Name: an integrated platform for genome-wide mapping of chromatin states using high-throughput chip-sequencing in tumor tissues
Uploaded: 2018-04-05T13:00:00
Description: Watch this Scientific Journal Video about An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues at JoVE.com

We thank Marcus Coyle, Curtis Gumbs, SMF core at MDACC for sequencing support. The work described in this article was supported by grants from the NIH grant (CA016672) to SMF Core and NCI awards (1K99CA160578 and R00CA160578) to K. R.

All clinical specimens were obtained following the guidelines of Institutional Review Board.
1. Buffer Preparation
<ol>
	<li>Make 200 mL of TE buffer (10 mM Tris-HCl, 10 mM ethylenediaminetetraacetic acid (EDTA) pH 8.0).</li>
	<li>Make 200 mL of STE buffer (10 mM Tris-HCl, 10 mM EDTA pH 8.0, 140 mM NaCl).</li>
	<li>Make 200 mL of 2.0 M glycine (37.52 g of glycine in 200 mL of water) and heat it to 65 &#176;C.</li>
	<li>Make 200 mL of 5% sodium deoxycholate (DOC) solution (10 g of DOC in 200 ...

<ol>
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This protocol describes a complete and comprehensive high-throughput ChIP-seq module for genome-wide mapping of chromatin states in human tumor tissues and cell lines. In any ChIP-seq protocol, one of the most important steps is antibody specificity. Here, this method illustrates immunoprecipitation conditions for the described six histone modifications, all of which are ChIP-grade and have been previously validated in our and other laboratories42,44,<...

The majority of mammalian genomes (98 - 99%) are comprised of noncoding sequence, and these nocoding regions contain regulatory elements known to participate in controlling gene expression and chromatin organization1,2. In a normal cell, the specific assembly of genomic DNA into compacted chromatin structure is critical for the spatial organization, regulation and precise timing of various DNA-associated processes3,4,5. In a cancer cell however, chromatin modifications by aberrant epigenetic mechanisms can lead to improper organization of chromatin structure, including access to regulatory elements, chromosomal looping systems, and gene expression patterns6,7,8,9,10.
Despite recent advances, we have limited understanding of epigenetic alterations that are associated with tumor progression or therapeutic response. The epigenome consists of an array of modifications, including histone marks and DNA methylation, which collectively form a dynamic state (referred to as chromatin state) that impinges upon gene expression networks and other processes critical for maintaining cellular identity. Recently, alterations in enhancers have been shown in multiple malignancies by studying H3K27Ac profiles11. Although such studies provide insight into the correlation of isolated epigenetic marks, more than 100 epigenetic modifications have been identified12,13 without clear understanding of their biological roles and interdependence. Furthermore, there are an even larger number of possible combinatorial patterns of these histone and DNA modifications, and it is these combinatorial patterns - not individual modifications - that dictate epigenetic states14. Hence, there is tremendous need to identify alterations in these chromatin states during cancer progression or responses to therapy. Comprehensive knowledge of epigenome alterations in cancers has been lagging in part due to technical (e.g. generation of large-scale data from small amount of clinical material/single cells) and analytical (e.g. algorithms to define combinatorial states) challenges. Therefore, there is critical need for robust high-throughput methods for profiling large number of histone modification marks from clinical material and easy-to-implement computational approaches to predict combinatorial patterns which will facilitate determination of epigenetic states associated with different stages of tumorigenesis and therapeutic resistance. Further, data available from recent epigenome profiling studies15,16,17,18,19,20,21,22,23 in normal tissues and cell lines can be integrated with chromatin profiles of tumors for further insights into epigenome contribution to tumor biology.
Chromatin profiling has become a powerful tool for identifying the global binding patterns of various chromatin modifications15,24. In recent years, ChIP-seq has become the &#34;gold standard&#34; for studying DNA-protein interactions on a global scale25,26,27. For any ChIP-seq experiment, there are critical steps necessary for its success, including tissue processing and disassociation, determing optimal sonication conditions, determing optimal antibody concentration for precipitation, library preparation, post-sequencing data processing, and downstream analysis. Each of these steps contain key quality control checkpoints, and when taken together, are crucial for properly identifying potential targets for functional validation. Through innovation in these steps, several prior studies have developed methodologies to perform ChIP or ChIP-Seq from small amount of tissues28,29,30,31,32. Further, some studies have suggested protocols for high-throughput ChIP experiments followed by PCR based quantitation33,34. Finally, some publically available analysis platforms for ChIP-Seq data are now available such as Easeq35 and Galaxy36. However, an integrated platform for performing ChIP-Seq in a high-throughput fashion in combination with a computational pipeline to perform single mark as well as chromatin state analyses has been lacking.
This protocol describes a complete and comprehensive ChIP-seq workflow for genome-wide mapping of chromatin states in tumor tissues and cell lines, with easy to follow guidelines encompassing all of the steps necessary for a successful experiment. By adopting a high-throughput method previously described by Blecher-Gonen et al.37, this protocol can be performed on dozens of samples in parallel and has been applied successfully on cancer cell lines and human tumors such as melanoma, colon, prostate, and glioblastoma multiforme. We demonstrate the methodology for six core histone modifications that represent key components of the epigenetic regulatory landscape in human melanoma cell lines and tumor samples. These modifications include H3K27ac (enhancers), H3K4me1 (active and poised enhancers), H3K4me3 (promoters), H3K79me2 (transcribed regions), H3K27me3 (polycomb repression), and H3K9me3 (heterochromatic repression). These marks can be used either alone or in combination to identify functionally distinct chromatin states representing both repressive and active domains.

