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Nielsen AJ, Albert GK, Sanchez A, Chen J, Liu J, Davalos AS, Geng D, Bradeen X, Hintzsche JD, Robinson W, McCarter M, Amato C, Tobin R, Couts K, Wilky BA, Davila E. DNA-PK inhibition enhances neoantigen diversity and increases T cell responses to immunoresistant tumors. J Clin Invest 2024; 134:e180278. [PMID: 39436696 PMCID: PMC11645140 DOI: 10.1172/jci180278] [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: 02/13/2024] [Accepted: 10/15/2024] [Indexed: 10/25/2024] Open
Abstract
Effective antitumor T cell activity relies on the expression and MHC presentation of tumor neoantigens. Tumor cells can evade T cell detection by silencing the transcription of antigens or by altering MHC machinery, resulting in inadequate neoantigen-specific T cell activation. We identified the DNA-protein kinase inhibitor (DNA-PKi) NU7441 as a promising immunomodulator that reduced immunosuppressive proteins, while increasing MHC-I expression in a panel of human melanoma cell lines. In tumor-bearing mice, combination therapy using NU7441 and the immune adjuvants stimulator of IFN genes (STING) ligand and the CD40 agonist NU-SL40 substantially increased and diversified the neoantigen landscape, antigen-presenting machinery, and, consequently, substantially increased both the number and repertoire of neoantigen-reactive, tumor-infiltrating lymphocytes (TILs). DNA-PK inhibition or KO promoted transcription and protein expression of various neoantigens in human and mouse melanomas and induced sensitivity to immune checkpoint blockade (ICB) in resistant tumors. In patients, protein kinase, DNA-activated catalytic subunit (PRKDC) transcript levels were inversely correlated with MHC-I expression and CD8+ TILs but positively correlated with increased neoantigen loads and improved responses to ICB. These studies suggest that inhibition of DNA-PK activity can restore tumor immunogenicity by increasing neoantigen expression and presentation and broadening the neoantigen-reactive T cell population.
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Affiliation(s)
- Allison J. Nielsen
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Gabriella K. Albert
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Amelia Sanchez
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Jiangli Chen
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Department of Veterans Affairs, Research Service, Rocky Mountain Regional Veterans Affairs, Aurora, Colorado, USA
| | - Jing Liu
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Andres S. Davalos
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Degui Geng
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Department of Veterans Affairs, Research Service, Rocky Mountain Regional Veterans Affairs, Aurora, Colorado, USA
| | - Xander Bradeen
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | | | - William Robinson
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Department of Veterans Affairs, Research Service, Rocky Mountain Regional Veterans Affairs, Aurora, Colorado, USA
- University of Colorado Comprehensive Cancer Center and
| | - Martin McCarter
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- University of Colorado Comprehensive Cancer Center and
- Department of Surgery, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Carol Amato
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Richard Tobin
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Department of Surgery, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Kasey Couts
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- University of Colorado Comprehensive Cancer Center and
| | - Breelyn A. Wilky
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- University of Colorado Comprehensive Cancer Center and
| | - Eduardo Davila
- Department of Medicine, Division of Medical Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Department of Veterans Affairs, Research Service, Rocky Mountain Regional Veterans Affairs, Aurora, Colorado, USA
- University of Colorado Comprehensive Cancer Center and
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2
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Cheng H, Zhao Y, Hou X, Ling F, Wang J, Wang Y, Cao Y. Unveiling the therapeutic prospects of IFNW1 and IFNA21: insights into glioma pathogenesis and clinical significance. Neurogenetics 2024; 25:337-350. [PMID: 38958838 DOI: 10.1007/s10048-024-00769-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Accepted: 06/25/2024] [Indexed: 07/04/2024]
Abstract
Glioma, a type of brain tumor, poses significant challenges due to its heterogeneous nature and limited treatment options. Interferon-related genes (IRGs) have emerged as potential players in glioma pathogenesis, yet their expression patterns and clinical implications remain to be fully elucidated. We conducted a comprehensive analysis to investigate the expression patterns and functional enrichment of IRGs in glioma. This involved constructing protein-protein interaction networks, heatmap analysis, survival curve plotting, diagnostic and prognostic assessments, differential expression analysis across glioma subgroups, GSVA, immune infiltration analysis, and drug sensitivity analysis. Our analysis revealed distinct expression patterns and functional enrichment of IRGs in glioma. Notably, IFNW1 and IFNA21 were markedly downregulated in glioma tissues compared to normal tissues, and higher expression levels were associated with improved overall survival and disease-specific survival. Furthermore, these genes showed diagnostic capabilities in distinguishing glioma tissues from normal tissues and were significantly downregulated in higher-grade and more aggressive gliomas. Differential expression analysis across glioma subgroups highlighted the association of IFNW1 and IFNA21 expression with key pathways and biological processes, including metabolic reprogramming and immune regulation. Immune infiltration analysis revealed their influence on immune cell composition in the tumor microenvironment. Additionally, elevated expression levels were associated with increased resistance to chemotherapeutic agents. Our findings underscore the potential of IFNW1 and IFNA21 as diagnostic biomarkers and prognostic indicators in glioma. Their roles in modulating glioma progression, immune response, and drug sensitivity highlight their significance as potential therapeutic targets. These results contribute to a deeper understanding of glioma biology and may inform the development of personalized treatment strategies for glioma patients.
