pRRophetic: An R Package for Prediction of Clinical Chemotherapeutic Response from Tumor Gene Expression Levels

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…

• CC
  Conquer Cancer Foundation
• AS
  American Society of Clinical Oncology
• UO
  University of Chicago

  Awards: UL1RR024999, P30 CA14599
• NI
  National Institutes of Health

  Awards: UL1RR024999, CA14599, P30 CA14599
• NC
  National Cancer Institute

  Awards: CA139278, CA14599, P30 CA14599, CA125183
• NC
  National Center for Advancing Translational Sciences

  Award: UL1RR024999