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.

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 analysis11.
1. FFPE Sample Deparaffinization and Rehydration
NOTE: This portion of the protocol is specific to FFPE samples. While paraffin-embedded samples can be more useful for this analysis because of the preservation of cellular and tissue morphology, this analysis can also be done with frozen sections. If using frozen sections, this portion can be omitted and proceed directly to chromogenic immunohistochemistry.
<ol>
	<li>Perform the following washes for 5 min each: Xylene, Xylene, 100% Ethanol, 100% Ethanol, 95% Ethanol, 95% Ethanol, 70% Ethanol, Deionized water, Deionized water</li>
</ol>
2. Antigen Retrieval
NOTE: This portion of the protocol is necessary to break methylene bridges formed during formalin fixation of FFPE samples and expose antigen sites for antibodies to bind.
<ol>
	<li>Dilute Tris-based high pH antigen unmasking solution at manufacturer recommendation in distilled water.</li>
	<li>Perform heat-mediated antigen retrieval using a microwave. Other forms of heat-mediated retrieval (such as pressure cooker, vegetable steamer, or boiling water) would also suffice.
	<ol>
		<li>Add the diluted unmasking solution into a non-sealed microwaveable vessel. Place slides into vessel. Place slides into microwave.</li>
		<li>Boil for 20 min at high power. Monitor liquid levels for evaporation, and replenish with distilled water as necessary.</li>
	</ol>
	</li>
	<li>Allow samples to cool in solution for 1 h at room temperature.</li>
</ol>
3. Chromogenic Immunohistochemistry
<ol>
	<li>Outline tissue sample with a hydrophobic pen to minimize volume of reagents necessary to cover sample. 
	NOTE: Be sure to keep tissue samples hydrated and do not let them dry out as this will affect staining efficacy.</li>
	<li>Pipet enough permeabilization solution (Tris-buffered saline (TBS) + 0.01% Triton-X) to cover tissue sample (typically about 100 - 200 &#181;L).</li>
	<li>Remove and discard solution and repeat step 3.2.</li>
	<li>Incubate samples at room temperature with blocking solution (2.5% horse serum + permeabilization solution).</li>
	<li>Incubate samples overnight in 4 &#186;C with primary antibodies diluted in blocking solution. 
	NOTE: All primary antibodies used here are diluted at 1:200, but optimal dilutions can be determined using serial dilutions starting with manufacturer recommendation. Detailed information on antibodies used in this protocol was previously published11.</li>
	<li>Detect primary antibodies using a horseradish peroxidase polymer reagent corresponding with the primary antibody host animal, following manufacturer protocol.</li>
	<li>Pipet enough permeabilization solution to cover tissue sample and incubate for 5 min.</li>
	<li>Remove and discard solution and repeat Step 3.7.</li>
	<li>Incubate slides in 0.3% H2O2 in 1x TBS for 15 min.</li>
	<li>Develop samples with a peroxidase diaminobenzidine (DAB) substrate for 2 - 10 min until desired stain intensity is achieved.</li>
	<li>Counterstain samples to identify cell nuclei, such as with hematoxylin, following manufacturer protocol.</li>
	<li>Dehydrate samples with 100% ethanol and xylene.</li>
	<li>Mount samples permanently with mounting media.</li>
</ol>
4. Regions of Interest Identification
<ol>
	<li>Image slides under brightfield microscopy capable of high resolution images. 
	NOTE: Use imaging cellular components at a minimum of 20x resolution.</li>
	<li>Move camera to specific regions of interest throughout tissue samples.</li>
	<li>Save images as TIFF files for quantification.</li>
</ol>
5. Image Analysis
<ol>
	<li>Open images in ImageJ for quantification of percent coverage.</li>
	<li>Use the Threshold Colour plugin to remove purple color from hematoxylin stained nuclei.</li>
	<li>Convert image to 8-bit.</li>
	<li>Add threshold without dark background.</li>
	<li>Process image using one of the 17 pre-loaded ImageJ threshold filters (i.e. MaxEntropy) so only DAB stained portions are included in the threshold. 
	NOTE: Select the optimal pre-loaded threshold filter that minimizes inclusion of background staining. This can depend on the quality of staining and specificity of antibody. Use the same threshold for all technical replicates within each patient sample.</li>
	<li>Apply threshold.</li>
	<li>Measure percent area of thresholded image.</li>
	<li>Average percent area coverage for multiple regions within each sample.</li>
</ol>

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Care Med. 162 (4), 1577-1586 (2000).</li><li>Turcan, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=IDH1+mutation+is+sufficient+to+establish+the+glioma+hypermethylator+phenotype.">IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype.</a> Nature. 483 (7390), 479-483 (2012).</li><li>Songtao, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=IDH+mutations+predict+longer+survival+and+response+to+temozolomide+in+secondary+glioblastoma.">IDH mutations predict longer survival and response to temozolomide in secondary glioblastoma.</a> Cancer Sci. 103 (2), 269-273 (2012).</li><li>Shinojima, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prognostic+Value+of+Epidermal+Growth+Factor+Receptor+in+Patients+with+Glioblastoma+Multiforme.">Prognostic Value of Epidermal Growth Factor Receptor in Patients with Glioblastoma Multiforme.</a> Cancer Res. 63, 6962-6970 (2003).</li><li>Karpel-Massler, G., Schmidt, U., Unterberg, A., Halatsch, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Therapeutic+inhibition+of+the+epidermal+growth+factor+receptor+in+high-grade+gliomas:+where+do+we+stand?.">Therapeutic inhibition of the epidermal growth factor receptor in high-grade gliomas: where do we stand?.</a> Mol. Cancer Res. 7 (7), 1000-1012 (2009).</li><li>Badie, B., Schartner, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+microglia+in+glioma+biology.">Role of microglia in glioma biology.</a> Microsc. Res. Tech. 54 (2), 106-113 (2001).</li><li>Watters, J. J., Schartner, J. M., Badie, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microglia+function+in+brain+tumors.">Microglia function in brain tumors.</a> J. Neurosci. Res. 81 (3), 447-455 (2005).</li><li>Alves, T. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Glioblastoma+cells:+A+heterogeneous+and+fatal+tumor+interacting+with+the+parenchyma.">Glioblastoma cells: A heterogeneous and fatal tumor interacting with the parenchyma.</a> Life Sci. 89 (15), 532-539 (2011).</li><li>Hambardzumyan, D., Gutmann, D. H., Kettenmann, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+microglia+and+macrophages+in+glioma+maintenance+and+progression.">The role of microglia and macrophages in glioma maintenance and progression.</a> Nat. Neurosci. 19 (1), 20-27 (2015).</li><li>Zhai, H., Heppner, F. L., Tsirka, S. 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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 vitro studies.
This protocol demonstrates a straightforward technique for quantitatively analyzing the populations of glial cells within the brain tumor microenvironment. This technique is widely adaptable and can be expanded to identify many other components of the microenvironment, such as blood vessels, chemokines, and more, as well as other cancers, such as breast or pancreatic, where the tumor resections can have larger parenchymal regions. Furthermore, this technique can be adapted to acquire other measurements, such as counts, and perimeter of cells to assess cell shape, as well as more complex morphology outcomes isotropy, clustering, orientation, and more. These techniques are also not limited to cancer, in that these staining and quantification methodologies can be used for any brain analyses, as demonstrated in our representative Protein Atlas quantification of healthy tissue, and our previously published comparison with epileptic brain tissue11.
Critical steps within this protocol include proper incubation and development of the chromogenic secondary. Care should be taken such that the chromogenic dye does not over-develop. This will make it difficult to differentiate between positive staining and background. The development time varies depending on the substrate reagent used and the affinity of the primary antibody. We use bright field microscopy to monitor development to ensure optimal staining while minimizing background staining. After staining, proper thresholding during analysis can help differentiate background from positive staining. A major limitation for this method is the inability to stain multiple components within the same tissue sample due to the use of chromogenic staining development. Immunofluorescence analysis could be conducted in a similar manner, but requires modification of the tools discussed in this method.
Specific to glioblastoma, there are a number of markers and cellular stains that have been used to analyze patient samples. These include IDH114,15, EGFRvIII16,17 as prognostic markers, as well as CD11b and CD45 for microglia and macrophages18,19. Our method expands this type of analysis to the cellular microenvironment, an often overlooked component of the tumor microenvironment in glioblastoma. Studies have looked at microglia presence and density in tumors20,21,22 as well as contributions of astrocytes9,23,24. Here we developed a protocol examining all of the glia - astrocytes, microglia, and oligodendrocytes - in the brain tumor microenvironment and to differentiate the adjacent or invasive regions of the tumor from the tumor bulk, which is where markers are usually identified in these tumors. By doing this, we believe we can more accurately assess the patient situation because we determined intra-patient heterogeneity and our previous publication showed that analysis of these locations and inclusion in statistical models is stronger at predicting outcomes than either location alone or overall samples11. Furthermore, since glioblastoma invasion is so diffuse, making it difficult to resect completely1,2, we believe the tissue in the adjacent regions is more representative of the invasive tissue left behind after resection, which contributes to inevitable recurrence. Therefore, better understanding of the adjacent regions may give more information about disease recurrence and patient treatment planning, as opposed to the traditionally studied bulk tissue that is resected prior to therapy in glioblastoma patients.

