Central Obesity in Relation to Breast Cancer Risk and Survival
Central Obesity in Relation to Breast Cancer Risk and Survival
批准号:
9918268
负责人:
Serena Catherine Houghton
金额:
$6.93万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-04-25 至 2021-07-24
关键词:
AddressAndrogen ReceptorAndrogensBiologicalBody mass indexBreast Cancer PreventionBreast Cancer Risk FactorBreast CarcinogenesisCancer PrognosisCentral obesityCharacteristicsChemopreventionDataDevelopmentDiagnosisEstrogen Receptor StatusEstrogen ReceptorsEstrogensEtiologyHigh Risk WomanHip region structureHormonalHormonesInflammatoryInsulinInsulin ReceptorLeadLinkMammary NeoplasmsMeasurementMeasuresMedical RecordsMenopausal StatusMetabolicMorbidity - disease rateMutationNurses&apos Health StudyObesityPIK3CA genePTEN genePathway interactionsPharmaceutical PreparationsPhysical activityPostmenopausePremenopauseProgesteroneProspective cohortQuestionnairesReportingResearchResourcesRiskRisk FactorsRisk ReductionRoleSample SizeSubgroupTimeTumor MarkersTumor TissueVisceral fatWaist-Hip RatioWomanWorkadipokinesbreast cancer diagnosisbreast cancer survivalburden of illnesscancer survivalcarcinogenesiscytokineepidemiology studyfollow-uphigh riskimprovedinsightinsulin signalingmalignant breast neoplasmmodifiable riskmolecular markermolecular subtypesmortalityreceptor expressionrisk prediction modelscreeningtumorwaist circumference
中文摘要
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英文摘要
PROJECT SUMMARY/ ABSTRACT
Given the substantial morbidity and mortality associated with a diagnosis of breast cancer, the identification of
modifiable risk factors and women at high risk for breast cancer is imperative. Body mass index (BMI), a
general measure of overall adiposity, is a risk factor that has been well established to be inversely related to
premenopausal breast cancer and positively associated with postmenopausal breast cancer. In contrast,
central adiposity, measured by waist circumference (WC) or waist-to-hip ratio (WHR), is characterized by high
levels of metabolically active visceral fat that leads to alterations in multiple hormones (e.g., insulin),
inflammatory cytokines, and adipokines, all of which have been implicated in breast cancer development.
Thus, I hypothesize that measures of central adiposity provide further information about breast cancer risk and
survival in addition to BMI. To date, few studies have had the statistical power to evaluate the link with
premenopausal breast cancers and even fewer have evaluated associations according to important tumor
characteristics and molecular subtypes. Therefore, I propose to improve understanding of the role of central
adiposity in breast cancer risk and survival. I aim to: 1) examine the independent association of central
adiposity with breast cancer risk by menopausal status and determine whether significant predictive
information is gained by adding central adiposity to the validated Rosner-Colditz risk prediction model; 2)
examine the relationship by tumor molecular subtypes; 3) examine the relationship by several key tumor
characteristics (i.e., estrogen receptor, androgen receptor, insulin receptor expression, PTEN loss, PIK3CA
mutations); and 4) lastly examine the association between central obesity and breast cancer survival. To
address these aims, I will utilize the rich questionnaire and biospecimen resources from two large prospective
cohorts, the Nurses' Health Study and Nurses' Health Study II. The women reported waist and hip
circumferences at two time points and breast cancer that was confirmed via medical record review.
Additionally, I have information on several tumor characteristics measured from available breast tumor tissue
blocks. With a large number of premenopausal breast cancer cases, multiple waist measurements, long follow-
up, and detailed tumor data, I will improve understanding of central obesity's role in breast carcinogenesis. By
evaluating subtypes and tumor characteristics, I should gain substantial new insight into biological mechanisms
and help confirm causality. This will allow us to identify women at higher risk for breast cancer development
and lower risk of breast cancer survival. Secondly, results gained from this work may improve risk prediction
models to help identify women at high risk of developing breast cancer who would be potential candidates for
potential chemoprevention or other risk-reducing options (e.g., increasing physical activity).
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