The FDA Office of Women’s Health (OWH) awards research grants for 1-2 year studies to support FDA regulatory decision-making and advance the science of women’s health. OWH has funded research projects that address health issues affecting women across their lifespan. This page highlights OWH-funded research related to breast cancer and mammography research.

Learn about other OWH-funded research

• Early Detection: Mammography, Diagnosis and Prognosis
• Cancer Treatment, Clinical Trials and Outcome Research
• Scientific Model System
• Etiology (Causes of Cancer)

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Completed Projects

Stimulate innovation in clinical evaluations and personalized medicine to improve patient outcomes with triple negative breast cancer - Beverly Lynn-Cook, PhD/NCTR (17)

Triple negative breast cancer is an aggressive form of breast cancer that frequently strikes young women. Due to its aggressive nature, its spreads to other parts of the body quickly. Unlike other breast cancers where targets have been identified for drug treatment, triple negative breast cancer lacks targets and, therefore, lacks treatment. This cancer, in addition to striking young women, has a high prevalence in women of color, particularly African American and Hispanic/Latina women. This cancer lacks hormone receptors in which targeted therapies have been developed. Although clinical trials are ongoing for new treatments for this aggressive type of breast cancer, understanding and discovering biomarkers and molecular signatures will aid in predicting risk and improve prognosis and treatment for this fatal disease. This study will investigate novel signaling pathways in women at high risk for triple negative breast cancer to identify early biomarkers. Furthermore, this study will track response to target agents in high risk women with mammary atypia. Our current “one-size-fits-all” approach to prevention is not working. While progress has been made in understanding the diverse biology of estrogen-receptor negative (ER-) breast cancer subtypes, we have little information on how breast cancer starts in an individual woman. Without this understanding, it is almost impossible to develop effective targeted prevention, particularly for triple negative breast cancer. We need a better understanding of the biology of triple negative breast cancer initiation in individual women. This collaborative transdisciplinary team between FDA, City of Hope and the University of Tennessee Health Science Center brings together expertise in women’s health, breast cancer biology, and epigenetic analyses to identify activated signaling networks in precancerous changes in high-risk women tissues. Together this transdisciplinary team aims to identify early signaling changes in high-risk women and deliver individualized targeted prevention strategies. Furthermore, identifying early signaling pathways will aid in developing strategies for chemoprevention and life-style changes.

Preservation of relevant clinical information in lossy compressed digital mammograms using objective image quality metrics - Aria Pezeshk, PhD/CDRH (16)

Capture and storage of medical images are becoming increasingly demanding for both screening and diagnostic purposes, resulting in the production of several petabytes of medical image data annually. With widespread use of screening mammography, and emergence of new modalities such as digital breast tomosynthesis (DBT) and breast CT that produce large numbers of images, efficient storage of such a vast amount of data has become a significant challenge. Moreover, the large size of images is the primary limiting factor in accessing patient data in telemedicine, electronic health records, and viewing medical images on mobile devices. While lossless image compression produces no risk to the interpretation of data and diagnosis, it does not allow for high compression rates. Lossy image compression and the associated higher compression ratios are therefore more desirable. The FDA currently interprets the Mammography Quality Standards Act (MQSA) as prohibiting lossy compression of digital mammograms for primary image interpretation, image retention, or transfer to the patient or her designated recipient. Reader studies are the most common type of study for discovering proper usage criteria of lossy compression algorithms across different organs and modalities. Such studies are often limited in size and scope, use different definitions of medical image quality as well as different study endpoints, and therefore arrive at conflicting conclusions. In this project we will use objective numerical image quality metrics to find proper limits that control the adverse effects of lossy image compression on both detection and estimation tasks in digital mammography. This project is expected to have a substantial regulatory impact by identifying proper study designs and metrics that can be used by the industry and users to assess the impact of lossy compression. In addition the results of this study can lead to updates to current MQSA guidance regarding usage of lossy image compression in mammography.

