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

Booth Id:
CBIO040

Category:
Computational Biology and Bioinformatics

Year:
2020

Finalist Names:
Patwa, Aalok (School: Archbishop Mitty High School)

Abstract:
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.