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Zhang W, Huang RS. Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data. Expert Opin Drug Discov 2024:1-13. [PMID: 38860709 DOI: 10.1080/17460441.2024.2365370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 06/04/2024] [Indexed: 06/12/2024]
Abstract
INTRODUCTION Prostate cancer (PC) is the most common malignancy and accounts for a significant proportion of cancer deaths among men. Although initial therapy success can often be observed in patients diagnosed with localized PC, many patients eventually develop disease recurrence and metastasis. Without effective treatments, patients with aggressive PC display very poor survival. To curb the current high mortality rate, many investigations have been carried out to identify efficacious therapeutics. Compared to de novo drug designs, computational methods have been widely employed to offer actionable drug predictions in a fast and cost-efficient way. Particularly, powered by an increasing availability of next-generation sequencing molecular profiles from PC patients, computer-aided approaches can be tailored to screen for candidate drugs. AREAS COVERED Herein, the authors review the recent advances in computational methods for drug discovery utilizing molecular profiles from PC patients. Given the uniqueness in PC therapeutic needs, they discuss in detail the drug discovery goals of these studies, highlighting their translational values for clinically impactful drug nomination. EXPERT OPINION Evolving molecular profiling techniques may enable new perspectives for computer-aided approaches to offer drug candidates for different tumor microenvironments. With ongoing efforts to incorporate new compounds into large-scale high-throughput screens, the authors envision continued expansion of drug candidate pools.
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Affiliation(s)
- Weijie Zhang
- Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, MN, USA
- Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA
| | - R Stephanie Huang
- Department of Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, MN, USA
- Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA
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2
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Maier A, Hartung M, Abovsky M, Adamowicz K, Bader GD, Baier S, Blumenthal DB, Chen J, Elkjaer ML, Garcia-Hernandez C, Helmy M, Hoffmann M, Jurisica I, Kotlyar M, Lazareva O, Levi H, List M, Lobentanzer S, Loscalzo J, Malod-Dognin N, Manz Q, Matschinske J, Mee M, Oubounyt M, Pastrello C, Pico AR, Pillich RT, Poschenrieder JM, Pratt D, Pržulj N, Sadegh S, Saez-Rodriguez J, Sarkar S, Shaked G, Shamir R, Trummer N, Turhan U, Wang RS, Zolotareva O, Baumbach J. Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing. Nucleic Acids Res 2024:gkae388. [PMID: 38783119 DOI: 10.1093/nar/gkae388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/08/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.
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Affiliation(s)
- Andreas Maier
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
| | - Michael Hartung
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
| | - Mark Abovsky
- Division of Orthopaedic Surgery, Schroeder Arthritis Institute, Toronto, Canada
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto, ON M5T 0S8, Canada
| | - Klaudia Adamowicz
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
| | - Gary D Bader
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
- The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Sylvie Baier
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - David B Blumenthal
- Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander University Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany
| | - Jing Chen
- Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Maria L Elkjaer
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Department of Neurology, Odense University Hospital, Odense, Denmark
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
- Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
| | | | - Mohamed Helmy
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Canada
- School of Public Health, University of Saskatchewan, Canada
- Department of Computer Science, University of Saskatchewan, Canada
- Department of Computer Science, Lakehead University, Canada
- Department of Computer Science, Idaho State University, USA
- Bioinformatics Institute (BII), A*STAR, Singapore
| | - Markus Hoffmann
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
- Institute for Advanced Study, Technical University of Munich, Germany
- National Institute of Diabetes, Digestive, and Kidney Diseases, Bethesda, MD 20892, USA
| | - Igor Jurisica
- Division of Orthopaedic Surgery, Schroeder Arthritis Institute, Toronto, Canada
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto, ON M5T 0S8, Canada
- Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, Canada
- Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Max Kotlyar
- Division of Orthopaedic Surgery, Schroeder Arthritis Institute, Toronto, Canada
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto, ON M5T 0S8, Canada
| | - Olga Lazareva