<table>
	<tbody>
		<tr>
			<td>ChIP-grade H3K4me1 antibody</td>
			<td>Abcam</td>
			<td>ab8895</td>
			<td></td>
		</tr>
		<tr>
			<td>ChIP-grade H3K27ac antibody</td>
			<td>Abcam</td>
			<td>ab4729</td>
			<td></td>
		</tr>
		<tr>
			<td>ChIP-grade H3K4me3 antibody</td>
			<td>Abcam</td>
			<td>ab8580</td>
			<td></td>
		</tr>
		<tr>
			<td>ChIP-grade H3K79me2 antibody</td>
			<td>Abcam</td>
			<td>ab3594</td>
			<td></td>
		</tr>
		<tr>
			<td>ChIP-grade H3K27me3 antibody</td>
			<td>Abcam</td>
			<td>ab6002</td>
			<td></td>
		</tr>
		<tr>
			<td>ChIP-grade H3K9me3 antibody</td>
			<td>Abcam</td>
			<td>ab8898</td>
			<td></td>
		</tr>
		<tr>
			<td>1M Tris HCl, pH 8.0</td>
			<td>Teknova</td>
			<td>T1080</td>
			<td></td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>Sigma-Aldrich</td>
			<td>E9884</td>
			<td></td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>Sigma-Aldrich</td>
			<td>S7653</td>
			<td></td>
		</tr>
		<tr>
			<td>Glycine</td>
			<td>Sigma-Aldrich</td>
			<td>G8898</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium deoxycholate</td>
			<td>Sigma-Aldrich</td>
			<td>30970</td>
			<td></td>
		</tr>
		<tr>
			<td>DPBS</td>
			<td>Sigma - Life Sciences</td>
			<td>D8537-500ML</td>
			<td></td>
		</tr>
		<tr>
			<td>SDS</td>
			<td>Sigma-Aldrich</td>
			<td>74255</td>
			<td></td>
		</tr>
		<tr>
			<td>Triton-X</td>
			<td>Sigma-Aldrich</td>
			<td>X100-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>LiCl</td>
			<td>Sigma-Aldrich</td>
			<td>746460</td>
			<td></td>
		</tr>
		<tr>
			<td>NP-40</td>
			<td>Calbiochem</td>
			<td>492016-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>1% TWEEN-20</td>
			<td>Fisher Bioreagents</td>
			<td>BP337-500</td>
			<td></td>
		</tr>
		<tr>
			<td>BSA - IgG-free</td>
			<td>Sigma - Life Sciences</td>
			<td>A2058-5G</td>
			<td></td>
		</tr>
		<tr>
			<td>HBSS</td>
			<td>Gibo</td>
			<td>14025092</td>
			<td></td>
		</tr>
		<tr>
			<td>GentleMACS C tube</td>
			<td>GentleMACS</td>
			<td>120-008-466</td>
			<td>disassociation tube</td>
		</tr>
		<tr>
			<td>16% Formaldehyde</td>
			<td>Peierce</td>
			<td>28906</td>
			<td></td>
		</tr>
		<tr>
			<td>miniProtease inhibitor&#160;</td>
			<td>Roche Diagnostics</td>
			<td>11836153001</td>
			<td>protease inhibitor tablets</td>
		</tr>
		<tr>
			<td>Dynabeads Protein G&#160;</td>
			<td>Invitrogen</td>
			<td>10009D</td>
			<td></td>
		</tr>
		<tr>
			<td>Bioruptor NGS tubes 0.65 mL</td>
			<td>Diagenode</td>
			<td>C30010011</td>
			<td>sonication tubes</td>
		</tr>
		<tr>
			<td>DynaMag - 96 Side Skirted</td>
			<td>Invitrogen</td>
			<td>120.27</td>
			<td>96-well magnetic stand</td>
		</tr>
		<tr>
			<td>TE buffer</td>
			<td>Promega</td>
			<td>V6231</td>
			<td></td>
		</tr>
		<tr>
			<td>RNase A</td>
			<td>Invitrogen</td>
			<td>12091021</td>
			<td></td>
		</tr>
		<tr>
			<td>Proteinase K</td>
			<td>Invitrogen</td>
			<td>100005393</td>
