Evidence map›Paper›PMID 31584970›Full record

ArticlePloS one2019

Whole genome sequencing to identify predictive markers for the risk of drug-induced interstitial lung disease.

Chihiro Udagawa, Hidehito Horinouchi, Kouya Shiraishi, Takashi Kohno, Takuji Okusaka, Hideki Ueno, Kenji Tamura, Yuichiro Ohe, Hitoshi Zembutsu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Chihiro UdagawaDivision of Genetics, National Cancer Center Research Institute, Tokyo, Japan.ORCID 0000-0002-3430-2555
Hidehito HorinouchiDepartment of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan.
Kouya ShiraishiDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Takashi KohnoDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Takuji OkusakaDepartment of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital, Tokyo, Japan.
Hideki UenoDepartment of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital, Tokyo, Japan.
Kenji TamuraDepartment of Breast and Medical Oncology, National Cancer Center Hospital, Tokyo, Japan.
Yuichiro OheDepartment of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan.
Hitoshi ZembutsuDivision of Genetics, National Cancer Center Research Institute, Tokyo, Japan.ORCID 0000-0002-1674-1968
National Cancer Centre Japan · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-induced interstitial lung disease (DIILD) is a serious side effect of chemotherapy in cancer patients with an extremely high mortality rate. In this study, to identify genetic variants with greater risk of DIILD, we carried out whole genome sequencing (WGS) of germline DNA samples from 26 patients who developed DIILD, and conducted a case-control association study between these 26 cases and general Japanese population controls registered in the integrative Japanese Genome Variation Database (iJGVD) as a screening study. The associations of 42 single nucleotide variants (SNVs) showing P < 0.0001 were further validated using an independent cohort of 18 DIILD cases as a replication study. A further combined analysis of the screening and replication studies showed a possible association of two SNVs, rs35198919 in intron 1 of the chromosome 22 open reading frame 34 (C22orf34) and rs12625311 in intron 1 of the teashirt zinc finger homeobox 2 (TSHZ2), with DIILD (Pcombined = 1.87 × 10-5 and 5.16 × 10-5, respectively). Furthermore, in a subgroup analysis of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI)-induced interstitial lung disease (ILD), we observed seven candidate SNVs that were possibly associated with ILD (P < 0.00001). This is the first study to identify genetic markers for the risk of DIILD using WGS. Collectively, our novel findings indicate that these SNVs may be applicable for predicting the risk of DIILD in patients receiving chemotherapy.

Indexed as

BiomarkersGenetic Predisposition to DiseaseAdultAgedAged, 80 and overAntineoplastic Combined Chemotherapy ProtocolsCase-Control StudiesFemaleHumansLung Diseases, InterstitialMaleMiddle AgedMutationNeoplasmsPolymorphism, Single NucleotidePrognosisBiomarkersProtein Kinase Inhibitors

Identifiers

PMID31584970
PMCPMC6777826
OpenAlexW2977360100

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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.