Toggle Main Menu Toggle Search

Open Access padlockePrints

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma

Lookup NU author(s): Dr Jérémie Nsengimana

Downloads


Licence

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

©2022 The Authors; Published by the American Association for Cancer Research. In melanoma, predicting which tumors will ultimately metastasize guides treatment decisions. Transcriptional signatures of primary tumors have been utilized to predict metastasis, but which among these are driver or passenger events remains unclear. We used data from the adjuvant AVAST-M trial to identify a predictive gene signature in localized tumors that ultimately metastasized. Using a zebrafish model of primary melanoma, we interrogated the top genes from the AVAST-M signature in vivo. This identified GRAMD1B, a cholesterol transfer protein, as a bona fide metastasis suppressor, with a majority of knockout animals rapidly developing metastasis. Mechanistically, excess free cholesterol or its metabolite 27-hydroxycholesterol promotes invasiveness via activation of an AP-1 program, which is associated with increased metastasis in humans. Our data demonstrate that the transcriptional seeds of metastasis are embedded within localized tumors, suggesting that early targeting of these programs can be used to prevent metastatic relapse. SIGNIFICANCE: We analyzed human melanoma transcriptomics data to identify a gene signature predictive of metastasis. To rapidly test clinical signatures, we built a genetic metastasis platform in adult zebrafish and identified GRAMD1B as a suppressor of melanoma metastasis. GRAMD1B-associated cholesterol overload activates an AP-1 program to promote melanoma invasion. This article is highlighted in the In This Issue feature, p. 1.


Publication metadata

Author(s): Suresh S, Rabbie R, Garg M, Lumaquin D, Huang T-H, Montal E, Ma Y, Cruz NM, Tang X, Nsengimana J, Newton-Bishop J, Hunter MV, Zhu Y, Chen K, de Stanchina E, Adams DJ, White RM

Publication type: Article

Publication status: Published

Journal: Cancer Discovery

Year: 2023

Volume: 13

Issue: 1

Pages: 194-215

Print publication date: 01/01/2023

Online publication date: 09/01/2023

Acceptance date: 14/10/2022

Date deposited: 23/01/2023

ISSN (print): 2159-8274

ISSN (electronic): 2159-8290

Publisher: American Association for Cancer Research

URL: https://doi.org/10.1158/2159-8290.CD-22-0427

DOI: 10.1158/2159-8290.CD-22-0427

PubMed id: 36259947


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
719502
C8216/A6129
C588/A10721
C588/A19167
CA83115
CR-UK
EMBL doctoral fellowship
F30CA254152
F99/K00
K00CA223016
P30 CA08748
T32 CA16000
Wellcome Trust
T32GM007739

Share