Evidence map›Paper›PMID 23113581›Full record

ArticleACS chemical biology2013

Antitumor effects of EGFR antisense guanidine-based peptide nucleic acids in cancer models.

Sufi M Thomas, Bichismita Sahu, Srinivas Rapireddy, Raman Bahal, Sarah E Wheeler, Eva M Procopio, Joseph Kim, Sonali C Joyce, Sarah Contrucci, Yun Wang and 6 more

Open access · greenAbstract read
In one paragraph

Article in ACS chemical biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

30 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
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  3. Review
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  5. Review
  6. Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Multifunctional Delivery Systems for Peptide Nucleic Acids.Pharmaceuticals (Basel, Switzerland) · 2020
    Review
  14. Next generation miRNA inhibition using short anti-seed PNAs encapsulated in PLGA nanoparticles.Journal of controlled release : official journal of the Controlled Release Society · 2020
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Antisense peptide nucleic acids as a potential anti-infective agent.Journal of microbiology (Seoul, Korea) · 2019
    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

16 authors at 2 institutions in 1 country.

Sufi M ThomasDepartment of Otolaryngology, University of Pittsburgh and University of Pittsburgh Cancer Institute, 200 Lothrop Street, Pittsburgh, Pennsylvania 15213, USA. smt30@pitt.edu
Bichismita Sahu
Srinivas Rapireddy
Raman Bahal
Sarah E Wheeler
Eva M Procopio
Joseph Kim
Sonali C Joyce
Sarah Contrucci
Yun Wang
Simion I Chiosea
Kira L Lathrop
Simon Watkins
Jennifer R Grandis
Bruce A Armitage
Danith H Ly
Carnegie Mellon University · USUPMC Hillman Cancer Center · US

Funding

WILD TYPE P53-BASED ADJUVANT IMMUNOTHERAPY FOR SCCHNP50CA097190 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHRISTOPHER J. BAKKENIST · 2004 to 2026
$49.6M
Vitamin D3 Modulation of Inflammation and Lung Cancer RiskP50CA090440 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DACIC, SANJA · 2001 to 2015
$34.6M
Virus Production and Manipulation of Protein/Gene Expression ModuleP30EY008098 · NEI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Ethan A Rossi · 1989 to 2026
$17.8M
Development of Cell-Permeable Peptide Nucleic AcidR01GM077261 · NIGMS · CARNEGIE-MELLON UNIVERSITY · PI LY, DANITH H · 2006 to 2010
$1.1M
NCI NIH HHS 5P50 CA 090440-07NCI NIH HHS P50 CA090440NCI NIH HHS P50 CA097190NEI NIH HHS EY08098NEI NIH HHS P30 EY008098NIGMS NIH HHS R01 GM076251NIGMS NIH HHS R01 GM077261
6 · The paper itself

Abstract

Peptide nucleic acids have emerged over the past two decades as a promising class of nucleic acid mimics because of their strong binding affinity and sequence selectivity toward DNA and RNA, and resistance to enzymatic degradation by proteases and nucleases. While they have been shown to be effective in regulation of gene expression in vitro, and to a small extent in vivo, their full potential for molecular therapy has not yet been fully realized due to poor cellular uptake. Herein, we report the development of cell-permeable, guanidine-based peptide nucleic acids targeting the epidermal growth factor receptor (EGFR) in preclinical models as therapeutic modality for head and neck squamous cell carcinoma (HNSCC) and nonsmall cell lung cancer (NSCLC). A GPNA oligomer, 16 nucleotides in length, designed to bind to EGFR gene transcript elicited potent antisense effects in HNSCC and NSCLC cells in preclinical models. When administered intraperitoneally in mice, EGFRAS-GPNA was taken-up by several tissues including the xenograft tumor. Systemic administration of EGFRAS-GPNA induced antitumor effects in HNSCC xenografts, with similar efficacies as the FDA-approved EGFR inhibitors: cetuximab and erlotinib. In addition to targeting wild-type EGFR, EGFRAS-GPNA is effective against the constitutively active EGFR vIII mutant implicated in cetuximab resistance. Our data reveals that GPNA is just as effective as a molecular platform for treating cetuximab resistant cells, demonstrating its utility in the treatment of cancer.

Indexed as

AnimalsAntineoplastic AgentsCarcinoma, Non-Small-Cell LungCarcinoma, Squamous CellCell Line, TumorDisease Models, AnimalDose-Response Relationship, DrugDrug Screening Assays, AntitumorErbB ReceptorsGuanidineHead and Neck NeoplasmsHumansLung NeoplasmsMiceOligonucleotides, AntisensePeptide Nucleic AcidsAntineoplastic AgentsErbB ReceptorsGuanidineOligonucleotides, AntisensePeptide Nucleic Acids

Identifiers

PMID23113581
PMCPMC3684443
OpenAlexW2035857996

What OpenQuestion holds

Textmetadata
LicenceTDM
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.