PROJECT SUMMARY
The incidence of Endometrial Cancer (EC) has been rising, with a notable increase in mortality rates, especially
among Black women who face a higher risk of aggressive EC subtypes. Current diagnostic methods for EC are
invasive, costly, and typically utilized in advanced stages of the disease, highlighting a critical need for early
detection techniques. This project aims to enhance early EC detection and understand the complex interplay of
genetic, social, and environmental factors contributing to EC risk, with a focus on addressing disparities in EC
outcomes among different racial and ethnic groups. In the proposed research, we aim to determine the burden
of rare germline pathogenic variation associated with endometrial cancer risk in racially and ethnically diverse
case control cohorts utilizing the All of USs biobank datasets. This approach will provide new insights into the
genetic factors influencing EC, especially in underrepresented populations. We will create advanced risk models
that integrate a wide array of risk factors, including genetic predispositions and lifestyle factors, into
comprehensive predictive models, combining genetic data with non-genetic factors (e.g., BMI, diabetes history,
PCOS) and validated across different racial and ethnic subgroups, offering a personalized risk assessment tool
for EC. The successful completion of this project will yield a comprehensive understanding of the genetic and
non-genetic factors contributing to EC risk, particularly in racial and ethnic groups that have been historically
understudied. The development of integrated risk models will facilitate early detection of EC, leading to timely
interventions and potentially better survival rates. This project has the potential to revolutionize EC screening
and prevention strategies, making them more effective and accessible across diverse populations, thereby
addressing a significant public health concern.
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