The study aimed to investigate the mechanism by which cancer-associated fibroblasts (CAFs) are activated by cancer cells and construct a risk model to predict the prognosis of patients with pancreatic cancer (PC) after surgery. Pancreatic stellate cells were isolated from human pancreatic tissue and co-cultured with cancer cells to verify their crosstalk. Liquid chromatography-tandem mass spectrometry was used to detect proteins secreted by cancer cells. The online tools Gene Expression Profiling Interactive Analysis, UALCAN, and the Human Protein Atlas were used to analyse gene expression in PC. Expression data from the cancer genome atlas and the clinical samples were used to develop a training receiver operating characteristic (ROC) model and an external validation ROC model, respectively. We identified that cancer cells promote the activation of inflammatory CAFs (iCAF) through secretory proteins, which promote PC metastasis. Six candidate proteins secreted by cancer cells were identified which promote iCAF formation. These proteins were highly expressed in tumours and were associated with a poor prognosis in patients with PC. Moreover, a 6-gene model was constructed to predict death risk in patients at 1, 2 and 3 years after surgery. The training areas under the ROC curves (AUC) of 1-, 2- and 3-year death risks were 0.780, 0.792 and 0. 825, respectively. The externally validated AUC of death at 3 years post-surgery was 0.728. In conclusion, cancer cell-secreted proteins play a vital role in iCAF formation, and the 6-gene model may be a potential marker for predicting whether PC patients will benefit from surgery.
Keywords: cancer-associated fibroblast; pancreatic cancer; pancreatic stellate cells; prognosis; proteins.
© 2022 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.