Mammographic CAD device testing using computationally inserted microcalcification clusters and masses - Berkman Sahiner, PhD/CDRH (16)

Breast cancer is the second leading cause of cancer death and the most prevalent cancer type among American women. There is considerable evidence that early diagnosis with screening imaging modalities improves the chance of survival for patients with breast cancer. Many breast imaging techniques benefit from computer-aided diagnosis (CAD) devices, which help radiologists detect cancerous lesions by automatically prompting suspicious locations identified through advanced computerized image analysis methods. Most CAD devices used for breast cancer screening are first developed and assessed for a specific “original” acquisition system, e.g., a specific image detector, or a specific image acquisition methodology in digital breast tomosynthesis (DBT). When CAD developers are ready to apply their CAD device to a new acquisition system, they are typically expected to assess their CAD device with the new system. The acquisition of a large and representative set of abnormalities for the new acquisition system can be a bottleneck, since the prevalence of breast cancer in the screening population is low. Our project aims to address this problem by using an innovative technique called lesion blending. Using well-defined imaging characteristics of the original and new acquisition systems, this technique will allow its users to blend lesions imaged under the original acquisition system into normal images acquired with the new system. Since normal images are easier to collect, this will allow CAD developers to assess their CAD device using fewer resources and expeditiously for the new acquisition system. In this project, this concept will be demonstrated with mammographic CAD devices, because previous data exists to validate our approach. However, the general idea is applicable to other current breast cancer screening modalities, such as DBT, and future screening modalities, such as breast CT. By allowing timely and proper assessment of devices for improved breast cancer detection, our project is expected to make a significant impact on women’s health.

Spectral photoacoustic tomography (PAT) for breast tumor oximetry: Test method development, in vivo validation, and computational modeling - Brian Garra, MD/CDRH (16)

Breast cancer is the second leading cause of cancer–related death in American women. A new imaging modality called Photoacoustic Tomography (PAT) can potentially help with detection and classification of breast cancers. In PAT, a laser pulse stimulates tissue to generate and send back sound waves from which images are created by an ultrasound machine. PAT can not only image abnormal small blood vessels due to absorption of the laser pulse by hemoglobin, but can also measure the amount of oxygen in the hemoglobin (called oximetry). Both of these features can be used to distinguish cancers from benign tumors and can help identify aggressive cancers. Despite great scientific interest and development of new PAT products intended for commercial use, no standard methods for testing PAT oximetry systems exist. This lack of proper test methods has hampered FDA regulatory review of new systems. We propose using tissue simulating materials and phantoms we previously developed for PAT imaging testing, to construct new phantoms and tests for PAT oximetry performance testing. A custom research-grade PAT system will be tested for its ability to measure hemoglobin oxygenation using these new phantoms, and the test results will be validated against measurements obtained using the same PAT system on rats. These results will be used to devise a simple but scientifically rigorous phantom and test methods for testing of new commercial systems during design, production and regulatory review. The results will also be used to complete development of a computational model of PAT system performance that, in the future, could be used in place of the phantom tests. Together all of these methods will markedly reduce the time and expense of performance testing and regulatory evaluation of new PAT systems for breast cancer evaluation.

Phantom-based evaluation of photoacoustic imaging systems for breast tumor vasculature quantification - Brian Garra, MD, CDRH (14)

