Objectives

The main objective of this Action is to comprehensively understand the impact of inherited susceptibility in CRC for profiling individual disease risk and performing early screening and treatment monitoring. By doing so, new molecular biomarkers will be implemented and validated for personalized CRC medicine.

The following specific objectives will be pursued in order to achieve the previous general aim:

  1. 1

    Identification of new CRC susceptibility variants:

    A polygenic model of inherited susceptibility to CRC implies the co-inheritance of multiple risk variants. So far, 20 common, low-penetrance genetic variants for CRC susceptibility have been identified by GWAS. This Action will permit to boost sample size and statistical power (participating cohorts sum up more than 50,000 cases and 50,000 controls) and, therefore, it is very likely that additional genetic variants linked to CRC will be identified. Large-scale meta-analyses of existing and newly generated GWAS data will be performed and replication of initial GWAS findings in additional cohorts will be used to robustly confirm those genetic variants that participate in CRC susceptibility.

  2. 2

    Functional links for CRC susceptibility variants:

    Most GWAS variants are unlikely to alter protein function and fine mapping and functional studies will be used to identify a correlated functional variant. The identification of the functional variation that causes increased CRC risk may lead to the development of new means of preventing the disease. However, the journey from the associated polymorphism to functional variant is not simple and will require additional work. In order to perform an initial search for readily identifiable functional variants, fine mapping in the regions close to each disease-associated single nucleotide polymorphism (SNP) or copy number variant (CNV) should be undertaken, enriching for variants in strong linkage disequilibrium (LD) with that SNP and with possible functional effects. Basic functional work should also be performed, such as assessing the levels of mRNAs and proteins in each region in patients of known genotypes, as well as more complex studies such as chromatin mapping, gene reporter and allele-specific expression experiments.

  3. 3

    Genetic variants involved in CRC survival and treatment toxicity:

    CRC genetic susceptibility variants could also act as biomarkers for CRC survival and treatment response. For instance, inherited genetic variants can modulate the pharmacokinetics/pharmacodynamics of drugs used in CRC treatment by substantially affecting individual response and toxicity to chemotherapy. Therefore, GWAS data will be analyzed regarding CRC survival and treatment toxicity in order to identify genetic variants linked to differential prognosis and adverse drug reactions.

  4. 4

    Genetic variants enriched in crc subgroups:

    The impact of CRC susceptibility genetic variation will not be universally generic and some of the risk variants will impact preferentially on CRC subtypes, such as early-onset or microsatellite-unstable CRC (MSI+ CRC). If some of the CRC genetic susceptibility variants appear to be associated with some clinical and familial features, it could have potential important implications for screening and surveillance strategies for this disease.

  5. 5

    New predisposition genes for crc in families with unknown genetic basis:

    Next generation sequencing will be useful to identify new CRC predisposition genes in selected high-risk and early-onset families with unknown genetic basis from the participating cohorts.

  6. 6

    Interactions between crc susceptibility variants and environment:

    CRC risk is undoubtedly determined by complex interactions between genetic and lifestyle/dietary risk factors. Epidemiological studies have established several dietary risk factors for colorectal neoplasia; these include low vegetable and high red meat consumption and micronutrient deficiency and excessive alcohol intake. CRC genetic susceptibility variants are thus likely to interact with these environmental lifestyle risk factors to modify risk and they should be incorporated into models of predisposition.

  7. 7

    High-risk crc profile of inherited variants by statistical modeling:

    Besides gene-environment interactions, it is also entirely conceivable that epistatic interactions between CRC genetic susceptibility variants may exist. A high-risk CRC profile using mentioned parameters could be developed using data from all participating cohorts and be very useful as a molecular tool for personalized CRC medicine.

COST is supported by the EU Framework Programme Horizon 2020