Abstract
Background. Human mesenchymal stem cells (hMSCs) have been shown to reside as stromal cells in human gliomas as glioma-associated hMSCs (GA-hMSCs), but their biological role remains unclear. Because recent evidence indicates that GA-hMSCs drive tumor cell proliferation and stemness, we hypothesized that a higher percentage of GA-hMSCs in tumors predicts poor patient prognosis. Method. We determined the percentage of cells coexpressing GA-hMSC markers CD105+/CD73+/CD90+ from patients with newly diagnosed high-grade glioma and analyzed the association between this percentage and overall survival (OS) in 3 independent cohorts: fresh surgical glioblastoma specimens (cohort 1, N = 9), cultured tumor specimens at passage 3 (cohort 2, N = 28), and The Cancer Genome Atlas (TCGA) database. Results. In all cohorts, patient OS correlated with the percentages of GA-hMSCs in tumors. For cohort 1, the median OS of patients with tumors with a low percentage of triple-positive cells was 46 months, and for tumors with a high percentage of triple-positive cells, it was 12 months (hazard ratio [HR] = 0.24; 95% CI: 0.02-0.5, P =.02). For cohort 2, the median OS of patients with tumors with a low percentage of GA-hMSCs was 66 months, and for tumors with a high percentage, it was 11 months (HR = 0.38; 95% CI: 0.13-0.9, P =.04). In the database of TCGA, the median OS times in patients with high and low coexpression levels of CD105/CD73/CD90 were 8.4 months and 13.1 months (HR = 0.4; 95% CI: 0.1-0.88; P =.04), respectively. Conclusions. The percentage of GA-MSCs inversely correlates with OS, suggesting a role for GA-MSCs in promoting aggressive behavior of gliomas.
Original language | English (US) |
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Pages (from-to) | 660-668 |
Number of pages | 9 |
Journal | Neuro-oncology |
Volume | 19 |
Issue number | 5 |
DOIs | |
State | Published - May 1 2017 |
Keywords
- Glioblastoma
- Mesenchymal stem cells
- Microenvironment
- Prognosis
ASJC Scopus subject areas
- Oncology
- Clinical Neurology
- Cancer Research
MD Anderson CCSG core facilities
- Biostatistics Resource Group