			<td></td>
		</tr>
		<tr>
			<td>AMPure XP beads</td>
			<td>Beckman Coulter</td>
			<td>A63882</td>
			<td>paramagnetic beads</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>Sigma-Aldrich</td>
			<td>E7023</td>
			<td></td>
		</tr>
		<tr>
			<td>Qubit ds DNA High Sensitivity Assay Kit</td>
			<td>Invitrogen</td>
			<td>Q32854</td>
			<td>high sensitivity DNA reagents</td>
		</tr>
		<tr>
			<td>NEBNext Ultra II DNA Library Prep Kit</td>
			<td>New England BioLabs</td>
			<td>E7645L</td>
			<td>DNA Library Prep Kit</td>
		</tr>
		<tr>
			<td>Nuclease-free water</td>
			<td>Ambion</td>
			<td>AM9932</td>
			<td></td>
		</tr>
		<tr>
			<td>High sensitivity D1000 ScreenTape</td>
			<td>Agilent Technologies</td>
			<td>5067-5584</td>
			<td>high sensitivity DNA reagents</td>
		</tr>
		<tr>
			<td>High sensitivity D1000 reagents</td>
			<td>Agilent Technologies</td>
			<td>5067-5585</td>
			<td>high sensitivity DNA reagents</td>
		</tr>
		<tr>
			<td>Multiplex Oligos (Index primers- Set 1)</td>
			<td>New England BioLabs</td>
			<td>E7335L</td>
			<td>Multiplex Oligos&#160;</td>
		</tr>
		<tr>
			<td>Multiplex Oligos (Index primers- Set 2)</td>
			<td>New England BioLabs</td>
			<td>E7500L</td>
			<td>Multiplex Oligos&#160;</td>
		</tr>
		<tr>
			<td>TapeStation 4200</td>
			<td>Agilent Technologies</td>
			<td>G2991AA</td>
			<td>high sensitivity DNA electropherogram instrument</td>
		</tr>
		<tr>
			<td>Bioruptor Pico sonication device&#160;</td>
			<td>Diagenode</td>
			<td>B01060001</td>
			<td>water bath disruputor</td>
		</tr>
		<tr>
			<td>Mixer</td>
			<td>Nutator</td>
			<td>421105</td>
			<td></td>
		</tr>
		<tr>
			<td>Bio-Rad C1000 Touch Thermal Cycler</td>
			<td>Bio-Rad</td>
			<td>1851196</td>
			<td>PCR Thermal cycler</td>
		</tr>
		<tr>
			<td>Water Bath</td>
			<td>Fisher Scientific</td>
			<td>2322</td>
			<td></td>
		</tr>
		<tr>
			<td>Multichannel Pipet</td>
			<td>Denville</td>
			<td>1003123</td>
			<td></td>
		</tr>
		<tr>
			<td>Tube Revolver</td>
			<td>Thermo-Scientific</td>
			<td>88881001</td>
			<td></td>
		</tr>
		<tr>
			<td>96-Well Skirted Plate</td>
			<td>Eppendorf</td>
			<td>47744-110</td>
			<td></td>
		</tr>
		<tr>
			<td>Allegra X-12R Centrifuge&#160;</td>
			<td>Beckman Coulter</td>
			<td>A99464</td>
			<td>benchtop centrifuge</td>
		</tr>
		<tr>
			<td>Centrifuge 5424</td>
			<td>Eppendorf</td>
			<td>22620461</td>
			<td>tabletop centrifuge</td>
		</tr>
		<tr>
			<td>Optical tube strips (8x Strip)</td>
			<td>Agilent Technologies</td>
			<td>401428</td>
			<td></td>
		</tr>
		<tr>
			<td>Optical tube strip caps (8x strip)</td>
			<td>Agilent Technologies</td>
			<td>401425</td>
			<td></td>
		</tr>
		<tr>
			<td>Loading Tips, 10 Pk</td>
			<td>Agilent Technologies</td>
			<td>5067-5599</td>
			<td></td>
		</tr>
		<tr>
			<td>IKA MS3 vortex</td>
			<td>IKA</td>
			<td>3617000</td>
			<td>vortex</td>
		</tr>
	</tbody>
</table>

