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

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, 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

Abstract

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

Figures

Figure 1.
Figure 1.
Schema outlining a high-level model of the process from the time of patient consent to the generation of a Personalized OncoGenomics report and discussion with the patient.
Figure 2.
Figure 2.
CONSORT diagram of the 100 adult patients consented into the Personalized OncoGenomics (POG) study.
Figure 3.
Figure 3.
Working definitions for genomics output and potential clinical impact of this data.

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Source: PubMed

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