Name: comparative lesions analysis through a targeted sequencing approach
Uploaded: 2019-11-05T13:00:00
Description: Watch this Scientific Journal Video about Comparative Lesions Analysis Through a Targeted Sequencing Approach at JoVE.com

The study was supported by the Italian Cancer Genome Project (Grant No. FIRB RBAP10AHJB), Associazione Italiana Ricerca Cancro (AIRC; Grant No. 12182 to AS and 18178 to VC), FP7 European Community Grant (Cam-Pac No 602783 to AS). The funding agencies had no role in the collection, analysis and interpretation of data or in the writing of the manuscript.

The material used in the study was collected under a specific protocol, which was approved by the local ethics committee. Written informed consent from all patients was available.
1. Histological and immunophenotypical revision of tissue specimens
NOTE: An expert pathologist is responsible for activities described hereafter.
<ol>
	<li>Histopathological revision of selected cases according to well-established diagnostic criteria.
	<ol>
		<li>Use the microtome to cu...

<ol>
	<li>Koboldt, D. C., Steinberg, K. M., Larson, D. E., Wilson, R. K., Mardis, E. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+next-generation+sequencing+revolution+and+its+impact+on+genomics.">The next-generation sequencing revolution and its impact on genomics.</a> Cell. 155 (1), 27-38 (2013).</li><li>McGranahan, N., Swanton, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clonal+Heterogeneity+and+Tumor+Evolution:+Past,+Present,+and+the+Future.">Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future.</a> Cell. 168 (4), 613-628 (2017).</li><li>Stratton, M. R., Campbell, P. J., Futreal, 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=The+cancer+genome.">The cancer genome.</a> Nature. 458 (7239), 719-724 (2009).</li><li>Makohon-Moore, A. P., 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=Limited+heterogeneity+of+known+driver+gene+mutations+among+the+metastases+of+individual+patients+with+pancreatic+cancer.">Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer.</a> Nature Genetics. 49 (3), 358-366 (2017).</li><li>Seyfried, T. N., Huysentruyt, L. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+origin+of+cancer+metastasis.">On the origin of cancer metastasis.</a> Critical reviews in oncogenesis. 18 (1-2), 43-73 (2013).</li><li>McLaren, W., 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=Deriving+the+consequences+of+genomic+variants+with+the+Ensembl+API+and+SNP+Effect+Predictor.">Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor.</a> Bioinformatics. 26 (16), 2069-2070 (2010).</li><li>Robinson, J. T., 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=Integrative+genomics+viewer.">Integrative genomics viewer.</a> Nature Biotechnology. 29 (1), 24-26 (2011).</li><li>Amato, E., 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=Molecular+alterations+associated+with+metastases+of+solid+pseudopapillary+neoplasms+of+the+pancreas.">Molecular alterations associated with metastases of solid pseudopapillary neoplasms of the pancreas.</a> The Journal of Pathology. 247 (1), 123-134 (2019).</li><li>Mafficini, A., 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=Reporting+tumor+molecular+heterogeneity+in+histopathological+diagnosis.">Reporting tumor molecular heterogeneity in histopathological diagnosis.</a> PLoS One. 9 (8), e104979 (2014).</li><li>Shi, W., 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=Reliability+of+Whole-Exome+Sequencing+for+Assessing+Intratumor+Genetic+Heterogeneity.">Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity.</a> Cell Reports. 25 (6), 1446-1457 (2018).</li><li>Simbolo, M., 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=DNA+qualification+workflow+for+next+generation+sequencing+of+histopathological+samples.">DNA qualification workflow for next generation sequencing of histopathological samples.</a> PLoS One. 8 (6), e62692 (2013).</li><li>Connor, A. A., 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=Integration+of+Genomic+and+Transcriptional+Features+in+Pancreatic+Cancer+Reveals+Increased+Cell+Cycle+Progression+in+Metastases.">Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases.</a> Cancer Cell. 35 (2), 267-282 (2019).</li><li>Priestley, P., 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=Pan-cancer+whole+genome+analyses+of+metastatic+solid+tumors.">Pan-cancer whole genome analyses of metastatic solid tumors.</a> bioRxiv. , (2018).</li></ol>

Our method enables the identification of molecular alterations involved in progression of solid tumors through integration of vertical data (i.e., morphology, DNA sequencing, and immunohistochemistry) from distinct lesions of a given patient. We demonstrated the capability of our method to detect clonal and subclonal events in a mutational silent tumor type (i.e., SPN, solid-pseudopapillary neoplasm of the pancreas) by interrogating the coding sequences of 409 cancer relevant genes8. An advantage ...

The advent of next generation sequencing (NGS) has revolutionized the way cancers are diagnosed and treated1. NGS coupled to multiregional sequencing have exposed a high degree of intra-tumoral heterogeneity (ITH) in solid tumors2, which explains in part the failure of targeted therapy due to the presence of subclones with differing drug sensitivity2. An important challenge posed by genome-wide sequencing studies is the necessity to distinguish between passenger (i.e., neutral) and driver mutations in individual cancers3. Several studies have indeed shown that, in certain tumors, passenger mutations account for the majority of ITH, while driver alterations tend to be conserved among lesions of the same individual4. It is also important to note that large mutational burden (as seen in lung cancers and melanoma) does not necessarily imply a large subclonal mutational burden2. Therefore, a high degree of ITH can be found in tumors with low mutational burden.
Metastases are responsible for more than 90% of cancer-related death worldwide5; therefore, capturing the mutational heterogeneity of driver genes among primary and metastatic lesions is critical to the design of effective therapies for advanced-stage diseases. Clinical sequencing is generally performed on nucleic acids from fixed tissues, which renders genome-wide exploration difficult because of poor DNA quality. On the other hand, the intent of clinical sequencing is to identify actionable mutations and/or mutations that might predict responsiveness/unresponsiveness to a given therapeutic regimen. As it stands, sequencing can be restricted to a smaller fraction of the genome for timely extraction of clinically relevant information. The transition from low-throughput DNA profiling (e.g., Sanger Sequencing) to NGS has rendered it possible to analyze hundreds of cancer-relevant genes at a high depth of coverage, which allows for the detection of subclonal events. Here, we report a method for comparative lesions analysis that allows for the identification of clonal and subclonal populations among different specimens from the same individual. The method described here integrates three well-established approaches (histological analysis, high-coverage multi-lesion sequencing, and immunophenotypic analyses) to predict functional consequences of the variations identified. The approach is schematically described in Figure 1 and has been applied to the study of 5 metastatic cases of solid pseudopapillary neoplasms (SPNs) of the pancreas. While we describe processing and analysis of formalin-fixed paraffin-embedded (FFPE) tissue specimens, the same procedure can be applied to genetic material from fresh-frozen tissue.

