Name: digital spatial profiling for characterization of the microenvironment in adult-type diffusely infiltrating glioma
Uploaded: 2022-09-13T12:50:00
Description: Watch this Scientific Journal Video about Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma at JoVE.com

The authors acknowledge the support of the Laboratory for Clinical Genomics and Advanced Technology in the Department of Pathology and Laboratory Medicine of the Dartmouth Hitchcock Health System. The authors also acknowledge the Pathology Shared Resource at the Dartmouth Cancer Center with NCI Cancer Center Support Grant 5P30 CA023108-37.

The protocol outlined below follows the guidelines of the Dartmouth-Hitchcock Human Research Ethics Committee. Informed consent was obtained from the patients whose tissue samples were included in this study. See the Table of Materials section for details related to all materials, reagents, equipment, and software used in this protocol.
1. Slide preparation17
<ol>
	<li>Retrieve or prepare formalin-fixed, paraffin-embedded tissue from ...

<ol>
	<li>Pedersen, P. H., 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=Migratory+patterns+of+lac-z+transfected+human+glioma+cells+in+the+rat+brain.">Migratory patterns of lac-z transfected human glioma cells in the rat brain.</a> International Journal of Cancer. 62 (6), 767-771 (1995).</li><li>Wang, J., 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=Invasion+of+white+matter+tracts+by+glioma+stem+cells+is+regulated+by+a+NOTCH1-SOX2+positive-feedback+loop.">Invasion of white matter tracts by glioma stem cells is regulated by a NOTCH1-SOX2 positive-feedback loop.</a> Nature Neuroscience. 22 (1), 91-105 (2019).</li><li>Iwadate, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epithelial-mesenchymal+transition+in+glioblastoma+progression.">Epithelial-mesenchymal transition in glioblastoma progression.</a> Oncology Letters. 11 (3), 1615-1620 (2016).</li><li>Tao, C., 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=Genomics+and+prognosis+analysis+of+epithelial-mesenchymal+transition+in+glioma.">Genomics and prognosis analysis of epithelial-mesenchymal transition in glioma.</a> Frontiers in Oncology. 10, 183 (2020).</li><li>Cuddapah, V. A., Robel, S., Watkins, S., Sontheimer, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+neurocentric+perspective+on+glioma+invasion.">A neurocentric perspective on glioma invasion.</a> Nature Reviews Neuroscience. 15 (7), 455-465 (2014).</li><li>Barthel, L., 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=Glioma:+molecular+signature+and+crossroads+with+tumor+microenvironment.">Glioma: molecular signature and crossroads with tumor microenvironment.</a> Cancer and Metastasis Reviews. 1 (1), 53-75 (2021).</li><li>Ziegler, D. S., Kung, A. L., Kieran, M. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anti-apoptosis+mechanisms+in+malignant+gliomas.">Anti-apoptosis mechanisms in malignant gliomas.</a> Journal of Clinical Oncology. 26 (3), 493-500 (2008).</li><li>Berghoff, A. 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=Programmed+death+ligand+1+expression+and+tumor-infiltrating+lymphocytes+in+glioblastoma.">Programmed death ligand 1 expression and tumor-infiltrating lymphocytes in glioblastoma.</a> Neuro-Oncology. 17 (8), 1064-1075 (2015).</li><li>Merritt, C. 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=Multiplex+digital+spatial+profiling+of+proteins+and+RNA+in+fixed+tissue.">Multiplex digital spatial profiling of proteins and RNA in fixed tissue.</a> Nature Biotechnology. 38 (5), 586-599 (2020).</li><li>Van, T. M., Blank, C. U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+user's+perspective+on+GeoMxTM+digital+spatial+profiling.">A user's perspective on GeoMxTM digital spatial profiling.</a> Immuno-Oncology Technology. 1, 11-18 (2019).</li><li>Garcia-Pardo, M., Calles, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ROS-1+NSCLC+therapy+resistance+mechanism.">ROS-1 NSCLC therapy resistance mechanism.</a> Precision Cancer Medicine. , (2021).</li><li>Ye, L., 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=Digital+spatial+profiling+of+individual+glomeruli+from+patients+with+anti-neutrophil+cytoplasmic+autoantibody-associated+glomerulonephritis.">Digital spatial profiling of individual glomeruli from patients with anti-neutrophil cytoplasmic autoantibody-associated glomerulonephritis.</a> Frontiers in Immunology. 13, 831253 (2022).</li><li>Bergholtz, H., 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=Best+practices+for+spatial+profiling+for+breast+cancer+research+with+the+GeoMx+digital+spatial+profiler.">Best practices for spatial profiling for breast cancer research with the GeoMx digital spatial profiler.</a> Cancers. 13 (17), 4456 (2021).</li><li>Brady, L., 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=Inter-+and+intra-tumor+heterogeneity+of+metastatic+prostate+cancer+determined+by+digital+spatial+gene+expression+profiling.">Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling.</a> Nature Communications. 12 (1), 1426 (2021).</li><li>Kulasinghe, A., 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=Highly+multiplexed+digital+spatial+profiling+of+the+tumor+microenvironment+of+head+and+neck+squamous+cell+carcinoma+patients.">Highly multiplexed digital spatial profiling of the tumor microenvironment of head and neck squamous cell carcinoma patients.