• Vogt WC, Jia C, Garra BS, et al. Quantitative assessment of photoacoustic tomography systems integrating clinical ultrasound transducers using novel tissue-simulating phantoms. Proc. SPIE. 9323, Photons Plus Ultrasound: Imaging and Sensing 2015, 932333. (March 11, 2015) doi: 10.1117/12.2080283.
• Vogt WC, Jia C, Wear KA, et al. Design and Phantom-based Validation of a Bimodal Ultrasound-Photoacoustic Imaging System for Spectral Detection of Optical Biomarkers. Proc. SPIE 9315, Design and Quality for Biomedical Technologies VIII, 931502 (11 March 2015); doi: 10.1117/12.2082847.
• Vogt WC, Jia C, Wear KA, et al. Quantitative Assessment of Photoacoustic Tomography Systems Integrating Clinical Ultrasound Transducers Using Novel Tissue-Simulating Phantoms. Proc. SPIE 9323, Photons Plus Ultrasound: Imaging and Sensing 2015, 932333 (11 March 2015); doi: 10.1117/12.2080283.
• Vogt WC, Jia C, Wear KA, et al. Biologically relevant photoacoustic imaging phantoms with tunable optical and acoustic properties. J Biomed Opt. 2016; 21(10), 101405 (1-11).

Incremental Values of Sequential Procedures for Diagnosing Breast Cancer - Zhiwei Zhang, PhD, CDRH (13)

• Liu W, Pantoja-Galicia N, Zhang B, et al. Generalized linear mixed models for multi-reader multi-case studies of diagnostic tests. Stat Methods Med Res 2015 Apr 5. DOI: 10.1177/0962280215579476. [Epub ahead of print]

Safety and Efficacy of Iron Oxide Nanoparticles Used as MRI Contrast Agents for Breast Cancer Imaging - Peter Goering, PhD, CDRH (12)

• Zhang Q, Rajan SS, Tyner KM, et al. Effects of iron oxide nanoparticles on biological responses and MR imaging properties in human mammary healthy and breast cancer epithelial cells. J Biomed Mater Res Part B: Appl Biomater. 2016 Jul;104(5):1032-42. doi: 10.1002/jbm.b.33450. Epub 2015 May 26.

Evaluating radiation risks and benefits of breast CT for diagnosing breast cancer – Robert Jennings, PhD, CDRH (11)

• Kontson K and Jennings RJ. Characterization of scatter magnitude and distribution in dedicated breast computed tomography with bowtie filters. J Med Imaging (Bellingham) 2014; 1(3), 033505-1 to 033505-13. Published online 2014 Dec 18. doi: 10.1117/1.JMI.1.3.033505.
• Kontson K, Jennings R. Bowtie filters for dedicated breast CT: Theory and computational implementation. Med Phys 2015; 42:1453-1462.
• Kontson K, Jennings RJ. Bowtie filters for dedicated breast CT: Analysis of bowtie filter material selection. Med Phys 2015; 42:5270-5277.

Reproducibility in the quantitative assessment of multiple tissue-based biomarkers for breast cancer using light and digital microscopy – Nicholas Petrick, PhD, CDRH (11)

• Keay T, Conway CM, O’Flaherty N, et al. Reproducibility in automated quantitative assessment of HER2/neu for breast cancer. J Pathol Inform 2013; 4:19.
• Gavrielides MA, Gallas BD, Lenz P, et al. Observer variability in the interpretation of HER2/neu immunohistochemical expression with unaided and computer-aided digital microscopy. Arch Pathol Lab Med 2011;135:233-242.
• Gavrielides MA, Conway C, O’Flaherty N, et al. Observer performance in the use of digital and optical microscopy for the interpretation of tissue-based biomarkers. Analyt Cellular Pathol 2014, Article ID 157308, 10 pages. http://dx.doi.org/10.1155/2014/157308.

Dose and image quality optimizations in various full-field digital mammography systems - Kish Chakrabarti, PhD, CDRH (10)

• Liu H, Chakrabarti K, Kaczmarek RV, et al. Evaluation of clinical full field digital mammography with the task specific system-model-based Fourier Hotelling observer (SMFHO) SNR. Med Phys 2014; 41, 051907; doi: 10.1118/1.4870377.

