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Predicting Recurrence in Triple-Negative Breast Cancer Patients through Analysis of the Tumor-Immune Microenvironment

ISEF · 2020 Computational Biology and Bioinformatics

Patwa, Aalok · Archbishop Mitty High School

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Overview

My research identifies novel ways to predict recurrence in triple-negative breast cancer patients. I used multiplexed ion beam imaging to analyze cell prevalence and protein expression in the tumor-immune microenvironment. My results show that the organization of cells and biomarkers effectively predicts recurrence in TNBC and can help doctors pursue strategic therapies, saving more lives.

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Source: Regeneron International Science and Engineering Fair

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