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Affiliation(s)
- Hong Cheng
- Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou University, No.136 Jiangyang Middle Road, Yangzhou, 225000, Jiangsu, China.
| | - Yingjie Zhao
- Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou University, No.136 Jiangyang Middle Road, Yangzhou, 225000, Jiangsu, China
- Cardiovascular Medicine, The Third People's Hospital of Danyang, Danyang, 212300, Jiangsu, China
| | - Xiaoli Hou
- Yangzhou Vocational University Medical College, Yangzhou, 225000, Jiangsu, China
| | - Fang Ling
- Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou University, No.136 Jiangyang Middle Road, Yangzhou, 225000, Jiangsu, China
- Otorhinolaryngology, The Third People's Hospital of Danyang, Danyang, 212300, Jiangsu, China
| | - Jing Wang
- Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou University, No.136 Jiangyang Middle Road, Yangzhou, 225000, Jiangsu, China
- Medicine Section, The Third People's Hospital of Danyang, Danyang, 212300, Jiangsu, China
| | - Yixia Wang
- Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou University, No.136 Jiangyang Middle Road, Yangzhou, 225000, Jiangsu, China
| | - Yasen Cao
- Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Institute of Translational Medicine, Yangzhou University Medical College, Yangzhou University, No.136 Jiangyang Middle Road, Yangzhou, 225000, Jiangsu, China
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Wei Z, Wang Y, Ma W, Xing W, Lu P, Shang Z, Li F, Li H, Wang Y. Serine-arginine splicing factor 2 promotes oesophageal cancer progression by regulating alternative splicing of interferon regulatory factor 3. RNA Biol 2023; 20:359-367. [PMID: 37335045 PMCID: PMC10281462 DOI: 10.1080/15476286.2023.2223939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 03/07/2023] [Accepted: 04/03/2023] [Indexed: 06/21/2023] Open
Abstract
OBJECTIVE Often, alternative splicing is used by cancer cells to produce or increase proteins that promote growth and survival through alternative splicing. Although RNA-binding proteins are known to regulate alternative splicing events associated with tumorigenesis, their role in oesophageal cancer (EC) has rarely been explored. METHODS We analysed the expression pattern of several relatively well characterized splicing regulators on 183 samples from TCGA cohort of oesophageal cancer; the effectiveness of the knockdown of SRSF2 was subsequently verified by immunoblotting; we measured the ability of cells treated with lenti-sh-SRSF2/lenti-sh2-SRSF2 to invade through an extracellular matrix coating by transwell invasion assay; using RNA-seq data to identify its potential target genes; we performed qRT-PCR to detect the changes of exon 2 usage in lenti-sh-SRSF2 transduced KYSE30 cells to determine the possible effect of SRSF2 on splicing regulation of IRF3; RNA Electrophoretic mobility shift assay (RNA-EMSA) was performed by the incubation of purified SRSF2 protein and biotinylated RNA probes; we performed luciferase assay to confirm the effect of SRSF2 on IFN1 promoter activity. RESULTS We found upregulation of SRSF2 is correlated with the development of EC; Knock-down of SRSF2 inhibits EC cell proliferation, migration, and invasion; SRSF2 regulates the splicing pattern of IRF3 in EC cells; SRSF2 interacts with exon 2 of IRF3 to regulate its exclusion; SRSF2 inhibits the transcription of IFN1 in EC cells. CONCLUSION This study identified a novel regulatory axis involved in EC from the various aspects of splicing regulation.
