Cargando…

Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC

BACKGROUND: Chemoresistance is a primary clinical challenge for the management of small cell lung cancer. Additionally, transcriptional regulation by super enhancer (SE) has an important role in tumor evolution. The functions of SEs, a key class of noncoding DNA cis-regulatory elements, have been th...

Descripción completa

Detalles Bibliográficos
Autores principales: Bao, Jiarong, Li, Man, Liang, Shumei, Yang, Yunchu, Wu, Jingfang, Zou, Qingqing, Fang, Shun, Chen, Size, Guo, Linlang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532255/
https://www.ncbi.nlm.nih.gov/pubmed/31118037
http://dx.doi.org/10.1186/s12920-019-0520-9
_version_ 1783420984981716992
author Bao, Jiarong
Li, Man
Liang, Shumei
Yang, Yunchu
Wu, Jingfang
Zou, Qingqing
Fang, Shun
Chen, Size
Guo, Linlang
author_facet Bao, Jiarong
Li, Man
Liang, Shumei
Yang, Yunchu
Wu, Jingfang
Zou, Qingqing
Fang, Shun
Chen, Size
Guo, Linlang
author_sort Bao, Jiarong
collection PubMed
description BACKGROUND: Chemoresistance is a primary clinical challenge for the management of small cell lung cancer. Additionally, transcriptional regulation by super enhancer (SE) has an important role in tumor evolution. The functions of SEs, a key class of noncoding DNA cis-regulatory elements, have been the subject of many recent studies in the field of cancer research. METHODS: In this study, using chromatin immunoprecipitation-sequencing and RNA-sequencing (RNA-seq), we aimed to identify SEs associated with chemoresistance from H69AR cells. Through integrated bioinformatics analysis of the MEME chip, we predicted the master transcriptional factors (TFs) binding to SE sites and verified the relationships between TFs of SEs and drug resistance by RNA interference, cell counting kit 8 assays, quantitative real-time reverse transcription polymerase chain reaction. RESULTS: In total, 108 SEs were screened from H69AR cells. When combining this analysis with RNA-seq data, 45 SEs were suggested to be closely related to drug resistance. Then, 12 master TFs were predicted to localize to regions of those SEs. Subsequently, we selected forkhead box P1 (FOXP1), interferon regulatory factor 1 (IRF1), and specificity protein 1 (SP1) to authenticate the functional relationships of master TFs with chemoresistance via SEs. CONCLUSIONS: We screened out SEs involved with drug resistance and evaluated the functions of FOXP1, IRF1, and SP1 in chemoresistance. Our findings established a large group of SEs associated with drug resistance in small cell lung cancer, revealed the drug resistance mechanisms of SEs, and provided insights into the clinical applications of SEs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12920-019-0520-9) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6532255
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-65322552019-05-29 Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC Bao, Jiarong Li, Man Liang, Shumei Yang, Yunchu Wu, Jingfang Zou, Qingqing Fang, Shun Chen, Size Guo, Linlang BMC Med Genomics Research Article BACKGROUND: Chemoresistance is a primary clinical challenge for the management of small cell lung cancer. Additionally, transcriptional regulation by super enhancer (SE) has an important role in tumor evolution. The functions of SEs, a key class of noncoding DNA cis-regulatory elements, have been the subject of many recent studies in the field of cancer research. METHODS: In this study, using chromatin immunoprecipitation-sequencing and RNA-sequencing (RNA-seq), we aimed to identify SEs associated with chemoresistance from H69AR cells. Through integrated bioinformatics analysis of the MEME chip, we predicted the master transcriptional factors (TFs) binding to SE sites and verified the relationships between TFs of SEs and drug resistance by RNA interference, cell counting kit 8 assays, quantitative real-time reverse transcription polymerase chain reaction. RESULTS: In total, 108 SEs were screened from H69AR cells. When combining this analysis with RNA-seq data, 45 SEs were suggested to be closely related to drug resistance. Then, 12 master TFs were predicted to localize to regions of those SEs. Subsequently, we selected forkhead box P1 (FOXP1), interferon regulatory factor 1 (IRF1), and specificity protein 1 (SP1) to authenticate the functional relationships of master TFs with chemoresistance via SEs. CONCLUSIONS: We screened out SEs involved with drug resistance and evaluated the functions of FOXP1, IRF1, and SP1 in chemoresistance. Our findings established a large group of SEs associated with drug resistance in small cell lung cancer, revealed the drug resistance mechanisms of SEs, and provided insights into the clinical applications of SEs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12920-019-0520-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-22 /pmc/articles/PMC6532255/ /pubmed/31118037 http://dx.doi.org/10.1186/s12920-019-0520-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Bao, Jiarong
Li, Man
Liang, Shumei
Yang, Yunchu
Wu, Jingfang
Zou, Qingqing
Fang, Shun
Chen, Size
Guo, Linlang
Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC
title Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC
title_full Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC
title_fullStr Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC
title_full_unstemmed Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC
title_short Integrated high-throughput analysis identifies super enhancers associated with chemoresistance in SCLC
title_sort integrated high-throughput analysis identifies super enhancers associated with chemoresistance in sclc
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6532255/
https://www.ncbi.nlm.nih.gov/pubmed/31118037
http://dx.doi.org/10.1186/s12920-019-0520-9
work_keys_str_mv AT baojiarong integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT liman integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT liangshumei integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT yangyunchu integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT wujingfang integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT zouqingqing integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT fangshun integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT chensize integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc
AT guolinlang integratedhighthroughputanalysisidentifiessuperenhancersassociatedwithchemoresistanceinsclc