Development of standard color management methods for assessment of immunohistochemical HER2 expression in breast cancer using digital microscopy - Aldo Badano, PhD, CDRH (10)

• Gavrielides MA, Gallas BD, Lenz P, et al. Observer variability in the interpretation of HER2/neu immunohistochemical expression with unaided and computer-aided digital microscopy. Arch Pathol Lab Med 2011;135:233-242.
• Wei-Chung C, Tannous W, Badano A. Impact of solid-state lighting on observer performance of color discrimination. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 83181T (February 20, 2012); doi:10.1117/12.912436; http://dx.doi.org/10.1117/12.912436. http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1385359.
• Wang J, Liu P, Chen WC, Badano A. P-40: Suite Mobile: A Lab for Studying Mobile Displays in Motion. SID Symposium Digest of Technical Papers. 2011 June; 42(1):1245-1248.

Mammography breast cancer screening rates among disadvantaged women within a prepaid health care system - Rosalie Bright, ScD, CDRH (97)

Optimization of mammography - Robert Jennings, PhD, CDRH (97)

• Jafroudi H, Muntz EP, Jennings, RJ. Multiparameter Optimization of Mammography - An Update. Proc. SPIE 2163, Medical Imaging 1994: Physics of Medical Imaging, 2 (May 1, 1994); doi:10.1117/12.174244.
• Jennings, RJ, Fewell RT, Jafroudi H, et al. Laboratory Evaluation of an Optimized Mammographic Imaging System. Proc. SPIE 0914, Medical Imaging II, 176 (June 27, 1988); doi:10.1117/12.968630.

Mammography quality standards act facilities workshop - Barbara Ward-Groves, MPH, ORA (95)

Development of Mammography Quality Standards Act (MQSA) Speaker Kits - Carol Sierka, CDRH (94)

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Ongoing Projects

Evaluation of the Impact of Dose Interruptions and Reductions on the Clinical Efficacy of Targeted Breast Cancer Drugs – Amal Ayyoub, PhD/CDER (FY 2023) - Project begins October 2022

Prediction of response to therapy for advanced/metastatic breast cancer: Joint analysis of radiologic and genomic data using machine learning - Berkman Sahiner, PhD/CDRH (2021) 
Although various treatment options are available for metastatic breast cancer (MBC), it is an incurable condition. The key goals in the treatment of patients with MBC are to prolong survival and symptom relief, with an emphasis on restricting treatment-related toxicities. Drug therapy is helpful for prolonging survival and maintaining quality of life for MBC patients. A range of data sources are available for personalizing a patient’s response to therapy, but the information incorporated into oncology drug development is typically limited to one or a few markers, and it is currently unclear how different information about a patient (e.g. imaging, genomic, histopathologic, clinical data) can be best integrated to individualize patient management. 
Machine learning algorithms have recently been applied to a range of tasks in medicine. However, important gaps remain: Only a limited number of studies have applied machine learning to predict response to cancer therapy based on serial imaging. The potential of using machine learning to combine data from multiple disciplines (e.g., radiology, genetics, pathology and informatics) has not been fully tapped. The goal of this project is to develop machine learning models to combine different sources of data for the same patient to help predict the patient’s response to therapy while undergoing drug treatment for MBC. The models will be trained and validated on a large, multi-institutional data set provided by our pharmaceutical industry collaborator. 
The developed models may significantly help MBC patients and the care team by enabling timely decisions about whether to continue treatment or seek alternative treatments. As importantly, the development of such models with collaboration from multiple Centers within the FDA is likely to provide important indications about potential pitfalls in model development and generalizability of the machine learning approaches for these purposes, thus preparing the Agency for likely future submissions in this area. 

