Immunofluorescence profiling of collagen subtypes is a predictor of treatment outcomes in pancreatic cancer.

Desmoplasia in pancreatic ductal adenocarcinoma (PDAC) is characterized by elevated levels of tumor collagen. Desmoplasia restricts drug delivery in PDAC, contributes to treatment resistance, and is associated with poor survival outcomes. We have previously shown that photodynamic therapy (PDT)-based treatment remediates desmoplasia in orthotopic PDAC tumors by reducing second harmonic generation signals from collagen by >90% and by reducing collagen alignment by >10-fold [19]. Remediating desmoplasia correlated with improved survival outcomes in mice. To understand this phenomenon at a fundamental level, it is important to dissect the impact of therapy on collagen subtypes. In this study, we demonstrate that immunofluorescence profiling of collagen subtypes I, II, III and IV in PDAC tumors 72 h following multiple treatment regimens is predictive of long-term outcomes. Treatment regimens include nanoliposomal irinotecan chemotherapy (nal-IRI; akin to ONIVYDE™), a combination of nal-IRI chemotherapy with PDT encapsulated in a single photoactivable multi-inhibitor liposome (PMIL) and an EGFR-targeted PMIL construct (TPMIL). Results show that the relative tumor content of collagen I, II and III was inversely correlated with overall survival (P ≤ 0.0013, P ≤ 0.0001, P ≤ 0.0011, respectively), while, surprisingly, the relative tumor content of collagen IV was directly correlated with overall survival (P ≤ 0.0001). Similar relationships were observed between the relative tumor content of collagen subtypes and the residual tumor volume at day 88 following treatment. Considering that the relationship between collagen subtypes and treatment outcomes is observed across multiple treatment regimens, immunofluorescence profiling at 72 h following treatment appears to be predictive of tumor growth inhibition and survival in PDAC. Early immunofluorescence collagen subtype profiling may therefore aid in treatment personalization and may inform the dosimetry and scheduling of combination regimens for PDAC, such as chemotherapy and emerging PDT-based combinations, to maximize patient survival benefit.