Name: detection of rare mutations in ctdna using next generation sequencing
Uploaded: 2017-08-24T15:00:00
Description: Watch this Scientific Journal Video about Detection of Rare Mutations in CtDNA Using Next Generation Sequencing at JoVE.com

This work is supported by Geneplus&#8211;Beijing Institute.

Tumor specimens and blood samples were obtained according to a protocol approved by the Ethics Committee of Peking University People&#39;s Hospital. Written informed consent was obtained from the patients to use their samples. Participants were screened according to the following criteria: female, advanced Non-Small Cell Lung Cancer, EGFR p.L858R mutation indicated by previous Sanger Sequencing, disease progression following two session of EGFR targeted therapy with Erlotinib, and ER-Seq which was applied to ctDNA to ana...

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Transl. Med. 4, (2012).</li><li>Kobayashi, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EGFR+mutation+and+resistance+of+non-small-cell+lung+cancer+to+gefitinib.">EGFR mutation and resistance of non-small-cell lung cancer to gefitinib.</a> N. Engl. J. Med. 352, 786-792 (2005).</li><li>Kuang, Y., Rogers, A., Yeap, Y., Wang, L., Makrigiorgos, M., Vetrand, K., Thiede, S., Distel, R. J., Ja&#776;nne, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Noninvasive+detection+of+EGFR+T790M+in+gefitinib+or+erlotinib+resistant+non-small+cell+lung+cancer.">Noninvasive detection of EGFR T790M in gefitinib or erlotinib resistant non-small cell lung cancer.</a> Clin. Cancer Res. 15, 2630-2636 (2009).</li><li>Taniguchi, K., Uchida, J., Nishino, K., Kumagai, T., Okuyama, T., Okami, J., Higashiyama, M., Kodama, K., Imamura, F., Kato, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+detection+of+EGFR+mutations+in+circulating+tumor+DNA+derived+from+lung+adenocarcinomas.">Quantitative detection of EGFR mutations in circulating tumor DNA derived from lung adenocarcinomas.</a> Clin. Cancer Res. 17, 7808-7815 (2011).</li><li>Leary, R. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+personalized+tumor+biomarkers+using+massively+parallel+sequencing.">Development of personalized tumor biomarkers using massively parallel sequencing.</a> Sci. Transl. 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The existence of circulating tumor DNA (ctDNA) was discovered more than 30 years ago, however the application of ctDNA analyses is still not routine in clinical practice. Interest in the practical application of ctDNA methods has increased with the development of technologies for ctDNA detection and analysis. Tumor monitoring with ctDNA offers a minimally-invasive approach for the assessment of microscopic residual disease, response to therapy, and tumor molecular profiles under the background of tumor evolution and intr...