<table>
	<tbody>
		<tr>
			<td>2100 Bioanalyzer Instrument</td>
			<td>Agilent Technologies</td>
			<td>G2939BA</td>
			<td>&#160;Automated electrophoresis tool</td>
		</tr>
		<tr>
			<td>Agencourt AMPure XP Kit</td>
			<td>Fisher Scientific</td>
			<td>NC9959336</td>
			<td>Beads technology for the purification of PCR products; beads-based purification reagent</td>
		</tr>
		<tr>
			<td>Agilent High Sensitivity DNA Kit</td>
			<td>Agilent Technologies</td>
			<td>5067-4627</td>
			<td>Library quantification</td>
		</tr>
		<tr>
			<td>Anti-BAP1</td>
			<td>Santa Cruz Biotechnology</td>
			<td>sc-28383</td>
			<td>Antibody</td>
		</tr>
		<tr>
			<td>Anti-GLUT1</td>
			<td>Thermo Scientific</td>
			<td>RB-9052</td>
			<td>Antibody</td>
		</tr>
		<tr>
			<td>Anti-KDM6A</td>
			<td>Cell Signaling</td>
			<td>#33510</td>
			<td>Antibody</td>
		</tr>
		<tr>
			<td>Anti-p53</td>
			<td>Novocastra</td>
			<td>NCL-L-p53-DO7</td>
			<td>Antibody</td>
		</tr>
		<tr>
			<td>Anti-&#946;catenin</td>
			<td>Sigma-Aldrich</td>
			<td>C7207</td>
			<td>Antibody</td>
		</tr>
		<tr>
			<td>Blocking Solution</td>
			<td>home made</td>
			<td>-</td>
			<td>5 % Bovine serum albumin (BSA) in TBST</td>
		</tr>
		<tr>
			<td>Endogenous peroxidases inactivation solution</td>
			<td>home made</td>
			<td>-</td>
			<td>3% H2O2 in Tris-buffered saline (TBS) 1x</td>
		</tr>
		<tr>
			<td>Leica CV ultra</td>
			<td>Leica</td>
			<td>70937891</td>
			<td>Entellan mountin media</td>
		</tr>
		<tr>
			<td>Epitope Retrieval Solution 1</td>
			<td>Leica Biosystems</td>
			<td>AR9961</td>
			<td>Citrate based pH 6.0 epitope retrieval solution</td>
		</tr>
		<tr>
			<td>Epitope Retrieval Solution 2</td>
			<td>Leica Biosystems</td>
			<td>AR9640</td>
			<td>EDTA based pH 9.0 epitope retrieval solution</td>
		</tr>
		<tr>
			<td>Eppendorf 0.2 ml PCR Tubes, clear</td>
			<td>Eppendorf</td>
			<td>951010006</td>
			<td>Tubes</td>
		</tr>
		<tr>
			<td>Eppendorf DNA LoBind Tubes, 1.5 mL</td>
			<td>Eppendorf</td>
			<td>22431021</td>
			<td>Tubes</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>DIAPATH</td>
			<td>A0123</td>
			<td>IHC deparaffinization reagent</td>
		</tr>
		<tr>
			<td>ImmEdge Pen&#160;Hydrophobic&#160;Barrier&#160;Pen</td>
			<td>Vector Laboratories</td>
			<td>H&#173;4000</td>
			<td>Hydrophobic Pen</td>
		</tr>
		<tr>
			<td>ImmPACT DAB&#160;Peroxidase</td>
			<td>Vector Laboratories</td>
			<td>SK&#173;4105</td>
			<td>HRP substrate</td>
		</tr>
		<tr>
			<td>ImmPRESS Anti&#173;Rabbit&#160;Ig&#160;Reagent&#160;Peroxidase</td>
			<td>Vector Laboratories</td>
			<td>MP&#173;7401&#173;50</td>
			<td>Secondary antibody</td>
		</tr>
		<tr>
			<td>ImmPRESS Anti&#173;Mouse&#160;Ig&#160;Reagent&#160;Peroxidase</td>
			<td>Vector Laboratories</td>
			<td>MP&#173;7402&#173;50</td>
			<td>Secondary antibody</td>
		</tr>
		<tr>
			<td>Integrative Genomics Viewer (IGV)</td>
			<td>Broad Institute</td>
			<td>-</td>
			<td>https://software.broadinstitute.org/software/igv/home</td>
		</tr>
		<tr>
			<td>Ion AmpliSeq Comprehensive Cancer Panel</td>
			<td>Thermofisher Scientific</td>
			<td>4477685</td>
			<td>Multiplexed target selection of 409 cancer related gene. https://assets.thermofisher.com/TFS-Assets/CSD/Reference-Materials/ion-ampliseq-cancer-panel-gene-list.pdf</td>
		</tr>
		<tr>
			<td>Ion AmpliSeq Library Kit 2.0</td>
			<td>Thermofisher Scientific</td>
			<td>4480441</td>
			<td>Preparation of amplicon libraries using Ion AmpliSeq panels</td>
		</tr>
		<tr>
