As an EXCEL summer scholar, Destiny Ortiz Fernandez ’22 is working to uncover if there is a genetic link between race and two types of kidney cancer: papillary renal cell carcinoma and chromophobe renal cell carcinoma. She is collaborating with Khadijah Mitchell, Peter C.S. d’Aubermont, M.D., Scholar of Health and Life Sciences and assistant professor of biology, a human geneticist who focuses on health disparities. Together, they hope to better understand why cancer tumors tend to be more aggressive in African Americans. If there is a genetic factor, it means scientists can develop therapies that target the cancer in more effective ways.

Khadijah Mitchell and Destiny Ortiz Fernandez ’22 in masks and lab coats in Rockwell lab

Khadijah Mitchell (left) is mentoring Destiny Ortiz Fernandez ’22.

“I think it’s really important to study racial health disparities, and how they are impacting communities of color, specifically Black communities,” says Fernandez, a neuroscience major. “I hope that this project contributes to a future where health disparities are taken into consideration when looking at how to help communities that are disproportionately impacted by diseases. Knowing that my work is meant to help people who look like me or people from my community is extremely humbling and a privilege. As a Lafayette student, this experience is further prepping me for my future endeavors as a scientist. Under Dr. Mitchell’s mentorship, I feel more confident than ever in my skills and knowledge.”

Learn about other student-faculty research projects.

Undergraduate Research

EXCEL Scholars Program

Lafayette is dedicated to providing students unique academic opportunities. Scholars work closely and collaboratively with faculty on significant research projects that hone critical-thinking and communication skills.

Learn more
Categorized in: Biology, Class of 2022, Innovation and Research, Neuroscience, News and Features, Research, STEM, Students

Leave a Reply

Your email address will not be published.

You may use basic HTML tags and attributes.