Human endogenous retroviruses (HERVs) associated with glioblastoma risk and prognosis.

in Cancer gene therapy by Harun Mazumder, Hui-Yi Lin, Melody Baddoo, Wojciech Gałan, Diana Polania-Villanueva, Chindo Hicks, David Otohinoyi, Francesca Peruzzi, Zbigniew Madeja, Victoria P Belancio, Erik K Flemington, Krzysztof Reiss, Monika Rak

TLDR

  • The study discovers HERV expression as a potential biomarker for GBM disease progression, but it shows limitations in predicting LGG survival or progression.

Abstract

Emerging evidence suggests expression from human endogenous retrovirus (HERV) loci likely contributes to, or is a biomarker of, glioblastoma multiforme (GBM) disease progression. However, the relationship between HERV expression and GBM malignant phenotype is unclear. Applying several in silico analyses based on data from The Cancer Genome Atlas (TCGA), we derived a locus-specific HERV transcriptome for glioma that revealed 211 HERVs significantly dysregulated in the comparisons of GBM vs. normal brain (NB), GBM vs. low-grade glioma (LGG), and LGG vs. NB. Our analysis supported development of a unique HERV scoring algorithm that segregated GBM, LGG, and NB. Interestingly, lower HERV scores showed correlation with lower survival in GBM. However, HERV scores were less robust in predicting LGG survival or LGG progression to GBM. Functional prediction analysis linked the 211 HERV loci with 18 voltage-gated potassium channel genes. The functional link between dysregulated HERVs and specific potassium channel genes may contribute to better understanding of GBM pathogenesis, disease progression, and possibly drug resistance.

Overview

  • The study aims to investigate the relationship between human endogenous retrovirus (HERV) expression and glioblastoma multiforme (GBM) disease progression.
  • The study uses in silico analyses on data from The Cancer Genome Atlas (TCGA) to derive a locus-specific HERV transcriptome for glioma and develop a HERV scoring algorithm.
  • The primary objective of the study is to understand the contributory role of HERV expression in GBM malignant phenotype and potentially identify biomarkers for disease progression.

Comparative Analysis & Findings

  • A total of 211 HERVs were significantly dysregulated in the comparisons of GBM vs. normal brain (NB), GBM vs. low-grade glioma (LGG), and LGG vs. NB.
  • The HERV scoring algorithm successfully segregated GBM, LGG, and NB with lower HERV scores showing correlation with lower survival in GBM.
  • However, HERV scores were less robust in predicting LGG survival or LGG progression to GBM, indicating the algorithm's limitations in these contexts

Implications and Future Directions

  • The study's findings suggest that HERV expression may serve as a biomarker for GBM disease progression, potentially informing treatment strategies.
  • Future studies should investigate the functional roles of the 211 HERV loci linked to voltage-gated potassium channel genes in GBM pathogenesis and disease progression.
  • The study's results also highlight the need for further research on the predictive power of HERV scores in LGG and the development of more robust diagnostic algorithms
Read Full Article