s)
- Miguel A Chávez-Fumagalli
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Daniela P Lage
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Grasiele S V Tavares
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Débora V C Mendonça
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Daniel S Dias
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Patrícia A F Ribeiro
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Fernanda Ludolf
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Lourena E Costa
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Vinicio T S Coelho
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Eduardo A F Coelho
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil; Departamento de Patologia Clínica, COLTEC, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
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17
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Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res 2017; 45:W98-W102. [PMID: 28407145 PMCID: PMC5570223 DOI: 10.1093/nar/gkx247] [Citation(s) in RCA: 6198] [Impact Index Per Article: 885.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2017] [Revised: 03/27/2017] [Accepted: 04/05/2017] [Indexed: 12/11/2022] Open
Abstract
Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
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Affiliation(s)
- Zefang Tang
- BIOPIC, School of Life Sciences, Peking University, Beijing 100871, China
| | - Chenwei Li
- BIOPIC, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Boxi Kang
- BIOPIC, School of Life Sciences, Peking University, Beijing 100871, China
| | - Ge Gao
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Cheng Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- School of Life Sciences, Peking University, Beijing 100871, China
| | - Zemin Zhang
- BIOPIC, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA 95064, USA
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
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18
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Design, synthesis, biological evaluation and molecular docking study on peptidomimetic analogues of XK469. Eur J Med Chem 2016; 124:311-325. [DOI: 10.1016/j.ejmech.2016.08.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Revised: 08/05/2016] [Accepted: 08/06/2016] [Indexed: 11/19/2022]
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19
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Fauteux F, Hill JJ, Jaramillo ML, Pan Y, Phan S, Famili F, O'Connor-McCourt M. Computational selection of antibody-drug conjugate targets for breast cancer. Oncotarget 2016; 7:2555-71. [PMID: 26700623 PMCID: PMC4823055 DOI: 10.18632/oncotarget.6679] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2015] [Accepted: 11/21/2015] [Indexed: 01/03/2023] Open
Abstract
The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics.
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Affiliation(s)
- François Fauteux
- Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada
| | - Jennifer J. Hill
- Human Health Therapeutics, National Research Council Canada, Ottawa, Ontario, Canada
| | - Maria L. Jaramillo
- Human Health Therapeutics, National Research Council Canada, Montreal, Quebec, Canada
| | - Youlian Pan
- Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada
| | - Sieu Phan
- Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada
| | - Fazel Famili
- Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada
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20
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Jayaraman A, Jamil K, Khan HA. Identifying new targets in leukemogenesis using computational approaches. Saudi J Biol Sci 2015; 22:610-22. [PMID: 26288567 PMCID: PMC4537869 DOI: 10.1016/j.sjbs.2015.01.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Revised: 01/04/2015] [Accepted: 01/12/2015] [Indexed: 02/08/2023] Open
Abstract
There is a need to identify novel targets in Acute Lymphoblastic Leukemia (ALL), a hematopoietic cancer affecting children, to improve our understanding of disease biology and that can be used for developing new therapeutics. Hence, the aim of our study was to find new genes as targets using in silico studies; for this we retrieved the top 10% overexpressed genes from Oncomine public domain microarray expression database; 530 overexpressed genes were short-listed from Oncomine database. Then, using prioritization tools such as ENDEAVOUR, DIR and TOPPGene online tools, we found fifty-four genes common to the three prioritization tools which formed our candidate leukemogenic genes for this study. As per the protocol we selected thirty training genes from PubMed. The prioritized and training genes were then used to construct STRING functional association network, which was further analyzed using cytoHubba hub analysis tool to investigate new genes which could form drug targets in leukemia. Analysis of the STRING protein network built from these prioritized and training genes led to identification of two hub genes, SMAD2 and CDK9, which were not implicated in leukemogenesis earlier. Filtering out from several hundred genes in the network we also found MEN1, HDAC1 and LCK genes, which re-emphasized the important role of these genes in leukemogenesis. This is the first report on these five additional signature genes in leukemogenesis. We propose these as new targets for developing novel therapeutics and also as biomarkers in leukemogenesis, which could be important for prognosis and diagnosis.
