Grant Number:	1R01CA135288-01A1 Interpret this number
Primary Investigator:	Hu, Jennifer
Organization:	University Of Miami School Of Medicine
Project Title:	Impact of Genomics on Disparities in Breast Cancer Radiosensitivity
Fiscal Year:	2010

DESCRIPTION (provided by applicant): Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death in American women. Lumpectomy followed by radiotherapy (RT) has significantly improved survival. However, about 30% of patients develop a Grade 2 or worse early or late skin reaction, pain, breast edema and poor cosmetic results that impact quality of life. Inter-individual variability in the development of RT-induced adverse reactions in normal tissue is well-documented for both acute and late effects. African-American (AA) and underserved populations are less likely than Whites to receive the recommended adjuvant RT, if treated, have a higher risk for developing RT-related side effects and worse clinical outcome. To achieve our long-term goals in improving quality of life, clinical outcome, and overcoming breast cancer disparities, we will use a genome- wide approach to test genomic prediction models for RT-induced adverse reactions and recurrence in three racial/ethnic populations. We will test a new paradigm that multiple genetic variations and functional phenotypes contribute to radiation sensitivity that may predict RT-induced side effects and clinical outcome. Investigating this new paradigm will develop powerful tools in identifying high-risk populations and targets for personalized intervention and treatment. Aim 1 will evaluate polygenic models of RT-induced early adverse skin reactions (EASRs) in 1000 breast cancer patients with a comprehensive evaluation of genome-wide nonsynonymous single nucleotide polymorphisms (nsSNPs; n=21,877). Aim 2 will evaluate the association between RT-induced EASRs and three functional DNA damage/repair phenotypes. Aim 3 will develop polygenic models of genome-wide nsSNPs in predicting RT-induced late side effects and/or recurrence in a breast cancer cohort of 850 women with a median follow up of 8 years (range 4-12 years). The outcome of the proposed research will advance our scientific knowledge in the accurate assessment of prognosis in cancer patients, which is crucial to controlling the suffering and death due to breast cancer. Prediction models provide an important approach to assessing cancer risk, progression, quality of life, and prognosis. These prediction models may identify individuals at high risk of developing adverse reactions or recurrence who may benefit from targeted treatment or other interventions. They also may enable the development of benefit-risk indices that will aid in the design and planning of clinical treatment. The proposed research will use a hypothesis- driven approach to integrate genetic and functional biomarkers in developing optimal prediction models of RT- induced adverse reactions and recurrence. The outcome will target effective intervention and treatment strategies, and ultimately improve quality of life and progression-free survival in breast cancer patients, particularly in minority and underserved populations with more aggressive disease and worse clinical outcome. This will be the largest and most complete genetic analysis of RT-related clinical outcome to date, and will move the field significantly towards the goal of more effective, personalized therapy for breast cancer patients. PUBLIC HEALTH RELEVANCE: Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death in American women. The long-term goal of this study is to improve quality of life, clinical outcome, and breast cancer disparities. The proposed research will use a genome-wide approach to develop and validate genomic prediction models for radiotherapy-induced early and late side effects as well as local-regional recurrence in three racial/ethnic populations. The outcome of the proposed research will advance our scientific knowledge in the accurate assessment of prognosis and response to therapy in cancer patients, which is crucial to controlling the suffering and death due to breast cancer.




The interrelationship between obesity and race in breast cancer prognosis: a prospective cohort study.
Authors: Schindler E.A. , Takita C. , Collado-Mesa F. , Reis I.M. , Zhao W. , Yang G.R. , Acosta L.G. , Hu J.J. .
Source: Bmc Women's Health, 2024-05-30 00:00:00.0; 24(1), p. 312.
EPub date: 2024-05-30 00:00:00.0.
PMID: 38816709
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The Interrelationship between Obesity and Race in Breast Cancer Prognosis: A Prospective Cohort Study.
Authors: Schindler E.A. , Takita C. , Collado-Mesa F. , Reis I.M. , Zhao W. , Yang G.R. , Acosta L.G. , Hu J.J. .
Source: Research Square, 2023-09-25 00:00:00.0; , .
EPub date: 2023-09-25 00:00:00.0.
PMID: 37841856
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Smoking and Radiation-induced Skin Injury: Analysis of a Multiracial, Multiethnic Prospective Clinical Trial.
Authors: Hughes R.T. , Ip E.H. , Urbanic J.J. , Hu J.J. , Weaver K.E. , Lively M.O. , Winkfield K.M. , Shaw E.G. , Diaz L.B. , Brown D.R. , et al. .
Source: Clinical Breast Cancer, 2022 Dec; 22(8), p. 762-770.
EPub date: 2022-09-16 00:00:00.0.
PMID: 36216768
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Genome-wide enriched pathway analysis of acute post-radiotherapy pain in breast cancer patients: a prospective cohort study.
Authors: Lee E. , Takita C. , Wright J.L. , Slifer S.H. , Martin E.R. , Urbanic J.J. , Langefeld C.D. , Lesser G.J. , Shaw E.G. , Hu J.J. .
Source: Human Genomics, 2019-06-13 00:00:00.0; 13(1), p. 28.
EPub date: 2019-06-13 00:00:00.0.
PMID: 31196165
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Association between C-reactive protein and radiotherapy-related pain in a tri-racial/ethnic population of breast cancer patients: a prospective cohort study.
Authors: Lee E. , Nelson O.L. , Puyana C. , Takita C. , Wright J.L. , Zhao W. , Reis I.M. , Lin R.Y. , Hlaing W.M. , Bakalar J.L. , et al. .
Source: Breast Cancer Research : Bcr, 2019-05-28 00:00:00.0; 21(1), p. 70.
EPub date: 2019-05-28 00:00:00.0.
PMID: 31138314
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Association Between Inflammatory Biomarker C-Reactive Protein and Radiotherapy-Induced Early Adverse Skin Reactions in a Multiracial/Ethnic Breast Cancer Population.
Authors: Hu J.J. , Urbanic J.J. , Case L.D. , Takita C. , Wright J.L. , Brown D.R. , Langefeld C.D. , Lively M.O. , Mitchell S.E. , Thakrar A. , et al. .
Source: Journal Of Clinical Oncology : Official Journal Of The American Society Of Clinical Oncology, 2018-07-10 00:00:00.0; , p. JCO2017771790.
EPub date: 2018-07-10 00:00:00.0.
PMID: 29989859
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Characterization of risk factors for adjuvant radiotherapy-associated pain in a tri-racial/ethnic breast cancer population.
Authors: Lee E. , Takita C. , Wright J.L. , Reis I.M. , Zhao W. , Nelson O.L. , Hu J.J. .
Source: Pain, 2016 May; 157(5), p. 1122-31.
PMID: 26780493
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Prospective evaluation of radiation-induced skin toxicity in a race/ethnically diverse breast cancer population.
Authors: Wright J.L. , Takita C. , Reis I.M. , Zhao W. , Lee E. , Nelson O.L. , Hu J.J. .
Source: Cancer Medicine, 2016 Mar; 5(3), p. 454-64.
PMID: 26763411
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Racial variations in radiation-induced skin toxicity severity: data from a prospective cohort receiving postmastectomy radiation.
Authors: Wright J.L. , Takita C. , Reis I.M. , Zhao W. , Lee E. , Hu J.J. .
Source: International Journal Of Radiation Oncology, Biology, Physics, 2014-10-01 00:00:00.0; 90(2), p. 335-43.
PMID: 25304794
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Inflammatory biomarker C-reactive protein and radiotherapy-induced early adverse skin reactions in patients with breast cancer.
Authors: Rodriguez-Gil J.L. , Takita C. , Wright J. , Reis I.M. , Zhao W. , Lally B.E. , Hu J.J. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2014 Sep; 23(9), p. 1873-83.
PMID: 24917184
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Complementary and alternative medicine in reducing radiation-induced skin toxicity.
Authors: Hu J.J. , Cui T. , Rodriguez-Gil J.L. , Allen G.O. , Li J. , Takita C. , Lally B.E. .
Source: Radiation And Environmental Biophysics, 2014 Aug; 53(3), p. 621-6.
EPub date: 2014-05-05 00:00:00.0.
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Authors: O'Flaherty J.T. , Wooten R.E. , Samuel M.P. , Thomas M.J. , Levine E.A. , Case L.D. , Akman S.A. , Edwards I.J. .
Source: Plos One, 2013; 8(5), p. e63076.
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