The authors acknowledge Thomas Wu for processing NGS files. We thank James Ziai for the results discussions and manuscript review and Meredith Triplet and Rachel Taylor for internal manuscript revision.

All human tissues were acquired from commercial biobanks or accredited tissue banks under warranty that appropriate Institutional Review Board approval and informed consent were obtained.
NOTE: The protocol is performed using the Discovery Ultra and the GeoMx Digital Spatial Profiler. See the Table of Materials for details about reagents, equipment, and software used in this protocol.
1. Automated visualization protocol for spatial proteomics assays
<ol>
	<li>Program autostainer to apply fluorescent visualization antibodies
	<ol>
		<li>In the autostainer software, click on the home button and choose Protocols. Then, click on Create/Edit Protocols and select RUO DISCOVERY Universal as the procedure.</li>
		<li>Click on First Sequence &#62; Deparaffinization &#62; Depar v2. For Medium Temperature, choose 72 Deg C, then click on Pretreatment and select Cell Conditioning and CC1 Reservoir. For Very High Temperature, choose 100 Deg C, then click on CC1 8 Min and continue clicking until CC1 64 Min is selected.</li>
		<li>Click on Inhibitor &#62; DISCOVERY Inhibitor, and for Incubation Time, choose 8 Minutes. Then, click on Antibody &#62; High Temp Ab Incubation; for Low Temperature, choose 37 Deg C; for Antibody, choose the antibody number from the dispenser label (Antibody 6 in this example); for Plus Incubation Time, select 32 Minutes. 
		NOTE: This protocol has three different antibody numbers. The first antibody is FAP, the second is Pan-Cytokeratin, and the third is Antibody X.</li>
		<li>Click on Multimer HRP &#62; Multimer HRP Blocker, then for Antibody Blocking, choose Gt Ig Block, and for Incubation Time, choose 4 Minutes. Next, on Multimer HRP Reagent, select OMap anti-Rb HRP, and for Incubation Time, choose 16 Minutes. Then, click on Cy5, and for Long Incubation Time, choose 0 Hr 8 Min.</li>
		<li>Click on Dual Sequence and choose Antibody Denaturation, then select Antibody Denature CC2-1, and for Very High Temperature, choose 100 Deg C. Ensure that incubation time is 8 min. Next, click on DS Inhibitor and select Neutralize.</li>
		<li>Click on DS Antibody, and for Very Low Temperature, choose 37 Deg C. Then, in Antibody, choose the antibody number from the dispenser label (Antibody 3 in this example), and for Plus Incubation Time, select 32 Minutes.</li>
		<li>Click on DS Multimer HRP and choose DS Multimer HRP Blocker. Then, for Antibody Blocking, select Gt Ig Block, and for Incubation Time, choose 4 Minutes. Next, on Multimer HRP Reagent, select OMap anti-Ms HRP, and for Incubation Time, choose 16 Minutes. Then, click on DS Rhodamine 6G, and for Long Incubation Time, choose 0 Hr 8 Min.</li>
		<li>Click on Triple Stain and select TS Antibody Denaturation, then select Antibody Denature CC2-2, and for Very High Temperature, select 100 Deg C. Ensure that incubation time is 8 min. Next, click on TS Inhibitor and select TS Neutralize.</li>
		<li>Click on TS Antibody, and for Very Low Temperature, select 37 Deg C. Then, in Antibody, select the antibody number from the dispenser label (Antibody 7 in this example), and for Plus Incubation Time, select 32 Minutes.</li>
		<li>Click on TS Multimer HRP and choose TS Multimer HRP Blocker. Then, for Antibody Blocking, select Gt Ig Block, and for Incubation Time, choose 4 Minutes. Next, on Multimer HRP Reagent, select OMap anti-Rb HRP, and for Incubation Time, choose 16 Minutes. Then, click on TS FAM, and for Long Incubation Time, choose 0 Hr 8 Min.</li>
		<li>Add a title to the protocol. Select a protocol number, add a comment, and click on Active followed by Save.</li>
	</ol>
	</li>
	<li>Prepare slides, print labels, and start the autostainer run
	<ol>
