eRNA profiling uncovers the enhancer landscape of oesophageal adenocarcinoma and reveals new deregulated pathways

Abstract

Cancer is driven by both genetic and epigenetic changes that impact on gene expression profiles and the resulting tumourigenic phenotype. Enhancers are transcriptional regulatory elements that are key to our understanding of how this rewiring of gene expression is achieved in cancer cells. Here we have harnessed the power of RNA-seq data from hundreds of patients with oesophageal adenocarcinoma (OAC) or its precursor state Barrett's oesophagus (BO) coupled with open chromatin maps to identify potential enhancer RNAs (eRNAs) and their associated enhancer regions in this cancer. We identify ~1000 OAC-specific enhancers and use this data to uncover new cellular pathways that are operational in OAC. Among these are enhancers for JUP, MYBL2 and CCNE1, and we show that their activity is required for cancer cell viability. We also demonstrate the clinical utility of our dataset for identifying disease stage and patient prognosis. Our data therefore identify an important set of regulatory elements that enhance our molecular understanding of OAC and point to potential new therapeutic directions.

Data availability

All data have been deposited at ArrayExpress; OE19 KAS-seq and CUT&TAG data (E-MTAB-11357 and E-MTAB-11356, respectively) and OE19 HiC data (E-MTAB-12664).

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Ibrahim Ahmed

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7424-6658
  2. Shen-Hsi Yang

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Samuel Ogden

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0217-881X
  4. Wei Zhang

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Yaoyong Li

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. The OCCAMS Consortium

  7. Andrew D Sharrocks

    Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
    For correspondence
    andrew.d.sharrocks@manchester.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7395-9552

Funding

Medical Research Council (MR/V010263/1)

  • Samuel Ogden

Wellcome Trust (102171/B/13/Z)

  • Ibrahim Ahmed

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. William C Hahn, Dana-Farber Cancer Institute, United States

Version history

  1. Preprint posted: May 11, 2022 (view preprint)
  2. Received: June 6, 2022
  3. Accepted: February 20, 2023
  4. Accepted Manuscript published: February 20, 2023 (version 1)
  5. Version of Record published: March 9, 2023 (version 2)

Copyright

© 2023, Ahmed et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Ibrahim Ahmed
  2. Shen-Hsi Yang
  3. Samuel Ogden
  4. Wei Zhang
  5. Yaoyong Li
  6. The OCCAMS Consortium
  7. Andrew D Sharrocks
(2023)
eRNA profiling uncovers the enhancer landscape of oesophageal adenocarcinoma and reveals new deregulated pathways
eLife 12:e80840.
https://doi.org/10.7554/eLife.80840

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https://doi.org/10.7554/eLife.80840

Further reading

    1. Cancer Biology
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    Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome-edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.

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    Background:

    Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer.

    Methods:

    Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs).

    Results:

    Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18–1.27) in men, and 1.26 (1.22–1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10–2.51) for men and 1.94 (1.78–2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = –1.01 in men, p<0.001; Beta = –0.98 in women, p<0.001).

    Conclusions:

    Within and across genetic risk groups, older PhenoAge was consistently related to an increased risk of incident cancer with adjustment for chronological age and the aging process could be retarded by adherence to a healthy lifestyle.

    Funding:

    This work was supported by the National Natural Science Foundation of China (82230110, 82125033, 82388102 to GJ; 82273714 to MZ); and the Excellent Youth Foundation of Jiangsu Province (BK20220100 to MZ).