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Junior Clinical Cooperation Unit Multiparametric methods for early detection of prostate cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
- European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany
| | - Hagai Levi
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
| | - Markus List
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Sebastian Lobentanzer
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - Joseph Loscalzo
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Quirin Manz
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Julian Matschinske
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Miles Mee
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | - Mhaned Oubounyt
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
| | - Chiara Pastrello
- Division of Orthopaedic Surgery, Schroeder Arthritis Institute, Toronto, Canada
- Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto, ON M5T 0S8, Canada
| | - Alexander R Pico
- Institute of Data Science and Biotechnology, Gladstone Institutes, 1650 Owens Street, San Francisco, 94158 California, USA
| | - Rudolf T Pillich
- Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Julian M Poschenrieder
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Dexter Pratt
- Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Nataša Pržulj
- Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain
- Department of Computer Science, University College London, London WC1E 6BT, UK
- ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain
| | - Sepideh Sadegh
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
- Clinical Genome Center, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Julio Saez-Rodriguez
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - Suryadipto Sarkar
- Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander University Erlangen-Nürnberg (FAU), 91052 Erlangen, Germany
| | - Gideon Shaked
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
| | - Ron Shamir
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
| | - Nico Trummer
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Ugur Turhan
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
| | - Rui-Sheng Wang
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Olga Zolotareva
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
| | - Jan Baumbach
- Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany
- Computational Biomedicine Lab, Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
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Wang Q, Huang Q, Ying X, Shen J, Duan S. Unveiling the role of tRNA-derived small RNAs in MAPK signaling pathway: implications for cancer and beyond. Front Genet 2024; 15:1346852. [PMID: 38596214 PMCID: PMC11002130 DOI: 10.3389/fgene.2024.1346852] [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: 11/30/2023] [Accepted: 03/13/2024] [Indexed: 04/11/2024] Open
Abstract
tRNA-derived small RNAs (tsRNAs) are novel small non-coding RNAs originating from mature or precursor tRNAs (pre-tRNA), typically spanning 14 to 30 nt. The Mitogen-activated protein kinases (MAPK) pathway orchestrates cellular responses, influencing proliferation, differentiation, apoptosis, and transformation. tsRNAs influence the expression of the MAPK signaling pathway by targeting specific proteins within the pathway. Presently, four MAPK-linked tsRNAs have implications in gastric cancer (GC) and high-grade serous ovarian cancer (HGSOC). Notably, tRF-Glu-TTC-027 and tRF-Val-CAC-016 modulate MAPK-related protein expression, encompassing p38, Myc, ERK, CyclinD1, CyclinB, and c-Myc, hindering GC progression via MAPK pathway inhibition. Moreover, tRF-24-V29K9UV3IU and tRF-03357 remain unexplored in specific mechanisms. KEGG analysis posits varied tsRNAs in MAPK pathway modulation for diverse non-cancer maladies. Notably, high tRF-36-F900BY4D84KRIME and tRF-23-87R8WP9IY expression relates to varicose vein (VV) risk. Elevated tiRNA-Gly-GCC-001, tRF-Gly-GCC-012, tRF-Gly-GCC-013, and tRF-Gly-GCC-016 target spinal cord injury (SCI)-related brain-derived neurotrophic factor (BDNF), influencing MAPK expression. tRF-Gly-CCC-039 associates with diabetes foot sustained healing, while tRF-5014a inhibits autophagy-linked ATG5 in diabetic cardiomyopathy (DCM). Additionally, tsRNA-14783 influences keloid formation by regulating M2 macrophage polarization. Upregulation of tRF-Arg-ACG-007 and downregulation of tRF-Ser-GCT-008 are associated with diabetes. tsRNA-04002 alleviates Intervertebral disk degeneration (IDD) by targeting PRKCA. tsRNA-21109 alleviates Systemic lupus erythematosus (SLE) by inhibiting macrophage M1 polarization. The upregulated tiNA-Gly-GCC-002 and the downregulated tRF-Ala-AGC-010, tRF-Gln-CTG-005 and tRF-Leu-AAG-001 may be involved in the pathogenesis of Lupus nephritis (LN) by affecting the expression of MAPK pathway. Downregulation of tsRNA-1018, tsRNA-3045b, tsRNA-5021a and tsRNA-1020 affected the expression of MAPK pathway, thereby improving Acute lung injury (ALI). This review comprehensively dissects tsRNA roles in MAPK signaling across cancers and other diseases, illuminating a novel avenue for translational medical exploration.
