Frontiers in Genetics (May 2014)
Bioinformatics for Precision Medicine in Oncology: principles and application to the SHIVA clinical trial
- Nicolas eServant,
- Nicolas eServant,
- Nicolas eServant,
- Julien eRoméjon,
- Julien eRoméjon,
- Julien eRoméjon,
- Pierre eGestraud,
- Pierre eGestraud,
- Pierre eGestraud,
- Philippe eLa Rosa,
- Philippe eLa Rosa,
- Philippe eLa Rosa,
- Georges eLucotte,
- Georges eLucotte,
- Georges eLucotte,
- Séverine eLair,
- Séverine eLair,
- Séverine eLair,
- Virginie eBernard,
- Bruno eZeitouni,
- Bruno eZeitouni,
- Bruno eZeitouni,
- Fanny eCoffin,
- Fanny eCoffin,
- Fanny eCoffin,
- Gérôme eJules-Clément,
- Gérôme eJules-Clément,
- Gérôme eJules-Clément,
- Gérôme eJules-Clément,
- Florent eYvon,
- Florent eYvon,
- Florent eYvon,
- Alban eLermine,
- Alban eLermine,
- Alban eLermine,
- Patrick ePoullet,
- Patrick ePoullet,
- Patrick ePoullet,
- Stéphane eLiva,
- Stéphane eLiva,
- Stéphane eLiva,
- Stuart ePook,
- Stuart ePook,
- Stuart ePook,
- Tatiana ePopova,
- Camille eBarette,
- Camille eBarette,
- Camille eBarette,
- Camille eBarette,
- François ePrud'homme,
- François ePrud'homme,
- François ePrud'homme,
- Jean-Gabriel eDick,
- Maud eKamal,
- Christophe eLe Tourneau,
- Christophe eLe Tourneau,
- Emmanuel eBarillot,
- Emmanuel eBarillot,
- Emmanuel eBarillot,
- Philippe eHupé,
- Philippe eHupé,
- Philippe eHupé,
- Philippe eHupé
Affiliations
- Nicolas eServant
- Institut Curie
- Nicolas eServant
- INSERM
- Nicolas eServant
- Mines ParisTech
- Julien eRoméjon
- Institut Curie
- Julien eRoméjon
- INSERM
- Julien eRoméjon
- Mines ParisTech
- Pierre eGestraud
- Institut Curie
- Pierre eGestraud
- INSERM
- Pierre eGestraud
- Mines ParisTech
- Philippe eLa Rosa
- Institut Curie
- Philippe eLa Rosa
- INSERM
- Philippe eLa Rosa
- Mines ParisTech
- Georges eLucotte
- Institut Curie
- Georges eLucotte
- INSERM
- Georges eLucotte
- Mines ParisTech
- Séverine eLair
- Institut Curie
- Séverine eLair
- INSERM
- Séverine eLair
- Mines ParisTech
- Virginie eBernard
- Institut Curie
- Bruno eZeitouni
- Institut Curie
- Bruno eZeitouni
- INSERM
- Bruno eZeitouni
- Mines ParisTech
- Fanny eCoffin
- Institut Curie
- Fanny eCoffin
- INSERM
- Fanny eCoffin
- Mines ParisTech
- Gérôme eJules-Clément
- Institut Curie
- Gérôme eJules-Clément
- INSERM
- Gérôme eJules-Clément
- Mines ParisTech
- Gérôme eJules-Clément
- INSERM
- Florent eYvon
- Institut Curie
- Florent eYvon
- INSERM
- Florent eYvon
- Mines ParisTech
- Alban eLermine
- Institut Curie
- Alban eLermine
- INSERM
- Alban eLermine
- Mines ParisTech
- Patrick ePoullet
- Institut Curie
- Patrick ePoullet
- INSERM
- Patrick ePoullet
- Mines ParisTech
- Stéphane eLiva
- Institut Curie
- Stéphane eLiva
- INSERM
- Stéphane eLiva
- Mines ParisTech
- Stuart ePook
- Institut Curie
- Stuart ePook
- INSERM
- Stuart ePook
- Mines ParisTech
- Tatiana ePopova
- INSERM
- Camille eBarette
- Institut Curie
- Camille eBarette
- INSERM
- Camille eBarette
- Mines ParisTech
- Camille eBarette
- Institut Curie
- François ePrud'homme
- Institut Curie
- François ePrud'homme
- Institut Curie
- François ePrud'homme
- Institut Curie
- Jean-Gabriel eDick
- Institut Curie
- Maud eKamal
- Institut Curie
- Christophe eLe Tourneau
- INSERM
- Christophe eLe Tourneau
- Institut Curie
- Emmanuel eBarillot
- Institut Curie
- Emmanuel eBarillot
- INSERM
- Emmanuel eBarillot
- Mines ParisTech
- Philippe eHupé
- Institut Curie
- Philippe eHupé
- INSERM
- Philippe eHupé
- Mines ParisTech
- Philippe eHupé
- CNRS
- DOI
- https://doi.org/10.3389/fgene.2014.00152
- Journal volume & issue
-
Vol. 5
Abstract
Precision medicine (PM) requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of i) warranting the integration and the traceability of data, ii) ensuring the correct processing and analyses of genomic data and iii) applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.
Keywords