Basal Levels of DNA Damage Detected by Micronuclei and Comet Assays in Untreated Breast Cancer Patients and Healthy Women

Overview

Journal Clin Exp Med

Specialty General Medicine

Date 2009 Nov 11

PMID 19902326

Citations 15

Authors

Raquel A Santos

Ana Claudia Teixeira

Monica B Mayorano

Helio H A Carrara

Jurandyr M Andrade

Catarina S Takahashi

Affiliations

Soon will be listed here.

Abstract

Breast cancer is the second most frequent type of cancer worldwide and is the most common malignant disease among women. Risk factors for breast cancer include early menarche, late menopause, hormonal therapies, exposure to environmental pollutants, smoking and alcohol use. However, increased or prolonged exposure to estrogen is the most important risk factor. It has been suggested that accumulation of DNA damage may contribute to breast carcinogenesis. Epidemiological studies suggest that cytogenetic biomarkers such as micronuclei in peripheral blood lymphocytes may predict cancer risk because they indicate genomic instability in target tissues. The objective of the present study was to evaluate the frequencies of micronuclei and the extent of DNA damage detected by comet assay in peripheral blood lymphocytes of untreated breast cancer patients and healthy women. The study was conducted using peripheral blood lymphocytes from 45 women diagnosed for Ductal "in situ" or invasive breast carcinoma and 85 healthy control women. Micronuclei and comet assays were performed to detect spontaneous DNA damage. The results showed that micronuclei frequencies and tail intensity, detected by comet assay, were significantly higher in the breast cancer group than in controls. The levels of DNA damage were similar in smokers and non-smokers, and aging did not influence the frequencies of micronuclei or tail intensity values observed in either group. In conclusion, the present work demonstrates higher levels of DNA damage in untreated breast cancer patients than in healthy women.

Citing Articles

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Penalized negative binomial models for modeling an overdispersed count outcome with a high-dimensional predictor space: Application predicting micronuclei frequency.

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