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 known about the complex mechanisms contributing to GBM invasion. The tumor microenvironment, or tissue surrounding the cancer, has been implicated in the progression of tumors in multiple cancers6,7. The glioblastoma tumor microenvironment, in particular, is relatively under-characterized and is uniquely complex, composing of multiple glial cells, such as astrocytes, microglia, and oligodendrocytes, as well as extracellular matrix, soluble factors, and biophysical factors. Experimentally, astrocytes and microglia have been shown to increase glioma progression and invasion8,9,10, but the composition of all glial cells in the native human brain microenvironment is unknown.
We previously showed microenvironmental components can predict patient survival by quantitatively analyzing cellular components of the glioblastoma microenvironment and incorporating our analyses into a proportional hazards model11. Here, we describe the quantitative analysis method for identifying 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 and ImageJ to analyze percent coverage of staining for each glial population. Assessing percent coverage creates a simple measurement for determining the morphological differences of cells, particularly those affected by interactions with cancer cells. Previous studies for quantifying histopathological staining use standard staining such as hematoxylin and eosin12 or Masson&#39;s trichrome13, which do not take advantage of the specificity of antibody-based immunohistochemistry staining. Our method was developed to directly quantify the glial populations within glioblastoma patient tumor resections, which we aim to use to elucidate the complex glioblastoma microenvironment.

