The authors would like to thank Carmina Espiritu and Robin E. Taylor for their support in automated dissection development as well as the Genentech Pathology Core Laboratory staff that supported this work.

Prior to initiation, obtain appropriate tissue specimens according to Institutional Review Board (IRB) protocols. All methods described here have been approved by the Institutional Animal Care and Use Committee (IACUC) of Genentech, Inc.
1. Tissue and slide preparation
<ol>
	<li>Select FFPE or fresh frozen tissue blocks and utilize the corresponding processing method below.</li>
	<li>Cut tissue block sections onto positively charged glass slides at the desired thickness. Serially section the FFPE tissue in ribbons with the first reference section cut at a thickness appropriate for H&#38;E staining (i.e., 4 &#181;m) followed by 1-4 sections at a thickness ranging from 4-20 &#181;m based on the need and tissue availability. Collect the tissue sections onto positively charged glass microscope slides. 
	NOTE: Fresh frozen reference tissue sections should be stained immediately with Hematoxylin and Eosin (H&#38;E) using routine protocols for frozen sections and the unstained frozen sections held at -20 &#176;C until they are needed for harvest.</li>
	<li>Allow all the FFPE sections to dry at room temperature overnight.</li>
	<li>Bake the FFPE reference slides at 60 &#176;C for 30 min and then stain with H&#38;E using routine protocols.</li>
	<li>Scan the H&#38;E stained slides on a whole slide imager at 20x magnification or greater.</li>
	<li>Annotate the scanned slide images for tumor regions of interest using a vendor provided viewing platform or open-source viewer. Export these annotations as either a low-magnification screenshot or save them as a metadata file containing X-Y pixel coordinates corresponding to polygon vertices. 
	NOTE: The former is less technically challenging to work with, but the latter offers advantages in process automation.</li>
	<li>Create digital masks of the annotated regions of interest in line with the approach used and export the manual annotations. 
	&#8203;NOTE: If a screenshot/image of the annotations is used, simple image processing software can be used to select a region and to fill in the entire selection. Using X-Y coordinates for each ROI requires the use of a programming language to read both the image data and polygon coordinates to create a low-mag image with filled in regions of interest. The user should work with the automated dissection instrument vendor to establish a process based on their individual software availability and needs. If scanning, digital slide annotation and/or digital mask creation is unavailable, careful on-slide annotation using a marker can be performed and used in place of a digital mask as a reference image. Pseudocode for digital mask creation has been provided in Supplementary File 1.</li>
</ol>
2. Automated tissue dissection
<ol>
	<li>Place the unstained sample tissue slides onto the stage in the first through fourth slide positions when using digital slide reference. When using on-slide annotation rather than a digital option, place the unstained sample tissue slides onto the stage in the second through fourth slide positions with a reference slide in the first position.</li>
	<li>Create a milling job using the automated tissue dissection software: Job Selection &#62; Create New Job &#62; Case ID&#160;&#62; Name the milling job; go to Thickness &#62; Section Thickness using the up or down arrow tab; then go to Tissue Preparation &#62; Paraffinized or Deparaffinized, Reference Image &#62; From File &#62; Import Image &#62; File to import from the dropdown as the digital reference, if applicable. Select From Stage for on stage slide reference. When fields are complete, scan the stage by selecting the Scan Stage button in the bottom-right corner to capture each sample tissue slide in the first through fourth position.</li>
	<li>Select the tissue area for image capture.
	<ol>
		<li>If using an on-stage reference, drag the box from one corner to the opposite to create a rectangular area over tissue. Select the circular bubble under the rectangular area to capture the stage reference image. If using a digital reference image, overlay the image on the rectangular area selected. Resize and align the digital reference grossly in course zoom to best match the size and position over the sample tissue.</li>
		<li>Copy this rectangle field onto remaining sample tissue slides in the second through fourth slide positions by selecting the copy option in the upper-right corner of the reference image. Align and resize grossly as necessary. 
		NOTE: When using an on-slide reference image rather than a digital mask, select which slide on the stage should be used as the reference.</li>
	</ol>
	</li>
	<li>Align the reference and sample slides
	<ol>
		<li>When the reference image is grossly aligned on tissue sample slides in all slide positions, select the Scan Stage button in the lower-right corner of the screen to move into the fine adjustment step. Select the first stage position and Transform tool icon (the third icon down in the right-hand toolbar) to make fine alignment and zoom adjustments of the reference to best match the sample slide overlay. Use the Reference to Sample sliding bar at the bottom of the screen toggling between reference image and sample image along with the Zoom In and Zoom Out feature to adjust and achieve alignment of each slide position. Replicate this process in the second through fourth sample slide positions.</li>
	</ol>
	</li>
	<li>Select the milling area of region of interest
	<ol>
		<li>Once optimal sample overlay of each of the four slide positions is achieved, draw milling path designations using the Color Picker tool icon (the tenth icon down in the right-hand toolbar) on the colored portion of masked reference image. Select the Extend to Similar&#160;box if multiple slides or areas are annotated for dissection and then select the Get Annotation(s) button in lower right to draw milling paths onto sample slides.&#160;</li>
		<li>Select the milling path in the first slide position. 
		NOTE: When the milling path is selected in the first slide position, it will be copied onto the remaining slide positions and milling tip usage will be calculated. The milling tip usage in the upper-left corner is calculated based on the area covered and the tip size selected. If more than four tips are calculated, a larger tip size can be selected to capture the annotated ROI. Tip size can be selected or changed on the left side of the screen under the Milling Tip arrow and tip usage will be recalculated.</li>
		<li>When the milling path is calculated, collect the annotated ROI with four or less milling tips. Select the Setup Stage button in the lower right of the screen to prompt loading of milling tips from placed collection tubes in their proper designation on stage.</li>
	</ol>
	</li>
	<li>Fill the reservoir with 3.0 mL of the dissection buffer most appropriate for the tissue type (FFPE or fresh frozen) and downstream nucleic acid extraction kit needs and select the Dissect button in the lower-right corner of the screen. Use molecular grade mineral oil or an appropriate buffer from commercially available nucleic acid extraction kits. 
	NOTE: Automated dissection of slides and selected regions of interest then begins and samples are collected by the instrument. The unit head will pick up milling tips from the back of the stage and fill with dissection fluid from the reservoir. Tips then spin along the milling path aspirating sample tissue from slides until complete or full. The collected sample with dissection fluid is then dispensed into collection tubes located at the back of the stage.</li>
	<li>When automated dissection is complete, remove the collection tubes and the dissected sample slides from the stage and place them in a tube rack and slide rack, respectively. 
	NOTE: Fresh frozen harvests should be taken directly into nucleic acid extraction as per the manufacturer&#39;s instructions and post-dissection fresh frozen sections should be H&#38;E stained immediately using routine protocols for frozen sections.</li>
	<li>Bake the post dissected tissue slides at 60 &#176;C for 30 min and then stain with H&#38;E using routine protocols.</li>
	<li>Scan the post dissected H&#38;E stained slides on a whole slide imager at 20x magnification and/or archive for a reference of what tissue was not collected and remains on the slide. 
	&#8203;NOTE: See step 1.5 above for alternative scanning options.</li>
</ol>
3. Nucleic acid extraction
<ol>
	<li>Pool and pellet the tissue. Perform the nucleic acid extraction using a commercially available kit and following the manufacturer&#39;s instructions.</li>
</ol>

<ol><li>Cho, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tissue+recommendations+for+precision+cancer+therapy+using+next+generation+sequencing%3A+a+comprehensive+single+cancer+center%27s+experiences%5BTitle%5D)+AND+%22Oncotarget%22%5BJournal%5D)">Tissue recommendations for precision cancer therapy using next generation sequencing: a comprehensive single cancer center's experiences.</a> Oncotarget. 8 (26), 42478-42486 (2017).</li>
<li>Smits, A. J. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+estimation+of+tumor+cell+percentage+for+molecular+testing+by+pathologists+is+not+accurate%5BTitle%5D)+AND+%22Modern+Pathology%3A+An+Official+Journal+of+the+United+States+and+Canadian+Academy+of+Pathology%2C+Inc%22%5BJournal%5D)">The estimation of tumor cell percentage for molecular testing by pathologists is not accurate.</a> Modern Pathology: An Official Journal of the United States and Canadian Academy of Pathology, Inc. 27 (2), 168-174 (2014).</li>
<li>Poole-Wilson, P. A., Langer, G. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Effect+of+pH+on+ionic+exchange+and+function+in+rat+and+rabbit+myocardium%5BTitle%5D)+AND+%22The+American+Journal+of+Physiology%22%5BJournal%5D)">Effect of pH on ionic exchange and function in rat and rabbit myocardium.</a> The American Journal of Physiology. 229 (3), 570-581 (1975).</li>
<li>Viray, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+prospective%2C+multi-institutional+diagnostic+trial+to+determine+pathologist+accuracy+in+estimation+of+percentage+of+malignant+cells%5BTitle%5D)+AND+%22Archives+of+Pathology+%26+Laboratory+Medicine%22%5BJournal%5D)">A prospective, multi-institutional diagnostic trial to determine pathologist accuracy in estimation of percentage of malignant cells.</a> Archives of Pathology & Laboratory Medicine. 137 (11), 1545-1549 (2013).</li>
<li>El-Serag, H. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Gene+Expression+in+Barrett%27s+Esophagus%3A+Laser+capture+versus+whole+tissue%5BTitle%5D)+AND+%22Scandinavian+Journal+of+Gastroenterology%22%5BJournal%5D)">Gene Expression in Barrett's Esophagus: Laser capture versus whole tissue.</a> Scandinavian Journal of Gastroenterology. 44 (7), 787-795 (2009).</li>
<li>Harrell, J. C., Dye, W. W., Harvell, D. M. E., Sartorius, C. A., Horwitz, K. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Contaminating+cells+alter+gene+signatures+in+whole+organ+versus+laser+capture+microdissected+tumors%3A+a+comparison+of+experimental+breast+cancers+and+their+lymph+node+metastases%5BTitle%5D)+AND+%22Clinical+%26+Experimental+Metastasis%22%5BJournal%5D)">Contaminating cells alter gene signatures in whole organ versus laser capture microdissected tumors: a comparison of experimental breast cancers and their lymph node metastases.</a> Clinical & Experimental Metastasis. 25 (1), 81-88 (2008).</li>
<li>Kim, H. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Distinctions+in+gastric+cancer+gene+expression+signatures+derived+from+laser+capture+microdissection+versus+histologic+macrodissection%5BTitle%5D)+AND+%22BMC+Medical+Genomics%22%5BJournal%5D)">Distinctions in gastric cancer gene expression signatures derived from laser capture microdissection versus histologic macrodissection.</a> BMC Medical Genomics. 4, 48(2011).</li>
<li>Klee, E. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Impact+of+sample+acquisition+and+linear+amplification+on+gene+expression+profiling+of+lung+adenocarcinoma%3A+laser+capture+micro-dissection+cell-sampling+versus+bulk+tissue-sampling%5BTitle%5D)+AND+%22BMC+Medical+Genomics%22%5BJournal%5D)">Impact of sample acquisition and linear amplification on gene expression profiling of lung adenocarcinoma: laser capture micro-dissection cell-sampling versus bulk tissue-sampling.</a> BMC Medical Genomics. 2, 13(2009).</li>
<li>Civita, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Laser+capture+microdissection+and+RNA-seq+analysis%3A+High+sensitivity+approaches+to+explain+histopathological+heterogeneity+in+human+glioblastoma+FFPE+archived+tissues%5BTitle%5D)+AND+%22Frontiers+in+Oncology%22%5BJournal%5D)">Laser capture microdissection and RNA-seq analysis: High sensitivity approaches to explain histopathological heterogeneity in human glioblastoma FFPE archived tissues.</a> Frontiers in Oncology. 9, 482(2019).</li>
<li>Emmert-Buck, M. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Laser+capture+microdissection%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Laser capture microdissection.</a> Science. 274 (5289), 998-1001 (1996).</li>
<li>Bonner, R. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Laser+capture+microdissection%3A+molecular+analysis+of+tissue%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Laser capture microdissection: molecular analysis of tissue.</a> Science. 278 (5342), 1481-1483 (1997).</li>
<li>Hunt, J. L., Finkelstein, S. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Microdissection+techniques+for+molecular+testing+in+surgical+pathology%5BTitle%5D)+AND+%22Archives+of+Pathology+%26+Laboratory+Medicine%22%5BJournal%5D)">Microdissection techniques for molecular testing in surgical pathology.</a> Archives of Pathology & Laboratory Medicine. 128 (12), 1372-1378 (2004).</li>
<li>Espina, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Laser-capture+microdissection%5BTitle%5D)+AND+%22Nature+Protocols%22%5BJournal%5D)">Laser-capture microdissection.</a> Nature Protocols. 1, 586-603 (2006).</li>
<li>Grafen, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optimized+expression-based+microdissection+of+formalin-fixed+lung+cancer+tissue%5BTitle%5D)+AND+%22Laboratory+Investigation%3B+A+Journal+of+Technical+Methods+and+Pathology%22%5BJournal%5D)">Optimized expression-based microdissection of formalin-fixed lung cancer tissue.</a> Laboratory Investigation; A Journal of Technical Methods and Pathology. 97 (7), 863-872 (2017).</li>
<li>Javey, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((innovative+tumor+tissue+dissection+tool+for+molecular+oncology+diagnostics%5BTitle%5D)+AND+%22The+Journal+of+Molecular+Diagnnostics%3A+JMD%22%5BJournal%5D)">innovative tumor tissue dissection tool for molecular oncology diagnostics.</a> The Journal of Molecular Diagnnostics: JMD. (21), 1525-1578 (2021).</li>
<li>Adey, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+mill+based+instrument+and+software+system+for+dissecting+slide-mounted+tissue+that+provides+digital+guidance+and+documentation%5BTitle%5D)+AND+%22BMC+Clinical+Pathology%22%5BJournal%5D)">A mill based instrument and software system for dissecting slide-mounted tissue that provides digital guidance and documentation.</a> BMC Clinical Pathology. 13 (1), 29(2013).</li>
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Charles A Havnar, Oliver Zill, Jeff Eastham, Jeffrey Hung, Jennifer Giltnane, Nicolas Lounsbury, Daniel Oreper, Sarajane Saturnio, and Amy A Lo are employees and stockholders of Genentech and Roche and Mana Javey and Emmanuel Naouri are employees and stockholders of Roche.

