Arpit Aggarwal
BME PhD Proposal Presentation

Date: 2024-03-20
Time: 3-4pm EST
Location / Meeting Link: Zoom (via link: https://emory.zoom.us/j/4346780350?omn=95308864196)

Committee Members:
Anant Madabhushi (Advisor); Saurabh Sinha; Ahmet Coskun; Susan Modesitt; T. Rinda Soong


Title: Digital Pathology-based Biomarkers for Prognosis in Gynecologic Cancers

Abstract:
Gynecologic cancers, such as ovarian, cervical, and uterine cancers, play a significant role in cancer-related mortality among women in the United States. This emphasizes the need for precise prognostic tools to guide treatment decisions and improve survival outcomes. This proposal aims to tackle these challenges by leveraging digital pathology to analyze Hematoxylin and Eosin (H&E) images, providing a nuanced understanding of the Tumor Microenvironment (TME) of gynecologic cancers. The primary focus is on quantitatively evaluating the combined impact of immune and collagen components on the progression of gynecologic cancers. To achieve this goal, we have outlined three specific aims: 1. Phenotyping Diverse TME Components through H&E Image Analysis: Develop a robust pipeline to segment and extract quantitative features from TME components, including tumor-associated macrophages, tumor-infiltrating lymphocytes, and collagen fibers. 2. Investigating Translational Impact of Quantitative Features from Diverse TME Components on H&E Images: Explore the combined impact of Tumor-Infiltrating Lymphocytes and Collagen architecture features on gynecologic cancer progression. Additionally, predict the added benefits of immunotherapy for ovarian cancer patients treated with primary debulking surgery using these set of features. 3. Elucidating Tumor Biology of Ovarian Cancers through TME Relationships: Focus on exploring the immune-collagen relationship within the TME to enhance our understanding of ovarian cancer progression.