The authors would like to thank Dr Rita Shaknovich and members of Elemento lab, Melnick lab, and Tam lab for thoughtful discussions. We would also like to thank the Genomics Resources Core Facility at Weill Cornell Medical College for performing the VDJ-sequencing. YJ was supported by ASH Scholar Award. WT and OE are supported by Weill Cornell Cancer Center Pilot Grant. OE is supported by the NSF CAREER award, the Starr Cancer Consortium and the Hirschl Trust. We would also like to thank Katherine Benesch, JD, MPH for her generous support to this project.

1. VDJ Amplification
1.1) DNA Extraction from Tumor Samples
<ol>
	<li>Extract DNA from thin sections (10-20 &#181;m) of frozen O.C.T. embedded normal or malignant tissues.
	<ol>
		<li>Digest 10-30 thin sections of embedded tissue cut by a cryostat microtome in 4 ml Nucleic Lysis Buffer (0.0075 M Tris HCl, pH 8.2; 0.3 M NaCl; 0.002 M Na2EDTA) with Proteinase K (0.5 mg/ml, final concentration) and 0.625% SDS in a 15 ml centrifuge tube in a 37 &#176;C water bath overnight.</li>
		<li>Add 1 ml of saturated NaCl (5 M) to the digestion mixture and shake vigorously for 15 sec.</li>
		<li>Centrifuge at 1,100 x g for 15 min at room temperature.</li>
		<li>Transfer the supernatant to a new 15 ml centrifuge tube and add two volumes of 100% Ethanol.</li>
		<li>Mix by inverting the tube 6-8 times. Centrifuge at 5,000 x g for 60 min at 4 &#176;C to collect the precipitated DNA.</li>
		<li>Wash the DNA pellet twice with 70% ethanol. Centrifuge at 5,000 x g for 15 min each time to collect the pellet.</li>
		<li>Dissolve DNA in 100-400 &#181;l TE buffer at room temperature on a shaker overnight. The DNA yield is 5 to 200 &#181;g (final concentration between 50-500 ng/&#181;l) depending on the size of the tissue</li>
	</ol>
	</li>
	<li>Extract DNA from thin sections (10-20 &#181;m) of formalin-fixed, paraffin- embedded (FFPE) normal or malignant tissue.
	<ol>
		<li>Incubate paraffin sections in 1 ml xylene twice at room temperature for 10 min each time in a 1.5 ml microcentrifuge tube to de-paraffinize. Collect the tissue sections by spinning at 13,000 x g for 5 min at room temperature.</li>
		<li>Incubate sections in 1 ml 100% ethanol twice at room temperature, 10 min each time to remove residue xylenes. Collect the tissue sections by spinning at 13,000 x g for 5 min at room temperature. The paraffin is completely dissolved at this point and only the tissue section is remaining.</li>
		<li>Air-dry the sections at room temperature for 10-15 min.</li>
		<li>Make a 0.5 mg/ml Proteinase K solution with 1x PCR buffer (diluted from 10x PCR buffer with nuclease-free water). Add the Proteinase K solution to the samples in a final volume of 50-100 &#181;l and incubate overnight at 37 &#176;C.</li>
		<li>Heat the samples at 95 &#176;C for 10 min to inactivate Proteinase K. 
		Note: At this step, sample DNA is dissolved in the PCR buffer and can be used in Steps 1.2 and 1.3 directly. The DNA yield is 0.5 to 20 &#181;g (final concentration between 10-200 ng/&#181;l) depending on the size of the tissue.</li>
	</ol>
	</li>
</ol>
1.2) DNA Quality Assessment
<ol>
	<li>Mix 0.25 &#181;l Taq DNA polymerase with 45 &#181;l of master mix from the commercial ladder kit in a PCR tube.</li>
	<li>Add 5 &#181;l DNA prepared from 1.1.1.7 or 1.1.2.5 into the PCR tube and mix well by pipetting up and down for at least 5 times.</li>
	<li>Use the following conditions to amplify the DNA: 95 &#176;C for 7 min; followed by 35 cycles of 45 sec at 95 &#176;C, 45 sec at 60 &#176;C, and 90 sec at 72 &#176;C; then 72 &#176;C for 10 min and hold at 15 &#176;C.</li>
	<li>Prepare a 2% agarose gel in TBE (Tris/Borate/EDTA).</li>
	<li>Mix 20 &#181;l PCR reaction with 4 &#181;l 6x loading dye, and load onto a 2% agarose gel.</li>
	<li>Stain the agarose gel with 0.5 &#181;g/ml ethidium bromide solution and detect PCR products with a gel imagining system. Note: the samples that yield 5 PCR products at sizes of 100, 200, 300, 400, and 600 bp will be continued to generate VDJ amplicons. 