an integrated platform for genome-wide mapping of chromatin states using high-throughput chip-sequencing in tumor tissues

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.

This protocol allows the immunoprecipitation from frozen tumor tissues and cell lines that can be performed on dozens of samples in parallel using a high-throughput method (Figure 1A). Chromatin fragments should range between ~200 - 1000 bps for optimal immunoprecipitation. We have noted that the time needed to achieve same shearing length differs for different tissue and cell types. The success of ChIP from small amounts of tissue depends on...

Watch this Scientific Journal Video about An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues at JoVE.com

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Here, we describe an optimized high-throughput ChIP-sequencing protocol and computational analyses pipeline for the determination of genome-wide chromatin state patterns from frozen tumor tissues and cell lines.

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of ...

The overall goal of this protocol is to unbiasedly identify combinatorial chromatin state patterns in tumor tissues and cancer cell lines. This method could help answer key questions in the cancer epigenetics field such as how a barren histone modification states could contribute to tumor genesis. The main advantage of this technique is that multiple histone modifications, as well as multiple samples could be processed both simultaneously, as well as efficiently.First, dissociate 50 milligrams of melanoma tissue manually and two milliliters of Hank's Balanced Salt Solution or HBSS, using a sterile razor blade. Mince the tissue into three or four millimeter pieces for approximately five minutes in a sterile tissue culture dish. Transfer the tissue solution to a dissociator tube and add another eighth milliliters of HBSS.Further dissociate the tissue, using a dissociator, until homogenized. Next, crosslink the tissue, adding 200 microliters of 16%formaldehyde per three milliliters of HBSS. Using a mixer, shake the mixture at 10 rpms for exactly 10 minutes at 37 degrees Celsius.After removing the sample from the incubator, add 200 microliters of tumoral glycine per three milliliters of sample and shake the mixture at 10 rpms for five minutes at 37 degrees Celsius. Spin the sample at 934 times g for five minutes at four degrees Celsius using a bench top centrifuge. When finished, remove the supernatant and add five milliliters of ice cold PBS.Then, centrifuge the sample again at 934 times g then remove the supernatant. Add 300 microliters of ChIP harvest buffer with protease inhibitors per 50 milligrams of tissue and lyse the samples for 30 minutes on ice. While the cells are lysing, turn on the water bath disruptor and associated cooling system and allow the temperature to reach four degrees Celsius.Place the sonicator tube in the water bath disruptor and sonicate the melanoma tissue for 60 cycles at 30 seconds on and 30 seconds off to obtain chromatin fragments of 200 to 600 base pairs. For eight milligrams of melanoma tissue, incubate three micrograms of each histone antibody with 20 microliters of protein g magnetic beads and 100 microliters of binding blocking buffer for two hours at four degrees Celsius with rotation, using a tube revolver. After sonication, dilute the sample five times using ChIP dilution buffer to bring the SDS concentration down to 0.1%After incubation of the antibody and protein g magnetic beads is complete, remove the ChIP dilution buffer and re suspend the beads in 240 microliters of the fresh buffer.Then, place 20 microliters aliquots of the beads into 12 separate tubes, each of which will be used for a separate tissue sample. Aliquot the sonicated material evenly to the protein g beads with specific antibody and rotate the tubes using a tube revolver overnight at four degrees Celsius. On the morning after reverse cross linking, transfer the antibody protein solution to a 96 well plate and place it on a magnetic stand.After allowing the beads to adhere for at least 30 seconds, remove the supernatant. Wash the beads five times with 150 microliters of ice cold RIPA wash buffer using a multi channel pipette. Move the magnet continuously for 30 seconds per wash, then remove the supernatant.After the washing steps, add an elution buffer master mix, containing 44 microliters of direct elution buffer, one microliter of Rnase and five microliters of protenase k per chip and input the sample for reverse cross linking. Incubate the samples using a PCR thermal cycler for four hours at 37 degrees Celsius, four hours at 50 degrees Celsius and eight to 16 hours at 65 degrees Celsius. On the next morning, place the samples back on the magnet and transfer the supernatant to a