July 24, 2025 Story by: Publisher
Groundbreaking research from Emory University has used artificial intelligence to identify genetic and pathologic differences that may explain why Black women experience worse outcomes from endometrial cancer—a disease that affects over 66,000 women in the U.S. each year.
Black women are particularly at risk, with an 80% higher mortality rate than other demographic groups and a greater chance of contracting more aggressive cancer subtypes. Regardless of lifestyle choices and health care equity, studies still show Black women have lower survival rates.
“Racism and equitable access to health care certainly play a big role in the increased mortality for populations of color,” says Anant Madabhushi, executive director of the Emory Empathetic AI For Health Institute. “But with endometrial cancer, it may not completely explain the difference in mortality. One of our underlying hypotheses is that beyond social determinants of health, there are also potentially biological differences between different populations that need to be studied in a very precise way.”
Led by Emory’s Department of Pathology and Laboratory Medicine, the study represents one of the most comprehensive AI-based investigations into racial disparities in gynecologic cancer outcomes to date. Researchers leveraged machine learning to analyze histopathologic images and tumor genomic data from large, national cancer databases.
Endometrial cancer is a type of cancer that begins in the lining of the uterus, known as the endometrium. It is the most common form of uterine cancer, often affecting women after menopause. Symptoms may include abnormal vaginal bleeding, pelvic pain, or weight loss. While often treatable if caught early, more aggressive subtypes can be harder to manage—especially among certain populations, like Black women, who face disproportionately worse outcomes due to both biological and systemic factors.
In their research, published recently in NPJ Precision Oncology, Madabhushi’s team examined tissue slides of endometrial tumors from populations of both African American and European American women. They looked for differences in overall structural features and complex microscopic interaction in the tumor between the body’s natural immune cells and different subcellular features such as connective tissue.
Machine learning helped sort the results into different risk models for the two groups, based particularly on differences between the behavior of tumor infiltrating lymphocytes, the white blood cells that attack the tumor as part of the body’s natural response to cancer. In the data used to train AI models, white women were more likely to have tumors associated with better survival rates, while Black women had a higher proportion of subtypes with higher mortality.
The AI-developed risk profiles found that in Black women, those lymphocytes tended to interact more with the cellular supporting tissue called stroma, but in white women, they interacted with epithelial tissue, the layer of protective cells that line internal and external body surfaces. The investigators found that a risk model that combined both groups didn’t accurately predict risk for Black women. Only the risk profile developed specifically from the data from Black women was able to more precisely predict greater risks for that group.
“We absolutely could not have made these discoveries without AI,” says Madabhushi, who’s affiliated with Emory’s Winship Cancer Institute. He doesn’t hesitate to call it a “stunning” insight into ways cancer develops in different populations.
The discovery has implications for the developing science of immune therapy, which harnesses the body’s natural defenses, including tumor infiltrating lymphocytes, to fight cancer.
“As we think about therapeutics for Black women with endometrial cancer, we may have to explicitly consider the findings in this study in the way we design immunotherapies for Black women as opposed to the way we’ve previously done it, which is sort of a one size fits all,” says Madabhushi.
He adds that gynecologic cancers haven’t been as publicly visible as breast cancer tends to be. One of the goals of the Empathetic AI for Health Institute is to look at projects that disproportionately affect underrepresented populations.
“If you want to pick an example of a disease that disproportionately affects women of color, It has to be endometrial cancer,” he says. Though the new study doesn’t explain everything about how tumors develop in different populations, Madabhushi says it clearly establishes that cancer progression isn’t a single thing but is driven by genetic differences.
Key Findings
- Black women are more likely to develop aggressive subtypes of endometrial cancer, particularly high-grade, non-endometrioid tumors.
- AI detected significant differences in the tumor microenvironment and mutational profiles, which could influence how cancers grow and respond to treatment.
- Even after adjusting for known factors like age, tumor stage, and socioeconomic status, Black women were more likely to have tumors with markers of poor prognosis.
Recent data highlight a concerning racial disparity in EC survival rates, particularly with African American (AA) women facing a significantly higher mortality risk compared to European American (EA) women.
The 5-year mortality rate stands at 39% for AA women and 20% for EA women, drawing attention to multifaceted disparities rooted in systematic racism, structural biases, and cultural influences.
Studies have shown that delayed diagnoses among AA women contribute to this higher mortality, along with lifestyle choices and comorbid conditions.
Although AA women more often present with advanced stages of disease, higher grade tumors, and more aggressive type II tumors, their survival is significantly lower for all tumor types even after stratifying by age, stage, and grade
Why It Matters
Endometrial cancer is among the few cancers where mortality rates are rising, and Black women are nearly twice as likely to die from the disease compared to white women. Previous research has cited systemic inequities in care and delayed diagnosis, but this study points to biological differences as well—differences that could guide more tailored treatments in the future.
The researchers hope this data can inform the development of personalized therapies, diagnostic tools, and risk stratification models that are racially inclusive.
What’s Next?
Emory’s team is now collaborating with oncologists and geneticists nationwide to expand the dataset and validate the findings in clinical trials. They are also advocating for increased funding to study racial disparities in cancer biology, a field historically underfunded.
