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. 2017:2017:PO.17.00036.
doi: 10.1200/PO.17.00036. Epub 2017 Sep 13.

Clinical Use of Precision Oncology Decision Support

Amber Johnson  1 , Yekaterina B Khotskaya  1 , Lauren Brusco  1 , Jia Zeng  1 , Vijaykumar Holla  1 , Ann M Bailey  1 , Beate C Litzenburger  1 , Nora Sanchez  1 , Md Abu Shufean  1 , Sarina Piha-Paul  2 , Vivek Subbiah  2 , David Hong  2 , Mark Routbort  3 , Russell Broaddus  4 , Kenna R Mills Shaw  1 , Gordon B Mills  1   5 , John Mendelsohn  1   6 , Funda Meric-Bernstam  1   2   7
Affiliations

Clinical Use of Precision Oncology Decision Support

Amber Johnson et al. JCO Precis Oncol. 2017.

Abstract

Purpose: Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced.

Methods: Genomic alterations were annotated to determine actionability based on a variant's known or potential functional and/or therapeutic significance. The medical records of a subset of patients annotated in 2015 were manually reviewed to assess trial enrollment. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued.

Results: PODS processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) across 49 tumor types for 1,197 patients. 2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable/potentially actionable alteration. 20.6% (110/535) patients annotated enrolled on a genotype-matched trial. Trial enrolment was significantly higher for patients with actionable/potentially actionable alterations (92/333, 27.6%) than those with unknown (16/136, 11.8%) and non-actionable (2/66, 3%) alterations (p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials. Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials.

Conclusion: Over half of alterations annotated were of unknown significance or non-actionable. Physicians were more likely to enroll a patient on a genotype-matched trial when an annotation supported actionability. Future studies are needed to demonstrate the impact of decision support on trial enrollment and oncologic outcomes.

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Conflict of interest statement

Declaration of Interests: Amber Johnson, Yekaterina Khotskaya, Lauren Brusco, Jia Zeng, Vijaykumar Holla, Ann Bailey, Beate Lizenburger, Nora Sanchez, Md Abu Shufean, Sarina Piha-Paul, Vivek Subbiah, David Hong, Mark Routbort, Russell Broaddus, and Kenna Shaw declare no conflict of interest. Dr. Funda Meric-Bernstam is conducting research sponsored by Aileron, AstraZeneca, Bayer, Calithera, CytoMx, Effector Pharmaceuticals, Debiopharma, Genentech, Novartis, PUMA, Taiho, and Zymeworks. She serves as a consultant for Dialecta and is a member on the Advisory Boards for Clearlight Diagnostics, Darwin Health, GRAIL, Inflection Biosciences, and Pieris. Dr. Gordon Mills serves as a consultant for Adventist Health, Allostery, AstraZeneca, Catena Pharmaceuticals, Critical Outcome Technologies, ImmunoMet, Lilly, Medimmune, Nuevolution, Novartis, Precision Medicine, Provista Diagnostics, Roche, Signalchem Lifesciences, Symphogen, Takeda/Millenium Parmaceuticals, Tau Therapeutics, and Tarveda. Dr. Mills holds stock options in Catena Pharmaceuticals, ImmunoMet, and Spindle Top Ventures. Dr. Mills is conducting research sponsored by Adelson Medical Research Foundation, AstraZeneca, Breast Cancer Research Foundation, Critical Outcomes Technology, Illumina, Ionis, Karus, Komen Research Foundation, Nanostring, and Takeda/Millenium Pharmaceuticals. Dr. John Mendelsohn is a compensated board member at Merrimack Pharmaceuticals, where he also owns stock. He also receives royalty payments from the University of California San Diego.

Figures

Fig 1.
Fig 1.
Requests received and annotations provided. The percentage of requests is shown for (A) each indicated tumor type (top 25) and (B) annotation type (full panel or select alterations). The number of annotations provided within each gene is shown for (C) full panel or (D) select alteration annotations. Genes with 20 or more annotations are shown.
Fig 2.
Fig 2.
Actionable genes and variants reported. (A) The percentage of annotations provided in an actionable or nonactionable gene, as defined at the time of annotation. The percentage of annotations delivered with the indicated actionable variant calls for (B) all or (C) only actionable genes. (D) The number of actionable annotations provided within each specified gene (minimum of 10 actionable annotations per gene). (E) The total number of annotations provided with an actionable variant call (blue bars) and the subset that is actionable (yellow bars) are shown per tumor type for types with at least 10 annotations.
Fig 3.
Fig 3.
Clinical decisions made for a subset of patients annotated with actionable variant calls. (A) Patients annotated in 2015 through clinician-initiated requests and for treatment planning conferences. The fraction of patients represented by the highest variant call (yellow column) and the corresponding fraction of patients with that call enrolled in a trial (gray column). (B) Accrual in genomically matched clinical trials on the basis of variant actionability (P < .001). (C) A subset of patients annotated in 2015 through a clinician-initiated request and for whom a survey was returned. The fraction of patients represented by the highest variant call (yellow column) and the corresponding fraction of patients with that call enrolled in a trial (gray column). Trial enrollment varied significantly by variant actionability (P < .001).
Fig 4.
Fig 4.
The distribution of genes that led to patient trial enrollment after annotation; 110 of 535 patients annotated by the Precision Oncology Decision Support team in 2015 enrolled in a genotype-matched trial on the basis of one of the 32 genes shown.
See this image and copyright information in PMC

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