Breast cancer still kills 45,000 women a year in the US alone and over 270,000 women are given a diagnosis of either invasive or in situ disease. Screening is our major public health intervention. And yet we likely overdiagnose as many or more women than we save with screening and it does not impact the outcomes of the most aggressive cancers. We have assembled an extraordinary set of resources that include datasets with long term follow-up as well as a unique prospective trial that will include comprehensive host risk and tumor annotation to address the underlying biology (from both the tumor and host perspective) of indolent (IDLE) and interval cancers. Our goal is to identify better ways to screen for and treat the most aggressive cancers and avoid overdiagnosis and overtreatment as well as the inadvertent labeling of indolent lesions as cancers. Testable Hypotheses 1. Commercially available assays can identify ultralow risk breast tumors (MammaPrint Ultralow Risk for invasive cancer, Oncotype-DCIS-category 1 for DCIS). 2. The combined use of commercially available assays plus additional genomic, pathology, and immune based assays along with mode of detection can further differentiate IDLE from ultralow breast lesions. 3. Among the malignant features differentiating screen-detected from interval breast cancers are the degrees of cellular and molecular heterogeneity and type/extent of immune microenvironment and host response. 4. Since interval cancers are often biologically distinct from screen detected cancers, we hypothesize that genetic risk factors will be useful to distinguish the risk of interval from screen detected cancers.
Specific Aims : 1. Stratify low risk invasive tumors into low vs. ultralow vs. IDLE and high risk into interval vs. screen- detected using gene expression profiling, pathology features, immune profiling in fully annotated invasive cancer data sets and validate the best predictors in a prospective California-wide screening trial. 2. Develop adjunctive assays to stratify DCIS lesions into IDLE, ultralow, moderate and high-risk DCIS breast lesions using gene expression profiling, and measures of tumor immune micro-environment in established data sets and validate using a prospective registry of 300 DCIS cases 3. Develop a model using known germline breast cancer risk variants to predict women predisposed toward ultralow and IDLE screen detected tumors, and those predisposed to interval detected breast cancers, using data from a fully annotated California-wide screening trial that includes germline and tumor profiling.

Public Health Relevance

Breast cancer is the most common cancer among women, but represents a collection of diseases that span behavior from indolent to aggressive. Screening necessarily magnifies and brings to attention the indolent lesions and does not improve outcomes for those that present between screen, so called interval cancers. Using unique data sets and a prospective new screening trial, we intend to add to commercially available tests to clearly designate ultralow risk tumors, and further determine what features make the indolent lesions of epithelial origin (IDLE). Further, we will interrogate the biology of interval cancers to develop better approaches for screening and treatment. Finally we will determine the genomic and immune tumor environment to better understand the populations in which interval and IDLE tumors arise, to refine screening policy.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Ghosh-Janjigian, Sharmistha
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
Schools of Medicine
San Francisco
United States
Zip Code
Buckley, Alexandra R; Ideker, Trey; Carter, Hannah et al. (2018) Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas. Genome Med 10:69
Mori, Hidetoshi; Cardiff, Robert D; Borowsky, Alexander D (2018) Aging Mouse Models Reveal Complex Tumor-Microenvironment Interactions in Cancer Progression. Front Cell Dev Biol 6:35
Esserman, Laura J; Yau, Christina; Thompson, Carlie K et al. (2017) Use of Molecular Tools to Identify Patients With Indolent Breast Cancers With Ultralow Risk Over 2 Decades. JAMA Oncol 3:1503-1510
Campbell, Michael J; Baehner, Frederick; O'Meara, Tess et al. (2017) Characterizing the immune microenvironment in high-risk ductal carcinoma in situ of the breast. Breast Cancer Res Treat 161:17-28
Mori, Hidetoshi; Chen, Jane Q; Cardiff, Robert D et al. (2017) Pathobiology of the 129:Stat1 -/- mouse model of human age-related ER-positive breast cancer with an immune infiltrate-excluded phenotype. Breast Cancer Res 19:102
Bannon, Amber E; Kent, Jason; Forquer, Isaac et al. (2017) Biochemical, Molecular, and Clinical Characterization of Succinate Dehydrogenase Subunit A Variants of Unknown Significance. Clin Cancer Res 23:6733-6743
Shieh, Yiwey; Eklund, Martin; Esserman, Laura (2016) Detection of ductal carcinoma in situ and subsequent interval cancers. BMJ 352:i551
Levy, Eric; Marty, Rachel; Gárate Calderón, Valentina et al. (2016) Immune DNA signature of T-cell infiltration in breast tumor exomes. Sci Rep 6:30064