Evidence map›Paper›PMID 30012197›Full record

ArticleBiology direct2018

Accumulation of potential driver genes with genomic alterations predicts survival of high-risk neuroblastoma patients.

Chen Suo, Wenjiang Deng, Trung Nghia Vu, Mingrui Li, Leming Shi, Yudi Pawitan

Open access · goldAbstract read
In one paragraph

Article in Biology direct, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.9field-weighted citation impact, top 10% 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

19 citing papers in PubMed, 25 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

6 authors at 2 institutions in 2 countries.

Chen SuoDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai, China.
Wenjiang DengDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Box 281, Nobels vag 12A, Karolinska Institutet, 171 77, Stockholm, PO, Sweden.
Trung Nghia VuDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Box 281, Nobels vag 12A, Karolinska Institutet, 171 77, Stockholm, PO, Sweden.
Mingrui LiState Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Leming ShiState Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
Yudi PawitanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Box 281, Nobels vag 12A, Karolinska Institutet, 171 77, Stockholm, PO, Sweden. yudi.pawitan@ki.se.ORCID 0000-0003-0324-7052
Fudan University · CNKarolinska Institutet · SE

Funding

China Postdoctoral Science Foundation NO.2016M591600 and NO.2017T100267Chinese Scholarship Council NO.201600160085National Key Research and Development Program of China 2017YFC0907000National Natural Science Foundation of China NO.31600673
6 · The paper itself

Abstract

backgroundNeuroblastoma is the most common pediatric malignancy with heterogeneous clinical behaviors, ranging from spontaneous regression to aggressive progression. Many studies have identified aberrations related to the pathogenesis and prognosis, broadly classifying neuroblastoma patients into high- and low-risk groups, but predicting tumor progression and clinical management of high-risk patients remains a big challenge.

resultsWe integrate gene-level expression, array-based comparative genomic hybridization and functional gene-interaction network of 145 neuroblastoma patients to detect potential driver genes. The drivers are summarized into a driver-gene score (DGscore) for each patient, and we then validate its clinical relevance in terms of association with patient survival. Focusing on a subset of 48 clinically defined high-risk patients, we identify 193 recurrent regions of copy number alterations (CNAs), resulting in 274 altered genes whose copy-number gain or loss have parallel impact on the gene expression. Using a network enrichment analysis, we detect four common driver genes, ERCC6, HECTD2, KIAA1279, EMX2, and 66 patient-specific driver genes. Patients with high DGscore, thus carrying more copy-number-altered genes with correspondingly up- or down-regulated expression and functional implications, have worse survival than those with low DGscore (P = 0.006). Furthermore, Cox proportional-hazards regression analysis shows that, adjusted for age, tumor stage and MYCN amplification, DGscore is the only significant prognostic factor for high-risk neuroblastoma patients (P = 0.008).

conclusionsIntegration of genomic copy number alteration, expression and functional interaction-network data reveals clinically relevant and prognostic putative driver genes in high-risk neuroblastoma patients. The identified putative drivers are potential drug targets for individualized therapy. REVIEWERS: This article was reviewed by Armand Valsesia, Susmita Datta and Aleksandra Gruca.

Indexed as

AnimalsComparative Genomic HybridizationDNA Copy Number VariationsGene DosageGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNeuroblastomaProportional Hazards ModelsDriver genesHigh-riskIntegrative analysisNeuroblastomaSurvival

Identifiers

PMID30012197
PMCPMC6048860
OpenAlexW2884889531

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.