Detection of brain cancer using genome-wide cell-free DNA fragmentomes.

in Cancer discovery by Dimitrios Mathios, Noushin Niknafs, Akshaya V Annapragada, Ernest J Bobeff, Elaine J Chiao, Kavya Boyapati, Keerti Boyapati, Sarah Short, Adrianna L Bartolomucci, Stephen Cristiano, Shashikant Koul, Nicholas A Vulpescu, Leonardo Ferreira, Jamie E Medina, Daniel C Bruhm, Vilmos Adleff, Małgorzata Podstawka, Patrycja Stanisławska, Chul-Kee Park, Judy Huang, Gary L Gallia, Henry Brem, Debraj Mukherjee, Justin M Caplan, Jon Weingart, Christopher M Jackson, Michael Lim, Jillian Phallen, Robert B Scharpf, Victor E Velculescu

TLDR

  • A blood-based assay using cell-free DNA fragmentomes was developed to detect brain cancer with high accuracy, potentially accelerating diagnosis and improving patient outcomes.
  • The study found that cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation.
  • Results were validated in an independent prospectively collected cohort, demonstrating the robustness of the blood-based assay.

Abstract

Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer diagnosis. In this study, we analyzed genome-wide cell-free (cfDNA) fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of individuals with (n=148) or without (n=357) brain cancer. Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas (AUC=0.90, 95% CI: 0.87-0.93) and these results were validated in an independent prospectively collected cohort. cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation. These analyses reveal the properties of cfDNA in patients with brain cancer and open new avenues for noninvasive detection of these individuals.

Overview

  • This study aims to develop a blood-based assay for the detection of brain cancers, investigating the properties of cell-free DNA (cfDNA) fragmentomes in patients with brain cancer.
  • The study analyzed genome-wide cfDNA fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of 148 patients with brain cancer and 357 patients without brain cancer.
  • Machine learning analyses of cfDNA fragmentome features detected brain cancer with an area under the receiver operating characteristic curve (AUC) of 0.90 and 95% confidence interval (CI) of 0.87-0.93.

Comparative Analysis & Findings

  • Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas, with high accuracy and a large area under the receiver operating characteristic curve (AUC).
  • The study found that cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation.
  • Results were validated in an independent prospectively collected cohort, demonstrating the robustness of the blood-based assay.

Implications and Future Directions

  • This study opens new avenues for non-invasive detection of patients with brain cancer, potentially accelerating diagnosis and improving patient outcomes.
  • Further research is needed to refine the blood-based assay and extend its application to different types of brain cancers.
  • The study's findings highlight the potential of cfDNA fragmentomes as a diagnostic biomarker for brain cancer and other diseases, and may pave the way for the development of liquid biopsies.
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