Unlock Brain Tumor Insights With Imaging Mass Cytometry
App Note / Case Study
Published: November 14, 2024
Credit: iStock
Understanding the intricacies of the brain tumor microenvironment (TME) is crucial for developing precise diagnostic and therapeutic strategies, but the high degree of complexity often limits research insights.
However, the latest imaging techniques, such as imaging mass cytometry (IMC) offer unprecedented insight into the TME by uncovering spatial distribution distinct molecular markers without autofluorescence data artifacts.
This application focus explores how IMC can be applied to identify major cell populations that make up mouse brain matter.
Download this application focus to discover:
- How IMC technology provides detailed insights into the TME
- Techniques for identifying cellular origins, immune interactions and tumor phenotypes in glioblastoma models
- Practical guidance on single-cell analysis to advance neuro-oncology studies and improve therapeutic outcomes
IMAGING
WHAT’S INSIDE
Objectives
Study Design
Results
• Maxpar Neuro Phenotyping
IMC Panel Kit
• Maxpar OnDemand Mouse
Neuro-Oncology IMC Bundle
Conclusions
Tips for Success
Methods
Required Reagents
References
Introduction
Brain neoplasms represent a complex form of cancer that is challenging to
classify and treat. More than 120 tumor subtypes originate from various parts
of the central nervous system, which makes identifying the composition
of the tumor microenvironment (TME) vital for early assessment of
progression, treatment, and prevention1
. Imaging Mass Cytometry™ (IMC™)
offers unprecedented insight into the TME by simultaneously uncovering
the spatial distribution of 40-plus distinct molecular markers without
autofluorescence data artifacts, facilitating the research of brain neoplasms.
Here, we demonstrate the application of a high-plex Maxpar® OnDemand
Mouse Neuro-Oncology IMC Bundle on normal and tumor formalin-fixed,
paraffin-embedded (FFPE) mouse brain tissues (Figure 1). This panel consists
of the validated Maxpar Neuro Phenotyping IMC Panel Kit (201337) and the
Maxpar OnDemand™ Mouse Immuno-Oncology IMC Panel Kit (9100005),
as shown in Table 1.
The Neuro Phenotyping IMC Panel consists of cross-reactive clones
(human and mouse) and enables flexible panel design for brain-specific
research goals, such as brain tumor classification and assessment of
neuronal inflammation, activation, and development. We applied the Maxpar
OnDemand Mouse Neuro-Oncology IMC Bundle on mouse normal brain
and glioblastoma tissues. We successfully identified major cell populations
that make up mouse brain matter, such as neurons, astrocytes, microglia,
and oligodendrocytes. Various tumor cell phenotypes and resident and
infiltrating immune cells were detected in mouse glioblastoma TME.
Unravel the Complexity
of Mouse Brain Tumors
Maxpar OnDemand Mouse
Neuro-Oncology IMC Bundle
APPLICATION NOTE
Objectives
• Showcase the performance of high-parameter IMC imaging on mouse
brain tissues using the Maxpar Neuro Phenotyping IMC Panel Kit.
• Illustrate the ability of the 35-marker Maxpar OnDemand Mouse Neuro-Oncology
IMC Bundle to identify immuno-oncological processes within the brain TME.
• Exhibit the power of the panels to enable single-cell analysis for
fast and accurate brain tumor and immune cell phenotyping.
Signaling pathway activation
in glioblastoma
2 | Application Note | Unravel the Complexity of Mouse Brain Tumors
* Panel kits are part of the Maxpar OnDemand Mouse Immuno-Oncology IMC Panel Kit.
Figure 1. Maxpar OnDemand Mouse Neuro-Oncology IMC Bundle. The panels are specifically designed to highlight the structure and cellular
composition within the normal and diseased mouse brain TME. For additional details regarding specific metal combinations, antibody clones, and
targets, refer to Table 1.
Subsequent single-cell analysis provided a
comprehensive and quantitative assessment of the
brain TME in mouse glioblastoma tissues. Empowered
by the Maxpar OnDemand Mouse Neuro-Oncology
IMC Bundle, IMC can accelerate brain tumor research
and provide insights into the spatial complexity of
neuronal neoplasms.
Study Design
A high-parameter 40-marker antibody panel designed to
highlight central features of the mouse neurological TME
(Figure 1, Table 1) is presented in this application note.
The Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle consists of the Maxpar Neuro Phenotyping IMC
Panel Kit in combination with the Maxpar OnDemand
Mouse Immuno-Oncology IMC Panel Kit. In addition, we
used the Maxpar IMC Cell Segmentation Kit (201500)
and Cell-ID™ Intercalator-Ir (201192A). This high-plex IMC
panel was assembled to reveal critical insights about
tissue structure and the functional state of cells in normal
and tumor-containing brain tissues (Table 1).
Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle (PN 9100005NO):
• Maxpar Neuro Phenotyping IMC Panel Kit detects
the underlying cellular and structural composition
of normal and tumorous brain tissue in both mouse
and human. Moreover, the antibody kit highlights
major cell populations as well as their activated or
senescent state.
• Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle detects activation of signaling pathways,
metabolism and growth, metastatic potential in
cancer cells, and the presence of lymphoid and
myeloid cell subtypes of immune cell infiltrates and
their functional state.
Other components:
• The IMC Cell Segmentation Kit and Cell-ID
Intercalator-Ir were applied to facilitate
single-cell analysis.
Unravel the Complexity of Mouse Brain Tumors | Application Note | 3
The full panel was applied on sagittal sections of mouse
normal (C57/BL6) brain and syngeneic glioblastoma
(GL261) tissue. A variety of distinct sections of the normal
brain (cerebral cortex, cerebellum, hippocampus) and
glioblastoma (tumor core and margins) were ablated.
Normal and tumor tissue slides were prepared and
stained using optimized antibody dilutions. The panel
was titrated and tested on normal and tumor samples.
Tissue slides were ablated using the Hyperion™ Imaging
System. Qualitative data analysis, multiplexed image
rendering, and single-channel image extractions were
performed using MCD™ Viewer. Quantitative single-cell
analysis was performed for glioblastoma data using a
pipeline consisting of 2 steps: CellProfiler™ was used
for cell segmentation and histoCAT™ was used for
t-distributed stochastic neighbor embedding (t-SNE)
and PhenoGraph clustering. See Methods for additional
experimental details regarding samples, staining,
ablation, and data analysis.
Results
Maxpar Neuro Phenotyping IMC Panel Kit detects
the spatial position of major cell lineages in the brain
The brain is a complex organ composed of a vast array
of cell types, each with its own unique function and role
in brain physiology. Classifying major cell lineages in
the brain is crucial to understanding the organization
and function of its complex structure1
. The Maxpar
Neuro Phenotyping IMC Panel Kit combines markers
for neurons, astrocytes, microglia, oligodendrocytes,
and endothelial cells, offering important insights into
brain development and function (Figures 1 and 2).
In normal mouse tissues (cerebral cortex, cerebellum,
hippocampus), NeuN labels neuronal cell bodies and
MAP2 highlights axonal projections within the white
matter. Astrocytes expressing GFAP are also abundantly
found. S100β-expressing astrocytes, Iba1-expressing
microglia, and Olig2-expressing oligodendrocytes
are dispersed in the brain tissue. CD34 highlights the
presence of large and small blood vessels.
Figure 2. Maxpar Neuro Phenotyping IMC Panel Kit identifies
distinct spatial positioning of the major brain cell lineages in
normal mouse brains. Rendered images of FFPE mouse brain
tissues demonstrate the performance of markers with virtually
no background, typically observed in brain tissues due to
autofluorescence. Scale bar applies to all images in the figure. Cerebral cortex
NeuN MAP2 S100β Iba1 GFAP CD34 Olig2
Cerebellum Hippocampus
1.8 mm
4 | Application Note | Unravel the Complexity of Mouse Brain Tumors
Figure 3. The Maxpar OnDemand Mouse Neuro-Oncology IMC Bundle provides assessment of cellular origin, stemness, and differentiation
of glioblastoma tumor cells. Tumor cells of oligodendrocyte precursor cell lineage expressing Olig2 are detected (inset A, white arrowhead).
Stem cell-like tumor cells expressing CD44 are observed (A). Tumor cells expressing S100β at high (inset A, yellow arrowhead) and low levels
(inset A, white arrowhead) are present. β-catenin (inset B, yellow arrowhead) and Ki-67 (inset B, white arrowhead) define activated tumor cells
undergoing cell replication. Vimentin (A) and β-actin (B) expression highlights the structural features of the tumor cell cytoskeleton.
Figure 4. The Maxpar OnDemand Mouse Neuro-Oncology IMC Bundle provides assessment of tissue architecture in glioblastoma.
