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Docetaxel is the preferred chemotherapeutic agent in patients with castrate‐resistant prostate cancer (CRPC). However, patients eventually develop docetaxel resistance and in the absence of effective treatment options. Consequently, it is essential to investigate the mechanisms generating docetaxel resistance and develop novel alternative therapeutic targets. RNA sequencing was undertaken on docetaxel‐sensitive and docetaxel‐resistant prostate cancer (PCa) cells. Subsequently, chemoresistance, cancer stemness, and lipid metabolism were investigated. To obtain insight into the precise activities and action mechanisms of NOTCH3 in docetaxel‐resistant PCa, immunoprecipitation, mass spectrometry, ChIP, luciferase reporter assay, cell metabolism, and animal experiments were performed. Through RNA sequencing analysis, we found that NOTCH3 expression was markedly higher in docetaxel‐resistant cells relative to parental cells, and that this trend was continued in docetaxel‐resistant PCa tissues. Experiments in vitro and in vivo revealed that NOTCH3 enhanced stemness, lipid metabolism, and docetaxel resistance in PCa. Mechanistically, NOTCH3 is bound to TUBB3 and activates the MAPK signaling pathway. Moreover, NOTCH3 was directly regulated by MEF2A in docetaxel‐resistant cells. Notably, targeting NOTCH3 and the MEF2A/TUBB3 signaling axis was related to docetaxel chemoresistance in PCa. Overall, these results demonstrated that NOTCH3 fostered stemness, lipid metabolism, and docetaxel resistance in PCa via the TUBB3 and MAPK signaling pathways. Therefore, NOTCH3 may be employed as a prognostic biomarker in PCa patients. NOTCH3 could be a therapeutic target for PCa patients, particularly those who have developed docetaxel resistance. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "ScRNA-seq revealed an immunosuppression state and tumor microenvironment heterogeneity related to lymph node metastasis in prostate cancer" published in Experimental Hematology & Oncology. The correction addresses an error in Fig. 3E, F of the article, where the authors mistakenly used the wrong picture. The correct figure is provided in the correction notice. The original article has been corrected. The publisher, Springer Nature, remains neutral regarding jurisdictional claims and institutional affiliations. [Extracted from the article]

Background. Reprogramming of lipid metabolism is closely associated with tumor development, serving as a common and critical metabolic feature that emerges during tumor evolution. Meanwhile, immune cells in the tumor microenvironment also undergo aberrant lipid metabolism, and altered lipid metabolism also has an impact on the function and status of immune cells, further promoting malignant biological behavior. Consequently, we focused on lipid metabolism-related genes for constructing a novel prognostic marker and evaluating immune status in prostate cancer. Methods. Information about prostate cancer patients was obtained from TCGA and GEO databases. The NMF algorithm was conducted to identify the molecular subtypes. The least absolute shrinkage and selection operator (Lasso) regression analysis was applied to establish a prognostic risk signature. CIBERSORT algorithm was used to calculate immune cell infiltration levels in prostate cancer. External clinical validation data were used to validate the results. Results. Prostate cancer samples were divided into two subtypes according to the NMF algorithm. A six-gene risk signature (PTGS2, SGPP2, ALB, PLA2G2A, SRD5A2, and SLC2A4) was independent of prognosis and showed good stability. There were significant differences between risk groups of patients with respect to the infiltration of immune cells and clinical variables. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR. Conclusion. We constructed a six-gene signature with lipid metabolism in prostate cancer to effectively predict prognosis and reflect immune microenvironment status. [ABSTRACT FROM AUTHOR]

There is growing evidence that phagocytosis regulatory factors (PRFs) play important roles in tumor progression, and therefore, identifying and characterizing these factors is crucial for understanding the mechanisms of cellular phagocytosis in tumorigenesis. Our research aimed to comprehensively characterize PRFs in prostate adenocarcinoma (PRAD) and to screen and determine important PRFs in PRAD which may help to inform tumor prognostic and therapeutic signatures based on these key PRFs. Here, we first systematically described the expression of PRFs in PRAD and evaluated their expression patterns and their prognostic value. We then analyzed prognostic phagocytic factors by Cox and Lasso analysis and constructed a phagocytic factor-mediated risk score. We then divided the samples into two groups with significant differences in overall survival (OS) based on the risk score. Then, we performed correlation analysis between the risk score and clinical features, immune infiltration levels, immune characteristics, immune checkpoint expression, IC50 of several classical sensitive drugs, and immunotherapy efficacy. Finally, the Human Protein Atlas (HPA) database was used to determine the protein expression of 18 PRF characteristic genes. The aforementioned results confirmed that multilayer alterations of PRFs were associated with the prognosis of patients with PRAD and the degree of macrophage infiltration. These findings may provide us with potential new therapies for PRAD. [ABSTRACT FROM AUTHOR]

Background. Despite the constant iteration of small-molecule inhibitors and immune checkpoint inhibitors, PRAD (prostate adenocarcinoma) patients with distant metastases and biochemical recurrence maintain a poor survival outcome along with an increasing morbidity in recent years. N7-Methylguanine, a new-found type of RNA modification, has demonstrated an essential role in tumor progression but has hardly been studied for its effect on prostate carcinoma. The current study aimed to seek m7G (N7-methylguanosine) related prognostic biomarkers and potential targets for PRAD treatment. Methods. 42 genes related to m7G were collected from former literatures and GSEA (Gene Set Enrichment Analysis) website. Then, RNA-seq (RNA sequencing) and clinical data from TCGA-PRAD (The Cancer Genome Atlas-Prostate) cohort were retrieved to screen the differentially expressed m7G genes to further construct a multivariate Cox prognostic model for PRAD. Next, GSE116918, a prostate cancer cohort acquired from GEO (Gene Expression Omnibus) database, was analyzed for the external validation group to assess the ability to predict BFFS (biochemical failure-free survival) of our m7G prognostic signature. Kaplan-Meier, ROC (receiver operator characteristic), AUC (areas under ROC curve), and calibration curves were adopted to display the performance of this prognostic signature. In addition, immune infiltration analysis was implemented to evaluate the effect of these m7G genes on immunoinfiltrating cells. Correlation with drug susceptibility of the m7G signature was also analyzed by matching drug information in CellMiner database. Results. The m7G-related prognostic signature, including three genes (EIF3D, EIF4A1, LARP1) illustrated superior prognostic ability for PRAD in both training and validation cohorts. The 5-year AUC were 0.768 for TCGA-PRAD and 0.608 for GSE116918. It can well distinguish patients into different risk groups of biochemical recurrence (p =1e-04 for TCGA-PRAD and p =0.0186 for GSE116918). Immune infiltration analysis suggested potential regulation of m7G genes on neutrophils and dendritic cells in PRAD. Conclusions. A m7G-related prognostic signature was constructed and validated in the current study, giving new sights of m7G methylation in predicting the prognostic and improving the treatment of PRAD. [ABSTRACT FROM AUTHOR]