Evidence map›Paper›PMID 28292264›Full record

ArticleBMC cancer2017

Establishment of patient-derived gastric cancer xenografts: a useful tool for preclinical evaluation of targeted therapies involving alterations in HER-2, MET and FGFR2 signaling pathways.

Haiyong Wang, Jun Lu, Jian Tang, Shitu Chen, Kuifeng He, Xiaoxia Jiang, Weiqin Jiang, Lisong Teng

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

32 citing papers in PubMed, 47 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Haiyong WangDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China.
Jun LuDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China.
Jian TangDepartment of oncology, Jiaxing First Hospital, Jiaxing, 314000, Zhejiang Province, China.
Shitu ChenDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China.
Kuifeng HeDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China.
Xiaoxia JiangDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China.
Weiqin JiangDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China.
Lisong TengDepartment of surgical oncology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang Province, China. lsteng@zju.edu.cn.
Zhejiang University · CNFirst Hospital of Jiaxing · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTargeted therapies are emerging treatment options for gastric cancer (GC). Patient-derived tumor xenograft(PDX) models of GC closely retain the features of the original clinical cancer, offering a powerful tool for preclinical drug efficacy testing. This study aimed to establish PDX GC models, and explore therapeutics targeting Her2, MET(cMet), and FGFR2, which may assist doctor to select the proper target therapy for selected patients.

methodsGC tissues from 32 patients were collected and implanted into immuno-deficient mice. Using immunohistochemistry(IHC) and fluorescent in-situ hybridization (FISH), protein levels and/or gene amplification of Her2, cMet and FGFR2 in those tissues were assessed. Finally, anti-tumor efficacy was tested in the PDX models using targeted inhibitors.

resultsA total of 9 passable PDX models were successfully established from 32 gastric cancer xenograft donors, consisting of HER2,cMet and FGFR2 alterations with percentages of 4(12.5%), 8(25.0%) and 1(3.1%) respectively. Crizotinib and AZD4547 exerted marked antitumor effects exclusively in PDX models with cMet (G30,G31) and FGFR2(G03) amplification. Interestingly, synergistic antitumor activity was observed in G03 (FGFR2-amplifed and cMet non-amplified but IHC [2+]) with simultaneous treatment with Crizotinib and ADZ4547 at day 30 post-treatment. Further in vitro biochemistry study showed a synergistic inhibition of the MAPK/ERK pathway. HER2,cMet and FGFR2 alterations were found in 17 (10.4%), 32(19.6%) and 6(3.7%) in a group of 163 GC patients, and cMet gene amplification or protein overexpression(IHC 3+) was associated with poor prognosis.

conclusionsThese PDX GC models provide an ideal platform for drug screening and evaluation. GC patients with positive cMet or FGFR2 gene amplification may potentially benefit from cMet or FGFR2 targeted therapies or combined targeted therapy.

Indexed as

AnimalsAntineoplastic AgentsBenzamidesCell Line, TumorCrizotinibDrug SynergismErb-b2 Receptor Tyrosine KinasesFemaleHumansKaplan-Meier EstimateMice, Inbred BALB CMice, NudeMiddle AgedMolecular Targeted TherapyPiperazinesProtein Kinase InhibitorsAntineoplastic AgentsAZD4547BenzamidesCrizotinibERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesFGFR2 protein, humanMET protein, humanPiperazinesProtein Kinase InhibitorsProto-Oncogene Proteins c-metPyrazolesPyridinesReceptor, Fibroblast Growth Factor, Type 2cMetFGFRGastric cancerHer2Targeted therapyXenograft

Identifiers

PMID28292264
PMCPMC5348902
OpenAlexW2600505732

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.