In search of novel germline mutations underlying childhood and early onset cancer, we have identified, using nationwide population-based registry data, a cohort of more than 9000 early onset cancer patients and their 58,000 relatives at high risk of familial cancer based on tumor or patient-related factors (tumor type, age at diagnosis, comorbidities) or family history. Using cancer epidemiological methods, registry data analysis has quantified risk of cancer in relatives of early onset cancer patients as well as risk of second cancers. Blood samples have been collected for whole genome sequencing to identify novel germline mutations.
To investigate the use of liquid biopsy in monitoring and early detection, we study cohorts of cancer patients as well as individuals with known cancer predisposition or who are at risk of cancer based on former history. We collect serial plasma samples from these patients undergoing surveillance to see if ctDNA levels correlate with traditional radiological examinations and laboratory results. We hypothesize that such an assay will be able to detect the presence of cancer before it becomes symptomatic and, when combined with current screening protocols, could improve outcomes for patients with increased risk for cancer.
Colorectal adenocarsinoma is a rare diagnosis in the pediatric and AYA (adolescents and young adults) age group, making up less than 1 % of all cancer cases in children under 20 years. A majority of the cases present with advanced disease in diagnosis and overall survival in patients with stage III and stage IV disease being as low as 30 % and 7 %. Previous case reports suggest that poorly differentiated, mucinous and signet ring cell histologies are more prevalent in this patient group and likely contribute to the poorer outcomes. Our aim is to describe the genomic landscape in the pediatric and AYA group by whole exome sequencing of paired tumour-normal tissue samples to better understand the reasons behind the worse outcomes. This project is a collaboration with Dana Farber Cancer Institute.
The reproductive history of a woman has a long lasting impact on her future risk of cancer. Exposures during pregnancy may also have an impact on later cancer risk in the offspring. We are interested of using data from nationwide population based registries to investigate this phenomenon, taking advantage of machine learning models and causal inference methodology.