NEW Project 1: Complex Personalized Cancer Risk Profiles in Diverse Populations
The vision for 21st century medicine is to understand complex disease etiologies in order to Predict individuals at risk, Pre-empt disease development, Personalize treatment, and ensure Participation of diverse populations (the “4P’s”). In our first SPORE funding cycle, we adopted emerging high throughput whole genome strategies including Genome Wide Association studies (GWAS), whole exome sequencing (WES) and whole genome sequencing (WGS) to identify breast cancer risk variants in diverse populations. We developed a protocol of intensive surveillance with biannual MRI and yearly mammograms to preempt disease development in highrisk women and observed for the first time that aggressive breast cancer in BRCA1/BRCA2 mutation carriers could be down-staged with biannual MRI screening.
Controversies and uncertainties in the clinical application of genetic markers for personalized risk assessment, including commercially available panels for mutations in cancer susceptibility genes, remains a huge barrier to the translation of these scientific advances to the clinics serving populations at risk. There are no data regarding patient experiences, and the risks, benefits and clinical utility of either panel or polygenic risk assessment for breast cancer susceptibility. This underscores the urgent need for multidisciplinary translational research that focuses on how to advance gene discoveries into clinical practice in a way that benefits the health and minimizes the risks for cancer patients, and also accommodates individuals’ differences in desires and needs for genomic information.
Our objective in this population science project is to use our unique clinical resources and the outstanding translational genomics infrastructure developed over the past funding cycle, as well as our behavioral science expertise in the ethical, legal and social implications (ELSI) issues associated with the implementation of novel models of genomic risk assessment to address these needs.
We hypothesize that genomic markers influence breast cancer risk and that population specific Polygenic Risk Score (PRS) can be used to stratify diverse populations of women into risk categories.
Aim 1. Evaluate the performance of population specific Polygenic Risk Score in clinically defined cohorts of high-risk women. We will genotype 600,000 SNPs using Oncochip, which has been designed in collaboration with multiple groups interested in identifying common and rare SNPs associated with cancer susceptibility. We will also use a “biobanking” chip HumanCore + Exome) including all exome content and a scaffold of SNPs sufficient with imputation to 1000 Genomes Project data to interrogate the rest of the genome. The combination of these two chips will provide interrogation of the entire genome with deep interrogation of regions already implicated in cancer risk (and pharmaco phenotypes related to cancer) as well as deep interrogation of rare coding variants captured in the first 10’s of thousands of whole genome and whole exome sequencing studies. The combination of these two products will provide efficiencies and economies of scale to genotype 700 cases and 700 controls enrolled in our SPORE. Granular data, including pathology, imaging, treatment, epidemiological questionnaire and blood for genotyping are available on all cases and controls recruited in the previous SPORE funding cycle.
We hypothesize that performance of risk reductive behaviors might be improved with communication of complex personalized uptake cancer risk profiles that include Polygenic Risk Score (PRS).
Aim 2. To assess stakeholder (patient and provider) preferences for, and evaluate the uptake and short term and longitudinal risks and benefits (i.e. patients’ understanding, reactions to, use and perceived utility) of communicating Complex Personalized Cancer Risk Profiles including polygenic risk (as defined in Aim 1 to ethnically diverse high risk patients identified at three Cancer Risk Assessment Programs. Our theoretical model grounded in the Self-regulation Theory of Health Behavior is designed to identify those who might be at greater benefit or risk of receiving this information and how communication of
that information might best be tailored to optimize patient outcomes. We will pre-assess, using combined qualitative and quantitative techniques, stake-holder (patient and health care provider) preferences to inform a theoretically grounded and empirically informed model for return of Complex Personalized Cancer Risk Profiles including polygenic risk results developed in Aim1. We will evaluate uptake and short-term and longitudinal cognitive, affective, behavioral effects of receipt of Personalized Cancer Risk Profiles. We will examine potential biological (e.g., cancer risk factors, personal and familial cancer history), affective (e.g. anxiety, depression, perceived stress) and cognitive (e.g. knowledge and perception of genomic disease) mediators and moderators, as suggested by Self-Regulation Theory of Health Behavior of the biopsychosocial impact of clinical delivery of Personalized Cancer Risk Profiles.