Evidence map›Paper›PMID 31583841›Full record

ArticleThoracic cancer2019

Prognostic significance of IMMT expression in surgically-resected lung adenocarcinoma.

Yasuhiro Hiyoshi, Yuichi Sato, Masaaki Ichinoe, Ryo Nagashio, Daisuke Hagiuda, Makoto Kobayashi, Seiichiro Kusuhara, Satoshi Igawa, Kazu Shiomi, Naoki Goshima and 5 more

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2019. 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
0.3field-weighted citation impact, top 40% 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, 10 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

15 authors at 2 institutions in 1 country.

Yasuhiro HiyoshiDepartment of Respiratory Medicine, School of Medicine, Kitasato University, Sagamihara, Japan.
Yuichi SatoApplied Tumor Pathology, Graduate School of Medical Sciences, Kitasato University, Sagamihara, Japan.ORCID 0000-0002-4441-0306
Masaaki IchinoeDepartment of Pathology, School of Medicine, Kitasato University, Sagamihara, Japan.
Ryo NagashioApplied Tumor Pathology, Graduate School of Medical Sciences, Kitasato University, Sagamihara, Japan.
Daisuke HagiudaApplied Tumor Pathology, Graduate School of Medical Sciences, Kitasato University, Sagamihara, Japan.
Makoto KobayashiApplied Tumor Pathology, Graduate School of Medical Sciences, Kitasato University, Sagamihara, Japan.
Seiichiro KusuharaDepartment of Respiratory Medicine, School of Medicine, Kitasato University, Sagamihara, Japan.
Satoshi IgawaDepartment of Respiratory Medicine, School of Medicine, Kitasato University, Sagamihara, Japan.ORCID 0000-0002-7527-8766
Kazu ShiomiDepartment of Thoracic and Cardiovascular Surgery, School of Medicine, Kitasato University, Sagamihara, Japan.
Naoki GoshimaNational Institute of Advanced Industrial Science and Technology Tokyo Bay Area Center, Koto-ku, Japan.
Yoshiki MurakumoDepartment of Pathology, School of Medicine, Kitasato University, Sagamihara, Japan.
Makoto SaegusaDepartment of Pathology, School of Medicine, Kitasato University, Sagamihara, Japan.
Yukitoshi SatohDepartment of Thoracic and Cardiovascular Surgery, School of Medicine, Kitasato University, Sagamihara, Japan.
Noriyuki MasudaDepartment of Respiratory Medicine, School of Medicine, Kitasato University, Sagamihara, Japan.
Katsuhiko NaokiDepartment of Respiratory Medicine, School of Medicine, Kitasato University, Sagamihara, Japan.
Kitasato University · JPNational Institute of Advanced Industrial Science and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMitochondrial dysfunction contributes to many types of human disorders and cancer progression. Inner membrane mitochondrial protein (IMMT) plays an important role in the maintenance of mitochondrial structure and function. The aims of this study were to examine IMMT expression in lung adenocarcinoma and evaluate its correlation with clinicopathological parameters and patient prognosis.

methodsIMMT expression was immunohistochemically studied in 176 consecutive lung adenocarcinoma resection tissues, and its correlations with clinicopathological parameters were evaluated. Kaplan-Meier survival analysis and Cox-proportional hazards models were used to estimate the effect of IMMT expression on survival.

resultsHigh-IMMT expression was detected in 84 of 176 (47.7%) lung adenocarcinomas. Levels were significantly correlated with advanced disease stage (stage II and III; P = 0.024), larger tumor size (>3 cm; P = 0.002), intratumoral vascular invasion (P < 0.001), and poorer adenocarcinoma patient prognosis (P = 0.002). Based on 176 patients with adenocarcinoma, multivariate analysis revealed that IMMT expression was an independent predictor of poorer survival (HR, 1.99; 95% confidence interval [CI], 1.06-3.74; P = 0.031). Further, treating A549 cells derived from lung adenocarcinoma, with IMMT siRNA resulted in significantly decreased proliferation.

conclusionHere, we first demonstrated that high-IMMT expression is related to some clinicopathological parameters, and that its expression is an independent prognostic predictor of poorer survival in patients with lung adenocarcinoma; further studies are required to clarify the biological function of IMMT in lung adenocarcinoma. However, results suggest that this protein could be a novel prognostic indicator and therapeutic target.

Indexed as

Up-RegulationAdenocarcinoma of LungBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleMitochondrial ProteinsMuscle ProteinsNeoplasm StagingPrognosisSurvival AnalysisBiomarkers, TumorIMMT protein, humanMitochondrial ProteinsMuscle ProteinsIMMTimmunohistochemistrylung adenocarcinomaprognostic markerTCGA database

Identifiers

PMID31583841
PMCPMC6825906
OpenAlexW2979234203

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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.