Evidence map›Paper›PMID 24123531›Full record

ArticleHead & neck2014

HRAS mutations and resistance to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib in head and neck squamous cell carcinoma cells.

J Hun Hah, Mei Zhao, Curtis R Pickering, Mitchell J Frederick, Genevieve A Andrews, Samar A Jasser, David R Fooshee, Zvonimir L Milas, Chad Galer, Daisuke Sano and 6 more

Abstract read
In one paragraph

Article in Head & neck, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

21 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. New insights into RAS in head and neck cancer.Biochimica et biophysica acta. Reviews on cancer · 2023
    Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Review
  11. Understanding the Mechanisms of Resistance inInternational journal of molecular sciences · 2019
    Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Functional Precision Medicine Identifies Novel Druggable Targets and Therapeutic Options in Head and Neck Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018
    Article
  18. Identification of Key Genes and Pathways in Tongue Squamous Cell Carcinoma Using Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2017
    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 4 institutions in 3 countries.

J Hun HahDepartment of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Otolaryngology - Head and Neck Surgery, Seoul National University Hospital and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
Mei Zhao
Curtis R Pickering
Mitchell J Frederick
Genevieve A Andrews
Samar A Jasser
David R Fooshee
Zvonimir L Milas
Chad Galer
Daisuke Sano
William N William
Edward Kim
John Heymach
Lauren A Byers
Vali Papadimitrakopoulou
Jeffrey N Myers
The University of Texas MD Anderson Cancer Center · USOrlando Health · USSeoul National University Hospital · KRYokohama City University · JP

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Targeting the p53 pathway for reversal of oral premalignancyP50CA097007 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MYERS, JEFFREY NICHOLAS · 2002 to 2012
$26.1M
TRAINING OF ACADEMIC HEAD AND NECK SURGICAL ONCOLOGISTST32CA060374 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MYERS, JEFFREY NICHOLAS · 1995 to 2010
$797k
NCI NIH HHS CA016672NCI NIH HHS P30 CA016672NCI NIH HHS P50 CA097007NCI NIH HHS P50CA097007NCI NIH HHS T32 CA060374NCI NIH HHS T32CA060374
6 · The paper itself

Abstract

backgroundThe purpose of this study was to identify mechanisms of innate resistance to an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, erlotinib, in a panel of head and neck squamous cell carcinoma (HNSCC) cell lines. Specifically, we analyzed the role of HRAS mutations in erlotinib resistance.

methodsErlotinib sensitivity was determined by methyl thiazolyl-tetrazolium (MTT) assays. Molecular signaling pathways and somatic mutations were examined. Changes in sensitivity after modulation of HRAS expression were evaluated.

resultsAll 7 cell lines were wild-type for EGFR and KRAS regardless of erlotinib sensitivity; however, 1 erlotinib-resistant cell line (HN31) harbored an HRAS G12D mutation. Downregulation of HRAS expression by small interfering RNA (siRNA) or short hairpin RNA (shRNA) in HN31 led to increased erlotinib sensitivity in vitro and in vivo. Transfection of activating HRAS-mutant (G12D and G12V) constructs into erlotinib-sensitive cell lines made them more resistant to erlotinib.

conclusionActivating HRAS mutations can confer erlotinib resistance in an HRAS mutant HNSCC cell line.

Indexed as

MutationAnimalsBlotting, WesternCarcinoma, Squamous CellCell Line, TumorCell ProliferationDown-RegulationDrug Resistance, NeoplasmErlotinib HydrochlorideHead and Neck NeoplasmsHumansMiceMolecular Targeted TherapyProtein Kinase InhibitorsProto-Oncogene Proteins p21(ras)QuinazolinesErlotinib HydrochlorideHRAS protein, humanProtein Kinase InhibitorsProto-Oncogene Proteins p21(ras)Quinazolinesepidermal growth factor receptorerlotinibhead and neck squamous cell carcinomaHRASresistance

Identifiers

PMID24123531
PMCPMC4010580
OpenAlexW2123099397

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.