Verification of Novel Predictive Biomarkers of Doxorubicin-induced Cardiotoxicity in Breast Cancer Patients - Li-Rong Yu, PhD/NCTR (2021) 
Chemotherapy is a major treatment option for cancer patients and anthracyclines (e.g., doxorubicin (DOX)) are commonly used for treating a wide range of cancers. However, they can cause life-threatening heart damage (cardiotoxicity) for some patients. Currently, non-invasive medical imaging tests are the most practical cardiotoxicity monitoring tools; nonetheless they are not sensitive enough for early detection of heart damage.  In a preliminary analysis of blood samples from 70 female breast cancer patients taken before and after the first and second cycles of DOX treatments, we identified potential novel blood protein and metabolite biomarkers for predicting heart injury resulted from the treatment. The goal of this study is to verify the predictive performance of these biomarkers in a separate group of 120 new patients. Ultimately, these predictive biomarkers may provide an earlier and better individualized risk assessment in female breast cancer patients of chemotherapy-induced cardiotoxicity, thus providing opportunities for prevention or therapeutic intervention of cardiac injury. These novel biomarkers could enable personalized female breast cancer therapy tailored toward maximal efficacy and minimal cardiotoxicity and have a potential to assess the safety of promising new therapies. 
 
Completed Projects

Patient Reported Outcomes (PRO) Symptom Data to Complement Traditional Exposure-Response (ER) Analysis for Dose optimization during Breast Cancer Drug Development - Jeanne Fourie Zirkelbach, CDER (19)

Development of a targeted microRNA-based epigenetic therapeutic approach for breast cancer treatment – Igor Pogribny, PhD, NCTR (11)

Safety and efficacy of biomarkers using gene expression data for breast cancer patient treatment and care - Subok Park, PhD, CDRH (10)

Qualifying Imaging Biomarkers to Monitor Neoadjuvant Chemotherapy in Breast Cancer Patients to Identify Responders Using Positron Emission Tomography (PET) - Christy John, PhD, CDER (08)

Discovery and evaluation of interspecies biomarkers to identify and characterize the cardiotoxic effects of Transtuzumab (Herceptin), a novel antibody used in the treatment of breast cancer - Eugene Herman, PhD, CDER (01)

Improve the efficacy of chemotherapeutic drugs for the treatment of breast cancer - Emily Shacter, PhD, CBER (98)

IP-10: A potential new therapeutic for breast cancer - Giovanna Tosato, MD, CBER (96)

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Ongoing Projects

Dataset to validate digital-pathology algorithms that quantify tumor-infiltrating lymphocytes in breast cancer - Brandon Gallas, PhD/CDRH (2021) 
We will create a validation dataset of pathologist annotations for artificial intelligence and machine learning (AI/ML) algorithms that process whole slide images (WSIs). Our focus will be on algorithm performance assessment in the context of estimating the density of immune cells in breast cancer called stromal tumor infiltrating lymphocytes (sTILs). The density of sTILs has been shown to predict outcomes without therapies and responses to immune therapies. sTILs can be evaluated simply at low cost with a microscope and standard specimen preparation. As such, sTIL evaluation can be incorporated in breast cancer management activities worldwide, even low-to-middle-income settings, and is expected to reduce the use of toxic chemotherapies. 
We have engaged an international, multidisciplinary team working in the pre-competitive space. Collaborators and consultants include clinician-scientists from academic hospitals, international health systems, academics, professional societies, and medical device manufacturers. By engaging diverse stakeholders, we aim to address multiple perspectives and emphasize interoperability across platforms. 
To collect the data, we will recruit and train pathologists to estimate sTILs. We will collect the data on microscope and digital platforms. In addition to live events where we can use the microscope system, the digital platforms allow us to crowdsource pathologists from anywhere in the world on web-based platforms (PathPresenter and caMicroscope). We have found these events are low-cost, efficient opportunities to recruit and train pathologists to collect high quality data. 
We are pursuing qualification of the validation dataset as an FDA Medical Device Development Tool (MDDT). This offers an opportunity to receive feedback from an FDA review team while building the dataset fit for a regulatory purpose. The pursuit of MDDT qualification will inform regulatory frameworks and be instructive to others to develop their own validation datasets, and the dataset will be a high-value public resource that can be used in AI/ML algorithm submissions. 

