Plasma IL13Rα2 as a novel liquid biopsy biomarker for glioblastoma

Vladimir Khristov, Darya Nesterova, Mara Trifoi, Taylor Clegg, Annika Daya, Thomas Barrett, Emily Tufano, Ganesh Shenoy, Bhavyata Pandya, Gela Beselia, Nataliya Smith, Oliver Mrowczynski, Brad Zacharia, Kristin Waite, Justin Lathia, Jill Barnholtz-Sloan, James Connor

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Purpose: Glioblastoma (GBM) is the most common and deadliest brain tumor with unrelenting and rapid disease progression. The standard of care for GBM is surgical excision followed by radiation with concurrent and adjuvant temozolomide-centered chemotherapy (TMZ). Treatment failure and resistance is the rule and despite advances in imaging technology, early detection of treatment failure or impending resistance remains a challenge. There is a dire, unmet, need in clinical practice for minimally-invasive diagnostic tools to enable timely understanding of disease progression and treatment response. Here, we aim to address this clinical need by leveraging a unique characteristic of GBM: the overexpression of the α2 variant of the IL-13 receptor in over 75% of GBM tumors. Methods: In this study we examined patients with primary GBM from Penn State and Cleveland Clinic compared to healthy controls. Results: IL13Rα2 was detectable in plasma of GBM patients using ELISA but detection could be optimized by PEG precipitation to enrich for extracellular vesicles (EVs). Patients with GBM had elevated levels of plasma IL13Rα2, which correlated to levels of this receptor in the tumor tissue. Elevated plasma levels of IL13Rα2 predicted longer overall survival (OS) (19.8 vs. 13.2 months). Similarly, detection of IL13Rα2 + cells in tumor tissue also predicted longer OS (22.1 vs. 12.2 months). Conclusion: These findings strongly suggest that expression of the IL13Rα2 receptor confer survival advantage in GBM patients, which can be determined through a minimally-invasive liquid biopsy. Detection of plasma IL13Rα2 can also be used to select GBM patients for targeted tumor therapy.

Original languageEnglish (US)
Pages (from-to)743-752
Number of pages10
JournalJournal of neuro-oncology
Volume160
Issue number3
DOIs
StatePublished - Dec 2022

All Science Journal Classification (ASJC) codes

  • Oncology
  • Neurology
  • Clinical Neurology
  • Cancer Research

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