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The genetic heterogeneity of colorectal cancer predisposition - guidelines for gene discovery

View Article: PubMed Central - PubMed

ABSTRACT

Background: Colorectal cancer (CRC) is a cumulative term applied to a clinically and genetically heterogeneous group of neoplasms that occur in the bowel. Based on twin studies, up to 45 % of the CRC cases may involve a heritable component. Yet, only in 5–10 % of these cases high-penetrant germline mutations are found (e.g. mutations in APC and DNA mismatch repair genes) that result in a familial aggregation and/or an early onset of the disease. Genome-wide association studies have revealed that another ~5 % of the CRC cases may be explained by a cumulative effect of low-penetrant risk factors. Recent attempts to identify novel genetic factors using whole exome and whole genome sequencing has proven to be difficult since the remaining, yet to be discovered, high penetrant CRC predisposing genes appear to be rare. In addition, most of the moderately penetrant candidate genes identified so far have not been confirmed in independent cohorts. Based on literature examples, we here discuss how careful patient and cohort selection, candidate gene and variant selection, and corroborative evidence may be employed to facilitate the discovery of novel CRC predisposing genes.

Conclusions: The picture emerges that the genetic predisposition to CRC is heterogeneous, involving complex interplays between common and rare (inter)genic variants with different penetrances. It is anticipated, however, that the use of large clinically well-defined patient and control datasets, together with improved functional and technical possibilities, will yield enough power to unravel this complex interplay and to generate accurate individualized estimates for the risk to develop CRC.

No MeSH data available.


Related in: MedlinePlus

Strategy for (colorectal) cancer predisposition gene identification. Commonalities of recently published successful MPS studies to identify cancer predisposition genes in hereditary CRC and potential improvements as described in the main text
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Fig3: Strategy for (colorectal) cancer predisposition gene identification. Commonalities of recently published successful MPS studies to identify cancer predisposition genes in hereditary CRC and potential improvements as described in the main text

Mentions: Beyond the successful identification of novel candidate genes for the rare cancer syndromes mentioned above, the methodologies and guidelines applied to these syndromes have benefited largely from those used in syndromes with Mendelian inheritance patterns [106, 107, 129]. As such, the success rates appear to be similar to the ~0.5 genes identified per disease studied with a Mendelian inheritance pattern [106]. The methodologies and criteria used to study these diseases encompass a couple of distinct entities, i.e., (1) patient and cohort selection, (2) candidate gene and variant selection and (3) corroborative evidence to support causality, including co-segregation, recurrence, functional and somatic evidence (Fig. 3).Fig. 3


The genetic heterogeneity of colorectal cancer predisposition - guidelines for gene discovery
Strategy for (colorectal) cancer predisposition gene identification. Commonalities of recently published successful MPS studies to identify cancer predisposition genes in hereditary CRC and potential improvements as described in the main text
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC5121185&req=5

Fig3: Strategy for (colorectal) cancer predisposition gene identification. Commonalities of recently published successful MPS studies to identify cancer predisposition genes in hereditary CRC and potential improvements as described in the main text
Mentions: Beyond the successful identification of novel candidate genes for the rare cancer syndromes mentioned above, the methodologies and guidelines applied to these syndromes have benefited largely from those used in syndromes with Mendelian inheritance patterns [106, 107, 129]. As such, the success rates appear to be similar to the ~0.5 genes identified per disease studied with a Mendelian inheritance pattern [106]. The methodologies and criteria used to study these diseases encompass a couple of distinct entities, i.e., (1) patient and cohort selection, (2) candidate gene and variant selection and (3) corroborative evidence to support causality, including co-segregation, recurrence, functional and somatic evidence (Fig. 3).Fig. 3

View Article: PubMed Central - PubMed

ABSTRACT

Background: Colorectal cancer (CRC) is a cumulative term applied to a clinically and genetically heterogeneous group of neoplasms that occur in the bowel. Based on twin studies, up to 45 % of the CRC cases may involve a heritable component. Yet, only in 5–10 % of these cases high-penetrant germline mutations are found (e.g. mutations in APC and DNA mismatch repair genes) that result in a familial aggregation and/or an early onset of the disease. Genome-wide association studies have revealed that another ~5 % of the CRC cases may be explained by a cumulative effect of low-penetrant risk factors. Recent attempts to identify novel genetic factors using whole exome and whole genome sequencing has proven to be difficult since the remaining, yet to be discovered, high penetrant CRC predisposing genes appear to be rare. In addition, most of the moderately penetrant candidate genes identified so far have not been confirmed in independent cohorts. Based on literature examples, we here discuss how careful patient and cohort selection, candidate gene and variant selection, and corroborative evidence may be employed to facilitate the discovery of novel CRC predisposing genes.

Conclusions: The picture emerges that the genetic predisposition to CRC is heterogeneous, involving complex interplays between common and rare (inter)genic variants with different penetrances. It is anticipated, however, that the use of large clinically well-defined patient and control datasets, together with improved functional and technical possibilities, will yield enough power to unravel this complex interplay and to generate accurate individualized estimates for the risk to develop CRC.

No MeSH data available.


Related in: MedlinePlus