Completed Projects

Tool development of modeling and simulations for metastatic breast cancer - Jingyu Yu, PhD/CDER (16)

Worldwide, breast cancer is the leading type of cancer in women, accounting for 25% of all cases. Although survival rate is high for women with breast cancer, the five-year survival rate after diagnosis for metastatic (stage 4) breast cancer patients is 40 percent based on MD Anderson researchers. The Critical Path Initiative of the US Food and Drug Administration calls for leveraging existing knowledge from clinical data through the use of quantitative modeling to improve the drug development process. We therefore propose to quantify the relationship between early tumor size after treatment and clinical outcome (e.g., patient survival, progression free survival) in women with metastatic breast cancer using the pooled clinical data submitted to the Food and Drug Administration by multiple pharmaceutical companies. Our proposal aims at demonstrating how data mining of drug registration trials for metastatic breast cancer agents enables us to develop a pharmacostatistical model that can capture the time course tumor size change and link time of death or disease progression to risk factors and the tumor size information after start of therapy. The disease model we propose here may reduce the failure rate of drugs by selecting the right dose for right candidate compounds that are highly efficacius on the basis of a predicted survival benefit for women with metastatic breast cancer.

Calcium and material characterization in women using dual-energy computed tomography - Nicholas Petrick, PhD, CDRH (14)

Development, validation and dissemination of computational modeling tools to estimate radiation dose and image quality of emerging imaging technologies for the diagnosis and staging of breast cancer - Andreu Badal-Soler, PhD, CDRH (12)

• Ghammraoui B, Badal A. Monte Carlo simulation of novel breast imaging modalities based on coherent x-ray scattering. Phys Med Bio 2014 July; 59(13):3501-3516.

Development of a tissue-mimicking physical phantom and quantitative, assessment tools for standardizations, optimization, and NSF risk reduction in dynamic contrast-enhanced MRI of the breast - Aldo Badano, Ph.D., CDRH (09)

• Freed M. The effect of protocol parameters on contrast agent washout curve separability in breast DCE-MRI: A simulation study. Magn Reson Med 2011; 68(2):516-522.
• Freed M, de Zwart JA, Hariharan P, et al. Development and characterization of a dynamic lesion phantom for the quantitative evaluation of dynamic contrast-enhanced MRI. Med Phys. 2011; 38(10):5601-5611.
• Badano A, Freed M, Fang Y. Oblique incidence effects in direct x-ray detectors: A first-order approximation using a physics-based analytical model. Med. Phys. Med Phys 2011; 38(4):2095-2098.
• Freed M, de Zwart JA, Loud JT, et al. An anthropomorphic phantom for quantitative evaluation of breast MRI. Med Phys 2011; 38(2):743-753.
• Freed M, Badal A, Jennings RJ, et al. X-ray properties of an anthropomorphic breast phantom for MRI and x-ray imaging. Phys. Med. Biol 2011; 56 (12):3513–3533.
• Freed M, Miller S, Tang K, et al. Experimental validation of Monte Carlo (MANTIS) simulated x-ray response of columnar CsI scintillator screens. Med Phys 2009; 36(11):4944-4956.

Effects of Proposed Revisions to the Regulations Implementing the Mammography Quality Standards Act - Steven Tucker, OC (08)

Dose and Image Quality in Full Field mammography - Kish Chakrabarti, PhD, CDRH (08)

• Liu H, Kyprianou IS, Badano A, et al. SKE/BKE Task-based methodology for calculating Hoteling observer SNR in mammography. Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72581D (March 10, 2009); doi:10.1117/12.813833

Patient Safety and Imaging Performance of Three-Dimensional (3D) X-Rays Systems for Detection of Breast Cancer - Subok Park, PhD, CDRH (08)

