Turning a blood test into a screening tool for breast cancer
Researchers in Montreal are pursuing a blood-based screening that could one day detect breast cancer earlier in younger women. Led by Dr. Saima Hassan, the team combines laser profiling of immune cells with artificial intelligence to interpret complex signals in blood samples, aiming to shift how screening is done for the next generation of patients.
How the approach works
Laser profiling of immune cells
The technique uses laser-based profiling to examine immune cells circulating in a small blood sample. By capturing subtle molecular changes, the method seeks to identify early cancer signatures that might not be visible through traditional imaging, particularly in younger patients whose breast tissue presents differently on mammograms.
AI-driven analysis
Data from blood samples feed into sophisticated AI models designed to distinguish cancer-related patterns from normal biological variation. The researchers train these models by comparing samples from women diagnosed with breast cancer to those from healthy controls, teaching the AI what to look for in diverse patient populations. Over time, the system could refine its predictions and improve accuracy, especially when integrated with a patient’s broader clinical profile.
Why this matters for younger women
Quebec’s health authorities have signaled consideration of expanding screening to include women aged 45–49, with some discussions about even younger cohorts. Currently, screening guidelines invite women aged 50–74 for mammography every two years. A blood-based test could offer a less burdensome option, potentially expanding access for women in remote regions and offering a more comfortable alternative for those who dislike mammography. The goal is to identify individuals at higher risk who should receive further imaging sooner, without overburdening the healthcare system.
Precision medicine and the path to clinical use
The researchers emphasize a precision medicine approach: AI could tailor its analyses to factors such as age and ethnicity, recognizing that immune and biochemical signals can vary across populations. This personalized angle aims to improve sensitivity for younger women, who often present with different disease dynamics than older patients. Yet experts also acknowledge that, even in a best-case scenario, a definitive cancer diagnosis and treatment decisions will still rely on a biopsy when indicated by imaging or clinical suspicion.
What needs to happen before it reaches clinics
The promise is clear, but the work is not finished. The team is actively comparing blood samples from women with breast cancer to those from healthy controls to identify robust biomarkers and validate AI predictions. Before any test is offered in clinical settings, it must undergo rigorous validation, multicenter trials, and regulatory review. The researchers stress that rapid blood screening would function as a triage tool, helping to prioritize who needs imaging and possible biopsy rather than replacing established diagnostics.
Meet the researchers and supporters
The project unites Dr. Saima Hassan of the Centre hospitalier de l’Université de Montréal with colleagues including Dr. Réjean Lapointe, engineer Frédéric Leblond, and AI expert Samuel Kadoury. Funders include the Canadian Cancer Society and the Lotte & John Hecht Foundation, highlighting a strong commitment to advancing cancer screening through innovative science.
Looking ahead
As data accumulates and AI models improve, a blood-based, noninvasive screening option could complement mammography, broadening access for people in rural or underserved areas and reducing the need for frequent, discomforting tests. The ultimate vision is a quick, reliable blood test that helps stratify patients by risk and guides timely imaging and intervention, while preserving the essential role of biopsy in confirming diagnosis and guiding treatment.
