Introduction

Prognosis in advanced pancreatic ductal adenocarcinoma (aPDAC) is particularly poor. Few patients benefit from second-line chemotherapy, while most experience side effects, highlighting the need for biomarkers. The PREDICT trial examined in aPDAC patients whether first-line time-to-treatment failure (TTF1) predicts second-line treatment failure (TTF2) but found no association. In our translational study we hypothesized that the responsiveness of the tumor immune microenvironment (TiME) might determine second-line therapy outcome and examined whether treatment-naive tissue immune features are also reflected in the peripheral blood after one line of chemotherapy.

Aims & Methods

In the PREDICT trial, patients received 5-FU/LV plus nanoliposomal irinotecan second-line after gemcitabine/nab-paclitaxel (Gem-nabPac) first-line therapy. We stratified PREDICT patients by shortest vs. longest TTF2. Treatment-naive primary tumor tissues from 20 patients were analyzed by NanoString transcriptomic profiling and multiplexed immunohistochemistry to characterize differences in the TiME. Peripheral blood mononuclear cells (PBMCs) were obtained immediately before second-line therapy from 82 patients and analyzed using multiparameter flow cytometry with an automated gating procedure and gene expression profiling via RT-qPCR. A feature selection and machine learning pipeline integrated PBMC and clinical data to derive a minimal predictor for TTF2 outcome and prognosis that was validated across different treatment regimens on an independent external cohort of 30 patients with aPDAC.

Results

Treatment-naive tumors of patients in the long-TTF2 group exhibited an immune-active (“hot”) TiME with CXCR3⁺ CD8⁺ cytotoxic T cell infiltration into the cancer cell compartment via CXCR3-dependant inflammatory chemokine signaling. Analysis of PBMCs obtained directly before second-line therapy showed that these immune features were sustained over one line of treatment and reflected in PBMCs. A PBMC-based machine learning model (“TTF2Pred”) identified a 7-feature immune signature that accurately distinguished long vs. short TTF2 patient groups outperforming multivariate clinical data or CA19-9 benchmark models. TTF2Pred robustness was confirmed by external validation and showed the best overall performance post-Gem-nabPac first-line treatment. Among the seven TTF2Pred features, long-TTF2 patients exhibited more circulating CXCR3⁺ activated T cells and plasmacytoid dendritic cells, while short-TTF2 patients had more circulating platelet–leukocyte (platelet-monocyte, platelet-neutrophil) aggregates and exhausted T cells.

Conclusion

PDAC patients with an immune-active, treatment-naïve TiME have a better outcome on second-line therapy, and these tissue characteristics are reflected in circulating PBMCs after one line of chemotherapy. A parsimonious circulating PBMC-based signature offers a minimally invasive predictor of second-line outcome that could inform personalized therapy.