Broadly, this project aims to characterize the heterogeneity of tumors on a genetic, transcriptional, and spatial level. Specifically, by applying Slide-seq, a spatial transcriptomics method with near-cellular resolution, to prostate cancer samples, we may identify genetic variants that reflect processes relating to tumor growth and development. By identifying somatic mutations, we hope to delineate genetic differences in tumor tissue and potentially subclonal structure, which has key implications in prostate cancer treatment, which faces challenges in treatment variation between individuals and the development of drug resistance over time.

I am participating in SuperUROP, because I am interested in research in the long-term, and the program provides a structured way to investigate and communicate a project. I have done research in bioinformatics since high school, and am excited to contribute to a fast-evolving field with major biomedical applications.