Identifying bifurcated paths with differential function impact in glioblastomas evolution

Int J Cancer. 2020 Dec 1;147(11):3139-3151. doi: 10.1002/ijc.33276. Epub 2020 Sep 12.

Abstract

The evolutionary dynamics of human cancers has been investigated popularly and several bifurcated paths in cancer evolutionary trajectories are revealed to be with differential outcomes and phenotypes. However, whether such bifurcated paths exist in glioblastoma (GBM) remains unclear. In 385 GBM samples, through determining the clonal status of cancer driver events and inferring their temporal order, we constructed a temporal map of evolutionary trajectories at the patient population level. By investigating the differential impact on clinical outcome, we identified four key bifurcated paths, namely, "chromosome 10 copy number loss (ie, 10 loss) → chromosome 19 copy number gain (ie, 19 gain): 10 loss → 13q loss"; "10 loss → 19 gain: 10 loss → 15q loss"; "10 loss → 19 gain: 10 loss → 6q loss" and "10 loss → 19 gain: 10 loss → 16q loss". They formed a core multibranches path, with 10 loss being regarded as the common earliest event followed by 19 gain and four other departure events (13q loss, 15q loss, 6q loss and 16q loss), which may account for their difference in genome instability and patient survival time. Compared to "10 loss → 19 gain", the patients with "10 loss → 13q loss" had higher telomerase activity. Notably, there were obvious discrepancies in immune activity and immune cell infiltration level between patients with "10 loss → 13q/16q loss" and "10 loss → 19 gain", highlighting the bifurcated paths' effect on tumor immune microenvironment. In summary, our study identifies four key bifurcated paths in GBM for the first time, suggesting the feasibility of patient stratification and prognosis prediction based on key bifurcated paths.

Keywords: GBM; bifurcated path; copy number alteration; differential function impact; evolutionary trajectories.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain Neoplasms / genetics*
  • Chromosomes, Human / genetics*
  • Clonal Evolution
  • Gene Dosage
  • Gene Regulatory Networks*
  • Glioblastoma / genetics*
  • Humans
  • Male
  • Mutation
  • Prognosis
  • Survival Analysis
  • Tumor Microenvironment