2. Academic Validation
  3. Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma

Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma

  • Nat Commun. 2024 Nov 21;15(1):10089. doi: 10.1038/s41467-024-54138-9.
Elizabeth G Fernandez 1,  Wilson X Mai 1,  Kai Song 2,  Nicholas A Bayley 1,  Jiyoon Kim 3,  Henan Zhu 1,  Marissa Pioso 1,  Pauline Young 1,  Cassidy L Andrasz 1 4,  Dimitri Cadet 1,  Linda M Liau 5 6,  Gang Li 3,  William H Yong 7,  Fausto J Rodriguez 7,  Scott J Dixon 8,  Andrew J Souers 9,  Jingyi Jessica Li 3 5 4 10 11,  Thomas G Graeber 1 5 12 13,  Timothy F Cloughesy 1 5 14,  David A Nathanson 15 16
Affiliations

Affiliations

  • 1 Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • 2 Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
  • 3 Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, Los Angeles, California, USA.
  • 4 Department of Human Genetics, University of California, Los Angeles, CA, 90095-7088, USA.
  • 5 Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA.
  • 6 Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
  • 7 Department of Pathology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
  • 8 Department of Biology, Stanford University, Stanford, CA, 94305, USA.
  • 9 AbbVie, Inc., 1 North Waukegan Road, North Chicago, IL, 60064, USA.
  • 10 Department of Computational Medicine, University of California, Los Angeles, CA, 90095-1766, USA.
  • 11 Department of Statistics and Data Science, University of California, Los Angeles, CA, 90095-1554, USA.
  • 12 UCLA Metabolomics Center, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • 13 Crump Institute for Molecular Imaging, University of California Los Angeles, Los Angeles, CA, 90095, USA.
  • 14 Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
  • 15 Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA. dnathanson@mednet.ucla.edu.
  • 16 Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA. dnathanson@mednet.ucla.edu.
PMID: 39572533 DOI: 10.1038/s41467-024-54138-9
Abstract

Genomic profiling often fails to predict therapeutic outcomes in Cancer. This failure is, in part, due to a myriad of genetic alterations and the plasticity of Cancer signaling networks. Functional profiling, which ascertains signaling dynamics, is an alternative method to anticipate drug responses. It is unclear whether integrating genomic and functional features of solid tumours can provide unique insight into therapeutic vulnerabilities. We perform combined molecular and functional characterization, via BH3 profiling of the intrinsic apoptotic machinery, in glioma patient samples and derivative models. We identify that standard-of-care therapy rapidly rewires apoptotic signaling in a genotype-specific manner, revealing targetable apoptotic vulnerabilities in gliomas containing specific molecular features (e.g., TP53 WT). However, integration of BH3 profiling reveals high mitochondrial priming is also required to induce glioma Apoptosis. Accordingly, a machine-learning approach identifies a composite molecular and functional signature that best predicts responses of diverse intracranial glioma models to standard-of-care therapies combined with ABBV-155, a clinical drug targeting intrinsic Apoptosis. This work demonstrates how complementary functional and molecular data can robustly predict therapy-induced cell death.

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