Lessons learned from the application of whole-genome analysis to the treatment of patients with advanced cancers

• DOI: 10.1101/mcs.a000570
• Publication Date: 2015-10-05T18:28:38Z
• Authors: Janessa Laskin; Steven Jones; Samuel Aparicio; Stephen Chia; Carolyn Ch'ng; Rebecca Deyell; Peter Eirew; Alexandra Fok; Karen Gelmon; Cheryl Ho; David Huntsman; Martin Jones; Katayoon Kasaian; Aly Karsan; Sreeja Leelakumari; Yvonne Li; Howard Lim; Yussanne Ma; Colin Mar; Monty Martin; Richard Moore; Andrew Mungall; Karen Mungall; Erin Pleasance; S. Rod Rassekh; Daniel Renouf; Yaoqing Shen; Jacqueline Schein; Kasmintan Schrader; Sophie Sun; Anna Tinker; Eric Zhao; Stephen Yip; Marco A. Marra
• Keywords: Personalized Medicine

Given the success of targeted agents in specific populations it is expected that some degree molecular biomarker testing will become standard care for many, if not all, cancers. To facilitate this, cancer centers worldwide are experimenting with "panel" sequencing selected mutations. Recent advances genomic technology enable generation genome-scale data sets individual patients. Recognizing risk, inherent panel sequencing, failing to detect meaningful somatic alterations, we sought establish processes integrate from whole-genome analysis (WGA) into routine care. Between June 2012 and August 2014, 100 adult patients incurable cancers consented participate Personalized OncoGenomics (POG) study. Fresh tumor blood samples were obtained used RNA sequencing. Computational approaches identify candidate driver mutations, genes, pathways. Diagnostic drug information then based on these "drivers." Reports generated discussed weekly a multidisciplinary team setting. Other working groups assembled guidelines interpretation, communication, integration findings patient Of 78 whom WGA was possible, results considered actionable 55 cases. In 23 cases, received treatments motivated by WGA. Our experience indicates clinicians scientists can implement paradigm which integrated late stage inform systemic therapy decisions.