			<td>Ion Chef Instrument</td>
			<td>Thermofisher Scientific</td>
			<td>4484177</td>
			<td>Automated library preparation, template preparation and chip loading</td>
		</tr>
		<tr>
			<td>Ion PI Chip Kit v3 or Ion 540 Chip</td>
			<td>Thermofisher Scientific</td>
			<td>A26771 or A27766</td>
			<td>Barcoded chips for sequencing</td>
		</tr>
		<tr>
			<td>Ion PI Hi-Q Chef Kit or Ion 540 Kit-Chef</td>
			<td>Thermofisher Scientific</td>
			<td>A27198 or A30011</td>
			<td>Template preparation</td>
		</tr>
		<tr>
			<td>Ion PI Hi-Q Sequencing 200 Kit or Ion S5 Sequencing Kit</td>
			<td>Thermofisher Scientific</td>
			<td>A26433 or A30011</td>
			<td>Sequencing</td>
		</tr>
		<tr>
			<td>Ion Proton or Ion GeneStudio S5 System</td>
			<td>Thermofisher Scientific</td>
			<td>4476610 or A38196</td>
			<td>Sequencing system</td>
		</tr>
		<tr>
			<td>Ion Reporter Software - AmpliSeq Comprehensive Cancer Panel tumour-normal pair</td>
			<td>Thermofisher Scientific</td>
			<td>4487118</td>
			<td>Workflow</td>
		</tr>
		<tr>
			<td>Ion Reporter Software - uploader plugin</td>
			<td>Thermofisher Scientific</td>
			<td>4487118</td>
			<td>Data analysis tool</td>
		</tr>
		<tr>
			<td>Ion Torrent Suite Software - Coverege Analysis plugin</td>
			<td>Thermofisher Scientific</td>
			<td>4483643</td>
			<td>Plugin that describe the level of sequance coverage produced</td>
		</tr>
		<tr>
			<td>Ion Torrent Suite Software - Variant Caller plugin</td>
			<td>Thermofisher Scientific</td>
			<td>4483643</td>
			<td>Plugin able to identify single-nucleotide polymorphisms (SNPs), insertions and deletions in a sample across a reference</td>
		</tr>
		<tr>
			<td>Ion Xpress Barcode Adapters 1-96 Kit</td>
			<td>Thermofisher Scientific</td>
			<td>4474517</td>
			<td>Unique barcode adapters</td>
		</tr>
		<tr>
			<td>NanoDrop 2000/2000c Spectrophotometers</td>
			<td>Thermofisher Scientific</td>
			<td>ND-2000</td>
			<td>DNA purity detection</td>
		</tr>
		<tr>
			<td>NCBI reference sequence (RefSeq) database</td>
			<td>NCBI</td>
			<td>-</td>
			<td>https://www.ncbi.nlm.nih.gov/refseq/</td>
		</tr>
		<tr>
			<td>Platinum PCR SuperMix High Fidelity</td>
			<td>Fisher Scientific</td>
			<td>12532-016 or 12532-024</td>
			<td>SuperMix for PCR amplification; high-fidelity PCR mix</td>
		</tr>
		<tr>
			<td>QIAamp DNA Blood Mini Kit</td>
			<td>Quiagen</td>
			<td>51106 0r 51104</td>
			<td>DNA blood extraction kit</td>
		</tr>
		<tr>
			<td>QIAamp DNA FFPE Tissue</td>
			<td>Quiagen</td>
			<td>56404</td>
			<td>DNA FFPE tissue extraction kit</td>
		</tr>
		<tr>
			<td>Qubit 2.0 Fluorometer</td>
			<td>Thermofisher Scientific</td>
			<td>Q32866</td>
			<td>DNA quantification</td>
		</tr>
		<tr>
			<td>Qubit dsDNA BR Assay Kit</td>
			<td>Thermofisher Scientific</td>
			<td>Q32850</td>
			<td>Kit for DNA quantification on Qubit 2.0 Fluorometer</td>
		</tr>
		<tr>
			<td>TBST</td>
			<td>home made</td>
			<td>-</td>
			<td>Tris-buffered saline (TBS) and 0.1% of Tween 20</td>
		</tr>
		<tr>
			<td>Tissue-Tek Prisma Plus &#38; Tissue-Tek Film</td>
			<td>Sakura Europe</td>
			<td>6172</td>
			<td>Automated tissue slide stainer instrument</td>
		</tr>
		<tr>
			<td>Variant Effect Predictor (VEP) software</td>
			<td>EMBI-EBI</td>
			<td>-</td>
			<td>http://grch37.ensembl.org/Homo_sapiens /Tools/VEP</td>
		</tr>
		<tr>
			<td>Xilene, mix of isomeres</td>
			<td>Carlo Erba</td>
			<td>492306</td>
			<td>IHC deparaffinization reagent</td>
		</tr>
	</tbody>
</table>

