Human tissue samples represent an invaluable source of information for the analysis of disease-specific cellular alterations and their variation between different pathologies. In cancer research, advancing a comprehensive understanding of the unique characteristics of individual tumor types and their microenvironment is of considerable importance for clinical translation. However, investigating human brain tumor tissue is challenging due to the often-limited availability of surgical specimens. Here we describe a multimodule integrated pipeline for the processing of freshly resected human brain tumor tissue and matched blood that enables analysis of the tumor microenvironment, with a particular focus on the tumor immune microenvironment (TIME). The protocol maximizes the information yield from limited tissue and includes both the preservation of bulk tissue, which can be performed within 1 h following surgical resection, as well as tissue dissociation for an in-depth characterization of individual TIME cell populations, which typically takes several hours depending on tissue quantity and further downstream processing. We also describe integrated modules for immunofluorescent staining of sectioned tissue, bulk tissue genomic analysis and fluorescence- or magnetic-activated cell sorting of digested tissue for subsequent culture or transcriptomic analysis by RNA sequencing. Applying this pipeline, we have previously described the overall TIME landscape across different human brain malignancies, and were able to delineate disease-specific alterations of tissue-resident versus recruited macrophage populations. This protocol will enable researchers to use this pipeline to address further research questions regarding the tumor microenvironment.
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All data generated or analyzed during this study are included in either this paper or our original research study5. Transcriptomic data generated using this pipeline are available at https://joycelab.shinyapps.io/braintime/. FCM data of the comparison of various brain tumor dissociation methods (included in Fig. 5a,b) have been deposited at the flow cytometry repository (http://flowrepository.org/): FR-FCM-Z3MF. Data not included in the aforementioned sources can be obtained from the corresponding author upon request due to patient privacy protection.
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We express our gratitude to all patients who kindly agreed to donate tissue under protocol PB 2017-00240, F25/99. We thank the neurosurgery operating room staff and the technicians at the Pathology department of the Centre Hospitalier Universitaire Vaudois (CHUV) for their support in providing human patient samples; L. Bejarano Bosque, V. Wischnewski, A. Zomer and S. Watson in the Joyce lab for their technical assistance during sample processing; N. Piazzon for coordinating ATRX staining and IDH pyrosequencing performed at the Pathology department; the team of the UNIL Mouse Pathology Facility for cryosectioning of patient tissues; and K. Blackney and F. Sala de Oyanguren of the UNIL Flow Cytometry Facility for assistance with FAC sorting. Research in the Joyce lab is funded by the Carigest Foundation, ISREC Foundation, the Swiss Bridge Award, Breast Cancer Research Foundation, Cancer Research UK, Ludwig Institute for Cancer Research and the University of Lausanne. K.S. is supported in part by an Erwin-Schrödinger Fellowship from the Austrian Science Fund (FWF, J4343-B28). F.K. was supported in part by the German Research Foundation (DFG, KL2491/1-1) and Fondation Medic. A.A-P. is supported by an EMBO Long-term Postdoctoral Fellowship (EMBO ALTF 654-2019).
The authors declare no competing interests.
Peer review information Nature Protocols thanks Burkhard Becher and the other, anonymous reviewer(s) for their contribution to the peer review of this work.
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Key reference using this protocol
Klemm, F. et al. Cell 181, 1643–1660.e17 (2020): https://doi.org/10.1016/j.cell.2020.05.007
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Maas, R.R., Soukup, K., Klemm, F. et al. An integrated pipeline for comprehensive analysis of immune cells in human brain tumor clinical samples. Nat Protoc 16, 4692–4721 (2021). https://doi.org/10.1038/s41596-021-00594-2
Nature Reviews Clinical Oncology (2022)