Johnson Amber, Khotskaya Yekaterina B, Brusco Lauren, Zeng Jia, Holla Vijaykumar, Bailey Ann M, Litzenburger Beate C, Sanchez Nora, Shufean Md Abu, Piha-Paul Sarina, Subbiah Vivek, Hong David, Routbort Mark, Broaddus Russell, Mills Shaw Kenna R, Mills Gordon B, Mendelsohn John, Meric-Bernstam Funda
Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
JCO Precis Oncol. 2017;2017. doi: 10.1200/PO.17.00036. Epub 2017 Sep 13.
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.
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.
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 (). Actionable alterations in , , and 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.
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.
精准肿瘤学因缺乏决策支持而受到阻碍，难以确定肿瘤基因组改变的功能和治疗意义以及相关的临床可用选项。为了弥补这一知识差距，我们成立了精准肿瘤学决策支持（PODS）团队，该团队在改变层面提供注释，随后确定临床决策是否受到影响。
根据变异的已知或潜在功能和/或治疗意义对基因组改变进行注释，以确定其可操作性。对2015年注释的部分患者的病历进行人工审核，以评估试验入组情况。开展了一项基于网络的调查，以了解未采用基因型匹配疗法的原因。
PODS处理了1197例患者49种肿瘤类型的1669项注释请求，涉及4084处改变（2254处独特改变）。对669例患者的2444条注释包含可操作变异调用：32.5%可操作，9.4%可能可操作，29.7%未知，28.4%不可操作。66%的患者至少有一处可操作/可能可操作的改变。注释的患者中有20.6%（110/535）入组了基因型匹配试验。有可操作/可能可操作改变的患者的试验入组率（92/333，27.6%）显著高于有未知改变（16/136，11.8%）和不可操作改变（2/66，3%）的患者（）。、和中的可操作改变最常导致入组基因型匹配试验。临床医生列举了有可操作改变的患者未参加试验的各种原因。
超过一半的注释改变意义未知或不可操作。当注释支持可操作性时，医生更有可能让患者参加基因型匹配试验。需要未来的研究来证明决策支持对试验入组和肿瘤学结果的影响。