		<li>Bake vendor procured FFPE (Formalin-fixed, paraffin-embedded) human tissue sections in an oven set to 70 &#176;C for 20-60 min. While slides are baking, print labels by clicking Create Label in the autostainer software. Next, click on Protocols, select the protocol number, and click on Close/Print. Add relevant information on the slide label and click on Print.</li>
		<li>Remove slides from the oven and let them cool down to room temperature (RT). Apply the previously printed protocol labels to the corresponding slides.</li>
		<li>Load refillable antibody dispensers with antibodies according to the antibody label number assigned in step 1.1. In this protocol, use Antibody 6 for FAP at 1 &#181;g/mL, use Antibody 3 for Pan-Cytokeratin at 0.1 &#181;g/mL, and use Antibody 7 for Antibody X at 2.5 &#181;g/mL. Dilute each antibody in the specified diluent and prime the refillable antibody dispensers.</li>
		<li>Gather blocking, detection, and amplification pre-filled reagent dispensers mentioned above and place them on a reagent tray. Load slides in the slide trays (up to 30 slides per run) and click on Running followed by Yes. Note that DAPI is not used for nuclear counterstaining.</li>
		<li>Confirm the start of the run by checking the run duration on the autostainer software. The protocol takes ~11 h for completion and can run overnight.</li>
		<li>The next day, ensure run completion by observing green flashing lights on the slide tray slots. Then, take the slides off the instrument and rinse the slides vigorously in 1x Reaction Buffer until the liquid coverslip solution is completely removed.</li>
	</ol>
	</li>
	<li>Spatial profiling platform protocol for proteomics assay
	<ol>
		<li>Follow the spatial proteomics protocol indicated in the note below. Include the following changes to the protocol to enable the 3-plex automated labeling procedure.</li>
		<li>Perform steps 1.2.1-1.2.6&#160;the day before starting the spatial proteomics protocol and move straight to the antigen retrieval step of the spatial proteomics protocol after performing step 1.2.6. Omit the visualization procedure outlined in the spatial profiling proteomics protocol.</li>
		<li>Replace SYTO 13 with SYTO 64 at 5000 nM to enable fluorophore integration. Dilute SYTO 64 in 1x TBS and incubate in a humidity chamber for 15 min.</li>
		<li>When setting up the scan parameters in the spatial profiling platform, select the filters and focusing channels according to the fluorophores used in the visualization panel to allow 3-plex integration. Use FITC for DISCOVERY FAM and set the exposure to 200 ms, use Cy3 for DISCOVERY Rhodamine 6G and set the exposure to 200 ms, use Texas Red for SYTO 64 and set the exposure to 50 ms (specify this as the focus channel), and finally, use Cy5 for DISCOVERY Cy5, set the exposure to 200 ms, and save changes. 
		NOTE: Detailed instructions of the spatial profiling proteomics protocol are found on the official website Support tab by selecting Documentation &#62; User Manuals. Here, look for the protein protocol for nCounter using Bond RX.</li>
	</ol>
	</li>
</ol>
2. ROI selection for spatial transcriptomics assays
<ol>
	<li>Bake FFPE cell pellet sections in an oven set to 70 &#176;C for 20-60 min. Follow the spatial profiling platform NGS protocol indicated in the note below and scan slides on the spatial profiling platform, selecting sizes of 50 &#181;m and 300 &#181;m. The following recommendation is highlighted for the spatial transcriptomics assay:
	<ol>
		<li>When preparing the library, if various sizes of ROIs were selected, pool together ROIs of similar sizes to make one library per size. This is to ensure that sufficient sequencing depths are achieved for all ROIs without bias from size. 
		NOTE: Detailed instructions of the spatial profiling platform are found on the official website Support tab by selecting Documentation &#62; User Manuals. Here, look for the RNA protocol for NGS applications using Bond RX.</li>
	</ol>
	</li>
</ol>