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Affiliation(s)
- Qurui Wang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Qinyuan Huang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Xiaowei Ying
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Jinze Shen
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Shiwei Duan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
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4
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Yan Q, Su X, Chen Y, Wang Z, Han W, Xia Q, Mao Y, Si J, Li H, Duan S. LINC00941: a novel player involved in the progression of human cancers. Hum Cell 2024; 37:167-180. [PMID: 37995050 DOI: 10.1007/s13577-023-01002-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/20/2023] [Indexed: 11/24/2023]
Abstract
LINC00941, also known as lncRNA-MUF, is an intergenic non-coding RNA located on chromosome 12p11.21. It actively participates in a complex competing endogenous RNA network, regulating the expression of microRNA and its downstream proteins. Through transcriptional and post-transcriptional regulation, LINC00941 plays a vital role in multiple signaling pathways, influencing cell behaviors such as tumor cell proliferation, epithelial-mesenchymal transition, migration, and invasion. Noteworthy is its consistently high expression in various tumor types, closely correlating with clinicopathological features and cancer prognoses. Elevated LINC00941 levels are associated with adverse clinical outcomes, including increased tumor size, extensive lymphatic metastasis, and distant metastasis, leading to poorer survival rates across different cancers. Additionally, LINC00941 and its associated genes are linked to various targeted drugs available in the market. In this comprehensive review, we systematically summarize existing studies, detailing LINC00941's differential expression, clinicopathological and prognostic implications, regulatory mechanisms, and associated therapeutic drugs. Our analysis includes relevant charts and incorporates bioinformatics analyses to verify LINC00941's differential expression in pan-cancer and explore potential transcriptional regulation patterns of downstream targets. This work not only establishes a robust data foundation but also guides future research directions. Given its potential as a significant cancer biomarker and therapeutic target, further investigation into LINC00941's differential expression and regulatory mechanisms is essential.
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Affiliation(s)
- Qibin Yan
- Institute of Pharmacy, Zhejiang University of Technology, Hangzhou, Zhejiang, China
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Department of Pharmacy, Hangzhou City University School of Medicine, Hangzhou, Zhejiang, China
| | - Xinming Su
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Yunzhu Chen
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Zehua Wang
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Wenbo Han
- Department of Pharmacy, Hangzhou City University School of Medicine, Hangzhou, Zhejiang, China
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Qing Xia
- Institute of Pharmacy, Zhejiang University of Technology, Hangzhou, Zhejiang, China
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Yunan Mao
- Department of Pharmacy, Hangzhou City University School of Medicine, Hangzhou, Zhejiang, China
| | - Jiahua Si
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China
| | - Hanbing Li
- Institute of Pharmacy, Zhejiang University of Technology, Hangzhou, Zhejiang, China.
| | - Shiwei Duan
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
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Shen J, Su X, Pan M, Wang Z, Ke Y, Wang Q, Dong J, Duan S. Current insights into the oncogenic roles of lncRNA LINC00355. CANCER INNOVATION 2023; 2:448-462. [PMID: 38125763 PMCID: PMC10730005 DOI: 10.1002/cai2.91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/29/2023] [Accepted: 07/26/2023] [Indexed: 12/23/2023]
Abstract
Long noncoding RNAs (lncRNAs) are a class of nonprotein-coding transcripts that are longer than 200 nucleotides. LINC00355 is a lncRNA located on chromosome 13q21.31 and is consistently upregulated in various cancers. It regulates the expression of downstream genes at both transcriptional and posttranscriptional levels, including eight microRNAs (miR-15a-5p, miR-34b-5p, miR-424-5p, miR-1225, miR-217-5p, miR-6777-3p, miR-195, and miR-466) and three protein-coding genes (ITGA2, RAD18, and UBE3C). LINC00355 plays a role in regulating various biological processes such as cell cycle progression, proliferation, apoptosis, epithelial-mesenchymal transition, invasion, and metastasis of cancer cells. It is involved in the regulation of the Wnt/β-catenin signaling pathway and p53 signaling pathway. Upregulation of LINC00355 has been identified as a high-risk factor in cancer patients and its increased expression is associated with poorer overall survival, recurrence-free survival, and disease-free survival. LINC00355 upregulation has been linked to several unfavorable clinical characteristics, including advanced tumor node metastasis and World Health Organization stages, reduced Karnofsky Performance Scale scores, increased tumor size, greater depth of invasion, and more extensive lymph node metastasis. LINC00355 induces chemotherapy resistance in cancer cells by regulating five downstream genes, namely HMGA2, ABCB1, ITGA2, WNT10B, and CCNE1 genes. In summary, LINC00355 is a potential oncogene with great potential as a diagnostic marker and therapeutic target for cancer.
