Evidence map›Paper›PMID 24739241›Full record

ArticleGenome medicine2014

Transcriptional dissection of pancreatic tumors engrafted in mice.

Raquel Martinez-Garcia, David Juan, Antonio Rausell, Manuel Muñoz, Natalia Baños, Camino Menéndez, Pedro P Lopez-Casas, Daniel Rico, Alfonso Valencia, Manuel Hidalgo

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2014. 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
3.1field-weighted citation impact, top 7% 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, 45 citations in OpenAlex.

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  17. Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors.Annals of oncology : official journal of the European Society for Medical Oncology · 2017
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  19. Treatment of Pancreatic Cancer Patient-Derived Xenograft Panel with Metabolic Inhibitors Reveals Efficacy of Phenformin.Clinical cancer research : an official journal of the American Association for Cancer Research · 2017
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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

10 authors at 3 institutions in 2 countries.

Raquel Martinez-GarciaGastrointestinal Cancer Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
David JuanStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Antonio RausellSIB Swiss Institute of Bioinformatics, Vital-IT Group, 1015 Lausanne, Switzerland ; Institute of Microbiology, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland.
Manuel MuñozGastrointestinal Cancer Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Natalia BañosGastrointestinal Cancer Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Camino MenéndezGastrointestinal Cancer Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Pedro P Lopez-CasasGastrointestinal Cancer Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Daniel RicoStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Alfonso ValenciaStructural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Manuel HidalgoGastrointestinal Cancer Clinical Research Unit, Clinical Research Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.
Spanish National Cancer Research Centre · ESCentro de Investigación del Cáncer · ESSIB Swiss Institute of Bioinformatics · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEngraftment of primary pancreas ductal adenocarcinomas (PDAC) in mice to generate patient-derived xenograft (PDX) models is a promising platform for biological and therapeutic studies in this disease. However, these models are still incompletely characterized. Here, we measured the impact of the murine tumor environment on the gene expression of the engrafted human tumoral cells.

methodsWe have analyzed gene expression profiles from 35 new PDX models and compared them with previously published microarray data of 18 PDX models, 53 primary tumors and 41 cell lines from PDAC. The results obtained in the PDAC system were further compared with public available microarray data from 42 PDX models, 108 primary tumors and 32 cell lines from hepatocellular carcinoma (HCC). We developed a robust analysis protocol to explore the gene expression space. In addition, we completed the analysis with a functional characterization of PDX models, including if changes were caused by murine environment or by serial passing.

resultsOur results showed that PDX models derived from PDAC, or HCC, were clearly different to the cell lines derived from the same cancer tissues. Indeed, PDAC- and HCC-derived cell lines are indistinguishable from each other based on their gene expression profiles. In contrast, the transcriptomes of PDAC and HCC PDX models can be separated into two different groups that share some partial similarity with their corresponding original primary tumors. Our results point to the lack of human stromal involvement in PDXs as a major factor contributing to their differences from the original primary tumors. The main functional differences between pancreatic PDX models and human PDAC are the lower expression of genes involved in pathways related to extracellular matrix and hemostasis and the up- regulation of cell cycle genes. Importantly, most of these differences are detected in the first passages after the tumor engraftment.

conclusionsOur results suggest that PDX models of PDAC and HCC retain, to some extent, a gene expression memory of the original primary tumors, while this pattern is not detected in conventional cancer cell lines. Expression changes in PDXs are mainly related to pathways reflecting the lack of human infiltrating cells and the adaptation to a new environment. We also provide evidence of the stability of gene expression patterns over subsequent passages, indicating early phases of the adaptation process.

Identifiers

PMID24739241
PMCPMC4062047
OpenAlexW2157541293

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.