Defining cellular states of quiescence in human brain tumors

Project: Research project

Project Details

Description

Defining cellular states of quiescence in human brain tumors Defining cellular states of quiescence in human brain tumors In recent work with the Paddison lab we analyzed scRNA-seq data from neuroepithelial stem cells (NSCs) and reconstructed the cell cycle phases including a Neural G0-like phase. We then developed the ccAF classifier to classify cells as one of these cell cycle states and applied it to single cells from dissociated GBM tumors. The genes that classified Neural G0 were used to define a Neural G0 gene expression signature. Investigation of patient GBM tumors showed that the Neural G0 gene expression stratifies long and short-term glioma survivors, where tumors with higher Neural G0 expression survive on average 4.6 years longer than those with low expression. For this proposal we will conduct computational studies to improve the ccAF classifier by identifying and incorporating for G0-like for cells from the mesenchymal subtype, because the Neural G0 category is under-represented in cells that have a mesenchymal subtype expression pattern. We will also develop a single-cell implementation of the SYGNAL pipeline to construct gene regulatory networks, which will need to be adapted to handle dropouts, a common problem in single-cells studies. We will also work with Dr. Paddison, Dr. Patel, and their laboratories to provide whatever additional analyses that help to test the hypothesis that glioblastoma cells adopt G0-like states in tumors. We will have monthly meetings with Dr. Paddison, Dr. Patel, and their laboratories to remain informed on progress of the scRNA-seq data acquisition, provide updates on analysis, share analysis results, and facilitate collaboration. In addition we will utilize social media platforms like Microsoft Teams and Slack to share input, data, and analyses in a timely manner.
StatusFinished
Effective start/end date4/1/224/2/22

Funding

  • HHS: National Institutes of Health (NIH): $379,793.00

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