TY - JOUR
T1 - Association between lifestyle factors and CpG island methylation in a cancer-free population
AU - Brait, Mariana
AU - Ford, Jean G.
AU - Papaiahgari, Srinivas
AU - Garza, Mary A.
AU - Lee, Jin I.
AU - Loyo, Myriam
AU - Maldonado, Leonel
AU - Begum, Shahnaz
AU - McCaffrey, Lee
AU - Howerton, Mollie
AU - Sidransky, David
AU - Emerson, Mark R.
AU - Ahmed, Saifuddin
AU - Williams, Carla D.
AU - Hoque, Mohammad Obaidul
PY - 2009/11
Y1 - 2009/11
N2 - Background: Many risk factors have been associated with cancer, such as age, family history, race, smoking, high-fat diet, and poor nutrition. It is important to reveal the molecular changes related to risk factors that could facilitate early detection, prevention, and overall control of cancer. Methods: We selected six cancer-specific methylated genes that have previously been reported in primary tumors and have also been detected in different bodily fluids of cancer patients. Here, we used quantitative fluorogenic real-time methylation-specific PCR in plasma DNA samples for the detection of methylation changes from an asymptomatic population who do not have any known cancer. Results: The promoter methylation frequencies of the studied genes were as follows: APC (7%), CCND2 (22%), GSTP1 (2%), MGMT (9%), RARβ2 (29%), and P16 (3%). Promoter methylation of at least one of the genes analyzed was observed in ∼46% (72 of 157) of the samples by binary dichotomization. Promoter hypermethylation of at least two genes was detected in 17% (26 of 157) of the samples. RARβ2 methylation was observed in 45% of subjects who had a high-fat diet in contrast with those who had a low-fat diet (23%; P =0.007). Discussion: Our findings may help to elucidate early methylation changes that may lead to cancer development. These methylation changes could be due to exposure to risk factors and may be useful for cancer prevention measures such as changes in lifestyle. Longitudinal follow-up of a high-risk population is needed to understand the association of methylation of candidate genes in cancer development.
AB - Background: Many risk factors have been associated with cancer, such as age, family history, race, smoking, high-fat diet, and poor nutrition. It is important to reveal the molecular changes related to risk factors that could facilitate early detection, prevention, and overall control of cancer. Methods: We selected six cancer-specific methylated genes that have previously been reported in primary tumors and have also been detected in different bodily fluids of cancer patients. Here, we used quantitative fluorogenic real-time methylation-specific PCR in plasma DNA samples for the detection of methylation changes from an asymptomatic population who do not have any known cancer. Results: The promoter methylation frequencies of the studied genes were as follows: APC (7%), CCND2 (22%), GSTP1 (2%), MGMT (9%), RARβ2 (29%), and P16 (3%). Promoter methylation of at least one of the genes analyzed was observed in ∼46% (72 of 157) of the samples by binary dichotomization. Promoter hypermethylation of at least two genes was detected in 17% (26 of 157) of the samples. RARβ2 methylation was observed in 45% of subjects who had a high-fat diet in contrast with those who had a low-fat diet (23%; P =0.007). Discussion: Our findings may help to elucidate early methylation changes that may lead to cancer development. These methylation changes could be due to exposure to risk factors and may be useful for cancer prevention measures such as changes in lifestyle. Longitudinal follow-up of a high-risk population is needed to understand the association of methylation of candidate genes in cancer development.
UR - http://www.scopus.com/inward/record.url?scp=72749090135&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=72749090135&partnerID=8YFLogxK
U2 - 10.1158/1055-9965.EPI-08-1245
DO - 10.1158/1055-9965.EPI-08-1245
M3 - Article
C2 - 19861513
AN - SCOPUS:72749090135
SN - 1055-9965
VL - 18
SP - 2984
EP - 2991
JO - Cancer Epidemiology Biomarkers and Prevention
JF - Cancer Epidemiology Biomarkers and Prevention
IS - 11
ER -