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Updated: Aug 5, 2025

Isolation of Proximal Fluids to Investigate the Tumor Microenvironment of Pancreatic Adenocarcinoma
Published on: November 5, 2020
A Liquid-Liquid Phase Separation-Related Index Associate with Biochemical Recurrence and Tumor Immune Environment of
Qi You1,2, Jia-Yin Chen1,2, Xiao-Hui Wu1,2
1Department of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China.
Abstract:
To identify liquid-liquid phase separation (LLPS)-related molecular clusters, and to develop and validate a novel index based on LLPS for predicting the prognosis of prostate cancer (PCa) patients. We download the clinical and transcriptome data of PCa from TCGA and GEO database. The LLPS-related genes (LRGs) were extracted from PhaSepDB. Consensus clustering analysis was used to develop LLPS-related molecular subtypes for PCa. The LASSO cox regression analysis was performed to establish a novel LLPS-related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Preliminary experimental verification was performed. We initially identified a total of 102 differentially expressed LRGs for PCa. Three LLPS related molecular subtypes were identified. Moreover, we established a novel LLPS related signature for predicting BCRFS of PCa patients. Compared to low-risk patients in the training cohort, testing cohort and validating cohort, high-risk populations meant a higher risk of BCR and significantly poorer BCRFS. The area under receiver operating characteristic curve were 0.728, 0.762, and 0.741 at 1 year in the training cohort, testing cohort and validating cohort. Additionally, the subgroup analysis indicated that this index was especially suitable for PCa patients with age ≤ 65, T stage III-IV, N0 stage or in cluster 1. The FUS, which was the potential biomarker related to PCa liquid-liquid phase separation, was preliminarily identified and verified. This study successfully developed three LLPS-related molecular subtypes and identified a novel LLPS related molecular signature, which performed well in predicting BCRFS of PCa.
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