Germline Variants and the Population-Wide Risk of Breast Cancer
Abstract
Background: Breast cancer often appears multiple times in families, meaning that a first- or second-degree relative has the disease. This tendency reflects a familial predisposition that is linked to genetic causes. That is, there are defects in the DNA that makes up our genetic code – genes – and this causes some women to have a much greater risk than others to develop breast cancer. The exact nature of these defects is known for some genes such as BRCA1, BRCA2, TP53, and PTEN, but they account for only 25% of the familiar risk. So, by and large the majority of breast cancer-related DNA gene defects remain unknown. Overarching Challenge: To improve prevention and early detection of breast cancer, genetic tests have been developed to detect the DNA defects that are already known. But because the known gene defects are relatively few, meaning that they cover only a small fraction of all those that are relevant, the tests have not been very effective so far. Therefore, the overarching challenges our proposal address are (1) identify determinants of breast cancer initiation, risk, or susceptibility and (2) prevent breast cancer. Specially, we aim to identify many more novel DNA defects that are at the root of breast cancer and get passed on from one generation to the next. The discovery of these risk factors would improve our ability to predict which women are at increased risk for breast cancer before they develop it and hence enable us to screen much more effectively. Objectives and Hypothesis: The crux of the matter is how to detect more effectively than is currently possible the DNA defects that predispose to breast cancer. This is very difficult because all individuals carry a large number of DNA defects, and only a small fraction of these affect breast cancer risk. So, finding those by conventional methods is tantamount to looking for a needle in a haystack. What is innovative and impactful about our approach is that we will attempt to discern the causative DNA defects by developing and applying a new way to measure the strength of a DNA defect in causing cancer. The idea is that most DNA defects in healthy women will be negligible in raising cancer risk and can safely be discarded as irrelevant. But in women who later developed breast cancer, there will be a clearly recognizable set of DNA defects that are impactful, and that tend to occur again and again across patients. Those impactful DNA defects should, we believe, be directly relevant to disease risk. Specific Aims: This study is in two main parts. In the first part, our computational team led by the Initiating Principal Investigator (PI) Dr. Olivier Lichtarge will measure properly the strength of a DNA defect. For this, we have unique tools that go back and look at evolutionary history to infer which DNA changes were mild and which were impactful. Once this is measured, we will develop and merge a series of complementary computer programs (algorithms), including machine learning methods, to identify segments of DNA that carry impactful gene defects in patients with breast cancer but not in healthy women, and these defects will then be used as a fingerprint to recognize other women who are at risk of the disease. In a second part of the study, our laboratory team led by the Partnering PI Dr. Yi Li and the co-investigator Dr. Larry Donehower will first use human breast cells to rigorously test the leading DNA gene defects we identified that are novel. After this round of laboratory testing in cultured cells, we will further examine the five leading candidate mutants in our mouse models of human breast cancer that we have specifically designed and developed for this task of validation. Impact: (1) Our results will identify new DNA defects that predispose to the genetic risk of developing breast cancer. (2) In turn, this will lead to new methods to predict risk and thereby develop genetic tests to screen the general population in order to identify a
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310078
Entities
People
- Olivier Lichtarge
Organizations
- Baylor College of Medicine
- United States Army