This work is supported by NIH-funded AIDS and Cancer Specimen Resource (<a href="https://www.acsr1.com/">ACSR</a>, UM1 CA181255-2) under its biospecimen science program. The video was filmed and post-production editing was performed by Mayo Clinic Media Services.

All samples were collected and used in compliance with approved Mayo Clinic IRB protocols (PR16-000507 and PR2207-02).
1. Sample preparation
<ol>
	<li>Turn on the tissue floatation water bath. Set the temperature to 39 &#176;C and allow the water to come to temperature. Soak wooden collection sticks in the water bath.</li>
	<li>Identify and retrieve the FFPE tissue blocks to be sectioned.</li>
	<li>Pre-label microscope slides using a histology grade permanent marker that can withstand solvent washes.</li>
	<li>Use a microtome to section the FFPE blocks. Cut at least 2 full-face sections at a thickness of 4-5 &#956;m per section for each block (Figure 1A).</li>
	<li>Transfer the freshly cut ribbon of tissue sections to the pre-warmed tissue floatation bath for slide mounting (Figure 1B, C). 
	NOTE: The warm water helps to &#34;iron&#34; out the wrinkles in the sections (Figure 1C).</li>
	<li>Handling each section sequentially, use forceps to break a single section away from the ribbon (Figure 1D).</li>
	<li>Collect the single section on a pre-labeled microscope slide.
	<ol>
		<li>Submerge the microscope slide at an angle underneath the section, positioning the slide such that the edge of the tissue section touches the slide (Figure 1E).</li>
		<li>Once in contact with the tissue section, pull the slide out of the floatation bath slowly to allow the tissue section to straighten out flush against the slide as it emerges from the water (Figure 1F).</li>
	</ol>
	</li>
	<li>Mount 1 tissue section per slide and repeat until all the sections have been collected.</li>
	<li>Allow the slide-mounted tissue sections to dry thoroughly at room temperature (RT).</li>
</ol>
2. Pathological review
<ol>
	<li>Perform H&#38;E staining on one representative tissue section for each block9.</li>
	<li>Submit the freshly stained H&#38;Es for pathological review by a board-certified pathologist. 
	&#8203;NOTE: During the review, the pathologist determines and records the percentage tumor content in each tissue and circles the tumor area on each H&#38;E slide (see Figure 2 and Figure 3, Row 1). Table 1 outlines the percentage tumor content by cellularity determined during the pathological review of the H&#38;Es for samples A-E shown in Figure 3, Row 1. Sections with &#60;60% tumor content require macro-dissection7. The number of sections needed for nucleic acid extraction depends on the size of the circled tumor area. If insufficient sections were cut in section 1 of the protocol and further cuts are possible, then additional sections may need to be cut.</li>
</ol>
3. Deparaffinization
<ol>
	<li>In a fume hood, prefill two glass staining dishes with undiluted histology grade d-Limonene or a d-Limonene based solvent and 1 glass staining dish with undiluted 200-proof molecular grade ethanol. 
	CAUTION: Avoid d-Limonene contact with skin and eyes, avoid inhalation of vapor or mist, and keep away from sources of ignition. Keep ethanol away from heat, sparks, and open flames, avoid spilling and contact with the skin or eyes, ventilate well and avoid breathing vapors. 
	NOTE: Fill the dishes sufficiently to submerge the racked slides (Figure 4A); 250 mL is required to fill the 20-slide staining dishes shown. Replace the d-Limonene and ethanol washes after every 40 slides. D-Limonene (C10H16) is an alternative, similarly effective, and less toxic dewaxing agent to xylene that is becoming more commonplace in histological methodologies and yields good quality nucleic acid post extraction10,11,12,13,14. Although this protocol may be performed using more biofriendly alternatives15, their effects, if any, on extracted nucleic acid quality remains to be determined.</li>
	<li>Rack the unstained FFPE tissue mounted slides into the glass Coplin slide-racks (Figure 4A, inset).</li>
	<li>Submerge the racked slides in d-Limonene wash 1 for 2 min; gently agitate for the first 20 s. 
	NOTE: To minimize carryover between washes, when removing the rack of slides from a wash, allow the rack to drain briefly before gently dabbing the bottom of the rack on tissue paper to remove excess wash.</li>
	<li>Submerge the racked slides in undiluted D-Limonene wash 2 for 2 min; gently agitate for the first 20 s. Remove, drain and dab the rack again.</li>
	<li>Submerge the racked slides in the ethanol wash for 2 min; gently agitate for the first 20 s. Remove the rack and place it on an absorbent tissue to drain. Allow the slides to air dry for at least 10 min, but no more than 2 h.</li>
</ol>
3. Macrodissection
<ol>
	<li>On the bench, prefill a Coplin glass jar with 50 mL of 3% glycerol in DNase/RNase free water 
	NOTE: Replace the glycerol wash after every 40 slides.</li>
	<li>Pre-label and prefill 1.5 mL microtubes with 160 &#181;L of tissue digestion buffer per microtube. 
	NOTE: Nucleic acid extractions performed after macrodissection used a DNA/RNA FFPE extraction kit (Table of Materials). Thus, the tissue digestion buffer used in this protocol comprised 10 &#181;L of Proteinase K and 150 &#181;L of PKD buffer.</li>
	<li>Trace the pathological markings on the H&#38;E onto the back of the deparaffinized tissue slides. 
	NOTE: Compared to non-deparaffinized tissues (Figure 3, Row 2 and Figure 4B), deparaffinized tissues are white and highly visible (Figure 3, Row 3, and Figure 4C). It is this heightened visibility and discernability of deparaffinized tissue features that permit macrodissection. Place the H&#38;E face down on the bench and place the front of the deparaffinized slide against the back of the matched pathologist reviewed H&#38;E (Figure 4D). Align the deparaffinized tissue with the H&#38;E tissue (Figure 4E). Tracing the pathologist&#39;s markings is a critical step in the macrodissection process, and care should be taken to reproduce these markings as accurately as possible. This can be particularly challenging for small and or disconnected tissues such as samples B, D, and E (Figure 3, Figure 4E, and Figure 4E inset i). To aid tracing, one should use an inky fine or ultrafine nibbed marker (Figure 4E, inset ii) to trace the pathologist-drawn markings. Ethanol wipes may be useful to remove errors and permit retracing if needed.</li>
	<li>Turn the now marked deparaffinized slide tissue face-up and trace the line of the marker with the corner of a clean razor blade to pre-cut the edges of the tumor area.</li>
	<li>Handling each slide sequentially, dip the deparaffinized slides into the 3% glycerol solution. Ensure the tissue is completely submerged before removing the slide slowly (Figure 4F). 
	NOTE: The purpose of the glycerol dip is to dampen the tissue to aid tissue collection but also to reduce the build-up of static charge that can cause repulsion between the tissue and the plastic microtube in which the collected tissue must be placed.</li>
	<li>Gently wipe the back of the slide with a tissue to remove the excess glycerol solution, and lay the slide on the bench, wiped side face down. Allow tissues to briefly airdry for 1-2 min. 
	NOTE: Carry over of excess glycerol into the extraction process can negatively affect the yield and quality of nucleic acid extractions. Tissues should be slightly damp but not visibly wet when collected.</li>
	<li>Depending on where the tumor area of interest is situated on the slide, use the flat edge of the razor blade to either (a) directly collect the tumor tissue, using the razor to scrape/collect the tissue of interest off the slide, or (b) remove and discard non-tumor tissue first before collecting the tumor tissue of interest (Figure 3). 
	NOTE: Collected tissue tends to gather or roll up at the bottom of the blade (Figure 4G)</li>
	<li>Use a wooden stick to remove the collected tissue from the blade (Figure 4H and inset) and transfer it to the appropriate pre-labeled and prefilled microtube (Figure 4I). 
	NOTE: The digestion buffer serves to &#34;pull&#34; the tissue from the wooden pick into the liquid.</li>
	<li>Proceed to nucleic acid extraction. 
	NOTE: Nucleic acid extractions were completed using the DNA/RNA FFPE extraction kit per the manufacturer&#39;s instructions, and the resulting nucleic acids were quantified using a UV-vis spectrophotometer. The resulting RNA was run on the digital gene expression profiling-based DLBCL90 assay16.</li>
</ol>

