Communications BiologyCancer BiologyPeer-reviewed journal article
Neutrophil Extracellular Trap gene expression signatures identify prognostic and targetable signaling axes for inhibiting metastasis of pancreatic tumours
Paul C. McDonaldiD, James Thomas TophamiD, Shannon J. AwreyiD, Hossein TavakoliiD, Rebekah Carroll, Wells S. BrowniD, Zachary J. GerbeciD, Steve E. KallogeriD, Joanna M. KarasinskaiD, Patricia A. TangiD, Rachel Anne GoodwiniD, Steven J.M. JonesiD, Janessa J. LaskiniD, Marco A. MarraiD, Gregg B. MoriniD, Daniel John RenoufiD, David F. SchaefferiD, Shoukat DedhariD
Abstract
Tumour associated neutrophils (TANs) can promote metastasis through the interaction of Neutrophil Extracellular Traps (NETs) with tumour cells. Here, we examined the contribution of NETs in the progression of Pancreatic Ductal Adenocarcinoma (PDAC), which is characterized by high metastatic propensity. We carried out consensus clustering and pathway enrichment analysis of NET-related genes in an integrated cohort of 369 resectable and metastatic PDAC patient tumour samples, and compiled two gene expression signatures comprising of either, integrin-actin cytoskeleton, and Epithelial to Mesenchymal Transition (EMT) signaling, or cell death signaling, which identified patients with very poor to better overall survival, respectively. Tumour Infiltrating neutrophils and NETs associate with ITGB1, CCDC25 and ILK, within clinical and experimental PDAC tumours. Functionally, exposure of PDAC cells to NETs identified a cytoskeletal dynamic-associated CCDC25/ITGB1/ILK signaling complex which stimulates EMT and migration/ invasion. Furthermore, NETosis-driven experimental metastasis of PDAC cells is significantly inhibited by ILK knock down. Our data identify novel NET-related gene expression signatures for PDAC patient stratification, and reveal targetable signaling axes to prevent and treat disease progression and metastasis.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 18
- FWCI
- 6.12
- Field percentile
- top 2%
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