Evidence map›Paper›PMID 20113473›Full record

ArticleJournal of translational medicine2010

Anti-viral state segregates two molecular phenotypes of pancreatic adenocarcinoma: potential relevance for adenoviral gene therapy.

Vladia Monsurrò, Stefania Beghelli, Richard Wang, Stefano Barbi, Silvia Coin, Giovanni Di Pasquale, Samantha Bersani, Monica Castellucci, Claudio Sorio, Stefano Eleuteri and 6 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2010. 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
2.3field-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

32 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Immunotherapeutic Challenges for Pediatric Cancers.Molecular therapy oncolytics · 2019
    Review
  11. Article
  12. Bioselection Reveals miR-99b and miR-485 as Enhancers of Adenoviral Oncolysis in Pancreatic Cancer.Molecular therapy : the journal of the American Society of Gene Therapy · 2019
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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

16 authors at 2 institutions in 2 countries.

Vladia MonsurròDepartment of Pathology, University of Verona Medical School, Verona, Italy.
Stefania Beghelli
Richard Wang
Stefano Barbi
Silvia Coin
Giovanni Di Pasquale
Samantha Bersani
Monica Castellucci
Claudio Sorio
Stefano Eleuteri
Andrea Worschech
Jay A Chiorini
Paolo Pederzoli
Harvey Alter
Francesco M Marincola
Aldo Scarpa
University of Verona · ITNational Institutes of Health · US

Funding

Adeno-associated Virus Biology And Utilization For Gene TransferZIADE000695 · NIDCR · NATIONAL INSTITUTE OF DENTAL & CRANIOFACIAL RESEARCH · PI CHIORINI, JAY · 2009 to 2025
$36.6M
Immunogenetics of Vaccine TherapyZIACL002115 · CLC · CLINICAL CENTER · PI MARINCOLA, FRANCESCO M · 2009 to 2010
$0k
Immunogenetic Study of Infectious Diseases and CancerZIACL002118 · CLC · CLINICAL CENTER · PI MARINCOLA, FRANCESCO M · 2009 to 2012
$0k
6 · The paper itself

Abstract

backgroundPancreatic ductal adenocarcinoma (PDAC) remains a leading cause of cancer mortality for which novel gene therapy approaches relying on tumor-tropic adenoviruses are being tested.

methodsWe obtained the global transcriptional profiling of primary PDAC using RNA from eight xenografted primary PDAC, three primary PDAC bulk tissues, three chronic pancreatitis and three normal pancreatic tissues. The Affymetrix GeneChip HG-U133A was used. The results of the expression profiles were validated applying immunohistochemical and western blot analysis on a set of 34 primary PDAC and 10 established PDAC cell lines. Permissivity to viral vectors used for gene therapy, Adenovirus 5 and Adeno-Associated Viruses 5 and 6, was assessed on PDAC cell lines.

resultsThe analysis of the expression profiles allowed the identification of two clearly distinguishable phenotypes according to the expression of interferon-stimulated genes. The two phenotypes could be readily recognized by immunohistochemical detection of the Myxovirus-resistance A protein, whose expression reflects the activation of interferon dependent pathways. The two molecular phenotypes discovered in primary carcinomas were also observed among established pancreatic adenocarcinoma cell lines, suggesting that these phenotypes are an intrinsic characteristic of cancer cells independent of their interaction with the host's microenvironment. The two pancreatic cancer phenotypes are characterized by different permissivity to viral vectors used for gene therapy, as cell lines expressing interferon stimulated genes resisted to Adenovirus 5 mediated lysis in vitro. Similar results were observed when cells were transduced with Adeno-Associated Viruses 5 and 6.

conclusionOur study identified two molecular phenotypes of pancreatic cancer, characterized by a differential expression of interferon-stimulated genes and easily recognized by the expression of the Myxovirus-resistance A protein. We suggest that the detection of these two phenotypes might help the selection of patients enrolled in virally-mediated gene therapy trials.

Indexed as

AdenocarcinomaAdenoviridaeCarcinoma, Pancreatic DuctalGene Expression Regulation, NeoplasticPancreatic NeoplasmsAnimalsCell Line, TumorDependovirusGene Expression ProfilingGenetic TherapyGenetic VectorsHumansImmunityInterferonsMiceMice, NudeInterferonsRNA, Small Interfering

Identifiers

PMID20113473
PMCPMC2845551
OpenAlexW2144556129

What OpenQuestion holds

Textmetadata
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.