Evidence map›Paper›PMID 31807880›Full record

ArticleCancer immunology, immunotherapy : CII2020

Tumor mutation burden and immunological, genomic, and clinicopathological factors as biomarkers for checkpoint inhibitor treatment of patients with non-small-cell lung cancer.

Yuki Ozaki, Satoshi Muto, Hironori Takagi, Masayuki Watanabe, Takuya Inoue, Mitsuro Fukuhara, Takumi Yamaura, Naoyuki Okabe, Yuki Matsumura, Takeo Hasegawa and 9 more

Open access · bronzeAbstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
3.6field-weighted citation impact, top 6% 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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 43 citations in OpenAlex.

  1. Pooled it
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  13. Bioengineered · 2022
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  15. Genomic landscape and prognosis of patients withAnnals of translational medicine · 2022
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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

19 authors at 1 institution in 1 country.

Yuki OzakiDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.ORCID http://orcid.org/0000-0002-2143-3169
Satoshi MutoDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Hironori TakagiDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Masayuki WatanabeDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Takuya InoueDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Mitsuro FukuharaDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Takumi YamauraDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Naoyuki OkabeDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Yuki MatsumuraDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Takeo HasegawaDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Jun OhsugiDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Mika HoshinoDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Yutaka ShioDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan.
Daisuke TanakaTranslational Research Center, Fukushima Medical University, Fukushima, Japan.
Hideaki NanamiyaTranslational Research Center, Fukushima Medical University, Fukushima, Japan.
Jun-Ichi ImaiTranslational Research Center, Fukushima Medical University, Fukushima, Japan.
Takao IsogaiTranslational Research Center, Fukushima Medical University, Fukushima, Japan.
Shinya WatanabeTranslational Research Center, Fukushima Medical University, Fukushima, Japan.
Hiroyuki SuzukiDepartment of Chest Surgery, School of Medicine, Fukushima Medical University, 1 Hikarigaoka, Fukushima, 960-1295, Japan. hiro@fmu.ac.jp.
Fukushima Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer treatment using immune checkpoint inhibitors is widely used, although biomarkers predictive of response are not well established. However, both the expressions of programmed cell death ligand 1 (PD-L1) and the tumor mutation burden (TMB) hold promise as such biomarkers for immune checkpoint inhibitors; however, its characteristics and clinical and immunological impacts have not been fully analyzed. We, therefore, evaluated the clinical and immunological parameters related to TMB to identify potential new biomarkers. We enrolled 92 patients with non-small-cell lung cancer who underwent surgery at Fukushima Medical University Hospital from 2013 to 2016. TMB of individual tumors was calculated by whole-exome sequencing analysis. Major cancer-related gene mutations were evaluated using panel sequencing. Expression of PD-L1 and abundance of tumor-infiltrating lymphocytes were evaluated by immunohistochemistry using surgical samples. The median TMB value was 60. TMB was significantly higher in men, current or former smokers, and in patients with squamous cell carcinoma, tumor size ≥ 2.8 cm, wild-type EGFR, TP53 gene mutation-positive status, and cyclin-dependent kinase-inhibitor gene 2A mutation-positive status. According to multivariate analysis, TMB was significantly associated with EGFR gene mutation-negative status (p = 0.0111) and TP53 gene mutation-positive status (p = 0.0425). If TMB is identified as a robust biomarker for immune checkpoint inhibitor administration, analysis of TP53 and EGFR mutations may provide a relatively rapid and easy proxy for predicting TMB.

Indexed as

PneumonectomyAgedAntineoplastic Agents, ImmunologicalB7-H1 AntigenBiomarkers, TumorCarcinoma, Non-Small-Cell LungChemotherapy, AdjuvantErbB ReceptorsExome SequencingFemaleGenomicsHumansLungLung NeoplasmsLymphocytes, Tumor-InfiltratingMaleAntineoplastic Agents, ImmunologicalB7-H1 AntigenBiomarkers, TumorCD274 protein, humanEGFR protein, humanErbB ReceptorsTP53 protein, humanTumor Suppressor Protein p53BiomarkerImmune checkpoint inhibitorImmunologicalNon-small-cell lung cancerTumor mutation burden

Identifiers

PMID31807880
PMCPMC11027844
OpenAlexW2991861115

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.