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Affiliation(s)
- Archana Jayaraman
- Centre for Biotechnology and Bioinformatics, School of Life Sciences, Jawaharlal Nehru Institute of Advanced Studies (JNIAS), Secunderabad, Telangana, India
- Center for Biotechnology, Jawaharlal Nehru Technological University (JNTUH), Kukatpally, Hyderabad, Telangana, India
| | - Kaiser Jamil
- Centre for Biotechnology and Bioinformatics, School of Life Sciences, Jawaharlal Nehru Institute of Advanced Studies (JNIAS), Secunderabad, Telangana, India
- Corresponding author. at: Centre for Biotechnology and Bioinformatics, School of Life Sciences, Jawaharlal Nehru Institute of Advanced Studies (JNIAS), Buddha Bhawan, 6th Floor, M.G. Road, Secunderabad 500003, Telangana, India. Tel.: + 91 9676872626; fax: +91 40 27541551.
| | - Haseeb A. Khan
- Department of Biochemistry, College of Sciences, Bldg. 5, King Saud University, P.O. Box 2455, Riyadh, Saudi Arabia
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Yin L, Zheng L, Xu L, Dong D, Han X, Qi Y, Zhao Y, Xu Y, Peng J. In-silico prediction of drug targets, biological activities, signal pathways and regulating networks of dioscin based on bioinformatics. Altern Ther Health Med 2015; 15:41. [PMID: 25879470 PMCID: PMC4354738 DOI: 10.1186/s12906-015-0579-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2013] [Accepted: 02/21/2015] [Indexed: 11/25/2022]
Abstract
Background Inverse docking technology has been a trend of drug discovery, and bioinformatics approaches have been used to predict target proteins, biological activities, signal pathways and molecular regulating networks affected by drugs for further pharmacodynamic and mechanism studies. Methods In the present paper, inverse docking technology was applied to screen potential targets from potential drug target database (PDTD). Then, the corresponding gene information of the obtained drug-targets was applied to predict the related biological activities, signal pathways and processes networks of the compound by using MetaCore platform. After that, some most relevant regulating networks were considered, which included the nodes and relevant pathways of dioscin. Results 71 potential targets of dioscin from humans, 7 from rats and 8 from mice were screened, and the prediction results showed that the most likely targets of dioscin were cyclin A2, calmodulin, hemoglobin subunit beta, DNA topoisomerase I, DNA polymerase lambda, nitric oxide synthase and UDP-N-acetylhexosamine pyrophosphorylase, etc. Many diseases including experimental autoimmune encephalomyelitis of human, temporal lobe epilepsy of rat and ankylosing spondylitis of mouse, may be inhibited by dioscin through regulating immune response alternative complement pathway, G-protein signaling RhoB regulation pathway and immune response antiviral actions of interferons, etc. The most relevant networks (5 from human, 3 from rat and 5 from mouse) indicated that dioscin may be a TOP1 inhibitor, which can treat cancer though the cell cycle– transition and termination of DNA replication pathway. Dioscin can down regulate EGFR and EGF to inhibit cancer, and also has anti-inflammation activity by regulating JNK signaling pathway. Conclusions The predictions of the possible targets, biological activities, signal pathways and relevant regulating networks of dioscin provide valuable information to guide further investigation of dioscin on pharmacodynamics and molecular mechanisms, which also suggests a practical and effective method for studies on the mechanism of other chemicals.
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Abroun S, Saki N, Fakher R, Asghari F. Biology and bioinformatics of myeloma cell. ACTA ACUST UNITED AC 2013; 18:30-41. [PMID: 23253865 DOI: 10.1532/lh96.11003] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Multiple myeloma (MM) is a plasma cell disorder that occurs in about 10% of all hematologic cancers. The majority of patients (99%) are over 50 years of age when diagnosed. In the bone marrow (BM), stromal and hematopoietic stem cells (HSCs) are responsible for the production of blood cells. Therefore any destruction or/and changes within the BM undesirably impacts a wide range of hematopoiesis, causing diseases and influencing patient survival. In order to establish an effective therapeutic strategy, recognition of the biology and evaluation of bioinformatics models for myeloma cells are necessary to assist in determining suitable methods to cure or prevent disease complications in patients. This review presents the evaluation of molecular and cellular aspects of MM such as genetic translocation, genetic analysis, cell surface marker, transcription factors, and chemokine signaling pathways. It also briefly reviews some of the mechanisms involved in MM in order to develop a better understanding for use in future studies.
