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Researchers at the University of California, San Diego, have discovered a promising method to predict whether early-stage breast cancer will spread by evaluating the “stickiness” of tumor cells. This breakthrough, enabled by a specially designed microfluidic device, could significantly enhance diagnostic capabilities and help doctors personalize treatment strategies for high-risk patients.
Innovative Microfluidic Device
The newly developed device, tested in an investigator-initiated trial, sorts tumor cells by pushing them through fluid-filled chambers and measuring their adhesion to chamber walls. The study, published on March 5 in Cell Reports, found a compelling trend: tumor cells from aggressive cancers exhibited weak adhesion, while those from less aggressive cancers were more strongly adherent.
Professor Adam Engler, senior author and faculty member at UC San Diego’s Jacobs School of Engineering, emphasized the significance of this discovery: “If we can improve diagnostic capabilities with this method, we could better personalize treatment plans based on the tumors that patients have.”
Predicting Metastasis Risk in Breast Cancer
Previous research by Engler’s lab in collaboration with Dr. Anne Wallace, director of the Comprehensive Breast Health Center at Moores Cancer Center, established that weakly adherent cancer cells have a higher tendency to migrate and invade other tissues. The latest study focused on ductal carcinoma in situ (DCIS), an early-stage breast cancer that can either remain confined to the milk ducts or develop into invasive cancer. Current clinical decisions often rely on the lesion’s size and grade, which do not always accurately predict its behavior.
Dr. Wallace underscored the clinical importance of the study: “We don’t want to over-treat patients unnecessarily, but we must intervene aggressively when there’s a high risk of invasive cancer. This adhesion model could help us make more informed decisions.”
How the Device Works
Approximately the size of an index card, the microfluidic device contains chambers coated with fibronectin, an adhesive protein found in breast tissue. Tumor cells are introduced into the chambers and subjected to increasing shear stress as fluid flows through. Researchers classify cells based on when they detach, differentiating between strongly and weakly adherent cells.
The device was tested on tissue samples from 16 patients, including normal breast tissue, DCIS tumors, and invasive breast cancer tumors. The findings revealed that aggressive breast cancer samples contained weakly adherent cells, while normal breast tissue exhibited strong adhesion. DCIS samples varied, indicating a potential predictive metric for metastasis risk.
“Among DCIS patients, we found some with strongly adherent tumor cells and others with weakly adherent cells,” said Madison Kane, a bioengineering Ph.D. student and study co-first author. “We hypothesize that those with weakly adherent cells are at higher risk of developing invasive cancer and may be underdiagnosed initially.”
Future Implications
Researchers plan to track DCIS patients over five years to assess whether adhesion strength reliably predicts metastatic progression. If validated, this technique could provide oncologists with a powerful new tool for guiding treatment decisions and intervening before cancer spreads.
Professor Engler expressed optimism about the technology’s impact: “Our hope is that this device will allow us to identify high-risk patients early, so we can intervene before metastasis occurs.”
This project was made possible through interdisciplinary collaboration between UC San Diego’s bioengineering department and Moores Cancer Center. Funding from the National Institutes of Health, the National Science Foundation, and the National Cancer Institute played a crucial role in supporting the study.
Disclaimer:
This article is for informational purposes only and does not constitute medical advice. Patients should consult with their healthcare providers for personalized medical guidance. The findings discussed here are based on ongoing research and require further validation before clinical application.
