JCO Precision Oncology, JCO Clinical Cancer Informatics Feature Joint Special Series to Increase Accessibility of Next-Generation Sequencing in Community Oncology

Jan 15, 2021

By Geraldine Carroll, ASCO Publishing
Emerging technologies that fully leverage next-generation sequencing (NGS) in oncology will ease information overload suffered by oncology practitioners and fulfill the potential of these complicated—but treatment-changing—tumor genomics breakthroughs for patients.
Advances in NGS and bioinformatics have transformed cancer care and enabled oncologists and clinical trial investigators to individualize targeted therapies for specific patients based on their tumor genomics. The multiple data streams that are being used in precision medicine have rapidly evolved to include genomic molecular profiles, biometrics, data from wearable devices, and patient-reported outcomes. However, the oncology community faces challenges on how best to operationalize or translate this process to make it accessible and tailored to the needs and bandwidth of a typical oncology practice. 
A Special Series jointly published in JCO Precision Oncology and JCO Clinical Cancer Informatics takes on these challenges and includes guidance on factors and decision-making processes for selecting the right platform, how to reduce expenses from manual burdens, and how to allocate resources to successfully enable NGS for clinical cancer care. 
“We technically have the ability to do next-generation sequencing and gather large complicated data, but we need to understand how best to manage that data, and interpret it so patients with cancer can benefit from it,” said James M. Ford, MD, FASCO, editor in chief of JCO Precision Oncology and co-editor of the series.
It is crucial, Dr. Ford said, that oncology practices effectively navigate NGS platforms to truly reap the benefits of this technology for patients wherever they receive care. Oncologists in large practices or who are closely linked to medical schools and research centers are typically more accustomed to harnessing data-heavy resources and are more likely to have the computing technology required to fully put the data from the latest advances in tumor genomics into practice for individual patients. But small practices or those outside major referral centers, for example, often find it far more difficult to process the latest developments and to quickly interpret mountains of data for treatment plans.
The series tackles the data challenges arising from NGS, and the barriers that exist for implementing interpreted results for use in clinical decision-making. It also proposes solutions, including universal data standards applications that use application programming interfaces. 
Dr. Ford said that oncologists are frequently dealing with information overload, and systems are needed for the individual practitioner that help distill a complicated medical report into usable suggestions and help facilitate taking action on those suggestions. Several articles in the series share artificial intelligence (AI) approaches to manage data and how to make this simple and actionable for practitioners.
“To get a test report that is 17 pages long and lists 20 genes that changed and for each of those 10 potential clinical trials… it’s information overload,” Dr. Ford said. “It’s not very helpful for a practitioner in Kansas City, for example, to have 10 pages of clinical trials all over the country but not be able to get their patient on a local trial.”
With clinical trial eligibility being increasingly predicated on NGS testing, the series notes several computational clinical trial matching platforms that leverage NGS data to more efficiently access eligibility criteria. These platforms are designed to seamlessly integrate patient demographic, clinical, and laboratory data from electronic health records and match patient and trial locations, which is a major barrier to enrollment.
The series includes recommendations for adopting data standards and sharing data in computable formats, noting that the adoption of data standards, including HL7 FHIR and mCODE, by all entities that generate, transmit, and receive health information will also facilitate the implementation of precision oncology.
“The call to action is to do better. The proof of principle is that personalized medicine can work for oncology and we have examples of it, but the question now is how do we make this more accessible and more relevant to patients in the community oncology setting and not just those on a trial in a well-established academic medical center,” Dr. Ford said.

ASCO Journals Editorial Fellowship

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