Evidence map›Paper›PMID 30728464›Full record

ArticleLaboratory investigation; a journal of technical methods and pathology2019

A pipeline for rapidly generating genetically engineered mouse models of pancreatic cancer using in vivo CRISPR-Cas9-mediated somatic recombination.

Noboru Ideno, Hiroshi Yamaguchi, Takashi Okumura, Jonathon Huang, Mitchell J Brun, Michelle L Ho, Junghae Suh, Sonal Gupta, Anirban Maitra, Bidyut Ghosh

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Laboratory investigation; a journal of technical methods and pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

19 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. CRISPRingCancers · 2024
    Review
  6. Review
  7. Review
  8. Article
  9. Review
  10. CRISPR in cancer biology and therapy.Nature reviews. Cancer · 2022
    Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. Pre-clinical Models of Metastasis in Pancreatic Cancer.Frontiers in cell and developmental biology · 2021
    Review
  16. Article
  17. Review
  18. Journal of veterinary science · 2020
    Article
  19. Review
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 1 country.

Noboru IdenoDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA.
Hiroshi YamaguchiDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA.
Takashi OkumuraDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA.
Jonathon HuangDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA.
Mitchell J BrunDepartment of Chemical and Biomolecular Engineering, Rice University, Houston, TX, USA.
Michelle L HoDepartment of Bioengineering, Rice University, Houston, TX, USA.
Junghae SuhDepartment of Bioengineering, Rice University, Houston, TX, USA.
Sonal GuptaDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA.
Anirban MaitraDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA. amaitra@mdanderson.org.
Bidyut GhoshDepartment of Translational Molecular Pathology and Sheikh Ahmed Pancreatic Cancer Research Center, UT MD Anderson Cancer Center, Houston, TX, USA. bghosh@mdanderson.org.
Cancer Research Center · USRice University · USThe University of Texas MD Anderson Cancer Center · US

Funding

The RAS and P13K Pathways in Pancreatic AdenocarcinomaP01CA117969 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KALLURI, RAGHU · 2006 to 2025
$41.7M
NCI NIH HHS P01 CA117969
6 · The paper itself

Abstract

Genetically engineered mouse models (GEMMs) that recapitulate the major genetic drivers in pancreatic ductal adenocarcinoma (PDAC) have provided unprecedented insights into the pathogenesis of this lethal neoplasm. Nonetheless, generating an autochthonous model is an expensive, time consuming and labor intensive process, particularly when tissue specific expression or deletion of compound alleles are involved. In addition, many of the current PDAC GEMMs cause embryonic, pancreas-wide activation or loss of driver alleles, neither of which reflects the cognate human disease scenario. The advent of CRISPR/Cas9 based gene editing can potentially circumvent many of the aforementioned shortcomings of conventional breeding schema, but ensuring the efficiency of gene editing in vivo remains a challenge. Here we have developed a pipeline for generating PDAC GEMMs of complex genotypes with high efficiency using a single "workhorse" mouse strain expressing Cas9 in the adult pancreas under a p48 promoter. Using adeno-associated virus (AAV) mediated delivery of multiplexed guide RNAs (sgRNAs) to the adult murine pancreas of p48-Cre; LSL-Cas9 mice, we confirm our ability to express an oncogenic Kras

Indexed as

Neoplasms, ExperimentalPancreatic NeoplasmsAnimalsCRISPR-Cas SystemsDependovirusGene EditingGenetic VectorsGene Transfer TechniquesHEK293 CellsHumansMiceMice, Inbred C57BLMice, TransgenicRecombination, GeneticRNA, Guide, CRISPR-Cas SystemsRNA, Guide, CRISPR-Cas Systems

Identifiers

PMID30728464
OpenAlexW2949429643

What OpenQuestion holds

Textmetadata
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.