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Affiliation(s)
- Jinze Shen
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Xinming Su
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Ming Pan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Zehua Wang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Yufei Ke
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Qurui Wang
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Jingyin Dong
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
| | - Shiwei Duan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineHangzhou City UniversityHangzhouZhejiangChina
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Hwang KW, Yun JW, Kim HS. Unveiling the Molecular Landscape of FOXA1 Mutant Prostate Cancer: Insights and Prospects for Targeted Therapeutic Strategies. Int J Mol Sci 2023; 24:15823. [PMID: 37958805 PMCID: PMC10650174 DOI: 10.3390/ijms242115823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/12/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
Prostate cancer continues to pose a global health challenge as one of the most prevalent malignancies. Mutations of the Forkhead box A1 (FOXA1) gene have been linked to unique oncogenic features in prostate cancer. In this study, we aimed to unravel the intricate molecular characteristics of FOXA1 mutant prostate cancer through comprehensive in silico analysis of transcriptomic data from The Cancer Genome Atlas (TCGA). A comparison between FOXA1 mutant and control groups unearthed 1525 differentially expressed genes (DEGs), which map to eight intrinsic and six extrinsic signaling pathways. Interestingly, the majority of intrinsic pathways, but not extrinsic pathways, were validated using RNA-seq data of 22Rv1 cells from the GEO123619 dataset, suggesting complex biology in the tumor microenvironment. As a result of our in silico research, we identified novel therapeutic targets and potential drug candidates for FOXA1 mutant prostate cancer. KDM1A, MAOA, PDGFB, and HSP90AB1 emerged as druggable candidate targets, as we found that they have approved drugs throughout the drug database CADDIE. Notably, as most of the approved drugs targeting MAOA and KDM1A were monoamine inhibitors used for mental illness or diabetes, we suggest they have a potential to cure FOXA1 mutant primary prostate cancer without lethal side effects.
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Affiliation(s)
- Kyung Won Hwang
- Department of Biological Sciences, Sungkyunkwan University, Suwon 16419, Republic of Korea;
| | - Jae Won Yun
- Veterans Health Service Medical Research Institute, Veterans Health Service Medical Center, Seoul 05368, Republic of Korea;
| | - Hong Sook Kim
- Department of Biological Sciences, Sungkyunkwan University, Suwon 16419, Republic of Korea;
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7
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Shen J, Si J, Wang Q, Mao Y, Gao W, Duan S. Current status and future perspectives in dysregulated miR-492. Gene 2023; 877:147518. [PMID: 37295631 DOI: 10.1016/j.gene.2023.147518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/24/2023] [Accepted: 05/24/2023] [Indexed: 06/12/2023]
Abstract
MicroRNAs (miRNAs) are a class of single-stranded small non-coding RNAs with a length of 21-23 nucleotides. One such miRNA, miR-492, is located in the KRT19 pseudogene 2 (KRT19P2) of chromosome 12q22 and can also be generated from the processing of the KRT19 transcript at chromosome 17q21. Aberrant expression of miR-492 has been observed in cancers of various physiological systems. miR-492 has been shown to target at least 11 protein-coding genes, which are involved in the regulation of cellular behaviors such as growth, cell cycle, proliferation, epithelial- mesenchymal transition (EMT), invasion and migration. The expression of miR-492 can be regulated by both endogenous and exogenous factors. Furthermore, miR-492 is involved in the regulation of several signaling pathways including the PI3K/AKT signaling pathway, WNT/β-catenin signaling pathway, and MAPK signaling pathway. High expression of miR-492 has been closely associated with shorter overall survival in patients with gastric cancer, ovarian cancer, oropharyngeal carcinoma, colorectal cancer, and hepatocellular carcinoma. This study systematically summarizes the related research findings on miR-492, providing potential insights for future investigations.
