Introduction

The MAESTRO trial had randomized 693 locally advanced or metastatic pancreatic cancer patients to gemcitabine (G) + placebo vs G + evofosfamide (GE) and failed in phase III (OS hazard ratio (HR) 0.84, p=0.059). We hypothesized that clinical trial populations may include biomarker-defined subpopulations that benefit from the tested therapy. The accumulation of a multitude of subtle molecular aberrations during tumor progression limits the efficacy of anti-cancer drugs. A vast array of these variations can be assessed with Poly-Ligand Profiling (PLP), which is utilizing libraries of trillion unique single-stranded oligodeoxynucleotides (ssODNs) with aptameric binding properties. The aims of this study were to develop a PLP library that differentiates pancreatic cancer patients who can benefit (B) or not (NB) from GE or G therapy and identify the molecular targets of novel ligands.

Summary

• Poly-Ligand Profiling (PLP) is a novel platform for classifying pancreatic cancer patients according to their benefit from GE treatment, which is based on aptameric properties of ssODN libraries.
• The average simulated trial using data from all tumors increased the survival benefit to 116% of MAESTRO (average HR = 0.72), and 217% using only primary-site tumor (average HR = 0.63).
• Demonstrated a novel approach for targets identification in FFPE tissue samples, pulled-down with enriched PLP library.
• High-resolution MS of the PLP library pull-downs from gemcitabine non-benefiters cases reliably detected 20 proteins, 11 of which have reported association with pancreatic cancer and 6 of them are associated with gemcitabine resistance. 9 proteins are novel targets and require further evaluation.
• In principle, the novel PLP platform could be applied to different therapeutic®imen for the development of urgently needed companion diagnostic tests in cancer and other diseases.