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The authors have nothing to disclose.

FFPE tissues are frequently heterogeneous admixtures of tumor and non-tumor tissues. High sensitivity genomic tests are becoming increasingly prevalent in both clinical and research settings but can be confounded by the presence of contaminating non-tumor tissue. Indeed, a minimum tumor content of 60% is frequently recommended for genomic studies. Percentage tumor can be determined by the area of tissue occupied by the tumor material or by the proportion of tumor cells within the tissue. Although tumor by area is a commonly used metric for tumor purity, it does not always portray an accurate description of the tissue. Consider two tissues, both with 1000 cells, of which 500 are tumor cells. In tissue A, the 500 non-tumor cells are stromal cells with similar volumes to that of the tumor cell. In this tissue, the percentage of tumor can be considered 50% by both cellularity and area. In tissue B, the 500 non-tumor cells are fat cells with volumes that are 4x that of the tumor cell. In this tissue, the percentage tumor is still 50% by cellularity but 20% by area. A third tissue, tissue C, is composed of 500 tumor cells plus 400 fat cells and 800 stromal cells with volumes that are 4x and 0.5x that of the tumor cells, respectively. Given 100 fat cells equals the volume of 800 stromal cells, the percentage tumor of tissue C is 29% by cellularity (500/1700) but still 20% by area. Tissue D is also comprised of the tumor, fat, and stromal cells with volume ratios of 1x, 4x, and 0.1x. However, the number of cells is 400, 10, and 720, respectively. Thus, the percentage tumor of tissue D is 35% by cellularity (400/1130) but 78% by area. These examples are overly simplistic and do not reflect real-world tissue compositions but clearly convey the importance of tissue composition and the difference between tumor content by area and by cellularity. Importantly, when it comes to enriching tumor content for downstream nucleic acid extraction, tumor cellularity is the more important attribute due to the heightened confounding potential of extracting genomic material from more non-tumor cells than tumor cells. This not only underscores the need to assess the tumor content of tissues in terms of percentage cellularity but also the need to excise unwanted tissue in order to minimize any potential negative effects of the non-tumor tissue. There are several methods available for tissue enrichment, with the main ones being macrodissection and microdissection.
Macrodissection, the method described in this protocol, is relatively quick, simple, and does not require costly or specialized equipment. Although macrodissection can greatly improve tumor content, it is important to understand that it does not completely eliminate non-tumor material. The purpose of macrodissection is to enrich the tissue of interest sufficiently through the exclusion of unwanted tissue in order to reduce the "noise" stemming from unwanted tissue, which in turn can enhance the signal of interest from the tissue of interest. Thus, macrodissection mediated tumor enrichment is a way to enhance the signal-to-noise ratio in order to better detect markers of interest, particularly tumor-specific molecular markers with low abundance or poor expression. However, macrodissection has limitations due to the lack of precision offered by coarse tools such as razor blades and is susceptible to precision issues stemming from the line thickness of the pathologist's marker, as well as potential errors when tracing the pathologists H&amp;E demarcations. As alluded above, it is not possible to achieve 100% tumor purity due to the presence of inherent and tumor-inducing stromal elements (i.e., connective tissue, stromal fibroblasts, blood vessels, benign reactive lymphocytes, macrophages) embedded within the tumor itself. Indeed, many invasive or diffusely infiltrative malignancies induce a robust desmoplastic stromal response, resulting in clusters of tumor cells that are intimately admixed with stromal fibroblasts and other non-neoplastic cell types; where tumors associated with this stromal reaction pattern, such as pancreatic cancer tissues21, may benefit more from digitally guided microdissection rather than manual macrodissection. 
Manual microdissection is performed under a microscope to aid identification, dissection, and isolation of tissues specific cells or populations using a needle or scalpel and has the advantage of increased precision over macrodissection22. However, manual microdissection is a laborious process that lacks the finesse needed for complex tissues with low tumor contents or intricate features that are incompatible with manual dissection. Such tissues can be dissected using high-precision automated methods like laser capture microdissection. Indeed, digitally guided microdissection has been shown to yield higher percentage tumor contents compared to manual macrodissection in pancreatic cancer tissues23. However, the drawbacks of these high precision automated methods, such as the need for specialized, expensive equipment and highly trained individuals, have hindered its incorporation into workflows. A study by de Bruin et al. comparing the effects of macrodissection and laser capture microdissection (LCM) on gene expression profiling found that LCM samples had low total RNA yields (30 ng average) and required two rounds of mRNA amplification in order to meet the cDNA library prep input threshold24. The authors found that the resulting LCM gene expression profiles were affected by the rounds of mRNA amplification more than macrodissected profiles were affected by non-tumor stromal contributions and concluded that macrodissection could be adequately used to generate reliable gene expression data24. 
A significant advantage of NanoString digital gene expression profiling, particularly when working with highly degraded FFPE derived RNA, is that it does not require enzymatic dependent processes such as RNA amplification or preparation of cDNA libraries. However, assays are typically optimized for inputs between 50-300 ng of total RNA25,26, which, based on the findings of de Bruin et al.24, may not be compatible with microdissected tissues without increasing the tissue input; an unfavorable demand in an era where tissue samples are increasingly collected as small biopsies rather than surgical resections. The RNA inputs used for the DLBCL90 assay ranged from 68.5-300 ng for both the macrodissected and non-dissected tissues. The results show that macrodissection resulted in call changes in 60% of the samples examined and that these changes were observed irrespective of RNA input of the macrodissected samples. However, the COO probability for the low RNA input did encroach the COO GCB/UNC probability call threshold, where the thresholds are 0 to &lt;0.1 for GCB, 0.1-0.9 for UNC, and &gt;0.9 to 1.0 for ABC calls20. The principal DLBCL COO subtypes are GCB and ABC, which make up 41% and 44% of all DLBCL cases, with UNC representing an intermediate group of the two and ABC being the most aggressive20,27. Thus, while the COO call change upon macrodissection of sample C did not cause a frank change in COO subtype from GCB to ABC, the change from GCB to UNC may suggest a shift towards a more aggressive disease. Moreover, recent studies indicate that the UNC subtype is not simply just an intermediate subtype and that it may potentially possess subtype-specific therapeutically exploitable attributes28. Similarly, macrodissection of samples A and E did not cause frank changes in DHITsig calls from DH negative to DH positive, or vice versa. However, the movements of a GCB sample (sample A) from NEG to UNCLASS and an ABC sample (sample E) from UNCLASS to NEG upon macrodissection are biologically appropriate as double hit translocations involving BCL2 are reported to be an exclusively GCB phenomenon19. Although translocations are traditionally and ubiquitously detected by FISH in clinical settings, there is a growing momentum to identify an alternative less involved and time-consuming method for their detection. The DLBCL90 assay is an important tool that addresses this need, where the rationale for its use is strengthened by the finding that this assay is capable of detecting translocations cryptic to FISH probes used in clinical diagnostics29. 
The macrodissection protocol described above outlines a simple method that enables researchers to increase the tumor content of tissue samples that would ordinarily fall below commonly used study inclusion criteria thresholds. Including macrodissection in a study workflow enables researchers to salvage poorly tumor-dense tissues from study exclusion by increasing their tumor content. In turn, this permits increased confidence that the resulting RNA and DNA eluates represent the tumor under genomic investigation. Although other more precise methods for tissue dissection do exist, for tumors that grow in a more expansive, non-infiltrative, sheet-like, or solid fashion, macrodissection is likely sufficient. The results presented here highlight the importance of tumor purity in genomic assays and macrodissection as a reliable tool to achieve this.

Formalin-fixed paraffin-embedded (FFPE) tissues, collected as part of the normal clinical diagnostic process and retained in clinical tissue repositories, represent a vast resource for human research, including cancer research1. As our understanding of human disease deepens, it is becoming increasingly clear that diseases, previously thought to be single entities based on morphological and immunophenotypical characteristics, are in fact comprised of distinct molecular subtypes that require molecular subtyping assays. Consequently, high sensitivity genomic assays capable of discerning these subtypes have become increasingly important2. Although FFPE tissues are renowned for being poorly compatible with genomic techniques due to fixation-related issues, as technology and protocols evolve, these techniques are becoming increasingly compatible with this clinically ubiquitous tissue format3,4,5. However, FFPE tissues are often admixtures of tumor and non-tumor tissue materials, where the presence of non-tumor material is frequently unwanted and can, if present at a high proportion, significantly undermine and impact the results of genomic analyses6. Indeed, a minimum tumor content of 60% is frequently used for such analyses, where tissues that fall short of this threshold can be excluded, despite otherwise fulfilling the study criteria7. This can be particularly problematic in rare disease settings, where patient tissues are precious and difficult to collect in high numbers.
Macrodissection is a method that minimizes the effects of low tumor content by reducing the amount of normal tissue3. The removal of such confounding non-tumor material prior to nucleic acid extraction can significantly augment the tumor percentage content and thus the tumor purity of the extracted nucleic acids. Tissue resection critically relies upon expert pathological review, wherein the tumor region is identified and circled on a freshly generated hematoxylin and eosin (H&#38;E) stained tissue section by a board-certified pathologist8. The circled H&#38;E is then used to guide the removal and collection of unwanted and target tissues, respectively. This protocol describes the steps of macrodissection from pathological review through tissue harvesting as performed at the AIDS and Cancer Specimen Resource (ACSR) Technical Core Laboratory at the Mayo Clinic.

