Precision oncology has advanced rapidly over the last few decades, with breakthroughs in genetic sequencing, tumour modelling, and RNA therapeutics reshaping how cancers are diagnosed and treated. Yet rare cancers remain underserved, constrained by the limited genomic data resulting from small patient populations.
The Jerry Pelletier Initiative (JPI) is helping tackle this challenge by creating a precision oncology pipeline for early identification and analysis of rare cancers. Led by Principal Investigators Dr. Mark Lathrop and Dr. Morag Park, the initiative is supported by a team of co-investigators and collaborators, including our Tech Dev team at C3G.
C3G’s Role in building the precision oncology pipeline
C3G’s participation in the JPI project is being led by Vinicius Fava, with contributions from Robert Eveleigh, Mareike Janiak, Jose Hector Galvez, and Julian Martinez. Their work has focused on developing a pipeline for whole‑genome sequencing (WGS) analysis of rare cancers, enabling the reporting of somatic mutations, structural variants, and other clinically relevant and actionable genomic features.
To date, the analysis pipeline has successfully processed 5 rare cancer samples, with an additional 10 scheduled for the year and can generate clinic-ready reports approximately 7 days after sample collection, with the bioinformatics pipeline only taking around 24 hours to run. This allows clinicians to gain insights sooner and more rapidly explore potential treatment options.
Available through C3G’s GenPipes, the pipeline uses nanopore WGS paired tumour–normal sequencing as input and produces a scientific report developed using feedback from clinicians. It can also provide potential approved therapies through the use of the OncoKB Knowledge Base.
In addition to the WGS pipeline, Vinicius is building a framework to analyze single‑cell long‑read and short‑read datasets. This effort helps determine which technologies best capture features such as transcript isoforms and tumour‑specific gene fusions, information that is crucial for better biological understanding of rare cancers and for informing future targeted therapeutic strategies.