ArticleFrontiers in endocrinology2022
Novel biomarkers predict prognosis and drug-induced neuroendocrine differentiation in patients with prostate cancer.
Article in Frontiers in endocrinology, 2022. 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, 10 citations in OpenAlex.
- Integrative analysis of urinary microRNAs for prostate cancer detection: A proof-of-concept study.Translational oncology · 2026Article
- HMGN2 induces pyroptosis in tumour cells by modulating the STT3B/PD‑L1/caspase‑1/GSDMD axis.Molecular medicine reports · 2026Article
- A Neuroendocrine Differentiation-related Molecular Model for Prognosis Prediction in Prostate Cancer Patients.Current medicinal chemistry · 2026Article
- The Risk Genes S1PR5, CMC1, and ASAH1 as Potential Targets for the Diagnosis, Immunotherapy, and Treatment of Colon Adenocarcinoma by Single-Cell and Bulk RNA Sequencing Analysis.Current medicinal chemistry · 2026Article
- Neoadjuvant PD-1 blockade induces the autophagy of immune cells: a new target for synergistic therapy of recurrent glioblastoma.Biochemistry and biophysics reports · 2025Article
- Identifying MSMO1, ELOVL6, AACS, and CERS2 related to lipid metabolism as biomarkers of Parkinson's disease.Scientific reports · 2024Article
- [Dynamic trajectory and cell communication of different cell clusters in malignant progression of glioblastoma].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2024Article
- Article
- Aggrephagy-related patterns in tumor microenvironment, prognosis, and immunotherapy for acute myeloid leukemia: a comprehensive single-cell RNA sequencing analysis.Frontiers in oncology · 2023Article
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7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: A huge focus is being placed on the development of novel signatures in the form of new combinatorial regimens to distinguish the neuroendocrine (NE) characteristics from castration resistant prostate cancer (CRPC) timely and accurately, as well as predict the disease-free survival (DFS) and progression-free survival (PFS) of prostate cancer (PCa) patients. Methods: Single cell data of 4 normal samples, 3 CRPC samples and 3 CRPC-NE samples were obtained from GEO database, and CellChatDB was used for potential intercellular communication, Secondly, using the "limma" package (v3.52.0), we obtained the differential expressed genes between CRPC and CRPC-NE both in single-cell RNA seq and bulk RNA seq samples, and discovered 12 differential genes characterized by CRPC-NE. Then, on the one hand, the diagnosis model of CRPC-NE is developed by random forest algorithm and artificial neural network (ANN) through Cbioportal database; On the other hand, using the data in Cbioportal and GEO database, the DFS and PFS prognostic model of PCa was established and verified through univariate Cox analysis, least absolute shrinkage and selection operator (Lasso) regression and multivariate Cox regression in R software. Finally, somatic mutation and immune infiltration were also discussed. Results: Our research shows that there exists specific intercellular communication in classified clusters. Secondly, a CRPC-NE diagnostic model of six genes ( Conclusions: This study revealed the heterogeneity between CRPC and CRPC-NE from different perspectives, and developed a reliable diagnostic model of CRPC-NE and robust prognostic models for PCa.
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