Presented here is a protocol for the application of digital annotation and automated dissection to dissect tumor regions from low tumor content FFPE or fresh frozen tissues for tumor enrichment and use in WES. Combining digital annotation and mask creation with automated dissection significantly reduces the required hands-on time and expertise common to classical methods of tumor enrichment inclusive of manual macrodissection and LCM. The protocol demonstrates a potentially important mid-range tumor enrichment option that allows for not only low tumor content enrichment but also enrichment in cases where it is challenging to dissect distributed tumor nests away from the tumor adjacent normal tissue for meaningful tumor enrichment with high throughput and a moderate level of precision. While the use of our workflow for low tumor content xenograft tissues is demonstrated here, it was also found that this protocol works across tissue types, including human, murine, and xenograft tissues for a variety of normal tissues and cancer indications.
Therefore, it could also apply to a broad range of applications where enriching for specific regions of interest without significant contamination of background tissue would be beneficial (i.e., to enrich for a specific brain region) or even for removal of areas of tissue prior to nucleic acid extraction using classical macrodissection.
Many platforms exist on the market for slide scanning and digital annotation. It is therefore important to remain aware that platform compatibility may present limitations and specified platforms within any protocol may not be broadly available in all laboratories. Therefore, significant efforts were made to provide alternative options within the described protocol that will guide users in making any necessary modifications based on their available resources. An option for removal of the digital annotation component has also been noted to allow for careful manual on-slide annotation. The options provided for modifications will maximize the ability of users to find an option that works with their current platform and software availability.
While digital annotation and automated dissection have been demonstrated to be broadly applied to both FFPE and fresh frozen tissue, it is important to note that the boundaries of the automated tissue dissection instrument have been pushed beyond its intended use with FFPE specimens and the protocol is meant for research use only. Here, successful tumor enrichment was demonstrated through automated tumor dissection of low tumor content FFPE as well as fresh frozen tissues for nucleic acid extraction, WES and RNA sequencing. The protocol shows that xenograft and human tissue regions of interest could be enriched prior to WES and RNA sequencing in basic and translational research settings and also note that other downstream molecular applications, including PCR, from both tissue types would be possible. The protocol expands FFPE automated dissection options and lays the groundwork for fresh frozen tissue automated dissection that could be developed and validated further for use in clinical settings.