Next-generation sequencing (NGS), a powerful tool to investigate the mysteries of the genome, can provide a large quantity of information, which may reveal genetic alterations. The application of NGS analysis in the clinic has become more common, especially for personalized medicine. One of the greatest limitations of NGS, however, is a high error rate. Although it is deemed suitable for studying inherited mutations, the analysis of rare mutations is greatly limited1,2, especially when analyzing DNA obtained from a &#34;liquid biopsy&#34;.
Circulating tumor DNA (ctDNA) is cell-free DNA (cfDNA) in the blood that is shed from tumor cells. In most cases, the quantity of ctDNA is extremely low, which make its detection and analysis very challenging. However, ctDNA has many attractive features: its isolation is minimally invasive, it can be detected in the early stages of tumor growth, the ctDNA level reflects therapeutic efficiency, and ctDNA contains DNA mutations found in both primary and metastatic lesions3,4,5. Therefore, given the rapid development of the NGS technique and analysis, the application of ctDNA detection has become more attractive.
Different massively parallel sequencing approaches have been utilized for ctDNA detection but none of these approaches have been accepted for routine use in clinics due to their limitations: low sensitivity, lack of versatility, and a relatively high cost6,7,8. For example, duplex sequencing, based on a unique identifier tag (UID), repeatedly corrects errors in the consensus bidirectionally, rectifying most sequencing errors. However, the feasibility of this method is lost due to its high cost and low data utilization9,10. Similarly, CAPP-Seq and its improved iteration, CAPP-IDES11,12, have greater practicality in cfDNA detection, though the accuracy and universality of these methods need improvement.
To meet the current need for accurate ctDNA detection and analysis, we developed a new strategy, Enrich Rare Mutation Sequencing (ER-Seq). This approach combines the following: unique sequencing adapters to efficiently recover ctDNA molecules, with bidirectional error correction and the ability to distinguish a single mutation out of &#62; 1 &#215; 107 wild-type nucleotides; 1021 kb probes which enrich measurement of target regions that cover over 95% of the tumor-related mutations from 12 tumors, including lung cancer, colorectal cancer, gastric cancer, breast cancer, kidney cancer, pancreatic cancer, liver cancer, thyroid cancer, cervical cancer, esophageal cancer, and endometrial carcinoma (Table 1); and baseline database screening making it efficient and easy to precisely detect rare mutations in ctDNA.
To build a baseline database, find all the gene mutations by ER-Seq from a number of the same type of samples (~1000 at the beginning). These real mutations must be verified by several other reliable detection methods and analysis. Next, summarize the pattern of false mutations and cluster all the false mutations to build the initial baseline database. Continue adding false mutations found from subsequent sequencing experiments to this database. Therefore, this baseline database becomes a dynamic expanded database, which significantly improves sequencing accuracy.
To promote progress in tumor diagnosis and monitoring, we present ER-Seq, a low cost and feasible method for the acquisition of universal data. We present a case study which underwent ER-Seq analysis, demonstrating its accuracy for detecting rare mutations and feasibility for use in the clinic.

<table>
	<tbody>
		<tr>
			<td>QIAamp Circulating Nucleic Acid Kit</td>
			<td>Qiagen</td>
			<td>55114</td>
			<td>DNA Extraction from Peripheral Blood for cfDNA</td>
		</tr>
		<tr>
			<td>QIAamp DNA Blood Mini Kit</td>
			<td>Qiagen</td>
			<td>51105</td>
			<td>DNA Extraction from Peripheral Blood for gDNA</td>
		</tr>
		<tr>
			<td>Quant-iT dsDNA HS Assay Kit</td>
			<td>Invitrogen</td>
			<td>Q32854</td>
			<td>Measure cfDNA concentration</td>
		</tr>
		<tr>
			<td>Quant-iT dsDNA BR Assay Kit</td>
			<td>Invitrogen</td>
			<td>Q32853</td>
			<td>Measure library concentration</td>
		</tr>
		<tr>
			<td>Agilent DNA 1000 Reagents</td>
			<td>Agilent</td>
			<td>5067-1504</td>
			<td>Measure cfDNA and library fragments</td>
		</tr>
		<tr>
			<td>The NEBNext UltraII DNA Library Prep Kit for Illumina</td>
			<td>NEB</td>
			<td>E7645L</td>
			<td>Library Preparation</td>
		</tr>
		<tr>
			<td>Agencourt SPRIselect Reagent</td>
			<td>Beckman</td>
			<td>B23317</td>
			<td>DNA fragment screening and purification</td>
		</tr>
		<tr>
			<td>Tris-HCl (10 mM, pH 8.0)-100ML</td>
			<td>Sigma</td>
			<td>93283</td>
			<td>Dissolution</td>
		</tr>
		<tr>
			<td>xGen Lockdown Probes</td>
			<td>IDT</td>
			<td>&#8212;&#8212;</td>
			<td>xGen Custom Probe</td>
		</tr>
		<tr>
			<td>Human Cot-1 DNA</td>
			<td>Life</td>
			<td>15279-011</td>
			<td>Targeted DNA capture</td>
		</tr>
		<tr>
			<td>Dynabeads M-270 Streptavidin</td>
			<td>Life</td>
			<td>65305</td>
			<td>Targeted DNA capture</td>
		</tr>
		<tr>
			<td>xGen Lockdown Reagents</td>
			<td>IDT</td>
			<td>1072281</td>
			<td>Targeted DNA capture</td>
		</tr>
		<tr>
			<td>KAPA HiFi HotStart ReadyMix</td>
			<td>KAPA</td>
			<td>KK2602</td>
			<td>post-capture PCR enrichment libraries</td>
		</tr>
		<tr>
			<td>KAPA Library Quantification Kit</td>
			<td>KAPA</td>
			<td>KK4602</td>
			<td>Measure library concentration</td>
		</tr>
		<tr>
			<td>NextSeq 500 High Output Kit v2((150 cycles)</td>
			<td>illumina</td>
			<td>FC-404-2002</td>
			<td>Sequence</td>
		</tr>
		<tr>
			<td>Centrifuge5810</td>
			<td>eppendorf</td>
			<td>5810</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanodrop8000</td>
			<td>Thermo Scientific</td>
			<td>8000</td>
			<td>Measure gDNA concentration</td>
		</tr>
		<tr>
			<td>Qubit 2.0</td>
			<td>Invitrogen</td>
			<td></td>
			<td>Quantify</td>
		</tr>
		<tr>
			<td>Agilent 2100 Bioanalyzer</td>
			<td>Agilent</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>ThermoMixer C</td>
			<td>eppendorf</td>
			<td></td>
			<td>Incubation</td>
		</tr>
		<tr>
			<td>16-tube DynaMagTM-2 Magnet</td>
			<td>Life</td>
			<td>12321D</td>
			<td></td>
		</tr>
		<tr>
			<td>Concentrator plus</td>
			<td>eppendorf</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>PCR</td>
			<td>AB</td>
			<td>simplyamp</td>
			<td></td>
		</tr>
		<tr>
			<td>QPCR</td>
			<td>AB</td>
			<td>7500Dx</td>
			<td></td>
		</tr>
		<tr>
			<td>NextSeq 500</td>
			<td>illumina</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