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Veronica Ibarra-Lopez, Sangeeta Jayakar, Yeqing Angela Yang, Zora Modrusan, and Sandra Rost&#160;are employees and stockholders of Genentech, a member of the Roche Group. Other companies that are part of Roche produce reagents and instruments used in this manuscript. Ciara Martin is a full-time employee of NanoString Technologies Inc, which produces reagents and instruments used in this manuscript.

To date, directly conjugated fluorescent antibodies in a manual protocol are most commonly used as visualization panels for spatial proteomics or spatial transcriptomics assays9,10. However, the use of directly conjugated fluorescent antibodies can be challenging for less abundant markers, limiting the selection of suitable antibodies. This protocol shows that labeling of visualization markers can be automated on an automated staining platform using TSA technolog...

Advances in multiplexing techniques continue to provide better characterization tools for targets present in tumors. The tumor microenvironment (TME) is a complex system of tumor cells, infiltrating immune cells, and stroma, where spatial information is critical to better understand and interpret mechanisms of interaction between biomarkers of interest1. With emerging techniques such as the GeoMx Digital Spatial Profiler (DSP) and 10x Visium, multiple targets can be detected and quantified simultaneously within their spatial context. The use of immunofluorescence protocols that facilitate tissue visualization can further improve the spatial profiling capabilities of these technologies.
The Spatial Omics technology we focused on for this method development consists of spatial proteomics and transcriptomics assays where oligonucleotides are attached to antibodies or RNA probes via a UV-sensitive photocleavable linker. Histological slides are labeled with these oligo-conjugated antibodies or probes and then imaged on the spatial profiling platform. Next, ROIs of different sizes and shapes are selected for illumination, and the photocleaved oligonucleotides are aspirated and collected in a 96-well plate. The photocleaved oligonucleotides are prepared to be quantified with either the Nanostring nCounter system or Next Generation Sequencing (NGS)2,3 (Figure 1)4,5.
Cell distributions vary within tissues, and the ability to characterize specific locations of cells using selected markers and different ROI sizes is of great importance to fully understand the tissue environment and identify specific features. In the Spatial Omics technology mentioned here, the standard visualization protocol uses directly conjugated antibodies and is a manual protocol. The standard markers to distinguish between tumor and stroma are panCytokeratin (panCK) and CD456,7, but additional markers are necessary to target specific cell populations of interest. Furthermore, the use of directly conjugated fluorescent antibodies lacks amplification, which limits antibody selection to abundant markers. Additionally, manual assays are subject to more variability than automated workflows8. Therefore, it is desirable to have a customizable, automated, and amplified visualization protocol for ROI selection.
Here, the study demonstrates that, for spatial proteomics assays, TSA technology can be used for visualization protocols on an automated platform resulting in a more targeted and standardized assay. In addition, TSA based assays enable the use of low-expressing markers, increasing the range of targets that can be selected for visualization. A 3-plex assay for panCK, FAP, and Antibody X was developed using an automated platform where panCK and FAP were used to differentiate between tumor and stroma, respectively. Antibody X is a stromal protein frequently encountered in tumors, but its biology and impact on anti-tumor immunity are not fully understood. Characterizing the immune contexture in areas rich in Antibody X can elucidate its role in anti-tumor immunity and therapeutic response, as well as its potential as a drug target.
While customized automated TSA visualization panels proved to be successful for spatial proteomics assays, the application of these assays for spatial transcriptomics assays could not be confirmed. This is most likely due to the reagents and the protocol used for the automated visualization protocols, which seem to compromise RNA integrity. Recognizing that an automated labeling protocol for visualization markers can be used for spatial proteomics assays but not for spatial transcriptomics assays provides important guidance on Spatial Omics technology assay designs.
