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.

A Novel Pipeline for Identification and Prioritization of Gene Fusions in Patient-derived Xenografts of Metastatic Colorectal Cancer / Paciello, Giulia; Acquaviva, Andrea; Consalvo, Petti; Claudio, Isella; Enzo, Medico; Ficarra, Elisa. - (2014), pp. 142-148. ((Intervento presentato al convegno 5th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 tenutosi a Angers, Loire Valley, fra nel 3-6 March 2014 [10.5220/0004799401420148].

A Novel Pipeline for Identification and Prioritization of Gene Fusions in Patient-derived Xenografts of Metastatic Colorectal Cancer

FICARRA, ELISA
2014

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.
5th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
Angers, Loire Valley, fra
3-6 March 2014
142
148
Paciello, Giulia; Acquaviva, Andrea; Consalvo, Petti; Claudio, Isella; Enzo, Medico; Ficarra, Elisa
A Novel Pipeline for Identification and Prioritization of Gene Fusions in Patient-derived Xenografts of Metastatic Colorectal Cancer / Paciello, Giulia; Acquaviva, Andrea; Consalvo, Petti; Claudio, Isella; Enzo, Medico; Ficarra, Elisa. - (2014), pp. 142-148. ((Intervento presentato al convegno 5th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 tenutosi a Angers, Loire Valley, fra nel 3-6 March 2014 [10.5220/0004799401420148].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1240331
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