Mutation based treatment recommendations from next generation sequencing data

A comparison of web tools

Jaymin M. Patel, Joshua Knopf, Eric Reiner, Veerle Bossuyt, Lianne Epstein, Michael DiGiovanna, Gina Chung, Andrea Silber, Tara Sanft, Erin Hofstatter, Sarah Mougalian, Maysa Abu-Khalaf, James Platt, Weiwei Shi, Peter Gershkovich, Christos Hatzis, Lajos Pusztai

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Interpretation of complex cancer genome data, generated by tumor target profiling platforms, is key for the success of personalized cancer therapy. How to draw therapeutic conclusions from tumor profiling results is not standardized and may vary among commercial and academically-affiliated recommendation tools. We performed targeted sequencing of 315 genes from 75 metastatic breast cancer biopsies using the FoundationOne assay. Results were run through 4 different web tools including the Drug-Gene Interaction Database (DGidb), My Cancer Genome (MCG), Personalized Cancer Therapy (PCT), and cBioPortal, for drug and clinical trial recommendations. These recommendations were compared amongst each other and to those provided by FoundationOne. The identification of a gene as targetable varied across the different recommendation sources. Only 33% of cases had 4 or more sources recommend the same drug for at least one of the usually several altered genes found in tumor biopsies. These results indicate further development and standardization of broadly applicable software tools that assist in our therapeutic interpretation of genomic data is needed. Existing algorithms for data acquisition, integration and interpretation will likely need to incorporate artificial intelligence tools to improve both content and real-time status.

Original languageEnglish (US)
Pages (from-to)22064-22076
Number of pages13
JournalOncotarget
Volume7
Issue number16
DOIs
StatePublished - Apr 19 2016
Externally publishedYes

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Mutation
Neoplasms
Therapeutics
Genes
Genome
Biopsy
Artificial Intelligence
Drug Interactions
Software
Clinical Trials
Databases
Breast Neoplasms
Drug Therapy
Pharmaceutical Preparations

All Science Journal Classification (ASJC) codes

  • Oncology

Cite this

Patel, J. M., Knopf, J., Reiner, E., Bossuyt, V., Epstein, L., DiGiovanna, M., ... Pusztai, L. (2016). Mutation based treatment recommendations from next generation sequencing data: A comparison of web tools. Oncotarget, 7(16), 22064-22076. https://doi.org/10.18632/oncotarget.8017

Mutation based treatment recommendations from next generation sequencing data : A comparison of web tools. / Patel, Jaymin M.; Knopf, Joshua; Reiner, Eric; Bossuyt, Veerle; Epstein, Lianne; DiGiovanna, Michael; Chung, Gina; Silber, Andrea; Sanft, Tara; Hofstatter, Erin; Mougalian, Sarah; Abu-Khalaf, Maysa; Platt, James; Shi, Weiwei; Gershkovich, Peter; Hatzis, Christos; Pusztai, Lajos.

In: Oncotarget, Vol. 7, No. 16, 19.04.2016, p. 22064-22076.

Research output: Contribution to journalArticle

Patel, JM, Knopf, J, Reiner, E, Bossuyt, V, Epstein, L, DiGiovanna, M, Chung, G, Silber, A, Sanft, T, Hofstatter, E, Mougalian, S, Abu-Khalaf, M, Platt, J, Shi, W, Gershkovich, P, Hatzis, C & Pusztai, L 2016, 'Mutation based treatment recommendations from next generation sequencing data: A comparison of web tools', Oncotarget, vol. 7, no. 16, pp. 22064-22076. https://doi.org/10.18632/oncotarget.8017
Patel, Jaymin M. ; Knopf, Joshua ; Reiner, Eric ; Bossuyt, Veerle ; Epstein, Lianne ; DiGiovanna, Michael ; Chung, Gina ; Silber, Andrea ; Sanft, Tara ; Hofstatter, Erin ; Mougalian, Sarah ; Abu-Khalaf, Maysa ; Platt, James ; Shi, Weiwei ; Gershkovich, Peter ; Hatzis, Christos ; Pusztai, Lajos. / Mutation based treatment recommendations from next generation sequencing data : A comparison of web tools. In: Oncotarget. 2016 ; Vol. 7, No. 16. pp. 22064-22076.
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