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Related Experiment Video

Updated: Aug 26, 2025

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

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Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma.

Nishika Karbhari1, Rachael Barney2, Scott Palisoul2

  • 1Department of Neurology, Dartmouth-Hitchcock Medical Center.

Journal of Visualized Experiments : Jove
|October 3, 2022
PubMed
Summary
This summary is machine-generated.

Digital spatial profiling (DSP) enables precise quantification of protein expression in specific tissue regions. This method aids in understanding glioma heterogeneity and tumor spread by analyzing protein distribution in distinct areas.

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Area of Science:

  • Oncology
  • Proteomics
  • Biotechnology

Background:

  • Diffusely infiltrating gliomas exhibit high morbidity and mortality due to their infiltrative nature and proteomic complexity.
  • Tumor progression is linked to dysregulated proteins affecting cellular stability and microenvironment integrity.
  • Existing glioma analyses lack spatial stratification of proteomic data, limiting understanding of tumor heterogeneity.

Purpose of the Study:

  • To investigate the spatial distribution of proteins and immune cells in gliomas.
  • To leverage Digital Spatial Profiling (DSP) for multilayered proteomic analysis of tumor regions.
  • To gain insights into glioma proliferation and propagation mechanisms through spatial proteomic stratification.

Main Methods:

  • Construction of tissue microarrays from archived glioblastoma core biopsies.
  • Incubation of tissue samples with UV-photocleavable DNA oligonucleotide-conjugated antibodies targeting proteins of interest.
  • Quantification of protein expression within user-defined regions of interest (ROIs) using DSP technology.

Main Results:

  • DSP allows for efficient quantification of protein expression within specified spatial regions of tissue specimens.
  • The method enables differential expression analysis of multiple proteins across distinct tumor areas.
  • Spatial stratification of proteomic data provides valuable insights into glioma heterogeneity.

Conclusions:

  • Digital Spatial Profiling is a powerful tool for multilayered proteomic analysis of complex tissues like gliomas.
  • Understanding spatial protein distribution is crucial for deciphering glioma proliferation and propagation mechanisms.
  • DSP facilitates customized spatial analysis of proteomic data, advancing glioma research.