<table><tbody><tr><td>200-proof ethanol</td><td>Decon</td><td>2701</td><td></td></tr><tr><td>AllPrep DNA/RNA FFPE Kit</td><td>Qiagen</td><td>80234</td><td>DNA/RNA FFPE extraction kit</td></tr><tr><td>Coplin pots</td><td>Various</td><td>x</td><td></td></tr><tr><td>DLBCL90 probes</td><td>NanoString</td><td>various</td><td>Digital gene expression profiling based DLBCL90 assay</td></tr><tr><td>d-Limonene</td><td>VWR</td><td>89376-092</td><td></td></tr><tr><td>Forceps</td><td>Various</td><td>x</td><td></td></tr><tr><td>Glass micrscope slides</td><td>FisherBrand</td><td>12-550-15</td><td></td></tr><tr><td>Glycerol</td><td>VWR</td><td>0854-1L</td><td></td></tr><tr><td>Master kits</td><td>NanoString</td><td>various</td><td></td></tr><tr><td>Microtome</td><td>Leica</td><td>RM2265</td><td></td></tr><tr><td>Microtubes</td><td>Ambion</td><td>AM12400</td><td></td></tr><tr><td>NanoDrop One</td><td>Thermo Scientific</td><td>ND-ONE-W</td><td>Spectrophotometer for DNA, RNA and protein qualitation</td></tr><tr><td>nCounter</td><td>NanoString</td><td>x</td><td>Digital gene expression profiling platform used to run the DLBCL90 assay</td></tr><tr><td>Permanent marker</td><td>Electrib Microscope Sciences</td><td>72109-12</td><td></td></tr><tr><td>Razor blade dispenser</td><td>Electrib Microscope Sciences</td><td>71985-10</td><td></td></tr><tr><td>Razor blades</td><td>Electrib Microscope Sciences</td><td>71985-23</td><td></td></tr><tr><td>Tissue digestion buffer</td><td>Qiagen</td><td>80234</td><td></td></tr><tr><td>Ultrapure water</td><td>VWR</td><td>SH30538.02</td><td></td></tr><tr><td>Waterbath</td><td>Triangle Biomedical Sciences</td><td>TFB-120</td><td></td></tr><tr><td>Wooden stick</td><td>FisherBrand</td><td>22363158</td><td></td></tr></tbody></table>

enhancing tumor content through tumor macrodissection

The presence of contaminating non-tumor tissues in formalin-fixed paraffin-embedded (FFPE) tissues can greatly undermine genomic studies. Herein we describe macrodissection, a method designed to augment the percentage tumor content of a tissue specimen by removing and eliminating unwanted tissue prior to performing downstream nucleic acid extractions. FFPE tissue blocks were sectioned to produce 4-5 &#181;m slide-mounted tissue sections. A representative section was submitted for hematoxylin and eosin (H&#38;E) staining and subsequently reviewed by a board-certified pathologist. During the review, the pathologist identified and marked the regions of tumor tissue in the H&#38;E. Once complete, the demarked H&#38;E was used to guide resection of the serial unstained sections from the same tissue block. To demonstrate the effects of macrodissection, RNA extracted from matched macrodissected and non-dissected Diffuse Large B-Cell Lymphomas (DLBCL) were run on a digital gene expression assay capable of determining DLBCL subtype and BCL2 translocation status. The results showed that macrodissection changed the subtype or BCL2 translocation status calls in 60% of the samples examined. In conclusion, macrodissection is a simple and effective method for performing tumor enrichment prior to nucleic acid extractions, the product of which can then be confidently used in downstream genomic studies.

