June 30, 2026 – A novel study has found that obesity is associated with a distinct molecular program driving the transition from early-stage, premalignant breast lesions to invasive breast cancer. Rather than simply showing increased activation of classical invasive pathways, tumors from obese patients exhibited a distinct stress-adaptive phenotype. The findings from the study in The American Journal of Pathology , published by Elsevier, suggest that metabolic health could be an important factor in future risk stratification and treatment decision-making.
Obesity is a major and increasing risk factor for breast cancer. Ductal carcinoma in situ (DCIS), often referred to as stage 0, accounts for nearly 25% of all newly detected breast lesions and carries an increased lifetime risk of developing invasive ductal carcinoma (IDC). However, not all DCIS lesions progress to IDC.
There are still many unknowns regarding the molecular mechanisms and how obesity exactly impacts the progression of early-stage, premalignant breast lesions to invasive breast cancer.
"A significant clinical challenge in DCIS is determining which lesions are most likely to progress to invasive breast cancer so that patients are not overtreated or undertreated," explains lead investigator Elizabeth A. Wellberg, PhD, Department of Pathology, Stephenson Cancer Center, and the Harold Hamm Diabetes Center, University of Oklahoma Health Campus. "Using spatial transcriptomic profiling of epithelial, stromal, and immune compartments from DCIS and IDC lesions in obese and non-obese patients, our study investigated how obesity alters the molecular features associated with breast cancer invasion."
The researchers found that rather than being dominated by classical proliferative and epithelial-to-mesenchymal transition pathways, tumors arising in an obese setting may follow a fundamentally different invasive program driven by metabolic stress adaptation, inflammation, and remodeling of the tumor microenvironment. This was accompanied by an increased sulfatase 2 (SULF2) expression, suggesting that obesity may influence both tumor biology and prognostic interpretation.
"Our study highlights that progression from DCIS to invasive disease is not driven by tumor cells alone. Instead, invasion appears to involve extensive cooperation between epithelial, stromal, and immune cell populations, and obesity influences all of these compartments as well as the signaling interactions between them," says co-lead investigator Bethany N. Hannafon, PhD, Departments of Obstetrics and Gynecology, Cell Biology, and Pathology, and Stephenson Cancer Center, University of Oklahoma Health Campus.
Dr. Wellberg adds, "An important aspect of this work is the recognition that molecular indicators of progression need to be interpreted within their local tissue context. By using spatial transcriptomics, we were able to examine how distinct cell populations interact within the tumor microenvironment, revealing patterns that would likely be obscured in traditional bulk tissue analyses."
These findings suggest that standard prognostic approaches may not fully capture invasive risk in obese patients. Incorporating metabolic health, immune composition, and obesity-associated molecular features into diagnostic and prognostic models could improve risk stratification and patient management.
In addition, the identification of pathways associated with oxidative stress, inflammatory signaling, and extracellular matrix remodeling, including upregulation of SULF2, may help identify new therapeutic targets specifically relevant to the progression of obesity-associated breast cancer.
Co-investigator Cole Hladik, PhD, Department of Cell Biology, University of Oklahoma Health Campus, concludes, "Our findings suggest that assessing cancer cell-specific markers alone may not fully capture the biological context driving disease progression, particularly in patients with metabolic dysfunction. This study highlights the potential importance of incorporating metabolic factors such as obesity and diabetes into breast cancer risk stratification and treatment planning."
