Innovative platform for chemoresistance: advancing functional precision medicine in breast cancer

Abstract

To validate a novel in vitro chemoresistance platform by assessing the chemoresistance profiles of naïvetreatment breast cancer and residual tumors after neoadjuvant chemotherapy. Methods: Patients with primary invasive
breast cancer (naïve-treatment) and residual disease after neoadjuvant chemotherapy were included. Tumor samples were
obtained and cultured on the chemoresistance platform with several cytotoxic drugs used for breast cancer treatment.
After 72 hours, cell viability was evaluated, with resistance categorized as low, intermediate, and high. Results: Samples
from 70 patients with primary breast cancer and 27 with residual disease after neoadjuvant chemotherapy were tested
using the chemoresistance platform. Patients undergoing upfront surgery exhibited significantly favorable clinicopathological characteristics and prognosis, such as older age, smaller tumors, negative axillary lymph node, and luminal subtype, compared to those with residual disease who presented younger age, larger tumors, positive axillary lymph node,
and more triple-negative breast cancer. The chemoresistance platform revealed distinct resistance patterns, with tumors
showing higher resistance to taxanes than to anthracyclines and cyclophosphamide (p<0.05). Residual disease after neoadjuvant chemotherapy exhibited significantly higher resistance to docetaxel, paclitaxel, doxorubicin, and cyclophosphamide than primary tumors, possibly indicating the acquisition of resistance during treatment. High resistance in residual disease after neoadjuvant chemotherapy correlated with a worse prognosis, with 8% experiencing local recurrence,
24% developing metastasis (p=0.0001), and 12% dying from disease progression (p=0.0500). Overall survival was 98.5%
in the primary tumor group and 88% in the residual disease after neoadjuvant chemotherapy group. Conclusion: The
chemoresistance platform effectively identified drug resistance patterns based on tumor characteristics, demonstrating
the potential of functional precision medicine to personalize and improve breast cancer treatment by avoiding inefficient
drugs, particularly in the context of treatment de-escalation.