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Gao Y, Jia Y, Yu Z, Ji X, Liu X, Han L, Zhang H, Zhu B, Xu M. Analysis of the differential expression and prognostic relationship of DEGs in AML based on TCGA database. Eur J Med Res 2023; 28:103. [PMID: 36850007 PMCID: PMC9969712 DOI: 10.1186/s40001-023-01060-3] [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: 06/26/2022] [Accepted: 02/12/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND Acute myeloid leukemia (AML) is a common and lethal hematological malignant hyperplastic disease originating from hematopoietic stem cells. The purpose of this study is to obtain the key differentially expressed gene (DEG) related to the survival of AML by The Cancer Genome Atlas (TCGA) database and to verify these genes by a clinical follow-up investigation, in order to identify valuable predictive and prognostic biomarkers for early diagnosis of AML and predict the survival rates. METHODS The RNA sequencing (RNA-Seq) data and clinical information of TCGA-LAML were downloaded from the TCGA database. After that we (1) screened the survival-related DEGs by Cox regression analysis, (2) selected the cytogenetics risk-related DEGs by DESeq2 R package, and (3) filtrated the genes in the top10 pathways of up-regulated and down-regulated of Normalization Enrichment Score (NES) by Gene Set Enrichment Analysis (GSEA). Finally, we focused the intersectional genes of above three parts as the key gene of the present study. The following Multivariate.
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Affiliation(s)
- Yue Gao
- grid.410734.50000 0004 1761 5845Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009 China ,Public Health Research Institute of Jiangsu Province, Nanjing, 210009 China
| | - Yinnong Jia
- grid.285847.40000 0000 9588 0960School of Pharmaceutical Sciences and Yunnan Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming, 650500 China
| | - Zhengmin Yu
- grid.410734.50000 0004 1761 5845Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009 China ,Public Health Research Institute of Jiangsu Province, Nanjing, 210009 China
| | - Xinyu Ji
- grid.410734.50000 0004 1761 5845Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009 China ,Public Health Research Institute of Jiangsu Province, Nanjing, 210009 China
| | - Xiaowen Liu
- grid.410734.50000 0004 1761 5845Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009 China ,Public Health Research Institute of Jiangsu Province, Nanjing, 210009 China
| | - Lei Han
- grid.410734.50000 0004 1761 5845Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009 China ,Public Health Research Institute of Jiangsu Province, Nanjing, 210009 China ,grid.89957.3a0000 0000 9255 8984Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166 China
| | - Hengdong Zhang
- grid.410734.50000 0004 1761 5845Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009 China ,Public Health Research Institute of Jiangsu Province, Nanjing, 210009 China ,grid.89957.3a0000 0000 9255 8984Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166 China
| | - Baoli Zhu
- grid.89957.3a0000 0000 9255 8984Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166 China
| | - Ming Xu
- Department of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, No. 172 Jiangsu Road, Nanjing, 210009, China. .,Public Health Research Institute of Jiangsu Province, Nanjing, 210009, China. .,Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
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Safikhani Z, Smirnov P, Thu KL, Silvester J, El-Hachem N, Quevedo R, Lupien M, Mak TW, Cescon D, Haibe-Kains B. Gene isoforms as expression-based biomarkers predictive of drug response in vitro. Nat Commun 2017; 8:1126. [PMID: 29066719 PMCID: PMC5655668 DOI: 10.1038/s41467-017-01153-8] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 08/23/2017] [Indexed: 01/09/2023] Open
Abstract
Next-generation sequencing technologies have recently been used in pharmacogenomic studies to characterize large panels of cancer cell lines at the genomic and transcriptomic levels. Among these technologies, RNA-sequencing enable profiling of alternatively spliced transcripts. Given the high frequency of mRNA splicing in cancers, linking this feature to drug response will open new avenues of research in biomarker discovery. To identify robust transcriptomic biomarkers for drug response across studies, we develop a meta-analytical framework combining the pharmacological data from two large-scale drug screening datasets. We use an independent pan-cancer pharmacogenomic dataset to test the robustness of our candidate biomarkers across multiple cancer types. We further analyze two independent breast cancer datasets and find that specific isoforms of IGF2BP2, NECTIN4, ITGB6, and KLHDC9 are significantly associated with AZD6244, lapatinib, erlotinib, and paclitaxel, respectively. Our results support isoform expressions as a rich resource for biomarkers predictive of drug response.
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Affiliation(s)
- Zhaleh Safikhani
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, Canada, M5G1L7
| | - Petr Smirnov
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
| | - Kelsie L Thu
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Institut de Recherches Cliniques de Montréal, 110 Pine Avenue West, Montreal, QC, Canada, H2W 1R7
| | - Jennifer Silvester
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Institut de Recherches Cliniques de Montréal, 110 Pine Avenue West, Montreal, QC, Canada, H2W 1R7
| | - Nehme El-Hachem
- Institut de Recherches Cliniques de Montréal, 110 Pine Avenue West, Montreal, QC, Canada, H2W 1R7
| | - Rene Quevedo
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, Canada, M5G1L7
| | - Mathieu Lupien
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, Canada, M5G1L7
| | - Tak W Mak
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, Canada, M5G1L7
- Campbell Family Institute for Breast Cancer Research, 620 University Avenue, Toronto, ON, Canada, M5G2C1
| | - David Cescon
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7
- Campbell Family Institute for Breast Cancer Research, 620 University Avenue, Toronto, ON, Canada, M5G2C1
- Division of Medical Oncology and Hematology, Department of Medicine, University of Toronto, 27 King's College Circle, Toronto, ON, Canada, M5S 1A1
| | - Benjamin Haibe-Kains
- Princess Margaret Cancer Centre, University Health Network, 101 College Street, Toronto, ON, Canada, M5G1L7.
- Department of Medical Biophysics, University of Toronto, 101 College Street, Toronto, ON, Canada, M5G1L7.
- Department of Computer Science, University of Toronto, 10 King's College Road, Toronto, ON, Canada, M5S 3G4.
- Ontario Institute of Cancer Research, 661 University Avenue, Suite 510, Toronto, ON, Canada, M5G 0A3.
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