Evidence map›Paper›PMID 32277151›Full record

ArticleScientific reports2020

A novel diagnostic system to evaluate epidermal growth factor receptor impact as a prognostic and therapeutic indicator for lung adenocarcinoma.

Kazuya Takakuwa, Kaoru Mogushi, Min Han, Tomoaki Fujii, Masaki Hosoya, Arina Yamanami, Tomomi Akita, Chikamasa Yamashita, Tetsu Hayashida, Shunsuke Kato and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

11 authors at 4 institutions in 1 country.

Kazuya TakakuwaDepartment of Clinical Oncology, Juntendo University Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.
Kaoru MogushiDepartment of Clinical Oncology, Juntendo University Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.
Min HanDepartment of Clinical Oncology, Juntendo University Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.
Tomoaki FujiiDepartment of Cancer Genome Research, Sasaki Institute, Sasaki Foundation, Kandasurugadai, Chiyoda-ku, Tokyo, Japan.
Masaki HosoyaDepartment of Clinical Oncology, Juntendo University Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.
Arina YamanamiInternational School of the Sacred Heart, Shibuya-Ku, Tokyo, Japan.
Tomomi AkitaDepartment of Pharmaceutics and Drug Delivery, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Yamazaki, Noda, Chiba, Japan.
Chikamasa YamashitaDepartment of Pharmaceutics and Drug Delivery, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Yamazaki, Noda, Chiba, Japan.
Tetsu HayashidaDepartment of Surgery, Keio University School of Medicine, Shinanomachi 35, Shinjuku-ku, Tokyo, Japan.
Shunsuke KatoDepartment of Clinical Oncology, Juntendo University Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.
Shigeo YamaguchiDepartment of Clinical Oncology, Juntendo University Graduate School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan. yamashige33@gmail.com.
Juntendo University · JPTokyo University of Science · JPKeio University · JPSasaki Institute · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many driver pathways for cancer cell proliferation have been reported. Driver pathway activation is often evaluated based on a single hotspot mutation such as EGFR L858R. However, because of complex intratumoral networks, the impact of a driver pathway cannot be predicted based on only a single gene mutation. Here, we developed a novel diagnostic system named the "EGFR impact score" which is based on multiplex mRNA expression profiles, which can predict the impact of the EGFR pathway in lung cancer cells and the effect of EGFR-tyrosine kinase inhibitors on malignancy. The EGFR impact score indicated robust predictive power for the prognosis of early-stage lung cancer because this score can evaluate the impact of the EGFR pathway on the tumor and genomic instability. Additionally, the molecular features of the poor prognostic group resembled those of biomarkers associated with immune checkpoint inhibitors. The EGFR impact score is a novel prognostic and therapeutic indicator for lung adenocarcinoma.

Indexed as

Gene Expression ProfilingAdenocarcinoma of LungAlgorithmsAntineoplastic Agents, ImmunologicalAntineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorCell ProliferationDatasets as TopicDisease-Free SurvivalErbB ReceptorsFeasibility StudiesFollow-Up StudiesGene Expression Regulation, NeoplasticHumansLung NeoplasmsMutationAntineoplastic Agents, ImmunologicalBiomarkers, TumorEGFR protein, humanErbB ReceptorsProtein Kinase Inhibitors

Identifiers

PMID32277151
PMCPMC7148318
OpenAlexW3015450907

What OpenQuestion holds

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LicenceCC BY
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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.