• Park S, Jennings R, Liu H, et al. A statistical, task-based evaluation method for 3D x-ray breast imaging systems using variable-background phantoms. Med Phys 2010; 37(12):6253-70.
• Young S, Bakic P, Myers KJ, et al. Performance tradeoffs in a model breast tomosynthesis system. The Optical Society of America’s Digital Image Processing and Analysis Conference 2010, http://www.opticsinfobase.org/abstract.cfm?uri=DIPA-2010-DTuA3. (conference paper)
• Park S, Zeng R, and Myers KJ. Singular system analysis for breast tomosynthesis systems for choosing angular projections. Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 762243 (23 March 2010); doi: 10.1117/12.844237. (conference paper)
• Park S and Clarkson E. An efficient method of estimating the Bayesian classifier in detection tasks involving complex high-dimensional data,” Joint Statistical Meetings 2010, http://www.amstat.org/meetings/jsm/2010/onlineprogram/AbstractDetails.cfm?abstractid=307237. (conference paper)
• Park S, Liu H, Leimbach R, et al. A task-based evaluation method for x-ray breast imaging systems using variable background phantoms. Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72581L (March 12, 2009); doi:10.1117/12.813572. http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=813756. (conference paper)
• Young S, Park S, Anderson KS, et al. Estimating breast tomosynthesis performance in detection tasks with variable-background phantoms. Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72580O (14 March 2009); doi: 10.1117/12.813900. (conference paper)
• Witten JM, Park S, and Myers KJ. Using partial least squares to compute efficient channels for the Bayesian ideal observer. Proc. SPIE 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment, 72630Q (March 12, 2009); doi:10.1117/12.813550. http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=816000. (conference paper)

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Ongoing Projects

The role of epigenetic mechanisms in re-expression of ER, PR, and HER receptors in triple negative breast cancer: effects of FDA approved epigenetic drugs and dietary agents - Beverly Lyn-Cook, PhD/NCTR (16)

Triple negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer. About 15% of breast cancers falls into this category. TNBC often strikes premenopausal women. TNBC patients generally have a poorer prognosis and early relapse that often results in death. This subtype of cancer lacks targeted therapies receptors, such as the estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor-2 (HER2). TNBC patients cannot, thereby, be treated with targeted therapies that blocks the action of these receptors, such as tamoxifen and Herceptin. Therefore, these patients are limited to cytotoxic chemotherapies with harsh side effects. Risk factors for TNBC include: being of African descent, BRCA1 mutation, a strong family history of breast cancer, lifestyle and environmental factors. Although mutations are involved in the initiation of TNBC, research has revealed that individuals are controlled by factors other than DNA sequences; these factors are termed epigenetics. Epigenetics refers to changes in gene expression that do not directly affect DNA sequences. In humans, these epigenetic mechanisms involve DNA methylation, histone modifications, and noncoding RNAs that control tissue-specific gene expression. This study will examine whether an epigenetic drug (vorinostat) and a dietary agent (indole-3-carbinol), which have been shown to exert their effects through epigenetic mechanisms, can re-express critical targeted receptors (ER, PR and HER2) in TNBC cells and render these resistant cells sensitive to approved FDA cancer drugs such as tamoxifen, raloxifene or Herceptin.

Oncomutation profile of triple negative breast cancer: Additional studies in African American women - Meagan Myers, PhD/NCTR (15)

Breast cancer is the second most deadly cancer in American women, with an estimated 40,000 deaths each year. Breast cancers in African American women display different characteristics than in Caucasian women, such as an earlier onset, more aggressive tumor characteristics, and a less favorable outcome. Many differences have been attributed to these disparities, most notably the higher prevalence of triple-negative breast cancer (TNBC) in women of African American decent. While differences in epidemiology and prognosis between African American and Caucasian women with breast cancer, and specifically TNBC, have been described in the literature, little if any data is available regarding possible differences in somatic gene mutations found in the breast tumors from African American compared to Caucasian women. To this end, utilizing the sensitive and quantitative Allele-Specific Competitor Blocker PCR, point mutations in the PIK3CA, HRAS and BRAF genes will be quantified in African American normal breast and 4 different subtypes of breast cancer, including TNBC. Data generated from this study will be compared to our OWH FY12 study, titled “Oncomutation Profile of Triple Negative Breast Cancer”, which was comprised mostly from Caucasian women. Completion of this project will promote women's health by facilitating the development of personalized approaches to treat breast cancer, including TNBC for which there are currently limited treatment options. The data generated from increasing the sample diversity in our dataset will strengthen current knowledge of the molecular differences between breast cancers of different ethnic origins. Furthermore, research into potential differences in low frequency somatic point mutations in these unfavorable tumors of women of African origin may further progress towards the ultimate goal of individualized cancer therapy.