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Affiliation(s)
- Jinze Shen
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
| | - Jiahua Si
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
| | - Qurui Wang
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
| | - Yunan Mao
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
| | - Wei Gao
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
| | - Shiwei Duan
- Department of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
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8
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Xia Q, Shen J, Wang Q, Ke Y, Yan Q, Li H, Zhang D, Duan S. LINC00324 in cancer: Regulatory and therapeutic implications. Front Oncol 2022; 12:1039366. [PMID: 36620587 PMCID: PMC9815511 DOI: 10.3389/fonc.2022.1039366] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 11/21/2022] [Indexed: 12/24/2022] Open
Abstract
LINC00324 is a 2082 bp intergenic noncoding RNA. Aberrant expression of LINC00324 was associated with the risk of 11 tumors and was closely associated with clinicopathological features and prognostic levels of 7 tumors. LINC00324 can sponge multiple miRNAs to form complex ceRNA networks, and can also recruit transcription factors and bind RNA-binding protein HuR, thereby regulating the expression of a number of downstream protein-coding genes. LINC00324 is involved in 4 signaling pathways, including the PI3K/AKT signaling pathway, cell cycle regulatory pathway, Notch signaling pathway, and Jak/STAT3 signaling pathway. High expression of LINC00324 was associated with larger tumors, a higher degree of metastasis, a higher TNM stage and clinical stage, and shorter OS. Currently, four downstream genes in the LINC00324 network have targeted drugs. In this review, we summarize the molecular mechanisms and clinical value of LINC00324 in tumors and discuss future directions and challenges for LINC00324 research.
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Affiliation(s)
- Qing Xia
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China,College of Pharmacy, Zhejiang University of Technology, Hangzhou, Zhejiang, China,Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Zhejiang University City College, Hangzhou, Zhejiang, China
| | - Jinze Shen
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China
| | - Qurui Wang
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China
| | - Yufei Ke
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China
| | - Qibin Yan
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China
| | - Hanbing Li
- College of Pharmacy, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Dayong Zhang
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China,*Correspondence: Dayong Zhang, ; Shiwei Duan,
| | - Shiwei Duan
- Department of Clinical Medicine, Zhejiang University City College School of Medicine, Hangzhou, Zhejiang, China,*Correspondence: Dayong Zhang, ; Shiwei Duan,
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Novel Insights into miR-944 in Cancer. Cancers (Basel) 2022; 14:cancers14174232. [PMID: 36077769 PMCID: PMC9454979 DOI: 10.3390/cancers14174232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 08/24/2022] [Accepted: 08/27/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary miR-944 is localized in intron 4 of TP63. ΔNp63 in intron 3 of TP63 recruits the transcription factor AP-2 to promote miR-944 gene expression, which mediates epidermal differentiation induction by ΔNp63. miR-944 is dysregulated in various cancers. In squamous cell carcinoma. miR-944 can target and inhibit 27 protein-coding genes, thereby regulating cell cycle, proliferation, apoptosis, epithelial mesenchymal transition, cancer cell invasion and migration, and other cell behaviors. The genes targeted by miR-944 are involved in three signaling pathways, including the Wnt/β-catenin pathway, Jak/STAT3 pathway, and PI3K/AKT pathway. miR-944 was regulated by a total of 11 competing endogenous RNAs, including 6 circular RNAs and 5 long non-coding RNAs. Abnormally expressed miR-944 can act as an independent prognostic factor and is closely related to tumor invasion, lymph node metastasis, TNM staging, and drug resistance. miR-944 is expected to become a critical biomarker with great clinical application value in cancer. Abstract miRNA is a class of endogenous short-chain non-coding RNAs consisting of about 22 nucleotides. miR-944 is located in the fourth intron of the TP63 gene in the 3q28 region. miR-944 is abnormally expressed in cancers in multiple systems including neural, endocrine, respiratory, reproductive, and digestive systems. miR-944 can target at least 27 protein-coding genes. miR-944 can regulate a series of cell behaviors, such as cell cycle, proliferation, invasion and migration, EMT, apoptosis, etc. miR-944 participates in the networks of 11 ceRNAs, including six circRNAs and five lncRNAs. miR-944 is involved in three signaling pathways. The abnormal expression of miR-944 is closely related to the clinicopathological conditions of various cancer patients. Deregulated expression of miR-944 is significantly associated with clinicopathology and prognosis in cancer patients. In addition, miR-944 is also associated with the development of DDP, RAPA, DOX, and PTX resistance in cancer cells. miR-944 is involved in the anticancer molecular mechanisms of matrine and Rhenium-liposome drugs. In conclusion, this work systematically summarizes the related findings of miR-944, which will provide potential hints for follow-up research on miR-944.
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