401
|
Tan J, Zheng X, Li M, Ye F, Song C, Xu C, Zhang X, Li W, Wang Y, Zeng S, Li H, Chen G, Huang X, Ma D, Liu D, Gao Q. C/EBPβ promotes poly(ADP-ribose) polymerase inhibitor resistance by enhancing homologous recombination repair in high-grade serous ovarian cancer. Oncogene 2021; 40:3845-3858. [PMID: 33966038 PMCID: PMC8175237 DOI: 10.1038/s41388-021-01788-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 03/12/2021] [Accepted: 04/12/2021] [Indexed: 02/03/2023]
Abstract
PARP inhibitors (PARPi) are efficacious in treating high-grade serous ovarian cancer (HG-SOC) with homologous recombination (HR) deficiency. However, they exhibit suboptimal efficiency in HR-proficient cancers. Here, we found that the expression of CCAAT/enhancer-binding protein β (C/EBPβ), a transcription factor, was inversely correlated with PARPi sensitivity in vitro and in vivo, both in HR-proficient condition. High C/EBPβ expression enhanced PARPi tolerance; PARPi treatment in turn induced C/EBPβ expression. C/EBPβ directly targeted and upregulated multiple HR genes (BRCA1, BRIP1, BRIT1, and RAD51), thereby inducing restoration of HR capacity and mediating acquired PARPi resistance. C/EBPβ is a key regulator of the HR pathway and an indicator of PARPi responsiveness. Targeting C/EBPβ could induce HR deficiency and rescue PARPi sensitivity accordingly. Our findings indicate that HR-proficient patients may benefit from PARPi via targeting C/EBPβ, and C/EBPβ expression levels enable predicting and tracking PARPi responsiveness during treatment.
Collapse
Affiliation(s)
- Jiahong Tan
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Xu Zheng
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Mengchen Li
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Fei Ye
- grid.33199.310000 0004 0368 7223Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Chunyan Song
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Cheng Xu
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Xiaoxue Zhang
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Wenqian Li
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Ya Wang
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Shaoqing Zeng
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Huayi Li
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Gang Chen
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Xiaoyuan Huang
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Ding Ma
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Dan Liu
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| | - Qinglei Gao
- grid.33199.310000 0004 0368 7223Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China ,grid.33199.310000 0004 0368 7223Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
| |
Collapse
|
402
|
Zheng X, Huai C, Xu Q, Xu L, Zhang M, Zhong M, Qiu X. FKBP-CaN-NFAT pathway polymorphisms selected by in silico biological function prediction are associated with tacrolimus efficacy in renal transplant patients. Eur J Pharm Sci 2020; 160:105694. [PMID: 33383132 DOI: 10.1016/j.ejps.2020.105694] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/26/2020] [Accepted: 12/22/2020] [Indexed: 12/26/2022]
Abstract
AIM The aim of the present study was to investigate the potential effects of genetic variations in the FKBP-CaN-NFAT pathway on clinical events associated with tacrolimus efficacy in Chinese renal transplant patients. METHODS One hundred and forty Chinese renal transplant patients of Han ethnicity with over five years of follow-up were enrolled in our study. A pool of single nucleotide polymorphisms (SNPs) (1284 SNPs) was extracted from the Ensembl database according to chromosomal regions of the candidate genes. Next, 109 SNPs were screened out from this pool using multiple bioinformatics tools for subsequent genotyping using the MALDI-TOF-MS method. The associations of these candidate SNPs with acute rejection, nephrotoxicity, pneumonia and post-transplant estimated glomerular filtration rate (eGFR) were explored. RESULTS Fourty-four SNPs were found to be associated with tacrolimus-related clinical drug response. Specifically, eight SNPs were associated with the incidence of biopsy-proven acute rejection, four SNPs were associated with the rate of nephrotoxicity, 16 SNPs were correlated with the onset of pneumonia, and 26 SNPs were found to significantly influence post-transplant eGFR trend. An elaborate scoring system was implemented to prioritize the validation of these potentially causal SNPs. In particular, NFATC2 rs150348438 (G>T) performed well during integrative scoring (Ptotal=23.8) and was significantly associated with the occurrence of pneumonia (P = 0.0035, HR=0.91, 95% CI=0.85-0.97) and post-transplant eGFR levels (P = 0.000003). CONCLUSIONS NFATC2 rs150348438, rs6013219, rs1052653, and NFATC1 rs754093, ranking high in scoring, significantly affected the post-transplant eGFR and the incidence of pneumonia, acute rejection, and nephrotoxicity in renal transplant patients taking tacrolimus. Those SNPs may alter the expression and regulation of FKBP-CaN-NFAT pathway by influencing transcription regulation, mature mRNA degradation and RNA splicing, or protein coding. Critical SNPs of high ranking may serve as PD-associated pharmacogenetic biomarkers indicating individual response variability of TAC, and thus aid the clinical management of renal transplant patients.
Collapse
Affiliation(s)
- Xinyi Zheng
- Department of Pharmacy, Huashan hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Cong Huai
- Bio-X Institutes, Shanghai Jiao Tong University and Research Division, 55 Guangyuan West Road, Shanghai, 200030, China
| | - Qinxia Xu
- Department of Pharmacy, Zhongshan hospital, Fudan University, Shanghai, China
| | - Luyang Xu
- Department of Pharmacy, Huashan hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Ming Zhang
- Department of Nephrology, Huashan hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Mingkang Zhong
- Department of Pharmacy, Huashan hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China.
| | - Xiaoyan Qiu
- Department of Pharmacy, Huashan hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China.
| |
Collapse
|
403
|
Zhang B, Zhou Q, Xie Q, Lin X, Miao W, Wei Z, Zheng T, Pang Z, Liu H, Chen X. SPC25 overexpression promotes tumor proliferation and is prognostic of poor survival in hepatocellular carcinoma. Aging (Albany NY) 2020; 13:2803-2821. [PMID: 33408271 PMCID: PMC7880370 DOI: 10.18632/aging.202329] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 11/08/2020] [Indexed: 12/29/2022]
Abstract
Background: The nuclear division cycle 80 (NDC80) complex assures proper chromosome segregation during the cell cycle progression. SPC25 is a crucial component of NDC80, and its role in hepatocellular carcinoma (HCC) has been explored recently. This study characterized the differential expression of SPC25 in HCC patients of different races and HBV infection status. Methods: Expression patterns of SPC25 were evaluated in TCGA and Chinese HCC patients. Kaplan-Meier analysis was applied to examine the predictive value of SPC25. In vitro and in vivo functional assays were conducted to explore the role of SPC25 in HCC. Bioinformatics methods were applied to investigate the regulatory mechanisms of SPC25. Findings: The mRNA levels of SPC25 were up-regulated in HCC. SPC25 has a significantly higher transcriptional level in Asian patients than Caucasian patients. SPC25 promoted HCC cell proliferation in vitro and tumor growth in vivo by accelerating the cell cycle. We identified transcription factors, miRNAs, and immune cells that may interact with SPC25. Interpretation: The findings suggest that increased expression of SPC25 is associated with poor prognosis of HCC and enhances the proliferative capacity of HCC cells. SPC25 could serve as a valuable prognostic marker and a novel treatment target for HCC.
Collapse
Affiliation(s)
- Baozhu Zhang
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Qing Zhou
- Department of Core Facility, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Qiankun Xie
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong, China
| | - Xiaohui Lin
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Wenqiang Miao
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Zhaoguang Wei
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Tingting Zheng
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Zuoliang Pang
- Department of Oncology, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Haosheng Liu
- Department of Core Facility, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| | - Xi Chen
- Department of Core Facility, People's Hospital of Shenzhen Baoan District, The Affiliated Baoan Hospital of Shenzhen, Southern Medical University, Shenzhen 518101, Guangdong, China
| |
Collapse
|
404
|
Zhu X, Cheng Y, Wu F, Sun H, Zheng W, Jiang W, Shi J, Ma S, Cao H. MFAP2 Promotes the Proliferation of Cancer Cells and Is Associated With a Poor Prognosis in Hepatocellular Carcinoma. Technol Cancer Res Treat 2020; 19:1533033820977524. [PMID: 33280519 PMCID: PMC7724263 DOI: 10.1177/1533033820977524] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Backgrounds: Microfibril-associated protein 2 (MFAP2) is an extracellular matrix protein
that regulates the function of microfibrils by interacting with fibrillin.
MFAP2 has been reported to play an important role in metabolic diseases and
has been shown to be significantly overexpressed in head and neck squamous
cell carcinoma and Hepatocellular carcinoma (HCC). However, the molecular
function and prognostic value of MFAP2 have never been reported in HCC or
other tumors. Methods: In the present study, expression characteristics of MFAP2 in HCC, its
influence on the development of HCC, as well as its function and potential
mechanism in HCC were verified by Quantitative reverse
transcription-polymerase chain reaction, bioinformatics data mining and in
vitro cell experiments. Results: MFAP2 was prominently high-expressed in HCC and associated with cancer
stages. HCC patients with higher MFAP2 expression displayed lower overall
survival (OS) and disease-specific survival(DSS), while there was no
significant difference in recurrence-free survival (RFS). In vitro
experiments showed that downregulation of MFAP2 inhibited proliferation,
migration level of HCC cells. Transcription factors, DNA methyltransferases,
immune factors may interact with MFAP2 mRNA to promote tumor progression in
HCC. Conclusion: These findings suggest that MFAP2 may play a key role in the development of
HCC. Therefore, MFAP2 may be a valuable prognostic marker and an effective
anticancer target in HCC.
Collapse
Affiliation(s)
- Xiang Zhu
- Department of General Surgery, The East District of Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu, People's Republic of China.,Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Ye Cheng
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Fan Wu
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Haoyao Sun
- Department of Radio-Oncology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu, People's Republic of China
| | - Wubin Zheng
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Wei Jiang
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Junfeng Shi
- Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Shijie Ma
- Department of Gastroenterology, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Nanjing, People's Republic of China
| | - Hongyong Cao
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| |
Collapse
|
405
|
Riege K, Kretzmer H, Sahm A, McDade SS, Hoffmann S, Fischer M. Dissecting the DNA binding landscape and gene regulatory network of p63 and p53. eLife 2020; 9:e63266. [PMID: 33263276 PMCID: PMC7735755 DOI: 10.7554/elife.63266] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 12/01/2020] [Indexed: 12/13/2022] Open
Abstract
The transcription factor p53 is the best-known tumor suppressor, but its sibling p63 is a master regulator of epidermis development and a key oncogenic driver in squamous cell carcinomas (SCC). Despite multiple gene expression studies becoming available, the limited overlap of reported p63-dependent genes has made it difficult to decipher the p63 gene regulatory network. Particularly, analyses of p63 response elements differed substantially among the studies. To address this intricate data situation, we provide an integrated resource that enables assessing the p63-dependent regulation of any human gene of interest. We use a novel iterative de novo motif search approach in conjunction with extensive ChIP-seq data to achieve a precise global distinction between p53-and p63-binding sites, recognition motifs, and potential co-factors. We integrate these data with enhancer:gene associations to predict p63 target genes and identify those that are commonly de-regulated in SCC representing candidates for prognosis and therapeutic interventions.
Collapse
Affiliation(s)
- Konstantin Riege
- Computational Biology Group, Leibniz Institute on Aging – Fritz Lipmann Institute (FLI)JenaGermany
| | - Helene Kretzmer
- Department of Genome Regulation, Max Planck Institute for Molecular GeneticsBerlinGermany
| | - Arne Sahm
- Computational Biology Group, Leibniz Institute on Aging – Fritz Lipmann Institute (FLI)JenaGermany
| | - Simon S McDade
- Patrick G Johnston Centre for Cancer Research, Queen's University BelfastBelfastUnited Kingdom
| | - Steve Hoffmann
- Computational Biology Group, Leibniz Institute on Aging – Fritz Lipmann Institute (FLI)JenaGermany
| | - Martin Fischer
- Computational Biology Group, Leibniz Institute on Aging – Fritz Lipmann Institute (FLI)JenaGermany
| |
Collapse
|
406
|
van de Grift YBC, Heijmans N, van Amerongen R. How to Use Online Tools to Generate New Hypotheses for Mammary Gland Biology Research: A Case Study for Wnt7b. J Mammary Gland Biol Neoplasia 2020; 25:319-335. [PMID: 33625717 PMCID: PMC7960620 DOI: 10.1007/s10911-020-09474-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 11/25/2020] [Indexed: 12/21/2022] Open
Abstract
An increasing number of '-omics' datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific '-omics' datasets and thereby expand the in silico toolbox.
