Purpose: Pancreatic cancer (PC) remains a lethal disease, and gemcitabine resistance is prevalent. However, the biomarkers suggestive of gemcitabine resistance remain unclear.
Methods: Bioinformatic tools identified ribonucleotide reductase catalytic subunit M1 (RRM1) in gemcitabine-related datasets. A cox regression model revealed the predictive value of RRM1 with clinical features. An external clinical cohort confirmed the prognostic value of RRM1. RRM1 expression was validated in gemcitabine-resistant cells in vitro and in orthotopic PC model. CCK8, flow cytometry, transwell migration, and invasion assays were used to explore the effect of RRM1 on gemcitabine-resistant cells. The CIBERSORT algorithm investigated the impact of RRM1 on immune infiltration.
Results: The constructed nomogram based on RRM1 effectively predicted prognosis and was further validated. Moreover, patients with higher RRM1 had shorter overall survival. RRM1 expression was significantly higher in PC tissue and gemcitabine-resistant cells in vitro and in vivo. RRM1 knockdown reversed gemcitabine resistance, inhibited migration and invasion. The infiltration levels of CD4 + T cells, CD8 + T cells, neutrophils, and plasma cells correlated markedly with RRM1 expression, and communication between tumor and immune cells probably depends on NF-κB/mTOR signaling.
Conclusion: RRM1 may be a potential marker for prognosis and a target marker for gemcitabine resistance in PC.
Keywords: Bioinformatics; Gemcitabine resistance; Immune infiltration; Nomogram; Pancreatic cancer; RRM1.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.