	CAUTION: Ethidium bromide is a potent mutagen. Please handle with extreme caution by wearing protective gears, i.e. gloves, and dispose into specific containers per institution&#8217;s guidelines.</li>
</ol>
1.3) VDJ PCR
1.3.1) Amplify Recombined IgH VDJ Segment from Framework Region 1 (IgVHFR1)
<ol>
	<li>Mix 45 &#181;l master mix from the tube labeled as &#8220;Mix 2&#8221; of a commercial somatic IGH Hypermutation Assay for Gel Detection kit, 0.25 &#181;l Taq DNA polymerase, and 5 &#181;l sample DNA prepared from 1.1.1.7 or 1.1.2.5 in a PCR tube.</li>
	<li>Use the following conditions to amplify the DNA: 95 &#176;C for 7 min; followed by 35 cycles of 45 sec at 95 &#176;C, 45 sec at 60 &#176;C, and 90 sec at 72 &#176;C; then 72 &#176;C for 10 min and hold at 15 &#176;C.</li>
	<li>Resolve the entire PCR product in a 2% agarose gel by electrophoresis.</li>
	<li>Stain the agarose gel with 0.5 &#181;g/ml ethidium bromide solution and detect PCR products with a gel imaging system. A monoclonal amplicon is expected with the size range of 310-380 bp.</li>
	<li>Excise the gel portion containing the monoclonal amplicon between 310-380 bp.</li>
	<li>Purify DNA from excised gel using a standard Gel Extraction Kit according to manufacturer&#8217;s protocol. Note: for samples that FR1 fragments could be obtained, there is no need to amply IgVHFR2 and IgVHFR3.</li>
</ol>
1.3.2) Amplify Recombined IgH VDJ Segment from Framework Region 2 (IgVHFR2)
<ol>
	<li>Mix 45 &#181;l master mix from the tube labeled as &#8220;Tube B&#8221; of a commercial IGH Gene Clonality Assay for Gel Detection kit, 0.25 &#181;l Taq DNA polymerase, and 5 &#181;l sample DNA prepared from 1.1.1.7 or 1.1.2.5 in a PCR tube.</li>
	<li>Use the following conditions to amplify the DNA: 95 &#176;C for 7 min; followed by 35 cycles of 45 sec at 95 &#176;C, 45 sec at 60 &#176;C, and 90 sec at 72 &#176;C; then 72 &#176;C for 10 min and leave at 15&#176;C.</li>
	<li>Resolve the entire PCR product in a 2% agarose gel by electrophoresis.</li>
	<li>Visualize PCR product(s) by 0.5 &#181;g/ml ethidium bromide staining. A monoclonal amplicon may be observed within the size range of 250-295 bp.</li>
	<li>Excise the gel portion containing the monoclonal amplicon between 250-295 bp.</li>
	<li>Purify DNA from excised gel using a standard Gel Extraction Kit according to manufacturer&#8217;s protocol.</li>
</ol>
1.4) Optimize VDJ PCR
<ol>
	<li>Use the following modified PCR conditions to amplify IgVHFR1 and IgVHFR2 using suboptimal DNA: 95 &#176;C for 7 min, 40 cycles of 95 &#176;C for 60 sec, 60 &#176;C for 60 sec, and 72 &#176;C for 90 sec, final extension at 72 &#176;C for 10 min.</li>
</ol>
2. VDJ Amplicon Library Preparation and Sequencing
2.1) Library Preparation
2.1.1) End-repair
<ol>
	<li>Transfer VDJ PCR product from 1.3 into a PCR tube and add Resuspension Buffer from DNA Sample Preparation Kit to bring up the volume to 60 &#181;l.</li>
	<li>Add 40 &#181;l of End Repair Mix from DNA Sample Preparation Kit and mix thoroughly.</li>
	<li>Incubate the reaction at 30 &#176;C for 30 min in a pre-heated thermocycler (30 &#176;C) with a pre-heated lid at 100 &#176;C.</li>
	<li>Mix 136 &#181;l magnetic beads and 24 &#181;l PCR grade water first in a 1.5 ml tube, then transfer the entire End-repair reaction from 2.1.1.3 into the 1.5 ml tube and mix well with the beads solution.</li>
	<li>Place tubes on a magnetic stand for 2 min to allow the separation of the beads from the solution. Aspirate the supernatant, and wash the beads with 80% fresh prepared EtOH twice while the tube is on the magnetic stand.</li>
