Application of artificial neural networks to link genetic and environmental factors to DNA methylation in colorectal cancer.
OBJECTIVE
We applied artificial neural networks (ANNs) to understand the connections among polymorphisms of genes involved in folate metabolism, clinico-pathological features and promoter methylation levels of MLH1, APC, CDKN2A(INK4A), MGMT and RASSF1A in 83 sporadic colorectal cancer (CRC) tissues, and to link dietary and lifestyle factors with gene promoter methylation.


METHODS
Promoter methylation was assessed by means of methylation-sensitive high-resolution melting and genotyping by PCR-RFLP technique. Data were analyzed with the Auto Contractive Map, a special kind of ANN able to define the strength of the association of each variable with all the others and to visually show the map of the main connections.


RESULTS
We observed a strong connection between the low methylation levels of the five CRC genes and the MTR 2756AA genotype. Several other connections were revealed, including those between dietary and lifestyle factors and the methylation levels of CRC genes.


CONCLUSIONS
ANNs revealed the complexity of the interconnections among factors linked to DNA methylation in CRC.
Department of Translational Research & New Technologies in Medicine & Surgery, Division of Medical Genetics, University of Pisa, Medical School, Via Roma 55, 56126 Pisa, Italy.
Fabio
F
Coppedè
Enzo
E
Grossi
Angela
A
Lopomo
Roberto
R
Spisni
Massimo
M
Buscema
Lucia
L
Migliore
D000368:Aged; D015179:Colorectal Neoplasms / Q000235:genetics*; D019175:DNA Methylation; D004032:Diet; D005260:Female; D005492:Folic Acid / Q000378:metabolism; D059647:Gene-Environment Interaction; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D011110:Polymorphism, Genetic; D011401:Promoter Regions, Genetic
D005492:Folic Acid
APC; CDKN2A; DNA methylation; MGMT; MLH1; RASSF1A; artificial neural networks; colorectal cancer; folate; polymorphisms