Next generation sequencing (NGS) is increasingly utilized for both patient care and in cancer research to help guide treatments and facilitate scientific discovery. Tissue is often limited and small specimens with variable tumor content are routinely used. Tumor adequacy and integrity, therefore, remain a barrier to obtaining meaningful data. Samples with lower tumor percentages may cause difficulty in distinguishing true variants from sequencing artifacts and are often ineligible for NGS1. Tumor enrichment of low tumor content cases, those below 20%, has been shown to help yield sufficient material in order to generate reproducible sequencing data and ensure low frequency variants are not missed2,3. However, limits will vary depending on the platforms utilized and planned use of the data generated.
Traditionally, enrichment of tumor regions for extraction is performed by manual macrodissection or laser capture microdissection (LCM) of formalin fixed paraffin embedded (FFPE) slides. Manual macrodissection, or scraping specified tissue areas from slides, allows tumor regions to be removed for use in downstream assays with relatively low cost, but with low accuracy and low precision2,4. Minimal technical accuracy can be very effective with higher tumor content cases where large swaths of tumor are present and/or minimal tissue loss does not significantly impact results, but low tumor content cases or cases with more dispersed tumor require increased precision. LCM was therefore invented in the 1990s and became a valuable way to precisely remove small, defined, microscopic regions of tissue from formalin fixed paraffin embedded (FFPE) slides5,6,7,8. LCM can be utilized to collect single cell populations when complex heterogeneity of the sample exists9 allowing for collection of previously difficult to separate cell populations. However, LCM requires costly machinery that requires extensive technical expertise and hands-on time10,11,12,13,14.
The instrument used for automated tissue dissection has precision in between that of LCM (~10 &#181;m) and macrodissections (~1 mm)15. Additionally, it exhibits both cost and technical expertise requirements between that of macrodissection and LCM and is designed to perform rapid tissue enrichment from sequential FFPE slides to alleviate the disadvantages of previous methods15. Automated dissection in this fashion utilizes digital annotations or on-stage slide reference image overlays onto serially sectioned unstained tissue slides for dissecting and enriching regions of interest. The instrument uses plastic spinning blade milling tips, 1.5 mL collection tubes and can be used with a number of different fluids for dissection to collect regions of interest for downstream assays inclusive of nucleic extraction and sequencing. The spinning plastic milling tip utilizes inner and outer syringe barrel reservoirs and a plunger to collect buffer, then mills and collects tissue16. The variable milling tip size diameter (250 &#181;m, 525 &#181;m, 725 &#181;m) can allow for dissection of separate tissue areas for comparison, multifocal regions that can be pooled or individual small areas from single or multiple FFPE slides. Section thicknesses used for harvest can be adjusted based on individual experiment needs and users can ensure regions of interest have not been depleted by performing an additional H&#38;E on one serial section immediately after the last section used for harvest.
Automated dissection was identified as a way to enrich tumor content in low tumor content cases and we tested and expanded the intended functionality of an automated tissue dissection instrument, which is currently marketed for use on FFPE clinical specimens up to 10 &#181;m in thickness. The work shows that automated dissection can be applied to both FFPE and fresh frozen human or animal tissue sections up to 20 &#181;m in thickness for research purposes. The protocol also demonstrates an approach to digitally annotate and automate dissection for tumor enrichment in tissues with low tumor content and/or cases with nested, dispersed tumor where meaningful macrodissection is challenging or not feasible and show both quality and yield of nucleic acid sufficient for NGS. Automated dissection can therefore provide mid-level precision and increased throughput for tumor enrichment and could also be applied to enrich other regions of interest or combined with other platforms to answer research or clinical questions.

<table><tbody><tr><td>Agilent SureSelectXT</td><td>Agilent</td><td>G9611A</td><td></td></tr><tr><td>AVENIO Millisect Fill Station</td><td>Roche</td><td>8106533001</td><td></td></tr><tr><td>AVENIO Millisect Instrument, Base</td><td>Roche</td><td>8106568001</td><td></td></tr><tr><td>AVENIO Millisect Instrument, Head</td><td>Roche</td><td>8106550001</td><td></td></tr><tr><td>AVENIO Millisect Milling Tips Small</td><td>Roche</td><td>8106509001</td><td></td></tr><tr><td>AVENIO Millisect PC</td><td>Roche</td><td>8106495001</td><td></td></tr><tr><td>BioAnalyzer</td><td>Agilent</td><td>G2939BA</td><td></td></tr><tr><td>Eppendorf 5427R</td><td>Eppendorf</td><td>22620700</td><td>Micro-centrifuge</td></tr><tr><td>Incubation Buffer</td><td>Promega</td><td>D920D</td><td></td></tr><tr><td>Leica Autostainer XL</td><td>Leica</td><td>ST5010</td><td>Automated stainer</td></tr><tr><td>Molecular Grade Mineral Oil</td><td>Sigma</td><td>M5904-500ML</td><td></td></tr><tr><td>Proteinase K</td><td>Promega</td><td>V302B</td><td>Digestion buffer</td></tr><tr><td>Qiagen AllPrep DNA/RNA Mini Kit</td><td>Qiagen</td><td>80284</td><td></td></tr><tr><td>RLT Plus buffer</td><td>Qiagen</td><td>80204</td><td></td></tr><tr><td>Superfrost Plus positively charged microscope slides</td><td>Thermo Scientific</td><td>6776214</td><td></td></tr></tbody></table>

automated dissection protocol for tumor enrichment in low tumor content tissues

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly with many downstream assays such as next generation sequencing. Automated tissue dissection is a new methodology that automates and improves tumor enrichment in these common, low tumor content tissues by decreasing the user-dependent imprecision of traditional macro-dissection and time, cost, and expertise limitations of laser capture microdissection by using digital image annotation overlay onto unstained slides. Here, digital hematoxylin and eosin (H&#38;E) annotations are used to target small tumor areas using a blade that is 250 &#181;m2 in diameter in unstained formalin fixed paraffin embedded (FFPE) or fresh frozen sections up to 20 &#181;m in thickness for automated tumor enrichment prior to nucleic acid extraction and whole exome sequencing (WES). Automated dissection can harvest annotated regions in low tumor content tissues from single or multiple sections for nucleic acid extraction. It also allows for capture of extensive pre- and post-harvest collection metrics while improving accuracy, reproducibility, and increasing throughput with utilization of fewer slides. The described protocol enables digital annotation with automated dissection on animal and/or human FFPE or fresh frozen tissues with low tumor content and could also be used for any region of interest enrichment to boost adequacy for downstream sequencing applications in clinical or research workflows.

FFPE and FF mouse liver sections containing metastatic colorectal cancer in xenografts were selected. Sections were H&#38;E stained (Figure 1A,E,I) and scanned on a whole slide imager at 20x magnification. A pathologist digitally annotated tumor regions of interest and a mask was generated using commercial software and formatted as a digital png reference image (Figure 1B,F,J). Serial 10 &#181;m and 20 &#181;m thick unstained sample slides were placed on the stage and automated dissection was performed as described above. Fresh frozen tissues were collected in a lysis buffer from a commercially available kit and carried directly into nucleic acid extraction following the manufacturer&#39;s instructions. FFPE samples were collected using molecular grade mineral oil and dissected samples were pooled together and centrifuged at 25,000 x g for 20 min at 4 &#176;C. The supernatant was removed and the minimal mineral oil required was used to resuspend, transfer, and collect the dissected tissue into a single collection tube for each sample appropriately. Samples were shipped at room temperature to a vendor for nucleic acid extraction, RNA and DNA sizing, quantity, integrity, and purity determination following the manufacturer&#39;s instructions. Sequencing libraries were created and used for hybridization and capture with commercial options following the manufacturer&#39;s instructions. Post dissected sample slides were H&#38;E stained using routine staining protocols to confirm dissection areas in 10 &#181;m (Figure 1C,G,K) and 20 &#181;m (Figure 1D,H,L) slides and dissection metrics were captured (Supplementary Table 1). Exome sequencing generated approximately 75 million 100 bp paired-end reads, yielding an average depth of coverage (before removing duplicate reads) of 150x per sample, with 99.9% reads aligned and a 78% on-target rate. RNA sequencing metrics demonstrated just over 55 million bp paired-end reads, a 98% alignment rate, and a 19.4% duplication rate with 77% concordant reads.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62394/62394fig01.jpg" /> 
Figure 1; Successful dissection of tumor nests from fresh frozen and FFPE tissue. H&#38;E stained mouse fresh frozen (A-D) and FFPE (E-L) liver tissue with colorectal cancer metastasis. 4 &#181;m reference slides used for digital annotation (A, E, I) demonstrate examples with a low tumor percent for the total tissue area (I) and distributed tumor nests (E) that classically present challenges to tumor enrichment. Annotated and digitally masked H&#38;E reference slides (B, F, J) were generated and post-dissection 10 &#181;m (C, G, K) and 20 &#181;m (D, H,L) H&#38;E stained slides demonstrate successful harvest of selected areas. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62394/62394fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplementary File 1: Pseudocode utilized to create digital masks from annotations to use in automated dissection. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62394/JoVE Millisect Figure 1.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Table 1: Example captured metrics from automated dissection and nucleic acid extraction. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62394/JoVE Supplementary Table 1.docx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues at JoVE.com

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

Digital annotation with automated tissue dissection provides an innovative approach to enriching tumor in low tumor content cases and is adaptable to both paraffin and frozen tissue types. The described workflow improves accuracy, reproducibility and throughput and could be applied to both research and clinical settings.

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly ...

automated-dissection-protocol-for-tumor-enrichment-low-tumor-content

Nanyang Technological University

Research

JoVE Journal

Cancer Research

2.5K Views.  Genentech. Isolatie of verrijking van kleine verspreide gebieden van belang van FFPE, of vers bevroren materiaal, kan sneller en efficiënter worden bereikt met geautomatiseerde dissectie dan met traditionele methoden. Extractie van genomisch materiaal uit FFPE, of vers ingevroren weefsel, is een vereiste voor veel klinische en translationele onderzoekslaboratoria. Geautomatiseerde dissectie vult een aanzienlijke kloof tussen macrodissectie en laser capture microdissectie.Annoteer om te beginnen ...

Video: Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

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

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

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

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

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective anti-tumor strategies. Although concerns are frequently raised due to differences in sample processing and depth of coverage, next-generation sequencing of solid tumors have unraveled a highly variable degree of ITH across tumor types. Capturing the genetic relatedness between primary and metastatic lesions through the identification of clonal and subclonal populations is critical to the design of therapies for advance-stage diseases. Here, we report a method for comparative lesions analysis that allows for the identification of clonal and subclonal populations among different specimens from the same patient. The experimental approach described here integrates three well-established approaches: histological analysis, high-coverage multi-lesion sequencing, and immunophenotypic analyses. In order to minimize the effects on the detection of subclonal events by inappropriate sample processing, we subjected tissues to careful pathological examination and neoplastic cell enrichment. Quality controlled DNA from neoplastic lesions and normal tissues was then subjected to high coverage sequencing, targeting the coding regions of 409 relevant cancer genes. While only looking at a limited genomic space, our approach enables evaluating the extent of heterogeneity among somatic alterations (single-nucleotide mutations and copy-number variations) in distinct lesions from a given patient. Through comparative analysis of sequencing data, we were able to distinguish clonal vs. subclonal alterations. The majority of ITH is often ascribed to passenger mutations; therefore, we also used immunohistochemistry to predict functional consequences of mutations. While this protocol has been applied to a specific tumor type, we anticipate that the methodology described here is broadly applicable to other solid tumor types.

This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.

Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective ...

Behavior

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput methods are needed to selectively isolate discrete cellular populations in solid tumor malignancies. This protocol describes a high-throughput workflow, enabled by artificial intelligence (AI), that segments images of hematoxylin and eosin (H&#38;E)-stained, thin tissue sections into pathology-confirmed regions of interest for selective harvest of histology-resolved cell populations using laser microdissection (LMD). This strategy includes a novel algorithm enabling the transfer of regions denoting cell populations of interest, annotated using digital image software, directly to laser microscopes, thus enabling more facile collections. Successful implementation of this workflow was performed, demonstrating the utility of this harmonized method to selectively harvest tumor cell populations from the TME for quantitative, multiplexed proteomic analysis by high-resolution mass spectrometry. This strategy fully integrates with routine histopathology review, leveraging digital image analysis to support enrichment of cellular populations of interest and is fully generalizable, enabling harmonized harvests of cell populations from the TME for multiomic analyses.

This protocol describes a high-throughput workflow for artificial intelligence-driven segmentation of pathology-confirmed regions of interest from stained, thin tissue section images for enrichment of histology-resolved cell populations using laser microdissection. This strategy includes a novel algorithm enabling the transfer of demarcations denoting cell populations of interest directly to laser microscopes.

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell ...

A Simple and Rapid Protocol to Non-enzymatically Dissociate Fresh Human Tissues for the Analysis of Infiltrating Lymphocytes

The ability of malignant cells to evade the immune system, characterized by tumor escape from both innate and adaptive immune responses, is now accepted as an important hallmark of cancer. Our research on breast cancer focuses on the active role that tumor infiltrating lymphocytes play in tumor progression and patient outcome. Toward this goal, we developed a methodology for the rapid isolation of intact lymphoid cells from normal and abnormal tissues in an effort to evaluate them proximate to their native state. Homogenates prepared using a mechanical dissociator show both increased viability and cell recovery while preserving surface receptor expression compared to enzyme-digested tissues. Furthermore, enzymatic digestion of the remaining insoluble material did not recover additional CD45+ cells indicating that quantitative and qualitative measurements in the primary homogenate likely genuinely reflect infiltrating subpopulations in the tissue fragment. The lymphoid cells in these homogenates can be easily characterized using immunological (phenotype, proliferation, etc.) or molecular (DNA, RNA and/or protein) approaches. CD45+ cells can also be used for subpopulation purification, in vitro expansion or cryopreservation. An additional benefit of this approach is that the primary tissue supernatant from the homogenates can be used to characterize and compare cytokines, chemokines, immunoglobulins and antigens present in normal and malignant tissues. This protocol functions extremely well for human breast tissues and should be applicable to a wide variety of normal and abnormal tissues.

This protocol describes the rapid non-enzymatic dissociation of fresh human tissue fragments for qualitative and quantitative assessment of CD45+ cells (lymphocytes/leukocytes) present in various normal and malignant human tissues. Additionally, the supernatant obtained from the primary tissue homogenate can be collected and stored for further analysis or experimentation.

The ability of malignant cells to evade the immune system, characterized by tumor escape from both innate and adaptive immune responses, is now accepted ...