new 96 well PCR plate which contains the amino precipitated DNA.Add 2.3 x paramagnetic beads to the solution and carefully pipette up and down 25 times using a multi channel pipette. Following this, incubate at room temperature for four minutes. Then place the samples back on the magnet and incubate at room temperature for another four minutes.After discarding the supernatant, add 150 microliters of 70%ethanol to the samples and incubate at room temperature for 30 seconds without disturbing the beads. After allowing the beads to dry, remove the samples from the magnet and add 30 microliters of 10 millimolar traceal. Mix by pipetting 25 times.After incubating the samples at room temperature, place them back on the magnet and incubate at room temperature for another four minutes. Transfer 20 microliters of each sample to a new 96 well plate for library preparation. After PCR amplification, remove the samples and bring the total volume to 100 microliters using nucleus free water.Perform double sided paramagnetic size selection by first adding 55 microliters of beads to each sample and mixing 25 times with a pipette. Then incubate at room temperature for four minutes. Place the samples back on the magnet and incubate at room temperature for another four minutes to attain large fragments on the beads that are unsuitable for sequencing.After incubation, transfer the supernatant to a new 96 well PCR plate. Add another 25 microliters of paramagnetic beads and mix by pipetting 25 times and incubate at room temperature off the magnet for four minutes. After incubating at room temperature, place the samples back on the magnet and incubate at room temperature for four minutes.Then discard the supernatant. While leaving the samples on the magnet, add 150 microliters of 70%ethanol and incubate at room temperature for 30 seconds without disturbing the beads. Remove the ethanol and repeat the wash.After allowing the beads to dry, remove the samples from the magnet and add 25 microliters of 10 millimolar traceal pH 8.0. Mix by pipetting 25 times and incubate at room temperature, off the magnet for four minutes. After incubating at room temperature, place the samples back on the magnet and incubate at room temperature for four minutes.Now, quantify the libraries using a high sensitivity DNA electropherogram instrument before multiplexing to ensure the sizes are suitable for sequencing. This protocol allows immunoprecipitation of frozen tumor tissues and cell lines that can be performed on dozens of samples and parallel using a high throughput method. Chromatin fragments should range between 200 and 1000 base pairs for optimal immunoprecipitation.Purified ChIP DNA should be quantified before proceeding to library preparation. Completed libraries suitable for multiplexing and next generation sequencing should range between 200 and 600 base pairs and be devoid of any primer dimers. Upon post sequencing, there are many quality control metrics that should be met before proceeding to further steps of the pipeline, such as macs peak calling and chromHmm analysis.ChIP samples should be enriched over input DNA and each histone modification should display a distinct profile representing a specific component of the epigenetic landscape. The chrome HMM algorithm uses a Multivariate Hidden Markov Model to identify the most prominent reoccurring combinatorial and spacial chromatin patterns based on the histone modifications studied. Using these six modifications, chrome HMM identifies functionally distinct chromatin states representing both repressive and active domains, such as polycomb repression, heterochromatic repression, active transcription, and active enhancers.Once mastered, this technique can be done in three to four days, if it's performed properly. While attempting this procedure, it's important to determine optimal sonication conditions and specification for antibodies before continuing to library preparation and data analysis. For learning this procedure, other methods, such as RRS sequencing and chromosome confirmation capture can be performed to determine coalition of chromatin state parts with gene expression and higher chromatin structure.After the experiment, the technique has paved way for researchers in cancer epigenetics field to explore chromatin state patterns in patient tumor samples. After watching this video, you should have a good understanding of how to process and disassociate tumor tissues, perform chromatin immunoprecipitation, prepare libraries for nextgen sequecing, process post sequencing data and gain insights into initial steps of downstream analysis. Don't forget that when working with formaldehyde, it can be extremely hazardous and precautions, such as an appropriate fume hood, should always be taken when performing this procedure.

