Evidence map›Paper›PMID 40501949›Full record

ArticlebioRxiv : the preprint server for biology2025

Robust statistical assessment of Oncogenotype to Organotropism translation in xenografted zebrafish.

David Saucier, Xuexia Jiang, Divya Rajendran, Roshan Ravishankar, Erin Butler, Aruna Marchetto, Raushan T Kurmasheva, Thomas G P Grünewald, James F Amatruda, Gaudenz Danuser

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

David SaucierGreen Center for Systems Biology and Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA.
Xuexia JiangGreen Center for Systems Biology and Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA.
Divya RajendranGreen Center for Systems Biology and Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA.ORCID 0000-0002-5860-9586
Roshan RavishankarGreen Center for Systems Biology and Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA.ORCID 0000-0001-5778-2881
Erin ButlerDepartment of Pediatrics, UT Southwestern Medical Center, Dallas, TX, USA.ORCID 0000-0003-4178-4430
Aruna MarchettoMax-Eder Research Group for Pediatric Sarcoma Biology, Institute of Pathology, Faculty of Medicine, LMU Munich, Munich, Germany.ORCID 0000-0002-8873-2251
Raushan T KurmashevaGreehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio TX, USA.ORCID 0000-0003-3212-2363
Thomas G P GrünewaldHopp-Children's Cancer Center (KiTZ), Heidelberg, Germany.ORCID 0000-0003-0920-7377
James F AmatrudaCancer and Blood Disease Institute, Children's Hospital Los Angeles, Los Angeles, CA, USA.ORCID 0000-0002-9901-2137
Gaudenz DanuserGreen Center for Systems Biology and Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA.ORCID 0000-0001-8583-2014

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
Targeting EWSR1-FLI1 through Functional, Structural and Chemical ApproachesU54CA231649 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI NIJHAWAN, DEEPAK · 2019 to 2019
$10.0M
Technical Development Unit 2: Intelligent Hyperspectral Imaging of Subcellular Molecular States at the Whole Organ LevelU54CA268072 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI SEAN J MORRISON · 2021 to 2026
$9.1M
Functional causality in regulating cell morphogenesisR35GM136428 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI DANUSER, GAUDENZ · 2020 to 2024
$4.1M
The Mechanism of SOX6 in Ewing Sarcoma MetastasisF31CA236410 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI SAUCIER, DAVID HAMILTON · 2019 to 2020
$68k
NCI NIH HHS F31 CA236410NCI NIH HHS P30 CA014089NCI NIH HHS U54 CA231649NCI NIH HHS U54 CA268072NIGMS NIH HHS R35 GM136428
6 · The paper itself

Abstract

Organotropism results from the functional versatility of metastatic cancer cells to survive and proliferate in diverse microenvironments. This adaptivity can originate in clonal variation of the spreading tumor and is often empowered by epigenetic and molecular reprogramming of cell regulatory circuits. Related to organotropic colonization of metastatic sites are environmentally-sensitive, differential responses of cancer cells to therapeutic attack. Accordingly, understanding the organotropic profile of a cancer and probing the underlying driver mechanisms are of high clinical importance. However, determining systematically the organotropism of one cancer versus the organotropism of another cancer, potentially with the granularity of comparing the same cancer type between patients or tracking the evolution of a cancer in a single patient for the purpose of personalized treatment, has remained very challenging. It requires a host organism that allows observation of the spreading pattern over relatively short experimental times. Moreover, organotropic patterns often tend to be statistically weak and superimposed by experimental variation. Thus, an assay for organotropism must give access to statistical powers that can separate 'meaningful heterogeneity', i.e., heterogeneity that determines organotropism, from 'meaningless heterogeneity', i.e., heterogeneity that causes experimental noise. Here we describe an experimental workflow that leverages the physiological properties of zebrafish larvae for an imaging-based assessment of organotropic patterns over a time-frame of 3 days. The workflow incorporates computer vision pipelines to automatically integrate the stochastic spreading behavior of a particular cancer xenograft in tens to hundreds of larvae allowing subtle trends in the colonization of particular organs to emerge above random cell depositions throughout the host organism. We validate our approach with positive control experiments comparing the spreading patterns of a metastatic sarcoma against non-transformed fibroblasts and the spreading patterns of two melanoma cell lines with previously established differences in metastatic propensity. We then show that integration of the spreading pattern of xenografts in 40 - 50 larvae is necessary and sufficient to generate a

Identifiers

PMID40501949
PMCPMC12154647

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.