Fibronectin and collagen 1 markers offer insights into the positioning and composition of the extracellular matrix (inset A). αSMA labels
vasculature-associated pericytes and stromal cells (inset A). Endothelial cell markers CD34 and CD31 evaluate the vascular coverage
of the TME (inset B, yellow arrowhead). CD45 markers permit detection of immune cells (inset B, white arrowhead).
Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle deciphers the tumor and immune cell
populations in mouse glioblastoma TME
Glioblastoma is a highly complex and aggressive
type of brain cancer. The highly heterogenous tumor
tissue contains diverse zones with varying genetic,
molecular, and cellular profiles that promote resistance
to conventional therapies and tumor recurrence. Better
understanding of the complex biology of glioblastoma
is necessary to develop more effective treatments2.
The Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle offers a wide variety of markers for detailed
assessment of the brain TME.
Assessment of tumor origin, stemness,
and aggressiveness
Glioblastoma arises from glial precursor cells such
as astrocytes and oligodendrocytes in the brain3
.
The Neuro Phenotyping IMC Panel Kit includes
markers that help to determine the cellular origins of
any glioblastoma tissue. Assessment of the mouse
glioblastoma tissue revealed the presence of
Olig2 expression in tumor cells4
(Figures 3 and S1).
Expression of cancer stem cell (CSC) marker CD44
was detected in tumor cells, indicating the ability
of tumor cells to self-renew and differentiate into
potential metastatic cell types5. Expression of tumor
differentiation biomarkers S100β, β-catenin, and
Ki-67 was noted in most tumor cells, demonstrating
the aggressiveness of the tumor. Accumulation of
intermediate (vimentin+) and actin (β-actin+) filaments
in tumor cells demonstrates the ability of tumor cells to
migrate and metastasize from the primary tumor site.
Mouse glioblastoma
S100β Olig2 Vimentin CD44 S100β Olig2 Vimentin CD44 β-catenin Ki-67 β-actin
A
B A B
αSMA Fibronectin Collagen 1 αSMA Fibronectin Collagen 1 CD45 CD31 CD34
Mouse glioblastoma
A
B
A B
Unravel the Complexity of Mouse Brain Tumors | Application Note | 5
Extracellular matrix and vasculature
Glioblastoma exhibits abnormal distribution of
extracellular matrix (ECM), which can act as a physical
barrier to drug delivery and provide a protective
environment for tumor cells6. ECM markers fibronectin
and collagen 1 offer a detailed spatial assessment of
ECM composition (Figures 4 and S1). The vasculature
of glioblastoma undergoes faulty angiogenesis (the
formation of new blood vessels from pre-existing
ones) and forms leaky blood vessels that permit
increased intravasation of tumor cells, extravasation of
immune cells, and accumulation of fluid in the brain7,8.
Vascular markers αSMA, CD34, and CD31 permit a
detailed assessment of vascular density and function.
The accumulation of pan-immune cell marker CD45-
expressing cells adjacent to blood vessels highlights
extravasating immune cells.
Signaling and metabolism
Targeting signaling pathways that promote cell
proliferation and tumor survival is an active area of
research with a goal to develop small molecular
inhibitors to curb tumor growth9
. Phosphorylated
tyrosine (p-tyrosine) and pERK1/2 markers assess
the activation of receptor tyrosine kinase (RTK) and
Ras signaling pathways. Both markers are readily
expressed in glioblastoma tissue (Figures 5 and S1).
In glioblastoma, activation of the mTOR pathway,
which regulates metabolic activation in tumor cells,
is frequently observed10. Phosphorylated ribosomal
subunit 6 (pS6) serves as a marker for increased
metabolic activity, and its presence is detected in
glioblastoma tumor cells.
Immune cell infiltration
The tumor immune microenvironment (TIME) in
glioblastoma is a highly dynamic system composed
of lymphoid and myeloid cells that influence tumor
growth and progression. Infiltration of lymphoid
cells such as cytotoxic T cells, T helper cells, and B
cells is often associated with improved survival in
patients with glioblastoma11. Myeloid cells, including
macrophages and microglia, are also present in high
numbers in glioblastoma TIME and are indicative of
an immunosuppressive phenotype12 (Figures 6 and
S1). In mouse glioblastoma, specific T cell phenotypes
are detected by utilizing the differential expression of
CD3, CD8, CD4, and B220 markers. Myeloid cells are
identified using microglial marker Iba1, macrophage
marker F4/80, monocyte marker CD11b, and neutrophil
marker Ly-6G.
Figure 5. The Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle provides assessment of signaling and metabolic pathway
activation in glioblastoma. The presence of p-tyrosine signal
identifies cells with activated RTK-mediated signaling (inset A, white
arrowhead). pERK1/2 expression indicates cells with stimulated
mitogen-activated protein kinase (MAPK) signaling (inset A, yellow
arrowhead). pS6, a component of the mTOR signaling pathway,
highlights metabolically active cells (inset A, magenta arrowhead).
Mouse glioblastoma
p-tyrosine pERK1/2 pS6
A
A
6 | Application Note | Unravel the Complexity of Mouse Brain Tumors
and 12 display high levels of stem cell marker CD44,
indicative of high tumor stemness and the presence of
a heterogenous TME. Notably, stem cell-like tumor cells
in cluster 12 are embedded in the ECM due to their
spatial localization within fibronectin-enriched areas of
tumor tissue.
Activated tumor cells
Tumor-specific cell clusters 2, 7, 8, and 13 exhibit
elevated levels of Ki-67. Collectively, these
replicating cells represent 28% of the cells in the
TME. Clusters 7 and 8 contain cells with elevated
levels of S100β and pERK1/2, respectively, indicating
activation of cell differentiation processes. Cluster 13
demonstrates increased signal for the mTOR signaling
pathway component pS6, suggesting high cellular
metabolic activity.
Immune cells
Immune cells represent 12% of the total population of
the TME with myeloid cells being the predominant type
(77% of total immune cell population). All immune cell
clusters exhibit expression of CD45 and enrichment of
β-actin signal, suggestive of high migratory capacity.
Cluster 9 encompasses resident microglia (Iba1+).
Cluster 14 contains macrophages (F4/80+, CD11b+, MHC
class II+) expression whereas cluster 16 comprises
macrophages embedded in the ECM (fibronectin+,
collagen 1+). Cluster 15 is composed of cytotoxic T cells
(CD3+, CD8+). Cluster 17 contains regulatory T cells
(CD3+, CD4+, FoxP3+), whereas cluster 22 contains
T helper cells (CD3+, CD4+).
Figure 6. The Maxpar OnDemand Mouse Neuro-Oncology IMC Bundle provides an assessment of immune cell composition
in the TME. Lymphoid cells are identified by the expression of CD3 (T cells, white arrowheads) or B220 (B cells; inset A, yellow
arrowheads). T cells are further subdivided into specific cell lineages through the assessment of CD4 (T helper cells; inset A,
magenta arrowheads) and CD8 (cytotoxic T cells; inset A, blue arrowheads) markers. Infiltrating myeloid cells are identified by
combinatorial expression of F4/80 (inset B, blue arrowheads) and CD11b (inset B, yellow arrowheads). Exclusive Iba1 expression
highlights resident tissue microglia (inset B, magenta arrowheads).
Immune cell activation
Assessment of immune cell activity is important in
designing effective immunotherapeutic treatments.
Presence of cytotoxic T cells and regulatory T cells
provides important information about the state of the
TIME13. In mouse glioblastoma, the cytotoxic activation
marker granzyme B is detected in CD8+ T cells and
macrophages (Figure 7). Regulatory T cells expressing
the FoxP3 marker are identified in the TIME.
Maxpar OnDemand Mouse Neuro-Oncology
IMC Bundle enables single-cell analysis of
mouse glioblastoma
In combination with the IMC Cell Segmentation Kit,
the Maxpar OnDemand Mouse Neuro-Oncology IMC
Bundle facilitates single-cell analysis of the mouse
TME for the evaluation of tumor progression. Singlecell analysis of mouse glioblastoma detected a
total of 139,847 cells from 5 tumor cores (2.5 mm2
each). PhenoGraph analysis grouped the cells into
23 distinct clusters, with 12 designated as tumor
cell-specific, 8 as immune cell-specific, 1 as vascularspecific, and 2 as unspecified. Each cluster phenotype
is defined by the presence or absence of a combination
of markers from the antibody bundle (Figures 8 and S2).
Senescent tumor cells
Clusters 1, 4, and 12 highlight senescent tumor cells that
collectively make up 25% of the cells in the TME. Tumor
cells in cluster 1 express Olig2 and vimentin, suggestive
of non-replicative migratory cells. Cells in clusters 4
Unravel the Complexity of Mouse Brain Tumors | Application Note | 7
Figure 7. The Maxpar OnDemand Mouse Neuro-Oncology
IMC Bundle provides an assessment of immune cell
activation in the TME. Activated cytotoxic T cells (CD3+) are
identified by simultaneous expression of CD8 and granzyme B
(A, yellow arrowheads). Activated cytotoxic macrophages are
identified by simultaneous expression of F4/80 and granzyme
B (A, white arrowheads). Exhausted regulatory T cells (CD4+,
FoxP3+; B, yellow arrowheads) are distinguished from T helper
cells (CD4+; B, white arrowheads) through expression of FoxP3.
Scale bar applies to both images in the figure. Dashed line
demarcates tumor margin.
Figure 8. Single-cell analysis of mouse glioblastoma reveals
the cellular composition of the TME. The t-SNE plot illustrates
23 cellular clusters identified by PhenoGraph analysis. Spatial
positioning of the 14 clusters labeled in the t-SNE plot (A) are shown
overlaid on glioblastoma tissues (B–E). Clusters are identified by
marker expression along with the percent composition of cells in the
TME. Cell masks are overlaid on images demonstrating ICSK1 (green),
ICSK2 (red), and ICSK3 (blue). Vim, vimentin; FN, fibronectin; Col 1,
collagen 1; β-cat, β-catenin; β-act, β-actin.
Senescent tumor cells Activated tumor cells
Immune cells Vasculature
4 Stem-cell like tumor cells – CD44+, Vim+ 8%
1 Tumor cells – Olig2+, Vim+ 14%
12 Stem-cell like tumor cells – CD44+, FN+ 3%
7 Activated dierentiation – Olig2+, S100β+, Ki-67+ 6%
2 Activated replication – Olig2+, Ki-67+ 14%
8 Activated MAPK signaling – Olig2+, pERK1/2+, Ki-67+ 5%
13 Activated metabolic activity – Olig2+, pS6+, Ki-67+ 3%
14 Macrophages – CD45+, F4/80+, CD11b+, MHC-II+ 2%
9 Microglia – CD45low, Iba1+, Vim+ 4%
15 Cytotoxic T cells – CD45+, CD3+, CD8+ 2%
16 ECM embedded myeloid cells – FN+, Col 1+, F4/80+ 2%
17 Regulatory T cells – CD45+, CD3+, CD4+, FoxP3+ 1.2%
11 Endothelial cells – CD34+, CD31+, αSMA+, β-cat+ 3%
12
1
4
11
2
7
13 8
22 T helper cells – CD45+, CD3+, CD4+ 0.3%
t-SNE plot of PhenoGraph clusters
9
14 15
22 17 16
A
B C
D E
8 | Application Note | Unravel the Complexity of Mouse Brain Tumors
Vasculature
Vascular cells, identified by CD34 and CD31 signal and
represented by cluster 11, make up 3% of the total cell
population. High expression of vimentin was detected
in the vascular cells, which suggests activation of
vascular remodeling. In addition, enriched levels of
β-catenin and extensive αSMA+ pericyte coverage
suggest strong intercellular junctional integrity in
blood vessels14.
Conclusions
Despite significant progress in preclinical cancer
therapeutics, the lack of comprehensive data on their
effects on neurological tumors has been a major
challenge in their successful translation to the clinic.
IMC offers a unique opportunity to evaluate up to 40-
plus clinically relevant biomarkers while eliminating
false positive background signal typically observed in
brain tissues due to autofluorescence.
As described in this application note, the application
of the Maxpar OnDemand Mouse Neuro-Oncology
IMC Bundle enables researchers to conduct detailed
mouse neuro-oncology studies that can uncover
crucial insights into tumor development, progression,
and treatment. Our quantitative analysis of mouse
glioblastoma revealed insights regarding overall
cellular composition of the TME and tumor prognostic
parameters such as:
• Identity of tumor cell origin and stemness
• Activation of cellular processes in tumor cells
• Presence of resident and infiltrating immune cells
• Stimulation of immune cell activity
• Quantitative assessment of tumor tissue composition
Overall, the innovative Maxpar OnDemand Mouse
Neuro-Oncology IMC Bundle, including the human
and mouse cross-reactive Maxpar Neuro Phenotyping
IMC Panel Kit, facilitates accurate deciphering of
complex biological processes, providing translational
researchers and clinicians with a powerful tool to
advance the understanding of brain neoplasms and
improve patient outcomes.
Tips for Success
• For best results, use freshly cut FFPE tissue samples when possible.
• Perform a 3-point titration and include positive control tissue for all antibodies when optimizing working
concentration on tumor tissue. Recommended dilution ranges for each antibody can be found in the technical
data sheet (TDS-00721).
• After staining, samples should be stored at room temperature in slide holders inside a sealed bag in a
non-humid environment.
• Customers should reach out to their local Field Applications Specialist (FAS) for ordering and product support.
To be connected to a FAS, contact technical support.
Unravel the Complexity of Mouse Brain Tumors | Application Note | 9
Methods
Panel kit design
Antibodies were selected based on the best fit for
the neuro-oncology application on tissues and full
compatibility with the Maxpar OnDemand Mouse
Immuno-Oncology IMC Panel Kit. For ordering
information, refer to Table 1.
Tissue
Mouse normal brain tissue sections (sagittal cut)
were obtained from AMSBIO and mouse syngeneic
glioblastoma (GL261) full tissue sections were obtained
from Charles River and stored according to the
manufacturer’s recommendation before use. Several
regions of the normal brain were ablated, including
cerebellum, cerebral cortex, and hippocampus. Varying
regions of interest (ROI) were selected on glioblastoma
tissue, including tumor cores and margins.
Staining
Imaging was performed using the Hyperion Imaging
System with CyTOF® Software v7.0. Before ablation,
instrument tuning was performed using a tuning slide.
For normal and tumor tissue imaging, each ROI of
1.6 mm2 or 2.56 mm2* was selected and ablated at
200 Hz with 3 dB laser power and 1 µm resolution. For
normal tissue, 3 ROIs shown in Figure 2 were ablated.
For glioblastoma, 5 ROIs were selected from various
locations on the tissue including tumor margins and
cores. Single-channel channel images were exported
from MCD files and used for subsequent analysis.
Data analysis
MCD Viewer v1.0.560.6 (Standard BioTools™) was used
to render multiplexed and single channel 16-bit TIFF
images. For qualitative verification of staining, images
for each channel were rendered and verified to ensure
absence of non-specific and background staining. For
glioblastoma tissue, raw single channel OME-TIFF files
were exported for further analysis. Graphics shown in
Figure 1 were created using biorender.com.
Cell segmentation
The IMC Cell Segmentation Kit and Cell-ID IntercalatorIr were used to label the cell membrane and nuclei of
all cells present in the TME, respectively. CellProfiler
v4.2.1 was used to perform cell segmentation. A
basic pipeline for cell segmentation was assembled,
which included primary (nuclei) and secondary (cell
membrane) object identification modules. Images
containing individual cell masks were generated and
extracted for single-cell analysis.
Single-cell analysis
Single-channel OME-TIFF and cell masks for
glioblastoma ROIs were loaded into histoCAT v1.76.
t-SNE analysis and PhenoGraph clustering were
performed. Masks representing specific clusters were
plotted on to ROIs rendered with ICSK channels and
cell quantities for each cluster were extracted and
documented. All clusters were plotted on the t-SNE
graph (Figure 8).
* The recommended maximum ROI size for the Hyperion Imaging Systems is 1.5 x 1.5 mm (2.25 mm2), however it is possible to acquire larger
ROIs. The ROI size for brain tissue was assigned to capture the optimal structure of the tissues. Please reach out to your local FAS for best
practices regarding ROI selection.
10 | Application Note | Unravel the Complexity of Mouse Brain Tumors
Products Metal Marker Clone Target/Cellular Process Part No.