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Affiliation(s)
- Ziqing Wei
- Department of Thoracic Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Yuyao Wang
- Department of Biochemistry and Molecular Biology, Shanxi Medical University, Taiyuan, China
| | - Wenyuan Ma
- Department of Thoracic Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Wenqing Xing
- Department of Thoracic Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Peng Lu
- Department of Thoracic Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Zhijie Shang
- Department of Thoracic Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Feng Li
- Department of Molecular Biology, Shanxi Cancer Hospital/Institute, Affiliated Hospital of Shanxi Medical University, Taiyuan, China
| | - Huiyu Li
- Department of General Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
| | - Yuxuan Wang
- Department of Thoracic Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China
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4
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Zheng G, Bouamar H, Cserhati M, Zeballos CR, Mehta I, Zare H, Broome L, Hu R, Lai Z, Chen Y, Sharkey FE, Rani M, Halff GA, Cigarroa FG, Sun LZ. Integrin alpha 6 is upregulated and drives hepatocellular carcinoma progression through integrin α6β4 complex. Int J Cancer 2022; 151:930-943. [PMID: 35657344 PMCID: PMC9329238 DOI: 10.1002/ijc.34146] [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: 06/25/2021] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 12/24/2022]
Abstract
Integrin α6 (ITGA6) forms integrin receptors with either integrin β1 (ITGB1) or integrin β4 (ITGB4). How it functions to regulate hepatocellular carcinoma (HCC) progression is not well-elucidated. We found that ITGA6 RNA and protein expression levels are significantly elevated in human HCC tissues in comparison with paired adjacent nontumor tissues by RNA sequencing, RT-qPCR, Western blotting and immunofluorescence staining. Stable knockdown of ITGA6 with different ITGA6 shRNA expression lentivectors significantly inhibited proliferation, migration and anchorage-independent growth of HCC cell lines in vitro, and xenograft tumor growth in vivo. The inhibition of anchorage-dependent and -independent growth of HCC cell lines was also confirmed with anti-ITGA6 antibody. ITGA6 knockdown was shown to induce cell-cycle arrest at G0/G1 phase. Immunoprecipitation assay revealed apparent interaction of ITGA6 with ITGB4, but not ITGB1. Expression studies showed that ITGA6 positively regulates the expression of ITGB4 with no or negative regulation of ITGB1 expression. Finally, while high levels of ITGA6 and ITGB4 together were associated with significantly worse survival of HCC patients in TCGA data set, the association was not significant for high levels of ITGA6 and ITGB1. In conclusion, ITGA6 is upregulated in HCC tumors and has a malignant promoting role in HCC cells through integrin α6β4 complex. Thus, integrin α6β4 may be a therapeutic target for treating patients with HCC.
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Affiliation(s)
- Guixi Zheng
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
- Department of Clinical Laboratory, Qilu Hospital of Shandong University, China
| | - Hakim Bouamar
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Matyas Cserhati
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Carla R. Zeballos
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Isha Mehta
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Habil Zare
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Larry Broome
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Ruolei Hu
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
| | - Zhao Lai
- Greehey Children’s Cancer Research Institute, University of Texas Health Science Center at San Antonio, TX
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, TX
| | - Yidong Chen
- Greehey Children’s Cancer Research Institute, University of Texas Health Science Center at San Antonio, TX
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, TX
- Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, TX
| | - Francis E. Sharkey
- Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at San Antonio, TX
| | - Meenakshi Rani
- Transplant Center, University of Texas Health Science Center at San Antonio, TX
| | - Glenn A. Halff
- Transplant Center, University of Texas Health Science Center at San Antonio, TX
| | | | - Lu-Zhe Sun
- Department of Cell Systems & Anatomy, University of Texas Health Science Center at San Antonio, TX
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5
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Yogi N, Usui G, Matsusaka K, Fukuyo M, Fujiki R, Seki M, Takano S, Abe H, Morikawa T, Ushiku T, Ohtsuka M, Kaneda A. Association of tumors having Epstein-Barr virus in surrounding lymphocytes with poor prognosis. Cancer Med 2022; 12:1122-1136. [PMID: 35726701 PMCID: PMC9883551 DOI: 10.1002/cam4.4967] [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: 04/01/2022] [Revised: 05/12/2022] [Accepted: 06/10/2022] [Indexed: 02/02/2023] Open
Abstract
Infection with certain viruses is an important cause of cancer. The Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium recently analyzed the whole-genome sequencing (WGS) data from 2656 cases across 21 cancer types, and indicated that Epstein-Barr virus (EBV) is detected in many different cancer cases at a higher frequency than previously reported. However, whether EBV-positive cancer cases detected by WGS-based screening correspond to those detected by conventional histopathological techniques is still unclear. In this study, to elucidate the involvement of EBV in various cancers, we reanalyzed the WGS data of the PCAWG cohort combined with the analysis of clinical samples of gastric and pancreatic cancer in our cohort. Based on EBV copy number in each case, we classified tumors into three subgroups: EBV-High, EBV-Low, and EBV-Negative. The EBV-High subgroup was found to be EBV-positive in the cancer cells themselves, whereas the EBV-Low subgroup was EBV-positive in the surrounding lymphocytes. Further, the EBV-Low subgroup showed a significantly worse prognosis for both gastric cancer and across cancer types. In summary, we classified tumors based on EBV copy number and found a unique cancer subgroup, EBV-positive in the surrounding lymphocytes, which was associated with a poor prognosis.
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Affiliation(s)
- Norikazu Yogi
- Department of General Surgery, Graduate School of MedicineChiba UniversityJapan,Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan
| | - Genki Usui
- Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan,Department of Pathology, Graduate School of MedicineThe University of TokyoTokyoJapan,Department of Diagnostic PathologyNTT Medical Center TokyoTokyoJapan
| | - Keisuke Matsusaka
- Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan,Department of PathologyChiba University HospitalChibaJapan
| | - Masaki Fukuyo
- Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan
| | - Ryoji Fujiki
- Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan,Cancer Genomics CenterChiba University HospitalChibaJapan
| | - Motoaki Seki
- Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan,Cancer Genomics CenterChiba University HospitalChibaJapan
| | - Shigetsugu Takano
- Department of General Surgery, Graduate School of MedicineChiba UniversityJapan
| | - Hiroyuki Abe
- Department of Pathology, Graduate School of MedicineThe University of TokyoTokyoJapan
| | - Teppei Morikawa
- Department of Diagnostic PathologyNTT Medical Center TokyoTokyoJapan
| | - Tetsuo Ushiku
- Department of Pathology, Graduate School of MedicineThe University of TokyoTokyoJapan
| | - Masayuki Ohtsuka
- Department of General Surgery, Graduate School of MedicineChiba UniversityJapan
| | - Atsushi Kaneda
- Department of Molecular Oncology, Graduate School of MedicineChiba UniversityJapan
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6
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Dehkordi SK, Walker J, Sah E, Bennett E, Atrian F, Frost B, Woost B, Bennett RE, Orr TC, Zhou Y, Andhey PS, Colonna M, Sudmant PH, Xu P, Wang M, Zhang B, Zare H, Orr ME. Profiling senescent cells in human brains reveals neurons with CDKN2D/p19 and tau neuropathology. NATURE AGING 2021; 1:1107-1116. [PMID: 35531351 PMCID: PMC9075501 DOI: 10.1038/s43587-021-00142-3] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 10/26/2021] [Indexed: 12/20/2022]
Abstract
Senescent cells contribute to pathology and dysfunction in animal models1. Their sparse distribution and heterogenous phenotype have presented challenges for detecting them in human tissues. We developed a senescence eigengene approach to identify these rare cells within large, diverse populations of postmortem human brain cells. Eigengenes are useful when no single gene reliably captures a phenotype, like senescence; they also help to reduce noise, which is important in large transcriptomic datasets where subtle signals from low-expressing genes can be lost. Each of our eigengenes detected ~2% senescent cells from a population of ~140,000 single nuclei derived from 76 postmortem human brains with various levels of Alzheimer's disease (AD) pathology. More than 97% of the senescent cells were excitatory neurons and overlapped with tau-containing neurofibrillary tangles (NFTs). Cyclin dependent kinase inhibitor 2D (CDKN2D/p19) was predicted as the most significant contributor to the primary senescence eigengene. RNAscope and immunofluorescence confirmed its elevated expression in AD brain tissue whereby p19-expressing neurons had 1.8-fold larger nuclei and significantly more cells with lipofuscin than p19-negative neurons. These hallmark senescence phenotypes were further elevated in the presence of NFTs. Collectively, CDKN2D/p19-expressing neurons with NFTs represent a unique cellular population in human AD with a senescence phenotype. The eigengenes developed may be useful in future senescence profiling studies as they accurately identified senescent cells in snRNASeq datasets and predicted biomarkers for histological investigation.
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Affiliation(s)
- Shiva Kazempour Dehkordi
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, 7400 Merton Minter, San Antonio, TX, 78229, USA
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Jamie Walker
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, 7400 Merton Minter, San Antonio, TX, 78229, USA
| | - Eric Sah
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Emma Bennett
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Farzaneh Atrian
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas, USA
- Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Bess Frost
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, 7400 Merton Minter, San Antonio, TX, 78229, USA
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas, USA
- Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Benjamin Woost
- Department of Neurology, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Rachel E. Bennett
- Department of Neurology, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Timothy C. Orr
- Department of Healthcare Innovations, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yingyue Zhou
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Prabhakar S. Andhey
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Marco Colonna
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Peter H. Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Peng Xu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Department of Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Habil Zare
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, 7400 Merton Minter, San Antonio, TX, 78229, USA
- Department of Cell Systems and Anatomy, University of Texas Health San Antonio, San Antonio, Texas, USA
| | - Miranda E. Orr
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Salisbury VA Medical Center, Salisbury, NC, USA
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7
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Samimi H, Mehta I, Docking TR, Zainulabadeen A, Karsan A, Zare H. DNA methylation analysis improves the prognostication of acute myeloid leukemia. EJHAEM 2021; 2:211-218. [PMID: 34308417 PMCID: PMC8294109 DOI: 10.1002/jha2.187] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 02/24/2021] [Accepted: 03/04/2021] [Indexed: 12/12/2022]
Abstract
Integration of orthogonal data could provide new opportunities to pinpoint the underlying molecular mechanisms of hematologic disorders. Using a novel gene network approach, we integrated DNA methylation data from The Cancer Genome Atlas (n = 194 cases) with the corresponding gene expression profile. Our integrated gene network analysis classified AML patients into low-, intermediate-, and high-risk groups. The identified high-risk group had significantly shorter overall survival compared to the low-risk group (p-value ≤10-11). Specifically, our approach identified a particular subgroup of nine high-risk AML cases that died within 2 years after diagnosis. These high-risk cases otherwise would be incorrectly classified as intermediate-risk solely based on cytogenetics, mutation profiles, and common molecular characteristics of AML. We confirmed the prognostic value of our integrative gene network approach using two independent datasets, as well as through comparison with European LeukemiaNet and LSC17 criteria. Our approach could be useful in the prognostication of a subset of borderline AML cases. These cases would not be classified into appropriate risk groups by other approaches that use gene expression, but not DNA methylation data. Our findings highlight the significance of epigenomic data, and they indicate integrating DNA methylation data with gene coexpression networks can have a synergistic effect.
