Kelsey LaBella, PA-C
Physician Assistant
Yale New Haven Hospital
New Haven, Connecticut, United States
Kurt Schultz, MD
Surgery resident
Yale New Haven Health
New Haven, Connecticut, United States
Justin Bader, MD
Resident Physician
Yale New Haven Hospital
New Haven, Connecticut, United States
Nicole Aguirre, MD
Resident Physician
Yale New Haven Health Center
New Haven, Connecticut, United States
Kwasi A. Ofori, MBChB, MPH
Postdoctoral Researcher
Yale University School of Medicine
New Haven, Connecticut, United States
Alexandra M. Gustafson, MD
Resident Physician
Yale New Haven Hospital
New Haven, Connecticut, United States
David G. Su, MD
Resident Physician
Yale New Haven Hospital
hamden, Connecticut, United States
Anup Sharma, PhD
Research Scientist
Yale School of Medicine
New Haven, Connecticut, United States
Raghav Sundar, MD, PhD
Medical oncologist
Yale New Haven Health
New Haven, Connecticut, United States
Kiran K. Turaga, MD, MPH (he/him/his)
Chief of Surgical Oncology, Professor of Surgery
Yale University
New Haven, Connecticut, United States
Princy Gupta, MBBS
Postdoctoral Researcher
Yale School of Medicine
New Haven, Connecticut, United States
Treatment outcomes for peritoneal metastases (PM) remain highly variable, with marked interpatient heterogeneity in chemosensitivity and no established predictive biomarkers. Mass-based response testing (MRT) generates patient-specific drug sensitivity profiles by integrating genetic, epigenetic, and environmental factors. This study evaluates the feasibility of MRT in peritoneal metastases and its correlation with clinical response to chemotherapy before and after surgery.
Methods:
During surgery, viable tumor cells from peritoneal metastases were collected and treated ex vivo with chemotherapeutic agents. The single-cell mass distributions of control and drug-treated populations were compared to generate drug sensitivity profiles within 48 hours of sample acquisition. MRT predictions generated from tumor collected during surgery were correlated retrospectively with responses to neoadjuvant chemotherapy and prospectively with outcomes from chemotherapy administered after surgery.
Results:
MRT was performed on 29 patients: 19 with colorectal cancer, 7 with appendiceal cancer, 2 with mesothelioma, and 1 with an unknown primary. Among 18 patients evaluable for neoadjuvant chemotherapy, MRT predicted resistance in 83% (5/6) of patients who demonstrated radiographic progression. Correlation with post-surgery chemotherapy was available for 8 patients; MRT predicted resistance in 75% (3/4) patients who subsequently experienced progressive disease. Overall, 83% (15/18) of patients were predicted to be resistant to the chemotherapy they had received pre-operatively. Full radiographic correlations are summarized in Table 1.
Conclusions:
This study establishes the feasibility of performing MRT on PM samples, including those from previously treated patients. Across both neoadjuvant and adjuvant settings, tumors demonstrating resistance by MRT were associated with radiographic progressive disease. These findings support further evaluation of MRT as a functional precision-medicine tool to guide therapy selection in PM.