Evidence map›Paper›PMID 36259947›Full record

ArticleCancer discovery2023

Identifying the Transcriptional Drivers of Metastasis Embedded within Localized Melanoma.

Shruthy Suresh, Roy Rabbie, Manik Garg, Dianne Lumaquin, Ting-Hsiang Huang, Emily Montal, Yilun Ma, Nelly M Cruz, Xinran Tang, Jérémie Nsengimana and 7 more

Open access · hybridAbstract read
In one paragraph

Article in Cancer discovery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. 27-Hydroxycholesterol in cancer development and drug resistance.Journal of enzyme inhibition and medicinal chemistry · 2025
    Review
  4. Article
  5. Article
  6. Small Fish, Big Answers: Zebrafish and the Molecular Drivers of Metastasis.International journal of molecular sciences · 2025
    Review
  7. Article
  8. Review
  9. Article
  10. Adult zebrafish as advanced models of human disease.Disease models & mechanisms · 2023
    Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 5 institutions in 2 countries.

Shruthy SureshDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-2985-8284
Roy RabbieWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom.ORCID 0000-0002-9195-5659
Manik GargEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, United Kingdom.ORCID 0000-0003-0453-2058
Dianne LumaquinDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-5285-0467
Ting-Hsiang HuangDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0001-8739-0571
Emily MontalDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0001-7855-3631
Yilun MaDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-2297-9980
Nelly M CruzDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-9040-6957
Xinran TangDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-3411-8854
Jérémie NsengimanaBiostatistics Research Group, Population Health Sciences Institute, Faculty of Medical Sciences Newcastle University, Newcastle upon Tyne, United Kingdom.ORCID 0000-0002-3603-4208
Julia Newton-BishopUniversity of Leeds School of Medicine, Leeds, United Kingdom.ORCID 0000-0001-9147-6802
Miranda V HunterDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-6971-1738
Yuxin ZhuAntitumor Assessment Core Facility, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-0886-4116
Kevin ChenAntitumor Assessment Core Facility, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-3851-6016
Elisa de StanchinaAntitumor Assessment Core Facility, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0002-3873-315X
David J AdamsWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom.ORCID 0000-0001-9490-0306
Richard M WhiteDepartment of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, New York.ORCID 0000-0001-9099-9169
Memorial Sloan Kettering Cancer Center · USWellcome Sanger Institute · GBEuropean Bioinformatics Institute · GBNewcastle University · GBUniversity of Leeds · GB

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Weill Cornell/Rockefeller/Sloan-Kettering MST ProgramT32GM007739 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI HSU, KATHARINE C · 1985 to 2023
$51.1M
Genetic Epidermiology of MelanomaR01CA083115 · NCI · UNIVERSITY OF PENNSYLVANIA · PI BISHOP, DAVID TIMOTHY, ELDER, DAVID ERIC · 2001 to 2017
$13.0M
Dissecting the complexity of metastasis with mathematical models and quantitative experiments with in zebrafishR01CA229215 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI WHITE, RICHARD MARK, XAVIER, JOAO · 2018 to 2022
$3.1M
Identification and characterization of cancer cell states by novel computational and experimental technologies - Resubmission - 1U01CA260432 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Richard Mark White, ITAI YANAI · 2022 to 2026
$2.9M
Evolutionary dynamics of melanoma metastasisDP2CA186572 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI WHITE, RICHARD MARK · 2013 to 2013
$2.7M
Lipid programs in melanocyte transformationR01CA238317 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI OVERHOLTZER, MICHAEL H., WHITE, RICHARD MARK · 2020 to 2025
$2.0M
Investigating cancer metabolism and its potential for therapeutic interventionK00CA223016 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI MONTAL, EMILY DINA · 2019 to 2022
$391k
In vivo characterization of keratinocytes in the melanoma microenvironmentF30CA265124 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI MA, YILUN · 2021 to 2024
$206k
The role of lipids in melanoma progression via induction of ER stress and lipid droplet formationF30CA254152 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI LUMAQUIN, DIANNE · 2020 to 2023
$198k
Medical Research Council MR/V000292/1NCI NIH HHS DP2 CA186572NCI NIH HHS F30 CA254152NCI NIH HHS F30 CA265124NCI NIH HHS K00 CA223016NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA083115NCI NIH HHS R01 CA229215NCI NIH HHS R01 CA238317NCI NIH HHS U01 CA260432NIGMS NIH HHS T32 GM007739Wellcome Trust
6 · The paper itself

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.

Indexed as

MelanomaZebrafishAnimalsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeoplasm MetastasisNeoplasm Recurrence, LocalTranscription Factor AP-1Transcription Factor AP-1

Identifiers

PMID36259947
PMCPMC9827116
OpenAlexW4306793252

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.