Additionally, the study demonstrates that the spatial transcriptomics assay can be used to profile targets in regions as small as 50 &#181;m in diameter, or approximately 15 cells. Two different-sized ROIs were selected to test the ability of the assay to also detect transcripts in small ROIs. For each region of interest, oligos corresponding to 1,800 mRNA targets were collected and made into libraries according to the spatial profiling platform protocol. Libraries were individually indexed, subsequently pooled, and sequenced. This allowed the evaluation of both pooling efficiency and the capability of identifying specific cell populations in small ROIs.
This paper shows that for spatial proteomics assays, an automated protocol to guide ROI selection on specific markers of interest can be used to selectively target the interrogation of relevant tissue areas and characterize the spatial environment of the tissue. Furthermore, we demonstrate that smaller ROIs can be used for spatial transcriptomic assays to detect and characterize specific cell populations.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>10x Tris buffered saline (TBS)</td>
			<td>Cell Signaling Technologies</td>
			<td>12498S</td>
			<td>Diluted to 1x TBS in DEPC treated water</td>
		</tr>
		<tr>
			<td>Antibody X (not disclosed)</td>
			<td></td>
			<td></td>
			<td>antibody blinded due to confidentiality</td>
		</tr>
		<tr>
			<td>DEPC-treated water</td>
			<td>ThermoFisher</td>
			<td>AM9922</td>
			<td>Another can be used</td>
		</tr>
		<tr>
			<td>DISCOVERY Cell Conditioning ( CC1)</td>
			<td>Ventana</td>
			<td>950-500</td>
			<td></td>
		</tr>
		<tr>
			<td>DISCOVERY Cy5 Kit</td>
			<td>Ventana</td>
			<td>760-238</td>
			<td>Referred as Cy5</td>
		</tr>
		<tr>
			<td>DISCOVERY FAM Kit</td>
			<td>Ventana</td>
			<td>760-243</td>
			<td>Referred as FAM</td>
		</tr>
		<tr>
			<td>DISCOVERY Goat Ig Block</td>
			<td>Ventana</td>
			<td>760-6008</td>
			<td>Referred as Gt Ig Block</td>
		</tr>
		<tr>
			<td>DISCOVERY OmniMap anti-Ms HRP</td>
			<td>Ventana</td>
			<td>760-4310</td>
			<td>Referred as OMap anti-Ms HRP</td>
		</tr>
		<tr>
			<td>DISCOVERY OmniMap anti-Rb HRP</td>
			<td>Ventana</td>
			<td>760-4311</td>
			<td>Referred as OMap anti-Rb HRP</td>
		</tr>
		<tr>
			<td>DISCOVERY Rhodamine 6G Kit</td>
			<td>Ventana</td>
			<td>760-244</td>
			<td>Referred as Rhodamine 6G</td>
		</tr>
		<tr>
			<td>DISCOVERY ULTRA Automated Slide Preparation System</td>
			<td>Ventana</td>
			<td>05 987 750 001 / N750-DISU-FS</td>
			<td>Referred as autostainer on the manuscript</td>
		</tr>
		<tr>
			<td>FAP [EPR20021] Antibody</td>
			<td>Abcam</td>
			<td>Ab207178</td>
			<td></td>
		</tr>
		<tr>
			<td>GeoMx Digital Spatial Profiler</td>
			<td>NanoString</td>
			<td>GMX-DSP-1Y</td>
			<td>Referred as spatial profiling platform on the manuscript</td>
		</tr>
		<tr>
			<td>Humidity chamber</td>
			<td>Simport</td>
			<td>M920-2</td>
			<td>Another can be used</td>
		</tr>
		<tr>
			<td>Pan-Cytokeratin [AE1/AE3] Antibody</td>
			<td>Abcam</td>
			<td>Ab27988</td>
			<td></td>
		</tr>
		<tr>
			<td>ProLong Gold Antifade Mountant</td>
			<td>ThermoFisher</td>
			<td>P36934</td>
			<td></td>
		</tr>
		<tr>
			<td>Python</td>
			<td>Python</td>
			<td></td>
			<td>Statistical analysis</td>
		</tr>
		<tr>
			<td>Reaction Buffer (10x)</td>
			<td>Ventana</td>
			<td>950-300</td>
			<td></td>
		</tr>
		<tr>
			<td>Statistical analysis software</td>
			<td>GraphPad</td>
			<td>Prism 7</td>
			<td>Statistical analysis</td>
		</tr>
		<tr>
			<td>SYTO 64</td>
			<td>ThermoFisher</td>
			<td>S11346</td>
			<td></td>
		</tr>
		<tr>
			<td>ULTRA Cell Conditioning (ULTRA CC2)</td>
			<td>Ventana</td>
			<td>950-223</td>
			<td></td>
		</tr>
		<tr>
			<td>Ventana Antibody Diluent with Casein</td>
			<td>Ventana</td>
			<td>760-219</td>
			<td>Referred as specified diluent on the manuscript</td>
		</tr>
		<tr>
			<td>Ventana Primary antibody dispenser</td>
			<td>Ventana</td>
			<td></td>
			<td>Catalog number depends on dispenser number</td>
		</tr>
	</tbody>
</table>

spatial profiling of protein and rna expression in tissue: an approach to fine-tune virtual microdissection