A total of 5 Diffuse Large B-Cell Lymphoma (DLBCL) FFPE tissue blocks were sectioned, and the resulting sections were either macrodissected or not prior to nucleic acid extraction. The extracted RNA was run on the DLBCL90 assay16. Macrodissected samples were run twice, once using 5 µL of RNA stock concentration but no more than 300 ng of total RNA input and once using 5 µL of RNA stock diluted to match the RNA inputs of their respective non-dissected counterparts. The DLBCL90 results are outlined in Table 2.
DLBCL is comprised of 3 distinct cell of origin (COO) subtypes with different therapeutic responsiveness, namely GCB, ABC, and an intermediate group known as unclassified or UNC17,18. Translocations involving MYC, BCL2, and or BCL6 alone or in combination (double or triple hit) are also frequently observed in DLBCL, particularly in the GCB subtype19. The DLBCL90 assay is an expansion of its predecessor, the Lymph2Cx clinical assay, and is thus capable of DLBCL COO subtype determination but was principally developed to identify samples harboring double hit (DH) translocations involving BCL2 using digital gene expression as an alternative to fluorescence in-situ hybridization (FISH)16,20. The results in Table 2 show that macrodissection changed either the COO or the DHITsig status calls for 60% (3/5) of the samples examined.
Macrodissection of sample A had no effect on the COO call but changed the DHITsig call from NEG to UNCLASS, and this change was observed irrespective of the macrodissected sample RNA input and with similar probability scores (0.224, 0.254). In contrast, macrodissection of sample C had no effect on the DHITsig call but changed the COO call from GCB to UNC. Again, this change was observed irrespective of macrodissected sample RNA input. However, at 0.117, the COO call probability was closer to the call threshold of 0.1 for the macrodissected sample with reduced RNA input. Similar to sample A, macrodissection of sample E had no effect on the COO call but changed the DHITsig call. However, for sample E the call changed from UNCLASS to NEG and did so irrespective of the macrodissected sample RNA input with reasonably similar probability calls (0.849, 0.833). Notably, this call change to DHITsig NEG makes biological sense given that sample E was found to ABC-DLBCL, and double hit translocations involving BCL2 have been reported to be exclusively observed in GCB-DLBCL19.
<img alt="Microtome slicing and tissue preparation, histology workflow, water bath transfer process." class="xfigimg" src="/files/ftp_upload/62961/62961fig01.jpg" data-altupdatedat="1747911167000" data-alt="Figure 1"> 
Figure 1: Generating slide-mounted tissue sections using a microtome. (A) FFPE tissue block held in place by the microtome chuck and cut to produce a ribbon of sequential FFPE tissue sections. (B) Using pre-soaked wooden sticks, the ribbon is collected from the microtome and transferred to a warm water bath. (C) The warmth of the water helps to iron out the creases in the tissue ribbon. (D) Individual FFPE tissue sections are removed from the tissue ribbon by placing closed forceps at the junction of two sections and gently opening the forceps, which breaks sections away from one another. (E) Sections are collected from the water by submerging a glass slide at an angle and gently moving the side towards the tissue section until the edge of the section touches the glass slide. (F) Once the slide and section are touching, slowly remove the slide from the water, allowing the tissue section to fall flush against the slide. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62961/62961fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Microscopy technique; examining histology slides; optical microscope setup; tissue section analysis." class="xfigimg" src="/files/ftp_upload/62961/62961fig02.jpg" data-altupdatedat="1747911167000" data-alt="Figure 2"> 
Figure 2: Pathology and histological review of a hematoxylin and eosin (H&amp;E) stained sections. (A,B) The H&amp;E tissue section is subjected to microscopic review by a board-certified pathologist. (C,D) Once the pathologist has viewed the entire tissue and found that it is not 100% tumor tissue, the pathologist will use a marker to encircle the tumor area of the tissue. (E,F) Holding the marked H&amp;E against the original FFPE tissue block shows that not all the tissue is tumor material. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62961/62961fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Starch iodine test results, different sample reactions, grid layout, chemical analysis comparison." class="xfigimg" src="/files/ftp_upload/62961/62961fig03.jpg" data-altupdatedat="1747911167000" data-alt="Figure 3"> 
