Getting a jump on cancer with a genomic risk classifier
Creators: name: University Of California Office Of The President
Publisher: name: University of California Office of the President
publisherIdentifier: https://ror.org/00dmfq477
publisherIdentifierScheme: ROR
Year: 2024

description: This project was supported in part by a generous donation from the Katie Ann Buzbee Trust.
 
 
 
 Non-technical overview of the research topic and relevance to breast cancer: 
 
 Prevention is the ideal strategy for breast cancer treatment as it reduces the patient suffering both from the cancer and from the conventional treatments. Recent large studies that measure alterations in cancer DNA have identified and confirmed numerous recurrent changes to genes that can be found in the vast majority of breast cancers. In contrast to the cancers, little is understood about these genetic changes associated with the early stages of progression to breast cancer: changes from normal tissue to early neoplasias to carcinoma in situ to cancer. The evaluation of these “pre-invasive neoplasias” found in screening breast biopsies relies solely on how these lesions look under light microscope, based on concepts developed decades ago. These pre-invasive neoplasias (such as atypical ductal hyperplasia and columnar cell lesions) represent a dilemma in clinical management as, for example, only about 20% of atypical ductal hyperplasia lesions progress to cancer (though 80% do not). These lesions are becoming increasingly detected with more and more sensitive radiographic screening. 
 
 
 
 
 
 
 
 The question(s) or central hypotheses of the research: 
 
 Because breast cancer is composed of recurrent, common alterations in the DNA, we hypothesize that the identification of these changes in pre-invasive neoplasia will help us identify pre-invasive neoplasms that have a high likelihood of progressing to cancer. 
 
 
 
 
 
 
 
 The general methodology: 
 
 We propose a case-control study design that will enable us to measure the frequency of common DNA alterations in pre-invasive neoplasia that is adjacent to cancer (cases) compared to the frequency of these mutations in pre-invasive neoplasia with no adjacent cancer (controls). Our data will be derived from cancers from both women treated at an academic hospital as well as women in the multi-ethnic “Equality in Breast Cancer Care” (EBCC) study. We will use targeted sequencing and fluorescent in situ hybridization (FISH) to observe these DNA differences. We will then build a classifier using this data that is most effective in stratifying pre-invasive lesions for their likelihood of being associated with cancer. Our methods can be readily translated to the clinical laboratory for validation in a larger dataset and subsequently implemented through policy guidelines to the community level. 
 
 
 
 
 
 
 
 Innovative elements of the project: 
 
 The innovative elements of the project are the use of recurrent, common alterations in the DNA of breast cancers to predict likelihood of progressing to cancer. The concept of applying genomic data to breast cancer prevention is also highly innovative. Improved knowledge of which proliferative lesions will develop into cancer will help reduce cancer incidence and mortality by indicating when and where aggressive clinical treatment, like complete surgical excision, chemoprophylaxis, and/or close follow-up with the possible addition of intensive surveillance techniques such as breast magnetic resonance imaging (MRI), will benefit the patient and prevent cancer development.