Method Article

Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

DOI:

10.3791/56025

July 31st, 2017

In This Article

Summary

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This protocol was developed to quantitatively identify tumor microenvironment components in glioblastoma patient resections using chromogenic immunohistochemistry and ImageJ.

Abstract

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With the growing interest in the tumor microenvironment, we set out to develop a method to specifically determine the microenvironment components within patient samples of glioblastoma, the deadliest and most invasive brain cancer. Not only are quantitative methods beneficial for accurately describing diseased tissues, they can also potentially contribute to more accurate prognosis, diagnosis, and the development of tissue-engineered systems and replacements. In glioblastoma, glial cells, such as microglia and astrocytes, have been independently correlated with poor prognosis based on pathologist grading. However, the state of these cells and other glial cell components has not been well-described quantitatively. This can be difficult due to the large processes that mark these glial cells. Furthermore, most histological analyses focus on the overall tissue sample or only within the bulk of the tumor, as opposed to delineating quantifications based on regions within the highly heterogeneous tissue. Here, we describe a method for identifying and quantitatively analyzing the populations of glial cells within the tumor bulk and adjacent regions of tumor resections from glioblastoma patients. We used chromogenic immunohistochemistry to identify the glial cell populations in patient tumor resections and ImageJ to analyze percent coverage of staining for each glial population. With these techniques we are able to better describe the glial cells throughout regions of the glioma tumor microenvironment.

Introduction

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Glioblastoma (GBM), the most common and malignant brain cancer, is characterized by highly diffuse invasion from the primary tumor bulk into the surrounding healthy brain parenchyma1,2. This diffuse invasion makes the tumor particularly difficult to resect fully, and the invading cancer cells that remain post-therapy is the most common reason for inevitable recurrence2,3,4. Previously, we found inhibiting the diffuse glioma cell invasion to be therapeutically beneficial5, however little is know....

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Protocol

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This protocol identifies cellular components in formalin-fixed paraffin embedded (FFPE) samples, as is typical for banked clinical patient samples. Paraffin embedding allows for the best maintenance of cellular and tissue morphology as well as has better longevity of sections. The samples used for this analysis were accessed through the University of Virginia Biorepository and Tissue Research Facility. Patient samples were selected by a neuropathologist based on a definitive diagnosis of glioblastoma (astrocytoma, WHO grade IV) who had completed tumor resections at the University of Virginia between 2010 and 2013, and were de-identified prior to this analysis

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Results

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For this analysis, two regions of interests within our tumor resections - the primary tumor bulk and the adjacent regions, primarily composed of healthy tissue with diffuse invading cancer cells (Figure 1A, 1B) - were identified by collaborating neuropathologists on hematoxylin and eosin stained patient samples. Within each patient sample, positive staining for astrocytes (Figure 1C), microglia (

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Discussion

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Our method proposed here is a quantitative approach to analyzing histological samples stained using traditional chromogenic immunohistochemistry. Current methodology for this type of analysis includes similar staining protocols followed by grading by independent pathologists. This method has been reliable, yet for a number of applications, a more precise understanding of the cellular make-up is required, such as better understanding of the heterogeneity associated with tumors and accurate recapitulation of tumors for in .......

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Acknowledgements

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The authors thank Drs. Fahad Bafakih and Jim Mandell for acquisition and identification of patient samples, Garrett F. Beeghly for assistance with immunohistochemistry, and the Biorepository and Tissue Research Facility, the Cardiovascular Research Center Histology Core, and the Biomolecular Analysis Facility at the University of Virginia for assistance with sample acquisition, immunohistochemistry, and imaging.

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
XyleneFisher ChemicalX3P
Ethanol
High pH antigen unmasking solutionVector LabsH-3301
TBS
Triton-XAmresco9002-93-1
Horse serum
Anti-ALDH1L1 abcam ab56777
Anti-Iba1 abcam ab5076
Anti-Oligodendrocyte Specific Protein1 abcam ab53041
ImmPRESS anti-goatVector LabsMP-7405
ImmPRESS Universal (anti-mouse/rabbit)Vector LabsMP-7500
Hydrogen peroxideSigma Aldrich216763
ImmPACT DAB substrateVector LabsSK-4105
Hematoxylin counterstainThermoScientific72404
Histochoice Mounting MediaAmrescoH157-475
Aperio ScanscopeLeica Biosystems
Image ScanscopeLeica Biosystems
Super HT PAP PenResearch Products International195506

References

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  1. Claes, A., Idema, A. J., Wesseling, P. Diffuse glioma growth: a guerilla war. Acta Neuropathol. 114 (5), 443-458 (2007).
  2. Holland, E. C. Glioblastoma multiforme: the terminator. Proc. Natl. Acad. Sci. U. S. A. 97 (12), 6242-6244 (2000).
  3. Wild-Bode, C., Weller, M., Rimner, A., D....

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Tags

Glioblastoma Tumor MicroenvironmentChromogenic ImmunohistochemistryImageJ AnalysisGlial Cell QuantificationPatient Tumor ResectionsAntigen RetrievalPermeabilization SolutionPrimary AntibodiesDAB SubstrateHematoxylin Counterstain

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