<table><tbody><tr><td>Xylene</td><td>Fisher Chemical</td><td>X3P</td><td></td></tr><tr><td>Ethanol</td><td></td><td></td><td></td></tr><tr><td>High pH antigen unmasking solution</td><td>Vector Labs</td><td>H-3301</td><td></td></tr><tr><td>TBS</td><td></td><td></td><td></td></tr><tr><td>Triton-X</td><td>Amresco</td><td>9002-93-1</td><td></td></tr><tr><td>Horse serum</td><td></td><td></td><td></td></tr><tr><td>Anti-ALDH1L1&amp;nbsp;</td><td>abcam&amp;nbsp;</td><td>ab56777</td><td></td></tr><tr><td>Anti-Iba1&amp;nbsp;</td><td>abcam&amp;nbsp;</td><td>ab5076</td><td></td></tr><tr><td>Anti-Oligodendrocyte Specific Protein1&amp;nbsp;</td><td>abcam&amp;nbsp;</td><td>ab53041</td><td></td></tr><tr><td>ImmPRESS anti-goat</td><td>Vector Labs</td><td>MP-7405</td><td></td></tr><tr><td>ImmPRESS Universal (anti-mouse/rabbit)</td><td>Vector Labs</td><td>MP-7500</td><td></td></tr><tr><td>Hydrogen peroxide</td><td>Sigma Aldrich</td><td>216763</td><td></td></tr><tr><td>ImmPACT DAB substrate</td><td>Vector Labs</td><td>SK-4105</td><td></td></tr><tr><td>Hematoxylin counterstain</td><td>ThermoScientific</td><td>72404</td><td></td></tr><tr><td>Histochoice Mounting Media</td><td>Amresco</td><td>H157-475</td><td></td></tr><tr><td>Aperio Scanscope</td><td>Leica Biosystems</td><td></td><td></td></tr><tr><td>Image Scanscope</td><td>Leica Biosystems</td><td></td><td></td></tr><tr><td>Super HT PAP Pen</td><td>Research Products International</td><td>195506</td><td></td></tr></tbody></table>

quantitative immunohistochemistry of the cellular microenvironment in patient glioblastoma resections

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.

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 (Figure 1D), and oligodendrocytes (Figure 1E) via chromogenic immunohistochemistry was identified. These populations were identified using primary antibodies ALDH1L1, Iba1, and Oligodendrocyte-Specific Protein (OSP1) respectively11. Optimization of antibody dilutions is recommended, as well as consultation with manufacturer protocols to confirm if staining is accurate and positive (Figure 2). For example, we performed staining with no primary antibody for a negative control (Figure 2A), the manufacturer recommended (Figure 2B), and further dilutions (Figure 2C, 2D) before settling on the 1:200 dilution (Figure 2C) due to optimal positive staining of cell body and processes with minimizing background for the anti-ALDH1L1 antibody.
Using ImageJ, the percent coverage of OSP1+ oligodendrocyte staining was quantified to eventually compare differences in our regions of interest (Figure 3A). We removed the counterstained nuclei from the image using the Threshold Colour plugin in order to solely assess the positive DAB staining (Figure 3B). After converting the image to 8bit (Figure 3C), we then applied the MaxEntropy default threshold to the remaining positive DAB staining (Figure 3D). Here, we used the MaxEntropy threshold default because this particular default threshold best captured our positive stain while minimizing background, but different thresholds can be used to ensure analysis of the population of interest. Once the appropriate threshold has been applied to the image (Figure 3E), the percent coverage from the threshold can be measured (Figure 3F) and compared for multiple patients. Here, we quantified 3 - 5 areas within each region of interest, depending on the total area of the region of interest, and compared groups using paired t-tests with GraphPad Prism software. We also compared our GBM analyses with corresponding staining found in healthy brain tissue in the Protein Atlas database (Figure 3F). In our previous publication, we used this analysis for multiple microenvrionmental components (astrocytes, microglia, oligodendrocytes, and blood vessels) across 33 patients to develop a proportional hazards model for predicting overall patient survival11.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56025/56025fig1.jpg" /> 
Figure 1: Comparison of Tumor Bulk and Tumor Adjacent Regions of Interest for Glial Cells. 
A) Whole tumor sample from Patient 63 stained with hematoxylin and eosin with bulk and adjacent regions indicated. B) Hematoxylin and eosin staining, C) ALDH1L1+ astrocytes, D) Iba1+ microglia, and E) Oligodendrocyte Specific Protein-1 (OSP1)+ oligodendrocytes. Scale bar = 100 &#181;m. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56025/56025fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56025/56025fig2.jpg" /> 
Figure 2: Example Titration of Anti-ALDH1L1 Antibody. 
A) Negative control, B) 1:70 manufacturer recommendation dilution from stock, C) 1:200 dilution from stock, and D) 1:400 dilution from stock. 1:200 dilution was used for staining and analysis due to optimal positive staining of cell body and processes with minimizing background. Scale bar= 100 &#181;m. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56025/56025fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56025/56025fig3.jpg" /> 
Figure 3: ImageJ Analysis and Quantification of Area Coverage for Oligodendrocytes. 
A) Original OSP1+ staining of Patient 52. B) Removal of purple nuclei using Threshold_Colour plugin. C) Conversion to 8bit. D) MaxEntropy threshold captured and E) applied to minimize background staining. F) Comparison of adjacent and bulk regions in five patient samples, as well as healthy brain tissue through the Protein Atlas, for OSP1+ percent coverage. ***p&#60; 0.001, ****p&#60; 0.0001 via paired t-tests. Scale bar= 100 &#181;m. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56025/56025fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