Figure 3: Tissue samples. This image demonstrates the pathologically reviewed and tumor marked H&amp;Es (Row 1), unprocessed slide-mounted FFPE tissue sections (Row 2), deparaffinized slide-mounted FFPE tissue sections (Row 3), deparaffinized slide-mounted FFPE tissue sections with pathology markings traced on the back of the slide (Row 4), deparaffinized and macrodissected slide-mounted FFPE tissue sections (Row 5) for the 5 samples (A-E) used to demonstrate this protocol. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62961/62961fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Tissue sectioning process; microtome; stained slides; histology preparation; sample analysis." class="xfigimg" src="/files/ftp_upload/62961/62961fig04.jpg" data-altupdatedat="1747911167000" data-alt="Figure 4"> 
Figure 4: Deparaffinization and macro-dissection of FFPE tissue sections: (A) In a fume hood, FFPE tissues mounted in a slide rack are washed in two d-limonene washes and one ethanol wash. (B,C) Post wash, all the paraffin has been removed, and only the tissue remains on the slide, which is now white and highly visible compared to its prewashed counterpart. (D) The deparaffinized slide-mounted tissue section is placed face down on the back of its matching marked H&amp;E. (E) The tumor area markings on the H&amp;E are then traced on the back of the deparaffinized slide using a fine or ultrafine nibbed permanent marker (F) The marked deparaffinized slide-mounted tissue section is then dipped in a glycerol wash to dampen the tissue section for collection. The slide is removed slowly from the glycerol, and the back of the slide wiped with a tissue to remove excess glycerol before laying the slide tissue face-up on the bench. (G) Using the flat side of a clean razor blade, the tissue is macrodissected, and the unwanted tissue outside of the pathologist markings is discarded before collecting the tissue of interest, which gathers along the edge of the blade. (H) A wooden stick is used to remove the collected tissue from the edge of the blade. (I) The tissue is then transferred to a pre-labeled microtube prefilled tissue digestion buffer and is ready for nucleic acid extraction. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62961/62961fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:font-size="7px" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2" style="min-width: 80px;">Sample ID</td>
			<td colspan="2" style="min-width: 80px;">Whole Tissue (a)</td>
			<td colspan="2" style="min-width: 80px;">Circled area of tissue (b)</td>
			<td rowspan="2" style="min-width: 80px;">Overall tumor content of whole tissue (c)</td>
			<td rowspan="2" style="min-width: 80px;">Fold increase in tumor content by macrodissection (d)</td>
			<td colspan="2" style="min-width: 80px;">Not macrodissected (e)</td>
			<td colspan="2" style="min-width: 80px;">Macrodissected (f)</td>
		</tr>
		<tr>
			<td style="min-width: 80px;">% Viable tumor</td>
			<td style="min-width: 80px;">% Other</td>
			<td style="min-width: 80px;">% Viable tumor</td>
			<td style="min-width: 80px;">% Other</td>
			<td style="min-width: 80px;"># of 5 µm slides extracted</td>
			<td style="min-width: 80px;">RNA conc (ng/µL)</td>
			<td style="min-width: 80px;"># of 5 µm slides extracted</td>
			<td style="min-width: 80px;">RNA conc 
			(ng/µL)</td>
		</tr>
		<tr>
			<td style="min-width: 80px;">Sample A</td>
			<td style="min-width: 80px;">60</td>
			<td style="min-width: 80px;">40</td>
			<td style="min-width: 80px;">75</td>
			<td style="min-width: 80px;">25</td>
			<td style="min-width: 80px;">45</td>
			<td style="min-width: 80px;">1.7</td>
			<td style="min-width: 80px;">2</td>
			<td style="min-width: 80px;">19.0</td>
			<td style="min-width: 80px;">4</td>
			<td style="min-width: 80px;">58.3</td>
		</tr>
		<tr>
			<td style="min-width: 80px;">Sample B</td>
			<td style="min-width: 80px;">60</td>
			<td style="min-width: 80px;">40</td>
			<td style="min-width: 80px;">65</td>
			<td style="min-width: 80px;">35</td>
			<td style="min-width: 80px;">39</td>
			<td style="min-width: 80px;">1.7</td>
			<td style="min-width: 80px;">1</td>
			<td style="min-width: 80px;">34.0</td>
			<td style="min-width: 80px;">2</td>
			<td style="min-width: 80px;">60.0</td>
		</tr>
		<tr>
			<td style="min-width: 80px;">Sample C</td>
			<td style="min-width: 80px;">40</td>
			<td style="min-width: 80px;">60</td>
			<td style="min-width: 80px;">65</td>
			<td style="min-width: 80px;">35</td>
			<td style="min-width: 80px;">26</td>
			<td style="min-width: 80px;">2.5</td>
			<td style="min-width: 80px;">1</td>
			<td style="min-width: 80px;">13.7</td>
			<td style="min-width: 80px;">2</td>
			<td style="min-width: 80px;">46.2</td>
		</tr>
		<tr>
			<td style="min-width: 80px;">Sample D</td>
			<td style="min-width: 80px;">35</td>
			<td style="min-width: 80px;">65</td>
			<td style="min-width: 80px;">90</td>
			<td style="min-width: 80px;">10</td>
			<td style="min-width: 80px;">32</td>
			<td style="min-width: 80px;">2.9</td>
			<td style="min-width: 80px;">1</td>