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Research

JoVE Journal

Cancer Research

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

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

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

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

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

The Establishment of a Lung Colonization Assay for Circulating Tumor Cell Visualization in Lung Tissues

Metastasis is the major cause of cancer death. The role of circulating tumor cells (CTCs) in promoting cancer metastasis, in which lung colonization by CTCs critically contributes to early lung metastatic processes, has been vigorously investigated. As such, animal models are the only approach that captures the full systemic process of metastasis. Given that problems occur in previous experimental designs for examining the contributions of CTCs to blood vessel extravasation, we established an in vivo lung colonization assay in which a long-term-fluorescence cell-tracer, carboxyfluorescein succinimidyl ester (CFSE), was used to label suspended tumor cells and lung perfusion was performed to clear non-specifically trapped CTCs prior to lung removal, confocal imaging, and quantification. Polymeric fibronectin (polyFN) assembled on CTC surfaces has been found to mediate lung colonization in the final establishment of metastatic tumor tissues. Here, to specifically test the requirement of polyFN assembly on CTCs for lung colonization and extravasation, we performed short term lung colonization assays in which suspended Lewis lung carcinoma cells (LLCs) stably expressing FN-shRNA (shFN) or scramble-shRNA (shScr) and pre-labeled with 20 &#956;M of CFSE were intravenously inoculated into C57BL/6 mice. We successfully demonstrated that the abilities of shFN LLC cells to colonize the mouse lungs were significantly diminished in comparison to shScr LLC cells. Therefore, this short-term methodology may be widely applied to specifically demonstrate the ability of CTCs within the circulation to colonize the lungs.

An animal model is needed to decipher the role of circulating tumor cells (CTCs) in promoting lung colonization during cancer metastasis. Here, we established and successfully performed an in vivo assay to specifically test the requirement of polymeric fibronectin (polyFN) assembly on CTCs for lung colonization.

Metastasis is the major cause of cancer death. The role of circulating tumor cells (CTCs) in promoting cancer metastasis, in which lung colonization by ...

Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy

High-throughput genome-wide RNAi (RNA interference) screening technology has been widely used for discovering host factors that impact&#160;virus replication. Here we present the application of this technology to uncovering host targets that specifically modulate the replication of Maraba virus, an oncolytic rhabdovirus, and vaccinia virus with the goal of enhancing therapy. While the protocol has been tested for use with oncolytic Maraba virus and oncolytic vaccinia virus, this approach is applicable to other oncolytic viruses and can also be utilized for identifying host targets that modulate virus replication in mammalian cells in general. This protocol describes the development and validation of an assay for high-throughput RNAi screening in mammalian cells, the key considerations and preparation steps important for conducting a primary high-throughput RNAi screen, and a step-by-step guide for conducting a primary high-throughput RNAi screen; in addition, it broadly outlines the methods for conducting secondary screen validation and tertiary validation studies. The benefit of high-throughput RNAi screening is that it allows one to catalogue, in an extensive and unbiased fashion, host factors that modulate any aspect of virus replication for which one can develop an in vitro assay such as infectivity, burst size, and cytotoxicity. It has the power to uncover biotherapeutic targets unforeseen based on current knowledge.

Here we describe a protocol for employing high-throughput RNAi screening to uncover host targets that can be manipulated to enhance oncolytic virus therapy, specifically rhabodvirus and vaccinia virus therapy, but it can be readily adapted to other oncolytic virus platforms or for discovering host genes that modulate virus replication generally.

High-throughput genome-wide RNAi (RNA interference) screening technology has been widely used for discovering host factors that impact&#160;virus ...