Immunology and Infection

Isolation of Nuclei for Multiome Sequencing in Solid Tumor Specimen

Optimized Nuclei Isolation from Fresh and Frozen Solid Tumor Specimens for Multiome Sequencing

Multiome sequencing, which provides same-cell/paired single-cell RNA- and the assay for transposase-accessible chromatin with sequencing (ATAC-sequencing) data, represents a breakthrough in our ability to discern tumor cell heterogeneity-a primary focus of translational cancer research at this time. However, the quality of sequencing data acquired using this advanced modality is highly dependent on the quality of the input material. 
Digestion conditions need to be optimized to maximize cell yield without sacrificing quality. This is particularly challenging in the context of solid tumors with dense desmoplastic matrices that must be gently broken down for cell release. Freshly isolated cells from solid tumor tissue are more fragile than those isolated from cell lines. Additionally, as the cell types isolated are heterogeneous, conditions should be selected to support the total cell population. 
Finally, nuclear isolation conditions must be optimized based on these qualities in terms of lysis times and reagent types/ratios. In this article, we describe our experience with nuclear isolation for the 10x Genomics multiome sequencing platform from solid tumor specimens. We provide recommendations for tissue digestion, storage of single-cell suspensions (if desired), and nuclear isolation and assessment.

Author Spotlight: Enhancing Nuclei Isolation for Multiome Sequencing in Challenging Tumor Microenvironments

The protocol provides a reliable and optimized approach to the isolation of nuclei from solid tumor specimens for multiome sequencing using the 10x Genomics platform, including recommendations for tissue dissociation conditions, cryopreservation of single-cell suspensions, and assessment of isolated nuclei.

Multiome sequencing, which provides same-cell/paired single-cell RNA- and the assay for transposase-accessible chromatin with sequencing (ATAC-sequencing) ...

Protocol for Prostatectomy Specimen Mapping and Dissection

Enhancing Prostate Tumor Biobanking Reliability with Improved Sampling Technique and Histological Characterization

Acquiring fresh and well-characterized tumor tissue samples is critical for conducting high-quality &#34;omics&#34; studies. However, it can be particularly challenging in the context of prostate cancer (PC) due to the unique nature of this organ and the high heterogeneity associated with this tumor. On the other hand, histopathologically characterizing samples before their storage without causing significant tissue alterations is also an intriguing challenge. In this context, we present a new method for acquiring, mapping, characterizing, and micro-dissecting resected prostate tissue based on anatomopathological criteria.
Unlike previously published protocols, this method reduces the time required for histopathological analysis of the prostate specimen without compromising its structure, which is crucial for assessing surgical margins. Furthermore, it enables the delineation and micro-macro dissection of fresh prostate tissue samples, with a focus on histological tumor areas defined by pathological criteria such as Gleason score, precursor lesions (high-grade prostatic intraepithelial neoplasia - PIN), and inflammatory lesions (prostatitis). These samples are then stored in a Biobank for subsequent research analyses.

Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking

This protocol describes a method for facilitating the collection of samples from radical prostatectomy specimens. The goal is to map, characterize, and micro-macro dissect tissue samples from the specimens based on anatomopathological criteria before storing them in a Biobank.

Acquiring fresh and well-characterized tumor tissue samples is critical for conducting high-quality &#34;omics&#34; studies. However, it can be ...

Tumor Dissociation Protocol for Single-Cell RNA Sequencing Analysis

Dissociation of Human and Mouse Tumor Tissue Samples for Single-cell RNA Sequencing

Human tumor samples hold a plethora of information about their microenvironment and immune repertoire. Effective dissociation of human tissue samples into viable cell suspensions is a required input for the single-cell RNA sequencing (scRNAseq) pipeline. Unlike bulk RNA sequencing approaches, scRNAseq enables us to infer the transcriptional heterogeneity in tumor specimens at the single-cell level. Incorporating this approach in recent years has led to many discoveries, such as identifying immune and tumor cellular states and programs associated with clinical responses to immunotherapies and other types of treatments. Moreover, single-cell technologies applied to dissociated tissues can be used to identify accessible chromatin regions T and B cell receptor repertoire, and the expression of proteins, using DNA barcoded antibodies (CITEseq).
The viability and quality of the dissociated sample are critical variables when using these technologies, as these can dramatically affect the cross-contamination of single cells with ambient RNA, the quality of the data, and interpretation. Moreover, long dissociation protocols can lead to the elimination of sensitive cell populations and the upregulation of a stress response gene signature. To overcome these limitations, we devised a rapid universal dissociation protocol, which has been validated on multiple types of human and murine tumors. The process begins with mechanical and enzymatic dissociation, followed by filtration, red blood lysis, and live dead enrichment, suitable for samples with a low input of cells (e.g., needle core biopsies). This protocol ensures a clean and viable single-cell suspension paramount to the successful generation of Gel Bead-In Emulsions (GEMs), barcoding, and sequencing.

Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors

This protocol outlines the procedure for rapidly dissociating human and mouse tumor samples for single-cell RNA sequencing.

Human tumor samples hold a plethora of information about their microenvironment and immune repertoire. Effective dissociation of human tissue samples into ...

High-Throughput Dissociation and Orthotopic Implantation of Breast Cancer Patient-Derived Xenografts