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Affiliation(s)
- Hanie Samimi
- Department of Computer ScienceTexas State UniversitySan MarcosTexasUSA
| | - Isha Mehta
- Department of Cell Systems & AnatomyThe University of Texas Health Science CenterSan AntonioTexasUSA
| | - Thomas Roderick Docking
- Canada's Michael Smith Genome Sciences CentreBritish Columbia Cancer Research CentreVancouverBritish ColumbiaCanada
| | | | - Aly Karsan
- Canada's Michael Smith Genome Sciences CentreBritish Columbia Cancer Research CentreVancouverBritish ColumbiaCanada
| | - Habil Zare
- Department of Cell Systems & AnatomyThe University of Texas Health Science CenterSan AntonioTexasUSA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTexasUSA
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8
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Hu B, Wei Q, Li X, Ju M, Wang L, Zhou C, Chen L, Li Z, Wei M, He M, Zhao L. Development of an IFNγ response-related signature for predicting the survival of cutaneous melanoma. Cancer Med 2020; 9:8186-8201. [PMID: 32902917 PMCID: PMC7643661 DOI: 10.1002/cam4.3438] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 07/21/2020] [Accepted: 08/13/2020] [Indexed: 12/24/2022] Open
Abstract
Background The tumor microenvironment (TME) plays a critical role in tumorigenesis, development, and therapeutic efficacy. Major advances have been achieved in the treatment of various cancers through immunotherapy. Nevertheless, only a minority of patients have positive responses to immunotherapy, which is partly due to conditions of the immunosuppressive microenvironment. Therefore, it is essential to identify prognostic biomarkers that reflect heterogeneous landscapes of the TME. Methods and materials Based upon the ESTIMATE algorithm, we evaluated the infiltrating levels of immune and stromal components derived from patients afflicted by various types of cancer from The Cancer Genome Atlas database (TCGA). According to respective patient immune and stromal scores, we categorized cases into high‐ and low‐scoring subgroups for each cancer type to explore associations between TME and patient prognosis. Gene Set Enrichment Analyses (GSEA) were conducted and genes enriched in IFNγ response signaling pathway were selected to facilitate establishment of a risk model for predicting overall survival (OS). Furthermore, we investigated the associations between the prognostic signature and tumor immune infiltration landscape by using CIBERSORT algorithm and TIMER database. Results Among the cancers assessed, the immune scores for skin cutaneous melanoma (SKCM) were the most significantly correlated with patients' survival time (P < .0001). We identified and validated a five‐IFNγ response‐related gene signature (UBE2L6, PARP14, IFIH1, IRF2, and GBP4), which was closely correlated with the prognosis for SKCM afflicted patients. Multivariate Cox regression analysis indicated that this risk model was an independent prognostic factor for SKCM. Tumor‐infiltrating lymphocytes and specific immune checkpoint molecules had notably differential levels of expression in high‐ compared to low‐risk samples. Conclusion In this study, we established a novel five‐IFNγ response‐related gene signature that provided a better and increasingly comprehensive understanding of tumor immune landscape, and which demonstrated good performance in predicting outcomes for patients afflicted by SKCM.
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Affiliation(s)
- Baohui Hu
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Qian Wei
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Xueping Li
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Mingyi Ju
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Lin Wang
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Chenyi Zhou
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Lianze Chen
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Zinan Li
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Minjie Wei
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Miao He
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
| | - Lin Zhao
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer immune peptide drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang, China
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9
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Kim YJ, Kim K, Lee KH, Kim J, Jung W. Immune expression signatures as candidate prognostic biomarkers of age and gender survival differences in cutaneous melanoma. Sci Rep 2020; 10:12322. [PMID: 32703987 PMCID: PMC7378165 DOI: 10.1038/s41598-020-69082-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 05/12/2020] [Indexed: 12/24/2022] Open
Abstract
This study aims to investigate the difference of gene expression and its prognostic significance in younger women with melanoma. Significantly upregulated genes in tumors compared to normal skin tissues were extracted. Among these genes, genes that significantly affected survival according to expression level were selected, and pathway annotation was performed. The patient proportion with high/low expression of the most significant pathways was analyzed in each age (< 50, 50-59, ≥ 60) and gender group. Survival was analyzed according to age, gender, and pathways. The most significant pathways that were upregulated in tumor tissues and also had impacts on survival were programmed cell death protein [PD]-1, interferon-γ, and interferon-α/β pathways. In women, the immune signaling rate in patients was higher than men and decreased with age (63.5%, 53.8%, and 47.6%). In men, the decreasing tendency was minimal (47.6%, 50.0%, and 41.6%). In patients aged < 60 years, women had a favorable survival rate than men (p = 0.055). Except for patients with high immune signaling, no survival difference was observed between genders (p = 0.6). In conclusion, younger female melanoma patients had high immune signaling than older women and men. This immune signaling improved survival of the younger female patients.