Native Chromatin Immunoprecipitation Using Murine Brain Tumor Neurospheres

Epigenetic modifications may be involved in the development and progression of glioma. Changes in methylation and acetylation of promoters and regulatory regions of oncogenes and tumor suppressors can lead to changes in gene expression and play an important role in the pathogenesis of brain tumors. Native chromatin immunoprecipitation (ChIP) is a popular technique that allows the detection of modifications or other proteins tightly bound to DNA. In contrast to cross-linked ChIP, in native ChIP, cells are not treated with formaldehyde to covalently link protein to DNA. This is advantageous because sometimes crosslinking may fix proteins that only transiently interact with DNA and do not have functional significance in gene regulation. In addition, antibodies are generally raised against unfixed peptides. Therefore, antibody specificity is increased in native ChIP. However, it is important to keep in mind that native ChIP is only applicable to study histones or other proteins that bind tightly to DNA. This protocol describes the native chromatin immunoprecipitation on murine brain tumor neurospheres.

Epigenetic mechanisms are frequently altered in glioma. Chromatin immunoprecipitation could be used to study the consequences of genetic alterations in glioma that result from changes in histone modifications which regulate chromatin structure and gene transcription. This protocol describes native chromatin immunoprecipitation on murine brain tumor neurospheres.

Epigenetic modifications may be involved in the development and progression of glioma. Changes in methylation and acetylation of promoters and regulatory ...

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is exposed to in vivo. Solid tumors grow not as a sheet attached to plastic, but instead as a collection of clonal cells in a three-dimensional (3D) space interacting with their neighbors, and with distinct spatial properties such as the disruption of normal cellular polarity. These interactions cause 3D-cultured cells to acquire morphological and cellular characteristics which are more relevant to in vivo tumors. Additionally, a tumor mass is in direct contact with other cell types such as stromal and immune cells, as well as the extracellular matrix from all other cell types. The matrix deposited is comprised of macromolecules such as collagen and fibronectin.
In an attempt to increase the translation of research findings in oncology from bench to bedside, many groups have started to investigate the use of 3D model systems in their drug development strategies. These systems are thought to be more physiologically relevant because they attempt to recapitulate the complex and heterogeneous environment of a tumor. These systems, however, can be quite complex, and, although amenable to growth in 96-well formats, and some now even in 384, they offer few choices for large-scale growth and screening. This observed gap has led to the development of the methods described here in detail to culture tumor spheroids in a high-throughput capacity in 1536-well plates. These methods represent a compromise to the highly complex matrix-based systems, which are difficult to screen, and conventional 2D assays. A variety of cancer cell lines harboring different genetic mutations are successfully screened, examining compound efficacy by using a curated library of compounds targeting the Mitogen-Activated Protein Kinase or MAPK pathway. The spheroid culture responses are then compared to the response of cells grown in 2D, and differential activities are reported. These methods provide a unique protocol for testing compound activity in a high-throughput 3D setting.

Across a wide variety of disease indications, more physiologically relevant models are being developed and implemented into drug discovery programs. The new model system described here demonstrates how three-dimensional tumor spheroids can be cultured and screened in a high-throughput 1536-well plate-based system to search for new oncology drugs.

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is ...

Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as tumors. Because digital polymerase chain reactions (PCR) enable the precise quantification of DNA copy number variants, they are becoming an essential tool for detecting rare genetic variations, such as drug-resistant mutations. It is expected that molecular diagnoses using digital PCR (dPCR) will be available in clinical practice in the near future; thus, how to efficiently conduct dPCR with human genetic material is a hot topic. Here, we introduce a method to detect Adenomatous polyposis coli (APC) somatic mosaicism using dPCR with the chip-in-a-tube format, which allows eight dPCR reactions to be simultaneously conducted. Care should be taken when filling and sealing the reaction mixture on the chips. This article demonstrates how to avoid the over- and underestimation of positive partitions. Furthermore, we present a simple procedure for collecting the dPCR product from the partitions on the chips, which can then be used to confirm the specific amplification. We hope that this methods report will help promote the dPCR with the chip-in-a-tube method in genetic research.

Digital polymerase chain reaction (PCR) is a useful tool for the high-sensitivity detection of single nucleotide variants and DNA copy number variants. Here, we demonstrate key considerations for measuring rare variants in the human genome using digital PCR with the chip-in-a-tube format.

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as ...

