Evidence map›Paper›PMID 32617305›Full record

ArticleAnnals of translational medicine2020

High-level gain of mesenchymal-epithelial transition factor (MET) copy number using next-generation sequencing as a predictive biomarker for MET inhibitor efficacy.

Shibo Wu, Guodong Li, Xin Zhao, Jianxing Xiang, Analyn Lizaso, Junyi Ye, Chunlei Shi, Lingxiang Chen

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

8 authors at 6 institutions in 1 country.

Shibo WuDepartment of Respiratory Medicine, Lihuili Hospital, Ningbo Medical Center, Ningbo, China.
Guodong LiDepartment of Interventional Therapy, Fudan University Shanghai Cancer Center, Shanghai China.
Xin ZhaoDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jianxing XiangBurning Rock Biotech, Guangzhou, China.
Analyn LizasoBurning Rock Biotech, Guangzhou, China.
Junyi YeBurning Rock Biotech, Guangzhou, China.
Chunlei ShiDepartment of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.
Lingxiang ChenDepartment of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Burning Rock Biotech (China) · CNFirst Affiliated Hospital of Chinese PLA General Hospital · CNFudan University Shanghai Cancer Center · CNNanjing Medical University · CNNingbo Medical Center Lihuili Hospital · CNShanghai Chest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn clinical oncology, targeted next-generation sequencing (NGS) has become an integral part of the routine molecular diagnostics repertoire. However, a consensus is yet to be agreed on the optimal mesenchymal-epithelial transition factor (

methodsSequencing data from matched plasma and tissue samples from 40

resultsAdCN, calculated as the absolute CN generated from NGS relative to the maximum mutant allele fraction (maxMAF) per sample, was demonstrated to have a high correlation with

conclusionsWe derived a normalization method that could reflect the relative CN and distinguish

Indexed as

crizotinibMesenchymal-epithelial transition factor amplification (MET amplification)mesenchymal-epithelial transition factor copy number gain (MET CN gain)mesenchymal-epithelial transition factor tyrosine kinase inhibitor (MET TKI)predictive biomarker

Identifiers

PMID32617305
PMCPMC7327325
OpenAlexW3027327874

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.