Completed Projects

Quantitative oncomutation profile of triple negative breast cancer - Meagan Myers, PhD, NCTR (12)

Integrated analysis of single nucleotide polymorphism and copy number variation in genome association of breast cancer - Ching-Wei Chang, PhD, NCTR(11)

Inactivation of UDP-Glucuronosyltransferases (UGTs) in human breast tissues: Accessing cancer risk, tamoxifen safety and toxicity - Athena Starlard-Davenport, PhD, NCTR (09)

• Starlard-Davenport A, Tryndyak VP, James, SR, et al. Mechanisms of epigenetic silencing of the Rassf1a gene during estrogen-induced breast carcinogenesis in ACI rats. Carcinogenesis 2010;31(3):376-381.
• Starlard-Davenport A, Lyn-Cook B, Beland F, et al. The role of UDP-glucuronosyltransferases and drug transporters in breast cancer drug resistance. Exp Oncol 2010;32(3):171-182.

Women’s radiation dose and excess cancer risk associated with x-ray computed tomography scans: quantification and risk-mitigation strategies - Iacovos S. Kyprianou, Ph.D., CDRH (09)

• Brunner CC, Abboud SF, Hoeschen C, et al. Signal detection and location-dependent noise in cone-beam computed tomography using the spatial definition of the hotelling SNR. Med Phys. 2012 Jun;39(6):3214-28
• Abboud S, Lee K, Vinehout K, Set al. A comparison of methods for estimating the line spread function of a CT imaging system. Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79615V (March 16, 2011); doi:10.1117/12.877665. http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=724228. (conference paper)
• Rupcich F, Kyprianou I, Badal A, et al. Energy deposition in the breast during CT scanning: quantification and implications for dose reduction. Medical lmaging 2011: Physics of Medical lmaging, edited by Norbert J. Pelc, Ehsan Samei, Robert M. Nishikawa, Proc. of SPIE Vol. 7961,796128. (conference paper)
• Dixon RL, Anderson JA, Bakalyar DM, et al. AAPM Report No. 111, Comprehensive Methodology for the Evaluation of Radiation Dose in X-Ray Computed Tomography: A New Measurement Paradigm Based on a Unified Theory for Axial, Helical, Fan-Beam, and Cone-Beam Scanning With or Without Longitudinal Translation of the Patient Table http://www.aapm.org/pubs/reports/RPT_111.pdf. (American Association of Physicists in Medicine, 2010).
• Badal A, Kyprianou IS, Banh DP, et al. Penmesh—Monte Carlo radiation transport simulation in a triangle meshes geometry. IEEE Transactions On Medical Imaging 2009; 28(12). http://ieeexplore.ieee.org/abstract/document/4912407/?reload=true.
• Brunner C, Hurrowitz S, Hoeschen C, et al. Noise characterization of computed tomography using the covariance matrix. Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76224Z (23 March 2010); doi: 10.1117/12.845494.

DNA adducts of tamoxifen - Frederick A. Beland, PhD, NCTR (96, 99)

• Marques MM and Beland FA. Identification of tamoxifen-DNA adducts formed by 4-hydroxytamoxifen quinone methide. Carcinogenesis 1997;20(3):471-477.
• Beland FA, McDaniel LP, Marques MM. Comparison of the DNA adducts formed by tamoxifen and 4-hydroxytamoxifen in vivo. Carcinogenesis 1999;18(10):1949-1997.

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Resources For You

• Projects by Funding Year
• FDA Resources For Women