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Gamallat Y, Felipe Lima J, Seyedi S, Li Q, Rokne JG, Alhajj R, Ghosh S, Bismar TA. Exploring The Prognostic Significance of SET-Domain Containing 2 (SETD2) Expression in Advanced and Castrate-Resistant Prostate Cancer. Cancers (Basel) 2024; 16:1436. [PMID: 38611113 PMCID: PMC11010867 DOI: 10.3390/cancers16071436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 04/02/2024] [Accepted: 04/04/2024] [Indexed: 04/14/2024] Open
Abstract
SET-domain containing 2 (SETD2) is a histone methyltransferase and an epigenetic modifier with oncogenic functionality. In the current study, we investigated the potential prognostic role of SETD2 in prostate cancer. A cohort of 202 patients' samples was assembled on tissue microarrays (TMAs) containing incidental, advanced, and castrate-resistant CRPCa cases. Our data showed significant elevated SETD2 expression in advanced and castrate-resistant disease (CRPCa) compared to incidental cases (2.53 ± 0.58 and 2.21 ± 0.63 vs. 1.9 ± 0.68; p < 0.001, respectively). Interestingly, the mean intensity of SETD2 expression in deceased vs. alive patients was also significantly different (2.31 ± 0.66 vs. 2 ± 0.68; p = 0.003, respectively). Overall, high SETD2 expression was found to be considered high risk and was significantly associated with poor prognosis and worse overall survival (OS) (HR 1.80; 95% CI: 1.28-2.53, p = 0.001) and lower cause specific survival (CSS) (HR 3.14; 95% CI: 1.94-5.08, p < 0.0001). Moreover, combining high-intensity SETD2 with PTEN loss resulted in lower OS (HR 2.12; 95% CI: 1.22-3.69, p = 0.008) and unfavorable CSS (HR 3.74; 95% CI: 1.67-8.34, p = 0.001). Additionally, high SETD2 intensity with ERG positive expression showed worse prognosis for both OS (HR 1.99, 95% CI 0.87-4.59; p = 0.015) and CSS (HR 2.14, 95% CI 0.98-4.68, p = 0.058). We also investigated the protein expression database TCPA, and our results showed that high SETD2 expression is associated with a poor prognosis. Finally, we performed TCGA PRAD gene set enrichment analysis (GSEA) data for SETD2 overexpression, and our data revealed a potential association with pathways involved in tumor progression such as the AMPK signaling pathway, the cAMP signaling pathway, and the PI3K-Akt signaling pathway, which are potentially associated with tumor progression, chemoresistance, and a poor prognosis.
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Affiliation(s)
- Yaser Gamallat
- Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; (Y.G.); (J.F.L.); (S.S.)
- Departments of Oncology, Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Joema Felipe Lima
- Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; (Y.G.); (J.F.L.); (S.S.)
- Departments of Oncology, Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Sima Seyedi
- Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; (Y.G.); (J.F.L.); (S.S.)
- Departments of Oncology, Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Qiaowang Li
- Department of Computer Science, University of Calgary, Calgary, AB T2N 1N4, Canada; (Q.L.)
| | - Jon George Rokne
- Department of Computer Science, University of Calgary, Calgary, AB T2N 1N4, Canada; (Q.L.)
| | - Reda Alhajj
- Department of Computer Science, University of Calgary, Calgary, AB T2N 1N4, Canada; (Q.L.)
- Department of Computer Engineering, Istanbul Medipol University, 34810 Istanbul, Turkey
- Department of Health Informatics, University of Southern Denmark, 5230 Odense, Denmark
| | - Sunita Ghosh
- Department of Medical Oncology, College of Health Sciences, University of Alberta, Edmonton, AB T6G 2R7, Canada
- Department of Public Health Sciences, Henry Ford Health, Detroit, MI 48202, USA
| | - Tarek A. Bismar
- Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; (Y.G.); (J.F.L.); (S.S.)
- Departments of Oncology, Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
- Tom Baker Cancer Center, Alberta Health Services, Calgary, AB T2N 4N1, Canada
- Prostate Cancer Centre, Alberta Health Services, Calgary, AB T2V 1P9, Canada
- Department of Pathology, Alberta Precision Labs, Calgary, AB T2V 1P9, Canada
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Li X, Zheng C, Xue X, Wu J, Li F, Song D, Li X. Integrated analysis of single-cell and bulk RNA sequencing identifies a signature based on macrophage marker genes involved in prostate cancer prognosis and treatment responsiveness. Funct Integr Genomics 2023; 23:115. [PMID: 37010617 DOI: 10.1007/s10142-023-01037-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/22/2023] [Accepted: 03/22/2023] [Indexed: 04/04/2023]
Abstract
In the tumor microenvironment, tumor-associated macrophages (TAMs) interact with cancer cells and contribute to the progression of solid tumors. Nonetheless, the clinical significance of TAM-related biomarkers in prostate cancer (PCa) is largely unexplored. The present study aimed to construct a macrophage-related signature (MRS) for predicting PCa patient prognosis based on macrophage marker genes. Six cohorts comprising 1056 PCa patients with RNA-Seq and follow-up data were enrolled. Based on macrophage marker genes identified by single-cell RNA-sequencing (scRNA-seq) analysis, univariate analysis, least absolute shrinkage and selection operator (Lasso)-Cox regression, and machine learning procedures were performed to derive a consensus MRS. Receiver operating characteristic curve (ROC), concordance index, and decision curve analyses were used to confirm the predictive capacity of the MRS. The predictive performance of the MRS for recurrence-free survival (RFS) was stable and robust, and the MRS outperformed traditional clinical variables. Furthermore, high-MRS-score patients presented abundant macrophage infiltration and high-expression levels of immune checkpoints (CTLA4, HAVCR2, and CD86). The frequency of mutations was relatively high in the high-MRS-score subgroup. However, the low-MRS-score patients had a better response to immune checkpoint blockade (ICB) and leuprolide-based adjuvant chemotherapy. Notably, abnormal ATF3 expression may be associated with docetaxel and cabazitaxel resistance in PCa cells, T stage, and the Gleason score. In this study, a novel MRS was first developed and validated to accurately predict patient survival outcomes, evaluate immune characteristics, infer therapeutic benefits, and provide an auxiliary tool for personalized therapy.
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Affiliation(s)
- Xiugai Li
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Chang Zheng
- Department of Clinical Epidemiology, First Affiliated Hospital of China Medical University, Shenyang, 110001, China
| | - Xiaoxia Xue
- Science Experiment Center, China Medical University, Shenyang, 110122, China
| | - Junying Wu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Fei Li
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Dan Song
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Xuelian Li
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China.
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