Effect of clonal competition model of PDAC liver metastasis on a pan-carcinoma gene signature of metastatic potential.

Abstract

e16452 Background: Liver metastasis is a leading cause of death amongst localized pancreatic ductal adenocarcinoma (PDAC) patients following surgical resection. Yet, there are no adjuvant therapies currently available targeting liver colonization in PDAC. We are hindered in our ability to develop such therapies by an incomplete understanding of PDAC liver metastasis' molecular mechanisms. Methods: To address this challenge, we labeled primary mouse PDAC subclones with DNA barcodes to characterize their pre-metastatic state using ATAC-seq and RNA-seq and determine their relative in vivo liver metastasis potential in competition assays in immunocompetent hosts. Results: We identified a gene signature separating metastasis-high and metastasis-low subclones orthogonal to the normal-to-PDAC and classical-to-basal axes. The metastasis-high subclones feature activation of inflammation-related genes and high NF-κB and Zeb/Snail family activity and the metastasis-low subclones feature activation of neuroendocrine, motility, and Wnt pathway genes and high CDX2 and HOXA13 activity. In a functional screen, we validated novel mediators of PDAC liver metastasis related to inflammation, including the NF-κB targets Fos and Il23a , and beyond inflammation including Myo1b and Tmem40 . We scored human PDAC tumors for our signature of metastatic potential from mouse and found that metastases have higher scores than primary tumors. Moreover, primary tumors with higher scores are associated with worse prognosis. We also found that our metastatic potential signature is enriched in other human carcinomas, suggesting that it is conserved across epithelial malignancies. Conclusions: This study establishes a model of clonal evolution during PDAC liver metastasis under immune selective pressure, revealing novel functional regulators amenable to therapeutic intervention in the adjuvant setting. Furthermore, it provides a method for scoring human carcinomas based on metastatic potential that may have prognostic and predictive value across multiple cancer subtypes.