In Vitro Assay to Study Tumor-macrophage Interaction

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

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

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

Establishment and Characterization of Small Bowel Neuroendocrine Tumor Spheroids

Small bowel neuroendocrine tumors (SBNETs) are rare cancers originating from enterochromaffin cells of the gut. Research in this field has been limited because very few patient derived SBNET cell lines have been generated. Well-differentiated SBNET cells are slow growing and are hard to propagate. The few cell lines that have been established are not readily available, and after time in culture may not continue to express characteristics of NET cells. Generating new cell lines could take many years since SBNET cells have a long doubling time and many enrichment steps are needed in order to eliminate the rapidly dividing cancer-associated fibroblasts. To overcome these limitations, we have developed a protocol to culture SBNET cells from surgically removed tumors as spheroids in extracellular matrix (ECM). The ECM forms a 3-dimensional matrix that encapsulates SBNET cells and mimics the tumor micro-environment for allowing SBNET cells to grow. Here, we characterized the growth rate of SBNET spheroids and described methods to identify SBNET markers using immunofluorescence microscopy and immunohistochemistry to confirm that the spheroids are neuroendocrine tumor cells. In addition, we used SBNET spheroids for testing the cytotoxicity of rapamycin.

Neuroendocrine tumors (NETs) originate from neuroendocrine cells of the neural crest. They are slow growing and challenging to culture. We present an alternative strategy to grow NETs from the small bowel by culturing them as spheroids. These spheroids have small bowel NET markers and can be used for drug testing.

Small bowel neuroendocrine tumors (SBNETs) are rare cancers originating from enterochromaffin cells of the gut. Research in this field has been limited ...

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer

DNA methylation is an important epigenetic change that is biologically meaningful and a frequent focus of cancer research. Genome-wide DNA methylation is a useful measure to provide an accurate analysis of the methylation status of gastrointestinal (GI) malignancies. Given the multiple potential translational uses of DNA methylation analysis, practicing clinicians and others new to DNA methylation studies need to be able to understand step by step how these genome-wide analyses are performed. The goal of this protocol is to provide a detailed description of how this method is used for the biomarker identification in GI malignancies. Importantly, we describe three critical steps that are needed to obtain accurate results during genome-wide analysis. Clearly and concisely written, these three methods are often lacking and not noticeable to those new to epigenetic studies. We used 48 samples of a GI malignancy (gastric cancer) to highlight practically how genome-wide DNA methylation analysis can be performed for GI malignancies.

Herein, we describe a procedure for genome-wide analysis of DNA methylation in gastrointestinal cancers. The procedure is of relevance to studies that investigate relationships between methylation patterns of genes and factors contributing to carcinogenesis in gastrointestinal cancers.

DNA methylation is an important epigenetic change that is biologically meaningful and a frequent focus of cancer research. Genome-wide DNA methylation is ...

Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable preclinical models that can accurately predict patient responses. One of the disadvantages of existing preclinical models is the inability to contextually preserve the human tumor microenvironment (TME) and accurately represent intratumoral heterogeneity, thus limiting the clinical translation of data. By contrast, by representing the culture of live fragments of human tumors, the patient-derived explant (PDE) platform allows drug responses to be examined in a three-dimensional (3D) context that mirrors the pathological and architectural features of the original tumors as closely as possible. Previous reports with PDEs have documented the ability of the platform to distinguish chemosensitive from chemoresistant tumors, and it has been shown that this segregation is predictive of patient responses to the same chemotherapies. Simultaneously, PDEs allow the opportunity to interrogate molecular, genetic, and histological features of tumors that predict drug responses, thereby identifying biomarkers for patient stratification as well as novel interventional approaches to sensitize resistant tumors. This paper reports PDE methodology in detail, from collection of patient samples through to endpoint analysis. It provides a detailed description of explant derivation and culture methods, highlighting bespoke conditions for particular tumors, where appropriate. For endpoint analysis, there is a focus on multiplexed immunofluorescence and multispectral imaging for the spatial profiling of key biomarkers within both tumoral and stromal regions. By combining these methods, it is possible to generate quantitative and qualitative drug response data that can be related to various clinicopathological parameters and thus potentially be used for biomarker identification.

This paper describes methods for the generation, drug treatment, and analysis of patient-derived explants for assessing tumor drug responses in a live, patient-relevant, preclinical model system.

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable ...