Abstract
Gliomas are aggressive tumors in the central nervous system and glioblastoma is the most malignant type. Ferroptosis is a programmed cell death that can modulate tumor resistance to therapy and the components of tumor microenvironment. However, the relationship between ferroptosis, tumor immune landscape, and glioblastoma progression is still elusive. In this work, data from bulk RNA-seq analysis, single cell RNA-seq analysis, and our own data (the Xiangya cohort) are integrated to reveal their relationships. A scoring system is constructed according to ferroptosis related gene expression, and high scoring samples resistant to ferroptosis and show worse survival outcome than low scoring samples. Notably, most of the high scoring samples are aggressive glioblastoma subtype, mesenchymal, and classical, by calculating RNA velocity. Cross-talk between high scoring glioblastoma cells and immunocytes are explored by R package ‘celltalker’. Ligand–receptor pairs like the TRAIL or TWEAK signaling pathway are identified as novel bridges implying how ferroptosis modulate immunocytes’ function and shape tumor microenvironment. Critically, potential drugs target to high scoring samples are predicted, namely, SNX2112, AZ628, and bortezomib and five compounds from the CellMiner database. Taken together, ferroptosis associates with glioblastoma aggressiveness, cross-talk with immunocytes and offer novel chemotherapy strategy.
Highlights
Gliomas are malignant tumors of the central nervous system [1]
Heatmap reveals the connection between the clustering model, gliomas clinical features and ferroptosis related gene expression
GBM, IDH wild type gliomas, and MGMT unmethylated gliomas are related to samples in cluster2
Summary
Gliomas are malignant tumors of the central nervous system [1]. Gliomas can be classified into several groups, including astrocytic tumors, oligodendroglial tumors, oligoastrocytic tumors, ependymal tumors, mixed neuronal glial tumors (such as gangliogliomas), etc. WHO grade IV gliomas, known as glioblastomas (GBMs), are the most aggressive type of gliomas with median overall survival time of GBM less than 14.6 months [2]. Four subtypes of GBM (proneural, neural, classical, and mesenchymal) which were proposed by Verhhak and his team based on GBM genome characteristics have been proved that can predict GBM prognosis [3]. Mesenchymal and classical GBM show more aggressive growth pattern, while proneural and neural GBM have better prognosis. Treatments like surgical removal, radiation therapy, and chemotherapy can slow tumor progression but tumor resistance to treatments is still a tough problem
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