Collapse
Affiliation(s)
- Yorick Bernardus Cornelis van de Grift
- Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands
| | - Nika Heijmans
- Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands
| | - Renée van Amerongen
- Developmental, Stem Cell and Cancer Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, the Netherlands.
| |
Collapse
|
407
|
Lin L, Holmes B, Shen MW, Kammeron D, Geijsen N, Gifford DK, Sherwood RI. Comprehensive Mapping of Key Regulatory Networks that Drive Oncogene Expression. Cell Rep 2020; 33:108426. [PMID: 33238122 PMCID: PMC7724632 DOI: 10.1016/j.celrep.2020.108426] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 10/12/2020] [Accepted: 11/02/2020] [Indexed: 02/06/2023] Open
Abstract
Gene expression is controlled by the collective binding of transcription factors to cis-regulatory regions. Deciphering gene-centered regulatory networks is vital to understanding and controlling gene misexpression in human disease; however, systematic approaches to uncovering regulatory networks have been lacking. Here we present high-throughput interrogation of gene-centered activation networks (HIGAN), a pipeline that employs a suite of multifaceted genomic approaches to connect upstream signaling inputs, trans-acting TFs, and cis-regulatory elements. We apply HIGAN to understand the aberrant activation of the cytidine deaminase APOBEC3B, an intrinsic source of cancer hypermutation. We reveal that nuclear factor κB (NF-κB) and AP-1 pathways are the most salient trans-acting inputs, with minor roles for other inflammatory pathways. We identify a cis-regulatory architecture dominated by a major intronic enhancer that requires coordinated NF-κB and AP-1 activity with secondary inputs from distal regulatory regions. Our data demonstrate how integration of cis and trans genomic screening platforms provides a paradigm for building gene-centered regulatory networks.
Collapse
Affiliation(s)
- Lin Lin
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences, Utrecht 3584 CT, the Netherlands
| | - Benjamin Holmes
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Max W Shen
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Darnell Kammeron
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences, Utrecht 3584 CT, the Netherlands
| | - Niels Geijsen
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences, Utrecht 3584 CT, the Netherlands; Department of Anatomy and Embryology, Leiden University Medical Center, Leiden 2300 RC, the Netherlands.
| | - David K Gifford
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Richard I Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA; Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences, Utrecht 3584 CT, the Netherlands.
| |
Collapse
|
408
|
Ho C, Lin CY. Genes Associated with Calcium Signaling are Involved in Alcohol-Induced Breast Cancer Growth. Alcohol Clin Exp Res 2020; 45:79-91. [PMID: 33222221 DOI: 10.1111/acer.14521] [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: 09/03/2020] [Revised: 10/26/2020] [Accepted: 11/16/2020] [Indexed: 11/27/2022]
Abstract
BACKGROUND Alcohol consumption is a risk factor for breast cancer, contributing to up to nearly 23,000 new cases each year. Mechanistic studies show that alcohol increases tumor aggressiveness and metastatic potential, promotes angiogenesis, induces chronic inflammation, and dysregulates RNA polymerase III-related genes. Alcohol has also been shown to affect estrogen signaling in breast cancer, including in our study of the transcriptomic effects of alcohol in breast cancer cells. METHODS To elucidate mechanisms of action of alcohol in breast cancer, we carried out secondary analyses of our alcohol-responsive transcriptome data using gene ontology and pathway databases and analysis tools and cistromic data analysis of candidate transcription factors which may mediate the transcriptomic alterations. Predicted alcohol-responsive pathways and mechanisms were perturbed and examined experimentally in breast cancer cells. The clinical relevance of identified genes was determined by expression profiles in patient samples and correlation with disease outcomes and alcohol consumption in previously published study cohorts. RESULTS Gene ontology analysis showed that alcohol alters the expression of many metabolism-related genes, and cistromic data of differentially expressed genes revealed the potential involvement of nuclear factor of activated T cells 3 (NFATC3) in mediating the transcriptomic effects of alcohol. Pathway analysis also predicted regulation of calcium signaling by alcohol in breast cancer cells. Chemical perturbation of this pathway reversed the effect of alcohol on breast cancer cell growth and reduced the elevated cytosolic Ca2+ levels induced by alcohol. Expression levels of alcohol-responsive genes in tumor samples from breast cancer patients are associated with poor disease outcomes. Moreover, expression of some of these genes was altered in breast cancer patients who consumed alcohol previously as compared to those who did not drink. CONCLUSION Alcohol alters expression of genes that regulate intracellular calcium levels and downstream signaling pathways which drive breast cancer cell proliferation and disease progression.
Collapse
Affiliation(s)
- Charles Ho
- From the, Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Science & Engineering Research Center, Houston, Texas, USA
| | - Chin-Yo Lin
- From the, Center for Nuclear Receptors and Cell Signaling, Department of Biology and Biochemistry, University of Houston, Science & Engineering Research Center, Houston, Texas, USA
| |
Collapse
|
409
|
Wang Z, Guan W, Wang M, Chen J, Zhang L, Xiao Y, Wang L, Li Y, Yu L. AML1-ETO inhibits acute myeloid leukemia immune escape by CD48. Leuk Lymphoma 2020; 62:937-943. [PMID: 33225787 DOI: 10.1080/10428194.2020.1849680] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Zhiding Wang
- Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, Shenzhen, China
- Department of Hematology, Chinese PLA General Hospital, Beijing, China
| | - Wei Guan
- Department of Hematology, Chinese PLA General Hospital, Beijing, China
| | - Mengzhen Wang
- Department of Hematology, Chinese PLA General Hospital, Beijing, China
| | - Jinghong Chen
- Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, Shenzhen, China
| | - Linlin Zhang
- Department of Hematology, Chinese PLA General Hospital, Beijing, China
| | - Yang Xiao
- Department of Hematology, Chinese PLA General Hospital, Beijing, China
| | - Lixin Wang
- Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, Shenzhen, China
| | - Yonghui Li
- Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, Shenzhen, China
| | - Li Yu
- Department of Hematology-Oncology, International Cancer Center, Shenzhen University General Hospital, Shenzhen University Health Science Center, Shenzhen, China
- Department of Hematology, Chinese PLA General Hospital, Beijing, China
| |
Collapse
|
410
|
Mei S, Huang X, Xie C, Mora A. GREG-studying transcriptional regulation using integrative graph databases. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5735477. [PMID: 32055858 PMCID: PMC7018612 DOI: 10.1093/database/baz162] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/08/2019] [Accepted: 12/31/2019] [Indexed: 01/08/2023]
Abstract
A gene regulatory process is the result of the concerted action of transcription factors, co-factors, regulatory non-coding RNAs (ncRNAs) and chromatin interactions. Therefore, the combination of protein-DNA, protein-protein, ncRNA-DNA, ncRNA-protein and DNA-DNA data in a single graph database offers new possibilities regarding generation of biological hypotheses. GREG (The Gene Regulation Graph Database) is an integrative database and web resource that allows the user to visualize and explore the network of all above-mentioned interactions for a query transcription factor, long non-coding RNA, genomic range or DNA annotation, as well as extracting node and interaction information, identifying connected nodes and performing advanced graphical queries directly on the regulatory network, in a simple and efficient way. In this article, we introduce GREG together with some application examples (including exploratory research of Nanog's regulatory landscape and the etiology of chronic obstructive pulmonary disease), which we use as a demonstration of the advantages of using graph databases in biomedical research. Database URL: https://mora-lab.github.io/projects/greg.html, www.moralab.science/GREG/.
Collapse
Affiliation(s)
- Songqing Mei
- School of Basic Medical Sciences, Guangzhou Medical University, Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China
| | - Xiaowei Huang
- Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China
| | - Chengshu Xie
- Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China
| | - Antonio Mora
- Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China
| |
Collapse
|
411
|
Chen YX, Rong Y, Jiang F, Chen JB, Duan YY, Dong SS, Zhu DL, Chen H, Yang TL, Dai Z, Guo Y. An integrative multi-omics network-based approach identifies key regulators for breast cancer. Comput Struct Biotechnol J 2020; 18:2826-2835. [PMID: 33133424 PMCID: PMC7585874 DOI: 10.1016/j.csbj.2020.10.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 09/13/2020] [Accepted: 10/01/2020] [Indexed: 02/06/2023] Open
Abstract
Although genome-wide association studies (GWASs) have successfully identified thousands of risk variants for human complex diseases, understanding the biological function and molecular mechanisms of the associated SNPs involved in complex diseases is challenging. Here we developed a framework named integrative multi-omics network-based approach (IMNA), aiming to identify potential key genes in regulatory networks by integrating molecular interactions across multiple biological scales, including GWAS signals, gene expression-based signatures, chromatin interactions and protein interactions from the network topology. We applied this approach to breast cancer, and prioritized key genes involved in regulatory networks. We also developed an abnormal gene expression score (AGES) signature based on the gene expression deviation of the top 20 rank-ordered genes in breast cancer. The AGES values are associated with genetic variants, tumor properties and patient survival outcomes. Among the top 20 genes, RNASEH2A was identified as a new candidate gene for breast cancer. Thus, our integrative network-based approach provides a genetic-driven framework to unveil tissue-specific interactions from multiple biological scales and reveal potential key regulatory genes for breast cancer. This approach can also be applied in other complex diseases such as ovarian cancer to unravel underlying mechanisms and help for developing therapeutic targets.
Collapse
Affiliation(s)
- Yi-Xiao Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Yu Rong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Feng Jiang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Jia-Bin Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Dong-Li Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China.,Research Institute of Xi'an Jiaotong University, Zhejiang Province 311215, PR China
| | - Hao Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China.,Research Institute of Xi'an Jiaotong University, Zhejiang Province 311215, PR China
| | - Zhijun Dai
- Department of Breast Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province 310003, PR China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, PR China
| |
Collapse
|
412
|
Huang D, Yi X, Zhou Y, Yao H, Xu H, Wang J, Zhang S, Nong W, Wang P, Shi L, Xuan C, Li M, Wang J, Li W, Kwan HS, Sham PC, Wang K, Li MJ. Ultrafast and scalable variant annotation and prioritization with big functional genomics data. Genome Res 2020; 30:1789-1801. [PMID: 33060171 PMCID: PMC7706736 DOI: 10.1101/gr.267997.120] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 09/22/2020] [Indexed: 02/06/2023]
Abstract
The advances of large-scale genomics studies have enabled compilation of cell type–specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.
Collapse
Affiliation(s)
- Dandan Huang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xianfu Yi
- School of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hongcheng Yao
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Hang Xu
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Jianhua Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Wenyan Nong
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Panwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona 85259, USA
| | - Lei Shi
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Chenghao Xuan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Miaoxin Li
- Center for Genome Research, Center for Precision Medicine, Zhongshan School of Medicine, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China
| | - Junwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona 85259, USA
| | - Weidong Li
- Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hoi Shan Kwan
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Pak Chung Sham
- Centre of Genomics Sciences, Departments of Psychiatry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, USA
| | - Mulin Jun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| |
Collapse
|
413
|
Gu SS, Wang X, Hu X, Jiang P, Li Z, Traugh N, Bu X, Tang Q, Wang C, Zeng Z, Fu J, Meyer C, Zhang Y, Cejas P, Lim K, Wang J, Zhang W, Tokheim C, Sahu AD, Xing X, Kroger B, Ouyang Z, Long H, Freeman GJ, Brown M, Liu XS. Clonal tracing reveals diverse patterns of response to immune checkpoint blockade. Genome Biol 2020; 21:263. [PMID: 33059736 PMCID: PMC7559192 DOI: 10.1186/s13059-020-02166-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 09/15/2020] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Immune checkpoint blockade (ICB) therapy has improved patient survival in a variety of cancers, but only a minority of cancer patients respond. Multiple studies have sought to identify general biomarkers of ICB response, but elucidating the molecular and cellular drivers of resistance for individual tumors remains challenging. We sought to determine whether a tumor with defined genetic background exhibits a stereotypic or heterogeneous response to ICB treatment. RESULTS We establish a unique mouse system that utilizes clonal tracing and mathematical modeling to monitor the growth of each cancer clone, as well as the bulk tumor, in response to ICB. We find that tumors derived from the same clonal populations showed heterogeneous ICB response and diverse response patterns. Primary response is associated with higher immune infiltration and leads to enrichment of pre-existing ICB-resistant cancer clones. We further identify several cancer cell-intrinsic gene expression signatures associated with ICB resistance, including increased interferon response genes and glucocorticoid response genes. These findings are supported by clinical data from ICB treatment cohorts. CONCLUSIONS Our study demonstrates diverse response patterns from the same ancestor cancer cells in response to ICB. This suggests the value of monitoring clonal constitution and tumor microenvironment over time to optimize ICB response and to design new combination therapies. Furthermore, as ICB response may enrich for cancer cell-intrinsic resistance signatures, this can affect interpretations of tumor RNA-seq data for response-signature association studies.
Collapse
Affiliation(s)
- Shengqing Stan Gu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Xiaoqing Wang
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Xihao Hu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Peng Jiang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Ziyi Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Nicole Traugh
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
| | - Xia Bu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Qin Tang
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Chenfei Wang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Zexian Zeng
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Jingxin Fu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Cliff Meyer
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Yi Zhang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Paloma Cejas
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Klothilda Lim
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Jin Wang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Wubing Zhang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Collin Tokheim
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Avinash Das Sahu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Xiaofang Xing
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Division of Gastrointestinal Cancer Translational Research Laboratory, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Benjamin Kroger
- University of Texas Southwestern Medical School, Dallas, TX, 75390, USA
| | - Zhangyi Ouyang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Henry Long
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Gordon J Freeman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
- Harvard Medical School, Boston, MA, 02115, USA.
| | - Myles Brown
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
- Harvard Medical School, Boston, MA, 02115, USA.
| | - X Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA.
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
| |
Collapse
|
414
|
Meyer CA, Liu XS. Computational Approaches to Modeling Transcription Factor Activity and Gene Regulation. Trends Biochem Sci 2020; 45:1094-1095. [PMID: 33051080 DOI: 10.1016/j.tibs.2020.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 09/21/2020] [Indexed: 12/01/2022]
Affiliation(s)
- Clifford A Meyer
- Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA.
| | - X Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| |
Collapse
|
415
|
Guan X, Deng H, Choi UL, Li Z, Yang Y, Zeng J, Liu Y, Zhang X, Li G. EZH2 overexpression dampens tumor-suppressive signals via an EGR1 silencer to drive breast tumorigenesis. Oncogene 2020; 39:7127-7141. [PMID: 33009487 DOI: 10.1038/s41388-020-01484-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 08/27/2020] [Accepted: 09/21/2020] [Indexed: 02/08/2023]
Abstract
The mechanism underlying EZH2 overexpression in breast cancer and its involvement in tumorigenesis remain poorly understood. In this study, we developed an approach to systematically identify the trans-acting factors regulating the EZH2 expression, and identified more than 20 such factors. We revealed reciprocal regulation of early growth response 1 (EGR1) and EZH2: EGR1 activates the expression of EZH2, and EZH2 represses EGR1 expression. Using CRISPR-mediated genome/epigenome editing, we demonstrated that EHZ2 represses EGR1 expression through a silencer downstream of the EGR1 gene. Deletion of the EGR1 silencer resulted in reduced cell growth, invasion, tumorigenicity of breast cancer cells, and extensive changes in gene expression, such as upregulation of GADD45, DDIT3, and RND1; and downregulation of genes encoding cholesterol biosynthesis pathway enzymes. We hypothesize that EZH2/PRC2 acts as a "brake" for EGR1 expression by targeting the EGR1 silencer, and EZH2 overexpression dampens tumor-suppressive signals mediated by EGR1 to drive breast tumorigenesis.
Collapse
Affiliation(s)
- Xiaowen Guan
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Houliang Deng
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Un Lam Choi
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Zhengfeng Li
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Yiqi Yang
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Jianming Zeng
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Yunze Liu
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Xuanjun Zhang
- Faculty of Health Sciences, University of Macau, Macau, China.,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China.,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
| | - Gang Li
- Faculty of Health Sciences, University of Macau, Macau, China. .,Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, China. .,Centre of Reproduction, Development and Aging, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China.
| |
Collapse
|
416
|
Miao B, Fu S, Lyu C, Gontarz P, Wang T, Zhang B. Tissue-specific usage of transposable element-derived promoters in mouse development. Genome Biol 2020; 21:255. [PMID: 32988383 PMCID: PMC7520981 DOI: 10.1186/s13059-020-02164-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 09/07/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Transposable elements (TEs) are a significant component of eukaryotic genomes and play essential roles in genome evolution. Mounting evidence indicates that TEs are highly transcribed in early embryo development and contribute to distinct biological functions and tissue morphology. RESULTS We examine the epigenetic dynamics of mouse TEs during the development of five tissues: intestine, liver, lung, stomach, and kidney. We found that TEs are associated with over 20% of open chromatin regions during development. Close to half of these accessible TEs are only activated in a single tissue and a specific developmental stage. Most accessible TEs are rodent-specific. Across these five tissues, 453 accessible TEs are found to create the transcription start sites of downstream genes in mouse, including 117 protein-coding genes and 144 lincRNA genes, 93.7% of which are mouse-specific. Species-specific TE-derived transcription start sites are found to drive the expression of tissue-specific genes and change their tissue-specific expression patterns during evolution. CONCLUSION Our results suggest that TE insertions increase the regulatory potential of the genome, and some TEs have been domesticated to become a crucial component of gene and regulate tissue-specific expression during mouse tissue development.
Collapse
Affiliation(s)
- Benpeng Miao
- Department of Developmental Biology, Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
- Department of Genetics, Edison Family Center for Genomic Sciences and Systems Biology, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Shuhua Fu
- Department of Developmental Biology, Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Cheng Lyu
- Department of Developmental Biology, Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Paul Gontarz
- Department of Developmental Biology, Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Ting Wang
- Department of Genetics, Edison Family Center for Genomic Sciences and Systems Biology, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, 63108, USA.
| | - Bo Zhang
- Department of Developmental Biology, Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA.
| |
Collapse
|
417
|
Hu G, Dong X, Gong S, Song Y, Hutchins AP, Yao H. Systematic screening of CTCF binding partners identifies that BHLHE40 regulates CTCF genome-wide distribution and long-range chromatin interactions. Nucleic Acids Res 2020; 48:9606-9620. [PMID: 32885250 PMCID: PMC7515718 DOI: 10.1093/nar/gkaa705] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 07/27/2020] [Accepted: 08/14/2020] [Indexed: 11/14/2022] Open
Abstract
CTCF plays a pivotal role in mediating chromatin interactions, but it does not do so alone. A number of factors have been reported to co-localize with CTCF and regulate CTCF loops, but no comprehensive analysis of binding partners has been performed. This prompted us to identify CTCF loop participants and regulators by co-localization analysis with CTCF. We screened all factors that had ChIP-seq data in humans by co-localization analysis with human super conserved CTCF (hscCTCF) binding sites, and identified many new factors that overlapped with hscCTCF binding sites. Combined with CTCF loop information, we observed that clustered factors could promote CTCF loops. After in-depth mining of each factor, we found that many factors might have the potential to promote CTCF loops. Our data further demonstrated that BHLHE40 affected CTCF loops by regulating CTCF binding. Together, this study revealed that many factors have the potential to participate in or regulate CTCF loops, and discovered a new role for BHLHE40 in modulating CTCF loop formation.
Collapse
Affiliation(s)
- Gongcheng Hu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou 510530, China.,Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health GuangDong Laboratory), Guangzhou 510005, China.,Institute of Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaotao Dong
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou 510530, China.,Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health GuangDong Laboratory), Guangzhou 510005, China.,Institute of Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shixin Gong
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou 510530, China.,Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health GuangDong Laboratory), Guangzhou 510005, China.,Institute of Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yawei Song
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou 510530, China.,Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health GuangDong Laboratory), Guangzhou 510005, China.,Institute of Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Andrew P Hutchins
- Department of Biology, Southern University of Science and Technology, Shenzhen 518055, China
| | - Hongjie Yao
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou 510530, China.,Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health GuangDong Laboratory), Guangzhou 510005, China.,Institute of Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
418
|
Shim S, Seo PJ. EAT-UpTF: Enrichment Analysis Tool for Upstream Transcription Factors of a Group of Plant Genes. Front Genet 2020; 11:566569. [PMID: 33024441 PMCID: PMC7516213 DOI: 10.3389/fgene.2020.566569] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 08/17/2020] [Indexed: 12/02/2022] Open
Abstract
EAT-UpTF (Enrichment Analysis Tool for Upstream Transcription Factors of a group of plant genes) is an open-source Python script that analyzes the enrichment of upstream transcription factors (TFs) in a group of genes-of-interest (GOIs). EAT-UpTF utilizes genome-wide lists of TF-target genes generated by DNA affinity purification followed by sequencing (DAP-seq) or chromatin immunoprecipitation followed by sequencing (ChIP-seq). Unlike previous methods based on the two-step prediction of cis-motifs and DNA-element-binding TFs, our EAT-UpTF analysis enabled a one-step identification of enriched upstream TFs in a set of GOIs using lists of empirically determined TF-target genes. The tool is designed particularly for plant researches, due to the lack of analytic tools for upstream TF enrichment, and available at https://github.com/sangreashim/EAT-UpTF and http://chromatindynamics.snu.ac.kr:8080/EatupTF.
Collapse
Affiliation(s)
- Sangrea Shim
- Department of Chemistry, Seoul National University, Seoul, South Korea
- Plant Genomics and Breeding Institute, Seoul National University, Seoul, South Korea
| | - Pil Joon Seo
- Department of Chemistry, Seoul National University, Seoul, South Korea
- Plant Genomics and Breeding Institute, Seoul National University, Seoul, South Korea
- Research Institute of Basic Sciences, Seoul National University, Seoul, South Korea
| |
Collapse
|
419
|
Peng T, Zhai Y, Atlasi Y, Ter Huurne M, Marks H, Stunnenberg HG, Megchelenbrink W. STARR-seq identifies active, chromatin-masked, and dormant enhancers in pluripotent mouse embryonic stem cells. Genome Biol 2020; 21:243. [PMID: 32912294 PMCID: PMC7488044 DOI: 10.1186/s13059-020-02156-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Accepted: 08/26/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Enhancers are distal regulators of gene expression that shape cell identity and control cell fate transitions. In mouse embryonic stem cells (mESCs), the pluripotency network is maintained by the function of a complex network of enhancers, that are drastically altered upon differentiation. Genome-wide chromatin accessibility and histone modification assays are commonly used as a proxy for identifying putative enhancers and for describing their activity levels and dynamics. RESULTS Here, we applied STARR-seq, a genome-wide plasmid-based assay, as a read-out for the enhancer landscape in "ground-state" (2i+LIF; 2iL) and "metastable" (serum+LIF; SL) mESCs. This analysis reveals that active STARR-seq loci show modest overlap with enhancer locations derived from peak calling of ChIP-seq libraries for common enhancer marks. We unveil ZIC3-bound loci with significant STARR-seq activity in SL-ESCs. Knock-out of Zic3 removes STARR-seq activity only in SL-ESCs and increases their propensity to differentiate towards the endodermal fate. STARR-seq also reveals enhancers that are not accessible, masked by a repressive chromatin signature. We describe a class of dormant, p53 bound enhancers that gain H3K27ac under specific conditions, such as after treatment with Nocodazol, or transiently during reprogramming from fibroblasts to pluripotency. CONCLUSIONS In conclusion, loci identified as active by STARR-seq often overlap with those identified by chromatin accessibility and active epigenetic marking, yet a significant fraction is epigenetically repressed or display condition-specific enhancer activity.
Collapse
Affiliation(s)
- Tianran Peng
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands
| | - Yanan Zhai
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS, Utrecht, The Netherlands
- Department of Precision Medicine, University of Campania Luigi Vanvitelli, Vico L. De Crecchio 7, 80138, Naples, Italy
| | - Yaser Atlasi
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands
| | - Menno Ter Huurne
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands
| | - Hendrik Marks
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands
| | - Hendrik G Stunnenberg
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands.
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS, Utrecht, The Netherlands.
| | - Wout Megchelenbrink
- Department of Molecular Biology, Radboud Institute for Molecular Life Sciences, Radboud University, Geert Grooteplein Zuid 28, 6525 GA, Nijmegen, The Netherlands.
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584 CS, Utrecht, The Netherlands.
- Department of Precision Medicine, University of Campania Luigi Vanvitelli, Vico L. De Crecchio 7, 80138, Naples, Italy.
| |
Collapse
|
420
|
Tenney AP, Livet J, Belton T, Prochazkova M, Pearson EM, Whitman MC, Kulkarni AB, Engle EC, Henderson CE. Etv1 Controls the Establishment of Non-overlapping Motor Innervation of Neighboring Facial Muscles during Development. Cell Rep 2020; 29:437-452.e4. [PMID: 31597102 PMCID: PMC7032945 DOI: 10.1016/j.celrep.2019.08.078] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 06/16/2019] [Accepted: 08/22/2019] [Indexed: 01/06/2023] Open
Abstract
The somatotopic motor-neuron projections onto their cognate target muscles are essential for coordinated movement, but how that occurs for facial motor circuits, which have critical roles in respiratory and interactive behaviors, is poorly understood. We report extensive molecular heterogeneity in developing facial motor neurons in the mouse and identify markers of subnuclei and the motor pools innervating specific facial muscles. Facial subnuclei differentiate during migration to the ventral hindbrain, where neurons with progressively later birth dates—and evolutionarily more recent functions—settle in more-lateral positions. One subpopulation marker, ETV1, determines both positional and target muscle identity for neurons of the dorsolateral (DL) subnucleus. In Etv1 mutants, many markers of DL differentiation are lost, and individual motor pools project indifferently to their own and neighboring muscle targets. The resulting aberrant activation patterns are reminiscent of the facial synkinesis observed in humans after facial nerve injury. Tenney et al. demonstrate that embryonic facial motor neurons are transcriptionally diverse as they establish somatotopic innervation of the facial muscles, a process that requires the transcription factor ETV1. Facial-motor axon-targeting errors in Etv1 mutants cause coordination of whisking and eyeblink evocative of human blepharospasm.
Collapse
Affiliation(s)
- Alan P Tenney
- Center for Motor Neuron Biology and Disease (MNC), Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA.
| | - Jean Livet
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, 75012 Paris, France
| | - Timothy Belton
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
| | - Michaela Prochazkova
- Functional Genomics Section, National Institute of Dental and Craniofacial Research, NIH, Bethesda, MD 20892, USA
| | - Erica M Pearson
- Center for Motor Neuron Biology and Disease (MNC), Columbia University, New York, NY 10032, USA; Department of Neuroscience, Columbia University, New York, NY 10032, USA
| | - Mary C Whitman
- Department of Ophthalmology, Boston Children's Hospital/Harvard Medical School, Boston, MA 02115, USA
| | - Ashok B Kulkarni
- Functional Genomics Section, National Institute of Dental and Craniofacial Research, NIH, Bethesda, MD 20892, USA
| | - Elizabeth C Engle
- Department of Neurology, Boston Children's Hospital/Harvard Medical School, Boston, MA 02115, USA; Department of Ophthalmology, Boston Children's Hospital/Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Christopher E Henderson
- Center for Motor Neuron Biology and Disease (MNC), Columbia University, New York, NY 10032, USA; Columbia Stem Cell Initiative (CSCI), Columbia University, New York, NY 10032, USA; Columbia Translational Neuroscience Initiative (CTNI), Columbia University, New York, NY 10032, USA; Department of Rehabilitation and Regenerative Medicine, Columbia University, New York, NY 10032, USA; Department of Pathology and Cell Biology, Columbia University, New York, NY 10032, USA; Department of Neurology, Columbia University, New York, NY 10032, USA; Department of Neuroscience, Columbia University, New York, NY 10032, USA
| |
Collapse
|
421
|
Calcium signaling and epigenetics: A key point to understand carcinogenesis. Cell Calcium 2020; 91:102285. [PMID: 32942140 DOI: 10.1016/j.ceca.2020.102285] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 08/22/2020] [Accepted: 08/26/2020] [Indexed: 02/07/2023]
Abstract
Calcium (Ca2+) signaling controls a wide range of cellular processes, including the hallmarks of cancer. The Ca2+ signaling system encompasses several types of proteins, such as receptors, channels, pumps, exchangers, buffers, and sensors, of which several are mutated or with altered expression in cancer cells. Since epigenetic mechanisms are disrupted in all stages of carcinogenesis, and reversibly regulate gene expression, they have been studied by different research groups to understand their role in Ca2+ signaling remodeling in cancer cells and the carcinogenic process. In this review, we link Ca2+ signaling, cancer, and epigenetics fields to generate a comprehensive landscape of this complex group of diseases.
Collapse
|
422
|
Zhang Y, Huang YX, Wang DL, Yang B, Yan HY, Lin LH, Li Y, Chen J, Xie LM, Huang YS, Liao JY, Hu KS, He JH, Saw PE, Xu X, Yin D. LncRNA DSCAM-AS1 interacts with YBX1 to promote cancer progression by forming a positive feedback loop that activates FOXA1 transcription network. Theranostics 2020; 10:10823-10837. [PMID: 32929382 PMCID: PMC7482804 DOI: 10.7150/thno.47830] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/15/2020] [Indexed: 12/21/2022] Open
Abstract
Rationale: The forkhead box A1 (FOXA1) is a crucial transcription factor in initiation and development of breast, lung and prostate cancer. Previous studies about the FOXA1 transcriptional network were mainly focused on protein-coding genes. Its regulatory network of long non-coding RNAs (lncRNAs) and their role in FOXA1 oncogenic activity remains unknown. Methods: The Cancer Genome Atlas (TCGA) data, RNA-seq and ChIP-seq data were used to analyze FOXA1 regulated lncRNAs. RT-qPCR was used to detect the expression of DSCAM-AS1, RT-qPCR and Western blotting were used to determine the expression of FOXA1, estrogen receptor α (ERα) and Y box binding protein 1 (YBX1). RNA pull-down and RIP-qPCR were employed to investigate the interaction between DSCAM-AS1 and YBX1. The effect of DSCAM-AS1 on malignant phenotypes was examined through in vitro and in vivo assays. Results: In this study, we conducted a global analysis of FOXA1 regulated lncRNAs. For detailed analysis, we chose lncRNA DSCAM-AS1, which is specifically expressed in lung adenocarcinoma, breast and prostate cancer. The expression level of DSCAM-AS1 is regulated by two super-enhancers (SEs) driven by FOXA1. High expression levels of DSCAM-AS1 was associated with poor prognosis. Knockout experiments showed DSCAM-AS1 was essential for the growth of xenograft tumors. Moreover, we demonstrated DSCAM-AS1 can regulate the expression of the master transcriptional factor FOXA1. In breast cancer, DSCAM-AS1 was also found to regulate ERα. Mechanistically, DSCAM-AS1 interacts with YBX1 and influences the recruitment of YBX1 in the promoter regions of FOXA1 and ERα. Conclusion: Our study demonstrated that lncRNA DSCAM-AS1 was transcriptionally activated by super-enhancers driven by FOXA1 and exhibited lineage-specific expression pattern. DSCAM-AS1 can promote cancer progression by interacting with YBX1 and regulating expression of FOXA1 and ERα.
Collapse
|
423
|
Multiomics data integration unveils core transcriptional regulatory networks governing cell-type identity. NPJ Syst Biol Appl 2020; 6:26. [PMID: 32839455 PMCID: PMC7445234 DOI: 10.1038/s41540-020-00148-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 07/15/2020] [Indexed: 12/20/2022] Open
Abstract
A plethora of computational approaches have been proposed for reconstructing gene regulatory networks (GRNs) from gene expression data. However, gene regulatory processes are often too complex to predict from the transcriptome alone. Here, we present a computational method, Moni, that systematically integrates epigenetics, transcriptomics, and protein–protein interactions to reconstruct GRNs among core transcription factors and their co-factors governing cell identity. We applied Moni to 57 datasets of human cell types and lines and demonstrate that it can accurately infer GRNs, thereby outperforming state-of-the-art methods.
Collapse
|
424
|
Mapping the Effects of Genetic Variation on Chromatin State and Gene Expression Reveals Loci That Control Ground State Pluripotency. Cell Stem Cell 2020; 27:459-469.e8. [PMID: 32795400 DOI: 10.1016/j.stem.2020.07.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 02/07/2020] [Accepted: 07/02/2020] [Indexed: 12/23/2022]
Abstract
Mouse embryonic stem cells (mESCs) cultured in the presence of LIF occupy a ground state with highly active pluripotency-associated transcriptional and epigenetic circuitry. However, ground state pluripotency in some inbred strain backgrounds is unstable in the absence of ERK1/2 and GSK3 inhibition. Using an unbiased genetic approach, we dissect the basis of this divergent response to extracellular cues by profiling gene expression and chromatin accessibility in 170 genetically heterogeneous mESCs. We map thousands of loci affecting chromatin accessibility and/or transcript abundance, including 10 QTL hotspots where genetic variation at a single locus coordinates the regulation of genes throughout the genome. For one hotspot, we identify a single enhancer variant ∼10 kb upstream of Lifr associated with chromatin accessibility and mediating a cascade of molecular events affecting pluripotency. We validate causation through reciprocal allele swaps, demonstrating the functional consequences of noncoding variation in gene regulatory networks that stabilize pluripotent states in vitro.
Collapse
|
425
|
Wang C, Sun D, Huang X, Wan C, Li Z, Han Y, Qin Q, Fan J, Qiu X, Xie Y, Meyer CA, Brown M, Tang M, Long H, Liu T, Liu XS. Integrative analyses of single-cell transcriptome and regulome using MAESTRO. Genome Biol 2020; 21:198. [PMID: 32767996 PMCID: PMC7412809 DOI: 10.1186/s13059-020-02116-x] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 07/23/2020] [Indexed: 12/15/2022] Open
Abstract
We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses of single-cell RNA-seq (scRNA-seq) and ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions for pre-processing, alignment, quality control, expression and chromatin accessibility quantification, clustering, differential analysis, and annotation. By modeling gene regulatory potential from chromatin accessibilities at the single-cell level, MAESTRO outperforms the existing methods for integrating the cell clusters between scRNA-seq and scATAC-seq. Furthermore, MAESTRO supports automatic cell-type annotation using predefined cell type marker genes and identifies driver regulators from differential scRNA-seq genes and scATAC-seq peaks.
Collapse
Affiliation(s)
- Chenfei Wang
- Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Dongqing Sun
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Xin Huang
- Beijing Institute of Radiation Medicine, Beijing, 100850, China
| | - Changxin Wan
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Ziyi Li
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Ya Han
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Qian Qin
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Jingyu Fan
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Science and Technology, Tongji University, Shanghai, 200433, China
| | - Xintao Qiu
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - Yingtian Xie
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - Clifford A Meyer
- Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Myles Brown
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - Ming Tang
- Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Henry Long
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - Tao Liu
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263, USA.
| | - X Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA.
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
| |
Collapse
|
426
|
Tang Y, Hu Y, Wang J, Zeng Z. A novel risk score based on a combined signature of 10 immune system genes to predict bladder cancer prognosis. Int Immunopharmacol 2020; 87:106851. [PMID: 32763782 DOI: 10.1016/j.intimp.2020.106851] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/20/2020] [Accepted: 07/26/2020] [Indexed: 12/19/2022]
Abstract
Bladder cancer (BC) is a common internal malignant tumor with a poor prognosis worldwide. There is an urgent need to better understand the pathogenesis and progression of BC and to find useful biomarkers for diagnosis and prognosis. This study was aimed at developing a potential immunogenomic prognostic signature for BC patients. To identify possible immune-system-related genes (IRGs) whose parameters predict the survival of BC patients, we chose 371 BC patients and analyzed differentially expressed IRGs from The Cancer Genome Atlas (TCGA) datasets. We then derived a 10-IRG formula, including MMP9, RBP7, PDGFRA, AHNAK, OAS1, OLR1, RAC3, SLIT2, IGF1, and AGTR1, to estimate BC prognosis. To validate the mRNA levels of these IRGs, we performed quantitative PCR and found that the expression of these genes almost matched the corresponding mRNA expression levels in TCGA. Furthermore, we validated the prognostic value of the new risk model using two external datasets from Gene Expression Omnibus: GSE13507 (n = 165) and GSE32894 (n = 224). Our data pointed to a significant correlation between the risk model and patients' prognosis. Bioinformatic analysis revealed that products of the IRGs have possible effects on tumor immune processes such as an inflammatory response and cytokine-cytokine receptor interaction. Finally, assessment of the clinical value of the immune-system-based risk signature showed that several of these IRGs were differentially expressed between patients with different clinical characteristics: a high risk score positively correlated with female sex, advanced tumor stage, more advanced T stage, and lymph node metastasis. This immunogenomic signature may represents a reliable prognostic tool for BC and can help to design an individualized immunotherapy.
Collapse
Affiliation(s)
- Yunliang Tang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China; Department of Critical Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Yangyang Hu
- Department of Pharmacology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Jiao Wang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
| | - Zhenguo Zeng
- Department of Critical Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
| |
Collapse
|
427
|
Guan D, Xiong Y, Trinh TM, Xiao Y, Hu W, Jiang C, Dierickx P, Jang C, Rabinowitz JD, Lazar MA. The hepatocyte clock and feeding control chronophysiology of multiple liver cell types. Science 2020; 369:1388-1394. [PMID: 32732282 DOI: 10.1126/science.aba8984] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 07/16/2020] [Indexed: 12/14/2022]
Abstract
Most cells of the body contain molecular clocks, but the requirement of peripheral clocks for rhythmicity and their effects on physiology are not well understood. We show that deletion of core clock components REV-ERBα and REV-ERBβ in adult mouse hepatocytes disrupts diurnal rhythms of a subset of liver genes and alters the diurnal rhythm of de novo lipogenesis. Liver function is also influenced by nonhepatocytic cells, and the loss of hepatocyte REV-ERBs remodels the rhythmic transcriptomes and metabolomes of multiple cell types within the liver. Finally, alteration of food availability demonstrates the hierarchy of the cell-intrinsic hepatocyte clock mechanism and the feeding environment. Together, these studies reveal previously unsuspected roles of the hepatocyte clock in the physiological coordination of nutritional signals and cell-cell communication controlling rhythmic metabolism.
Collapse
Affiliation(s)
- Dongyin Guan
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ying Xiong
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Trang Minh Trinh
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yang Xiao
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Wenxiang Hu
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chunjie Jiang
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Pieterjan Dierickx
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Cholsoon Jang
- Lewis-Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Joshua D Rabinowitz
- Lewis-Sigler Institute for Integrative Genomics and Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Mitchell A Lazar
- Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. .,Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| |
Collapse
|
428
|
Rebollo R, Galvão-Ferrarini M, Gagnier L, Zhang Y, Ferraj A, Beck CR, Lorincz MC, Mager DL. Inter-Strain Epigenomic Profiling Reveals a Candidate IAP Master Copy in C3H Mice. Viruses 2020; 12:v12070783. [PMID: 32708087 PMCID: PMC7411935 DOI: 10.3390/v12070783] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 07/03/2020] [Accepted: 07/13/2020] [Indexed: 12/15/2022] Open
Abstract
Insertions of endogenous retroviruses cause a significant fraction of mutations in inbred mice but not all strains are equally susceptible. Notably, most new Intracisternal A particle (IAP) ERV mutagenic insertions have occurred in C3H mice. We show here that strain-specific insertional polymorphic IAPs accumulate faster in C3H/HeJ mice, relative to other sequenced strains, and that IAP transcript levels are higher in C3H/HeJ embryonic stem (ES) cells compared to other ES cells. To investigate the mechanism for high IAP activity in C3H mice, we identified 61 IAP copies in C3H/HeJ ES cells enriched with H3K4me3 (a mark of active promoters) and, among those tested, all are unmethylated in C3H/HeJ ES cells. Notably, 13 of the 61 are specific to C3H/HeJ and are members of the non-autonomous 1Δ1 IAP subfamily that is responsible for nearly all new insertions in C3H. One copy is full length with intact open reading frames and hence potentially capable of providing proteins in trans to other 1Δ1 elements. This potential “master copy” is present in other strains, including 129, but its 5’ long terminal repeat (LTR) is methylated in 129 ES cells. Thus, the unusual IAP activity in C3H may be due to reduced epigenetic repression coupled with the presence of a master copy.
Collapse
Affiliation(s)
- Rita Rebollo
- Terry Fox Laboratory, British Columbia Cancer, Vancouver, BC V5Z1L3, Canada; (L.G.); (Y.Z.)
- University of Lyon, INSA-Lyon, INRA, BF2i, UMR0203, F-69621 Villeurbanne, France;
- Correspondence: (R.R.); (D.L.M.)
| | | | - Liane Gagnier
- Terry Fox Laboratory, British Columbia Cancer, Vancouver, BC V5Z1L3, Canada; (L.G.); (Y.Z.)
| | - Ying Zhang
- Terry Fox Laboratory, British Columbia Cancer, Vancouver, BC V5Z1L3, Canada; (L.G.); (Y.Z.)
| | - Ardian Ferraj
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030, USA; (A.F.); (C.R.B.)
| | - Christine R. Beck
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030, USA; (A.F.); (C.R.B.)
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Matthew C. Lorincz
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T1Z3, Canada;
| | - Dixie L. Mager
- Terry Fox Laboratory, British Columbia Cancer, Vancouver, BC V5Z1L3, Canada; (L.G.); (Y.Z.)
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T1Z3, Canada;
- Correspondence: (R.R.); (D.L.M.)
| |
Collapse
|
429
|
Thiecke MJ, Wutz G, Muhar M, Tang W, Bevan S, Malysheva V, Stocsits R, Neumann T, Zuber J, Fraser P, Schoenfelder S, Peters JM, Spivakov M. Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers. Cell Rep 2020; 32:107929. [PMID: 32698000 PMCID: PMC7383238 DOI: 10.1016/j.celrep.2020.107929] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 06/01/2020] [Accepted: 06/29/2020] [Indexed: 12/20/2022] Open
Abstract
It is currently assumed that 3D chromosomal organization plays a central role in transcriptional control. However, depletion of cohesin and CTCF affects the steady-state levels of only a minority of transcripts. Here, we use high-resolution Capture Hi-C to interrogate the dynamics of chromosomal contacts of all annotated human gene promoters upon degradation of cohesin and CTCF. We show that a majority of promoter-anchored contacts are lost in these conditions, but many contacts with distinct properties are maintained, and some new ones are gained. The rewiring of contacts between promoters and active enhancers upon cohesin degradation associates with rapid changes in target gene transcription as detected by SLAM sequencing (SLAM-seq). These results provide a mechanistic explanation for the limited, but consistent, effects of cohesin and CTCF depletion on steady-state transcription and suggest the existence of both cohesin-dependent and -independent mechanisms of enhancer-promoter pairing.
Collapse
Affiliation(s)
- Michiel J Thiecke
- Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK
| | - Gordana Wutz
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Matthias Muhar
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Wen Tang
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Stephen Bevan
- Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK; Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, UK
| | - Valeriya Malysheva
- Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK; MRC London Institute of Medical Sciences, London W12 0NN, UK; Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London W12 0NN, UK
| | - Roman Stocsits
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Tobias Neumann
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Johannes Zuber
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Peter Fraser
- Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK; Department of Biological Science, Florida State University, Tallahassee, FL 32301, USA
| | - Stefan Schoenfelder
- Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK; Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, UK
| | - Jan-Michael Peters
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna 1030, Austria
| | - Mikhail Spivakov
- Nuclear Dynamics Programme, Babraham Institute, Cambridge CB22 3AT, UK; MRC London Institute of Medical Sciences, London W12 0NN, UK; Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London W12 0NN, UK.
| |
Collapse
|
430
|
van der Vos KE, Vis DJ, Nevedomskaya E, Kim Y, Choi W, McConkey D, Wessels LFA, van Rhijn BWG, Zwart W, van der Heijden MS. Epigenetic profiling demarcates molecular subtypes of muscle-invasive bladder cancer. Sci Rep 2020; 10:10952. [PMID: 32616859 PMCID: PMC7331601 DOI: 10.1038/s41598-020-67850-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 06/15/2020] [Indexed: 11/13/2022] Open
Abstract
Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease that often recurs despite aggressive treatment with neoadjuvant chemotherapy and (radical) cystectomy. Basal and luminal molecular subtypes have been identified that are linked to clinical characteristics and have differential sensitivities to chemotherapy. While it has been suggested that epigenetic mechanisms play a role in defining these subtypes, a thorough understanding of the biological mechanisms is lacking. This report details the first genome-wide analysis of histone methylation patterns of human primary bladder tumours by chromatin immunoprecipitations and next-generation sequencing (ChIP-seq). We profiled multiple histone marks: H3K27me3, a marker for repressed genes, and H3K4me1 and H3K4me3, which are indicators of active enhancers and active promoters. Integrated analysis of ChIP-seq data and RNA sequencing revealed that H3K4 mono-methylation demarcates MIBC subtypes, while no association was found for the other two histone modifications in relation to basal and luminal subtypes. Additionally, we identified differentially methylated H3K4me1 peaks in basal and luminal tumour samples, suggesting that active enhancers play a role in defining subtypes. Our study is the first analysis of histone modifications in primary bladder cancer tissue and provides an important resource for the bladder cancer community.
Collapse
Affiliation(s)
- K E van der Vos
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - D J Vis
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - E Nevedomskaya
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Division of Oncogenomics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Y Kim
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Division of Oncogenomics, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - W Choi
- Johns Hopkins Greenberg Bladder Cancer Institute, Brady Urological Institute, Johns Hopkins University, Baltimore, MD, USA
| | - D McConkey
- Johns Hopkins Greenberg Bladder Cancer Institute, Brady Urological Institute, Johns Hopkins University, Baltimore, MD, USA
| | - L F A Wessels
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Faculty of EEMCS, Delft University of Technology, Delft, The Netherlands
| | - B W G van Rhijn
- Department of Surgical Oncology (Urology), The Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - W Zwart
- Division of Oncogenomics, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Laboratory of Chemical Biology and Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - M S van der Heijden
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
| |
Collapse
|
431
|
Chen S, Cao GD, Wei W, Yida L, Xiaobo H, Lei Y, Ke C, Chen B, Xiong MM. Prediction and identification of immune genes related to the prognosis of patients with colon adenocarcinoma and its mechanisms. World J Surg Oncol 2020; 18:146. [PMID: 32600423 PMCID: PMC7325073 DOI: 10.1186/s12957-020-01921-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 06/17/2020] [Indexed: 02/06/2023] Open
Abstract
Background Colon adenocarcinoma (COAD) is a gastrointestinal tumor with a high degree of malignancy. Its deterioration process is closely related to the tumor microenvironment, and transcription factors (TF) play a regulatory role in this process. Currently, there is a lack of exploration between the genes related to the COAD tumor microenvironment and the survival prognosis of patients. Models composed of multiple genes usually predict the survival prognosis of patients more accurately than single genes. We can analyze the multigene models that can predict the prognosis of COAD from the current database. Methods The limma package of the R programming language is used for gene differential expression analysis. Kaplan-Meier curve is used to analyze the relationship between the patient risk score model and survival data. The hazard model is used to analyze the relationship between the risk score and the clinical data of COAD patients. The information of immune genes and immune cells is obtained from IMMPORT database and TIMER database. Receiver operating characteristic (ROC) curve is used to judge the stability of the model. Results We found 7 immune genes, which can built a risk score model to predict the survival prognosis of COAD. According to univariate and multivariate analysis, the risk score can be used as an independent predictor. The content of some immune microenvironment cells will also increase as the risk score increases. Conclusions We found 7 immune genes, such as SLC10A2 (solute carrier family 10 member 2), CXCL3 (C-X-C motif chemokine ligand 3), IGHV5-51 (immunoglobulin heavy variable 5-51), INHBA (inhibin subunit beta A), STC1 (stanniocalcin 1), UCN (urocortin), and OXTR (oxytocin receptor), can constitute a model for predicting the prognosis of COAD. They may provide potential therapeutic targets for clinical treatment of COAD.
Collapse
Affiliation(s)
- Sihan Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - G D Cao
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - Wu Wei
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - Lu Yida
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - He Xiaobo
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - Yang Lei
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - Chen Ke
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China
| | - Bo Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China.
| | - Mao Ming Xiong
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Aahui, China.
| |
Collapse
|
432
|
Ameur LB, Marie P, Thenoz M, Giraud G, Combe E, Claude JB, Lemaire S, Fontrodona N, Polveche H, Bastien M, Gessain A, Wattel E, Bourgeois CF, Auboeuf D, Mortreux F. Intragenic recruitment of NF-κB drives splicing modifications upon activation by the oncogene Tax of HTLV-1. Nat Commun 2020; 11:3045. [PMID: 32546717 PMCID: PMC7298006 DOI: 10.1038/s41467-020-16853-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 05/26/2020] [Indexed: 12/15/2022] Open
Abstract
Chronic NF-κB activation in inflammation and cancer has long been linked to persistent activation of NF-κB–responsive gene promoters. However, NF-κB factors also massively bind to gene bodies. Here, we demonstrate that recruitment of the NF-κB factor RELA to intragenic regions regulates alternative splicing upon NF-κB activation by the viral oncogene Tax of HTLV-1. Integrative analyses of RNA splicing and chromatin occupancy, combined with chromatin tethering assays, demonstrate that DNA-bound RELA interacts with and recruits the splicing regulator DDX17, in an NF-κB activation-dependent manner. This leads to alternative splicing of target exons due to the RNA helicase activity of DDX17. Similar results were obtained upon Tax-independent NF-κB activation, indicating that Tax likely exacerbates a physiological process where RELA provides splice target specificity. Collectively, our results demonstrate a physical and direct involvement of NF-κB in alternative splicing regulation, which significantly revisits our knowledge of HTLV-1 pathogenesis and other NF-κB-related diseases. The nuclear factors κB (NF-κB) is a transcription factor involved in immune functions, inflammation, and cancer. Here, the authors show that the NF-κB factor RELA regulates splicing of target genes by recruiting DDX17 on chromatin upon expression of the viral oncogene Tax.
Collapse
Affiliation(s)
- Lamya Ben Ameur
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Paul Marie
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Morgan Thenoz
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France.,Department of Pediatrics and Medical Genetics, Faculty of Medicine and Health Sciences, 9000, Gent, Belgium
| | - Guillaume Giraud
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Emmanuel Combe
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Jean-Baptiste Claude
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Sebastien Lemaire
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Nicolas Fontrodona
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | | | - Marine Bastien
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France.,School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
| | - Antoine Gessain
- Unité d'Epidémiologie et Physiopathologie des Virus Oncogénes, Institut Pasteur, Paris, France
| | - Eric Wattel
- Université Lyon 1, CNRS UMR5239, Oncovirologie et Biothérapies, Faculté de Médecine Lyon Sud, ENS - HCL, Pierre Bénite, France.,Université Lyon 1, Service d'Hématologie, Pavillon Marcel Bérard, Centre Hospitalier Lyon-Sud, Pierre Bénite, France
| | - Cyril F Bourgeois
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France
| | - Didier Auboeuf
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France.
| | - Franck Mortreux
- Laboratory of Biology and Modelling of the Cell, Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, 46 Allée d'Italie Site Jacques Monod, 69007, Lyon, France.
| |
Collapse
|
433
|
Folate Receptor β (FRβ) Expression in Tissue-Resident and Tumor-Associated Macrophages Associates with and Depends on the Expression of PU.1. Cells 2020; 9:cells9061445. [PMID: 32532019 PMCID: PMC7349916 DOI: 10.3390/cells9061445] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/02/2020] [Accepted: 06/08/2020] [Indexed: 02/07/2023] Open
Abstract
As macrophages exhibit a huge functional plasticity under homeostasis and pathological conditions, they have become a therapeutic target for chronic inflammatory diseases. Hence, the identification of macrophage subset-specific markers is a requisite for the development of macrophage-directed therapeutic interventions. In this regard, the macrophage-specific Folate Receptor β (FRβ, encoded by the FOLR2 gene) has been already validated as a target for molecular delivery in cancer as well as in macrophage-targeting therapeutic strategies for chronic inflammatory pathologies. We now show that the transcriptome of human macrophages from healthy and inflamed tissues (tumor; rheumatoid arthritis, RA) share a significant over-representation of the “anti-inflammatory gene set”, which defines the gene profile of M-CSF-dependent IL-10-producing human macrophages (M-MØ). More specifically, FOLR2 expression has been found to strongly correlate with the expression of M-MØ-specific genes in tissue-resident macrophages, tumor-associated macrophages (TAM) and macrophages from inflamed synovium, and also correlates with the presence of the PU.1 transcription factor. In fact, PU.1-binding elements are found upstream of the first exon of FOLR2 and most M-MØ-specific- and TAM-specific genes. The functional relevance of PU.1 binding was demonstrated through analysis of the proximal regulatory region of the FOLR2 gene, whose activity was dependent on a cluster of PU.1-binding sequences. Further, siRNA-mediated knockdown established the importance of PU.1 for FOLR2 gene expression in myeloid cells. Therefore, we provide evidence that FRβ marks tissue-resident macrophages as well as macrophages within inflamed tissues, and its expression is dependent on PU.1.
Collapse
|
434
|
Bernasconi A, Canakoglu A, Masseroli M, Ceri S. The road towards data integration in human genomics: players, steps and interactions. Brief Bioinform 2020; 22:30-44. [PMID: 32496509 DOI: 10.1093/bib/bbaa080] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 03/09/2020] [Accepted: 04/18/2020] [Indexed: 12/15/2022] Open
Abstract
Thousands of new experimental datasets are becoming available every day; in many cases, they are produced within the scope of large cooperative efforts, involving a variety of laboratories spread all over the world, and typically open for public use. Although the potential collective amount of available information is huge, the effective combination of such public sources is hindered by data heterogeneity, as the datasets exhibit a wide variety of notations and formats, concerning both experimental values and metadata. Thus, data integration is becoming a fundamental activity, to be performed prior to data analysis and biological knowledge discovery, consisting of subsequent steps of data extraction, normalization, matching and enrichment; once applied to heterogeneous data sources, it builds multiple perspectives over the genome, leading to the identification of meaningful relationships that could not be perceived by using incompatible data formats. In this paper, we first describe a technological pipeline from data production to data integration; we then propose a taxonomy of genomic data players (based on the distinction between contributors, repository hosts, consortia, integrators and consumers) and apply the taxonomy to describe about 30 important players in genomic data management. We specifically focus on the integrator players and analyse the issues in solving the genomic data integration challenges, as well as evaluate the computational environments that they provide to follow up data integration by means of visualization and analysis tools.
Collapse
|
435
|
Lv L, Zhao Y, Wei Q, Zhao Y, Yi Q. Downexpression of HSD17B6 correlates with clinical prognosis and tumor immune infiltrates in hepatocellular carcinoma. Cancer Cell Int 2020; 20:210. [PMID: 32514254 PMCID: PMC7268300 DOI: 10.1186/s12935-020-01298-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 05/27/2020] [Indexed: 12/24/2022] Open
Abstract
Background Hydroxysteroid 17-Beta Dehydrogenase 6 (HSD17B6), a key protein involved in synthetizing dihydrotestosterone, is abundant in the liver. Previous studies have suggested a role for dihydrotestosterone in modulating progress of various malignancies, and HSD17B6 dysfunction was associated with lung cancer and prostate cancer. However, little is known about the detailed role of HSD17B6 in hepatocellular carcinoma (HCC). Methods Clinical implication and survival data related to HSD17B6 expression in patients with HCC were obtained through TCGA, ICGC, ONCOMINE, GEO and HPA databases. Survival analysis plots were drawn with Kaplan–Meier Plotter. The ChIP-seq data were obtained from Cistrome DB. Protein–Protein Interaction and gene functional enrichment analyses were performed in STRING database. The correlations between HSD17B6 and tumor immune infiltrates was investigated via TIMER and xCell. The proliferation, migration and invasion of liver cancer cells transfected with HSD17B6 were evaluated by the CCK8 assay, wound healing test and transwell assay respectively. Expression of HSD17B6, TGFB1 and PD-L1 were assessed by quantitative RT-PCR. Results HSD17B6 expression was lower in HCC compared to normal liver and correlated with tumor stage and grade. Lower expression of HSD17B6 was associated with worse OS, PFS, RFS and DSS in HCC patients. HNF4A bound to enhancer and promoter regions of HSD17B6 gene, activating its transcription, and DNA methylation of HSD17B6 promoter negatively controlled the expression. HSD17B6 and its interaction partners were involved in androgen metabolism and biosynthesis in liver. HSD17B6 inhibited tumor cell proliferation, migration and invasion in liver cancer cells and low expression of HSD17B6 correlated with high immune cells infiltration, relative reduction of immune responses and multiple immune checkpoint genes expression in HCC, probably by regulating the expression of TGFB1. Conclusions This study indicate that HSD17B6 could be a new biomarker for the prognosis of HCC and an important negative regulator of immune responses in HCC.
Collapse
Affiliation(s)
- Lei Lv
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230031 Anhui People's Republic of China
| | - Yujia Zhao
- Teaching and Research Section of Nuclear Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032 Anhui People's Republic of China
| | - Qinqin Wei
- Teaching and Research Section of Nuclear Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032 Anhui People's Republic of China
| | - Ye Zhao
- Teaching and Research Section of Nuclear Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032 Anhui People's Republic of China
| | - Qiyi Yi
- Teaching and Research Section of Nuclear Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032 Anhui People's Republic of China
| |
Collapse
|
436
|
Wang J, Huang D, Zhou Y, Yao H, Liu H, Zhai S, Wu C, Zheng Z, Zhao K, Wang Z, Yi X, Zhang S, Liu X, Liu Z, Chen K, Yu Y, Sham PC, Li MJ. CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies. Nucleic Acids Res 2020; 48:D807-D816. [PMID: 31691819 PMCID: PMC7145620 DOI: 10.1093/nar/gkz1026] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 10/19/2019] [Accepted: 10/21/2019] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.
Collapse
Affiliation(s)
- Jianhua Wang
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Dandan Huang
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Yao Zhou
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Hongcheng Yao
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Huanhuan Liu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Sinan Zhai
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Chengwei Wu
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Zhanye Zheng
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Ke Zhao
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Zhao Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xianfu Yi
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Xiaorong Liu
- Clinical laboratory, Institute of Pediatrics, Shenzhen Children's Hospital, Shenzhen, China
| | - Zipeng Liu
- Centre of Genomics Sciences, State Key Laboratory of Brain and Cognitive Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Ying Yu
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Pak Chung Sham
- Centre of Genomics Sciences, State Key Laboratory of Brain and Cognitive Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Mulin Jun Li
- 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.,Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| |
Collapse
|
437
|
Lin CL, Tan X, Chen M, Kusi M, Hung CN, Chou CW, Hsu YT, Wang CM, Kirma N, Chen CL, Lin CH, Lathrop KI, Elledge R, Kaklamani VG, Mitsuya K, Huang THM. ERα-related chromothripsis enhances concordant gene transcription on chromosome 17q11.1-q24.1 in luminal breast cancer. BMC Med Genomics 2020; 13:69. [PMID: 32408897 PMCID: PMC7222439 DOI: 10.1186/s12920-020-0729-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 04/30/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Chromothripsis is an event of genomic instability leading to complex chromosomal alterations in cancer. Frequent long-range chromatin interactions between transcription factors (TFs) and targets may promote extensive translocations and copy-number alterations in proximal contact regions through inappropriate DNA stitching. Although studies have proposed models to explain the initiation of chromothripsis, few discussed how TFs influence this process for tumor progression. METHODS This study focused on genomic alterations in amplification associated regions within chromosome 17. Inter-/intra-chromosomal rearrangements were analyzed using whole genome sequencing data of breast tumors in the Cancer Genome Atlas (TCGA) cohort. Common ERα binding sites were defined based on MCF-7, T47D, and MDA-MB-134 breast cancer cell lines using univariate K-means clustering methods. Nanopore sequencing technology was applied to validate frequent rearrangements detected between ATC loci on 17q23 and an ERα hub on 20q13. The efficacy of pharmacological inhibition of a potentially druggable target gene on 17q23 was evaluated using breast cancer cell lines and patient-derived circulating breast tumor cells. RESULTS There are five adjoining regions from 17q11.1 to 17q24.1 being hotspots of chromothripsis. Inter-/intra-chromosomal rearrangements of these regions occurred more frequently in ERα-positive tumors than in ERα-negative tumors. In addition, the locations of the rearrangements were often mapped within or close to dense ERα binding sites localized on these five 17q regions or other chromosomes. This chromothriptic event was linked to concordant upregulation of 96 loci that predominantly regulate cell-cycle machineries in advanced luminal tumors. Genome-editing analysis confirmed that an ERα hub localized on 20q13 coordinately regulates a subset of these loci localized on 17q23 through long-range chromosome interactions. One of these loci, Tousled Like Kinase 2 (TLK2) known to participate in DNA damage checkpoint control, is an actionable target using phenothiazine antipsychotics (PTZs). The antiproliferative effect of PTZs was prominent in high TLK2-expressing cells, compared to low expressing cells. CONCLUSION This study demonstrates a new approach for identifying tumorigenic drivers from genomic regions highly susceptible to ERα-related chromothripsis. We found a group of luminal breast tumors displaying 17q-related chromothripsis for which antipsychotics can be repurposed as treatment adjuncts.
Collapse
Affiliation(s)
- Chun-Lin Lin
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Xi Tan
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Meizhen Chen
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Meena Kusi
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Chia-Nung Hung
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Chih-Wei Chou
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Ya-Ting Hsu
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Chiou-Miin Wang
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Nameer Kirma
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Chun-Liang Chen
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Ching-Hung Lin
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Kate I Lathrop
- Department of Medicine, Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Richard Elledge
- Department of Medicine, Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Virginia G Kaklamani
- Department of Medicine, Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Kohzoh Mitsuya
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA.
| | - Tim H-M Huang
- Department of Molecular Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA.
| |
Collapse
|
438
|
Levitsky V, Zemlyanskaya E, Oshchepkov D, Podkolodnaya O, Ignatieva E, Grosse I, Mironova V, Merkulova T. A single ChIP-seq dataset is sufficient for comprehensive analysis of motifs co-occurrence with MCOT package. Nucleic Acids Res 2020; 47:e139. [PMID: 31750523 PMCID: PMC6868382 DOI: 10.1093/nar/gkz800] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 08/12/2019] [Accepted: 09/09/2019] [Indexed: 01/20/2023] Open
Abstract
Recognition of composite elements consisting of two transcription factor binding sites gets behind the studies of tissue-, stage- and condition-specific transcription. Genome-wide data on transcription factor binding generated with ChIP-seq method facilitate an identification of composite elements, but the existing bioinformatics tools either require ChIP-seq datasets for both partner transcription factors, or omit composite elements with motifs overlapping. Here we present an universal Motifs Co-Occurrence Tool (MCOT) that retrieves maximum information about overrepresented composite elements from a single ChIP-seq dataset. This includes homo- and heterotypic composite elements of four mutual orientations of motifs, separated with a spacer or overlapping, even if recognition of motifs within composite element requires various stringencies. Analysis of 52 ChIP-seq datasets for 18 human transcription factors confirmed that for over 60% of analyzed datasets and transcription factors predicted co-occurrence of motifs implied experimentally proven protein-protein interaction of respecting transcription factors. Analysis of 164 ChIP-seq datasets for 57 mammalian transcription factors showed that abundance of predicted composite elements with an overlap of motifs compared to those with a spacer more than doubled; and they had 1.5-fold increase of asymmetrical pairs of motifs with one more conservative 'leading' motif and another one 'guided'.
Collapse
Affiliation(s)
- Victor Levitsky
- Department of Systems Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia.,Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Elena Zemlyanskaya
- Department of Systems Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia.,Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Dmitry Oshchepkov
- Department of Systems Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
| | - Olga Podkolodnaya
- Department of Systems Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
| | - Elena Ignatieva
- Department of Systems Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia.,Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Ivo Grosse
- Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia.,Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.,German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Leipzig, Germany
| | - Victoria Mironova
- Department of Systems Biology, Institute of Cytology and Genetics, Novosibirsk 630090, Russia.,Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia
| | - Tatyana Merkulova
- Department of Natural Science, Novosibirsk State University, Novosibirsk 630090, Russia.,Department of Molecular Genetics, Institute of Cytology and Genetics, Novosibirsk 630090, Russia
| |
Collapse
|
439
|
Cistrome Data Browser and Toolkit: analyzing human and mouse genomic data using compendia of ChIP-seq and chromatin accessibility data. QUANTITATIVE BIOLOGY 2020. [DOI: 10.1007/s40484-020-0204-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
440
|
Shang J, Zhu Z, Chen Y, Song J, Huang Y, Song K, Zhong J, Xu X, Wei J, Wang C, Cui L, Liu CY, Zhang J. Small-molecule activating SIRT6 elicits therapeutic effects and synergistically promotes anti-tumor activity of vitamin D 3 in colorectal cancer. Theranostics 2020; 10:5845-5864. [PMID: 32483423 PMCID: PMC7255010 DOI: 10.7150/thno.44043] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 04/07/2020] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) is the leading cause of cancer death; however, targets with broad anti-CRC effects are limited. Sirtuin6 (SIRT6) is a conserved nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase that is widely pathologically downregulated in CRC, but its pharmacological effect in CRC remains undefined due to the lack of small-molecule SIRT6 activators. We searched for a compound activating SIRT6 and investigated its anti-CRC effect in various models. Methods: We identified an allosteric SIRT6 activator, MDL-811. Its ability to enhance SIRT6 deacetylation at protein and cellular levels was evaluated by Fluor de Lys (FDL) and western blots. We assessed the proliferation of 26 CRC cell lines and patient-derived organoids (PDOs) treated with MDL-811. In vivo efficacy of MDL-811 was evaluated in HCT116 cell line- and patient-derived xenografts as well as a spontaneous CRC model. RNA sequencing and real-time quantitative PCR assays were performed to analyze gene expression changes in MDL-811-treated HCT116 cells. Along with controls in SIRT6-overexpressing HCT116 cells, the SIRT6-mediated histone H3 deacetylation at the Cytochrome P450 family 24 subfamily A member 1 (CYP24A1) gene locus was assessed by chromatin immunoprecipitation (ChIP) in MDL-811-treated HCT116 cells. A combination therapy against CRC based on the downstream gene of SIRT6 activation was evaluated in cells and mouse models. Results: MDL-811 significantly activated SIRT6 histone H3 deacetylation (H3K9Ac, H3K18Ac, and H3K56Ac) in vitro and had broad antiproliferative effects on diverse CRC cell lines and PDOs. More importantly, the in vivo anti-tumor efficacy of MDL-811 was demonstrated across cell line- and patient-derived xenografts and in the APCmin/+ spontaneous CRC model. Mechanically, we identified a new downstream target gene of SIRT6 in CRC, CYP24A1. Based on these findings, a combination drug strategy with MDL-811 to synergistically enhance the anti-CRC effect of vitamin D3 was validated in vitro and in vivo. Conclusions: Our data provide proof of concept that targeting SIRT6 using a small-molecule activator is an attractive therapeutic strategy for CRC and that MDL-811 could be a promising lead compound for further preclinical and clinical studies of treatments for CRC.
Collapse
|
441
|
Wu Y, Zhao J, Zhu H, Fan Z, Yuan X, Chen S, Mao R, Fan Y. SPACE: a web server for linking chromatin accessibility with clinical phenotypes and the immune microenvironment in pan-cancer analysis. Cell Mol Immunol 2020; 17:1294-1296. [PMID: 32238917 DOI: 10.1038/s41423-020-0416-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Accepted: 03/12/2020] [Indexed: 11/09/2022] Open
Affiliation(s)
- Yingcheng Wu
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China.,Laboratory of Medical Science, School of Medicine, Nantong University, Jiangsu, 226001, China
| | - Jingwei Zhao
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China.,Department of Pathophysiology, School of Medicine, Nantong University, Jiangsu, 226001, China
| | - Haoliang Zhu
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China.,Department of Pathophysiology, School of Medicine, Nantong University, Jiangsu, 226001, China
| | - Zhiwei Fan
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China.,Laboratory of Medical Science, School of Medicine, Nantong University, Jiangsu, 226001, China
| | - Xinpei Yuan
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China.,Department of Pathophysiology, School of Medicine, Nantong University, Jiangsu, 226001, China
| | - Shiyin Chen
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China.,Department of Pathophysiology, School of Medicine, Nantong University, Jiangsu, 226001, China
| | - Renfang Mao
- Department of Pathophysiology, School of Medicine, Nantong University, Jiangsu, 226001, China.
| | - Yihui Fan
- Department of Pathogenic Biology, School of Medicine, Nantong University, Jiangsu, 226001, China. .,Laboratory of Medical Science, School of Medicine, Nantong University, Jiangsu, 226001, China.
| |
Collapse
|
442
|
Hu S, Huo D, Yu Z, Chen Y, Liu J, Liu L, Wu X, Zhang Y. ncHMR detector: a computational framework to systematically reveal non-classical functions of histone modification regulators. Genome Biol 2020; 21:48. [PMID: 32093739 PMCID: PMC7038559 DOI: 10.1186/s13059-020-01953-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 02/06/2020] [Indexed: 01/02/2023] Open
Abstract
Recently, several non-classical functions of histone modification regulators (HMRs), independent of their known histone modification substrates and products, have been reported to be essential for specific cellular processes. However, there is no framework designed for identifying such functions systematically. Here, we develop ncHMR detector, the first computational framework to predict non-classical functions and cofactors of a given HMR, based on ChIP-seq data mining. We apply ncHMR detector in ChIP-seq data-rich cell types and predict non-classical functions of HMRs. Finally, we experimentally reveal that the predicted non-classical function of CBX7 is biologically significant for the maintenance of pluripotency.
Collapse
Affiliation(s)
- Shengen Hu
- Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092 China
| | - Dawei Huo
- Department of Cell Biology, Tianjin Medical University, 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Qixiangtai Road 22, Tianjin, China
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhaowei Yu
- Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092 China
| | - Yujie Chen
- Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092 China
| | - Jing Liu
- Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092 China
- Present address: Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing, China
| | - Lin Liu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Xudong Wu
- Department of Cell Biology, Tianjin Medical University, 2011 Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Qixiangtai Road 22, Tianjin, China
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China
- State Key Laboratory of Experimental Hematology, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, 300020 China
| | - Yong Zhang
- Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092 China
| |
Collapse
|
443
|
Singh K, Baird M, Fischer R, Chaitankar V, Seifuddin F, Chen YC, Tunc I, Waterman CM, Pirooznia M. Misregulation of ELK1, AP1, and E12 Transcription Factor Networks Is Associated with Melanoma Progression. Cancers (Basel) 2020; 12:E458. [PMID: 32079144 PMCID: PMC7072154 DOI: 10.3390/cancers12020458] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 02/10/2020] [Accepted: 02/12/2020] [Indexed: 01/17/2023] Open
Abstract
Melanoma is among the most malignant cutaneous cancers and when metastasized results in dramatically high mortality. Despite advances in high-throughput gene expression profiling in cancer transcriptomic studies, our understanding of mechanisms driving melanoma progression is still limited. We present here an in-depth bioinformatic analysis of the melanoma RNAseq, chromatin immunoprecipitation (ChIP)seq, and single-cell (sc)RNA seq data to understand cancer progression. Specifically, we have performed a consensus network analysis of RNA-seq data from clinically re-grouped melanoma samples to identify gene co-expression networks that are conserved in early (stage 1) and late (stage 4/invasive) stage melanoma. Overlaying the fold-change information on co-expression networks revealed several coordinately up or down-regulated subnetworks that may play a critical role in melanoma progression. Furthermore, by incorporating histone lysine-27 acetylation information and highly expressed genes identified from the single-cell RNA data from melanoma patient samples, we present a comprehensive list of pathways, putative protein-protein interactions (PPIs) and transcription factor (TF) networks that are driving cancer progression. From this analysis, we have identified Elk1, AP1 and E12 TF networks that coordinately change expression in late melanoma when compared to early melanoma, implicating these TFs in melanoma progression. Additionally, the sumoylation-associated interactome is upregulated in invasive melanoma. Together, this bioinformatic analysis potentially implicates a combination of TF networks and PPIs in melanoma progression, which if confirmed in the experimental systems, could be used as targets for drug intervention in melanoma.
Collapse
Affiliation(s)
- Komudi Singh
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.S.); (V.C.); (F.S.); (Y.-C.C.); (I.T.)
| | - Michelle Baird
- Cell and Developmental Biology Center, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (M.B.); (R.F.); (C.M.W.)
| | - Robert Fischer
- Cell and Developmental Biology Center, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (M.B.); (R.F.); (C.M.W.)
| | - Vijender Chaitankar
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.S.); (V.C.); (F.S.); (Y.-C.C.); (I.T.)
| | - Fayaz Seifuddin
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.S.); (V.C.); (F.S.); (Y.-C.C.); (I.T.)
| | - Yun-Ching Chen
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.S.); (V.C.); (F.S.); (Y.-C.C.); (I.T.)
| | - Ilker Tunc
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.S.); (V.C.); (F.S.); (Y.-C.C.); (I.T.)
| | - Clare M. Waterman
- Cell and Developmental Biology Center, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (M.B.); (R.F.); (C.M.W.)
| | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA; (K.S.); (V.C.); (F.S.); (Y.-C.C.); (I.T.)
| |
Collapse
|
444
|
Zhou Y, Sun Y, Huang D, Li MJ. epiCOLOC: Integrating Large-Scale and Context-Dependent Epigenomics Features for Comprehensive Colocalization Analysis. Front Genet 2020; 11:53. [PMID: 32117461 PMCID: PMC7029718 DOI: 10.3389/fgene.2020.00053] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 01/17/2020] [Indexed: 12/18/2022] Open
Abstract
High-throughput genome-wide epigenomic assays, such as ChIP-seq, DNase-seq and ATAC-seq, have profiled a huge number of functional elements across numerous human tissues/cell types, which provide an unprecedented opportunity to interpret human genome and disease in context-dependent manner. Colocalization analysis determines whether genomic features are functionally related to a given search and will facilitate identifying the underlying biological functions characterizing intricate relationships with queries for genomic regions. Existing colocalization methods leveraged diverse assumptions and background models to assess the significance of enrichment, however, they only provided limited and predefined sets of epigenomic features. Here, we comprehensively collected and integrated over 44,385 bulk or single-cell epigenomic assays across 53 human tissues/cell types, such as transcription factor binding, histone modification, open chromatin and transcriptional event. By classifying these profiles into hierarchy of tissue/cell type, we developed a web portal, epiCOLOC (http://mulinlab.org/epicoloc or http://mulinlab.tmu.edu.cn/epicoloc), for users to perform context-dependent colocalization analysis in a convenient way.
Collapse
Affiliation(s)
- Yao Zhou
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Yongzheng Sun
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Dandan Huang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China
| | - Mulin Jun Li
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China.,Collaborative Innovation Center of Tianjin for Medical Epigenetics, Tianjin Key Laboratory of Medical Epigenetics, Tianjin Medical University, Tianjin, China
| |
Collapse
|
445
|
Fu K, Hui B, Wang Q, Lu C, Shi W, Zhang Z, Rong D, Zhang B, Tian Z, Tang W, Cao H, Wang X, Chen Z. Single-cell RNA sequencing of immune cells in gastric cancer patients. Aging (Albany NY) 2020; 12:2747-2763. [PMID: 32039830 PMCID: PMC7041746 DOI: 10.18632/aging.102774] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 01/12/2020] [Indexed: 12/16/2022]
Abstract
Cancer immunotherapy has achieved positive clinical responses in the treatment of various cancers, including gastric cancer (GC). In this study, we characterized the heterogeneity of T cells isolated from GC patients at the single-cell level using single-cell RNA sequencing. We identified different immune cell subtypes and their heterogeneous transcription factors and depicted their developmental trajectories. In particular, we focused on exhausted CD8+ cells and Tregs and discovered that, as compared to control, the IRF8 transcription factor was downregulated in CD8+ tumour-infiltrating lymphocytes (TILs) from GC tissues, and that GC patients with lower IRF8 levels in blood CD8+ T cells tended to be a at a more advanced disease stage. These findings provide a theoretical basis for targeted immune therapy in GC.
Collapse
Affiliation(s)
- Kai Fu
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Bingqing Hui
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qian Wang
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Chen Lu
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Weihong Shi
- Jiangsu Research Center for Primary Health Development and General Education, Jiangsu Vocational College of Medicine, Yancheng, China
| | - Zhigang Zhang
- Department of General Surgery, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Dawei Rong
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Betty Zhang
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Canada
| | - Zhaofeng Tian
- Department of Laboratory Diagnostics, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Weiwei Tang
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Hongyong Cao
- Department of General Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Xuehao Wang
- Hepatobiliary/Liver Transplantation Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Living Donor Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
| | - Ziyi Chen
- Hepatobiliary/Liver Transplantation Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Living Donor Transplantation, Chinese Academy of Medical Sciences, Nanjing, China
| |
Collapse
|
446
|
Mishra GP, Ghosh A, Jha A, Raghav SK. BedSect: An Integrated Web Server Application to Perform Intersection, Visualization, and Functional Annotation of Genomic Regions From Multiple Datasets. Front Genet 2020; 11:3. [PMID: 32117432 PMCID: PMC7013082 DOI: 10.3389/fgene.2020.00003] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 01/06/2020] [Indexed: 11/17/2022] Open
Abstract
A large number of genomic regions, such as transcription factor binding sites (TFBSs) captured from next generation sequencing (NGS) data analyses or those available from the public resource database ENCODE, are generally overlapped to answer a variety of biological questions. Though several command-line tools are available to perform such an analysis, there is a notable lack of an integrated webserver application with which to identify genomic region intersections, generate publication-ready plots depicting subsets of the overlapped regions, and perform functional annotation. Thus, there is an ardent need for a comprehensive and user-friendly webserver application that allows the users to either upload multiple datasets or select from the integrated Gene Transcription Regulation Database (GTRD). We thus introduce BedSect (http://imgsb.org/bedsect/.), which not only fulfils the above criteria but also performs intersection analysis along with visualization of the intersection regions as an UpSet and correlation plot using the integrated Shiny application. Moreover, analyses, including functional annotation, gene ontology, and biological pathways enrichment for the identified unique and intersected genomic regions, can also be performed using the integrated GREAT tool. To view the genomic regions in the genome browser, the inbuilt hyperlink for UCSC can redirect the user to visualize the results as custom tracks.
Collapse
Affiliation(s)
- Gyan Prakash Mishra
- Immunogenomics and Systems Biology Laboratory, Institute of Life Sciences, Bhubaneswar, India
- School of Biotechnology, KIIT University, Bhubaneswar, India
| | - Arup Ghosh
- Immunogenomics and Systems Biology Laboratory, Institute of Life Sciences, Bhubaneswar, India
- School of Biotechnology, KIIT University, Bhubaneswar, India
| | - Atimukta Jha
- Immunogenomics and Systems Biology Laboratory, Institute of Life Sciences, Bhubaneswar, India
- Manipal Academy of Higher Education, Manipal, India
| | - Sunil Kumar Raghav
- Immunogenomics and Systems Biology Laboratory, Institute of Life Sciences, Bhubaneswar, India
- School of Biotechnology, KIIT University, Bhubaneswar, India
- Manipal Academy of Higher Education, Manipal, India
| |
Collapse
|
447
|
Li Z, Wang B, Gu S, Jiang P, Sahu A, Chen CH, Han T, Shi S, Wang X, Traugh N, Liu H, Liu Y, Wu Q, Brown M, Xiao T, Boland GM, Shirley Liu X. CRISPR Screens Identify Essential Cell Growth Mediators in BRAF Inhibitor-resistant Melanoma. GENOMICS, PROTEOMICS & BIOINFORMATICS 2020; 18:26-40. [PMID: 32413516 PMCID: PMC7393575 DOI: 10.1016/j.gpb.2020.02.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 01/20/2020] [Accepted: 02/26/2020] [Indexed: 12/21/2022]
Abstract
BRAF is a serine/threonine kinase that harbors activating mutations in ∼7% of human malignancies and ∼60% of melanomas. Despite initial clinical responses to BRAF inhibitors, patients frequently develop drug resistance. To identify candidate therapeutic targets for BRAF inhibitor resistant melanoma, we conduct CRISPR screens in melanoma cells harboring an activating BRAF mutation that had also acquired resistance to BRAF inhibitors. To investigate the mechanisms and pathways enabling resistance to BRAF inhibitors in melanomas, we integrate expression, ATAC-seq, and CRISPR screen data. We identify the JUN family transcription factors and the ETS family transcription factor ETV5 as key regulators of CDK6, which together enable resistance to BRAF inhibitors in melanoma cells. Our findings reveal genes contributing to resistance to a selective BRAF inhibitor PLX4720, providing new insights into gene regulation in BRAF inhibitor resistant melanoma cells.
Collapse
Affiliation(s)
- Ziyi Li
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Binbin Wang
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; Department of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Shengqing Gu
- Department of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Peng Jiang
- Department of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Avinash Sahu
- Department of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Chen-Hao Chen
- Department of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Tong Han
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Sailing Shi
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Xiaoqing Wang
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Nicole Traugh
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Hailing Liu
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Yin Liu
- Department of Clinical Laboratory, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China
| | - Qiu Wu
- Clinical Translational Research Center, Shanghai Pulmonary Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Myles Brown
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Tengfei Xiao
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA.
| | - Genevieve M Boland
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
| | - X Shirley Liu
- Department of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
| |
Collapse
|
448
|
Cheng Q, Ouyang X, Zhang R, Zhu L, Song X. Senescence-associated genes and non-coding RNAs function in pancreatic cancer progression. RNA Biol 2020; 17:1693-1706. [PMID: 31997706 DOI: 10.1080/15476286.2020.1719752] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023] Open
Abstract
Pancreatic cancer is a major cause of mortality with a poor diagnosis and prognosis that most often occurs in elderly patients. Few studies, however, focus on the interplay of age and pancreatic cancer at the transcriptional level. Here we evaluated the possible roles of age-dependent, differentially expressed genes (DEGs) in pancreatic cancer. These DEGs were used to construct a correlation network and clustered in six gene modules, among which two modules were highly correlated with patients' survival time. Integrating different datasets, including ATAC-Seq and ChIP-Seq, we performed multi-parallel analyses and identified eight age-dependent protein coding genes and two non-coding RNAs as potential candidates. These candidates, together with KLF5, a potent functional transcription factor in pancreatic cancer, are likely to be key elements linking cellular senescence and pancreatic cancer, providing insights on the balance between them, as well as on diagnosis and subsequent prognosis of pancreatic cancer.
Collapse
Affiliation(s)
- Qingyu Cheng
- Hefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China , Hefei, Anhui, China
| | - Xuan Ouyang
- Hefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China , Hefei, Anhui, China
| | - Ran Zhang
- Hefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China , Hefei, Anhui, China
| | - Lianbang Zhu
- The First Affiliated Hospital, Division of Life Sciences and Medicine, University of Science and Technology of China , Hefei, Anhui, China
| | - Xiaoyuan Song
- Hefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China , Hefei, Anhui, China
| |
Collapse
|
449
|
Lin QXX, Thieffry D, Jha S, Benoukraf T. TFregulomeR reveals transcription factors' context-specific features and functions. Nucleic Acids Res 2020; 48:e10. [PMID: 31754708 PMCID: PMC6954419 DOI: 10.1093/nar/gkz1088] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 10/25/2019] [Accepted: 11/01/2019] [Indexed: 12/25/2022] Open
Abstract
Transcription factors (TFs) are sequence-specific DNA binding proteins, fine-tuning spatiotemporal gene expression. Since genomic occupancy of a TF is highly dynamic, it is crucial to study TF binding sites (TFBSs) in a cell-specific context. To date, thousands of ChIP-seq datasets have portrayed the genomic binding landscapes of numerous TFs in different cell types. Although these datasets can be browsed via several platforms, tools that can operate on that data flow are still lacking. Here, we introduce TFregulomeR (https://github.com/benoukraflab/TFregulomeR), an R-library linked to an up-to-date compendium of cistrome and methylome datasets, implemented with functionalities that facilitate integrative analyses. In particular, TFregulomeR enables the characterization of TF binding partners and cell-specific TFBSs, along with the study of TF’s functions in the context of different partnerships and DNA methylation levels. We demonstrated that TFs’ target gene ontologies can differ notably depending on their partners and, by re-analyzing well characterized TFs, we brought to light that numerous leucine zipper TFBSs derived from ChIP-seq experiments documented in current databases were inadequately characterized, due to the fact that their position weight matrices were assembled using a mixture of homodimer and heterodimer binding sites. Altogether, analyses of context-specific transcription regulation with TFregulomeR foster our understanding of regulatory network-dependent TF functions.
Collapse
Affiliation(s)
- Quy Xiao Xuan Lin
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Denis Thieffry
- Computational Systems Biology Team, Institut de Biologie de l'École Normale Supérieure (IBENS), CNRS, INSERM, École Normale Supérieure, PSL Research University, Paris 75005, France
| | - Sudhakar Jha
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.,Department of Biochemistry, National University of Singapore, Singapore 117596, Singapore
| | - Touati Benoukraf
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.,Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL A1B 3V6, Canada
| |
Collapse
|
450
|
Chen L, Zhang J, Chen Q, Ge W, Meng L, Huang X, Shen P, Yuan H, Shi G, Miao Y, Jiang K. Long noncoding RNA SOX2OT promotes the proliferation of pancreatic cancer by binding to FUS. Int J Cancer 2020; 147:175-188. [PMID: 31837005 DOI: 10.1002/ijc.32827] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 11/03/2019] [Accepted: 11/11/2019] [Indexed: 12/30/2022]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors has one of the worst prognoses, and the role of long noncoding RNAs (lncRNAs) in the biological and pathological processes of pancreatic cancer, including tumor cell proliferation, is a popular topic in tumor research. Our previous study revealed the correlation between high levels of the lncRNA-SOX2OT (SOX2OT) with poor survival outcomes. Cell Counting Kit-8, EdU, Flow cytometry and Colony formation assays as well as Xenograft growth of PDAC cells in mice were used for the detection of PDAC cells proliferation progression. Fluorescence in situ hybridization, RNA-binding protein pulldown and RNA immunoprecipitation assays were also used to identify the putative mechanisms of SOX2OT participating in the tumor progression. SOX2OT and its potential downstream targets were verified by Western blot and quantitative real-time polymerase chain reaction (qRT-PCR). SOX2OT was confirmed to promote the proliferation of PDAC cells. It was found to directly physically bind to FUS and we also demonstrated that FUS protein stability was affected by binding with SOX2OT and FUS could suppressed PDAC tumor by regulating cell cycle-associated factors CCND1 and p27. Our findings suggest that SOX2OT may act as a tumor promoter in PDAC through physically binding FUS and regulating its downstream cell cycle-associated factors CCND1 and p27. It may serve as an effective target for antitumor treatment for pancreatic cancer.
Collapse
Affiliation(s)
- Lei Chen
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Jingjing Zhang
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Qun Chen
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Wanli Ge
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Lingdong Meng
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Xumin Huang
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Peng Shen
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Hao Yuan
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Guodong Shi
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Yi Miao
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| | - Kuirong Jiang
- Pancreas Center, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China.,Pancreas Institute of Nanjing Medical University, Nanjing, Jiangsu, People's Republic of China
| |
Collapse
|