Identify Cancer Stem Cell Signature in Malignant Brain Tumors – UROP Symposium

Identify Cancer Stem Cell Signature in Malignant Brain Tumors

Karanjeet Deol

Research Mentor: Xing Fan
Mentor Department: Neurosurgery and Cell and Developmental Biology, Medicine
Author(s): Not Available
Session: Session 2 (10:00 AM – 10:50 AM)
Presentation Type: Poster 31

Abstract

Glioblastoma is the most common malignant brain tumor in adults, with less than 5% of patients surviving more than 2 years, and new therapeutic strategies are desperately needed. The cancer stem cell hypothesis purports that only by removing cancer stem cells within a tumor can the cancer be cured. Although CD133 markers and side population have been used to isolate glioblastoma stem cells, recent data indicate that cancer stem cells also exist in CD133-negative and non-side-population cells in some cancers, including glioblastoma, suggesting that additional markers are needed to isolate a pure cancer stem cell population. There has also been a finding that the NOTCH signaling pathway regulates normal brain stem cells, and that glioblastomas contain stem-like cells with higher NOTCH activity. This study found that some cancer cells were resistant to the notch signaling pathways. Therefore, the goal of this proposal is to identify notch resistance within stem cell populations and, eventually, use these resistances to identify the gene signature of these cancer stem cells in malignant brain tumors. To achieve this, we will perform an Alamar Blue cell viability assay to determine the concentration of notch receptors that kills 50% of the cancer cells, and create a growth curve to identify the optimal concentration and incubation time for detecting resistant cells. Based on this result, we will plate the cells again using the new concentration determined by the Alamar Blue assay and wait a couple of days until 50% of the cells are killed. The remaining 50% of the cells that are still alive would be classified as notch-resistant. Then we will identify additional cancer stem cell signatures by screening a cohort of stemness genes by real-time RT-PCR in glioblastoma neurosphere lines and primary tumors.

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