</a> Frontiers in Oncology. 10, 607349 (2021).</li><li>Wang, D. Y. -. T., 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=Case+study:+Digital+spatial+profiling+of+metastatic+clear+cell+carcinoma+reveals+intra-tumor+heterogeneity+in+epithelial-mesenchymal+gradient.">Case study: Digital spatial profiling of metastatic clear cell carcinoma reveals intra-tumor heterogeneity in epithelial-mesenchymal gradient.</a> bioRxiv. , (2021).</li><li>GeoMx DSP. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+slide+preparation+user+manual.">Automated slide preparation user manual.</a> GeoMx DSP. , (2022).</li><li>Allam, M., Cai, S., Coskun, A. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplex+bioimaging+of+single-cell+spatial+profiles+for+precision+cancer+diagnostics+and+therapeutics.">Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics.</a> NPJ Precision Oncology. 4, 11 (2020).</li><li>Wolchok, J. D., 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=Overall+survival+with+combined+nivolumab+and+ipilimumab+in+advanced+melanoma.">Overall survival with combined nivolumab and ipilimumab in advanced melanoma.</a> New England Journal of Medicine. 377 (14), 1345-1356 (2017).</li><li>Blank, C. U., 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=Neoadjuvant+versus+adjuvant+ipilimumab+plus+nivolumab+in+macroscopic+stage+III+melanoma.">Neoadjuvant versus adjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma.</a> Nature Medicine. 24 (11), 1655-1661 (2018).</li><li>Matthews, R. T., 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=Brain-enriched+hyaluronan+binding+(BEHAB)/brevican+cleavage+in+a+glioma+cell+line+is+mediated+by+a+disintegrin+and+metalloproteinase+with+thrombospondin+motifs+(ADAMTS)+family+member.">Brain-enriched hyaluronan binding (BEHAB)/brevican cleavage in a glioma cell line is mediated by a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) family member.</a> Journal of Biological Chemistry. 275 (30), 22695-22703 (2000).</li><li>Paganetti, P. A., Caroni, P., Schwab, 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=Glioblastoma+infiltration+into+central+nervous+system+tissue+in+vitro:+involvement+of+a+metalloprotease.">Glioblastoma infiltration into central nervous system tissue in vitro: involvement of a metalloprotease.</a> Journal of Cell Biology. 107, 2281-2291 (1988).</li><li>Beli&#235;n, A. T., Paganetti, P. A., Schwab, 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=Membrane-type+1+matrix+metalloprotease+(MT1-MMP)+enables+invasive+migration+of+glioma+cells+in+central+nervous+system+white+matter.">Membrane-type 1 matrix metalloprotease (MT1-MMP) enables invasive migration of glioma cells in central nervous system white matter.</a> Journal of Cell Biology. 144 (2), 373-384 (1999).</li><li>Coulie, P. G., Vanden Eynde, B. J., vander Bruggen, P., Boon, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumour+antigens+recognized+by+T+lymphocytes:+At+the+core+of+cancer+immunotherapy.">Tumour antigens recognized by T lymphocytes: At the core of cancer immunotherapy.</a> Nature Reviews Cancer. 14 (2), 135-146 (2014).</li><li>Finn, O. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Vaccines+for+cancer+prevention:+a+practical+and+feasible+approach+to+the+cancer+epidemic.">Vaccines for cancer prevention: a practical and feasible approach to the cancer epidemic.</a> Cancer Immunology Research. 2 (8), 708-713 (2014).</li><li>Sharma, P., Allison, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+future+of+immune+checkpoint+therapy.">The future of immune checkpoint therapy.</a> Science. 348 (6230), 56-61 (2015).</li><li>Chen, L., Han, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anti-PD-1/PD-L1+therapy+of+human+cancer:+past,+present,+and+future.">Anti-PD-1/PD-L1 therapy of human cancer: past, present, and future.</a> Journal of Clinical Investigation. 125 (9), 3384-3391 (2015).</li><li>Cai, X., 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=Glioma-Associated+stromal+cells+stimulate+glioma+malignancy+by+regulating+the+tumor+immune+microenvironment.">Glioma-Associated stromal cells stimulate glioma malignancy by regulating the tumor immune microenvironment.</a> Frontiers in Oncology. 11, 672928 (2021).</li><li>Ishii, , 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=Histological+characterization+of+the+tumorigenic+&amp;#34;peri-necrotic+niche&amp;#34;+harboring+quiescent+stem-like+tumor+cells+in+glioblastoma.">Histological characterization of the tumorigenic &amp;#34;peri-necrotic niche&amp;#34; harboring quiescent stem-like tumor cells in glioblastoma.</a> PLoS One. 11 (1), 0147366 (2016).</li><li>Lewis, C. E., Pollard, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Distinct+role+of+macrophages+in+different+tumor+microenvironments.">Distinct role of macrophages in different tumor microenvironments.</a> Cancer Research. 66 (2), 605-612 (2006).</li><li>NanoString. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CosMx+Spatial+Molecular+Imager:+True+Single-Cell+In+Situ+Solution.">CosMx Spatial Molecular Imager: True Single-Cell In Situ Solution.</a> NanoString. , (2022).</li></ol>

