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| Status |
Public on Nov 05, 2024 |
| Title |
Classification of pediatric soft and bone sarcomas using DNA methylation-based profiling |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Pediatric sarcomas present heterogeneous morphology, genetics and clinical behavior posing a challenge for an accurate diagnosis. DNA methylation is an epigenetic modification that coordinates chromatin structure and regulates gene expression, determining cell type and function. DNA methylation-based tumor profiling classifier for sarcomas (known as sarcoma classifier) from the German Cancer Research Center (Deutsches Krebsforschungszentrum) was applied to 122 pediatric sarcomas referred to a reference pediatric oncology hospital. The classifiers reported 88.5% of agreement between histopathological and molecular classification confirming the initial diagnosis of all osteosarcomas and Ewing sarcomas. Transcriptome raw data quality was verified with FASTQC. We used STAR-fusion to identify and annotate fusion transcripts based on discordant read alignments with default configurations. ChimeraViz was used to plot fusion-genes.
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| Overall design |
RNA was extracted with RNeasy Kit (QIAGEN, Hilden, Germany; cat. ID: 74106) and quantified with High Sensitivity Qubit™ RNA Assay Kits (Invitrogen™, Waltham, MA, USA; cat. ID: Q32855). Transcriptome assay was performed using Illumina Stranded Total RNA Prep, Ligation with Ribo-Zero Plus (Illumina, San Diego, CA, USA) and sequenced on the NextSeq550 or NOVAseqX (Illumina Inc, San Diego, CA, USA). Paired-end runs were sequenced in 74 cycles per read (2 X 74), with an average of 41.5 million reads per sample.
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| Contributor(s) |
Maschietto M |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
Aug 19, 2024 |
| Last update date |
Nov 05, 2024 |
| Contact name |
Felipe Silva |
| E-mail(s) |
[email protected]
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| Organization name |
Boldrini
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| Street address |
R. Márcia Mendes, 506
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| City |
Campinas |
| ZIP/Postal code |
13083-884 |
| Country |
Brazil |
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| Platforms (2) |
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| Samples (14)
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| Relations |
| BioProject |
PRJNA1149753 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE275159_count.csv.gz |
973.5 Kb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Raw data are available in SRA |
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