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.

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.

Metrics

  • 2,184
    views
  • 269
    downloads
  • 8
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  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

Share this article

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

Further reading

    1. Cancer Biology
    2. Stem Cells and Regenerative Medicine
    Alison G Barber, Cynthia M Quintero ... Tannishtha Reya
    Research Article

    Despite advances in therapeutic approaches, lung cancer remains the leading cause of cancer-related deaths. To understand the molecular programs underlying lung cancer initiation and maintenance, we focused on stem cell programs that are normally extinguished with differentiation but can be reactivated during oncogenesis. Here, we have used extensive genetic modeling and patient-derived xenografts (PDXs) to identify a dual role for Msi2: as a signal that acts initially to sensitize cells to transformation, and subsequently to drive tumor propagation. Using Msi reporter mice, we found that Msi2-expressing cells were marked by a pro-oncogenic landscape and a preferential ability to respond to Ras and p53 mutations. Consistent with this, genetic deletion of Msi2 in an autochthonous Ras/p53-driven lung cancer model resulted in a marked reduction of tumor burden, delayed progression, and a doubling of median survival. Additionally, this dependency was conserved in human disease as inhibition of Msi2 impaired tumor growth in PDXs. Mechanistically, Msi2 triggered a broad range of pathways critical for tumor growth, including several novel effectors of lung adenocarcinoma. Collectively, these findings reveal a critical role for Msi2 in aggressive lung adenocarcinoma, lend new insight into the biology of this disease, and identify potential new therapeutic targets.

    1. Cancer Biology
    Rui Vasco Simoes, Rafael Neto Henriques ... Noam Shemesh
    Research Article

    Glioblastomas are aggressive brain tumors with dismal prognosis. One of the main bottlenecks for developing more effective therapies for glioblastoma stems from their histologic and molecular heterogeneity, leading to distinct tumor microenvironments and disease phenotypes. Effectively characterizing these features would improve the clinical management of glioblastoma. Glucose flux rates through glycolysis and mitochondrial oxidation have been recently shown to quantitatively depict glioblastoma proliferation in mouse models (GL261 and CT2A tumors) using dynamic glucose-enhanced (DGE) deuterium spectroscopy. However, the spatial features of tumor microenvironment phenotypes remain hitherto unresolved. Here, we develop a DGE Deuterium Metabolic Imaging (DMI) approach for profiling tumor microenvironments through glucose conversion kinetics. Using a multimodal combination of tumor mouse models, novel strategies for spectroscopic imaging and noise attenuation, and histopathological correlations, we show that tumor lactate turnover mirrors phenotype differences between GL261 and CT2A mouse glioblastoma, whereas recycling of the peritumoral glutamate-glutamine pool is a potential marker of invasion capacity in pooled cohorts, linked to secondary brain lesions. These findings were validated by histopathological characterization of each tumor, including cell density and proliferation, peritumoral invasion and distant migration, and immune cell infiltration. Our study bodes well for precision neuro-oncology, highlighting the importance of mapping glucose flux rates to better understand the metabolic heterogeneity of glioblastoma and its links to disease phenotypes.