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PACA-CA

Member Programs

Pancreatic Cancer Harmonized "Omics" analysis for Personalized Treatment

Lead Institution

Ontario Institute for Cancer Research, Canada

BROWSE THE DATA

Country

Canada

Program Description

Across two major clinical trials (COMPASS and PanGen), we collect biopsies from patients with non-resectable pancreatic ductal adenocarcinoma (PDAC; locally advanced or metastatic disease) and profile the tumours for genomic or transcriptomic aberrations that might guide second-line treatment. Originating in Toronto and Vancouver, these trials have expanded to several sites across Canada, including eight cities (Calgary, Edmonton, Halifax, Kingston, Montreal, Ottawa, Toronto and Vancouver) in five provinces (Alberta, British Columbia, Nova Scotia, Ontario and Quebec). Together, this coast to coast Canadian initiative comprises EPPIC (Enhanced Pancreatic Cancer Profiling for Individualized Care) and PancONE (Pancreatic Canadian Oncology Network). To date, we have completed whole genome and RNA sequencing of more than 250 cases, with tumour enrichment by laser capture microdissection performed on many cases. Sequencing and bioinformatics analysis is performed at the Ontario Institute for Cancer Research (OICR) in Toronto and the BC Cancer Genome Sciences Centre (GSC) in Vancouver. Our combined goal is to explore new treatment options and improve patient outcome.

Program Goals and Expected Outcomes

The Pancreatic Cancer Project in Canada is a world-leading, high content, profiling program of advanced pancreatic cancer. It is tightly integrated into real-time patient management, with seminal findings that help in the understanding of patient sensitivity and resistance to standard-of-care first line therapy. We also aim to identify molecular aberrations to help guide second-line treatment selection (i.e. personalized medicine).

What gaps in existing knowledge will be addressed by the study?

We aim to identify subsets of patients that are likely to respond to specific treatments, either in a first-line or second-line setting. These patients may be selected based on transcriptomic features, gene expression profiles or other molecular aberrations. Such biomarkers are not currently used to direct drug selection for patients in an unbiased manner.