detection of rare mutations in ctdna using next generation sequencing

The analysis of circulating tumor DNA (ctDNA) using next-generation sequencing (NGS) has become a valuable tool for the development of clinical oncology. However, the application of this method is challenging due to its low sensitivity in analyzing the trace amount of ctDNA in the blood. Furthermore, the method may generate false positive and negative results from this sequencing and subsequent analysis. To improve the feasibility and reliability of ctDNA detection in the clinic, here we present a technique which enriches rare mutations for sequencing, Enrich Rare Mutation Sequencing (ER-Seq). ER-Seq can distinguish a single mutation out of 1 x 107 wild-type nucleotides, which makes it a promising tool to detect extremely low frequency genetic alterations and thus will be very useful in studying disease heterogenicity. By virtue of the unique sequencing adapter&#39;s ligation, this method enables an efficient recovery of ctDNA molecules, while at the same time correcting for errors bidirectionally (sense and antisense). Our selection of 1021 kb probes enriches the measurement of target regions that cover over 95% of the tumor-related driver mutations in 12 tumors. This cost-effective and universal method enables a uniquely successful accumulation of genetic data. After efficiently filtering out background error, ER-seq can precisely detect rare mutations. Using a case study, we present a detailed protocol demonstrating probe design, library construction, and target DNA capture methodologies, while also including the data analysis workflow. The process to carry out this method typically takes 1-2 days.

The 1021 kb probes enriched target regions used in ER-Seq are shown in Table 1, which covers over 95% of the gene mutations in 12 common tumors. The wide range of these probes makes this process applicable to a majority of cancer patients. Additionally, our unique sequencing adapters and baseline database screening make it possible to detect rare mutations precisely.
Due to the different propert...

Watch this Scientific Journal Video about Detection of Rare Mutations in CtDNA Using Next Generation Sequencing at JoVE.com

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

This manuscript describes a technique for detecting mutations of low frequency in ctDNA, ER-Seq. This method is differentiated by its unique use of two-directional error correction, a special background filter, and efficient molecular acquirement.

The analysis of circulating tumor DNA (ctDNA) using next-generation sequencing (NGS) has become a valuable tool for the development of clinical oncology. ...

