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Proteogenomic analysis of glioblstoma reveals survival related patterns

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NIAID Data Ecosystem2026-03-12 收录
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https://www.omicsdi.org/dataset/pride/PXD018024
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In the current work, we present the first proteogenomic dataset of GBM clinical samples to date. We have assembled a cohort of 87 GBM patients of varying survival rates and performed MS-based proteomics analysis as well as RNA-seq in order to identify the molecular differences associated with survival and examine the contribution of each layer to GBM landscape. We show that each layer alone only partially reflects patient survival, but RNA-protein integration identifies clear patterns of layer-specific and layer-common processes specifically contributing to either short-term or long-term survival of patients. Furthermore, we compare our data to published single-cell RNA-seq of GBM tumors and evaluate the RNA-protein variability within single-cell based tumor subpopulations. We found that while all signatures of the four subpopulations tend to have high RNA-protein correlation, each signature is associated differently with survival. Altogether, these results highlight the potential of proteogenomics to further stratify heterogeneity in GBM tumors and identify processes contributing to poorer survival.
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2021-04-16
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