Neurotrophic tropomyosin receptor kinase (NTRK) genes encode tropomyosin receptor kinases (TRK) that belong to a family of proteins involved in cell growth, maturation, and survival. In normal cells, these transmembrane… Click to show full abstract
Neurotrophic tropomyosin receptor kinase (NTRK) genes encode tropomyosin receptor kinases (TRK) that belong to a family of proteins involved in cell growth, maturation, and survival. In normal cells, these transmembrane proteins TRKA, TRKB, and TRKC, are activated by four neurotrophins, i.e., NT3, NT4, nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF), with high specificity and affinity to specific TRKs. Somatic fusions of NRTK genes have been observed in rare and several common types of cancer with varying prevalence. In this type of molecular alternation, the fusion protein mediates a ligand-independent tropomyosin kinase activity thus promoting constitutive cell proliferation. Highly effective first-generation TRK inhibitors such as Larotrectinib or Entrectinib, are associated with high response rates, and those patients who develop resistance are often given second-generation TRK inhibitors such as LOXO-195. That said, the knowledge associated with NTRK fusions, their gene partners, mechanism of developing resistance, and treatments are quickly evolving. For example, there are 40-50 ongoing clinical trials that has patients with NTRK fusions as an inclusion criterion. Moreover, given the different rates at which screening is done for gene fusions in patients with common cancers, a real-world analyses of patient diagnosis, procedures, treatments, and responses, categorized by care setting will be highly useful for care providers, as well for drug makers in designing clinical trials.Complementary to the individual large cohort studies, real-world data offers promise to fill in some of the gaps that might exist in characterizing a patient population, especially for newly discovered ones. Insights gained from using such data will supplement knowledge of KOLs and are likely to improve design of patient-centric trials. In addition, not having a holistic view of the patient population might lead to missed opportunities in catering to a segment of patients who might otherwise have benefitted from the therapy. In this presentation we focus on understanding cancer patient population better, especially those with gene fusions such as NTRKs through use of real-world data. We derive this through integration of structured de-identified patient data from an oncology diagnostic lab, claims and EHR using the cutting-edge Datavant tokenization technology. Overall, we characterized >1300 patients with fusion genes, and ~50 patients with NTRK fusions. We also compare the results on treatments, procedures, lab tests, and survival with published results from cBioPortal. We will present our findings with preliminary data, describe the data sources used, outline the technologies leveraged, and conclude with lessons learned. Citation Format: Sivakumar Gowrisankar, Jason Gagner, Martin Keywood, Angela Qu. Studying novel patient population using integrated real-world data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 927.
               
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