Evidence map›Paper›PMID 24507750›Full record

ArticleJournal of translational medicine2014

Generation of orthotopic patient-derived xenografts from gastrointestinal stromal tumor.

Jason K Sicklick, Stephanie Y Leonard, Michele L Babicky, Chih-Min Tang, Evangeline S Mose, Randall P French, Dawn V Jaquish, Carl K Hoh, Michael Peterson, Richard Schwab and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.5field-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

20 citing papers in PubMed, 30 citations in OpenAlex.

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  12. Tumor-targetingHeliyon · 2018
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  16. Patient-derived xenografts: a relevant preclinical model for drug development.Journal of experimental & clinical cancer research : CR · 2016
    Review
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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

11 authors at 1 institution in 1 country.

Jason K SicklickDivision of Surgical Oncology and Department of Surgery, Moores UCSD Cancer Center, University of California, San Diego, 3855 Health Sciences Drive, Mail Code 0987, La Jolla, CA 92093-0987, USA. jsicklick@ucsd.edu.
Stephanie Y Leonard
Michele L Babicky
Chih-Min Tang
Evangeline S Mose
Randall P French
Dawn V Jaquish
Carl K Hoh
Michael Peterson
Richard Schwab
Andrew M Lowy
University of California, San Diego · US

Funding

VIRAL MALIGNANCYP30CA023100 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DIANE M SIMEONE · 1985 to 2026
$124.9M
UCSD Cancer Center Training Program in Drug DevelopmentT32CA121938 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Michael Bouvet, Dwayne G. Stupack · 2006 to 2026
$10.3M
Targeted Smart Nanoplatforms for Multimode ImagingP50CA128346 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI STUPACK, DWAYNE G. · 2008 to 2012
$6.9M
NCI NIH HHS P30 CA023100NCI NIH HHS P50 CA128346NCI NIH HHS T32 CA121938
6 · The paper itself

Abstract

backgroundGastrointestinal stromal tumor (GIST) is the most common sarcoma and its treatment with imatinib has served as the paradigm for developing targeted anti-cancer therapies. Despite this success, imatinib-resistance has emerged as a major problem and therefore, the clinical efficacy of other drugs has been investigated. Unfortunately, most clinical trials have failed to identify efficacious drugs despite promising in vitro data and pathological responses in subcutaneous xenografts. We hypothesized that it was feasible to develop orthotopic patient-derived xenografts (PDXs) from resected GIST that could recapitulate the genetic heterogeneity and biology of the human disease.

methodsFresh tumor tissue from three patients with pathologically confirmed GISTs was obtained immediately following tumor resection. Tumor fragments (4.2-mm3) were surgically xenografted into the liver, gastric wall, renal capsule, and pancreas of immunodeficient mice. Tumor growth was serially assessed with ultrasonography (US) every 3-4 weeks. Tumors were also evaluated with positron emission tomography (PET). Animals were sacrificed when they became moribund or their tumors reached a threshold size of 2500-mm3. Tumors were subsequently passaged, as well as immunohistochemically and histologically analyzed.

resultsHerein, we describe the first model for generating orthotopic GIST PDXs. We have successfully xenografted three unique KIT-mutated tumors into a total of 25 mice with an overall success rate of 84% (21/25). We serially followed tumor growth with US to describe the natural history of PDX growth. Successful PDXs resulted in 12 primary xenografts in NOD-scid gamma or NOD-scid mice while subsequent successful passages resulted in 9 tumors. At a median of 7.9 weeks (range 2.9-33.1 weeks), tumor size averaged 473 ± 695-mm³ (median 199-mm3, range 12.6-2682.5-mm³) by US. Furthermore, tumor size on US within 14 days of death correlated with gross tumor size on necropsy. We also demonstrated that these tumors are FDG-avid on PET imaging, while immunohistochemically and histologically the PDXs resembled the primary tumors.

conclusionsWe report the first orthotopic model of human GIST using patient-derived tumor tissue. This novel, reproducible in vivo model of human GIST may enhance the study of GIST biology, biomarkers, personalized cancer treatments, and provide a preclinical platform to evaluate new therapeutic agents for GIST.

Indexed as

Xenograft Model Antitumor AssaysAgedAnimalsDemographyDisease ProgressionFemaleFluorodeoxyglucose F18Gastrointestinal Stromal TumorsHumansMaleMiceMice, SCIDMiddle AgedPositron-Emission TomographyUltrasonographyFluorodeoxyglucose F18

Identifiers

PMID24507750
PMCPMC3930355
OpenAlexW2141149187

What OpenQuestion holds

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LicenceCC BY
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.