Neurotrophic tropomyosin receptor kinase (NTRK) gene fusions are rare oncogenic drivers in solid tumours. This study aimed to interrogate a large real-world database of comprehensive genomic profiling data to describe the genomic landscape and prevalence of NTRK gene fusions. NTRK fusion-positive tumours were identified from the FoundationCORE® database of >295,000 cancer patients. We investigated the prevalence and concomitant genomic landscape of NTRK fusions, predicted patient ancestry and compared the FoundationCORE cohort with entrectinib clinical trial cohorts (ALKA-372-001 [EudraCT 2012-000148-88]; STARTRK-1 [NCT02097810]; STARTRK-2 [NCT02568267]). Overall NTRK fusion-positive tumour prevalence was 0.30% among 45 cancers with 88 unique fusion partner pairs, of which 66% were previously unreported. Across all cases, prevalence was 0.28% and 1.34% in patients aged ≥18 and <18 years, respectively; prevalence was highest in patients <5 years (2.28%). The highest prevalence of NTRK fusions was observed in salivary gland tumours (2.62%). Presence of NTRK gene fusions did not correlate with other clinically actionable biomarkers; there was no co-occurrence with known oncogenic drivers in breast, or colorectal cancer (CRC). However, in CRC, NTRK fusion-positivity was associated with spontaneous microsatellite instability (MSI); in this MSI CRC subset, mutual exclusivity with BRAF mutations was observed. NTRK fusion-positive tumour types had similar frequencies in FoundationCORE and entrectinib clinical trials. NTRK gene fusion prevalence varied greatly by age, cancer type and histology. Interrogating large datasets drives better understanding of the characteristics of very rare molecular subgroups of cancer and allows identification of genomic patterns and previously unreported fusion partners not evident in smaller datasets.

Alternative statistical proposals have been developed to make a better use of the complex data generated by phase I trials. Their applications require a close collaboration between all actors of early phase clinical trials.

The results of this Phase I trial demonstrate the safety and preliminary antitumor activity of LY3039478 as a single agent. The clinical pharmacodynamic effect of LY3039478 on Notch targeted genes is considered as a major strength of this study. Overall, this work supports the rational for targeting Notch signalling and further implicates aberrant Notch signalling in tumor physiology.

Aims: The workload pressure on medical oncologists will increase in the near future. There are no comprehensive data available about the current workload of medical oncologists in Europe. Here we report the European results of a global survey of the workload of medical oncologists. Materials and methods: An online survey was distributed through a snowball method via national oncology societies to chemotherapy-prescribing physicians in 21 European countries. We compared the workload of medical oncologists in Eastern European countries (EECs) and Western European countries (WECs). The primary measure of workload was the annual number of new cancer patient consults seen per oncologist. Results: In total, 495 oncologists from 16 European countries completed our survey: 100 from seven EECs and 395 from nine WECs. The median number of annual consults per medical oncologist was 225 in EECs compared with 175 in WECs (P < 0.001). The proportion of medical oncologists seeing more than 300 consults/year was 35% (35/100) in EECs compared with 18% (68/395) in WECs. The median number of patients seen in a full day clinic was 25 in EECs and 15 in WECs (P < 0.001). Eastern European medical oncologists reported spending a median of 25 min per new consultation compared with 45 min in WECs (P < 0.001). The top two reported barriers in both EECs and WECs to patient care were high clinical volumes and insufficient time for reading. Conclusion:The clinical workload of medical oncologists in EECs was substantially higher than in WECs. European health policymakers and educators need to address existing disparities in the workload of medical oncologist, undertake plans for future workforce supply and consider alternative models of care.

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