Dissecting the tumor microenvironment of epigenetically driven gliomas: Opportunities for single-cell and spatial

Jonathan H Sussman1,2, Jason Xu1,2, Nduka Amankulor3

  • 1Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Neuro-Oncology Advances
|September 14, 2023
PubMed

Insights

Single-cell multiomics reveals complex intra-tumor heterogeneity in epigenetically driven gliomas, offering new avenues for personalized diagnostics and potent therapeutic strategies against these incurable brain neoplasms.

Area of Science:

  • Neuro-oncology
  • Genomics
  • Immunology

Background:

  • Malignant gliomas are aggressive brain tumors with poor outcomes and limited treatment progress.
  • Glioma research has faced challenges due to significant genomic, transcriptomic, and immunologic heterogeneity.
  • Single-cell and spatial omics technologies offer detailed characterization of tumor heterogeneity.

Purpose of the Study:

  • To review the application of single-cell multiomics in epigenetically driven gliomas.
  • To discuss future multiomic strategies for understanding glioma biology.
  • To explore advancements in personalized diagnostics and therapeutics for gliomas.

Main Methods:

  • Review of existing single-cell multiomic datasets for epigenetically driven gliomas.
  • Discussion of novel multiomic strategies and their potential applications.
  • Integration of multiomic data with digital pathology for enhanced diagnostics.

Main Results:

  • Single-cell multiomics enables granular annotation of transcriptional, epigenetic, and microenvironmental states in gliomas.
  • Epigenetically driven gliomas exhibit distinct transcriptional programs and immune microenvironments.
  • These technologies are crucial for disentangling intra-tumor features like differentiation and cell-cell interactions.

Conclusions:

  • Single-cell multiomics is a powerful tool for dissecting glioma complexity, particularly in epigenetically driven subtypes.
  • Future multiomic approaches hold promise for developing effective therapies and improving patient outcomes.
  • Enhanced diagnostics through digital pathology can leverage multiomic insights for personalized glioma treatment.