Big Data Powers USU Student Quest for Precision Oncology

By harmonizing thousands of public samples, this Navy M.D./Ph.D. candidate is using USU's computational power to uncover the protein signatures that define aggressive tumors.

April 2, 2026 by Hadiyah Brendel

Navy Ensign Joseph LaMorte, a member of the Class of 2030, is part of a growing cohort of graduate student-scientists who are leveraging big data to "crack the code" of human disease. Recently commissioned into the U.S. Navy on March 11, 2026, LaMorte is using the computational power at the Uniformed Services University (USU) to uncover the protein signatures that define aggressive tumors.

Working with massive, publicly available datasets-including those from the Murtha Cancer Center's APOLLO (Applied Proteogenomics Organizational Learning and Outcomes) project-LaMorte performed a "harmonized" pan-cancer analysis. By applying uniform statistical tests across thousands of samples from various cancer types, he identified universal trends in how RNA and protein correlate.

"People have looked at RNA and protein in individual cancer types before, but they were all using different methods," LaMorte explained. "By harmonizing the data across all cancer types, we could see if trends in RNA-to-protein regulation existed in common. We found that how closely these correlate-a statistic we call SRPC (Sample-wise RNA-to Protein Correlation)-tells you a dramatic amount about the tumor microenvironment."

Harmonizing the Data: Beyond the Mutation

LaMorte conducts his research under the mentorship of Dr. Matthew Wilkerson, professor of Anatomy, Physiology and Genetics and director of the Data Science Division for Military Precision Health at USU. Wilkerson's lab targets the gap between a tumor's genetic instructions (RNA) and its actual machinery (proteins).

While traditional oncology has long focused on mutations, LaMorte points out that over 50% of cancer patients have tumors with no identifiable driving mutation. To help these patients, researchers must look deeper into the cellular "neighborhood."

The Mismatch in the Machinery

The significance of this research was highlighted in a paper LaMorte co-authored with leaders in the field, including Dr. Craig Shriver, director of the Murtha Cancer Center/Murtha Cancer Research Center and Dr. Thomas Conrads. The study demonstrated that in many tumors, the "instructions" (RNA) do not match the "machinery" (proteins).

LaMorte's harmonization of these datasets revealed a striking biological divide between high SRPC tumors and low SRPC tumors. High SRPC tumors are primarily composed of cancer cells with rapid proliferation and distinct mutations. They often have a "weaker" immune environment, which can lead to significantly worse patient outcomes. Low SRPC tumors are often filled with "gunk" are supporting stromal cells, immune infiltration, and blood vessels. While complex, this "immune-rich" environment suggests the patient might be a better candidate for immunotherapy.

Clinical Precision: The Breast Cancer Case Study

The real-world impact of LaMorte's work lies in diagnostics, and his research specifically focused on breast cancer as a primary example. Because breast cancer treatment relies heavily on subtyping-identifying markers like HER2, estrogen receptors (ER), or progesterone receptors (PR)-diagnostic accuracy is critical.

Currently, these markers are often identified using either RNA or protein stains. However, LaMorte's work shows that if a patient has a "low correlation" tumor, an RNA test might return a different answer than a protein test.

"Our paper suggests that both need to be taken into consideration so patients don't get misclassified," LaMorte said. "We want to ensure that someone who could benefit from a treatment like anti-PDL1 actually receives it, and conversely, that a patient isn't subjected to the side effects of a medication that won't actually help them."

The Road to 2030: The Digital Oncologist

A member of the Class of 2030, LaMorte entered the M.D./Ph.D. program in 2023, following a familiar path. He is one of six brothers, and the second in his family to attend USU; his elder brother graduated from the university's School of Medicine in 2019.

"My brother went straight to medical school, but having him here put the university on my radar," LaMorte recalled. "When I looked at the M.D./Ph.D. program, I loved that USU is focused on efficiency. While many programs take eight or nine years, USU works with you to establish a project early, aiming for a seven-year completion. It's a great environment for supporting research alongside medical training."

As an ensign in the Navy, LaMorte views his bioinformatics training as a "portable" lab. When he completes his seven-year journey in 2030, he plans to move into an internal medicine residency followed by an oncology fellowship.

"One thing that's great about being equipped with these bioinformatics tools is that I don't need a physical lab space to do research," LaMorte noted. "I can primarily see patients as an oncologist, but then in whatever spare time I have, I can dive into research questions just from my computer."

By bridging the gap between big data and bedside care, LaMorte is ensuring that the next generation of Navy medicine is as precise as it is lethal against the threat of cancer.