	<li>Aspirate the ethanol solution completely and allow the beads to air dry for 15 min at room temperature for 15 min.</li>
	<li>Take tube off the magnetic stand and resuspend beads in 17.5 &#181;l Resuspension Buffer.</li>
	<li>Place tubes back onto the magnetic stand for 2 min to separate beads from the Resuspension Buffer. Remove the Resuspension Buffer (End-repair product is resuspended in the Resuspension buffer now) into a clean PCR tube.</li>
</ol>
2.1.2) A-tailing
<ol>
	<li>Add 12.5 &#181;l A-tailing mix into the PCR tube containing End-repair product and mix thoroughly.</li>
	<li>Incubate the PCR tube at 37 &#176;C for 30 min in a pre-heated thermocycler (37 &#176;C) with a pre-heated lid at 100 &#176;C.</li>
</ol>
2.1.3) Adaptor Ligation
<ol>
	<li>Add 2.5 &#181;l Resuspension Buffer, 2.5 &#181;l Ligation Mix, and 2.5 &#181;l DNA Adaptor Index into the A-tailing reaction.</li>
	<li>Incubate the reaction at 30 &#176;C for 30 minl in a pre-heated thermocycler (30 &#176;C) with a pre-heated lid at 100 &#176;C.</li>
	<li>Add 5 &#181;l Stop Ligation Buffer into each reaction and mix thoroughly.</li>
	<li>Mix 42.5 &#181;l well-mixed magnetic beads to clean the reaction following steps 2.1.1.5 to 2.1.1.8. Add 50 &#181;l Resuspension Buffer to elute the adaptor-ligated product.</li>
	<li>Clean the adaptor-ligated product for a second time by using 50 &#181;l well-mixed AMPure XP beads, and elute the product in 25 &#181;l Resuspension Buffer into a clean PCR tube.</li>
</ol>
2.1.4) Amplify DNA Fragments
<ol>
	<li>Add 5 &#181;l PCR Primer Cocktail and 25 &#181;l PCR Master Mix to the PCR tube containing adaptor-ligated product and mix thoroughly.</li>
	<li>Perform amplification in a pre-programmed thermocycler with the following conditions: 98 &#176;C for 30 sec; 10 cycles of 98 &#176;C for 10 sec, 60 &#176;C for 30 sec and 72 &#176;C for 30 sec; then 72 &#176;C for 5 min and hold at 10 &#176;C.</li>
	<li>Clean up the reaction by using 50 &#181;l well-mixed magnetic beads, and elute the final product in 30 &#181;l Resuspension Buffer.</li>
</ol>
2.1.5) Library Validation
<ol>
	<li>Quantify the final product with a fluorometer using manufacturer&#8217;s protocol. Final library concentration is between 2.5 to 20 ng/&#181;l.</li>
	<li>Assess the quality of the final product by using an analytical instrument with High Sensitivity DNA chip according to manufacturer&#8217;s protocol. Expect a single band with the expected size for either IGVHFR1, IGVHFR2 or IGVHFR3. The expected size of the library product equals the size of the original VDJ amplicon plus the size of the adaptors (~125 bp).</li>
</ol>
2.2) VDJ-PCR Library Pooling and Sequencing
<ol>
	<li>Calculate the molarity of each library fraction using the following formula: nM = [(ng/1,000)/bp*660] x 109 where ng is the concentration of the VDJ-PCR library measured in step 2.1.5.1 and bp is the peak size of the VDJ-PCR library measured in step 2.1.5.2.</li>
	<li>Dilute the library to 2 nM (10 &#181;l total) with DNase-free water.</li>
	<li>Combine the 10 &#181;l of the diluted 2 nM libraries together into a 1.5 ml tube.</li>
	<li>Add an equal volume of PhiX spike-in control into the 1.5 ml tube.</li>
	<li>Load the pool at 7 pM concentration onto a flowcell.</li>
	<li>Sequence the libraries using a paired-end 150 cycle sequencer according to manufacturer&#8217;s protocol.</li>
</ol>
3. Data Analysis
Note: A summary of the bioinformatics scripts used in this section can be found as a Supplementary Code File.
