Stromal Disruption Identified as a Biomarker for Breast Cancer Risk
New research reveals stromal disruption as a key biomarker linked to breast cancer risk and progression.
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Researchers at The National Institutes of Health have discovered a set of alterations in the structure and cellular makeup of breast connective tissue – known as stromal tissue – linked to a higher risk of aggressive breast cancer and poorer survival outcomes.
These changes, termed “stromal disruption”, hold promise as biomarkers to identify individuals at elevated risk for aggressive breast cancer, as well as those more likely to experience recurrence and increased mortality.
The study was published in the Journal of the National Cancer Institute.
Understanding breast cancer
Breast cancer – one of the most common cancers that affects women – occurs when breast cells mutate, become cancerous and form tumors. Typically, the disease affects women aged 50 years and older, but it can also affect younger women and men.
The most significant complication is metastatic breast cancer — breast cancer that spreads to other areas of your body, including your brain, bones, liver and lungs. Approximately 20–30% of women who have early-stage cancer later develop metastatic breast cancer.
Healthcare providers typically start breast cancer screening with physical exams and mammograms to detect potential abnormalities early. When suspicious areas are found, further imaging tests such as a breast ultrasound or magnetic resonance imaging provide detailed views to distinguish between solid masses and cysts. A definitive diagnosis is made through breast biopsy, where tissue samples are examined microscopically by pathologists.
Following diagnosis, immunohistochemistry testing evaluates hormone receptor status, such as estrogen and progesterone receptors, to guide treatment decisions and predict responsiveness to hormone therapies. Genetic testing may also identify mutations like BRCA1 and BRCA2, which influence both risk assessment and personalized treatment strategies.
Despite these tools, current diagnostic methods can miss aggressive tumor traits or inadequately predict disease progression, underscoring the need for more precise biomarkers. The recent discovery of a new tissue biomarker (i.e., stromal disruption) for aggressive breast cancer offers hope for improving diagnosis and patient outcomes by better identifying high-risk tumors.
“Stromal disruption refers to a series of changes in the architecture and cell composition of connective tissues of the breast, known as stromal tissue,” Dr. Mustapha Abubakar, an Earl Stadtman tenure-track investigator at The National Cancer Institute, told Technology Networks. “It is associated with an increased risk of developing aggressive breast cancer among women with benign breast disease and poorer survival among women with invasive breast cancer.”
“We were able to uncover a tissue biomarker for predicting aggressive breast cancer risk and survival outcome by using a single histological slide per patient,” he added.
Linking stromal disruption to breast cancer risk and progression
Abubakar and team used spatially resolved machine-learning algorithms to characterize stromal disruption of 4,023 healthy breast tissue samples, 974 benign breast tissue samples and 4,223 invasive breast cancer samples.
“We used supervised machine learning based on the random forest algorithm,” Abubakar explained. “It was trained to detect tissue level features – including stroma, epithelium and adipose tissue – to characterize stromal features, including architecture (e.g., dense vs loose, remodeled, desmoplastic or necrotic) and to characterize immune and non-immune cells within the stroma”.
In women who donated healthy breast tissue, they identified several risk factors linked to aggressive breast cancer – such as younger age, having two or more children, self-identifying as Black, being obese and family history – which were also associated with increased stromal disruption. This suggests these risk factors may influence breast cancer risk through a shared stromal tissue pathway.
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Among women with benign breast disease, those exhibiting substantial stromal disruption on biopsy faced a higher risk of developing aggressive breast cancer, as well as a faster onset of the disease, compared to those with minimal or no stromal disruption. For women diagnosed with invasive breast cancer, greater stromal disruption correlated with more aggressive disease characteristics and poorer survival outcomes, especially in cases of estrogen receptor-positive breast cancer, the most prevalent subtype.
“Stromal disruption was assessed using standard histological sections (otherwise referred to as hematoxylin and eosin staining), a technique that has been available for more than 100 years and is routinely performed in laboratories around the world at <$2 USD, requiring minimal expertise,” said Abubakar. “This makes stromal disruption inexpensive to assess and could be widely adopted in low-resource settings where molecular analysis is impractical or very expensive.”
Toward innovative therapies
The findings of this study offer valuable insights that could guide the development of innovative cancer prevention and treatment approaches focused specifically on the stromal microenvironment – the supportive tissue surrounding tumor cells. Targeting this microenvironment holds promise because disruptions within the stroma can influence tumor progression and aggressiveness.
Importantly, assessing stromal disruption presents a cost-effective and accessible method, making it particularly suitable for widespread implementation. This is especially relevant in low-resource settings, where advanced molecular analyses are often unavailable or prohibitively expensive, thereby limiting early detection and intervention options.
“We hope to see stromal disruption validated for clinical use. However, several things would have to happen before we can get there, the key to which, I think is the standardization of the machine learning algorithms and feature classification across different image analysis and artificial intelligence (AI) platforms,” Abubakar explained.
The researchers highlighted that stromal disruption is influenced by biological processes such as chronic inflammation and the body’s wound-healing response. These factors can contribute to changes in the tissue environment that may promote the development of more aggressive breast cancers.
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Given this, the team stressed the importance of further research to explore whether interventions aimed at preventing or mitigating stromal disruption – such as lifestyle modifications to reduce inflammation or the use of anti-inflammatory medications – could effectively lower breast cancer risk. This approach may be especially beneficial for women identified as high-risk, potentially offering a practical strategy to reduce the incidence of aggressive breast cancer forms through targeted prevention.
“Thanks to advances in AI (in this case machine learning), we are now able to extract way more information than is previously possible from routine histologic breast tissue slides, offering a practical, cost-effective tool to identify high-risk women for aggressive breast cancer well before disease develops or progresses,” Abubakar concluded.
Reference: Abubakar M, Duggan MA, Fan S, et al. Unraveling the role of stromal disruption in aggressive breast cancer etiology and outcomes. JNCI. 2025:djaf070. doi: 10.1093/jnci/djaf070
About the interviewee
Mustapha Abubakar, MD, PhD, joined The National Cancer Institute as a postdoctoral fellow in the Integrative Tumor Epidemiology Branch in 2017, was promoted to a research fellow in 2020 and was appointed as an Earl Stadtman tenure-track investigator and selected for The National Institutes of Health Distinguished Scholars Program in 2022.
He earned his medical degree from Bayero University, Nigeria, and trained as a pathologist in the Department of Pathology, Aminu Kano Teaching Hospital, Nigeria. He obtained his MSc in epidemiology from the Imperial College London and his PhD in molecular epidemiology, with a concentration in computational pathology and epidemiology, from the University of London’s Institute of Cancer Research: Royal Cancer Hospital, United Kingdom. Dr. Abubakar has received numerous awards for his work, including the DCEG Fellows Award for Research Excellence, Intramural Research Award, Fellowship Achievement Award and the AACR NextGen Star Award.
