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Review
. 2024 Sep 26;16(19):3283.
doi: 10.3390/cancers16193283.

Unveiling the Inflammatory Landscape of Recurrent Glioblastoma through Histological-Based Assessments

Affiliations
Review

Unveiling the Inflammatory Landscape of Recurrent Glioblastoma through Histological-Based Assessments

Nicholas B Dadario et al. Cancers (Basel). .

Abstract

The glioblastoma (GBM) tumor microenvironment consists of a heterogeneous mixture of neoplastic and non-neoplastic cells, including immune cells. Tumor recurrence following standard-of-care therapy results in a rich landscape of inflammatory cells throughout the glioma-infiltrated cortex. Immune cells consisting of glioma-associated macrophages and microglia (GAMMs) overwhelmingly constitute the bulk of the recurrent glioblastoma (rGBM) microenvironment, in comparison to the highly cellular and proliferative tumor microenvironment characteristic of primary GBM. These immune cells dynamically interact within the tumor microenvironment and can contribute to disease progression and therapy resistance while also providing novel targets for emerging immunotherapies. Within these varying contexts, histological-based assessments of immune cells in rGBM, including immunohistochemistry (IHC) and immunofluorescence (IF), offer a critical way to visualize and examine the inflammatory landscape. Here, we exhaustively review the available body of literature on the inflammatory landscape in rGBM as identified through histological-based assessments. We highlight the heterogeneity of immune cells throughout the glioma-infiltrated cortex with a focus on microglia and macrophages, drawing insights from canonical and novel immune-cell histological markers to estimate cell phenotypes and function. Lastly, we discuss opportunities for immunomodulatory treatments aiming to harness the inflammatory landscape in rGBM.

Keywords: histology; immune cells; macrophages; microglia; recurrent glioblastoma; tumor microenvironment.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The recurrent glioma immune microenvironment. Immune cells influence the glioma microenvironment and dynamically interact and evolve. Changes in environmental signals, cell–cell communication, and spatial influences in reference to the tumor can all alter the inflammatory landscape in glioma patients. This figure was created through BioRender.com. Abbreviations: GAMMs = glioma-associated microglia and macrophages; MDSC = myeloid-derived suppressor cells.
Figure 2
Figure 2
Common histological markers of GAMMs in rGBM samples according to immunofluorescence markers. In the top row, two examples are shown to label microglia-like cells (left) and macrophage-like cells (right). Iba1 is used in both examples as a pan myeloid marker, and then double-positive cells with Iba1+ and Tmem119+ or P2ry12+ are considered (resting) microglia compared to double positive Iba1+ with Msr1+ or MARCO+, which represent more macrophage-like cells. Note in the top right image, MARCO only labels a portion of Msr1+ cells, demonstrating a potential MARCO+ subpopulation of macrophages. The bottom row of the figures highlights the selectivity of these markers for different GAMMS, such that Iba1+/Tmem119+ cells do not overlap with Iba1+/Msr1+ cells. DAPI is used in all images in blue, while other markers are highlighted in the colors demonstrated on each figure panel. Markers used include P2ry12 (1:1000 anti-P2Y12 antibody, rabbit, Sigma-Aldrich, HPA014518, St. Louis, MO, USA), Tmem119 (1:500 anti-TMEM119 antibody, rabbit, Abcam, abcamab185333, Cambridge, UK), Iba1 (1:1000 anti-Iba1 antibody, chicken IgY, Aves Labs, 1BA1-0200, Davis, CA, USA), Msr1 (1:1000 anti-MSR1 antibody, mouse, Thermo Fisher J5HTR3, Waltham, MA, USA), and MARCO (1:1000 anti-MARCO antibody, rabbit, Invitrogen, PA5-64134, Waltham, MA, USA).
Figure 3
Figure 3
Standard-of-care therapies exert profound immunomodulatory effects on the TME. These treatments disrupt cellular components both directly and indirectly, creating a self-sustaining inflammatory milieu driven by complex signaling pathways, intercellular cross-talk, and cellular stress responses. This not only alters the peritumoral landscape but also drives intrinsic cellular changes by modulating transcriptional activity and gene expression. The effects of these changes can be effectively visualized and quantified through downstream immunohistochemical staining. This figure was created through BioRender.com.

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References

    1. Stupp R., Mason W.P., van den Bent M.J., Weller M., Fisher B., Taphoorn M.J., Belanger K., Brandes A.A., Marosi C., Bogdahn U., et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 2005;352:987–996. doi: 10.1056/NEJMoa043330. - DOI - PubMed
    1. Gill B.J., Pisapia D.J., Malone H.R., Goldstein H., Lei L., Sonabend A., Yun J., Samanamud J., Sims J.S., Banu M., et al. MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma. Proc. Natl. Acad. Sci. USA. 2014;111:12550–12555. doi: 10.1073/pnas.1405839111. - DOI - PMC - PubMed
    1. Al-Dalahmah O., Argenziano M.G., Kannan A., Mahajan A., Furnari J., Paryani F., Boyett D., Save A., Humala N., Khan F., et al. Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic and targetable tissue states. Nat. Commun. 2023;14:2586. doi: 10.1038/s41467-023-38186-1. - DOI - PMC - PubMed
    1. Campos B., Olsen L.R., Urup T., Poulsen H.S. A comprehensive profile of recurrent glioblastoma. Oncogene. 2016;35:5819–5825. doi: 10.1038/onc.2016.85. - DOI - PubMed
    1. Hoogstrate Y., Draaisma K., Ghisai S.A., van Hijfte L., Barin N., de Heer I., Coppieters W., van den Bosch T.P.P., Bolleboom A., Gao Z., et al. Transcriptome analysis reveals tumor microenvironment changes in glioblastoma. Cancer Cell. 2023;41:678–692.e677. doi: 10.1016/j.ccell.2023.02.019. - DOI - PubMed

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