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Status |
Public on Dec 02, 2021 |
Title |
Functional precision medicine pipeline combines comparative transcriptomics and tumor organoid modeling to identify be-spoke treatment strategies for glioblastoma |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
Li-Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer occurring in 30-50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used novel comparative transcriptomics analysis to identify genes that are uniquely overexpressed in a LFS GBM patient relative to a cancer compen-dium of 12,747 tumor RNA sequencing datasets including 200 GBMs. We then used ex vivo pa-tient derived organoid (PDO) viability assays with 4 patient derived cell lines to test efficacy of our identified target. Our comparative transcriptomics bioinformatics pipeline identified that STAT1 and STAT2 were significantly overexpressed in our patient indicating ruxolitinib, a Janus kinase 1 and 2 inhibitor, as a potential therapy. In our institutional high-grade glioma cohort of 45 patients, the LFS patient had the highest level of STAT1 and STAT2 expression. STAT1 and STAT2 expression levels in 4 cell lines derived from patients (including the LFS patient) corre-lated with levels identified in the respective parent tumors. Using 2D and 3D assays from pa-tient derived cells, our LFS patient of interest was among the most sensitive to ruxolitinib in comparison to patients with lower STAT1 and STAT2 expression levels. Additionally a sphe-roid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.
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Overall design |
mRNA expression levels derived from RNA-seq for one patient tumor sample and four cell lines derived from patient tumors.
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Contributor(s) |
Reed MR, Rodriguez A, Vaske OM |
Citation(s) |
34943910 |
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Submission date |
Nov 12, 2021 |
Last update date |
Mar 04, 2022 |
Contact name |
Analiz Rodriguez |
E-mail(s) |
ARodriguez@uams.edu
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Organization name |
University of Arkansas for Medical Sciences
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Department |
College of Medicine, Department of Neurosurgery
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Lab |
Rodriguez Lab
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Street address |
4301 W. Markham St Slot 507
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City |
Little Rock |
State/province |
AR |
ZIP/Postal code |
72205 |
Country |
USA |
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Platforms (2) |
GPL16791 |
Illumina HiSeq 2500 (Homo sapiens) |
GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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Samples (5)
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Relations |
BioProject |
PRJNA780017 |
SRA |
SRP345887 |