A novel DNA repair-related nomogram predicts survival in low-grade gliomas.

ABSTRACT:

Aims

We aimed to create a tumor recurrent-based prediction model to predict recurrence and survival in patients with low-grade glioma.

Methods

This study enrolled 291 patients (188 in the training group and 103 in the validation group) with clinicopathological information and transcriptome sequencing data. LASSO-COX algorithm was applied to shrink predictive factor size and build a predictive recurrent signature. GO, KEGG, and GSVA analyses were performed for function annotations of the recurrent signature. The calibration curves and C-Index were assessed to evaluate the nomogram's performance.

Results

This study found that DNA repair functions of tumor cells were significantly enriched in recurrent low-grade gliomas. A predictive recurrent signature, built by the LAS

SUBMITTER: Li G 

PROVIDER: S-EPMC7816205 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature