London Calling 2023: Low-cost nanopore transcriptomics enables robust characterisation of diverse tumour types in low-resource settings

Our aim is to apply low-coverage nanopore transcriptome sequencing to address cancer outcome disparities in low/middle-income countries (LMIC), particularly for children. We performed cDNA sequencing of over 700 pediatric cancer specimens, including acute leukemias, lymphomas, non-central nervous system solid tumors, and brain tumors. We developed a machine-learning classification model that is able to robustly classify these samples according to their primary tumour type and clinically relevant  genomic subtypes, despite huge variation in sequencing depth (over three orders of magnitude), sample and RNA quality (e.g. fresh-frozen and formalin-fixed paraffin-embedded), and processing. In collaboration with St. Jude Children’s Research Hospital, USA and collaborators in Malawi, Pakistan, India, Brazil, and  Guatemala, we have demonstrated the technical feasibility of this approach in diverse LMIC settings.