Poster (Scientific congresses and symposiums)
Improving the bioinformatics analysis of HTS clonality data in virus-induced leukemia
Hahaut, Vincent; Rosewick, Nicolas; Artesi, Maria et al.
2018Télévie Cancer Seminar 2018
 

Files


Full Text
Poster_Télévie2017_VincentHahautAVdB_2901.pdf
Author postprint (3.07 MB)
Request a copy

All documents in ORBi are protected by a user license.

Send to



Details



Keywords :
Deltaretrovirus; Clonality; Bioinformatics
Abstract :
[en] Proviral integration into the host genome is one of the main hallmarks of infection by oncogenic retroviruses. This event creates a life-long signature, each infected cell being characterized by a specific integration site (IS). Monitoring of the clonal architecture over time (clone: population of cells sharing an identical IS) has significantly contributed to a better understanding of HIV persistence, gene therapy vector mediated treatment and deltaretrovirus-induced leukemia. Our lab recently developed an optimized high-throughput sequencing (HTS) based clonality method. It enables the identification of proviral integration sites genome-wide while simultaneously quantifying the abundance of the corresponding clones. The method is superior to any of the previously available protocols, mainly in terms of sensitivity, cost-effectiveness and hands-on time, making it suitable for routine clinical observation of infected individuals. Using this method, we recently showed that longitudinal monitoring of the dominant leukemic clone in patients infected by Human T-cell Leukemia Virus-1 (HTLV-1) better predicts therapeutic response (Artesi et al, Leukemia, 2017). We applied the method to biological samples isolated from HTLV-1 infected patients and Bovine Leukemia Virus (BLV) infected animals (bovine and sheep). This resulted in the generation of an unprecedented volume of raw sequence data. In this study we developed a novel clonality analysis pipeline that better exploits the potential of the method, improving previously published protocols.
Disciplines :
Oncology
Author, co-author :
Hahaut, Vincent ;  Université de Liège - ULiège > Département des productions animales (DPA) > GIGA-R : Génomique animale
Rosewick, Nicolas;  Université Libre de Bruxelles - ULB
Artesi, Maria ;  Université de Liège - ULiège > GIGA-Research
Durkin, Keith  ;  Université de Liège - ULiège > Département des productions animales (DPA) > GIGA-R : Génomique animale
Burny, Arsène ;  Université de Liège - ULiège > Agro Biotech Gembloux
Bron, Dominique
Georges, Michel  ;  Université de Liège - ULiège > Département des productions animales (DPA) > GIGA-R : Génomique animale
Van den Broeke, Anne;  Institut Jules Bordet > Laboratory of Experimental Hematology
Language :
English
Title :
Improving the bioinformatics analysis of HTS clonality data in virus-induced leukemia
Publication date :
02 February 2018
Event name :
Télévie Cancer Seminar 2018
Event date :
2 Février 2018
Funders :
Télévie [BE]
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
Fonds Léon Fredericq [BE]
IBS Internationale Brachet Stiftung
Les amis de l'Institut Jules Bordet
Available on ORBi :
since 02 February 2018

Statistics


Number of views
91 (17 by ULiège)
Number of downloads
5 (5 by ULiège)

Bibliography


Similar publications



Contact ORBi