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein and RNA multiplexing by leveraging photo-cleavable oligo-tagged antibodies and probes, respectively. Oligos are cleaved and quantified from specific regions across the tissue to elucidate the underlying biology. Here, the study demonstrates that automated custom antibody visualization protocols can be utilized to guide ROI selection in conjunction with spatial proteomics assays. This specific method did not show acceptable performance with spatial transcriptomics assays. The protocol describes the development of a 3-plex immunofluorescent (IF) assay for marker visualization on an automated platform, using tyramide signal amplification (TSA) to amplify the fluorescent signal from a given protein target and increase the antibody pool to choose from. The visualization protocol was automated using a thoroughly validated 3-plex assay to ensure quality and reproducibility. In addition, the exchange of DAPI for SYTO dyes was evaluated to allow imaging of TSA-based IF assays on the spatial profiling platform. Additionally, we tested the ability of selecting small ROIs using the spatial transcriptomics assay to allow the investigation of highly-specific areas of interest (e.g., areas enriched for a given cell type). ROIs of 50 &#181;m and 300 &#181;m diameter were collected, which corresponds to approximately 15 cells and 100 cells, respectively. Samples were made into libraries and sequenced to investigate the capability to detect signals from small ROIs and profile-specific regions of the tissue. We determined that spatial proteomics technologies highly benefit from automated, standardized protocols to guide ROI selection. While this automated visualization protocol was not compatible with spatial transcriptomics assays, we were able to test and confirm that specific cell populations can successfully be detected even in small ROIs with the standard manual visualization protocol.

Automated visualization protocol to guide ROI selection 
In this paper, we present the use of an automated, custom TSA-based IF protocol to visualize the tissue and select specific ROIs. Visualization panel development using melanoma and human normal skin as control tissues consisted of epitope stability testing, fine-tuning of marker intensities, and bleedthrough assessment through leave one out controls. To test if epitope stability of the antibodies is affected by repetitive elution steps, FAP an...

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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Here, we describe a protocol for fine-tuning regions of interest (ROIs) for Spatial Omics technologies to better characterize the tumor microenvironment and identify specific cell populations. For proteomics assays, automated customized protocols can guide ROI selection, while transcriptomics assays can be fine-tuned utilizing ROIs as small as 50 &#181;m.

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein ...

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Cancer Research

4.8K Views.  Genentech. Here, we describe a protocol for fine-tuning regions of interest (ROIs) for Spatial Omics technologies to better characterize the tumor microenvironment and identify specific cell populations. For proteomics assays, automated customized protocols can guide ROI selection, while transcriptomics assays can be fine-tuned utilizing ROIs as small as 50 µm. 

Video: Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

Drosophila melanogaster has emerged as a powerful experimental system for functional and mechanistic studies of tumor development and progression in the context of a whole organism. Sophisticated techniques to generate genetic mosaics facilitate induction of visually marked, genetically defined clones surrounded by normal tissue. The clones can be analyzed through diverse molecular, cellular and omics approaches. This study describes how to generate fluorescently labeled clonal tumors of varying malignancy in the eye/antennal imaginal discs (EAD) of Drosophila larvae using the Mosaic Analysis with a Repressible Cell Marker (MARCM) technique. It describes procedures how to recover the mosaic EAD and brain from the larvae and how to process them for simultaneous imaging of fluorescent transgenic reporters and antibody staining. To facilitate molecular characterization of the mosaic tissue, we describe a protocol for isolation of total RNA from the EAD. The dissection procedure is suitable to recover EAD and brains from any larval stage. The fixation and staining protocol for imaginal discs works with a number of transgenic reporters and antibodies that recognize Drosophila proteins. The protocol for RNA isolation can be applied to various larval organs, whole larvae, and adult flies. Total RNA can be used for profiling of gene expression changes using candidate or genome-wide approaches. Finally, we detail a method for quantifying invasiveness of the clonal tumors. Although this method has limited use, its underlying concept is broadly applicable to other quantitative studies where cognitive bias must be avoided.

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

This protocol demonstrates how to generate fluorescently marked, genetically defined clonal tumors in the Drosophila eye/antennal imaginal discs (EAD). It describes how to dissect the EAD and brain from the third instar larvae and how to process them to visualize and quantify gene expression changes and tumor invasiveness.

Drosophila melanogaster has emerged as a powerful experimental system for functional and mechanistic studies of tumor development and progression in the ...

