Authors:
Paciello Giulia
1
;
Andrea Acquaviva
1
;
Consalvo Petti
2
;
Claudio Isella
2
;
Enzo Medico
3
and
Elisa Ficarra
1
Affiliations:
1
Politecnico di Torino, Italy
;
2
Institute for Cancer Research at Candiolo (IRCC), Italy
;
3
Institute for Cancer Research at Candiolo (IRCC) and Universita’ di Torino, Italy
Keyword(s):
RNA-sequencing, Metastatic Colorectal Cancer, Patient-derived Mouse Xenografts, Artifacts.
Related
Ontology
Subjects/Areas/Topics:
Bioinformatics
;
Biomedical Engineering
;
Genomics and Proteomics
;
Next Generation Sequencing
Abstract:
Metastatic spread to the liver is a frequent complication of colorectal cancer (CRC), occurring in almost
half of the cases, for which personalized treatment strategies are highly desirable. To this aim, it has been
proven that patient-derived mouse xenografts (PDX) of liver-metastatic CRC can be used to discover new
therapeutic targets and determinants of drug resistance. To identify gene fusions in RNA-Seq data obtained
from such PDX samples, we propose a novel pipeline that tackles the following issues: (i) discriminating
human from murine RNA, to filter out transcripts contributed by the mouse stroma that supports the PDX;
(ii) increasing sensitivity in case of suboptimal RNA-Seq coverage; (iii) prioritizing the detected chimeric
transcripts by molecular features of the fusion and by functional relevance of the involved genes; (iv) providing
appropriate sequence information for subsequent validation of the identified fusions. The pipeline, built on top
of Chimerascan(R.Iyer, 2011
) and deFuse(McPherson, 2011) aligner tools, was successfully applied to RNASeq
data from 11 PDX samples. Among the 299 fusion genes identified by the aforementioned softwares,
five were selected since passed all the filtering stages implemented into the proposed pipeline resulting as
biologically relevant fusions. Three of them were experimentally confirmed.
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