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

With the growing interest in the tumor microenvironment, we set out to develop a method to specifically determine the microenvironment components within ...

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9.6K Views.  University of Virginia.  Dit protocol werd ontwikkeld om tumormicro-milieukomponenten kwantitatief te identificeren bij glioblastoom-patiëntresecties onder toepassing van chromogene immunohistochemie en ImageJ. 

Video: Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for immunotherapies. Recent clinical advances in immunotherapy highlight the need for reproducible methods to accurately and thoroughly characterize the tumor and its associated immune infiltrate. Tumor enzymatic digestion and flow cytometric analysis allow broad characterization of numerous immune cell subsets and phenotypes; however, depth of analysis is often limited by fluorophore restrictions on panel design and the need to acquire large tumor samples to observe rare immune populations of interest. Thus, we have developed an effective and high throughput method for separating and enriching the tumor immune infiltrate from the non-immune tumor components. The described tumor digestion and centrifugal density-based separation technique allows separate characterization of tumor and tumor immune infiltrate fractions and preserves cellular viability, and thus, provides a broad characterization of the tumor immunologic state. This method was used to characterize the extensive spatial immune heterogeneity in solid tumors, which further demonstrates the need for consistent whole tumor immunologic profiling techniques. Overall, this method provides an effective and adaptable technique for the immunologic characterization of subcutaneous solid murine tumors; as such, this tool can be used to better characterize the tumoral immunologic features and in the preclinical evaluation of novel immunotherapeutic strategies.

Here we describe a method to separate and enrich components of the tumor immune and non-immune microenvironment in established subcutaneous tumors. This technique allows for the separate analysis of tumor immune infiltrate and non-immune tumor fractions which can permit comprehensive characterization of the tumor immune microenvironment.

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for ...

Cancer Research

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures

Analysis of protein expression in glioma is relevant for several aspects in the study of its pathology. Numerous proteins have been described as biomarkers with applications in diagnosis, prognosis, classification, state of tumor progression, and cell differentiation state. These analyses of biomarkers are also useful to characterize tumor neurospheres (NS) generated from glioma patients and glioma models. Tumor NS provide a valuable in vitro model to assess different features of the tumor from which they are derived and can more accurately mirror glioma biology. Here we describe a detailed method to analyze biomarkers in tumor NS using immunohistochemistry (IHC) on paraffin-embedded tumor NS.

Neurospheres grown as 3D cultures constitute a powerful tool to study glioma biology. Here we present a protocol to perform immunohistochemistry while maintaining the 3D structure of glioma neurospheres through paraffin embedding. This method enables the characterization of glioma neurosphere properties such as stemness and neural differentiation.

Analysis of protein expression in glioma is relevant for several aspects in the study of its pathology. Numerous proteins have been described as ...

