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 ...

<ol>
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L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+quantitative+assessment+of+PD-L1+using+digital+spatial+profiling.">Digital quantitative assessment of PD-L1 using digital spatial profiling.</a> Laboratory Investigation; A Journal of Technical Methods and Pathology. 100 (10), 1311-1317 (2020).</li><li>Carter, J. 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Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+bulk,+single-cell+to+spatial+RNA+sequencing.">From bulk, single-cell to spatial RNA sequencing.</a> International Journal of Oral Science. 13 (36), (2021).</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. 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Nanostring Available from: <a target="_blank" href="https://nanostring.com/wp-content/uploads/MK2593_GeoMx_Normalization-Protein.pdf">https://nanostring.com/wp-content/uploads/MK2593_GeoMx_Normalization-Protein.pdf</a> (2020)</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+spatial+profiler.">Best practices for spatial profiling for breast cancer research with the geomx spatial profiler.</a> Cancers. 13 (17), 4456 (2021).</li><li>Hwang, W. 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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 ...

This protocol helps to guide the selection of regions of interest for spatial omics technologies, which allows a more targeted characterization of tissues or cell populations. An automated protocol for ROI selection in proteomics assays is more robust and reproducible than manual protocols, and using 50 micrometer ROIs for transcriptomics assays allows profiling of specific cell populations. Start with programming the autostainer to apply fluorescent visualization antibodies.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. Click on First Sequence, then select Deparaffinazation, followed by Depar v2.For Medium Temperature, choose 72 degrees Celsius, then click on Pretreatment and select Cell Conditioning and CC1 Reservoir. For Very High Temperature, choose 100 degrees Celsius, then click on CC1 eight minutes, and continue clicking until CC1 64 minutes is selected. Click on Inhibitor, then select DISCOVERY Inhibitor, and for Incubation Time, choose eight minutes.Then click on Antibody, followed by High-Temp Antibody Incubation. For Low Temperature, choose 37 degrees Celsius. For Antibody, choose the ANTIBODY 6 from the dispenser label.For Plus Incubation Time, select 32 minutes. Click on Multimer HRP, then select Multimer HRP Blocker. Then for Antibody Blocking, choose Gt Ig Block.And for Incubation Time, choose four 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 zero hour, eight minutes.Click on Dual Sequence and choose Antibody Denaturation. Then select Antibody Denature CC2-1, and for a Very High Temperature, choose 100 degrees Celsius. Ensure that incubation time is eight minutes.Next, click on DS Inhibitor and select Neutralize. Click on DS Antibody, and for Very Low Temperature, choose 37 degrees Celsius. Then in Antibody, choose ANTIBODY 3 from the dispenser label.And for Plus Incubation Time, select 32 minutes. Click on DS Multimer HRP and choose DS Multimer HRP Blocker. Then for Antibody Blocking, select Gt Ig Block, and for Incubation Time, choose four 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 zero hour, eight minutes. Click on Triple Stain and select TS Antibody Denaturation, then select Antibody Denature CC2-2, and for Very High Temperature, select 100 degrees Celsius.Ensure that incubation time is eight minutes. Next, click on TS Inhibitor and select TS Neutralize. Click on TS Antibody, and for Very Low Temperature, select 37 degrees Celsius.Then in Antibody, select the ANTIBODY 7 from the dispenser label, and for Plus Incubation Time, select 32 minutes. Click on TS Multimer HRP and choose TS Multimer HRP Blocker. Then for Antibody Blocking, select Gt Ig Block, and for Incubation Time, choose four 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 zero hour, eight minutes. Click on Save and add a title to the protocol.Select a protocol number, add a comment, and click on Active, followed by Save. Bake vendor-procured formalin-fixed paraffin-embedded human tissue sections in an oven set to 70 degrees Celsius for 20 to 60 minutes. 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. Remove slides from the oven and let them cool down to room temperature.Apply the previously printed protocol labels to the corresponding slides. Load refillable antibody dispensers with antibodies according to the antibody label numbers. Dilute each antibody in the specified diluent and prime the refillable antibody dispensers.Gather blocking, detection, and amplification prefilled reagent dispensers and place them on the instrument reagent tray. Load slides in the slide drawers and click on Running, followed by Yes. Confirm the start of the run by checking the run duration on the autostainer software.The next day, ensure run completion by observing green flashing lights on the slide drawer slots. Then take the slides off the instrument and rinse the slides vigorously in 1x reaction buffer until liquid cover slip solution is completely removed. Replace SYTO 13 with SYTO 64 at 5, 000 nanomolar to enable fluorophore integration.Dilute SYTO 64 in 1x TBS and incubate in a humidity chamber for 15 minutes. Use FITC for DISCOVERY Fam and set the exposure to 200 milliseconds. Use Cy3 for DISCOVERY Rhodamine 6G and set the exposure to 200 milliseconds.Use Texas Red for SYTO 64 and set the exposure to 50 milliseconds. Specify SYTO 64 as the focus channel, and finally, use Cy5 for DISCOVERY Cy5. Set the exposure to 200 milliseconds and save changes.Bake formalin-fixed paraffin-embedded cell pellet sections in an oven set to 70 degrees Celsius for 20 to 60 minutes. Scan slides on the spatial profiling platform and select sizes of 50 micrometers and 300 micrometers. The automated visualization protocol was developed by including leave one out controls to confirm that there was no bleed through from the neighboring channels.The log 2 heat map of all the markers included in the spatial proteomics assay comparing the manual pan-cytokeratin CD 45 protocol in black to the automated 3-plex protocol in gray shows a Spearman R value of 0.88. Of the 31 antibodies used in the assays, 23 antibodies had a Spearman R value higher than or equal to 0.5. The log 2 heat map of selected targets included in the spatial transcriptomics assay comparing the manual pan-cytokeratin CD 45 protocol in black to the 3-plex automated protocol in gray showed differences in these values.The sequencing data for the 3-plex automated visualization protocol presented lower values when compared to the pan-cytokeratin CD 45 manual visualization protocol, which is also reflected by the low Spearman R values of 0.15. Also, a loss of dynamic range was observed when using the 3-plex visualization automated protocol. The detection of small ROIs in the spatial transcriptomics protocol was performed by the selection of circular regions of interest at 50 micrometer and 300 micrometer diameter RNA counts for selected targets on different cell lines were comparable between the two regions of interest sizes after normalization.This protocol for automated visualization panels can be adapted by researchers by exchanging markers in order to develop panels that precisely define ROIs to answer their spatial proteomics questions.

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JoVE Journal

Cancer Research

4.7K 조회수.  Genentech. 이 프로토콜은 공간 오믹스 기술에 대한 관심 영역의 선택을 안내하는 데 도움이 되며, 이를 통해 조직 또는 세포 집단의 보다 표적화된 특성을 분석할 수 있습니다. 단백질체학 분석에서 ROI 선택을 위한 자동화된 프로토콜은 수동 프로토콜보다 더 강력하고 재현성이 있으며, 전사체학 분석에 50마이크로미터 ROI를 사용하면 특정 세포 집단의 프로파일링이 가능합니다. 형광 ?...