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

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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.

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Long non-coding RNAs


World Health Organization


Lower grade gliomas


Glioblastoma multiforme


Central nervous system


The Cancer Genome Atlas


Chinese Glioma Genome Atlas


Hazard ratio


Progression-free survival


Interferon gamma


Concordance index


Area under curve


Receiver operating characteristics


University of Virginia 8


L1 least absolute shrinkage and selection operator


O6-methylguanine DNA methyltransferase


Fragment per kilobase per million


Gene transfer format


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


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

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Correspondence to Anindya Dutta.

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Kiran, M., Chatrath, A., Tang, X. et al. A Prognostic Signature for Lower Grade Gliomas Based on Expression of Long Non-Coding RNAs. Mol Neurobiol 56, 4786–4798 (2019).

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