1
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Aravind A, Nandakumar R, Ahmed M, Nisar M, Palollathil A, Kanichery A, Sreelan S, Sinan KM, Balaya RDA, Vijayakumar M, Prasad TSK, Raju R. REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status. Life Sci Alliance 2024; 7:e202302443. [PMID: 38719747 PMCID: PMC11077588 DOI: 10.26508/lsa.202302443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 04/26/2024] [Accepted: 04/26/2024] [Indexed: 05/12/2024] Open
Abstract
The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.
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Affiliation(s)
- Anjana Aravind
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Revathy Nandakumar
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Mukhtar Ahmed
- https://ror.org/02f81g417 Department of Zoology, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Mahammad Nisar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Mangalore, India
| | - Akhina Palollathil
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Anagha Kanichery
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Sourav Sreelan
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Mangalore, India
- Yenepoya Institute of Technology, Yenepoya (Deemed to be University), Mangalore, India
| | - Kp Munavvar Sinan
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Mangalore, India
- Yenepoya Institute of Technology, Yenepoya (Deemed to be University), Mangalore, India
| | | | - Manavalan Vijayakumar
- Department of Surgical Oncology, Yenepoya Medical College, Yenepoya (Deemed to be University), Mangalore, India
| | | | - Rajesh Raju
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed to be University), Mangalore, India
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2
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Sanjeev D, George M, John L, Gopalakrishnan AP, Priyanka P, Mendon S, Yandigeri T, Nisar M, Nisar M, Kanekar S, Balaya RDA, Raju R. Tyr352 as a Predominant Phosphosite in the Understudied Kinase and Molecular Target, HIPK1: Implications for Cancer Therapy. OMICS 2024; 28:111-124. [PMID: 38498023 DOI: 10.1089/omi.2023.0244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Homeodomain-interacting protein kinase 1 (HIPK1) is majorly found in the nucleoplasm. HIPK1 is associated with cell proliferation, tumor necrosis factor-mediated cellular apoptosis, transcription regulation, and DNA damage response, and thought to play significant roles in health and common diseases such as cancer. Despite this, HIPK1 remains an understudied molecular target. In the present study, based on a systematic screening and mapping approach, we assembled 424 qualitative and 44 quantitative phosphoproteome datasets with 15 phosphosites in HIPK1 reported across multiple studies. These HIPK1 phosphosites were not currently attributed to any functions. Among them, Tyr352 within the kinase domain was identified as the predominant phosphosite modulated in 22 differential datasets. To analyze the functional association of HIPK1 Tyr352, we first employed a stringent criterion to derive its positively and negatively correlated protein phosphosites. Subsequently, we categorized the correlated phosphosites in known interactors, known/predicted kinases, and substrates of HIPK1, for their prioritized validation. Bioinformatics analysis identified their significant association with biological processes such as the regulation of RNA splicing, DNA-templated transcription, and cellular metabolic processes. HIPK1 Tyr352 was also identified to be upregulated in Her2+ cell lines and a subset of pancreatic and cholangiocarcinoma tissues. These data and the systems biology approach undertaken in the present study serve as a platform to explore the functional role of other phosphosites in HIPK1, and by extension, inform cancer drug discovery and oncotherapy innovation. In all, this study highlights the comprehensive phosphosite map of HIPK1 kinase and the first of its kind phosphosite-centric analysis of HIPK1 kinase based on global-level phosphoproteomics datasets derived from human cellular differential experiments across distinct experimental conditions.