Patient-derived xenografts (PDXs) provide a clinically relevant method for recapitulating tumor-involved cell types and the tumor microenvironment, which is essential for advancing knowledge of breast cancer (BC). Additionally, PDX models enable the study of BC systemic effects, which is not possible using in vitro models. Traditional methods for implanting BC xenografts typically involve anesthesia and sterile surgical procedures, which are time-consuming, invasive, and limit the scalability of PDX models in BC research. This protocol describes a simple and scalable method for the orthotopic implantation of BC PDXs in mice. The immunodeficient mouse strain NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) was used for PDX engraftment. Human BC samples obtained from IRB-consented patients were mechanically and enzymatically dissociated, then resuspended in a solution of basement membrane extract (BME) and RPMI 1640. Animals were restrained by scruffing, and depilatory cream was applied to remove hair from the fat pads at the fourth inguinal nipple, followed by injection. Approximately 2 million cells in a 100 &#181;L suspension were bilaterally injected orthotopically into the mammary fat pads using a 26 G needle. Notably, no anesthetic was required, and the total procedure time was under 5 min, from cell preparation to injection. After a growth period of several months, tumors were excised and processed for authentication. Validation included receptor status assessment using immunohistochemistry with specific antibodies for traditional BC receptors (i.e., ER, PR, HER2). Tumor morphology was confirmed with hematoxylin and eosin (H&amp;E) staining, which was interpreted by a pathologist. Genetic similarity to the patient sample was verified through bulk RNA sequencing and short tandem repeat (STR) analysis. This approach to PDX engraftment and validation supports the rigorous development of models and high-throughput tumor implantation, enabling well-powered studies across various BC subtypes.

This protocol describes an efficient, non-surgical method for the orthotopic implantation of breast cancer patient-derived xenografts in mice. The technique involves enzymatic tumor dissociation followed by direct injection into the mammary fat pads, enabling high-throughput implantation. Comprehensive validation ensures model fidelity, facilitating rigorous studies across various breast cancer subtypes.

Patient-derived xenografts (PDXs) provide a clinically relevant method for recapitulating tumor-involved cell types and the tumor microenvironment, which ...

Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells

The use of in vitro cell line models for cancer research has been a useful tool. However, it has been shown that these models fail to reliably mimic patient tumors in different assays1. Human tumor xenografts represent the gold standard with respect to tumor biology, drug discovery, and metastasis research 2-4. Tumor xenografts can be derived from different types of material like tumor cell lines, tumor tissue from primary patient tumors4 or serially transplanted tumors. When propagated in vivo, xenografted tissue is infiltrated and vascularized by cells of mouse origin. Multiple factors such as the tumor entity, the origin of xenografted material, growth rate and region of transplantation influence the composition and the amount of mouse cells present in tumor xenografts. However, even when these factors are kept constant, the degree of mouse cell contamination is highly variable.
Contaminating mouse cells significantly impair downstream analyses of human tumor xenografts. As mouse fibroblasts show high plating efficacies and proliferation rates, they tend to overgrow cultures of human tumor cells, especially slowly proliferating subpopulations. Mouse cell derived DNA, mRNA, and protein components can bias downstream gene expression analysis, next-generation sequencing, as well as proteome analysis 5. To overcome these limitations, we have developed a fast and easy method to isolate untouched human tumor cells from xenografted tumor tissue. This procedure is based on the comprehensive depletion of cells of mouse origin by combining automated tissue dissociation with the benchtop tissue dissociator and magnetic cell sorting. Here, we demonstrate that human target cells can be can be obtained with purities higher than 96% within less than 20 min independent of the tumor type.

Human tumor xenografts are vascularized and infiltrated by cells of mouse origin during the growth phase in vivo. To circumvent the bias caused by these contaminating cells during downstream analysis, we developed a method allowing for comprehensive depletion of all mouse cells by magnetic cell sorting.

The use of in vitro cell line models for cancer research has been a useful tool. However, it has been shown that these models fail to reliably mimic ...

Medicine

Isolation of Immune Cells from Primary Tumors

Tumors create a unique immunosuppressive microenvironment (tumor microenvironment, TME) whereby leukocytes are recruited into the tumor by various chemokines and growth factors 1,2. However, once in the TME, these cells lose the ability to promote anti-tumor immunity and begin to support tumor growth and down-regulate anti-tumor immune responses 3-4. Studies on tumor-associated leukocytes have mainly focused on cells isolated from tumor-draining lymph nodes or spleen due to the inherent difficulties in obtaining sufficient cell numbers and purity from the primary tumor. While identifying the mechanisms of cell activation and trafficking through the lymphatic system of tumor bearing mice is important and may give insight to the kinetics of immune responses to cancer, in our experience, many leukocytes, including dendritic cells (DCs), in tumor-draining lymph nodes have a different phenotype than those that infiltrate tumors 5,6 . Furthermore, we have previously demonstrated that adoptively-transferred T cells isolated from the tumor-draining lymph nodes are not tolerized and are capable of responding to secondary stimulation in vitro unlike T cells isolated from the TME, which are tolerized and incapable of proliferation or cytokine production 7,8. Interestingly, we have shown that changing the tumor microenvironment, such as providing CD4+ T helper cells via adoptive transfer, promotes CD8+ T cells to maintain pro-inflammatory effector functions 5. The results from each of the previously mentioned studies demonstrate the importance of measuring cellular responses from TME-infiltrating immune cells as opposed to cells that remain in the periphery. To study the function of immune cells which infiltrate tumors using the Miltenyi Biotech isolation system9, we have modified and optimized this antibody-based isolation procedure to obtain highly enriched populations of antigen presenting cells and tumor antigen-specific cytotoxic T lymphocytes. The protocol includes a detailed dissection of murine prostate tissue from a spontaneous prostate tumor model (TRansgenic Adenocarcinoma of the Mouse Prostate -TRAMP) 10 and a subcutaneous melanoma (B16) tumor model followed by subsequent purification of various leukocyte populations.

In this report, we describe a protocol for isolating highly purified populations of leukocytes that infiltrate tumors. This protocol is adapted from the Miltenyi Biotech protocol to enhance yield and purity for isolating cells from complex tumor tissue.

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

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