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Series GSE248176 Query DataSets for GSE248176
Status Public on Dec 19, 2023
Title Modeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations [Exome panel]
Organism Homo sapiens
Experiment type Other
Summary Rhabdomyosarcoma (RMS) is the main form of pediatric soft-tissue sarcoma. Its cure rate has not improved in the last 20 years notably following relapse, and the lack of reliable preclinical models has so far hampered the design of new therapies. This is particularly true for highly heterogeneous fusion-negative RMS (FNRMS). Although methods have been proposed to establish FNRMS organoids, their efficiency remains limited to date, both in terms of derivation rate and ability to accurately mimic the original tumor.
Here, we present the development of a next-generation 3D-organoid model derived from relapsed adult and pediatric FNRMS. This model preserves the molecular features of the patients’ tumors and is expandable for several months in 3D, reinforcing its interest to drug combination screening with longitudinal efficacy monitoring.
As a proof-of-concept, we demonstrated its preclinical relevance by reevaluating the therapeutic opportunities of targeting apoptosis in FNRMS from a streamlined approach based on transcriptomic data exploitation.
 
Overall design We performed exome sequencing for a panel of genes on rhabdomyosarcoma tissue samples coming from 2 patients (2 samples) and their associated in vitro models (13 samples)
 
Contributor(s) Broutier L, Diot T
Citation(s) 38118405
Submission date Nov 17, 2023
Last update date Jan 12, 2024
Contact name Thomas Diot
Organization name Cancer Research Center of Lyon
Street address 28 Rue Laennec
City Lyon
ZIP/Postal code 69008
Country France
 
Platforms (1)
GPL24676 Illumina NovaSeq 6000 (Homo sapiens)
Samples (15)
GSM7906824 RMS2_O_P28* [Exome panel]
GSM7906825 RMS2_T [Exome panel]
GSM7906826 RMS2_O_P29* [Exome panel]
This SubSeries is part of SuperSeries:
GSE248183 Modeling the next-generation of rhabdomyosarcoma organoids to predict effective drug combinations
Relations
BioProject PRJNA1041881

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE248176_merged_samples_variants_filtered_germline.vcf.gz 322.2 Kb (ftp)(http) VCF
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Raw data are available in SRA
Processed data are available on Series record

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