			<td style="min-width: 80px;">57.3</td>
			<td style="min-width: 80px;">2</td>
			<td style="min-width: 80px;">60.0</td>
		</tr>
		<tr>
			<td style="min-width: 80px;">Sample E</td>
			<td style="min-width: 80px;">20</td>
			<td style="min-width: 80px;">80</td>
			<td style="min-width: 80px;">30</td>
			<td style="min-width: 80px;">70</td>
			<td style="min-width: 80px;">6</td>
			<td style="min-width: 80px;">5.0</td>
			<td style="min-width: 80px;">3</td>
			<td style="min-width: 80px;">25.2</td>
			<td style="min-width: 80px;">3</td>
			<td style="min-width: 80px;">44.6</td>
		</tr>
	</tbody>
</table>
Table 1: Pathology review data. The table shows (a) the percentage of viable tumor in the whole tissue section by area, (b) the percentage of viable tumor in the area circled/marked by the pathologist during the review by cellularity, (c) the estimated overall tumor cellularity of the whole tissue (a x b), (d) the estimated fold increase in tumor cellularity achieved with macrodissection, (e and f) the number of 5 µm unstained FFPE slide-mounted tissue sections extracted and the resulting RNA concentrations for matched non-macrodissected and macrodissected samples. % Other refers to all other tissues present in a given sample that is not tumor tissue and can include connective tissue, stromal fibroblasts, blood vessels as well as other inherent stromal elements. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62961/Table%201-62961R3.xlsx" target="_blank">Please click here to download this Table.</a>
<table border="1" fo:font-size="8px" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Sample ID</td>
			<td>RNA input (ng)</td>
			<td>DLBCL90 COO call</td>
			<td>DLBCL90 call  probability</td>
			<td>DHITsig call</td>
			<td>DHITsig pos probability</td>
			<td>DHITsig neg probability</td>
		</tr>
		<tr>
			<td rowspan="5">Not macrodissected</td>
			<td>Sample A</td>
			<td>95.0</td>
			<td>GCB</td>
			<td>0.000</td>
			<td>NEG</td>
			<td>0.135</td>
			<td>0.865</td>
		</tr>
		<tr>
			<td>Sample B</td>
			<td>170.0</td>
			<td>GCB</td>
			<td>0.000</td>
			<td>NEG</td>
			<td>0.032</td>
			<td>0.968</td>
		</tr>
		<tr>
			<td>Sample C</td>
			<td>68.5</td>
			<td>GCB</td>
			<td>0.028</td>
			<td>NEG</td>
			<td>0.033</td>
			<td>0.967</td>
		</tr>
		<tr>
			<td>Sample D</td>
			<td>286.5</td>
			<td>ABC</td>
			<td>0.998</td>
			<td>NEG</td>
			<td>0.002</td>
			<td>0.998</td>
		</tr>
		<tr>
			<td>Sample E</td>
			<td>126.0</td>
			<td>ABC</td>
			<td>0.989</td>
			<td>UNCLASS</td>
			<td>0.212</td>
			<td>0.788</td>
		</tr>
		<tr>
			<td rowspan="5">Macrodissected</td>
			<td>Sample A_M</td>
			<td>291.7</td>
			<td>GCB</td>
			<td>0.000</td>
			<td>UNCLASS</td>
			<td>0.224</td>
			<td>0.776</td>
		</tr>
		<tr>
			<td>Sample B_M</td>
			<td>300.0</td>
			<td>GCB</td>
			<td>0.000</td>
			<td>NEG</td>
			<td>0.016</td>
			<td>0.984</td>
		</tr>
		<tr>
			<td>Sample C_M</td>
			<td>231.2</td>
			<td>UNCLASS</td>
			<td>0.210</td>
			<td>NEG</td>
			<td>0.015</td>
			<td>0.985</td>
		</tr>
		<tr>
			<td>Sample D_M</td>
			<td>300.0</td>
			<td>ABC</td>
			<td>0.999</td>
			<td>NEG</td>
			<td>0.002</td>
			<td>0.998</td>
		</tr>
		<tr>
			<td>Sample E_M</td>
			<td>223.2</td>
			<td>ABC</td>
			<td>0.987</td>
			<td>NEG</td>
			<td>0.151</td>
			<td>0.849</td>
		</tr>
		<tr>
			<td rowspan="5">Macrodissected &amp; RNA diluted</td>
			<td>Sample A_M</td>
			<td>95.0</td>
			<td>GCB</td>
			<td>0.000</td>
			<td>UNCLASS</td>
			<td>0.254</td>
			<td>0.746</td>
		</tr>
		<tr>
			<td>Sample B_M</td>
			<td>170.0</td>
			<td>GCB</td>
			<td>0.000</td>
			<td>NEG</td>
			<td>0.023</td>
			<td>0.977</td>
		</tr>
		<tr>
			<td>Sample C_M</td>
			<td>68.5</td>
			<td>UNCLASS</td>
			<td>0.117</td>
			<td>NEG</td>
			<td>0.027</td>
			<td>0.973</td>
		</tr>
		<tr>
			<td>Sample D_M</td>
			<td>286.5</td>
			<td>ABC</td>
			<td>0.999</td>
			<td>NEG</td>
			<td>0.002</td>
			<td>0.998</td>
		</tr>
		<tr>
			<td>Sample E_M</td>
			<td>126.0</td>
			<td>ABC</td>
			<td>0.995</td>
			<td>NEG</td>
			<td>0.167</td>
			<td>0.833</td>
		</tr>
	</tbody>
</table>
Table 2: DLBCL90 digital gene expression assay results. Five samples (A-E) were either not macrodissected or macrodissected before nucleic acid extractions were performed. The resulting RNA was run on the DLBCL90 assay, for which the maximum RNA input volume is 5 µL. Non-macrodissected samples were run using 5 µL of stock RNA. Each macrodissected sample was run twice using (a) 5 µL of stock RNA unless aliquots of 60 ng/µL were possible and (b) 5 µL of stock RNA diluted to match the concentrations/input of their non-macrodissected counterparts. The suffix _M denotes that that sample was macrodissected. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/62961/Table%202-62961R3.xlsx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Enhancing Tumor Content through Tumor Macrodissection at JoVE.com

