Abstract
Background: The growth and metastasis of pancreatic cancer (PC) has been found to be closely associated with liquid-liquid phase separation (LLPS). This study sought to identify LLPS-related biomarkers in PC to construct a robust prognostic model. Methods: Transcriptomic data and clinical information related to PC were retrieved from publicly accessible databases. The PC-related data set was subjected to differential expression, Mendelian randomization (MR), univariate Cox, and least absolute selection and shrinkage operator analyses to identify biomarkers. Using the biomarkers, we subsequently constructed a risk model, identified the independent prognostic factors of PC, established a nomogram, and conducted an immune analysis. Results: The study identified four genes linked with an increased risk of PC; that is, PYGB, ACTR3, CCNA2, and ITGB1. Conversely, ATP8A1, and RAP1GAP2 were found to provide protection against PC. These findings contributed significantly to the development of a highly precise risk model in which risk, age, and pathology N stage were categorized as independent factors in predicting the prognosis of PC patients. Using these factors, a nomogram was established to predict survival outcomes accurately. An immune analysis revealed varying levels of eosinophils, gamma delta T cells, and other immune cells between the distinct risk groups. The high-risk patients exhibited increased potential for immune escape, while the low-risk patients showed a higher response to immunotherapy. Conclusions: Six genes were identified as having potential causal relationships with PC. These genes were integrated into a prognostic risk model, thereby serving as unique prognostic signatures. Our findings provide novel insights into predicting the prognosis of PC patients.
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Li, X., Yu, R., Shi, B., Chawla, A., Feng, X., Zhang, K., & Liang, L. (2024). Liquid-liquid phase separation-related features of PYGB/ACTR3/ CCNA2/ITGB1/ATP8A1/RAP1GAP2 predict the prognosis of pancreatic cancer. Journal of Gastrointestinal Oncology, 15(4), 1723–1745. https://doi.org/10.21037/jgo-24-426
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