Prognostic value of a microRNA signature as a novel biomarker in patients with lower-grade gliomas

Prognostic value of a microRNA signature as a novel biomarker in patients with lower-grade gliomas MicroRNAs (miRNAs) may act as prognostic biomarkers in a variety of cancers. The aim of this study was to identify and evaluate a prognostic miRNA signature in patients with lower-grade gliomas (LGGs). miRNA expression profiles and clinical data of patients with LGGs from the Chinese Glioma Genome Atlas (CGGA; the training cohort) and The Cancer Genome Atlas (TCGA; the validation cohort) were analyzed, and the least absolute shrinkage and selection operator Cox regression model was used to identify the miRNA signature, which was combined with clinical prognostic factors to develop an individualized survival prediction model. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to reveal the biological implications of the signature. We identified a four-miRNA signature that stratified patients in the training cohort into low- or high-risk groups according to overall survival time, a finding that was verified in the validation cohort. Multivariate Cox regression analysis indicated that the four-miRNA signature was an independent prognostic biomarker, and a nomogram combining this miRNA signature with clinicopathological and molecular factors showed high prognostic accuracy for individualized survival prediction in both TCGA (C-index = 0.83) and CGGA (C-index = 0.68) cohorts. Functional annotation indicated that the major biological processes of this prognostic miRNA signature were enriched in cell cycle and DNA repair-associated biological processes. Our findings indicated that our newly discovered four-miRNA signature may be an effective independent prognostic factor for the prediction of patients with LGGs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Neuro-Oncology Springer Journals

Prognostic value of a microRNA signature as a novel biomarker in patients with lower-grade gliomas

Loading next page...
 
/lp/springer_journal/prognostic-value-of-a-microrna-signature-as-a-novel-biomarker-in-v4FNrCUMq9
Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Medicine & Public Health; Oncology; Neurology
ISSN
0167-594X
eISSN
1573-7373
D.O.I.
10.1007/s11060-017-2704-5
Publisher site
See Article on Publisher Site

Abstract

MicroRNAs (miRNAs) may act as prognostic biomarkers in a variety of cancers. The aim of this study was to identify and evaluate a prognostic miRNA signature in patients with lower-grade gliomas (LGGs). miRNA expression profiles and clinical data of patients with LGGs from the Chinese Glioma Genome Atlas (CGGA; the training cohort) and The Cancer Genome Atlas (TCGA; the validation cohort) were analyzed, and the least absolute shrinkage and selection operator Cox regression model was used to identify the miRNA signature, which was combined with clinical prognostic factors to develop an individualized survival prediction model. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to reveal the biological implications of the signature. We identified a four-miRNA signature that stratified patients in the training cohort into low- or high-risk groups according to overall survival time, a finding that was verified in the validation cohort. Multivariate Cox regression analysis indicated that the four-miRNA signature was an independent prognostic biomarker, and a nomogram combining this miRNA signature with clinicopathological and molecular factors showed high prognostic accuracy for individualized survival prediction in both TCGA (C-index = 0.83) and CGGA (C-index = 0.68) cohorts. Functional annotation indicated that the major biological processes of this prognostic miRNA signature were enriched in cell cycle and DNA repair-associated biological processes. Our findings indicated that our newly discovered four-miRNA signature may be an effective independent prognostic factor for the prediction of patients with LGGs.

Journal

Journal of Neuro-OncologySpringer Journals

Published: Dec 4, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off