Enhancing Tumor Content through Tumor Macrodissection

This protocol presents a method to increase the percent tumor content of formalin-fixed paraffin-embedded tissue samples.

The presence of contaminating non-tumor tissues in formalin-fixed paraffin-embedded (FFPE) tissues can greatly undermine genomic studies. Herein we ...

enhancing-tumor-content-through-tumor-macrodissection

Nanyang Technological University

Research

JoVE Journal

Biology

9.7K Views.  Mayo Clinic. Formaline-gefixeerde paraffine-ingebedde of FFPE-weefsels zijn vaak mengsels van tumor- en niet-tumormaterialen, waarbij de aanwezigheid van niet-tumormateriaal vaak ongewenst is en, indien aanwezig in een hoog percentage, de resultaten van genomische analyse aanzienlijk kan beïnvloeden, dus het belangrijkste voordeel van macrodissectie in vergelijking met het werken met niet-gereseceerde weefsels is dat de resulterende gedeparaffiniseerde gereseceerde weefselsecties kunnen worden verzameld ...

Video: Enhancing Tumor Content through Tumor Macrodissection

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 ...

Cancer Research

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.

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 ...

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 ...

Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts

Invading colorectal cancer (CRC) cells have acquired the capacity to break free from their sister cells, infiltrate the stroma, and remodel the extracellular matrix (ECM). Characterizing the biology of this phenotypically distinct group of cells could substantially improve our understanding of early events during the metastatic cascade.

Tumor invasion is a dynamic process facilitated by bidirectional interactions between malignant epithelium and the cancer associated stroma. In order to examine cell-specific responses at the tumor stroma-interface we have combined organotypic co-culture and laser micro-dissection techniques.
Organotypic models, in which key stromal constituents such as fibroblasts are 3-dimentioanally co-cultured with cancer epithelial cells, are highly manipulatable experimental tools which enable invasion and cancer-stroma interactions to be studied in near-physiological conditions.

Laser microdissection (LMD) is a technique which entails the surgical dissection and extraction of the various strata within tumor tissue, with micron level precision.
By combining these techniques with genomic, transcriptomic and epigenetic profiling we aim to develop a deeper understanding of the molecular characteristics of invading tumor cells and surrounding stromal tissue, and in doing so potentially reveal novel biomarkers and opportunities for drug development in CRC.&#160;&#160;&#160;

Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts

Molecular profiling of laser microdissected cells and stroma from synthetic, tissue-engineered colorectal cancer models represents a novel and manipulatable approach to characterize and dissect the distinctive biology at the interface between tumor cells at the invasive front and cancer associated stromal cells. &#160;

Invading colorectal cancer (CRC) cells have acquired the capacity to break free from their sister cells, infiltrate the stroma, and remodel the ...

Medicine

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Gliomas are primary brain tumors characterized by their invasiveness and heterogeneity. Specific histological patterns such as pseudopalisades, microvascular proliferation, mesenchymal transformation and necrosis characterize the histological heterogeneity of high-grade gliomas. Our laboratory has demonstrated that the presence of high densities of mesenchymal cells, named oncostreams, correlate with tumor malignancy. We have developed a unique approach to understand the mechanisms that underlie glioma&#39;s growth and invasion. Here, we describe a comprehensive protocol that utilizes laser capture microdissection (LMD) and RNA sequencing to analyze differential mRNA expression of intra-tumoral heterogeneous multicellular structures (i.e., mesenchymal areas or areas of tumor invasion). This method maintains good tissue histology and RNA integrity. Perfusion, freezing, embedding, sectioning, and staining were optimized to preserve morphology and obtain high-quality laser microdissection samples. The results indicate that perfusion of glioma bearing mice using 30% sucrose provides good morphology and RNA quality. In addition, staining tumor sections with 4% Cresyl violet and 0.5% eosin results in good nuclear and cellular staining, while preserving RNA integrity. The method described is sensitive and highly reproducible and it can be utilized to study tumor morphology in various tumor models. In summary, we describe a complete method to perform LMD that preserves morphology and RNA quality for sequencing to study the molecular features of heterogeneous multicellular structures within solid tumors.

Laser microdissection (LMD) is a sensitive and highly reproducible technique that can be used to uncover pathways that mediate glioma heterogeneity and invasion. Here, we describe an optimized protocol to isolate discrete areas from glioma tissue using laser LMD followed by transcriptomic analysis.

Gliomas are primary brain tumors characterized by their invasiveness and heterogeneity. Specific histological patterns such as pseudopalisades, ...

