Breakthrough: can a blood test broaden breast cancer screening?
Researchers in Montreal are pursuing a blood-based approach to detect breast cancer in younger women. Led by Dr. Saima Hassan at the Centre hospitalier de l’Université de Montréal, the team is developing a simple blood draw that could help identify who is at risk and speed up diagnosis. The goal is to extend access to screening—especially for women living far from major centers—and to reduce some of the inconveniences associated with mammography.
“I’m really interested in understanding how we can better screen breast cancer in women under 50,” explains Dr. Hassan. “We want to know if a blood test could be used for women under 50, even under 40 or 30 in the future.”
Why target younger women?
In recent years, researchers have observed more cases of breast cancer among younger populations, a trend that poses distinct challenges for screening programs designed around older ages. In Quebec, health authorities have recommended integrating women aged 45 to 49 into the provincial screening program, while current guidelines primarily invite women aged 50 to 74 for biennial mammography. An easy, rapid blood test could help identify high‑risk individuals who might benefit from earlier or more frequent monitoring and could be particularly valuable for those living far from screening centers.
“For some women, the barrier to mammography is not just distance; it’s also the test itself—discomfort and scheduling can deter timely screening,” notes Dr. Hassan. An accurate, quick blood test could improve access and acceptance, enabling faster triage and reducing delays in diagnosis.
How does the technology work?
The laser-immune profiling approach
The research combines a laser‑based profiling technique of immune cells with advanced data analytics to create a high‑dimensional blood test. By examining immune cell signatures and related biochemical signals in the blood, scientists aim to detect early hallmarks of breast cancer even before tumors become radiologically apparent.
The team is using data from blood samples of women with diagnosed breast cancer alongside samples from healthy controls to train the system. This process teaches the artificial intelligence to recognize patterns that correlate with cancer, refining its ability to flag potential cases for further testing. As the model learns, it can incorporate individual factors such as age and, in the future, ethnicity, aligning with the broader aim of precision medicine—customizing screening and diagnostics to the patient’s profile.
“AI is a way to merge different signals—from the immune system to biochemical cues—and extract the most meaningful indicators for detecting breast cancer,” says Dr. Hassan. Yet she cautions that, even with a promising blood test, a biopsy will likely remain necessary for a definitive diagnosis and treatment planning when cancer is confirmed.
What does this mean for screening and care?
If proven effective, a rapid blood test could be deployed as a frontline screening tool to stratify patients by priority. Those with suspicious results could be fast-tracked for imaging and biopsy, while others might continue routine monitoring. Such a paradigm would complement, not replace, existing methods, potentially reducing unnecessary mammograms and revealing cancers earlier in younger women where outcomes can be better with timely intervention.
Next steps and timeline
Several years of work remain to validate the approach and demonstrate its reliability across diverse populations. The Montreal project is currently expanding its sample sets and refining the AI models to ensure reproducibility and clinical usefulness before any broader rollout. The work underscores a broader push in cancer research toward more accessible, patient-friendly screening options that can adapt to regional needs and demographic differences.
Meet the team and the funders
In addition to Dr. Hassan, the project brings together Dr. Réjean Lapointe, engineer Frédéric Leblond, and AI expert Samuel Kadoury. The research is supported by the Canadian Cancer Society and the Lotte & John Hecht Foundation, highlighting strong collaboration between institutions, clinicians, engineers, and data scientists in advancing cancer detection and care.