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Affiliation(s)
- Diya Sanjeev
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Mejo George
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Levin John
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | | | - Pahal Priyanka
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Spoorthi Mendon
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Tanuja Yandigeri
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Mahammad Nisar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Muhammad Nisar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | - Saptami Kanekar
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
| | | | - Rajesh Raju
- Centre for Integrative Omics Data Science (CIODS), Yenepoya (Deemed-to-be University), Mangalore, Karnataka, India
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Ramakrishnan K, Babu S, Shaji V, Soman S, Leelamma A, Rehman N, Raju R. Hepatitis B Virus Modulated Transcriptional Regulatory Map of Hepatic Cellular MicroRNAs. OMICS 2023; 27:581-597. [PMID: 38064540 DOI: 10.1089/omi.2023.0171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Hepatitis B virus (HBV) is an enveloped, hepatotropic, noncytopathic virus with a partially double-stranded DNA genome. It infects hepatocytes and is associated with progression to liver fibrosis and cirrhosis, culminating in hepatocellular carcinoma (HCC), accounting for 55% of total HCC cases. MicroRNAs (miRNAs) regulated by HBV play an important role in these pathologies. Mapping the miRNAs responsive to HBV and HBV-specific proteins, including HBV X protein (HBx) that harbor the majority of HBV-human protein interactions, could aid accelerate the diagnostics and therapeutics innovation against the infection and associated diseases. With this in mind, we used a unique annotation strategy whereby we first amassed 362 mature HBV responsive-human Differentially Expressed miRNAs (HBV-hDEmiRs). The core experimentally-validated messenger RNA targets of the HBV-hDEmiRs were mostly associated with viral infections and hepatic inflammation processes. Moreover, our annotation strategy enabled the characterization of HBx-dependent/independent HBV-hDEmiRs as a tool for evaluation of the impact of HBx as a therapeutic target. Bioinformatics analysis of the HBV-human protein-protein interactome revealed new insights into the transcriptional regulatory network of the HBV-hDEmiRs. We performed a comparative analysis of data on miRNAs gathered from HBV infected cell line studies and from tissue studies of fibrosis, cirrhosis, and HCC. Accordingly, we propose hsa-miR-15a-5p that is downregulated by multiple HBV proteins, including HBx, as a potential biomarker of HBV infection, and its progression to HCC. In all, this study underscores (1) the complexity of miRNA regulation in response to HBV infection and its progression into other liver pathologies and (2) provides a regulatory map of HBV-hDEmiRs and the underlying mechanisms modulating their expression through a cross talk between HBV viral proteins and human transcription factors.
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Affiliation(s)
| | - Sreeranjini Babu
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, India
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, Karnataka, India
| | - Vineetha Shaji
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, India
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, Karnataka, India
| | - Sowmya Soman
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, India
| | - Anila Leelamma
- Department of Biochemistry, NSS College, Nilamel, Kollam, Kerala, India
| | - Niyas Rehman
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, India
| | - Rajesh Raju
- Centre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, India
- Centre for Systems Biology and Molecular Medicine (CSBMM), Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, Karnataka, India
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Guha L, Bhat IA, Bashir A, Rahman JU, Pottoo FH. Nanotechnological Approaches for the Treatment of Triple-Negative Breast Cancer: A Comprehensive Review. Curr Drug Metab 2022; 23:781-799. [PMID: 35676850 DOI: 10.2174/1389200223666220608144551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 02/01/2022] [Accepted: 03/10/2022] [Indexed: 01/05/2023]
Abstract
Breast cancer is the most prevalent cancer in women around the world, having a sudden spread nowadays because of the poor sedentary lifestyle of people. Comprising several subtypes, one of the most dangerous and aggressive ones is triple-negative breast cancer or TNBC. Even though conventional surgical approaches like single and double mastectomy and preventive chemotherapeutic approaches are available, they are not selective to cancer cells and are only for symptomatic treatment. A new branch called nanotechnology has emerged in the last few decades that offers various novel characteristics, such as size in nanometric scale, enhanced adherence to multiple targeting moieties, active and passive targeting, controlled release, and site-specific targeting. Among various nanotherapeutic approaches like dendrimers, lipid-structured nanocarriers, carbon nanotubes, etc., nanoparticle targeted therapeutics can be termed the best among all for their specific cytotoxicity to cancer cells and increased bioavailability to a target site. This review focuses on the types and molecular pathways involving TNBC, existing treatment strategies, various nanotechnological approaches like exosomes, carbon nanotubes, dendrimers, lipid, and carbon-based nanocarriers, and especially various nanoparticles (NPs) like polymeric, photodynamic, peptide conjugated, antibody-conjugated, metallic, inorganic, natural product capped, and CRISPR based nanoparticles already approved for treatment or are under clinical and pre-clinical trials for TNBC.