3.1) Alignment and QC
<ol>
	<li>Map paired-end sequencing reads against a human IGH V, D and J region database downloaded from the IMGT website11 using an adapted nucleotide blast algorithm based upon &#8216;blastn&#8217; available from NCBI with gap open penalty of 2, gap extension penalty of 1, word length of 7, and e-value threshold of 10-4. Discard the read-pair does not map to both an IGH V and a J region.</li>
	<li>Count the remaining read-pairs that have IGH V and J mappings to obtain the frequencies of matching VJ combinations across all read pairs obtained from the sequencing run on the sample. Count a read-pair if it is mapped to both an IGH V and J gene, and then add its allele to the corresponding count for the particular VJ combination.</li>
	<li>Rank the counts for each recombined VDJ region obtained from 3.1.2 from the highest to the lowest. The VDJ region has the highest reads count is defined as major rearrangement combination.</li>
	<li>Discard aligned sequences that cover less than 35% of the domain major rearrangement identified in 3.1.3.</li>
</ol>
3.2) SHM Profile Identification
<ol>
	<li>Count all SHM patterns across the reads from step 3.1.3. Define each SHM pattern as a subclone.</li>
	<li>Count the number of the subclones that are corresponding to different unique SHM patterns, and the number of reads that are mapped to individual subclones.</li>
</ol>
3.3) Graphical Representation of Results
<ol>
	<li>Perform the phylogenetic analysis on the subclones using their corresponding SHM patterns using a neighborhood joining method from R package &#8220;ape&#8221; according to manufacturer&#8217;s protocol. Calculate a distance matrix from the individual distinct alignments to recreate the subclone phylogeny rooted to the germline sequence of the VJ combination in question for each paired sample set.</li>
	<li>Use the nucleotide sequence of each subclone as character vector and calculate the approximate string distance between all subclones in the major VJ rearrangement for both diagnosis and corresponding relapse samples using a Levenshtein distance measure where mathematically the distance between two alignments is given by dx,y(i,j) where dx,y(i,j) = 1 if i &#8800; j and 0 otherwise, and then sum this function over the length of the string corresponding to nucleotide sequences i and j.</li>
	<li>Graphically display the resulting matrix of subclone distances and their corresponding subclone counts in the following two ways:
	<ol>
		<li>Use R package &#8220;MASS&#8221; according to manufacturer&#8217;s protocol to apply multidimensional scaling to the subclone distance matrix and generate a two dimensional principle coordinates map, which is then plotted along with the logarithm of subclonal counts as the radius of the circle.</li>
		<li>Construct an undirected graph based upon the Levenshtein distance, where the vertices correspond to each distinct subclone arising from the major VJ rearrangement. 