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Affiliation(s)
- Yi-Jun Kim
- Department of Radiation Oncology, Ewha Womans University College of Medicine, 1071 Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Republic of Korea
- Institute of Convergence Medicine, Ewha Womans University Mokdong Hospital, Seoul, 07985, Republic of Korea
| | - Kyubo Kim
- Department of Radiation Oncology, Ewha Womans University College of Medicine, 1071 Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Republic of Korea.
| | - Kye Hwa Lee
- Biomedical Informatics Department, Asan Medical Center, Seoul, 05505, Republic of Korea
| | - Jiyoung Kim
- Department of Radiation Oncology, Ewha Womans University College of Medicine, 1071 Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Republic of Korea
| | - Wonguen Jung
- Department of Radiation Oncology, Ewha Womans University College of Medicine, 1071 Anyangcheon-ro, Yangcheon-gu, Seoul, 07985, Republic of Korea
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Abstract
Over the past decade, preclinical and clinical research have confirmed the essential role of interferons for effective host immunological responses to malignant cells. Type I interferons (IFNα and IFNβ) directly regulate transcription of >100 downstream genes, which results in a myriad of direct (on cancer cells) and indirect (through immune effector cells and vasculature) effects on the tumour. New insights into endogenous and exogenous activation of type I interferons in the tumour and its microenvironment have given impetus to drug discovery and patient evaluation of interferon-directed strategies. When combined with prior observations or with other effective modalities for cancer treatment, modulation of the interferon system could contribute to further reductions in cancer morbidity and mortality. This Review discusses new interferon-directed therapeutic opportunities, ranging from cyclic dinucleotides to genome methylation inhibitors, angiogenesis inhibitors, chemoradiation, complexes with neoantigen-targeted monoclonal antibodies, combinations with other emerging therapeutic interventions and associations of interferon-stimulated gene expression with patient prognosis - all of which are strategies that have or will soon enter translational clinical evaluation.
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11
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Agrahari R, Foroushani A, Docking TR, Chang L, Duns G, Hudoba M, Karsan A, Zare H. Applications of Bayesian network models in predicting types of hematological malignancies. Sci Rep 2018; 8:6951. [PMID: 29725024 PMCID: PMC5934387 DOI: 10.1038/s41598-018-24758-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 04/05/2018] [Indexed: 12/17/2022] Open
Abstract
Network analysis is the preferred approach for the detection of subtle but coordinated changes in expression of an interacting and related set of genes. We introduce a novel method based on the analyses of coexpression networks and Bayesian networks, and we use this new method to classify two types of hematological malignancies; namely, acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Our classifier has an accuracy of 93%, a precision of 98%, and a recall of 90% on the training dataset (n = 366); which outperforms the results reported by other scholars on the same dataset. Although our training dataset consists of microarray data, our model has a remarkable performance on the RNA-Seq test dataset (n = 74, accuracy = 89%, precision = 88%, recall = 98%), which confirms that eigengenes are robust with respect to expression profiling technology. These signatures are useful in classification and correctly predicting the diagnosis. They might also provide valuable information about the underlying biology of diseases. Our network analysis approach is generalizable and can be useful for classifying other diseases based on gene expression profiles. Our previously published Pigengene package is publicly available through Bioconductor, which can be used to conveniently fit a Bayesian network to gene expression data.
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Affiliation(s)
- Rupesh Agrahari
- Department of Computer Science, Texas State University, San Marcos, Texas, 78666, USA
| | - Amir Foroushani
- Department of Computer Science, Texas State University, San Marcos, Texas, 78666, USA
| | - T Roderick Docking
- Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, V5Z 1L3, Canada
| | - Linda Chang
- Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, V5Z 1L3, Canada
| | - Gerben Duns
- Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, V5Z 1L3, Canada
| | - Monika Hudoba
- Department of Pathology and Laboratory Medicine, Vancouver General Hospital, Vancouver, British Columbia, V5Z 1M9, Canada
| | - Aly Karsan
- Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, V5Z 1L3, Canada
| | - Habil Zare
- Department of Computer Science, Texas State University, San Marcos, Texas, 78666, USA. .,Department of Cell Systems & Anatomy, The University of Texas Health Science Center, San Antonio, Texas, 78229, USA.
