PRRophetic: An r package for prediction of clinical chemotherapeutic response from tumor gene expression levels

Paul Geeleher, Nancy Cox, R. Stephanie Huang

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

We recently described a methodology that reliably predicted chemotherapeutic response in multiple independent clinical trials. The method worked by building statistical models from gene expression and drug sensitivity data in a very large panel of cancer cell lines, then applying these models to gene expression data from primary tumor biopsies. Here, to facilitate the development and adoption of this methodology we have created an R package called pRRophetic. This also extends the previously described pipeline, allowing prediction of clinical drug response for many cancer drugs in a user-friendly R environment. We have developed several other important use cases; as an example, we have shown that prediction of bortezomib sensitivity in multiple myeloma may be improved by training models on a large set of neoplastic hematological cell lines. We have also shown that the package facilitates model development and prediction using several different classes of data.

Original languageEnglish (US)
Article numbere107468
JournalPloS one
Volume9
Issue number9
DOIs
StatePublished - Sep 17 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 Geeleher et al.

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