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Genotyping data of routinely processed matched primary/metastatic tumor samples.

Authors :
Kotoula V
Chatzopoulos K
Papadopoulou K
Giannoulatou E
Koliou GA
Karavasilis V
Pazarli E
Pervana S
Kafiri G
Tsoulfas G
Chrisafi S
Sgouramali H
Papakostas P
Pectasides D
Hytiroglou P
Pentheroudakis G
Fountzilas G
Source :
Data in brief [Data Brief] 2020 Dec 11; Vol. 34, pp. 106646. Date of Electronic Publication: 2020 Dec 11 (Print Publication: 2021).
Publication Year :
2020

Abstract

Genotypic and phenotypic comparisons of tumors in multiple tissue samples from the same patient are important for understanding disease evolution and treatment possibilities. Panel NGS genotyping is currently widely used in this context, whereby NGS variant filtering and final evaluation constitute the basis for meaningful comparisons. Here, we present the genotype data used for genotype / phenotype comparisons between matched primary / metastatic colorectal tumors in the work by Chatzopoulos et al (doi: 10.1016/j.humpath.2020.10.009), as well as the process followed for obtaining these data. We describe key issues while processing routinely formalin-fixed paraffin-embedded (FFPE) tumors for genotyping, NGS application (Ion Torrent), a stringent variant filtering algorithm for genotype analyses in FFPE tissues and particularly in matched tumor samples, and provide the respective datasets. Apart from research, tumor NGS genotyping is currently applied for clinical diagnostic purposes in Oncology. The datasets and method description provided herein (a) are important for comprehending the peculiarities of FFPE tumor genotyping, which is still mostly based on principles of germline DNA genotyping; (b) can be used in pooled analyses, e.g., of primary / metastatic tumors for the investigation of tumor evolution.<br />Competing Interests: The authors declare no conflicts of interest.<br /> (© 2020 The Authors.)

Details

Language :
English
ISSN :
2352-3409
Volume :
34
Database :
MEDLINE
Journal :
Data in brief
Publication Type :
Academic Journal
Accession number :
33365374
Full Text :
https://doi.org/10.1016/j.dib.2020.106646