Optimization of High Grade Glioma Cell Culture from Surgical Specimens for Use in  Clinically Relevant Animal Models and 3D Immunochemistry

Glioblastomas, the most common and aggressive form of astrocytoma, are refractory to therapy, and molecularly heterogeneous. The ability to establish cell cultures that preserve the genomic profile of the parental tumors, for use in patient specific in vitro and in vivo models, has the potential to revolutionize the preclinical development of new treatments for glioblastoma tailored to the molecular characteristics of each tumor.
Starting with fresh high grade astrocytoma tumors dissociated into single cells, we use the neurosphere assay as an enrichment method for cells presenting cancer stem cell phenotype, including expression of neural stem cell markers, long term self-renewal in vitro, and the ability to form orthotopic xenograft tumors. This method has been previously proposed, and is now in use by several investigators. Based on our experience of dissociating and culturing 125 glioblastoma specimens, we arrived at the detailed protocol we present here, suitable for routine neurosphere culturing of high grade astrocytomas and large scale expansion of tumorigenic cells for preclinical studies. We report on the efficiency of successful long term cultures using this protocol&#160;and suggest affordable alternatives for culturing dissociated glioblastoma cells that fail to grow as neurospheres. We also describe in detail a protocol for preserving the neurospheres 3D architecture for immunohistochemistry. Cell cultures enriched in CSCs, capable of generating orthotopic xenograft models that preserve the molecular signatures and heterogeneity of GBMs, are becoming increasingly popular for the study of the biology of GBMs and for the improved design of preclinical testing of potential therapies.

Protocol for propagation of dissociated high grade glioma surgical specimens in serum-free neurosphere medium to select for cells with cancer stem cell phenotype. For specimens that fail to grow as neurospheres, an alternative protocol is suggested. A paraffin embedding technique for maintaining the 3D neurosphere architecture for immunocytochemistry is described.

Glioblastomas, the most common and aggressive form of astrocytoma, are refractory to therapy, and molecularly heterogeneous. The ability to establish cell ...

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Diffusely infiltrating gliomas are associated with high morbidity and mortality due to the infiltrative nature of tumor spread. They are morphologically complex tumors, with a high degree of proteomic variability across both the tumor itself and its heterogenous microenvironment. The malignant potential of these tumors is enhanced by the dysregulation of proteins involved in several key pathways, including processes that maintain cellular stability and preserve the structural integrity of the microenvironment. Although there have been numerous bulk and single-cell glioma analyses, there is a relative paucity of spatial stratification of these proteomic data. Understanding differences in spatial distribution of tumorigenic factors and immune cell populations between the intrinsic tumor, invasive edge, and microenvironment offers valuable insight into the mechanisms underlying tumor proliferation and propagation. Digital spatial profiling (DSP) represents a powerful technology that can form the foundation for these important multilayer analyses.
DSP is a method that efficiently quantifies protein expression within user-specified spatial regions in a tissue specimen. DSP is ideal for studying the differential expression of multiple proteins within and across regions of distinction, enabling multiple levels of quantitative and qualitative analysis. The DSP protocol is systematic and user-friendly, allowing for customized spatial analysis of proteomic data. In this experiment, tissue microarrays are constructed from archived glioblastoma core biopsies. Next, a panel of antibodies is selected, targeting proteins of interest within the sample. The antibodies, which are preconjugated to UV-photocleavable DNA oligonucleotides, are then incubated with the tissue sample overnight. Under fluorescence microscopy visualization of the antibodies, regions of interest (ROIs) within which to quantify protein expression are defined with the samples. UV light is then directed at each ROI, cleaving the DNA oligonucleotides. The oligonucleotides are microaspirated and counted within each ROI, quantifying the corresponding protein on a spatial basis.

Proteomic dysregulation plays an important role in the spread of diffusely infiltrating gliomas, but several relevant proteins remain unidentified. Digital spatial processing (DSP) offers an efficient, high-throughput approach for characterizing the differential expression of candidate proteins that may contribute to the invasion and migration of infiltrative gliomas.

Diffusely infiltrating gliomas are associated with high morbidity and mortality due to the infiltrative nature of tumor spread. They are morphologically ...

Multiplex Immunofluorescence and Spatial Image Analysis of the Tumor Microenvironment

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers.
We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types.
This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.