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12
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Wang Q, Wang X, Liang Q, Wang S, Xiwen L, Pan F, Chen H, Li D. Distinct prognostic value of mRNA expression of guanylate-binding protein genes in skin cutaneous melanoma. Oncol Lett 2018; 15:7914-7922. [PMID: 29725478 PMCID: PMC5920493 DOI: 10.3892/ol.2018.8306] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Accepted: 03/14/2018] [Indexed: 01/04/2023] Open
Abstract
The purpose of the present study was to assess if guanylate-binding protein (GBP) mRNAs could be prognostic biomarkers for patients with skin cutaneous melanoma (SKCM). The prognostic value of GBP mRNA expression in patients with SKCM was investigated by analyzing gene expression data in 459 SKCM patients. The data were extracted from the OncoLnc database of The Cancer Genome Atlas. A high expression of GBP1, GBP2, GBP3, GBP4 and GBP5 were correlated with favorable overall survival (OS) in the SKCM patients followed for over 30 years. In addition, a high expression of GBP6 mRNA was not correlated with OS in the SKCM patients. A joint effects analysis showed that the co-incidence of the high expression of GBP1-5 was correlated with favorable overall survival in SKCM patients. Our findings suggest that GBP1-5 mRNAs in SKCM are associated with favorable prognosis and may be potential prognostic biomarkers. The combination of GBP1-5 could improve the sensitivity for predicting OS in SKCM patients.
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Affiliation(s)
- Qiaoqi Wang
- Cosmetic and Plastic Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530000, P.R. China
| | - Xiangkun Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Qian Liang
- Cosmetic and Plastic Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530000, P.R. China
| | - Shijun Wang
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, P.R. China
| | - Liao Xiwen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Fuqiang Pan
- Cosmetic and Plastic Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530000, P.R. China
| | - Hongyang Chen
- Cosmetic and Plastic Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530000, P.R. China
| | - Dong Li
- Cosmetic and Plastic Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530000, P.R. China
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Nobeyama Y, Nakagawa H. Silencing of interferon regulatory factor gene 6 in melanoma. PLoS One 2017; 12:e0184444. [PMID: 28877249 PMCID: PMC5587289 DOI: 10.1371/journal.pone.0184444] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Accepted: 08/23/2017] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Methylation of a CpG island (CGI; a dense cluster of CpGs) located in the 5' region of a gene suppresses transcription of that gene. Interferon regulatory factor 6 (IRF6) is associated with the expression of interferon, which is used as an effective adjuvant therapy for melanoma, and is regarded as a tumor suppressor. However, little is known about the methylation status of the IRF6 gene in melanoma. OBJECTIVE The purpose was to determine the methylation status of the CGI located in the 5' region of IRF6 (5' IRF6 CGI) in melanoma. METHODS Quantitative real-time methylation-specific PCR (RT-MSP) and bisulfite sequencing were performed to examine IRF6 gene methylation status. Quantitative real-time reverse transcription-PCR (RT-PCR) was performed to examine IRF6 expression. RESULTS The methylation level of the 5' IRF6 CGI was completely inversely correlated with cell sensitivity to interferon-β in eight examined melanoma cell lines. These methylation levels were high in the melanoma cell lines with suppression of IRF6 expression and were low in the cell lines with IRF6 expression. The methylation levels of the 5' IRF6 CGI ranged widely from 0.0% to 65.4% in 21 clinical melanoma samples but showed a narrow range of low levels between 0.0% to 7.2% in 24 clinical melanocytic nevus samples. These methylation levels were not associated with clinical parameters except for melanoma subtypes. CONCLUSION IRF6 is aberrantly silenced by DNA methylation of the 5' IRF6 CGI in melanoma. The methylation status of IRF6 is potentially associated with the sensitivity of melanoma to interferon.
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Affiliation(s)
- Yoshimasa Nobeyama
- Department of Dermatology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan
| | - Hidemi Nakagawa
- Department of Dermatology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan
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