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Details

Autor(en) / Beteiligte
Titel
Recommended testing algorithms for NTRK gene fusions in pediatric and selected adult cancers: Consensus of a Singapore Task Force
Ist Teil von
  • Asia-Pacific journal of clinical oncology, 2022-08, Vol.18 (4), p.394-403
Ort / Verlag
Australia: Wiley Subscription Services, Inc
Erscheinungsjahr
2022
Quelle
Wiley-Blackwell Journals
Beschreibungen/Notizen
  • The occurrence of neurotrophic tyrosine receptor kinase (NTRK) gene fusions in a wide range of tumor types presents an attractive opportunity for using a tropomyosin receptor kinase (TRK) inhibitor as cancer therapy. Recent clinical studies have demonstrated highly efficacious outcomes associated with the use of TRK inhibitors, such as larotrectinib and entrectinib in NTRK fusion‐bearing cancers, in both adult and pediatric populations. While NTRK gene fusions are commonly found in some uncommon adult and pediatric malignancies, they are also found, albeit rarely, in a wide range of more common malignancies. The potential value of testing for NTRK gene fusions in practically all advanced malignancies is underpinned by the remarkable therapeutic outcomes that TRK inhibitors offer. This requirement presents practical and financial challenges in real‐world oncological practice. Furthermore, different testing platforms exist to detect NTRK gene fusions, each with its advantages and disadvantages. It is, therefore, imperative to develop strategies for NTRK gene fusion testing in an attempt to optimize the use of limited tissue specimen and financial resources, and to minimize the turnaround time. A multidisciplinary task force of Singapore medical experts in both public and private sectors was convened in late 2020 to propose testing algorithms for adult colorectal tumors, sarcomas, non‐small cell lung cancer, and pediatric cancers, with particular adaptation to the Singapore oncological practice. The recommendations presented here highlight the heterogeneity of NTRK‐fusion positive cancers, and emphasize the need to customize the testing methods to each tumor type to optimize the workflow.

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