Given the diversity of proteins that could potentially influence the aggressiveness of gliomas and the notion that several of these proteins remain undiscovered, a high-throughput protein quantification method is an ideal technologic approach. Additionally, given that spatial data in oncologic samples often correlates with differential expression18, incorporating spatial profiling into the protein quantification approach allows for more effective analysis.
The high-thro...

Diffusely infiltrating gliomas are the most common type of malignant brain tumor in adults and are invariably lethal. The propensity for glioma cells to migrate extensively in the brain is a major therapeutic challenge. The mechanism by which they spread involves directed migration and unchecked invasion. Invasive glioma cells have been shown to exhibit tropism and migration along white matter tracts1, with recent research implicating demyelination of these tracts as an active, protumorigenic feature2. Invasion is mediated by an epithelial-to-mesenchymal transition, in which glioma cells acquire mesenchymal properties by reducing the expression of genes encoding extracellular matrix proteins and cell adhesion molecules, amplifying migration and facilitating propagation through the tumor microenvironment3,4,5.
At the molecular level, disruption of several proteins that confer cellular stability and interface with immunogenic components has been demonstrated6. Infiltrative gliomas are known to undergo suppression of proteins with anti-apoptotic (e.g., PTEN) properties7. They also overexpress proteins that promote evasion of the host immune response (e.g., PD1/PDL1)8. The dysregulation of these complex pathways enhances tumorigenicity and increases malignant potential.
Within samples of invasive glioma, the aim was to evaluate the differential expression of proteins key to cell growth, survival, and proliferation, and to microenvironment structural integrity between invasive and non-invasive components. Additionally, we sought to study the differential regulation of proteins with an active immunogenic role, offering insight to the mechanism by which compromised host immune defenses may enhance the proliferative and invasive potential of gliomas. This is especially relevant given the recent breadth of research demonstrating how immune markers and drivers of dysregulation in malignancy can serve as targets of immunotherapy. Identifying viable therapeutic targets among the many proteins involved in immunosurveillance and reactivity requires a highly sensitive and comprehensive approach.
Given the wide array of candidate proteins that can be studied, we sought a method akin to immunohistochemistry but with enhanced data processing efficiency. Within the field of cancer biology, DSP has emerged as a powerful technology with important advantages over alternative tools for proteomic analysis and quantification. The hallmark of DSP is its high-throughput multiplexing capability, allowing for simultaneous study of several different proteins within a sample, marking an important distinction from standard but lower-plex technologies such as immunohistochemistry (IHC)9,10. The multiplex feature of DSP does not compromise its fidelity as a quantitative and analytical tool, as demonstrated by studies comparing DSP to IHC. When used for proteomic quantification of non-small cell lung cancer specimens, for example, DSP has been shown to have similar results to IHC11. Additionally, DSP offers customizable regional specification, in which users can manually define regions within which to perform proteomic analysis. This presents an advantage over whole-section multiplex methods10,12. In a single round of processing, DSP thus offers multiple layers of analysis by surveying several protein targets across multiple regions of interest.
DSP has applications in several different pathological settings. DSP is especially advantageous in oncologic analysis, as spatial variation can correlate with cellular transformation and differential protein expression. For example, DSP has been used to compare the proteomic profile of breast cancer to the adjacent tumor microenvironment. This carries important implications for understanding the natural history of this tumor and its progression, as well as potential response to treatment13. Additional contexts illustrating the versatility of DSP include spatial quantification of protein diversity in prostate cancer14, association of immune cell marker expression with disease progression in head and neck squamous cell carcinoma15, and demonstration of an epithelial-mesenchymal gradient of protein expression distinguishing metastatic from primary clear cell ovarian cancer16. By implementing DSP, we characterize the spatial topography of proteins that could impact tumorigenesis and invasion of gliomas.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>BOND Research Detection System</td>
			<td>Leica Biosystems, Wetzlar, Germany</td>
			<td>DS9455</td>
			<td>Open detection system containing open containers in a reagent tray</td>
		</tr>
		<tr>
			<td>BOND Wash</td>
			<td>Leica Biosystems, Wetzlar, Germany</td>
			<td>AR950</td>
			<td>10X concentrated buffer solution for washing fixed tissue</td>
		</tr>
		<tr>
			<td>Buffer W</td>
			<td>NanoString, Seattle, WA</td>
			<td>contact company</td>
			<td>Blocking reagent</td>
		</tr>
		<tr>
			<td>Cy3 conjugation kit</td>
			<td>Abcam, Cambridge, UK</td>
			<td>AB188287</td>
			<td>Cy3 fluorescent antibody conjugation kit</td>
		</tr>
		<tr>
			<td>GeoMx Digital Spatial Profiler (DSP)</td>
			<td>NanoString, Seattle, WA</td>
			<td>contact company</td>
			<td>System for imaging and characterizing protein and RNA targets</td>
		</tr>
		<tr>
			<td>GeoMx DSP Instrument BufferKit</td>
			<td>NanoString, Seattle, WA</td>
			<td>100471</td>
			<td>Buffer kit for GeoMX DSP (including buffers for sample processing and preparation)</td>
		</tr>
		<tr>
			<td>GeoMx Hyb Code Pack_Protein</td>
			<td>NanoString, Seattle, WA</td>
			<td>121300401</td>
			<td>Controls for running GeoMX DSP experiemtns</td>
		</tr>
		<tr>
			<td>GeoMx Immune Cell Panel (Imm Cell Pro_Hs)</td>
			<td>NanoString, Seattle, WA</td>
			<td>121300101</td>
			<td>Protein module with targets for human immune cells and immuno-oncologic targets</td>
		</tr>
		<tr>
			<td>GeoMx Pan-Tumor Panel (Pan-Tumor_Hs)</td>
			<td>NanoString, Seattle, WA</td>
			<td>121300105</td>
			<td>Protein module with targets for multiple human tumor types and for markers of epithelial-mesenchymal transition</td>
		</tr>
		<tr>
			<td>GeoMx Protein Slide Prep FFPE</td>
			<td>NanoString, Seattle, WA</td>
			<td>121300308</td>
			<td>Sample preparation reagents for GeoMX DSP protein analysis</td>
		</tr>
		<tr>
			<td>IDH1-R132H antibody</td>
			<td>Dianova, Hamburg, Germany</td>
			<td>DIA-H09</td>
			<td>Monoclonal antibody against human IDH1 R132H</td>
		</tr>
		<tr>
			<td>LEICA Bond RX</td>
			<td>Leica Biosystems, Wetzlar, Germany</td>
			<td>contact company</td>
			<td>Fully automated IHC stainer</td>
		</tr>
		<tr>
			<td>Master Kit--12 reactions</td>
			<td>NanoString, Seattle, WA</td>
			<td>100052</td>
			<td>Materials and reagents for use with the nCounter Analysis system</td>
		</tr>
		<tr>
			<td>nCounter Analysis System</td>
			<td>NanoString, Seattle, WA</td>
			<td>contact company</td>
			<td>Automated system for multiplex target expression quantification (to be used with GeoMx DSP)</td>
		</tr>
		<tr>
			<td>TMA Master II</td>
			<td>3DHistech Ltd., Budapest, Hungary</td>
			<td></td>
			<td>To create the tissue microarray block</td>
		</tr>
	</tbody>
</table>

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.

Figure 4 shows the representative results from a DSP experiment performed on samples of glioblastoma. A heat map is presented, illustrating one of the methods by which to capture data visually using the DSP software. Rows represent protein targets, and each column corresponds to a region of interest. A color range of blue to red denotes low to high expression, respectively. Variability of color within a row reflects regional protein heterogeneity and suggests a possible spatial association w...

Watch this Scientific Journal Video about Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma at JoVE.com

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

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 ...

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