Author Spotlight: Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment  

In this article, a protocol for manual tyramide signal amplification (TSA) multiplex immunofluorescence (mIF) combined with image analysis and spatial analysis is described. This protocol can be used with formalin-fixed paraffin-embedded (FFPE) sections for the staining of two to six antigens per slide depending on the slide scanner available in the laboratory.

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending ...

Mapping the Tumor Immune Landscape: An In-Depth Multiplex IHC Analysis Protocol

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

This protocol describes in detail how immune cell characterization of the tumor microenvironment using multiplex immunohistochemistry is carried out.

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. ...

Isolation and Flow Cytometric Analysis of Glioma-infiltrating Peripheral Blood Mononuclear Cells

Our laboratory has recently demonstrated that natural killer (NK) cells are capable of eradicating orthotopically implanted mouse GL26 and rat CNS-1 malignant gliomas soon after intracranial engraftment if the cancer cells are rendered deficient in their expression of the &#946;-galactoside-binding lectin galectin-1 (gal-1). More recent work now shows that a population of Gr-1+/CD11b+ myeloid cells is critical to this effect. To better understand the mechanisms by which NK and myeloid cells cooperate to confer gal-1-deficient tumor rejection we have developed a comprehensive protocol for the isolation and analysis of glioma-infiltrating peripheral blood mononuclear cells (PBMC). The method is demonstrated here by comparing PBMC infiltration into the tumor microenvironment of gal-1-expressing GL26 gliomas with those rendered gal-1-deficient via shRNA knockdown. The protocol begins with a description of&#160;how to culture and prepare GL26 cells for inoculation into the syngeneic C57BL/6J mouse brain. It then explains the steps involved in the isolation and flow cytometric analysis of glioma-infiltrating PBMCs from the early brain tumor microenvironment. The method is adaptable to a number of in vivo experimental designs in which temporal data on immune infiltration into the brain is required. The method is sensitive and highly reproducible, as glioma-infiltrating PBMCs can be isolated from intracranial tumors as soon as 24 hr post-tumor engraftment with similar cell counts observed from time point matched tumors throughout independent experiments. A single experimentalist can perform the method from brain harvesting to flow cytometric analysis of glioma-infiltrating PBMCs in roughly 4-6 hr depending on the number of samples to be analyzed. Alternative glioma models and/or cell-specific detection antibodies may also be used at the experimentalists&#8217; discretion to assess the infiltration of several other immune cell types of interest without the need for alterations to the overall procedure.

Presented here is a straightforward method for the isolation and flow cytometric analysis of glioma-infiltrating peripheral blood mononuclear cells that yields time-dependent quantitative data on the number and activation status of immune cells entering the early brain tumor microenvironment.

Our laboratory has recently demonstrated that natural killer (NK) cells are capable of eradicating orthotopically implanted mouse GL26 and rat CNS-1 ...

Immunology and Infection

Stereotactic Adoptive Transfer of Cytotoxic Immune Cells in Murine Models of Orthotopic Human Glioblastoma Multiforme Xenografts

Glioblastoma multiforme (GBM), the most frequent and aggressive primary brain cancer in adults, is generally associated with a poor prognosis, and scarce efficient therapies have been proposed over the last decade. Among the promising candidates for designing novel therapeutic strategies, cellular immunotherapies have been targeted to eliminate highly invasive and chemo-radioresistant tumor cells, likely involved in a rapid and fatal relapse of this cancer. Thus, administration(s) of allogeneic GBM-reactive immune cell effectors, such as human V&#978;9V&#948;2 T lymphocytes, in the vicinity of the tumor would represents a unique opportunity to deliver efficient and highly concentrated therapeutic agents directly into the site of brain malignancies. Here, we present a protocol for the preparation and the stereotaxic administration of allogeneic human lymphocytes in immunodeficient mice carrying orthotopic human primary brain tumors. This study provides a preclinical proof-of-concept for both the feasibility and the antitumor efficacy of these cellular immunotherapies that rely on stereotactic injections of allogeneic human lymphocytes within intrabrain tumor beds.

Here, we present a protocol for the preparation and the stereotaxic administration of allogeneic human lymphocytes in immunodeficient mice carrying orthotopic human primary brain tumors. This study provides a proof-of-concept for both the feasibility and the antitumor efficacy of intrabrain-delivered cellular immunotherapies.

Glioblastoma multiforme (GBM), the most frequent and aggressive primary brain cancer in adults, is generally associated with a poor prognosis, and scarce ...

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Gliomas are primary brain tumors characterized by their invasiveness and heterogeneity. Specific histological patterns such as pseudopalisades, microvascular proliferation, mesenchymal transformation and necrosis characterize the histological heterogeneity of high-grade gliomas. Our laboratory has demonstrated that the presence of high densities of mesenchymal cells, named oncostreams, correlate with tumor malignancy. We have developed a unique approach to understand the mechanisms that underlie glioma&#39;s growth and invasion. Here, we describe a comprehensive protocol that utilizes laser capture microdissection (LMD) and RNA sequencing to analyze differential mRNA expression of intra-tumoral heterogeneous multicellular structures (i.e., mesenchymal areas or areas of tumor invasion). This method maintains good tissue histology and RNA integrity. Perfusion, freezing, embedding, sectioning, and staining were optimized to preserve morphology and obtain high-quality laser microdissection samples. The results indicate that perfusion of glioma bearing mice using 30% sucrose provides good morphology and RNA quality. In addition, staining tumor sections with 4% Cresyl violet and 0.5% eosin results in good nuclear and cellular staining, while preserving RNA integrity. The method described is sensitive and highly reproducible and it can be utilized to study tumor morphology in various tumor models. In summary, we describe a complete method to perform LMD that preserves morphology and RNA quality for sequencing to study the molecular features of heterogeneous multicellular structures within solid tumors.

Laser microdissection (LMD) is a sensitive and highly reproducible technique that can be used to uncover pathways that mediate glioma heterogeneity and invasion. Here, we describe an optimized protocol to isolate discrete areas from glioma tissue using laser LMD followed by transcriptomic analysis.

Gliomas are primary brain tumors characterized by their invasiveness and heterogeneity. Specific histological patterns such as pseudopalisades, ...

Neuroscience

Replicating Glioblastoma Invasion with Hyaluronan-Collagen I Hydrogel System

A Photopolymerizable Hyaluronic Acid-Collagen Model of the Invasive Glioma Microenvironment with Interstitial Flow

Glioblastoma recurrence is a major hindrance to treatment success and is driven by the invasion of glioma stem cells (GSCs) into healthy tissue that are inaccessible to surgical resection and are resistant to existing chemotherapies. Tissue-level fluid movement, or interstitial fluid flow (IFF), regulates GSC invasion in a manner dependent on the tumor microenvironment (TME), highlighting the need for model systems that incorporate both IFF and the TME. We present an accessible method for replicating the invasive TME in glioblastoma: a hyaluronan-collagen I hydrogel composed of human GSCs, astrocytes, and microglia seeded in a tissue culture insert. Elevated IFF can be represented by applying a fluid pressure head to the hydrogel. Additionally, this model can be tuned to replicate inter- or intra-patient differences in cellular ratios, flow rates, or matrix stiffnesses. Invasion can be quantified, while gels can be harvested for a variety of outcomes, including GSC invasion, flow cytometry, protein or RNA extraction, or imaging.

Author Spotlight: Patient-Informed 3D Model for Studying Glioblastoma Invasion via Interstitial Fluid Flow

We present a method for replicating the glioma tumor microenvironment at the invasive front that incorporates interstitial fluid flow. This model is a hyaluronan-collagen I hydrogel in a tissue culture insert where a fluid pressure head can be applied. Invasion can be quantified, and cells can be isolated or lysed.

Glioblastoma recurrence is a major hindrance to treatment success and is driven by the invasion of glioma stem cells (GSCs) into healthy tissue that are ...

Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

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