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Series GSE146670 Query DataSets for GSE146670
Status Public on Apr 30, 2020
Title Unique genomic and neoepitope landscapes across tumors: a study across time, tissues, and space within a single Lynch Syndrome patient
Organism Homo sapiens
Experiment type Genome variation profiling by array
Summary To investigate the longitudinal mutational patterns arising in Lynch Syndrome associated tumors we interrogated the genomes of five different cancers that arose over a period of 10 years in a patient who underwent resection in the absence of chemotherapy and radiation for each cancer. These included a papillary transitional cell carcinoma (PTCC) in the renal pelvis, a duodenal carcinoma, two separate CRCs that arose 3 years apart, and multiple regions of a triple negative breast cancer (TNBC). In each case we flow sorted tumor fractions from archived formalin fixed paraffin embedded (FFPE) tissue and profiled the tumor genomes with whole genome copy number variant (CNV) arrays and whole exome sequencing. These data were then used to identify the pathogenic variant underlying the diagnosis of LS, and to compare and contrast the CNV, mutational and neoepitope patterns across these divergent tumors that arose over a 10 year period. These results provide a unique analysis of distinct MSI+ tumors arising in a single LS patient.
 
Overall design We applied DNA content based flow sorting to isolate the nuclei from biopsies of five distinct tumors that arose in a patient with Lynch Syndrome over a 10 year period. We coupled this strategy with oligonucleotide array CGH (aCGH) and whole exome sequencing (WES), thereby obtaining high definition genomic profiles of from each tumor. The aCGH data was assessed with a series of QC metrics then analyzed using an aberration detection algorithm (ADM2). Reads from the WES BAM files were stripped using XYalign version 1.1.5 then mapped to the 1000 genomes version of GRCh38 using bwa-mem version 0.7.17. We applied EpitopeHunter to predict neoepitopes.
 
Contributor(s) Phung T, Lenkiewicz E, Malasi S, Sharma A, Anderson KS, Wilson MA, Pockaj BA, Barrett MT
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Submission date Mar 09, 2020
Last update date May 02, 2020
Contact name Michael Thomas Barrett
E-mail(s) barrett.michael@mayo.edu
Phone 480-301-6736
Organization name Mayo Clinic Arizona
Department Molecular Pharmacology and Experimental Therapeutics
Street address 13400 East Shea Boulevard
City Scottsdale
State/province AZ
ZIP/Postal code 85259
Country USA
 
Platforms (1)
GPL19387 Agilent-021850 SurePrint G3 Human CGH Microarray (Probe Name version)
Samples (5)
GSM4403944 PTCC-2008-P4
GSM4403945 Duodenal Carcinoma-2008-P4
GSM4403946 TNBC-B1-2017-P4
Relations
BioProject PRJNA611604

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
GSE146670_GEO.txt.gz 20.8 Mb (ftp)(http) TXT
GSE146670_Lynch-noduplicates-GEO.xlsx 49.2 Mb (ftp)(http) XLSX
GSE146670_RAW.tar 219.0 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table
Processed data are available on Series record

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