Announcing four new research awards for 2025

Four new Joint Institute research projects were awarded for 2025, bringing to 81 the total number of JI projects funded since the partnership’s launch in 2010. Three of the latest awards focus on cancer research—specifically breast, renal, and colorectal cancers—while a fourth project will apply artificial intelligence to help clarify whether COVID-19 vaccines are linked to serious effects.

Congratulations to the following research teams.

Engineered Bacteroides Vulgatus with Enhanced Cysteine Uptake to Boost Immunotherapy for Colorectal Cancer

UMMS PI: Grace Chen, MD, PhD (Internal Medicine)

PKUHSC PI: Pengyuan Wang, PhD (Surgery)

This project will study whether a specially modified gut bacteria, called Bacteroides vulgatus (BV), can boost the body’s immune response against colon cancer. The team will explore how this bacteria affects the tumor microenvironment and whether it helps make tumors more sensitive to immune checkpoint inhibitor (ICI) treatments. Specifically, the focus is on a version of Bacteroides vulgatus that have been engineered to be better at taking up cysteine, a natural amino acid (building block of protein) found in the intestines. In previous research, the team found that this engineered bacteria lowers cysteine levels in the gut, slowing tumor growth without causing harmful side effects in the rest of the body.

Now, Drs. Chen and Wang want to understand exactly how these bacteria help stop tumors from growing, and if they can make cancer treatments like ICIs work better—even in types of colon cancer that usually do not respond well to these treatments. Their findings could pave the way for new treatments that use the microbiome (the collection of bacteria in our gut) to help cancer immunotherapies work better in colon cancer and possibly other types of tumors.

Using Large Language Models and Biomedical Ontologies for Mobilizing the Construction and Applications of Directed Acyclic Graphs in Observational Health Data Research

UMMS PI: Oliver He (Microbiology & Immunology)

PKUHSC PI: Jian Du, PhD (National Institute of Data Science)

This project aims to improve COVID-19 vaccine research—specifically, understanding whether vaccines are linked to rare but serious side effects—using powerful artificial intelligence (AI) to read, sort and filter information from vast amounts of research data and health records. Employing language processing AI combined with medical dictionaries ensures data input is properly labeled, defined and understood in the same way, ultimately helping to discern actual causation from mere anecdotal coincidence.

The team’s ontology system will pull together and analyze evidence from different studies, creating a map (i.e., knowledge graph) showing possible cause-and-effect relationships between COVID19 vaccines and side effects such as Guillain-Barré Syndrome, kidney problems, heart inflammation, or blood clots. It uses established scientific approaches to make clear, understandable diagrams that guide researchers on which factors to focus on. By bringing together data from many sources and keeping the results transparent and current, this work will strengthen safety monitoring for COVID-19 vaccines and help support fact-based decisions to address concerns about vaccine safety.

Comprehensive Spatial Profiling of the Tumor Immune Microenvironment of Metastatic Renal Cell Carcinoma

UMMS PI: Simpa Salami, MD, MPH (Urology)

PKUHSC PI: Tao Xu, MD (Urology)
PKUHSC PI: Zixiong Huang, MD (Urology)

Renal cell carcinoma (RCC) is the most prevalent type of kidney cancer and is particularly dangerous because metastasis is common. New treatments called Immune Checkpoint Inhibitors (ICIs) have had success but are sometimes less effective for patients with metastatic renal cell carcinoma. By researching the Tumor Immune Microenvironment—the mix of different immune cells and other elements in and around the tumor—this team hopes to identify the mechanisms through which these cells interact with one another to promote or inhibit tumor growth, thereby improving the effectiveness of ICI treatments.

They will deploy advanced genetic analysis techniques on cancer tissue samples taken from patients at both research sites, looking carefully at both the spatial arrangement of cells and the detailed genetic makeup of the primary tumor and its metastases. Importantly, the project aims to broaden our understanding of how this cancer behaves and responds to treatments, potentially leading to better ways to predict and treat it in the future.

The Effect of pEZH2(T367) on the Tumor Microenvironment of Triple Negative Breast Cancer

UMMS PI: Celina Kleer, MD (Pathology)

PKUHSC PI: Yuqing Wang, MD (Institute for Medical Innovation and Research)

This project builds on a collaboration started when Dr. Wang visited Michigan Medicine for 12 months as a Joint Institute Collaboration Scholar, working alongside Dr. Kleer on breast cancer research. Triple negative breast cancer (TNBC) is a complex because each tumor is different and it often resists typical treatments, including chemotherapy and some immune-based therapies. In previous research, we discovered that, under certain conditions, the protein EZH2 can make TNBC more likely to spread by effectively hiding the tumor from the immune system. The team hypothesizes that a uniquely tagged version of EZH2 (pEZH2-T367) helps TNBC escape the immune system by changing the way tumor cells use energy and interact with immune cells. To investigate, they have modified TNBC cells in the lab and found that when the T367 part of EZH2 was changed, the tumors showed increased signs that the immune system could recognize and attack them.

To build on these findings, this project utilizes a special mouse model that mimics human TNBC. The work will shed light on how pEZH2-T367 alters the structure of DNA in TNBC cells and learn how these changes help the tumor avoid the immune system. Ultimately, this research could reveal new ways to predict which TNBC patients might respond to immunotherapy and discover new targets to make these treatments work better.