The overall goal of this technique is to detect mutations of low frequency in circulating tumor or ctDNA to provide clinical physicians a powerful tool to diagnose tumors and monitor tumor dynamics in response to therapy. The method of testing ctDNA can help answer key questions about what kinds of mutations a patient carries such as single nuclear-type variation, insertion deletion, copy number variation, and structural variation. The main advantage of this technqiue is high sensitivity and specificity which precise detection of low frequency mutations in ctDNA.Demonstrating the procedures will be Yuliang Yang, a technician from my laboratory. To begin, draw 10 milliliters of peripheral blood in a collection tube and gently invert the tube up and down six to eight times to mix the contents. Store blood samples in the collection tubes at six to 37 degrees Celsius for up to 72 hours.Centrifuge the collection tube at 1, 600 times g at room temperature for 10 minutes. Then use a disposal pipette to transfer the supernatant or plasma from the tube to four clean two milliliter appropriately labeled centrifuge tubes without disturbing the pellet. Use a clean disposal pipette to transfer one milliliter of the cells to a two milliliter appropriately labeled centrifuge tube.Store the cells at minus 20 degrees Celsius or colder before genomic or gDNA isolation. Next, centrifuge the plasma at 1, 600 times g at four degrees Celsius for 10 minutes. Then transfer the plasma to clean centrifuge tubes properly labeled as plasma leaving approximately 0.1 milliliter of residual volume at the bottom to avoid contamination.The buffy coat should be avoided from the plasma during the separation process. Otherwise, large DNA fragments extracted from the cells might dilute the ctDNA and affect the sensitivity of the test. Using a commercially available kit, isolate cfDNA from three milliliters of the collected plasma following the manufacturer's instructions.Then also with a kit, isolate gDNA from 200 microliters of white blood cells following the manufacturer's instructions. To fragment the gDNA control sample by sonication, prepare one microgram of gDNA sample in 100 microliters of Tris-EDTA buffer in a clean sonication tube. Set the sonication program to 30 seconds on and 30 seconds off for 12 cycles for a total of 12 minutes.After confirming the product contains 200 to 250 base pair fragments, transfer all fragmentation products to a new 1.5 milliliter tube containing 150 microliters of magnetic beads and incubate the sample for five minutes to select the correct fragments. Next, place the tube on a magnetic rack for 30 seconds and remove the supernatant. Then while keeping the tube on the rack, add 200 microliters of freshly prepared 80%ethanol to wash the beads.Incubate the beads for 30 seconds before removing the supernatant and repeat the wash. Keep the tube on the rack with the lid open to air dry the beads. Then elute the DNA fragments by adding 32 microliters of 10 millimolar Tris-HCL to the beads.To carry out the end prep reaction following the manufacturer's instructions, to a sterile nuclease-free tube, add seven microliters of reaction buffer, three microliters of the enzyme mix, 30 nanograms of cfDNA, and doubly distilled water for a total volume of 60 microliters. In a separate tube, add the same components but with one microgram of gDNA instead of cfDNA. Incubate the mixture in a thermal cycler at 20 degrees Celsius for 30 minutes followed by 65 degrees Celsius for 30 minutes without the lid heated.Immediately following the incubation, add 30 microliters of the ligation master mix, one microliter of the ligation enhancer, and four microliters of the unique sequencing adapter to the tube. Incubate the reaction in the thermal cycler at 20 degrees Celsius for 15 minutes without the lid heated. Vortex to resuspend the magnetic beads and leave the beads at room temperature for at least 30 minutes.Then add 87 microliters of the resuspended magnetic beads to the ligation reaction. Mix well by pipetting up and down and then incubate the sample at room temperature for five minutes. After washing and air drying the beads, elute the DNA target from the beads by adding 20 microliters of 10 millimolar Tris-HCL.Add 20 microliters of adapter ligated DNA fragments, five microliters of index primer i7, 25 microliters of library amplification master mix, and doubly distilled water up to a total volume of 50 microliters. PCR amplify the adapter ligated cfDNA or gDNA. Then add 45 microliters of suspended magnetic beads to the PCR-enriched DNA.Mix the sample by pipetting up and down and incubate it for five minutes. After removing the supernatant and washing the beads, use 30 microliters of 10 millimolar Tris-HCL to elute the DNA fragments with adapters. To carry out targeted DNA capture, in a sterile tube, block the sample by adding 1.5 micrograms of pooling libraries, eight microliters each of P5 block 100P and P7 block 100P, and five microliters of one microgram per microliter cock one DNA.Dry the contents of the tube using a vacuum concentrator set at 60 degrees Celsius. Hybridize the DNA capture probes with the library by adding 8.5 microliters of 2X hybridization buffer, 2.7 microliters of hybridization enhancer, and 1.8 microliters of nuclease-free doubly distilled water. Mix by pipetting up and down and incubate in the thermal mixer at 95 degrees Celsius for 10 minutes.Then immediately add four microliters of the custom probe. Incubate the samples in a thermal mixer at 65 degrees Celsius with the lid heated to 75 degrees Celsius for four hours. Incubate the hybridized target DNA with streptavidin beads then wash the beads to remove unbound DNA.Use the commercial kit according to the manufacturer's instructions to get a final 20 microliters of resuspended beads with captured DNA fragments. The washing step of unbound DNA from streptavidin beads should be quick. Otherwise, the capture efficiency of the targeted DNA might be affected.Amplify the captured DNA fragments by performing PCR using a commercial kit with two micromolar backbone oligonucleotides according to the manufacturer's instructions. Finally, add 45 microliters of suspended beads directly to the PCR product and enrich the amplified target DNA fragments bound to the beads by elution with 30 microliters of 10 millimolar Tris-HCL. Quantify the fragments and carry out sequencing and data analysis according to the text protocol.This table outlines how ER-seq improves coverage depth by 23%compared with the traditional method. This is due to its efficient recovery of cfDNA molecules, thus greatly enhancing the analysis of rare mutations. It is also clear that the unique sequencing adapters used in ER-seq enable easy differentiation of natural and PCR-induced duplications.As detailed in this table on the calling results, analysis based on ER-seq was 100%consistent for EGFR pL858R detection and the frequency of detection was a bit higher when compared with a traditional analysis. Importantly, ER-seq analysis enabled the detection of other relatively low frequency mutations including EGFR pT790M which was not recognized by traditional analysis due to high background noise. Once mastered, this technique can be done in 48 hours if it is performed properly.While attempting this procedure, it's important to remember to avoid loss of a very low quantity of cfDNA during extraction, library prep, and bead wash after hybridization. After watching this video, you should have a good understanding of how ctDNA from patient was collected, prepared, and targeted based on unique identified for sequencing. After its development, this technique paved the way for the researchers in the field of liquid biopsy to explore better practices in making clinic decisions.

