Evidence map›Paper›PMID 31182434›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2019

The EGFR Exon 19 Mutant L747-A750>P Exhibits Distinct Sensitivity to Tyrosine Kinase Inhibitors in Lung Adenocarcinoma.

Anna Truini, Jacqueline H Starrett, Tyler Stewart, Kumar Ashtekar, Zenta Walther, Anna Wurtz, David Lu, Jin H Park, Michelle DeVeaux, Xiaoling Song and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
4.9field-weighted citation impact, top 4% 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

39 citing papers in PubMed, 60 citations in OpenAlex.

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  17. Subtype of EGFR exon 19 deletion mutations.Translational lung cancer research · 2024
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 1 institution in 1 country.

Anna Truini *Yale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Jacqueline H Starrett *Department of Pathology, Yale School of Medicine, New Haven, Connecticut.
Tyler Stewart *Department of Medicine (Section of Medical Oncology), Yale School of Medicine, New Haven, Connecticut.
Kumar Ashtekar *Department of Pharmacology, Yale School of Medicine, New Haven, Connecticut.
Zenta WaltherDepartment of Pathology, Yale School of Medicine, New Haven, Connecticut.
Anna WurtzYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
David LuDepartment of Pharmacology, Yale School of Medicine, New Haven, Connecticut.
Jin H ParkDepartment of Pharmacology, Yale School of Medicine, New Haven, Connecticut.
Michelle DeVeauxDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut.
Xiaoling SongYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Scott GettingerYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Daniel ZeltermanYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Mark A LemmonYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Sarah B GoldbergYale Cancer Center, Yale School of Medicine, New Haven, Connecticut.
Katerina PolitiYale Cancer Center, Yale School of Medicine, New Haven, Connecticut. katerina.politi@yale.edu.
Yale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale SPORE in Lung Cancer (YSILC): The Biology and Personalized Treatment of Lung CancerP50CA196530 · NCI · YALE UNIVERSITY · PI Roy S Herbst · 2015 to 2026
$31.1M
Understanding EGF receptor activation by growth factors and oncogenic mutationsR01CA198164 · NCI · YALE UNIVERSITY · PI FERGUSON, KATHRYN M, LEMMON, MARK A · 2015 to 2024
$5.2M
Mutant EGF Receptor-Dependent Lung Cancer in Human Cell Lines and Transgenic MiceR01CA120247 · NCI · YALE UNIVERSITY · PI POLITI, KATERINA ABIGAIL · 2006 to 2014
$3.8M
Yale Cancer Biology Training GrantT32CA193200 · NCI · YALE UNIVERSITY · PI PETER M GLAZER, Qin Yan · 2016 to 2026
$3.6M
INVESTIGATING ACQUIRED RESISTANCE TO FIRST-LINE OSIMERTINIB IN EGFR MUTANT MODELS OF LUNG ADENOCARCINOMAF31CA228268 · NCI · YALE UNIVERSITY · PI STARRETT, JACQUELINE HEALY · 2019 to 2020
$36k
NCATS NIH HHS UL1 TR001863NCI NIH HHS F31 CA228268NCI NIH HHS P50 CA196530NCI NIH HHS R01 CA120247NCI NIH HHS R01 CA198164NCI NIH HHS T32 CA193200
6 · The paper itself

Abstract

purpose

resultsWe found that the L747-A750>P mutation, which represents about 4% of all Ex19Del mutations, displays unique inhibitor selectivity. L747-A750>P differs from other Ex19Del mutations in not being suppressed completely by erlotinib or osimertinib, yet is completely inhibited by low doses of afatinib. The HCC4006 cell line (with the L747-A750>P mutation) exhibited increased sensitivity to afatinib over erlotinib and osimertinib, and computational modeling suggests explanations for this sensitivity pattern. Clinically, patients with EGFR L747-A750>P mutant tumors showed inferior outcomes when treated with erlotinib than patients with E746-A750 mutant tumors.

conclusionsThese results highlight important differences between specific Ex19Del mutations that may be relevant for optimizing TKI choice for patients.

Indexed as

AcrylamidesAdenocarcinoma of LungAfatinibAniline CompoundsAnimalsCHO CellsCricetulusErbB ReceptorsErlotinib HydrochlorideExonsGene DeletionHumansIndolesModels, ChemicalMolecular Dynamics SimulationMutationAcrylamidesAfatinibAniline CompoundsEGFR protein, humanErbB ReceptorsErlotinib HydrochlorideIndolesosimertinibProtein Kinase InhibitorsPyrimidines

Identifiers

PMID31182434
PMCPMC6825535
OpenAlexW4230527528

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.