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Molecular Neurobiology

, Volume 56, Issue 7, pp 4786–4798 | Cite as

A Prognostic Signature for Lower Grade Gliomas Based on Expression of Long Non-Coding RNAs

  • Manjari Kiran
  • Ajay Chatrath
  • Xiwei Tang
  • Daniel Macrae Keenan
  • Anindya DuttaEmail author
Article

Abstract

Diffuse low-grade and intermediate-grade gliomas (together known as lower grade gliomas, WHO grade II and III) develop in the supporting glial cells of brain and are the most common types of primary brain tumor. Despite a better prognosis for lower grade gliomas, 70% of patients undergo high-grade transformation within 10 years, stressing the importance of better prognosis. Long non-coding RNAs (lncRNAs) are gaining attention as potential biomarkers for cancer diagnosis and prognosis. We have developed a computational model, UVA8, for prognosis of lower grade gliomas by combining lncRNA expression, Cox regression, and L1-LASSO penalization. The model was trained on a subset of patients in TCGA. Patients in TCGA, as well as a completely independent validation set (CGGA) could be dichotomized based on their risk score, a linear combination of the level of each prognostic lncRNA weighted by its multivariable Cox regression coefficient. UVA8 is an independent predictor of survival and outperforms standard epidemiological approaches and previous published lncRNA-based predictors as a survival model. Guilt-by-association studies of the lncRNAs in UVA8, all of which predict good outcome, suggest they have a role in suppressing interferon-stimulated response and epithelial to mesenchymal transition. The expression levels of eight lncRNAs can be combined to produce a prognostic tool applicable to diverse populations of glioma patients. The 8 lncRNA (UVA8) based score can identify grade II and grade III glioma patients with poor outcome, and thus identify patients who should receive more aggressive therapy at the outset.

Keywords

Long non-coding RNAs Gliomas Gene expression profiling Prognosis 

Abbreviations

lncRNA

Long non-coding RNAs

WHO

World Health Organization

LGG

Lower grade gliomas

GBM

Glioblastoma multiforme

CNS

Central nervous system

TCGA

The Cancer Genome Atlas

CGGA

Chinese Glioma Genome Atlas

HR

Hazard ratio

PFS

Progression-free survival

IFNG

Interferon gamma

Cindex

Concordance index

AUC

Area under curve

ROC

Receiver operating characteristics

UVA8

University of Virginia 8

L1-LASSO

L1 least absolute shrinkage and selection operator

MGMT

O6-methylguanine DNA methyltransferase

FPKM

Fragment per kilobase per million

GTF

Gene transfer format

Notes

Acknowledgments

We thank Dr. Stefan Bekiranov, Dr. William Pearson, and Dutta lab members for helpful discussions. M.K. is supported by a DOD award PC151085.

Funding Information

The work was supported by a V foundation award D2018-002 and R01 AR067712 from NIAMS.

Supplementary material

12035_2018_1416_MOESM1_ESM.docx (4.9 mb)
ESM 1 (DOCX 5047 kb)

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Biochemistry and Molecular GeneticsUniversity of Virginia School of MedicineCharlottesvilleUSA
  2. 2.Department of StatisticsUniversity of VirginiaCharlottesvilleUSA

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