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Drug resistance remains a major problem in the treatment of cancer for both hematological malignancies and solid tumors. Intrinsic or acquired resistance can be caused by a range of mechanisms, including increased drug elimination, decreased drug uptake, drug inactivation and alterations of drug targets. Recent data showed that other than by well-known genetic (mutation, amplification) and epigenetic (DNA hypermethylation, histone post-translational modification) modifications, drug resistance mechanisms might also be regulated by splicing aberrations. This is a rapidly growing field of investigation that deserves future attention in order to plan more effective therapeutic approaches. The protocol described in this paper is aimed at investigating the impact of aberrant splicing on drug resistance in solid tumors and hematological malignancies. To this goal, we analyzed the transcriptomic profiles of several in vitro models through RNA-seq and established a qRT-PCR based method to validate candidate genes. In particular, we evaluated the differential splicing of DDX5 and PKM transcripts. The aberrant splicing detected by the computational tool MATS was validated in leukemic cells, showing that different DDX5 splice variants are expressed in the parental vs. resistant cells. In these cells, we also observed a higher PKM2/PKM1 ratio, which was not detected in the Panc-1 gemcitabine-resistant counterpart compared to parental Panc-1 cells, suggesting a different mechanism of drug-resistance induced by gemcitabine exposure.

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Here we describe a protocol aimed at investigating the impact of aberrant splicing on drug resistance in solid tumors and hematological malignancies. To this goal, we analyzed the transcriptomic profiles of parental and resistant in vitro models through RNA-seq and established a qRT-PCR based method to validate candidate genes.

Drug resistance remains a major problem in the treatment of cancer for both hematological malignancies and solid tumors. Intrinsic or acquired resistance ...

Determination of Protein Expression Level in Cultured Cells by Immunocytochemistry on Paraffin-embedded Cell Blocks

Immunofluorescent staining is currently the method of choice for determination of protein expression levels in cell-culture systems when morphological information is also necessary. The protocol of immunocytochemical staining on paraffin-embedded cell blocks, presented herein, is an excellent alternative to immunofluorescent staining on non-paraffin-embedded fixed cells. In this protocol, a paraffin cell block from HeLa cells was prepared using the thromboplastin-plasma method, and immunocytochemistry was performed for the evaluation of two proliferation markers, CKAP2 and Ki-67. The nuclei and cytoplasmic morphology of the HeLa cells were well preserved in the cell-block slides. At the same time, the CKAP2 and Ki-67 staining patterns in the immunocytochemistry were quite similar to those in immunohistochemical staining in paraffin cancer tissues. With modified cell-culture conditions, including pre-incubation of HeLa cells under serum-free conditions, the effect could be evaluated while preserving architectural information. In conclusion, immunocytochemistry on paraffin-embedded cell blocks is an excellent alternative to immunofluorescent staining.

Currently, immunofluorescent staining on fixed cells is the method of choice for determination of protein expression levels when morphological information is also necessary. This protocol presented herein provides for an alternative method of immunocytochemistry on paraffin-embedded cell blocks.

Immunofluorescent staining is currently the method of choice for determination of protein expression levels in cell-culture systems when morphological ...

Spatial and Temporal Control of Murine Melanoma Initiation from Mutant Melanocyte Stem Cells

Cutaneous melanoma is well known as the most aggressive skin cancer. Although the risk factors and major genetic alterations continue to be documented with increasing depth, the incidence rate of cutaneous melanoma has shown a rapid and continuous increase during recent decades. In order to find effective preventative methods, it is important to understand the early steps of melanoma initiation in the skin. Previous data has demonstrated that follicular melanocyte stem cells (MCSCs) in the adult skin tissues can act as melanoma cells of origin when expressing oncogenic mutations and genetic alterations. Tumorigenesis arising from melanoma-prone MCSCs can be induced when MCSCs transition from a quiescent to active state. This transition in melanoma-prone MCSCs can be promoted by the modulation of either hair follicle stem cells&#39; activity state or through extrinsic environmental factors such as ultraviolet-B (UV-B). These factors can be artificially manipulated in the laboratory by chemical depilation, which causes transition of hair follicle stem cells and MCSCs from a quiescent to active state, and by UV-B exposure using a benchtop light. These methods provide successful spatial and temporal control of cutaneous melanoma initiation in the murine dorsal skin. Therefore, these in vivo model systems will be valuable to define the early steps of cutaneous melanoma initiation and could be used to test potential methods for tumor prevention.