Neuroscience

Advanced CAD Imaging for Surgical Margin Analysis in Cancer Care

Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping

After oncologic resection of malignant tumors, specimens are sent to pathology for processing to determine the surgical margin status. These results are communicated in the form of a written pathology report. The current standard-of-care pathology report provides a written description of the specimen and the sites of margin sampling without any visual representation of the resected tissue. The specimen itself is typically destroyed during sectioning and analysis. This often leads to challenging communication between pathologists and surgeons when the final pathology report is confirmed. Furthermore, surgeons and pathologists are the only members of the multidisciplinary cancer care team to visualize the resected cancer specimen. We have developed a 3D scanning and specimen mapping protocol to address this unmet need. Computer-aided design (CAD) software is used to annotate the virtual specimen clearly showing sites of inking and margin sampling. This map can be utilized by various members of the multidisciplinary cancer care team.

Author Spotlight: 3D Scanning and Augmented Reality for Enhanced Cancer Surgery Communication

A novel method for 3D scanning and virtual mapping of cancer resections is proposed with the goal of improving communication among the multidisciplinary cancer care team.

After oncologic resection of malignant tumors, specimens are sent to pathology for processing to determine the surgical margin status. These results are ...

Transumbilical Endoscopic Resection of Intra-abdominal Mesenchymal Tumor

Gastrointestinal stromal tumors (GISTs) typically occur in the stomach and proximal small intestine but can also be found in any other part of the digestive tract, including the abdominal cavity, albeit rarely. In the present case, the tumor was resected endoscopically through the anterior gastric wall. Computed tomography (CT) scan and gastroscopy of a 60-year-old woman revealed submucosal lesions in the gastric body. The possibility of a stromal tumor was considered more likely. The endoscopic surgery was performed under endotracheal anesthesia. After a solution had been injected at the lesion site in the stomach, the entire gastric wall was dissected to expose the tumor. As the lesion was in the abdominal cavity and its base was attached to the abdominal wall, it was accessed using a sterilized PCF colonoscope. A sodium chloride injection was administered at the base. The tumor was then peeled along its boundaries using the hooking and excision knife combined with the precutting knife. Subsequently, the tumor was pulled into the stomach through the incision made in the stomach and then extracted externally through the upper digestive tract using the ERCP spiral mesh basket. After confirming the absence of bleeding at the incision site, the endoscope was returned to the stomach, and the stomach opening was closed using purse-string sutures. The patient recovered satisfactorily following the surgery and was discharged on day 4. Histological examination revealed a low-risk stromal tumor (spindle cell type, &lt;5 mitosis/50 high-power fields [HPF]). Immunohistochemistry revealed positive staining for CD34 and CD117, negative staining for SMA, positive staining for DOG1, and negative staining for S100. Additionally, the expression of ki67 was 3%.

The article introduces the surgical method, endoscopic submucosal dissection (ESD) for the complete removal of intra-abdominal tumors using natural orifice transluminal endoscopic surgery (NOTES). The procedure reaches the stomach by using gastrointestinal endoscopy, creating a controlled perforation for tumor removal, followed by stitching the gastric incision.

Gastrointestinal stromal tumors (GISTs) typically occur in the stomach and proximal small intestine but can also be found in any other part of the ...

Laser Microdissection: A Technique to Isolate Invading Colorectal Cancer cells from a 3D Organotypic Culture Model

Source: Bullock M. et al., <a href="https://www-jove-com.remotexs.ntu.edu.sg/v/51475"> Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and&#160;Ex vivo&#160;Fibroblasts.</a> J. Vis. Exp. (2014).
The video describes the laser dissection of the 3D organotypic co-culture model with micron-level precision. In 3D organotypic models, stromal constituents such as fibroblasts are 3-dimensionally co-cultured with cancer epithelial cells. The 3D model serves as an experimental tool that enables invasion and cancer-stroma interactions to be studied in near-physiological conditions.

Source: Bullock M. et al.,  Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and&#160;Ex ...

JoVE Encyclopedia of Experiments

Colorectal Cancer

Assays & techniques

An Adjuvant Therapy in a Mouse Model with an Incompletely Resected Subcutaneous Tumor

Source: Rwandamuriye, F. X. et al., <a href="https://app-jove-com.remotexs.ntu.edu.sg/v/60882">A Mouse Model of Incompletely Resected Soft Tissue Sarcoma for Testing (Neo)adjuvant Therapies.</a>&#160;J. Vis. Exp.&#160;(2020)
This video illustrates testing of adjuvant or additional therapy in a mouse model with incompletely resected subcutaneous tumors. The partially tumor-resected mouse is treated with an antibody targeting the anti-cytotoxic protein of T regulatory cells, potentially reducing tumor regrowth and suggesting effective adjuvant therapy.

All procedures involving animal models have been reviewed by the local institutional animal care committee and the JoVE veterinary review board.
1. ...

Immunology

Immunotherapy

Model Development and Disease Study

Fluorescence-guided Tumor Resection and MSC-seeded Scaffold Implantation in Murine Model: A Surgical Procedure to Deliver Therapeutic Mesenchymal Stem Cells into Brain Tumor Resection Cavity in Mouse Model

Source: Sheets, K. T. et al. <a href="https://www-jove-com.remotexs.ntu.edu.sg/video/57452" target="_blank">Image-Guided Resection of Glioblastoma and Intracranial Implantation of Therapeutic Stem Cell-seeded Scaffolds.</a>&#160;J. Vis. Exp.&#160;(2018)
This video presents the surgical procedure for image-guided tumor resection and implantation of a bio-scaffold seeded with genetically engineered mesenchymal stem cells or MSCs expressing tumor necrosis factor-related apoptosis-inducing ligand or TRAIL. These therapeutic MSCs have the potential in treatment of brain tumors.

Source: Sheets, K. T. et al. Image-Guided Resection of Glioblastoma and Intracranial Implantation of Therapeutic Stem Cell-seeded Scaffolds.&#160;J. Vis. ...

Enhancing Tumor Content through Tumor Macrodissection

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