		Note: If the distance between two distinct clones is equal to one then there exists an edge between these two vertices. If the distance is greater than one, then there is no edge connecting them.</li>
		<li>Plot the graph of 3.3.3.2 using the tkplot function in the &#8220;iGraph&#8221; R package with the Kamada Kawai layout according to manufacturer&#8217;s protocol. The radius of the vertices is proportional to the cubed root of the total number of clones mapped to it and the shading uses a red and blue range to denote the proportion of clones that either belong to the diagnosis (blue) or relapse (red) samples.</li>
	</ol>
	</li>
</ol>
3.4) Heterogeneity (Entropy) Measurement
<ol>
	<li>Examine the numbers and subclone counts of the individual patterns of somatic hypermutation occurring in the major VJ rearrangement for each paired set of samples.</li>
	<li>Calculate the empirical entropy and residual empirical entropy adjusted for the number of distinct clones in each sample using the standard histogram based entropy estimation.</li>
</ol>

<ol>
	<li>Nowell, P. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+clonal+evolution+of+tumor+cell+populations.">The clonal evolution of tumor cell populations.</a> Science. 194 (4260), 23-28 (1976).</li><li>Greaves, M., Maley, C. 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+evolution+in+cancer.">Clonal evolution in cancer.</a> Nature. 481 (7381), 306-313 (2012).</li><li>Ding, L., 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=Clonal+evolution+in+relapsed+acute+myeloid+leukaemia+revealed+by+whole-genome+sequencing.">Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing.</a> Nature. 481 (7382), 506-510 (2012).</li><li>Jiao, W., Vembu, S., Deshwar, A. G., Stein, L., Morris, Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inferring+clonal+evolution+of+tumors+from+single+nucleotide+somatic+mutations.">Inferring clonal evolution of tumors from single nucleotide somatic mutations.</a> BMC bioinformatics. 15, 35 (2014).</li><li>Schatz, D. G., Ji, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recombination+centres+and+the+orchestration+of+V(D)J+recombination.">Recombination centres and the orchestration of V(D)J recombination.</a> Nature reviews immunology. 11 (4), 251-263 (2011).</li><li>Jacob, J., Kelsoe, G., Rajewsky, K., Weiss, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intraclonal+generation+of+antibody+mutants+in+germinal+centres.">Intraclonal generation of antibody mutants in germinal centres.</a> Nature. 354 (6352), 389-392 (1991).</li><li>Coiffier, B., 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=CHOP+chemotherapy+plus+rituximab+compared+with+CHOP+alone+in+elderly+patients+with+diffuse+large-B-cell+lymphoma.">CHOP chemotherapy plus rituximab compared with CHOP alone in elderly patients with diffuse large-B-cell lymphoma.</a> N Engl J Med. 346 (4), 235-242 (2002).</li><li>Larouche, J. F., 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=Lymphoma+recurrence+5+years+or+later+following+diffuse+large+B-cell+lymphoma:+clinical+characteristics+and+outcome.">Lymphoma recurrence 5 years or later following diffuse large B-cell lymphoma: clinical characteristics and outcome.</a> J Clin Oncol. 28 (12), 2094-2100 (2010).</li><li>Friedberg, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relapsed/refractory+diffuse+large+B-cell+lymphoma.">Relapsed/refractory diffuse large B-cell lymphoma.</a> Hematology Am Soc Hematol Educ Program. 2011, 498-505 (2011).</li><li>Gisselbrecht, C., 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=Salvage+regimens+with+autologous+transplantation+for+relapsed+large+B-cell+lymphoma+in+the+rituximab+era.">Salvage regimens with autologous transplantation for relapsed large B-cell lymphoma in the rituximab era.</a> J Clin Oncol. 28 (27), 4184-4190 (2010).</li><li>Lefranc, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=IMGT,+the+International+ImMunoGeneTics+Information+System+for+Immunoinformatics+:+methods+for+querying+IMGT+databases,+tools,+and+web+resources+in+the+context+of+immunoinformatics.">IMGT, the International ImMunoGeneTics Information System for Immunoinformatics : methods for querying IMGT databases, tools, and web resources in the context of immunoinformatics.</a> Molecular biotechnology. 40 (1), 101-111 (2008).</li><li>Jiang, Y., 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=Deep+sequencing+reveals+clonal+evolution+patterns+and+mutation+events+associated+with+relapse+in+B-cell+lymphomas.">Deep sequencing reveals clonal evolution patterns and mutation events associated with relapse in B-cell lymphomas.</a> Genome biology. 15 (8), 432 (2014).</li><li>Hanna, 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=Direct+reprogramming+of+terminally+differentiated+mature+B+lymphocytes+to+pluripotency.">Direct reprogramming of terminally differentiated mature B lymphocytes to pluripotency.</a> Cell. 133 (2), 250-264 (2008).</li></ol>

The authors have no conflicts of interest to disclose.

Because of the nearly unlimited number of iterations of sequence information coded by VDJ rearrangement and SHM at the IGH locus of human B cells, examination of the entire IGH repertoire by high-throughput deep-sequencing proved to be an efficient and comprehensive way to delineate clonal and sub-clonal B-cell populations. Furthermore, this strategy can be used to study the clonal evolution path of B cell tumor development, remission, and relapse by comparing the clonal and sub-clonal architectures of patient samples co...

