Dataset Information

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma.

ABSTRACT: 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.

SUBMITTER: Suresh S

PROVIDER: S-EPMC9827116 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma.

Suresh Shruthy S Rabbie Roy R Garg Manik M Lumaquin Dianne D Huang Ting-Hsiang TH Montal Emily E Ma Yilun Y Cruz Nelly M NM Tang Xinran X Nsengimana Jérémie J Newton-Bishop Julia J Hunter Miranda V MV Zhu Yuxin Y Chen Kevin K de Stanchina Elisa E Adams David J DJ White Richard M RM

Cancer discovery 20230101 1

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 ...[more]

PMID: 36259947

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Project description:Background: Collaboration between the human and animal health sectors, including the sharing of disease surveillance data, has the potential to improve public health outcomes through the rapid detection of zoonotic disease events prior to widespread transmission in humans. Kenya has been at the forefront of embracing a collaborative approach in Africa with the inception of the Zoonotic Disease Unit in 2011. Joint outbreak responses have been coordinated at the national level, yet little is currently documented on cross-sectoral collaboration at the sub-national level. Methods: Key informant interviews were conducted with 28 disease surveillance officers from the human and animal health sectors in three counties in western Kenya. An inductive process of thematic analysis was used to identify themes relating to barriers and drivers for cross-sectoral collaboration. Results: The study identified four interlinking themes related to drivers and barriers for cross-sectoral collaboration. To drive collaboration at the sub-national level there needs to be a clear identification of "common objectives," as currently exemplified by the response to suspected rabies and anthrax cases and routine meat hygiene activities. The action of collaboration, be it integrated responses to outbreaks or communication and data sharing, require "operational structures" to facilitate them, including the formalisation of reporting lines, supporting legislation and the physical infrastructure, from lab equipment to mobile phones, to facilitate the activities. These structures in turn require "appropriate resources" to support them, which will be allocated based on the "political will" of those who control the resources. Conclusions: Ongoing collaborations between human and animal disease surveillance officers at the sub-national level were identified, driven by common objectives such as routine meat hygiene and response to suspected rabies and anthrax cases. In these areas a suitable operational structure is present, including a supportive legislative framework and clearly designated roles for officers within both sectors. There was support from disease surveillance officers to increase their collaboration, communication and data sharing across sectors, yet this is currently hindered by the lack of these formal operational structures and poor allocation of resources to disease surveillance. It was acknowledged that improving this resource allocation will require political will at the sub-national, national and international levels.

Dataset Information

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma.

Significance

Publications

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma.

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