Abstract 1505P
Background
The recent phase II NEONAX trial examined PO and A Gem-nabPac CTX for rPDAC Pts. The objective of this study was to identify underlying alterations in the tumor immune microenvironment (TiME) associated with shortest (S) or longest (L) disease-free survival (DFS) and to identify corresponding biomarkers predicting CTX success.
Methods
Pts from both study arms were stratified into groups based on S- or L-DFS (n = 32, n = 8 Pts/group). PDAC tissues (surgical resection) were subjected to RNA (NanoStringTM, PanCancer IO360TM) profiling. CTX-naïve blood samples were analyzed via multiplexed ELISA (mELISA, 80-Plex ProcartaPlexTM). For feature selection via machine learning (ML), the Weka-based algorithms WrapperSubsetEval (WSE) with Naïve Bayes, J48, or a multilayer perceptron neuronal network (MLP) were used. Pts were divided into training (80%) and validation (20%) datasets and categorized by using either MLP or J48 classifiers.
Results
Comparisons of L- vs. S-DFS transcriptomics data revealed significantly increased inflammation (upregulated genes: CXCL9, SELP, CDH5), immune cell activation (enriched: NK cell cytotoxicity, activated CD8 T cells), and immune cell infiltration (CD8 T cells, NK cells) for treated (PO group) but not treatment-naïve (A group) L-TTF tumors. Screening of CTX-naïve blood samples (mELISA) detected 80 immune-related factors. Feature selection for S- vs. L-DFS prediction (n = 80 Pts; PO: n = 42, A: n = 38) revealed a panel of 8 proteins for the PO group (Naïve Bayes; CSF3, LGALS3, GZMA, CCL1, IL20, IL3, CCL7, PTX3), 6 proteins for the A group (J48; IL1A, IL1B, IL3, IL34, MIF, CCL19), and 7 proteins for the combined (c)rPDAC group (MLP; CCL21, CX3CL1, IL16, IL20, IL7, PTX3, TSLP). ML successfully predicted S-/L-DFS for the PO (via MLP), crPDAC (via MLP), and A (via J48) group (ROC-AUC (training) > 0.9, ROC-AUC (validation) > 0.9, respectively).
Conclusions
In our study, we have identified a favorable TiME for L-DFS rPDAC Pts under PO Gem-nabPac CTX. We further present minimal immune-related liquid biomarker signatures based on mELISA and ML for early prediction of Gem-nabPac CTX success in PO and A treatment settings, or for rPDAC Pts in general.
Clinical trial identification
NCT02047513; AIO Studie: AIO-PAK-0313.
Editorial acknowledgement
Legal entity responsible for the study
T. Seufferlein.
Funding
Celgene/Bristol Myers Squibb.
Disclosure
All authors have declared no conflicts of interest.
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