Cancer cells in the blood could be key to personalized breast cancer treatment, research suggests. Scientists from the University of Kansas Medical Center and the University of Michigan have developed a method to identify biomarkers that could help doctors choose the most effective treatment for individual patients. This approach could potentially spare patients from unnecessary, aggressive treatments.
The study, published in Science Advances, focuses on ductal carcinoma in situ (DCIS), a type of early-stage breast cancer. DCIS, found in around a quarter of breast cancer patients, often has a good prognosis, but it can become invasive in a significant number of untreated cases. The challenge lies in predicting which patients will benefit from aggressive interventions like surgery, radiation, and anti-hormonal therapy and which may only require surgery or no treatment at all.
Current guidelines recommend that all women with DCIS undergo treatment, including lumpectomy or mastectomy, with radiation therapy for lumpectomy patients and anti-hormonal therapy for hormone receptor-positive cases. However, this approach may be too aggressive for some patients, while others might not receive enough treatment.
To address this issue, researchers developed a 'labyrinth chip' that separates cancer and white blood cells from smaller blood cells. By processing a few milliliters of blood, they can obtain enough cancer cells for diagnostic testing. In the study, they analyzed the genes expressed in cancer cells from 34 patients with DCIS, comparing those in the blood with those in breast tissue biopsies.
The cancer cells from tissue biopsies were classified into four subtypes based on their active genes, two of which were also found in the blood at significant levels. These subtypes were associated with disease progression, chemotherapy resistance, and immune evasion. The researchers also found that Black patients, who tend to have higher breast cancer mortality rates, had more cancer cells in their blood and more immune suppression, suggesting that environmental factors may play a role in cancer progression.
The team is now working on identifying which cell types and biomarkers can reach and remain at secondary sites, using mouse models to track disease progression. This research could lead to more personalized treatment plans, ensuring that patients receive the most appropriate care based on their individual risk factors and cancer characteristics.
