TEST:

MammaPrint®

Patients with MammaPrint H2 tumors had a clinically meaningful benefit from anthracycline-containing chemotherapy, whereas patients with H1 tumors did not derive more benefit from AC-T than from TC despite overlapping high-risk features. These findings support the use of MammaPrint to inform chemotherapy regimen selection and warrant further validation.

P2, N=40, Recruiting, University of Illinois at Chicago | Trial completion date: May 2026 --> May 2027 | Trial primary completion date: May 2026 --> May 2027

Short-course preoperative ET induces rapid and reproducible morphological and immunophenotypic changes in ER-positive, HER2-negative breast cancer. Ki67-defined response is associated with genomic risk and PR expression, whereas microenvironmental features appear to have limited predictive value.

P1, N=32, Active, not recruiting, Patrick Dillon, MD | Recruiting --> Active, not recruiting

P=N/A, N=750, Completed, Novartis Pharmaceuticals

P=N/A, N=22, Completed, Universitair Ziekenhuis Brussel | Recruiting --> Completed

Approximately one-third of patients who met GEP criteria and were eligible for publicly known reimbursement received a GEP. Appropriate follow-up steps and further research seem required to analyse reasons for not ordering a GEP in times of reimbursement, since GEP results help chemotherapy decision-making.

We established a low-ITH subtyping framework that overcomes the limitations of single-biopsy-based molecular typing. Our findings offer a novel strategy to enhance the precision of breast cancer management.

P3, N=3680, Recruiting, National Cancer Institute (NCI) | Trial completion date: May 2027 --> May 2032 | Trial primary completion date: May 2027 --> May 2032

BRIDGE is a biologically grounded framework for neoadjuvant BC response prediction, validated on a rich set of different patients' cohorts. Its histopathology-based version opens the door for fast and low-cost prediction in the neoadjuvant setting, upon further prospective testing and validation.

P2, N=44, Recruiting, Abramson Cancer Center at Penn Medicine | N=66 --> 44

Although evaluated in breast cancer, CNet-Cox is readily extensible to other diseases, molecular interaction networks and time-to-event endpoints, providing a generalizable tool for digital pathology and precision oncology. Overall, our comprehensive downstream analyses highlight that CNet-Cox offers a novel network-aware survival model for systematically discovering connected biomarkers and delivering scalable, precise and interpretable risk prediction.