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Affiliation(s)
- Saeid Abroun
- Department of Hematology and Blood Banking, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
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23
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Horne TK, Abrahamse H, Cronjé MJ. Investigating the efficiency of novel metallo-phthalocyanine PDT-induced cell death in MCF-7 breast cancer cells. Photodiagnosis Photodyn Ther 2012; 9:215-24. [DOI: 10.1016/j.pdpdt.2011.12.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2011] [Revised: 12/07/2011] [Accepted: 12/10/2011] [Indexed: 11/28/2022]
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Sarita Rajender P, Ramasree D, Bhargavi K, Vasavi M, Uma V. Selective inhibition of proteins regulating CDK/cyclin complexes: strategy against cancer—a review. J Recept Signal Transduct Res 2010; 30:206-13. [DOI: 10.3109/10799893.2010.488649] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Yang Y, Adelstein SJ, Kassis AI. Target discovery from data mining approaches. Drug Discov Today 2009; 14:147-54. [PMID: 19135549 DOI: 10.1016/j.drudis.2008.12.005] [Citation(s) in RCA: 86] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2008] [Revised: 11/27/2008] [Accepted: 12/08/2008] [Indexed: 11/18/2022]
Abstract
Data mining of available biomedical data and information has greatly boosted target discovery in the 'omics' era. Target discovery is the key step in the biomarker and drug discovery pipeline to diagnose and fight human diseases. In biomedical science, the 'target' is a broad concept ranging from molecular entities (such as genes, proteins and miRNAs) to biological phenomena (such as molecular functions, pathways and phenotypes). Within the context of biomedical science, data mining refers to a bioinformatics approach that combines biological concepts with computer tools or statistical methods that are mainly used to discover, select and prioritize targets. In response to the huge demand of data mining for target discovery in the 'omics' era, this review explicates various data mining approaches and their applications to target discovery with emphasis on text and microarray data analysis. Two emerging data mining approaches, chemogenomic data mining and proteomic data mining, are briefly introduced. Also discussed are the limitations of various data mining approaches found in the level of database integration, the quality of data annotation, sample heterogeneity and the performance of analytical and mining tools. Tentative strategies of integrating different data sources for target discovery, such as integrated text mining with high-throughput data analysis and integrated mining with pathway databases, are introduced.
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Affiliation(s)
- Yongliang Yang
- Harvard Medical School, Harvard University, Department of Radiology, Armenise Building, Room D2-137, 200 Longwood Avenue, Boston, MA 02115, USA.
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Schmitt M, Mengele K, Schueren E, Sweep FCGJ, Foekens JA, Brünner N, Laabs J, Malik A, Harbeck N. European Organisation for Research and Treatment of Cancer (EORTC) Pathobiology Group standard operating procedure for the preparation of human tumour tissue extracts suited for the quantitative analysis of tissue-associated biomarkers. Eur J Cancer 2007; 43:835-44. [PMID: 17321128 DOI: 10.1016/j.ejca.2007.01.008] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2006] [Accepted: 01/04/2007] [Indexed: 11/20/2022]
Abstract
With the new concept of 'individualized treatment and targeted therapies', tumour tissue-associated biomarkers have been given a new role in selection of cancer patients for treatment and in cancer patient management. Tumour biomarkers can give support to cancer patient stratification and risk assessment, treatment response identification, or to identifying those patients who are expected to respond to certain anticancer drugs. As the field of tumour-associated biomarkers has expanded rapidly over the last years, it has become increasingly apparent that a strong need exists to establish guidelines on how to easily disintegrate the tumour tissue for assessment of the presence of tumour tissue-associated biomarkers. Several mechanical tissue (cell) disruption techniques exist, ranging from bead mill homogenisation and freeze-fracturing through to blade or pestle-type homogenisation, to grinding and ultrasonics. Still, only a few directives have been given on how fresh-frozen tumour tissues should be processed for the extraction and determination of tumour biomarkers. The PathoBiology Group of the European Organisation for Research and Treatment of Cancer therefore has devised a standard operating procedure for the standardised preparation of human tumour tissue extracts which is designed for the quantitative analysis of tumour tissue-associated biomarkers. The easy to follow technical steps involved require 50-300 mg of deep-frozen cancer tissue placed into small size (1.2 ml) cryogenic tubes. These are placed into the shaking flask of a Mikro-Dismembrator S machine (bead mill) to pulverise the tumour tissue in the capped tubes in the deep-frozen state by use of a stainless steel ball, all within 30 s of exposure. RNA is isolated from the pulverised tissue following standard procedures. Proteins are extracted from the still frozen pulverised tissue by addition of Tris-buffered saline to obtain the cytosol fraction of the tumour or by the Tris buffer supplemented with the non-ionic detergent Triton X-100, and, after high-speed centrifugation, are found in the tissue supernatant. The resulting tissue cell debris sediment is a rich source of genomic DNA.
