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Kukita A, Sone K, Kaneko S, Kawakami E, Oki S, Kojima M, Wada M, Toyohara Y, Takahashi Y, Inoue F, Tanimoto S, Taguchi A, Fukuda T, Miyamoto Y, Tanikawa M, Mori-Uchino M, Tsuruga T, Iriyama T, Matsumoto Y, Nagasaka K, Wada-Hiraike O, Oda K, Hamamoto R, Osuga Y. The Histone Methyltransferase SETD8 Regulates the Expression of Tumor Suppressor Genes via H4K20 Methylation and the p53 Signaling Pathway in Endometrial Cancer Cells. Cancers (Basel) 2022; 14:5367. [PMID: 36358786 PMCID: PMC9655767 DOI: 10.3390/cancers14215367] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 08/01/2023] Open
Abstract
The histone methyltransferase SET domain-containing protein 8 (SETD8), which methylates histone H4 lysine 20 (H4K20) and non-histone proteins such as p53, plays key roles in human carcinogenesis. Our aim was to determine the involvement of SETD8 in endometrial cancer and its therapeutic potential and identify the downstream genes regulated by SETD8 via H4K20 methylation and the p53 signaling pathway. We examined the expression profile of SETD8 and evaluated whether SETD8 plays a critical role in the proliferation of endometrial cancer cells using small interfering RNAs (siRNAs). We identified the prognostically important genes regulated by SETD8 via H4K20 methylation and p53 signaling using chromatin immunoprecipitation sequencing, RNA sequencing, and machine learning. We confirmed that SETD8 expression was elevated in endometrial cancer tissues. Our in vitro results suggest that the suppression of SETD8 using siRNA or a selective inhibitor attenuated cell proliferation and promoted the apoptosis of endometrial cancer cells. In these cells, SETD8 regulates genes via H4K20 methylation and the p53 signaling pathway. We also identified the prognostically important genes related to apoptosis, such as those encoding KIAA1324 and TP73, in endometrial cancer. SETD8 is an important gene for carcinogenesis and progression of endometrial cancer via H4K20 methylation.
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Affiliation(s)
- Asako Kukita
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Kenbun Sone
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Syuzo Kaneko
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo 103-0027, Japan
| | - Eiryo Kawakami
- Graduate School of Medicine, Chiba University, Chiba 263-8522, Japan
| | - Shinya Oki
- National Hospital Organization Tokyo Medical Center, Tokyo 152-8902, Japan
| | - Machiko Kojima
- Tazuke Kofukai, Medical Research Institute, Kitano Hospital, Osaka 530-8480, Japan
| | - Miku Wada
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Yusuke Toyohara
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Yu Takahashi
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Futaba Inoue
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Saki Tanimoto
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Ayumi Taguchi
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Tomohiko Fukuda
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Yuichiro Miyamoto
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Michihiro Tanikawa
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Mayuyo Mori-Uchino
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Tetsushi Tsuruga
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Takayuki Iriyama
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Yoko Matsumoto
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Kazunori Nagasaka
- Department of Obstetrics and Gynecology, Teikyo University School of Medicine, Tokyo 173-0003, Japan
| | - Osamu Wada-Hiraike
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Katsutoshi Oda
- Division of Integrated Genomics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Ryuji Hamamoto
- Division of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, Tokyo 103-0027, Japan
| | - Yutaka Osuga
- Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
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Zhu Y, Cang S, Chen B, Gu Y, Jiang M, Yan J, Shao F, Huang X. Patient Stratification of Clear Cell Renal Cell Carcinoma Using the Global Transcription Factor Activity Landscape Derived From RNA-Seq Data. Front Oncol 2020; 10:526577. [PMID: 33344220 PMCID: PMC7746882 DOI: 10.3389/fonc.2020.526577] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 10/26/2020] [Indexed: 12/24/2022] Open
Abstract
Clear cell renal cell carcinoma represents the most common type of kidney cancer. Precision medicine approach to ccRCC requires an accurate stratification of patients that can predict prognosis and guide therapeutic decision. Transcription factors are implicated in the initiation and progression of human carcinogenesis. However, no comprehensive analysis of transcription factor activity has been proposed so far to realize patient stratification. Here we propose a novel approach to determine the subtypes of ccRCC patients based on global transcription factor activity landscape. Using the TCGA cohort dataset, we identified different subtypes that have distinct up-regulated biomarkers and altered biological pathways. More important, this subtype information can be used to predict the overall survival of ccRCC patients. Our results suggest that transcription factor activity can be harnessed to perform patient stratification.