The following procedure describes a method for spatial and temporal control of melanocytic tumor initiation in murine dorsal skin, using a genetically engineered mouse model. This protocol describes macroscopic as well as microscopic cutaneous melanoma initiation.

Cutaneous melanoma is well known as the most aggressive skin cancer. Although the risk factors and major genetic alterations continue to be documented ...

In Vitro Assay to Study Tumor-macrophage Interaction

Tumor associated macrophages (TAMs) account for a large percentage of cells in the tumor mass for different types of cancers. Glioblastoma (GBM), a malignant brain tumor with no cure, has up to a half the tumor mass TAMs. TAMs can be pro-tumoral or anti-tumoral, depending on the activation of specific genes in the cells. Genetic mutations in the tumors, through regulating cytokine expression, can affect recruitment of TAMs to the tumor microenvironment. Here, we describe a quantitative cell-based assay to assess macrophage recruitment by the conditioned medium from the tumor cells. This assay uses the human macrophage cell line MV-4-11 to study macrophage attraction by the conditioned medium from glioblastoma, allowing for high reproducibility and low variability. Data generated with this assay can contribute to a better understanding of the interaction between the tumor and the tumor microenvironment. Similar assay can be used to assess interaction between the tumor cells and other immune cells, including T cells and natural killer (NK) cells.

This article represents a useful in vitro assay to evaluate the capability of conditioned medium from tumor cells to attract macrophages.

Tumor associated macrophages (TAMs) account for a large percentage of cells in the tumor mass for different types of cancers. Glioblastoma (GBM), a ...

High-Throughput Cellular Profiling of Targeted Protein Degradation Compounds Using HiBiT CRISPR Cell Lines

Targeted protein degradation compounds, including molecular glues or proteolysis targeting chimeras, are an exciting new therapeutic modality in small molecule drug discovery. This class of compounds induces protein degradation by bringing into proximity the target protein and the E3 ligase machinery proteins required to ubiquitinate and ultimately degrade the target protein through the ubiquitin-proteasomal pathway (UPP). Profiling of target protein degradation in a high-throughput fashion, however, remains highly challenging given the complexity of cellular pathways required to achieve degradation. Here we present a protocol and screening strategy based on the use of CRISPR/Cas9 endogenous tagging of target proteins with the 11 amino acid HiBiT tag which complements with high affinity to the LgBiT protein, to produce a luminescent protein. These CRISPR targeted cell lines with endogenous tags can be used to measure compound induced degradation in either real-time, kinetic live cell or endpoint lytic modes by monitoring luminescent signal using a luminescent plate-based reader. Here we outline the recommended screening protocols for the different formats, and&#160;also describe the calculation of key degradation parameters of rate, Dmax, DC50, Dmax50, as well as multiplexing with cell viability assays. These approaches enable rapid discovery and triaging of early stage compounds while maintaining endogenous expression and regulation of target proteins in relevant cellular backgrounds, allowing for efficient optimization of lead therapeutic compounds.

This protocol describes the quantitative luminescent detection of protein degradation kinetics in living cells that have been engineered using CRISPR/Cas9 to express antibody free endogenous protein detection tag fused to a target protein. Detailed instructions for calculating and obtaining quantitative degradation parameters, rate, Dmax, DC50, and Dmax50 are included.

Targeted protein degradation compounds, including molecular glues or proteolysis targeting chimeras, are an exciting new therapeutic modality in small ...

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

RNA sequencing (RNA-seq) is one of the most widely used technologies in transcriptomics as it can reveal the relationship between the genetic alteration and complex biological processes and has great value in diagnostics, prognostics, and therapeutics of tumors. Differential analysis of RNA-seq data is crucial to identify aberrant transcriptions, and limma, EdgeR and DESeq2 are efficient tools for differential analysis. However, RNA-seq differential analysis requires certain skills with R language and the ability to choose an appropriate method, which is lacking in the curriculum of medical education.
Herein, we provide the detailed protocol to identify differentially expressed genes (DEGs) between cholangiocarcinoma (CHOL) and normal tissues through limma, DESeq2 and EdgeR, respectively, and the results are shown in volcano plots and Venn diagrams. The three protocols of limma, DESeq2 and EdgeR are similar but have different steps among the processes of the analysis. For example, a linear model is used for statistics in limma, while the negative binomial distribution is used in edgeR and DESeq2. Additionally, the normalized RNA-seq count data is necessary for EdgeR and limma but is not necessary for DESeq2.
Here, we provide a detailed protocol for three differential analysis methods: limma, EdgeR and DESeq2. The results of the three methods are partly overlapping. All three methods have their own advantages, and the choice of method only depends on the data.