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Cancer Research

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific molecular profiles of a tumor may predict responsiveness to therapeutic agents or provide knowledge about prognosis. At our institution a tumor genotyping program was established as part of routine clinical care, screening both hematologic and solid tumors for a wide spectrum of mutations using two next-generation sequencing (NGS) panels: a custom, 33 gene hematological malignancies panel for use with peripheral blood and bone marrow, and a commercially produced solid tumor panel for use with formalin-fixed paraffin-embedded tissue that targets 47 genes commonly mutated in cancer. Our workflow includes a pathologist review of the biopsy to ensure there is adequate amount of tumor for the assay followed by customized DNA extraction is performed on the specimen. Quality control of the specimen includes steps for quantity, quality and integrity and only after the extracted DNA passes these metrics an amplicon library is generated and sequenced. The resulting data is analyzed through an in-house bioinformatics pipeline and the variants are reviewed and interpreted for pathogenicity. Here we provide a snapshot of the utility of each panel using two clinical cases to provide insight into how a well-designed NGS workflow can contribute to optimizing clinical outcomes.

This manuscript describes clinical protocols for two next-generation sequencing panels. One panel interrogates hematologic malignancies while the other panel targets genes commonly mutated in solid tumors. Molecular classification of driver mutations in human malignancies offers valuable prognostic and predictive information.

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific ...

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

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

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

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

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

Development of a Human Preclinical Model of Osteoclastogenesis from Peripheral Blood Monocytes Co-cultured with Breast Cancer Cell Lines

The crosstalk between tumor cells and bone cells in the bone microenvironment is crucial to understanding the mechanism of bone metastasis formation. We developed an in vitro fully human preclinical model of a co-culture of breast cancer cells and monocytes undergoing differentiation towards osteoclasts. We optimized a model of osteoclastogenesis starting from a sample of peripheral blood collected from healthy donors. Peripheral blood mononuclear cells (PBMCs) were first separated by density gradient centrifugation, seeded at a high density and induced to differentiate by adding two growth factors (GFs): receptor activator of nuclear factor-&#954;B ligand (RANKL) and macrophage colony-stimulating factor (MCSF). The cells were left in culture for 14 days and then fixed and analyzed by downstream analysis. In osteolytic bone metastases, one of the effects of cancer cell arrival in bone is the induction of osteoclastogenesis. We thus challenged our model with co-cultures of breast cancer cells to study the differentiation power of cancer cells with respect to GFs. A straightforward way of studying cancer cell-osteoclast interaction is to perform indirect co-cultures based on the use of conditioned medium collected from breast cancer cell cultures and mixed with fresh medium. This mixture is then used to induce osteoclast differentiation. We also optimized a method of direct co-culture in which cancer cells and monocytes undergoing differentiation share the medium and exchange secreted factors. This is a significant improvement over the original indirect co-culture method as researchers can observe the reciprocal interactions of the two cell types and perform downstream analyses for both cancer cells and osteoclasts. This method enables us to study the effect of drugs on the metastatic bone microenvironment and to seed cell lines other than those derived from breast cancer. The model can also be used to study other diseases such as osteoporosis or other bone conditions.

This protocol describes development of an in vitro human preclinical model of osteoclastogenesis from peripheral blood monocytes cultured with breast cancer cell lines to mimic the cancer cell-osteoclast interaction. The model could be used to further our understanding of bone metastasis formation and improve therapeutic options.

The crosstalk between tumor cells and bone cells in the bone microenvironment is crucial to understanding the mechanism of bone metastasis formation. We ...

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.

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 ...

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal gastric mucosa. Recently, we detected CDH1a transcript variant in fresh-frozen tumor tissues obtained from patients with GC. The expression of this variant in tissue samples was investigated by the chip-based digital PCR (dPCR) approach presented here. dPCR offers the potential for an accurate, robust, and highly sensitive measurement of nucleic acids and is increasingly utilized for many applications in different fields. dPCR is capable of detecting rare targets; in addition, dPCR offers the possibility for absolute and precise quantification of nucleic acids without the need for calibrators and standard curves. In fact, the reaction partitioning enriches the target from the background, which improves amplification efficiency and tolerance to inhibitors. Such characteristics make dPCR an optimal tool for the detection of the CDH1a rare transcript.

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

The manuscript describes a chip-based digital PCR assay to detect a rare CDH1 transcript variant (CDH1a) in fresh-frozen normal and tumor tissues obtained from patients with gastric cancer.

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal ...

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples from cancer patients often directly influences diagnosis, prognosis, and/or therapy selection. As a result, the accurate detection of gene fusions has become a critical component of clinical management for many disease types. Until recently, clinical gene fusion detection was predominantly accomplished through the use of single-gene assays. However, the ever-growing list of gene fusions with clinical significance has created a need for assessing fusion status of multiple genes simultaneously. Next generation sequencing (NGS)-based testing has met this demand through the ability to sequence nucleic acid in massively parallel fashion. Multiple NGS-based approaches that employ different strategies for gene target enrichment are now available for use in clinical molecular diagnostics, each with its own strengths and weaknesses. This article describes the use of anchored multiplex PCR (AMP)-based target enrichment and library preparation followed by NGS to assess for gene fusions in clinical solid tumor specimens. AMP is unique among amplicon-based enrichment approaches in that it identifies gene fusions regardless of the identity of the fusion partner. Detailed here are both the wet-bench and data analysis steps that ensure accurate gene fusion detection from clinical samples.

This article details the use of an anchored multiplex polymerase chain reaction-based library preparation kit followed by next-generation sequencing to assess for oncogenic gene fusions in clinical solid tumor samples. Both wet-bench and data analysis steps are described.

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples ...

A Rapid Screening Workflow to Identify Potential Combination Therapy for GBM using Patient-Derived Glioma Stem Cells

The glioma stem cells (GSCs) are a small fraction of cancer cells which play essential roles in tumor initiation, angiogenesis, and drug resistance in glioblastoma (GBM), the most prevalent and devastating primary brain tumor. The presence of GSCs makes the GBM very refractory to most of individual targeted agents, so high-throughput screening methods are required to identify potential effective combination therapeutics. The protocol describes a simple workflow to enable rapid screening for potential combination therapy with synergistic interaction. The general steps of this workflow consist of establishing luciferase-tagged GSCs, preparing matrigel coated plates, combination drug screening, analyzing, and validating the results.

The glioma stem cells (GSCs) are a small fraction of cancer cells which play essential roles in tumor initiation, angiogenesis, and drug resistance in ...

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

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

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

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

Generation and Culturing of High-Grade Serous Ovarian Cancer Patient-Derived Organoids

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the discovery of novel therapeutics and predictive biomarkers for ovarian cancer. These models recapitulate clonal heterogeneity, the tumor microenvironment, and cell-cell and cell-matrix interactions. Additionally, they have been shown to match the primary tumor morphologically, cytologically, immunohistochemically, and genetically. Thus, organoids facilitate research on tumor cells and the tumor microenvironment and are superior to cell lines. The present protocol describes distinct methods to generate patient-derived ovarian cancer organoids from patient tumors, ascites, and pleural fluid samples with a higher than 97% success rate. The patient samples are separated into cellular suspensions by both mechanical and enzymatic digestion. The cells are then plated utilizing a basement membrane extract (BME) and are supported with optimized growth media containing supplements specific to the culturing of high-grade serous ovarian cancer (HGSOC). After forming initial organoids, the PDOs can sustain long-term culture, including passaging for expansion for subsequent experiments.

Patient-derived organoids (PDO) are a three-dimensional (3D) culture that can mimic the tumor environment in vitro. In high-grade serous ovarian cancer, PDOs represent a model to study novel biomarkers and therapeutics.

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the ...

Engineering Oncogenic Heterozygous Gain-of-Function Mutations in Human Hematopoietic Stem and Progenitor Cells

Throughout their lifetime, hematopoietic stem and progenitor cells (HSPCs) acquire somatic mutations. Some of these mutations alter HSPC functional properties such as proliferation and differentiation, thereby promoting the development of hematologic malignancies. Efficient and precise genetic manipulation of HSPCs is required to model, characterize, and better understand the functional consequences of recurrent somatic mutations. Mutations can have a deleterious effect on a gene and result in loss-of-function (LOF) or, in stark contrast, may enhance function or even lead to novel characteristics of a particular gene, termed gain-of-function (GOF). In contrast to LOF mutations, GOF mutations almost exclusively occur in a heterozygous fashion. Current genome-editing protocols do not allow for the selective targeting of individual alleles, hampering the ability to model heterozygous GOF mutations. Here, we provide a detailed protocol on how to engineer heterozygous GOF hotspot mutations in human HSPCs by combining CRISPR/Cas9-mediated homology-directed repair and recombinant AAV6 technology for efficient DNA donor template transfer. Importantly, this strategy makes use of a dual fluorescent reporter system to allow for the tracking and purification of successfully heterozygously edited HSPCs. This strategy can be employed to precisely investigate how GOF mutations affect HSPC function and their progression toward hematological malignancies.

Novel strategies to faithfully model somatic mutations in hematopoietic stem and progenitor cells (HSPCs) are necessary to better study hematopoietic stem cell biology and hematological malignancies. Here, a protocol to model heterozygous gain-of-function mutations in HSPCs by combining the use of CRISPR/Cas9 and dual rAAV donor transduction is described.

Throughout their lifetime, hematopoietic stem and progenitor cells (HSPCs) acquire somatic mutations. Some of these mutations alter HSPC functional ...