comparative lesions analysis through a targeted sequencing approach

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

The study workflow is illustrated in Figure 1. Multi-lesions (n = 13) sequencing of 5 SPN cases targeting the coding sequences of 409 cancer related genes identified a total of 27 somatic mutations in 8 genes (CTNNB1, KDM6A, BAP1, TET1, SMAD4, TP53, FLT1, and FGFR3). Mutations were defined as founder/clonal when shared among all lesions of a given patient, and progressor/subclonal when detected in some but not all lesion...

Watch this Scientific Journal Video about Comparative Lesions Analysis Through a Targeted Sequencing Approach at JoVE.com

Comparative Lesions Analysis Through a Targeted Sequencing Approach

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

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

Our protocol allows the capture of the genetic relatedness between primary and metastatic lesions through the identification of molecular alterations involved in disease progression. Our method provides the opportunity to explore genetic relatedness in clinical specimen with high sensitivity and specificity. This is due to the integration of molecular and histopathological analysis.The assessment of intratumor heterogeneity in the cancer research field is of paramount importance in designing effective anti-tumor strategies and our method is broadly applicable to many solid tumor types. After preparing and quantifying the libraries of interest, dilute each library to a 100 picomolar concentration in nuclease-free water and combine 10 microliters of each diluted library for a single run in a single tube. Then mix the pooled libraries by pipetting.To initiate a sequencing run, first open the Torrent browser on a computer connected to the sequencing system. Plan a new run using the generic template for the selected application and under the kits tab select Ion Proton system or Ion Gene Studio S5 system. Select the appropriate chip from the chip type dropdown menu and select Ion AmpliSeq 2.0 Library Kit from the library kit dropdown list.Select the Ion Chef button for the template kit and select the appropriate Chef Kit from the template kit dropdown list. Select the appropriate sequencing kit from the sequencing kit dropdown menu and select Ion Express from the barcode set dropdown list. Under the plugin tab, select the coverage analysis plugin.Under the plan tab, select the GRCH37HG19 genome from the reference library dropdown list. From the target regions dropdown list, select the appropriate panel to be sequenced. Then set the number of barcodes to be sequenced and set the barcode name and sample name for each library.For a pooled libraries dilution, dilute the stock library with nuclease-free water to a 25 picomolar concentration for an ion proton chip and pipette 50 microliters of each diluted library to the bottom of the appropriate library sample tube. Load sample tubes containing the pooled diluted libraries onto the library preparation system and start the clonal amplification. For next generation sequencing, follow the on-screen instructions to initialize the instrument.When the clonal amplification is finished, open the Ion Chef instrument door, then open the lid of the chip loading centrifuge and remove the two chips from the library preparation system. Place the chips into separate chip storage containers and load one of the chips into the chip compartment in the instrument. Then close the chip compartment lid and start the sequencing.For mutation analysis, open the coverage analysis plugin and use the coverage analysis output to verify the depth of coverage and uniformity. Use the Torrent Variant Caller plugin to perform the variant calling selecting the germ line or somatic workflow as appropriate. Then download filtered variants variant call format files and use the variant effect predictor software in the NCBI RefSeq database to annotate the variants.To estimate the copy-number variations, use the ion reporter uploader plugin to load the sequencing data into the ion reporter software and use the comprehensive cancer panel tumor normal pair workflow to analyze the data. Manually filter the mutations and copy-number variations based on the scores assigned by the software and verify the variations visually with the Integrative Genomics Viewer. Then visually inspect the alignment for unusual reads that may generate artifactual calls and inspect the normalized coverage for all of the amplicons across a given gene against the normalized coverage of the baseline to verify the copy-number variations.For each case, index the mutation calls from the sequencing of normal tissue or blood or primary tumor or metastasis. Flag as germ line and discard calls that are also evident from the sequencing data of germ line DNA. Flag as clonal or founder the mutations that are shared among all lesions of a given patient.Then flag as subclonal or progressor the mutations that are detected in some but not all of the lesions of a given patient. In this representative experiment, multi-lesion sequencing of five solid pseudopapillary neoplasm cases targeting the coding sequences of 409 cancer-related genes identified a total of 27 somatic mutations in eight genes. Mutations were defined as founder or clonal when shared among all of the lesions of a given patient and progressor or subclonal when detected in some but not all of the lesions of a given patient.Consistently, immunohistochemical staining for beta-catenin and KMD6A was homogenous among the diverse lesions of cases with mutations of the corresponding genes. The moderate staining for KMD6A in mutated specimens suggest that genetic alteration is likely to alter the function rather than the expression of the protein. KMD6A loss of function in pancreatic tumors is associated with up regulation of the hypoxia marker GLUT-1.And accordingly, GLUT-1 was over expressed in cases bearing KMD6A mutations. Immunohistochemistry for BAP1 and TP53 confirmed that mutations in those genes were subclonal. In this virtual karyotype of a representative case showing the location, proximity, and copy-number status of altered genes, the copy-number variation analysis using sequencing data revealed alterations in all of the specimens analyzed.And in contrast to point mutations, the majority of copy-number variation alterations were subclonal. Validation and indexing of mutations and copy-number variation and using the tumor normal DNA comparison are important for avoiding the generation of artifactual calls that could invalidate the results. This procedure could also be applied to whole genome sequencing studies aimed at interrogating the entire genome for the identification of mutation between lesion of different solid tumor types.In the cancer research field, these techniques are critical tools for understanding the biology of diseases with important clinical implications aimed at designing personalized and effective targeted therapies.

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The lateral fluid percussion injury (FPI) model is well established and has been used to study TBI and post-traumatic epilepsy (PTE). However, ...

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Common ...

Evaluating Skilled Prehension in Mice Using an Auto-Trainer

We describe a method to introduce na&#239;ve mice to a novel prehension (reach-to-grasp) task. Mice are housed singly in cages with a frontal slot that ...

Two Different Real-Time Place Preference Paradigms Using Optogenetics within the Ventral Tegmental Area of the Mouse

Understanding how neuronal activation leads to specific behavioral output is fundamental for modern neuroscience. Combining optogenetics in rodents with ...