Evidence map›Paper›PMID 35326664›Full record

ArticleCancers2022

Early On-Treatment Prediction of the Mechanisms of Acquired Resistance to EGFR Tyrosine Kinase Inhibitors.

Yu-Ra Choi, Youngnam Cho, Seog-Yun Park, Sunshin Kim, Myungsun Shin, Yongdoo Choi, Dong Hoon Shin, Ji-Youn Han, Youngjoo Lee

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Therapeutic advances of targeting receptor tyrosine kinases in cancer.Signal transduction and targeted therapy · 2024
    Review
  3. Article
  4. 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

9 authors at 1 institution in 1 country.

Yu-Ra ChoiDivision of Translational Science, Research Institute, National Cancer Center, Goyang 10408, Korea.ORCID 0000-0002-5103-9592
Youngnam ChoDivision of Translational Science, Research Institute, National Cancer Center, Goyang 10408, Korea.
Seog-Yun ParkDepartment of Pathology, National Cancer Center, Goyang 10408, Korea.
Sunshin KimDivision of Precision Medicine, Research Institute, National Cancer Center, Goyang 10408, Korea.
Myungsun ShinDivision of Convergence Technology, National Cancer Center, Goyang 10408, Korea.
Yongdoo ChoiDivision of Convergence Technology, National Cancer Center, Goyang 10408, Korea.
Dong Hoon ShinDivision of Translational Science, Research Institute, National Cancer Center, Goyang 10408, Korea.ORCID 0000-0003-2531-6493
Ji-Youn HanDivision of Precision Medicine, Research Institute, National Cancer Center, Goyang 10408, Korea.
Youngjoo LeeDivision of Translational Science, Research Institute, National Cancer Center, Goyang 10408, Korea.ORCID 0000-0003-0180-189X
National Cancer Center · KR

Funding

Ministry of Education 2018R1D1A1B07040599National Cancer Center 2110021-1National Research Foundation of Korea 2017M3A9F9030559
6 · The paper itself

Abstract

backgroundPrediction of resistance mechanisms for epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) remains challenging. Thus, we investigated whether resistant cancer cells that expand shortly after EGFR-TKI treatment would eventually cause the resistant phenotype.

methodsWe generated two

resultsT790M mutation was only detected in the PC9GR cells, whereas

conclusionsEarly on-treatment kinetics in resistance-related gene alterations may predict the final mechanism of EGFR-TKI resistance.

Indexed as

C-MET amplificationDRUG resistanceEGFR mutationlung CANCERtyrosine kinase inhibitor

Identifiers

PMID35326664
PMCPMC8946020
OpenAlexW4220667620

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.