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Affiliation(s)
- Yanyan Zhu
- Department of Oncology, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
| | - Shundong Cang
- Department of Oncology, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
| | - Bowang Chen
- Research and Development, Zhiyu Inc, Shenzhen, China
- Zhiyu Center for Systems Biology, Shenzhen, China
| | - Yue Gu
- Department of Nephrology, Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
- Blood Purification Center, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
- Institute of Nephrology, Henan, China
| | - Miaomiao Jiang
- Research and Development, Zhiyu Inc, Shenzhen, China
- Zhiyu Center for Systems Biology, Shenzhen, China
| | - Junya Yan
- Department of Oncology, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
| | - Fengmin Shao
- Department of Nephrology, Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
- Blood Purification Center, Henan Provincial People’s Hospital; Zhengzhou University People’s Hospital, Zhengzhou, China
- Institute of Nephrology, Henan, China
| | - Xiaoyun Huang
- Research and Development, Zhiyu Inc, Shenzhen, China
- Zhiyu Center for Systems Biology, Shenzhen, China
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Li Z, Hu J, Qin Z, Tao Y, Lai Z, Wang Q, Li T. High-dimensional single-cell proteomics analysis reveals the landscape of immune cells and stem-like cells in renal tumors. J Clin Lab Anal 2019; 34:e23155. [PMID: 31855296 PMCID: PMC7246380 DOI: 10.1002/jcla.23155] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 10/29/2019] [Accepted: 11/02/2019] [Indexed: 12/16/2022] Open
Abstract
Background Renal tumors are highly heterogeneous, and identification of tumor heterogeneity is an urgent clinical need for effective treatment. Mass cytometry (MC) can be used to perform high‐dimensional single‐cell proteomics analysis of heterogeneous samples via cytometry by time‐of‐flight (CyTOF), in order to achieve more accurate observation and classification of phenotypes within a cell population. This study aimed to develop a high‐dimensional MC method for the detection and analysis of heterogeneity in renal tumors. Materials and Methods We collected tissue samples from 8 patients with different types of renal tumors. Single‐cell suspensions were prepared and stained using a panel of 28 immune cell‐centric antibodies and a panel of 21 stem‐like cell‐centric antibodies. The stained cells were detected using CyTOF. Result Renal tumors were divided into 25 immune cell subsets (4 CD4+ T cells, 7 CD8+ T cells, 1 B cells, 8 macrophages, 1 dendritic cells, 2 natural killer (NK) cells, 1 granulocyte, and 1 other subset) and 7 stem‐like cells subsets (based on positivity of vimentin, CD326, CD34, CD90, CD13, CD44, and CD47). Different types of renal tumors have different cell subsets with significantly different characteristics. Conclusion High‐dimensional single‐cell proteomics analysis using MC aids in the discovery and analysis of renal tumors heterogeneity. Additionally, it can be used to accurately classify the immune cell population and analyze the expression of stem cell‐related markers in renal tumors. Our findings provide a valuable resource for deciphering tumor heterogeneity and might improve the clinical management of patients with renal tumors.
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Affiliation(s)
- Zhijian Li
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Jiaxin Hu
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Zhao Qin
- Department of Plastic and Aesthetic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yuting Tao
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
| | - Zhiyong Lai
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Guangxi key laboratory for genomic and personalized medicine, Guangxi collaborative innovation center for genomic and personalized medicine, Nanning, China
| | - Qiuyan Wang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Guangxi key laboratory for genomic and personalized medicine, Guangxi collaborative innovation center for genomic and personalized medicine, Nanning, China
| | - Tianyu Li
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China.,Guangxi key laboratory for genomic and personalized medicine, Guangxi collaborative innovation center for genomic and personalized medicine, Nanning, China.,Department of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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