The prognostic potential of human prostate cancer-associated macrophage subtypes as revealed by single-cell transcriptomics
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Publication date
2021-10
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Abstract
Macrophages in the tumor microenvironment are causally linked with prostate cancer development and progression, yet little is known about their composition in neoplastic human tissue. By performing single cell transcriptomic analysis of human prostate cancer resident macrophages, three distinct populations were identified in the diseased prostate. Unexpectedly, no differences were observed between macrophages isolated from the tumorous and nontumorous portions of the prostatectomy specimens. Markers associated with canonical M1 and M2 macrophage phenotypes were identifiable, however these were not the main factors defining unique subtypes. The genes selectively associated with each macrophage cluster were used to develop a gene signature which was highly associated with both recurrence-free and metastasis-free survival. These results highlight the relevance of tissue-specific macrophage subtypes in the tumor microenvironment for prostate cancer progression and demonstrates the utility of profiling single-cell transcriptomics in human tumor samples as a strategy to design gene classifiers for patient prognostication. Implications: The specific macrophage subtypes present in a diseased human prostate have prognostic value, suggesting that the relative proportions of these populations are related to patient outcome. Understanding the relative contributions of these subtypes will not only inform patient prognostication, but will enable personalized immunotherapeutic strategies to increase beneficial populations or reduce detrimental populations.
Keywords
Molecular Biology, Oncology, Cancer Research
Citation
Siefert, J C, Cioni, B, Muraro, M J, Alshalalfa, M, Vivie, J, van der Poel, H G, Schoots, I G, Bekers, E, Feng, F Y, Wessels, L F A, Zwart, W & Bergman, A M 2021, 'The prognostic potential of human prostate cancer-associated macrophage subtypes as revealed by single-cell transcriptomics', Molecular Cancer Research, vol. 19, no. 10, pp. 1778-1791. https://doi.org/10.1158/1541-7786.MCR-20-0740