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Affiliation(s)
- Lahanya Guha
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research Mohali, S.A.S Nagar, Punjab 160062, India
| | - Ishfaq Ahmad Bhat
- Northern Railway Hospital, Sri Mata Vaishno Devi, Katra, Reasi 182320, India
| | - Aasiya Bashir
- Department of Pharmaceutical Sciences, Faculty of Applied Sciences and Technology, University of Kashmir, Hazratbal, Srinagar-190006, J&K, India
| | - Jawad Ur Rahman
- Department of Microbiology, College of Medicine, Imam Abdulrahman Bin Faisal University, P.O.BOX 1982, Dammam 31441, Saudi Arabia
| | - Faheem Hyder Pottoo
- Department of Pharmacology, College of Clinical Pharmacy, Imam Abdulrahman Bin Faisal University, P.O.BOX 1982, Dammam 31441, Saudi Arabia
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Sivan SL, Sukumara Pillai VCS. Smell Detection Agent Optimisation Framework and Systems Biology Approach to Detect Dys-Regulated Subnetwork in Cancer Data. Biomolecules 2022; 12:37. [PMID: 35053185 PMCID: PMC8774275 DOI: 10.3390/biom12010037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 11/23/2022] Open
Abstract
Network biology has become a key tool in unravelling the mechanisms of complex diseases. Detecting dys-regulated subnetworks from molecular networks is a task that needs efficient computational methods. In this work, we constructed an integrated network using gene interaction data as well as protein–protein interaction data of differentially expressed genes derived from the microarray gene expression data. We considered the level of differential expression as well as the topological weight of proteins in interaction network to quantify dys-regulation. Then, a nature-inspired Smell Detection Agent (SDA) optimisation algorithm is designed with multiple agents traversing through various paths in the network. Finally, the algorithm provides a maximum weighted module as the optimum dys-regulated subnetwork. The analysis is performed for samples of triple-negative breast cancer as well as colorectal cancer. Biological significance analysis of module genes is also done to validate the results. The breast cancer subnetwork is found to contain (i) valid biomarkers including PIK3CA, PTEN, BRCA1, AR and EGFR; (ii) validated drug targets TOP2A, CDK4, HDAC1, IL6, BRCA1, HSP90AA1 and AR; (iii) synergistic drug targets EGFR and BIRC5. Moreover, based on the weight values assigned to nodes in the subnetwork, PLK1, CTNNB1, IGF1, AURKA, PCNA, HSPA4 and GAPDH are proposed as drug targets for further studies. For colorectal cancer module, the analysis revealed the occurrence of approved drug targets TYMS, TOP1, BRAF and EGFR. Considering the higher weight values, HSP90AA1, CCNB1, AKT1 and CXCL8 are proposed as drug targets for experimentation. The derived subnetworks possess cancer-related pathways as well. The SDA-derived breast cancer subnetwork is compared with that of tools such as MCODE and Minimum Spanning Tree, and observed a higher enrichment (75%) of significant elements. Thus, the proposed nature-inspired algorithm is a novel approach to derive the optimum dys-regulated subnetwork from huge molecular network.
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6
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Zhang Y, Wang P, Li X, Ning S, Li X, Cao Y, Chen SX. GABC: A comprehensive resource and Genome Atlas for Breast Cancer. Int J Cancer 2020; 148:988-994. [PMID: 33064305 DOI: 10.1002/ijc.33347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 09/07/2020] [Accepted: 09/14/2020] [Indexed: 11/09/2022]
Abstract
We developed the Genome Atlas of Breast Cancer (GABC), a global map of noncoding events in the human genome associated with breast cancer that provides a valuable reference resource for users to investigate the underlying genome abnormalities in breast cancer patients. Although significant progress has been made in breast cancer treatment, its morbidity and recurrence rates in women are still high worldwide. Curation and integration of breast cancer-related dysregulations from multiple aspects is essential for disease prevention and diagnosis. In this study, we developed the GABC, which contains 10 172 aberrant noncoding events occurring at multiomics levels, including the genome (single nucleotide polymorphism and somatic mutation), transcriptome (long noncoding RNA and microRNA) and epigenome (DNA methylation, enhancer and superenhancer). Each event entry provides descriptions of detailed biological mechanisms specific to the region or element. Users can also check the genome locations and relationships of functional regulators. The GABC provides a flexible and user-friendly interface for users to search, browse and download data. In addition, the GABC provides an interface to submit newly discovered noncoding events that can be included in the database. Therefore, the GABC aims to constantly enhance our understanding of noncoding genomic events in breast cancer.
