Ontario Familial Colon Cancer Registry (OFCCR)

Aims/Goals:

  1. To determine the molecular (N=200) and histologic signatures present in population-based YOCRCs through somatic mutation, whole transcriptomics, and pathologist-supervised digital H&E tumor profiling.  

  1. To correlate unknown molecular and histologic signatures from Aim 1 with known etiologic (environmental and lifestyle) risk factors from our heavily curated, epidemiologically informed cohort to determine new YOCRC signatures. 

  1. To determine the molecular and/or histologic signatures that change in prevalence in YOCRCs diagnosed over a 10-year period i.e., identify temporal molecular and histologic signatures. These will be compared with existing publicly available database through the TCGA (The Cancer Genome Atlas). 

 

Summary:

Recent work has shown that somatic profiling of cancer genomes and transcriptomes can provide a historical record of the mutational processes, both endogenous and exogenous, that were active in tumor initiation and progression, providing a characteristic “signatures” for each cancer. The potential of machine learning assessment of digital images of hematoxylin and eosin (H&E)-stained sections to identify histologic profiles or “signatures” offers novel approaches to detail features of the tumor microenvironment. We hypothesize that a comprehensive tumor profiling approach generating somatic mutation, and whole transcriptomics, and deep learning-derived “histologic signatures” (Aim 1) of 200 richly characterized YOCRCs diagnosed, excluded for known high penetrance monogenic CRC and polyposis genes, over a 10-year period will identify signatures that have increased over this timeframe (temporal signatures; Aim 2). These temporal signatures will be associated with established etiological mechanisms (e.g. pks+ E.coli somatic mutation signature or assessed for novel associations with modifiable environmental/lifestyle risk factors (Aim 3).

Key Researchers