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.

Highlights

  • IntroductionMalignant tumors of the brain, such as glioblastomas, are among the most feared ones

  • Malignant tumors of the brain, such as glioblastomas, are among the most feared ones.They progress fast, killing about half of the patients within a year from the diagnosis [1]

  • Intra-tumoral geography of the brain tumor environment imposed by hypoxia contributes significantly to inter-tumor heterogeneity

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Summary

Introduction

Malignant tumors of the brain, such as glioblastomas, are among the most feared ones. They progress fast, killing about half of the patients within a year from the diagnosis [1]. Unlike for other types of cancers, survival rates for glioblastoma have not improved much in decades, even with a recently incorporated approach known as immunotherapy that instructs the patient’s immune system to recognize and kill cancer cells [2,3]. Finding out which cell types in a heterogeneous tumor are eradicated by the therapy and which resist it, will provide the context on the obstacles that boost in vivo resistance.

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