Integrative analysis of therapy resistance and transcriptomic profiling data in glioblastoma cells identifies

Leon Emanuel Schnöller1, Valerie Albrecht1, Nikko Brix1

  • 1Department of Radiation Oncology, University Hospital, LMU München, Marchioninistrasse 15, 81377, Munich, Germany.

Abstract

Insights

Identifying regulators of glioblastoma (GBM) treatment resistance is key. This study found that ATR and ATM expression correlates with radio/chemoresistance, offering potential targets for combined therapies.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Inherent resistance to radio/chemotherapy contributes to glioblastoma (GBM) recurrence and poor prognosis.
  • Identifying resistance regulators is crucial for developing effective treatments and improving patient outcomes.

Purpose of the Study:

  • To integrate treatment resistance data with DNA damage response (DDR) regulator expression in GBM cell lines.
  • To identify novel biomarkers and therapeutic vulnerabilities for overcoming inherent therapy resistance in GBM.

Main Methods:

  • Performed integrative analysis of treatment resistance and DDR gene expression in GBM cell lines.
  • Assessed radio/temozolomide resistance using clonogenic survival assays and qRT-PCR for 38 DDR regulators.
  • Validated top candidate regulators (e.g., ATR, LIG4, ATM) via pharmacological inhibition and DNA repair assays.

Main Results:

  • Radiotherapy resistance correlated with expression of PARP1, NBN, BLM, ATR, and LIG4.
  • ATR inhibition (AZD-6738) significantly radiosensitized GBM cells.
  • Temozolomide resistance correlated with MGMT and ATM expression; ATM inhibition showed slight sensitization in MGMT-low cells.

Conclusions:

  • Developed a systematic approach to identify GBM therapy resistance markers and vulnerabilities by integrating survival and gene expression data.
  • Proof-of-concept for using this integrative strategy to find potential therapeutic targets like ATR.
  • The approach is adaptable for other cancers and data types, with potential for upscaling.