ArticleInternational journal of molecular sciences2023
A Liquid-Liquid Phase Separation-Related Index Associate with Biochemical Recurrence and Tumor Immune Environment of Prostate Cancer Patients.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 14 citations in OpenAlex.
- A phase separation-related gene signature for prognosis prediction and immunotherapy response evaluation in gastric cancer with targeted natural compound discovery.Discover oncology · 2025Article
- Liquid-liquid phase separation-related genes associated with prognosis, tumor microenvironment characteristics, and tumor cell features in bladder cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- A novel liquid-liquid phase separation related gene signature including ARL6IP4 predicts prognosis and immune landscape in colorectal cancer.Frontiers in immunology · 2025Article
- Liquid-liquid phase separation: an emerging perspective on the tumorigenesis, progression, and treatment of tumors.Frontiers in immunology · 2025Review
- CD79B in myelodysplastic syndromes and acute myeloid leukemia: an integrative computational andFrontiers in medicine · 2025Article
- Membraneless organelles in health and disease: exploring the molecular basis, physiological roles and pathological implications.Signal transduction and targeted therapy · 2024Review
- Integrated machine learning algorithms reveal a bone metastasis-related signature of circulating tumor cells in prostate cancer.Scientific data · 2024Article
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10 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
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
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