Maxpar® Neuro Phenotyping
IMC™ Panel Kit (201337)
142Nd Iba1 EPR16588 Microglia 3142020D
143Nd GFAP GA-5 Astrocytes 3143030D
145Nd NeuN EPR12763 Neurons (nuclei) 3145019D
146Nd S100β EP1576Y Glial cells 3146021D
148Nd MAP2 EPR19691 Neurons 3148023D
167Er CD34 EP373Y Vascular cells 3167025D
168Er Olig2 EPR2673 Oligodendrocytes 3168028D
Maxpar
OnDemand
Mouse
ImmunoOncology
IMC Panel
Kit (9100005)
Maxpar OnDemand™
Mouse Tissue
Architecture
IMC Panel Kit
(9100001)
141Pr αSMA 1A4 Smooth muscle/stromal cells 3141017D
171Yb CD31 EPR17259 Vascular cell 91H027171
153Eu CD44 IM7 Tumor cell/immune cells 3153029D
151Eu CD45 D3F8Q Immune cells 91H029151
173Yb Collagen 1 Polyclonal Extracellular matrix 91H018173
152Sm Fibronectin EPR19241-46 Extracellular matrix 91H028152
174Yb Pan-cytokeratin AE-1/AE-3 Cytoskeletal filament 91H006174
Maxpar OnDemand
Mouse Cancer
Cell Process
IMC Panel Kit
(9100002)
154Sm β-actin 2F1-1 Cytoskeletal microfilament 3154021D
169Tm β-catenin 5H10 Ca2+ dependent cell adhesion 91H022169
172Yb BRCA1 MS110 Tumor suppressor 3172030D
158Gd E-cadherin 24E10 Ca2+ dependent cell adhesion 3158029D
147Sm EpCAM EPR20532-222 Ca2+ independent cell adhesion 91H024147
150Nd Ki-67 B56 Proliferating cells 91H017150
164Dy pERK1/2 D13.14.4E Ras signaling activation 91H039164
175Lu pS6[S235/S236] N7-548 mTOR pathway activation 3175031D
144Nd p-tyrosine P-Tyr-100 RTK* activation 3144024D
149Sm Vimentin D21H3 Mesenchymal cells 91H002149
Maxpar OnDemand
Mouse Immune
Phenotyping
IMC Panel Kit
(9100003)
176Yb B220 RA36B2 B cells 91H036176
163Dy CD11b EPR1344 MDSCs†, M1 macrophages 91H007163
170Er CD3 Polyclonal
(C-term)
Pan T cells 3170019D
159Tb CD4 BLR16J T helper cells 91H031159
162Dy CD8 EPR21769 Killer T cells 91H023162
156Gd F4/80 D2S9R Macrophages 91H030156
166Er Ly-6G 1A8 MDSCs, neutrophils 91H037166
161Dy MHC class II M5/114.15.2 Antigen presenting cells 91H038161
Maxpar OnDemand
Mouse Immune
Activation IMC
Panel Kit (9100004)
165Ho FoxP3 FJK-16s Regulatory T cells 91H032165
155Gd Granzyme B EPR22645-206 Cytotoxic immune cell activation 91H026155
160Gd iNOS SP126 Activated macrophages 91H025160
Cell-ID™ Intercalator-Ir‡
191Ir DNA1
DNA 201192A
193Ir DNA2
Maxpar IMC Cell Segmentation Kit‡
195Pt ICSK1
196Pt ICSK2 Cell membrane 201500
198Pt ICSK3
* Receptor tyrosine kinase
† Myeloid-derived suppressor cells
‡ Cell-ID Intercalator-Ir and the Maxpar IMC Cell Segmentation Kit are not part of the Maxpar OnDemand Mouse Neuro-Oncology IMC Bundle.
Table 1. Maxpar OnDemand Mouse Neuro-Oncology IMC Bundle (PN 9100005NO) for FFPE brain tissue application
Unravel the Complexity of Mouse Brain Tumors | Application Note | 11
Required reagents
Standard BioTools™ Part Number
Maxpar® PBS 201058
Cell-ID™ Intercalator-Ir 201192A
Maxpar Water 201069
Maxpar antibodies Multiple
Maxpar OnDemand™ Antibodies Multiple
Maxpar IMC™ Cell Segmentation Kit 201500
Third-Party Reagents Product Name Part Number
Sigma-Aldrich® m-Xylene ReagentPlus® 185566-1L
Commercial Alcohols Anhydrous
ethyl alcohol
P006EAAN
Agilent® Antigen Retrieval
Solution pH 9 (10x)
S236798-2
Thermo Scientific™ Triton™ X-100 85111
Sigma-Aldrich 10% Bovine
Serum Albumin
A3059
Charles River Mouse FFPE tumor Custom order
AMSBIO Mouse FFPE normal
brain tissue
7011-0220-5PK
References
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(2013): 477–484.
5. Biserova, K. et al. “Cancer stem cells: Significance in origin,
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and its impact on cancer therapy.” Frontiers in Molecular
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20 (2020): 26–41.
8. Pacheco, C. et al. “Glioblastoma vasculature: From its critical role
in tumor survival to relevant in vitro modelling.” Frontiers in Drug
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