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Affiliation(s)
- Yunpeng Zhang
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA.,Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA.,College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Peng Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xin Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Shangwei Ning
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yan Cao
- Department of Urology, Harbin Medical University Cancer Hospital, Harbin, China
| | - Steven Xi Chen
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA.,Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA
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Abstract
Triple-negative breast cancer (TNBC) types with poor prognosis are due to the absence of estrogen receptors, progesterone receptors and HEGFR-2. The lack of suitable therapy for TNBC has led the research community to turn toward epigenetic regulation and its protagonists that can modulate certain oncogenes and tumor suppressors. This has opened an important new field of therapy using epi-drugs, in preclinical and clinical trials. The epi-drugs are natural or synthetic molecules capable of inhibiting or modulating the activity of epigenetic proteins such as DNA methyltransferases, modulating the expression of interferon microRNAs, as well as histone methyltransferases, demethylases, acetyltransferases and deacetylases. This review investigated the epi-drugs used in the treatment of TNBC.
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Affiliation(s)
- Mouhamed Idrissou
- Department of Oncogenetics, Centre Jean Perrin, CBRV, 28 place Henri-Dunant, Clermont-Ferrand 63001, France.,INSERM U 1240 Molecular Imagery & Theranostic Strategies (IMoST), 58 Rue Montalembert, Clermont-Ferrand 63005, France
| | - Anna Sanchez
- Department of Oncogenetics, Centre Jean Perrin, CBRV, 28 place Henri-Dunant, Clermont-Ferrand 63001, France.,INSERM U 1240 Molecular Imagery & Theranostic Strategies (IMoST), 58 Rue Montalembert, Clermont-Ferrand 63005, France
| | - Frédérique Penault-Llorca
- INSERM U 1240 Molecular Imagery & Theranostic Strategies (IMoST), 58 Rue Montalembert, Clermont-Ferrand 63005, France.,Department of Biopathology, Centre Jean Perrin, 58 Rue Montalembert, Clermont-Ferrand 63011, France
| | - Yves-Jean Bignon
- Department of Oncogenetics, Centre Jean Perrin, CBRV, 28 place Henri-Dunant, Clermont-Ferrand 63001, France.,INSERM U 1240 Molecular Imagery & Theranostic Strategies (IMoST), 58 Rue Montalembert, Clermont-Ferrand 63005, France
| | - Dominique Bernard-Gallon
- Department of Oncogenetics, Centre Jean Perrin, CBRV, 28 place Henri-Dunant, Clermont-Ferrand 63001, France.,INSERM U 1240 Molecular Imagery & Theranostic Strategies (IMoST), 58 Rue Montalembert, Clermont-Ferrand 63005, France
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Andrade F, Nakata A, Gotoh N, Fujita A. Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer. Genet Mol Biol 2020; 43:e20180269. [PMID: 31487369 PMCID: PMC7198019 DOI: 10.1590/1678-4685-gmb-2018-0269] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 04/11/2019] [Indexed: 01/03/2023] Open
Abstract
Triple negative breast cancer (TNBC) is currently the only major breast tumor subtype without effective targeted therapy and, as a consequence, usually presents a poor outcome. Due to its more aggressive phenotype, there is an urgent clinical need to identify novel biomarkers that discriminate individuals with poor prognosis. We hypothesize that miRNAs can be used to this end because they are involved in the initiation and progression of tumors by altering the expression of their target genes. To identify a prognostic biomarker in TNBC, we analyzed the miRNA expression of a cohort composed of 185 patients diagnosed with TNBC using penalized Cox regression models. We identified a four-biomarker signature based on miR-221, miR-1305, miR-4708, and RMDN2 expression levels that allowed for the subdivision of TNBC into high- or low-risk groups (Hazard Ratio – HR = 0.32; 95% Confidence Interval - CI = 0.11–0.91; p = 0.03) and are also statistically associated with survival outcome in subgroups of postmenopausal status (HR = 0.19; 95% CI = 0.04–0.90; p= 0.016), node negative status (HR = 0.12; 95% CI = 0.01–1.04; p = 0.026), and tumors larger than 2cm (HR = 0.21; 95% CI = 0.05–0.81; p = 0.021). This four-biomarker signature was significantly associated with TNBC as an independent prognostic factor for survival.
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Affiliation(s)
- Fernando Andrade
- Universidade de São Paulo, Programa Internunidades de Pós-Graduação em Bioinformática, São Paulo, SP, Brazil
| | - Asuka Nakata
- Kanazawa University, Cancer Research Institute, Division of Cancer Cell Biology, Kanazawa, Ishikawa, Japan.,Universidade de São Paulo, Faculdade de Medicina, Departamento de Pediatria, São Paulo, SP, Brazil
| | - Noriko Gotoh
- Kanazawa University, Cancer Research Institute, Division of Cancer Cell Biology, Kanazawa, Ishikawa, Japan
| | - André Fujita
- Universidade de São Paulo, Instituto de Matemática e Estatística, Departamento de Ciência de Computação, São Paulo, SP, Brazil
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Tang C, Du Y, Liang Q, Cheng Z, Tian J. A selenium-containing selective histone deacetylase 6 inhibitor for targeted in vivo breast tumor imaging and therapy. J Mater Chem B 2019. [DOI: 10.1039/c9tb00383e] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
We have developed a HDAC6-selective inhibitor, SelSA, which can be utilized as a target for the detection and treatment of ERα(+) breast cancer and TNBC. The biodistribution study showed that SelSA can specifically target the breast tumor and display potent antitumor effects in vivo. This result will help to better improve the treatment efficacy against breast cancer.
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Affiliation(s)
- Chu Tang
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
- School of Life Science and Technology
- Xidian University
- Xi’an
- China
| | - Yang Du
- CAS Key Laboratory of Molecular Imaging
- The State Key Laboratory of Management and Control for Complex Systems
- Institute of Automation
- Chinese Academy of Sciences
- Beijing 100190
| | - Qian Liang
- CAS Key Laboratory of Molecular Imaging
- The State Key Laboratory of Management and Control for Complex Systems
- Institute of Automation
- Chinese Academy of Sciences
- Beijing 100190
| | - Zhen Cheng
- Molecular Imaging Program at Stanford (MIPS)
- Department of Radiology, and Bio-X Program
- Canary Center at Stanford for Cancer Early Detection
- Stanford University
- Stanford
| | - Jie Tian
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
- School of Life Science and Technology
- Xidian University
- Xi’an
- China
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10
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Sriroopreddy R, Sudandiradoss C. Integrative network-based approach identifies central genetic and transcriptomic elements in triple-negative breast cancer. Funct Integr Genomics 2017; 18:113-124. [DOI: 10.1007/s10142-017-0579-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Revised: 12/07/2017] [Accepted: 12/08/2017] [Indexed: 12/18/2022]
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11
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Davalos V, Martinez-Cardus A, Esteller M. The Epigenomic Revolution in Breast Cancer. The American Journal of Pathology 2017; 187:2163-2174. [DOI: 10.1016/j.ajpath.2017.07.002] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 07/06/2017] [Accepted: 07/06/2017] [Indexed: 02/09/2023]
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12
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Judes G, Rifaï K, Daures M, Dubois L, Bignon Y, Penault-llorca F, Bernard-gallon D. High-throughput «Omics» technologies: New tools for the study of triple-negative breast cancer. Cancer Lett 2016; 382:77-85. [DOI: 10.1016/j.canlet.2016.03.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 02/29/2016] [Accepted: 03/01/2016] [Indexed: 01/01/2023]
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13
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Vitali F, Cohen LD, Demartini A, Amato A, Eterno V, Zambelli A, Bellazzi R. A Network-Based Data Integration Approach to Support Drug Repurposing and Multi-Target Therapies in Triple Negative Breast Cancer. PLoS One 2016; 11:e0162407. [PMID: 27632168 PMCID: PMC5025072 DOI: 10.1371/journal.pone.0162407] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 08/22/2016] [Indexed: 01/08/2023] Open
Abstract
