Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling

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Abstract

Breast cancer is a heterogeneous disease, affecting over 3.5 million women worldwide, yet the functional role of cis-regulatory elements including super-enhancers in different breast cancer subtypes remains poorly characterized. Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis. Here we apply integrated epigenomic and transcriptomic profiling to uncover super-enhancer heterogeneity between breast cancer subtypes, and provide clinically relevant biological insights towards TNBC. Using CRISPR/Cas9-mediated gene editing, we identify genes that are specifically regulated by TNBC-specific super-enhancers, including FOXC1 and MET, thereby unveiling a mechanism for specific overexpression of the key oncogenes in TNBC. We also identify ANLN as a TNBC-specific gene regulated by super-enhancer. Our studies reveal a TNBC-specific epigenomic landscape, contributing to the dysregulated oncogene expression in breast tumorigenesis.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with poor prognostic outcomes. Here the authors characterize super-enhancer heterogeneity and they identify genes that are specifically regulated by TNBC-specific super-enhancers, including FOXC1, MET and ANLN.

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Most cited references 67

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Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

Ahmedin Jemal, Lindsey A Torre, Rebecca Siegel … (2018)

This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.

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STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

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Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

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Author and article information

Contributors

Xin Wang:

ORCID: http://orcid.org/0000-0002-5122-2418

xin.wang@cityu.edu.hk

Y. Rebecca Chin:

ORCID: http://orcid.org/0000-0001-8976-3466

rebecca.chin@cityu.edu.hk

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 14 April 2021

Publication date PMC-release: 14 April 2021

Publication date Collection: 2021

Volume: 12

Electronic Location Identifier: 2242

Affiliations

[1 ]GRID grid.35030.35, ISNI 0000 0004 1792 6846, Department of Biomedical Sciences, , City University of Hong Kong, ; Kowloon, Hong Kong

[2 ]GRID grid.35030.35, ISNI 0000 0004 1792 6846, Key Laboratory of Biochip Technology, Biotech and Health Centre, Shenzhen Research Institute, , City University of Hong Kong, ; Shenzhen, China

[3 ]GRID grid.256607.0, ISNI 0000 0004 1798 2653, Department of Breast Surgery, The Affiliate Tumor Hospital, , Guangxi Medical University, ; Nanning, China

[4 ]GRID grid.415499.4, ISNI 0000 0004 1771 451X, Department of Clinical Oncology, , Queen Elizabeth Hospital, ; Kowloon, Hong Kong

[5 ]GRID grid.415499.4, ISNI 0000 0004 1771 451X, Department of Pathology, , Queen Elizabeth Hospital, ; Kowloon, Hong Kong

Author information

Jingyu Li http://orcid.org/0000-0002-2511-4157

Haiying Ma http://orcid.org/0000-0002-5969-900X

William C. S. Cho http://orcid.org/0000-0003-4174-4586

Liang Zhang http://orcid.org/0000-0003-3100-8593

Kui Ming Chan http://orcid.org/0000-0001-6430-3340

Xin Wang http://orcid.org/0000-0002-5122-2418

Y. Rebecca Chin http://orcid.org/0000-0001-8976-3466

Article

Publisher ID: 22445

DOI: 10.1038/s41467-021-22445-0

PMC ID: 8046763

PubMed ID: 33854062

SO-VID: 6876dbd3-4269-4860-ab16-c7dc1ba229f6

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 21 August 2020

Date accepted : 9 March 2021

Funding

Funded by: FundRef https://doi.org/10.13039/501100002920, Research Grants Council, University Grants Committee (RGC, UGC);

Award ID: 21101917

Award ID: 11103318

Award ID: 21100615

Award ID: 11102118

Award ID: 11101919

Award ID: C7007-17GF

Award ID: 11102317

Award ID: 11103718

Award ID: 11103619

Award ID: C4041-17GF

Award ID: R4017-18

Award ID: 11101517

Award ID: R1020-18

Award ID: 11103719

Award Recipient : Liang Zhang Kui Ming Chan Xin Wang Y. Rebecca Chin

Funded by: FundRef https://doi.org/10.13039/501100010877, Shenzhen Science and Technology Innovation Commission;

Award ID: JCYJ20180507181659781

Award ID: JCYJ20170413141047772

Award ID: JCYJ20170818104203065

Award ID: JCYJ20180307124019360

Award ID: JCYJ20170818095453642

Award Recipient : Liang Zhang Kui Ming Chan Y. Rebecca Chin

Funded by: FundRef https://doi.org/10.13039/100007567, City University of Hong Kong (CityU);

Award ID: 9680252

Award ID: 9678226

Award ID: 7200515

Award ID: 9610359

Award Recipient : Xin Wang Y. Rebecca Chin

Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);

Award ID: 81802384

Award ID: 81702728

Award ID: 81972781

Award Recipient : Xin Wang Y. Rebecca Chin

Funded by: Guangdong Basic and Applied Basic Research Foundation (2019B030302012);

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ScienceOpen disciplines: Uncategorized

Keywords: breast cancer,gene regulatory networks

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ScienceOpen disciplines: Uncategorized

Keywords: breast cancer, gene regulatory networks

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Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling

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Karger: Oncology

Most cited references 67

Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

STAR: ultrafast universal RNA-seq aligner.

Fast gapped-read alignment with Bowtie 2.

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Cited by 31

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