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Affiliation(s)
- Manfred Schmitt
- Clinical Research Unit, Department of Obstetrics and Gynecology, Technical University of Munich, Germany.
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Zheng CJ, Han LY, Yap CW, Ji ZL, Cao ZW, Chen YZ. Therapeutic targets: progress of their exploration and investigation of their characteristics. Pharmacol Rev 2006; 58:259-79. [PMID: 16714488 DOI: 10.1124/pr.58.2.4] [Citation(s) in RCA: 132] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Modern drug discovery is primarily based on the search and subsequent testing of drug candidates acting on a preselected therapeutic target. Progress in genomics, protein structure, proteomics, and disease mechanisms has led to a growing interest in and effort for finding new targets and more effective exploration of existing targets. The number of reported targets of marketed and investigational drugs has significantly increased in the past 8 years. There are 1535 targets collected in the therapeutic target database compared with approximately 500 targets reported in a 1996 review. Knowledge of these targets is helpful for molecular dissection of the mechanism of action of drugs and for predicting features that guide new drug design and the search for new targets. This article summarizes the progress of target exploration and investigates the characteristics of the currently explored targets to analyze their sequence, structure, family representation, pathway association, tissue distribution, and genome location features for finding clues useful for searching for new targets. Possible "rules" to guide the search for druggable proteins and the feasibility of using a statistical learning method for predicting druggable proteins directly from their sequences are discussed.
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Affiliation(s)
- C J Zheng
- Bioinformatics and Drug Design Group, Department of Computational Science, National University of Singapore, Singapore, Singapore
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Zhou FL, Zhang WG, Chen G, Zhao WH, Cao XM, Chen YX, Tian W, Liu J, Liu SH. Serological identification and bioinformatics analysis of immunogenic antigens in multiple myeloma. Cancer Immunol Immunother 2006; 55:910-7. [PMID: 16193335 PMCID: PMC11030602 DOI: 10.1007/s00262-005-0074-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2005] [Accepted: 08/01/2005] [Indexed: 10/25/2022]
Abstract
Identifying appropriate tumor antigens is critical to the development of successful specific cancer immunotherapy. Serological analysis of tumor antigens by a recombinant cDNA expression library (SEREX) allows the systematic cloning of tumor antigens recognized by the spontaneous autoantibody repertoire of cancer patients. We applied SEREX to the cDNA expression library of cell line HMy2, which led to the isolation of six known characterized genes and 12 novel genes. Known genes, including ring finger protein 167, KLF10, TPT1, p02 protein, cDNA FLJ46859 fis, and DNMT1, were related to the development of different tumors. Bioinformatics was performed to predict 12 novel MMSA (multiple myeloma special antigen) genes. The prediction of tumor antigens provides potential targets for the immunotherapy of patients with multiple myeloma (MM) and help in the understanding of carcinogenesis. Crude lysate ELISA methodology indicated that the optical density value of MMSA-3 and MMSA-7 were significantly higher in MM patients than in healthy donors. Furthermore, SYBR Green real-time PCR showed that MMSA-1 presented with a high number of copy messages in MM. In summary, the antigens identified in this study may be potential candidates for diagnosis and targets for immunotherapy in MM.
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Affiliation(s)
- F. L. Zhou
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
- Environments and Genes Related to Diseases Key Laboratory of the Education Ministry, Xi’an Jiaotong University, Xi’an, 710004 China
| | - W. G. Zhang
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
- Environments and Genes Related to Diseases Key Laboratory of the Education Ministry, Xi’an Jiaotong University, Xi’an, 710004 China
| | - G. Chen
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
| | - W. H. Zhao
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
| | - X. M. Cao
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
| | - Y. X. Chen
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
| | - W. Tian
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
| | - J. Liu
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
| | - S. H. Liu
- Department of Hematology, The Second Hospital, School of Medicine, Xi’an Jiaotong University, The west five road, No. 157, Xi’an, 710004 China
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Zheng C, Han L, Yap CW, Xie B, Chen Y. Progress and problems in the exploration of therapeutic targets. Drug Discov Today 2006; 11:412-20. [PMID: 16635803 DOI: 10.1016/j.drudis.2006.03.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2005] [Revised: 03/01/2006] [Accepted: 03/17/2006] [Indexed: 10/24/2022]
Abstract
Drugs exert their therapeutic effect by binding and regulating the activity of a particular protein or nucleic acid target. A large number of targets have been explored for drug discovery. Continuous effort has been directed at the search for new targets and more-extensive exploration of existing targets. Knowledge of these targets facilitates the understanding of molecular mechanisms of drugs and the effort required for drug discovery and target searches. Areas of progress, current focuses of research and development and the difficulties in target exploration are reviewed. The characteristics of the currently explored targets and their correlation to the level of difficulty for target exploration are analyzed. From these characteristics, simple rules can be derived for estimating the difficulty level of target exploration. The feasibility of predicting druggable proteins by using simple rules and sequence-derived physicochemical properties is also discussed.
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Affiliation(s)
- Chanjuan Zheng
- Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
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Lloyd DG, Golfis G, Knox AJS, Fayne D, Meegan MJ, Oprea TI. Oncology exploration: charting cancer medicinal chemistry space. Drug Discov Today 2006; 11:149-59. [PMID: 16533713 DOI: 10.1016/s1359-6446(05)03688-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Approaches for the experimental determination of protein-ligand molecular interactions are reliant on the quality of the compounds being tested. The application of large, randomly designed combinatorial libraries has given way to the creation of more-focused 'drug-like' libraries. Prior to synthesis, we wish to screen the potential compounds to remove undesired chemical moieties and to be within a required range of physiochemical properties. We have used a principal-component analysis (PCA) computational approach to analyze the 3D descriptor space of active and non-active (hit-like) cancer medicinal chemistry compounds. We define hit-like those molecules passing the unmodified OpenEye FILTER program. Our analysis indicates that these compounds occupy quite different regions in space. Cancer-active compounds exist in a much greater volume of space than generic hit-like space and most of them fail the commonly applied filters for orally bioavailable drugs. This is of great significance when designing orally bioavailable cancer target drugs.
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Affiliation(s)
- David G Lloyd
- Molecular Design Group, School of Biochemistry and Immunology, Trinity College Dublin, Dublin 2, Ireland.
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Schultz RM. Dawn of a new era in molecular cancer therapeutics. PROGRESS IN DRUG RESEARCH. FORTSCHRITTE DER ARZNEIMITTELFORSCHUNG. PROGRES DES RECHERCHES PHARMACEUTIQUES 2005; 63:1-17. [PMID: 16265874 DOI: 10.1007/3-7643-7414-4_1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Affiliation(s)
- Richard M Schultz
- Division of Cancer Research, Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN 46285, USA.
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Lester DS. Clinical drug evaluation using imaging readouts: regulatory perspectives. PROGRESS IN DRUG RESEARCH. FORTSCHRITTE DER ARZNEIMITTELFORSCHUNG. PROGRES DES RECHERCHES PHARMACEUTIQUES 2005; 62:357-84. [PMID: 16329262 DOI: 10.1007/3-7643-7426-8_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Affiliation(s)
- David S Lester
- WW Clinical Technology, PGRD New Products Development, PGP Pfizer Inc., 685 Third Ave, MS 685/19/8, New York, NY 10017, USA.
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