Abstract

The Fbw7 ubiquitin ligase targets many proteins for proteasomal degradation, which include oncogenic transcription factors (TFs) (e.g., c-Myc, c-Jun, Notch). Fbw7 is a tumor suppressor and tumors often contain mutations in FBXW7, the gene that encodes Fbw7. The complexity of its substrate network has obscured the mechanisms of Fbw7-associated tumorigenesis, yet this understanding is needed for developing therapies. We used an integrated approach employing RNA-Seq and high-resolution mapping (CUT&RUN) of histone modifications and TF occupancy (c-Jun and c-Myc) to examine the combinatorial effects of mis-regulated Fbw7 substrates in colorectal cancer cells with engineered tumor-associated FBXW7 null or missense mutations. Both Fbw7 mutations caused widespread transcriptional changes associated with active chromatin and altered TF occupancy: some were common to both Fbw7 mutant cell lines, whereas others were mutation specific. We identified loci where both Jun and Myc were co-regulated by Fbw7, suggesting that substrates may have synergistic effects. One co-regulated gene was CIITA, the master regulator of MHC Class II gene expression. Fbw7 loss increased MHC Class II expression and Fbw7 mutations were correlated with increased CIITA expression in TCGA colorectal tumors and cell lines, which may have immunotherapeutic implications for Fbw7-associated cancers. Analogous studies in neural stem cells in which FBXW7 had been acutely deleted closely mirrored the results in colorectal cancer cells. Gene set enrichment analyses revealed Fbw7-asssociated pathways that were conserved across both cell types that may reflect fundamental Fbw7 functions. These analyses provide a framework for understanding normal and neoplastic context specific Fbw7 functions.

Data availability

- RNA-Seq and CUT&RUN sequencing data have been deposited in GEO under accession code GSE184041. Secure access token: cdmhkumwvtovbqn- All data generated or analyzed during the study are included in the manuscript and supporting files. Supplement figures are included as a separate PDF. Source Data files have been provided for Figures 1, 2, 3, 5 and 6. List of source data with a brief description can be found at the end of the manuscript.- Computational tools used in the study are mentioned in the Materials and Methods section. Code used are available at https://github.com/hnthirima.

The following data sets were generated

Article and author information

Author details

  1. Heshani Nayanga Thirmanne

    Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  2. Feinan Wu

    Genomics and Bioinformatics Resource, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  3. Derek H Janssens

    Basic Science Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1079-9525
  4. Jherek Swanger

    Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  5. Ahmed Diab

    Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  6. Heather Feldman

    Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  7. Robert A Amezquita

    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  8. Raphael Gottardo

    Vaccine and Infectious Disease Division, University of Washington, Seattle, United States
    Competing interests
    No competing interests declared.
  9. Patrick J Paddison

    Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    No competing interests declared.
  10. Steven Henikoff

    Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    steveh@fhcrc.org
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7621-8685
  11. Bruce E Clurman

    Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    bclurman@fredhutch.org
    Competing interests
    Bruce E Clurman, is an equity holder and paid consultant for Coho Therapeutics, a start up biotechnology company focused on molecular glues. There is no funding or relationship to this paper. He also has a sponsored research agreement from Coho Therapeutics to fund work that is unrelated to this manuscript..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5835-9361

Funding

National Cancer Institute (T32 CA080416)

  • Heshani Nayanga Thirmanne

National Cancer Institute (R01 CA215647)

  • Bruce E Clurman

National Cancer Institute (P30 CA015704)

  • Bruce E Clurman

National Institutes of Health (R01 HG010492)

  • Steven Henikoff

National Institutes of Health (R01NS119650)

  • Patrick J Paddison

National Cancer Institute (R01 CA190957)

  • Patrick J Paddison

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

Copyright

© 2022, Thirmanne 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

  • 1,173
    views
  • 195
    downloads
  • 7
    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. Heshani Nayanga Thirmanne
  2. Feinan Wu
  3. Derek H Janssens
  4. Jherek Swanger
  5. Ahmed Diab
  6. Heather Feldman
  7. Robert A Amezquita
  8. Raphael Gottardo
  9. Patrick J Paddison
  10. Steven Henikoff
  11. Bruce E Clurman
(2022)
Global and context-specific transcriptional consequences of oncogenic Fbw7 mutations
eLife 11:e74338.
https://doi.org/10.7554/eLife.74338

Share this article

https://doi.org/10.7554/eLife.74338

Further reading

    1. Cancer Biology
    Yumin Fu, Xinyu Guo ... Lianxin Liu
    Review Article

    Hepatocellular carcinoma (HCC), the most common type of liver tumor, is a leading cause of cancer-related deaths, and the incidence of liver cancer is still increasing worldwide. Curative hepatectomy or liver transplantation is only indicated for a small population of patients with early-stage HCC. However, most patients with HCC are not candidates for radical resection due to disease progression, leading to the choice of the conventional tyrosine kinase inhibitor drug sorafenib as first-line treatment. In the past few years, immunotherapy, mainly immune checkpoint inhibitors (ICIs), has revolutionized the clinical strategy for HCC. Combination therapy with ICIs has proven more effective than sorafenib, and clinical trials have been conducted to apply these therapies to patients. Despite significant progress in immunotherapy, the molecular mechanisms behind it remain unclear, and immune resistance is often challenging to overcome. Several studies have pointed out that the complex intercellular communication network in the immune microenvironment of HCC regulates tumor escape and drug resistance to immune response. This underscores the urgent need to analyze the immune microenvironment of HCC. This review describes the immunosuppressive cell populations in the immune microenvironment of HCC, as well as the related clinical trials, aiming to provide insights for the next generation of precision immunotherapy.

    1. Cancer Biology
    2. Genetics and Genomics
    Li Min, Fanqin Bu ... Shutian Zhang
    Research Article

    It takes more than 20 years for normal colorectal mucosa to develop into metastatic carcinoma. The long time window provides a golden opportunity for early detection to terminate the malignant progression. Here, we aim to enable liquid biopsy of T1a stage colorectal cancer (CRC) and precancerous advanced adenoma (AA) by profiling circulating small extracellular vesicle (sEV)-derived RNAs. We exhibited a full RNA landscape for the circulating sEVs isolated from 60 participants. A total of 58,333 annotated RNAs were detected from plasma sEVs, among which 1,615 and 888 sEV-RNAs were found differentially expressed in plasma from T1a stage CRC and AA compared to normal controls (NC). Then we further categorized these sEV-RNAs into six modules by a weighted gene coexpression network analysis and constructed a 60-gene t-SNE model consisting of the top 10 RNAs of each module that could well distinguish T1a stage CRC/AA from NC samples. Some sEV-RNAs were also identified as indicators of specific endoscopic and morphological features of different colorectal lesions. The top-ranked biomarkers were further verified by RT-qPCR, proving that these candidate sEV-RNAs successfully identified T1a stage CRC/AA from NC in another cohort of 124 participants. Finally, we adopted different algorithms to improve the performance of RT-qPCR-based models and successfully constructed an optimized classifier with 79.3% specificity and 99.0% sensitivity. In conclusion, circulating sEVs of T1a stage CRC and AA patients have distinct RNA profiles, which successfully enable the detection of both T1a stage CRC and AA via liquid biopsy.