Chapter Six - Molecular determinants of the interaction between glioblastoma CD133+ cancer stem cells and the extracellular matrix
Introduction
Glioblastoma multiforme (GBM) is one of the most aggressive types of human brain cancer. It is characterized by rapid invasive growth, significant brain infiltration and strong resistance to treatment. Despite advances in surgery, radical elimination of the tumor without causing severe and irreversible neurological damage to the patient remains a challenge (Costa, Lawson, Lelotte, et al., 2019). Therefore, the primary treatment type is high-dose radiation with multiple rounds of chemotherapy (Lukas, Wainwright, Ladomersky, et al., 2019). Prognosis for patients with this type of tumor is unfavorable, as the survival rate at 2 years following diagnosis is 27–43%, and the median survival time of patients with GBM is 15 months (Stupp & Ram, 2018). Due to their invasive ability, cancer cells that have deeply penetrated the brain tissue from the original lesion inevitably cause relapses, requiring new approaches and treatment protocols for patients with this disease.
The ability to penetrate the brain matter (Perrin, Samuel, Koszyca, et al., 2019) is due to the mesenchymal-like aggressive phenotype of cancer cells, and is influenced by coordinated intercellular interactions with the local microenvironment (Roos, Ding, Loftus, et al., 2017). The key properties of this phenotype include switching from adhesive E-cadherins to migratory N-cadherins, extending the range of integrin receptors on the cellular surface, developing the ability to produce extracellular matrix (ECM) components, synthesizing matrix metalloproteases (Bryukhovetskiy & Shevchenko, 2016).
Focal adhesion proteins are critical to underpinning the invasive potential of cancer cells with an aggressive phenotype (Bolteus, Berens, & Pilkington, 2001). GBM cells penetrate the brain tissue, adhere to ECM proteins and create cellular-matrix connections with structural and signaling functions that interact with the microenvironment (Huttenlocher & Horwitz, 2011). These connections between the ECM and the actin cytoskeleton of the cells also generate tension that is required for migration beyond the primary lesion. Inhibition of the interaction between cancer cells and the ECM is one of the aims of GBM treatment.
GBM relapse and progression is also attributed to cancer stem cells (CSCs) that have unique signaling and morphological properties (Singh, Clarke, Terasaki, et al., 2003), including an ability to initiate and support rapid tumor growth. CSCs occupy the dominant position in the GBM cellular hierarchy, and are detected at the anterior border of the tumor (Gimple, Bhargava, Dixit, et al., 2019), indicating that they are involved in invasive processes. However, it remains unclear if CSCs are more invasive than differentiated tumor cells, and if they contribute to the development of GBM with an aggressive phenotype.
The CD133 antigen is the most reliable marker for CSCs (Singh, Hawkins, Clarke, et al., 2004). This marker is introduced into GBM tissue by the symmetrical division of CSCs and by reprogramming of differentiated CD133-negative (CD133 −) tumor cells resulting in phenotypic plasticity (Li, Zhou, Xu, & Xiao, 2013) in the tumor cell population. The ability of to recruit normal neural CD133-positive (CD133 +) stem cells further complicates our understanding of its heterogeneity (Okawa, Gagrica, & Blin, 2017). The aim of the present study was, therefore, to compare the expression profiles of proteins involved in the interaction with the ECM, and signaling pathways in CD133 + CSCs and differentiated glioblastoma cells (DGCs). The present study may lead to the discovery of new molecular targets for regulating the invasive activity of CSCs.
Section snippets
Human GBM cells
For the present study, the U-87MG GBM cell line was obtained from the American Type Culture Collection (cat no. HTB-14™). This cell line is not the original U-87 line established at the University of Uppsala, but derived from a human glioblastoma of unknown origin (Allen, Bjerke, Edlund, et al., 2016). However, as demonstrated in our previous study, the stimulation of GBM U-87MG cells with transforming growth factor (TGF)-β1 led to a significant increase in the expression levels of proteins
CSCs have altered proteomes compared to DGCs
Proteome analysis identified 1990 unique proteins. A total of 1891 proteins were identified in the CSC sample, and 1748 proteins were found in the sample of differentiated GBM cells (DGCs). Identified proteins showed a high percentage of overlap between the two cell populations: 1649 proteins were present in all cell lysates; 242 proteins were found only in CSCs; and 99 proteins were observed only in DGCs. Among the discovered proteins, 589 had significantly different expression levels in CSCs (
Discussion
The present study investigated proteins that are upregulated in CSCs, and that serve a crucial role in their interaction with the ECM. Activation of hyaluronic acid receptors, CD44 (Table 1) and hyaluronan-mediated motility receptor (HMMR) in CSCs has been found to be a key factor for invasion (Mooney, Choy, Sidhu, et al., 2016). CD44 glycoprotein is described as a CSC marker in various cancer types, including GBM, and it is frequently used as an indicator of tumor cells with aggressive
Funding
This study was funded by the Ministry of Science and Higher Education of Russia (Contract no. 14.584.21.0027 ID:RFMEFI58417X0027).
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Ethics approval and consent to participate
Ethics approval and consent to participate.
Informed consent was obtained from all individual participants included in the study and all procedures performed in studies involving human participants were in accordance with the ethical standards of the Far Eastern Federal University and University of Uppsala.
Authors' contributions
V.S. and N.A. prepared and analyzed the samples, as well as performed the cell lysis, chromatography and mass spectrometry, and contributed to the bioinformatics analysis. S.A. provided and performed the statistical analysis and was responsible for the mathematical process of the results. Y.K. and H.S. discussed, analyzed and interpreted the results of the study, and also worked on the manuscript. I.B. wrote the manuscript, proposed the study idea, designed the study, offered support with the
Conflict of interest
The authors declare there are no conflicts of interests.
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