Abstract
Obese premenopausal women with breast cancer have poorer prognosis for long term survival, in part because their tumors are larger at the time of diagnosis than are found in normal weight women. Whether larger tumor mass is due to obesity-related barriers to detection or to effects on tumor biology is not known. This study used polygenic models for obesity and breast cancer to deconstruct this question with the objective of determining whether cell autonomous mechanisms contribute to the link between obesity and breast cancer burden. Assessment of the growth rates of 259 chemically induced mammary carcinomas from rats sensitive to dietary induced obesity (DS) and of 143 carcinomas from rats resistant (DR) to dietary induced obesity revealed that tumors in DS rats grew 1.8 times faster than in DR rats. This difference may be attributed to alterations in cell cycle machinery that permit more rapid tumor cell accumulation. DS tumors displayed protein expression patterns consistent with reduced G1/S checkpoint inhibition and a higher threshold of factors required for execution of the apoptotic cell death pathway. These mechanistic insights identify regulatory targets for life style modifications or pharmacological interventions designed to disrupt the linkage between obesity and tumor burden.
Highlights
There is a longstanding awareness within the public health community of the importance of identifying subpopulations of individuals that respond differently to various environmental exposures including those that relate to energy balance [1]
Mammary carcinogenesis was induced by injecting rats with the carcinogen MNU (50 mg/kg) carcinogenesis was induced by injecting with the carcinogen MNU
Due to the magnitude of the effect on tumor mass that was observed in tumor bearing dietary obesity sensitive (DS) versus dietary obesity resistant (DR) rats, we decided to deconstruct the mechanism behind increased tumor size in a premenopausal model for obesity and breast cancer
Summary
There is a longstanding awareness within the public health community of the importance of identifying subpopulations of individuals that respond differently to various environmental exposures including those that relate to energy balance [1]. The Gail model was developed in 1989 as a tool to model the influence of risk factors, including current age, age at menarche, parity, and family history, among other factors, on 5-year and lifetime invasive breast cancer risk [8]. Consistent with this observation [7], we recently reported that in a polygenic premenopausal model for obesity and breast cancer, the occurrence of breast cancer is markedly increased in rats that are susceptible to dietary induced obesity versus those that are resistant [9]
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