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Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma

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 id...

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Autores principales: Suresh, Shruthy, Rabbie, Roy, Garg, Manik, Lumaquin, Dianne, Huang, Ting-Hsiang, Montal, Emily, Ma, Yilun, Cruz, Nelly M, Tang, Xinran, Nsengimana, Jérémie, Newton-Bishop, Julia, Hunter, Miranda V., Zhu, Yuxin, Chen, Kevin, de Stanchina, Elisa, Adams, David J., White, Richard M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827116/
https://www.ncbi.nlm.nih.gov/pubmed/36259947
http://dx.doi.org/10.1158/2159-8290.CD-22-0427
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author Suresh, Shruthy
Rabbie, Roy
Garg, Manik
Lumaquin, Dianne
Huang, Ting-Hsiang
Montal, Emily
Ma, Yilun
Cruz, Nelly M
Tang, Xinran
Nsengimana, Jérémie
Newton-Bishop, Julia
Hunter, Miranda V.
Zhu, Yuxin
Chen, Kevin
de Stanchina, Elisa
Adams, David J.
White, Richard M.
author_facet Suresh, Shruthy
Rabbie, Roy
Garg, Manik
Lumaquin, Dianne
Huang, Ting-Hsiang
Montal, Emily
Ma, Yilun
Cruz, Nelly M
Tang, Xinran
Nsengimana, Jérémie
Newton-Bishop, Julia
Hunter, Miranda V.
Zhu, Yuxin
Chen, Kevin
de Stanchina, Elisa
Adams, David J.
White, Richard M.
author_sort Suresh, Shruthy
collection PubMed
description 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
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spelling pubmed-98271162023-01-10 Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma Suresh, Shruthy Rabbie, Roy Garg, Manik Lumaquin, Dianne Huang, Ting-Hsiang Montal, Emily Ma, Yilun Cruz, Nelly M Tang, Xinran Nsengimana, Jérémie Newton-Bishop, Julia Hunter, Miranda V. Zhu, Yuxin Chen, Kevin de Stanchina, Elisa Adams, David J. White, Richard M. Cancer Discov Research Articles 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 American Association for Cancer Research 2023-01-09 2022-10-19 /pmc/articles/PMC9827116/ /pubmed/36259947 http://dx.doi.org/10.1158/2159-8290.CD-22-0427 Text en ©2022 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.
spellingShingle Research Articles
Suresh, Shruthy
Rabbie, Roy
Garg, Manik
Lumaquin, Dianne
Huang, Ting-Hsiang
Montal, Emily
Ma, Yilun
Cruz, Nelly M
Tang, Xinran
Nsengimana, Jérémie
Newton-Bishop, Julia
Hunter, Miranda V.
Zhu, Yuxin
Chen, Kevin
de Stanchina, Elisa
Adams, David J.
White, Richard M.
Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma
title Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma
title_full Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma
title_fullStr Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma
title_full_unstemmed Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma
title_short Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma
title_sort identifying the transcriptional drivers of metastasis embedded within localized melanoma
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827116/
https://www.ncbi.nlm.nih.gov/pubmed/36259947
http://dx.doi.org/10.1158/2159-8290.CD-22-0427
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