A detailed protocol of differential expression analysis methods for RNA sequencing was provided: limma, EdgeR, DESeq2.

RNA sequencing (RNA-seq) is one of the most widely used technologies in transcriptomics as it can reveal the relationship between the genetic alteration ...

Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids

Novel 3D cancer organoid cultures derived from clinical patient specimens represent an important model system to evaluate intratumor heterogeneity and treatment response to targeted inhibitors in cancer. Pioneering work in gastrointestinal and pancreatic cancers has highlighted the promise of patient-derived organoids (PDOs) as a patient-proximate culture system, with an increasing number of models emerging. Similarly, work in other cancer types has focused on establishing organoid models and optimizing culture protocols. Notably, 3D cancer organoid models maintain the genetic complexity of original tumor specimens and thus translate tumor-derived sequencing data into treatment with genetically informed targeted therapies in an experimental setting. Further, PDOs might foster the evaluation of rational combination treatments to overcome resistance-associated adaptation of tumors in the future. The latter focuses on intense research efforts in non-small-cell lung cancer (NSCLC), as resistance development ultimately limits the treatment success of targeted inhibitors. An early assessment of therapeutically targetable mechanisms using NSCLC PDOs could help inform rational combination treatments. This manuscript describes a standardized protocol for the cell culture plate-based assessment of drug sensitivities to targeted inhibitors in NSCLC-derived 3D PDOs, with potential adaptability to combinational treatments and other treatment modalities.

This protocol describes a standardized evaluation of drug sensitivities to targeted signaling inhibitors in NSCLC patient-derived organoid models.

Novel 3D cancer organoid cultures derived from clinical patient specimens represent an important model system to evaluate intratumor heterogeneity and ...

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 ...

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is an effective methodology for tumor evaluation that improves the understanding of the tumor microenvironment. The visualization of protein expression in formalin-fixed, paraffin-embedded&#160;tissues is achieved when a specific fluorophore is annealed to an antibody-bound barcode via complementary oligonucleotides and then sample imaging is performed; indeed, this method allows for the use of customizable panels of more than 40 antibodies in a single tissue staining reaction. This method is compatible with fresh frozen tissue, formalin-fixed, paraffin-embedded tissue, cultured cells, and peripheral blood mononuclear cells, meaning that researchers can use this technology to view a variety of sample types at single-cell resolution. This method starts with a manual staining and fixing protocol, and all the antibody barcodes are applied using an antibody cocktail. The staining fluidics instrument is fully automated and performs iterative cycles of labeling, imaging, and removing spectrally distinct fluorophores until all the biomarkers have been imaged using a standard fluorescence microscope. The images are then collected and compiled across all the imaging cycles to achieve single-cell resolution for all the markers. The single-step staining and gentle fluorophore removal not only allow for highly multiplexed biomarker analysis but also preserve the sample for additional downstream analysis if desired (e.g., hematoxylin and eosin staining). Furthermore, the image analysis software enables image processing-drift compensation, background subtraction, cell segmentation, and clustering-as well as the visualization and analysis of the images and cell phenotypes for the generation of spatial network maps. In summary, this technology employs a computerized microfluidics system and fluorescence microscope to iteratively hybridize, image, and strip fluorescently labeled DNA probes that are complementary to tissue-bound, oligonucleotide-conjugated antibodies.

Multiplexed barcoding image analysis has recently improved the characterization of the tumor microenvironment, permitting comprehensive studies of cell composition, functional state, and cell-cell interactions. Herein, we describe a staining and imaging protocol using the barcoding of oligonucleotide-conjugated antibodies and cycle imaging, which allows for the use of a high-dimensional image&#160;analysis technique.

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is ...