Cancer is a clonal disease. Since thirty years ago when Peter C. Nowell proposed the cancer clonal evolution model1, many studies have tried to dissect clonal populations within tumor samples and reconstruct clonal expansion and evolution patterns that underlie the tumorigenesis process2. Recently, whole-genome sequencing has enabled investigators to take a deep look at the clonal heterogeneity and evolution3,4. However, due to the lack of tractable markers in many cell types, it is difficult to infer the precise clonal architecture and evolutionary path. Fortunately there is a natural clonality marker in mature B cells from which many lymphoid malignancies, including DLBCL, originate. In response to antigen stimulation, each B-cell can form a single productive IgH VDJ sequence by joining a VH (variable), a D (diversity), and a JH (joining) segment together from a large pool of these segments. During this process, small portions of the original sequence may be deleted and additional non-templated nucleotides may be added to create a unique VDJ rearrangement. This specific VDJ rearrangement can be inherited in all the progeny of this B-cell, therefore tagging individual mature B-cell and its offspring5. Furthermore, SHM occurs on the recombined VDJ sequences in the subsequent germinal center (GC) reaction to introduce additional mutations for the expansion of the antibody pool and the enhancement of antibody affinity6. Therefore, by comparing and contrasting VDJ and SHM patterns of lymphoma samples that have undergone these processes, intra-tumor heterogeneity could be delineated and clonal evolution path of the disease may be deduced.
Previously, VDJ rearrangement and SHM could be identified by PCR amplifying the recombined regions, cloning the PCR products, and subsequently Sanger sequencing to obtain sequence information. This approach is low-throughput and low yield, retrieving only a very small portion of the entire recombined VDJ repertoire, and hindering the characterization of the overall representation of the clonal population within a given sample. A modified approach was created by generating NGS indexed sequencing libraries from VDJ PCR products and performing PE 2x150 bp sequencing to obtain more than half a million recombined VDJ sequences per sample. In addition, a custom pipeline was developed to perform quality control (QC), align, filter VDJ sequencing reads to identify rearrangements and SHMs of each read, and perform phylogenetic analysis on the clonal architecture of each sample. In addition, a new approach has been established to further characterize the clonal evolution patterns for samples collected at various disease stages.
We have applied this technique to DLBCL patient samples. DLBCL is an aggressive form of non-Hodgkin lymphoma with frequent relapse in up to one third of the patients7. DLBCL relapses normally occur early, within 2 to 3 years of the initial diagnosis, although some do occur after 5 years8. Prognosis for relapsed patients is poor, with only 10% achieving 3 year progression-free survival due to limited treatment options. This is the basis to the urgent need for novel approaches to treat DLBCL relapse9,10. However, molecular mechanisms associated with DLBCL relapse are still largely unknown. Particularly, the role of clonal heterogeneity at diagnosis and clonal evolution during DLBCL relapse development are presently uncharacterized, making it difficult to define an accurate and useful biomarker to predict relapse. To address these questions, we applied our VDJ-sequencing approach on multiple pairs of matched primary diagnosis-relapse DLBCL sample pairs. Two distinct clonal evolutionary scenarios of relapse emerged from the comparison of the clonal architectures between the diagnosis and relapse samples that suggests multiple molecular mechanisms may be involved in DLBCL relapse.

