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Functional precision medicine pipeline combines comparative transcriptomics and tumor organoid modeling to identify be-spoke treatment strategies for glioblastoma

ABSTRACT: Functional precision medicine pipeline combines comparative transcriptomics and tumor organoid modeling to identify be-spoke treatment strategies for glioblastoma

PROVIDER: PRJNA780017 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR16936961_1.fastq.gz	Fastqsanger.gz
	SRR16936961_2.fastq.gz	Fastqsanger.gz
	SRR16936962_1.fastq.gz	Fastqsanger.gz
	SRR16936962_2.fastq.gz	Fastqsanger.gz
	SRR16936963_1.fastq.gz	Fastqsanger.gz

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Functional precision medicine pipeline combines comparative transcriptomics and tumor organoid modeling to identify be-spoke treatment strategies for glioblastoma

Project description: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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Project description: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 a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. 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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