Evidence map›Paper›PMID 26989078›Full record

ArticleOncotarget2016

Quantification of mutant alleles in circulating tumor DNA can predict survival in lung cancer.

Xue Yang, Minglei Zhuo, Xin Ye, Hua Bai, Zhijie Wang, Yun Sun, Jun Zhao, Tongtong An, Jianchun Duan, Meina Wu and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% 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

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

  1. Pooled it
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  5. Early ctDNA kinetics as a dynamic biomarker of cancer treatment response.bioRxiv : the preprint server for biology · 2024
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  16. PlasmaAnnals of translational medicine · 2021
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  19. Concomitant genetic alterations are associated with response toTranslational lung cancer research · 2020
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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

11 authors at 3 institutions in 1 country.

Xue YangDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Minglei ZhuoDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Xin YeAsia and Emerging Markets Innovative Medicine of AstraZeneca R & D, Shanghai, China.
Hua BaiDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Zhijie WangDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Yun SunAsia and Emerging Markets Innovative Medicine of AstraZeneca R & D, Shanghai, China.
Jun ZhaoDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Tongtong AnDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Jianchun DuanDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Meina WuDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Jie WangDepartment of Thoracic Medical Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Peking University Cancer Hospital · CNShanghai Innovative Research Center of Traditional Chinese Medicine · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe aimed to investigate the feasibility of droplet digital PCR (ddPCR) for the quantitative and dynamic detection of EGFR mutations and next generation sequencing (NGS) for screening EGFR-tyrosine kinase inhibitors (EGFR-TKIs) resistance-relevant mutations in circulating tumor DNA (ctDNA) from advanced lung adenocarcinoma (ADC) patients.

resultsDetection limit of EGFR mutation in ctDNA by ddPCR was 0.04%. Taking the EGFR mutation in tumor tissue as the golden standard, the concordance of EGFR mutations detected in ctDNA was 74% (54/73). Patients with EGFR mutation in ctDNA (n = 54) superior progression-free survival (PFS, median, 12.6 vs. 6.7 months, P < 0.001) and overall survival (OS, median, 35.6 vs. 23.8 months, P = 0.028) compared to those with EGFR wild type in ctDNA (n = 19). Patients with high EGFR-mutated abundance in ctDNA (> 5.15%) showed better PFS compared to those with low EGFR mutated abundance (≤ 5.15%) (PFS, median, 15.4 vs. 11.1 months, P = 0.021). NGS results showed that 66.6% (8/12) total mutational copy number were elevated and 76.5% (26/34) mutual mutation frequency increased after disease progression.

methodsSeventy-three advanced ADC patients with tumor tissues carrying EGFR mutations and their matched pre- and post-EGFR-TKIs plasma samples were enrolled in this study. Absolute quantities of plasma EGFR mutant and wild-type alleles were measured by ddPCR. Multi-genes testing was performed using NGS in 12 patients.

conclusionsDynamic and quantitative analysis of EGFR mutation in ctDNA could guide personalized therapy for advanced ADC. NGS shows good performance in multiple genes testing especially novel and uncommon genes.

Indexed as

MutationAdenocarcinomaAdultAgedAged, 80 and overAntineoplastic AgentsBiomarkers, TumorCarcinoma, Non-Small-Cell LungCirculating Tumor DNADisease ProgressionDNA, NeoplasmDrug Resistance, NeoplasmErbB ReceptorsFemaleFollow-Up StudiesHigh-Throughput Nucleotide SequencingAntineoplastic AgentsBiomarkers, TumorCirculating Tumor DNADNA, NeoplasmEGFR protein, humanErbB Receptorscirculating tumor DNAdroplet digital PCRepidermal growth factor receptornext-generation sequencingnon-small-cell lung cancer

Identifiers

PMID26989078
PMCPMC4991494
OpenAlexW2323579548

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.