Evidence map›Paper›PMID 27437769›Full record

ArticleOncotarget2016

Molecular gene signature and prognosis of non-small cell lung cancer.

Poyin Huang, Chiou-Ling Cheng, Ya-Hsuan Chang, Chia-Hsin Liu, Yi-Chiung Hsu, Jin-Shing Chen, Gee-Chen Chang, Bing-Ching Ho, Kang-Yi Su, Hsuan-Yu Chen and 1 more

Abstract 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 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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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.

Poyin HuangDepartment of Neurology, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.
Chiou-Ling ChengDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Ya-Hsuan ChangInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Chia-Hsin LiuInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Yi-Chiung HsuInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Jin-Shing ChenDepartment of Traumatology, National Taiwan University Hospital, Taipei, Taiwan.
Gee-Chen ChangFaculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan.
Bing-Ching HoDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Kang-Yi SuDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.
Hsuan-Yu ChenInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Sung-Liang YuDepartment of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current staging system for non-small cell lung cancer (NSCLC) is inadequate for predicting outcome. Risk score, a linear combination of the values for the expression of each gene multiplied by a weighting value which was estimated from univariate Cox proportional hazard regression, can be useful. The aim of this study is to analyze survival-related genes with TaqMan Low-Density Array (TLDA) and risk score to explore gene-signature in lung cancer. A total of 96 NSCLC specimens were collected and randomly assigned to a training (n = 48) or a testing cohort (n = 48). A panel of 219 survival-associated genes from published studies were used to develop a 6-gene risk score. The risk score was used to classify patients into high or low-risk signature and survival analysis was performed. Cox models were used to evaluate independent prognostic factors. A 6-gene signature including ABCC4, ADRBK2, KLHL23, PDS5A, UHRF1 and ZNF551 was identified. The risk score in both training (HR = 3.14, 95% CI: 1.14-8.67, p = 0.03) and testing cohorts (HR = 5.42, 95% CI: 1.56-18.84, p = 0.01) was the independent prognostic factor. In merged public datasets including GSE50081, GSE30219, GSE31210, GSE19188, GSE37745, GSE3141 and GSE31908, the risk score (HR = 1.50, 95% CI: 1.25-1.80, p < 0.0001) was also the independent prognostic factor. The risk score generated from expression of a small number of genes did perform well in predicting overall survival and may be useful in routine clinical practice.

Indexed as

AdultAgedCarcinoma, Non-Small-Cell LungFemaleGene Expression ProfilingHumansLung NeoplasmsMaleMiddle AgedPrognosisProportional Hazards ModelsRisk FactorsTranscriptomegene signaturenon-small cell lung cancerprognosisrisk scoreTaqMan Low-Density Array

Identifiers

PMID27437769
PMCPMC5239522

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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.