The integration of data and knowledge from heterogeneous sources can be a key success factor in drug design, drug repurposing and multi-target therapies. In this context, biological networks provide a useful instrument to highlight the relationships and to model the phenomena underlying therapeutic action in cancer. In our work, we applied network-based modeling within a novel bioinformatics pipeline to identify promising multi-target drugs. Given a certain tumor type/subtype, we derive a disease-specific Protein-Protein Interaction (PPI) network by combining different data-bases and knowledge repositories. Next, the application of suitable graph-based algorithms allows selecting a set of potentially interesting combinations of drug targets. A list of drug candidates is then extracted by applying a recent data fusion approach based on matrix tri-factorization. Available knowledge about selected drugs mechanisms of action is finally exploited to identify the most promising candidates for planning in vitro studies. We applied this approach to the case of Triple Negative Breast Cancer (TNBC), a subtype of breast cancer whose biology is poorly understood and that lacks of specific molecular targets. Our “in-silico” findings have been confirmed by a number of in vitro experiments, whose results demonstrated the ability of the method to select candidates for drug repurposing.
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Affiliation(s)
- Francesca Vitali
- Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Pavia, Italy
- * E-mail:
| | - Laurie D. Cohen
- Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Pavia, Italy
| | - Andrea Demartini
- Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Pavia, Italy
| | | | | | - Alberto Zambelli
- IRCCS-Fondazione S. Maugeri, Pavia, Italy
- Oncologia Medica, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Riccardo Bellazzi
- Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Pavia, Italy
- IRCCS-Fondazione S. Maugeri, Pavia, Italy
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Abstract
BACKGROUND Bladder Cancer (BC) has two clearly distinct phenotypes. Non-muscle invasive BC has good prognosis and is treated with tumor resection and intravesical therapy whereas muscle invasive BC has poor prognosis and requires usually systemic cisplatin based chemotherapy either prior to or after radical cystectomy. Neoadjuvant chemotherapy is not often used for patients undergoing cystectomy. High-throughput analytical omics techniques are now available that allow the identification of individual molecular signatures to characterize the invasive phenotype. However, a large amount of data produced by omics experiments is not easily accessible since it is often scattered over many publications or stored in supplementary files. OBJECTIVE To develop a novel open-source database, BcCluster (http://www.bccluster.org/), dedicated to the comprehensive molecular characterization of muscle invasive bladder carcinoma. MATERIALS A database was created containing all reported molecular features significant in invasive BC. The query interface was developed in Ruby programming language (version 1.9.3) using the web-framework Rails (version 4.1.5) (http://rubyonrails.org/). RESULTS BcCluster contains the data from 112 published references, providing 1,559 statistically significant features relative to BC invasion. The database also holds 435 protein-protein interaction data and 92 molecular pathways significant in BC invasion. The database can be used to retrieve binding partners and pathways for any protein of interest. We illustrate this possibility using survivin, a known BC biomarker. CONCLUSIONS BcCluster is an online database for retrieving molecular signatures relative to BC invasion. This application offers a comprehensive view of BC invasiveness at the molecular level and allows formulation of research hypotheses relevant to this phenotype.
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Affiliation(s)
- Akshay Bhat
- Charité-Universitätsmedizin Berlin, Berlin, Germany; Mosaiques diagnostics GmbH, Hannover, Germany
| | - Marika Mokou
- Biomedical Research Foundation Academy of Athens , Biotechnology Division, Athens, Greece
| | - Jerome Zoidakis
- Biomedical Research Foundation Academy of Athens , Biotechnology Division, Athens, Greece
| | - Vera Jankowski
- Institute for Molecular Cardiovascular Research (IMCAR) , Aachen, Germany
| | - Antonia Vlahou
- Biomedical Research Foundation Academy of Athens , Biotechnology Division, Athens, Greece
| | - Harald Mischak
- Mosaiques diagnostics GmbH, Hannover, Germany; BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
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