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Hypoxic Roadmap of Glioblastoma-Learning about Directions and Distances in the Brain Tumor Environment. | LitMetric

Hypoxic Roadmap of Glioblastoma-Learning about Directions and Distances in the Brain Tumor Environment.

Cancers (Basel)

Department of Neurosurgery, Harvey Cushing Neuro-Oncology Laboratories, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.

Published: May 2020

AI Article Synopsis

  • Glioblastoma, a malignant brain tumor, is challenging to treat and study due to its heterogeneity, meaning each tumor contains diverse cancer cells that adapt to their environment.
  • Researchers created a hypoxic map by analyzing gene expression data to understand how tumor cells respond to low oxygen levels, rooted in different anatomical regions of the tumor.
  • The study found that genes associated with autophagy and immune response in hypoxic regions could predict patient survival outcomes, revealing that adaptation to metabolic stress and immune evasion worsens patient prognosis.

Article Abstract

Malignant brain tumor-glioblastoma is not only difficult to treat but also hard to study and model. One of the reasons for these is their heterogeneity, i.e., individual tumors consisting of cancer cells that are unlike each other. Such diverse cells can thrive due to the simultaneous co-evolution of anatomic niches and adaption into zones with distorted homeostasis of oxygen. It dampens cytotoxic and immune therapies as the response depends on the cellular composition and its adaptation to hypoxia. We explored what transcriptome reposition strategies are used by cells in the different areas of the tumor. We created the hypoxic map by differential expression analysis between hypoxic and cellular features using RNA sequencing data cross-referenced with the tumor's anatomic features (Ivy Glioblastoma Atlas Project). The molecular functions of genes differentially expressed in the hypoxic regions were analyzed by a systematic review of the gene ontology analysis. To put a hypoxic niche signature into a clinical context, we associated the model with patients' survival datasets (The Cancer Genome Atlas). The most unique class of genes in the hypoxic area of the tumor was associated with the process of autophagy. Both hypoxic and cellular anatomic features were enriched in immune response genes whose, along with autophagy cluster genes, had the power to predict glioblastoma patient survival. Our analysis revealed that transcriptome responsive to hypoxia predicted worse patients' outcomes by driving tumor cell adaptation to metabolic stress and immune escape.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281616PMC
http://dx.doi.org/10.3390/cancers12051213DOI Listing

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