Gene Expression-Based Immune Cell Infiltration Analyses of Prostate Cancer and Their Associations with Survival Outcome
Prostate cancer is the second most common cancer and the fifth cause of cancer death in males. Currently, there are no effective therapies for prostate cancer yet, and the status of treatment remains severe. In this study, we analyzed the composition of tumor-infiltrating immune cells (TIICs) in prostate cancer and paracancerous samples based on the gene expression profiles using CIBERSORT. Calculation of the TIIC subset proportions in 52 paired prostate cancer and paracancerous samples showed that their proportions were similar in intergroup and varied in intragroup. Compared with the paracancerous samples, the proportion of M0 macrophages was significantly increased in prostate cancer samples. Cox regression analysis using the TIIC subpopulations as continuous variables revealed that high plasma cell proportion was associated with poor 3-year Disease-Free Survival (DFS) in prostate cancer (hazard ratios = 1.8e-76, p = 0.001). Moreover, three immune clusters, which presented distinct prognosis, were identified using hierarchical clustering analysis based on the proportions of TIIC subpopulations. Among them, cluster 1 had superior 3-year DFS, while cluster 3 showed inferior 3-year DFS (p = 0.025). In summary, our research provided a comprehensive analysis on the TIIC composition in prostate cancer and suggested that both plasma cells and different cluster patterns were associated with the prostate cancer prognosis, which should be helpful for the clinical surveillance and treatment of prostate cancer.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:39 |
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| Enthalten in: |
DNA and cell biology - 39(2020), 7 vom: 20. Juli, Seite 1194-1204 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hu, Ping [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 20.07.2020 Date Revised 20.07.2020 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1089/dna.2020.5371 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM310424682 |
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| 520 | |a Prostate cancer is the second most common cancer and the fifth cause of cancer death in males. Currently, there are no effective therapies for prostate cancer yet, and the status of treatment remains severe. In this study, we analyzed the composition of tumor-infiltrating immune cells (TIICs) in prostate cancer and paracancerous samples based on the gene expression profiles using CIBERSORT. Calculation of the TIIC subset proportions in 52 paired prostate cancer and paracancerous samples showed that their proportions were similar in intergroup and varied in intragroup. Compared with the paracancerous samples, the proportion of M0 macrophages was significantly increased in prostate cancer samples. Cox regression analysis using the TIIC subpopulations as continuous variables revealed that high plasma cell proportion was associated with poor 3-year Disease-Free Survival (DFS) in prostate cancer (hazard ratios = 1.8e-76, p = 0.001). Moreover, three immune clusters, which presented distinct prognosis, were identified using hierarchical clustering analysis based on the proportions of TIIC subpopulations. Among them, cluster 1 had superior 3-year DFS, while cluster 3 showed inferior 3-year DFS (p = 0.025). In summary, our research provided a comprehensive analysis on the TIIC composition in prostate cancer and suggested that both plasma cells and different cluster patterns were associated with the prostate cancer prognosis, which should be helpful for the clinical surveillance and treatment of prostate cancer | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Gao, Yuanyuan |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Yanjiao |e verfasserin |4 aut | |
| 700 | 1 | |a Yan, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Jiao |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Lujun |e verfasserin |4 aut | |
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