<table border="0" cellpadding="0" cellspacing="0" width="841">
	<tbody>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">Ethanol</td>
			<td style="width:163px;">VWR</td>
			<td style="width:123px;">89125-170</td>
			<td style="width:197px;">200 proof, for molecular biology</td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">TE buffer</td>
			<td>Life Technologies</td>
			<td>12090-015</td>
			<td style="width:197px;">10 mM Tris&#183;Cl, pH 8.0; 10mM EDTA</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Xylenes</td>
			<td>VWR</td>
			<td>EM-XX0055-6</td>
			<td>500 ml</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Proteinase K&#160;</td>
			<td style="width:163px;">Life Technonogies</td>
			<td>25530-015</td>
			<td>100 mg</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:359px;">Deoxynucleotide triphosphate (dNTP) Solution Mix</td>
			<td>Promega</td>
			<td style="width:123px;">U1515</td>
			<td style="width:197px;">10 mM each nucleotide</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10x PCR Buffer&#160;</td>
			<td>Roche</td>
			<td>11699105001</td>
			<td>Without MgCl2</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:46px;width:359px;">AmpliTaq Gold DNA Polymerase with Gold Buffer and MgCl2</td>
			<td style="width:163px;">Life Technonogies</td>
			<td style="width:123px;">4311806</td>
			<td>50 &#181;l at 5 U/&#181;l</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:359px;">Specimen Control Size Ladder</td>
			<td style="width:163px;">Invivoscribe Technologies&#160;</td>
			<td>2-096-0020</td>
			<td>33 reactions</td>
		</tr>
		<tr height="80">
			<td height="80" style="height:80px;width:359px;">IGH Somatic Hypermutation Assay v2.0 - Gel Detection</td>
			<td style="width:163px;">Invivoscribe Technologies&#160;</td>
			<td style="width:123px;">5-101-0030</td>
			<td style="width:197px;">33 reactions, Mix 2 for IGVHFR1 detection</td>
		</tr>
		<tr height="80">
			<td height="80" style="height:80px;">IGH Gene Clonality Assay - Gel Detection</td>
			<td style="width:163px;">Invivoscribe Technologies&#160;</td>
			<td>1-101-0020</td>
			<td style="width:197px;">33 reactions, Tube B for IGVHFR2 detection</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">GoTaq Flexi DNA Polymerase</td>
			<td>Promega</td>
			<td style="width:123px;">M8291</td>
			<td>20 &#181;l at 5 U/&#181;l</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10X Tris-Borate-EDTA (TBE) buffer</td>
			<td>Corning (cellgro)</td>
			<td style="width:123px;">46-011-CM</td>
			<td style="width:197px;">6x1 L</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">50X TAE BUFFER&#160;&#160;</td>
			<td>VWR</td>
			<td>101414-298</td>
			<td style="width:197px;">1 L</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ethidium bromide solution</td>
			<td>Sigma-Aldrich</td>
			<td>E1510</td>
			<td style="width:197px;">10 mg/ml</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">25 bp DNA Ladder</td>
			<td>Life Technologies</td>
			<td>10597011</td>
			<td style="width:197px;">1 &#181;g/&#181;l</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">100 bp DNA Ladder</td>
			<td>Life Technologies</td>
			<td>15628-019</td>
			<td style="width:197px;">1 &#181;g/&#181;l</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">UltraPure Agarose</td>
			<td>Life Technologies</td>
			<td>16500-500</td>
			<td style="width:197px;">500 g</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">40% Acrylamide/Bis Solution</td>
			<td>Bio-Rad Laboratories</td>
			<td>1610144</td>
			<td style="width:197px;">500 ml</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">QIAquick Gel Extraction Kit</td>
			<td>Qiagen</td>
			<td>28704</td>
			<td style="width:197px;">50 columns</td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">Agencourt AMPure XP</td>
			<td style="width:163px;">Beckman Coulter</td>
			<td style="width:123px;">A63881</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:359px;">Qubit dsDNA High Sensitivity Assay Kit</td>
			<td style="width:163px;">Life Technologies</td>
			<td style="width:123px;">Q32854</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:359px;">High Sensitivity DNA Kit</td>
			<td style="width:163px;">Agilent Technologies</td>
			<td style="width:123px;">5067-4626</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:359px;">2100 Bioanalyzer</td>
			<td style="width:163px;">Agilent Technologies</td>
			<td></td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:359px;">PhiX Control v3</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-110-3001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:359px;">MiSeq</td>
			<td style="width:163px;">Illumina</td>
			<td></td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit 2.0 Fluorometer</td>
			<td>Life Technologies</td>
			<td>Q32872</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">Resuspension buffer (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">End repair mix (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">A-tailing mix (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">Ligation mix (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">DNA adaptor index (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">Stop ligation buffer (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">PCR primer cocktail (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:359px;">PCR master mix (Illumina TruSeq DNA Sample Preparation Kit v2)</td>
			<td style="width:163px;">Illumina</td>
			<td>FC-121-2001</td>
			<td style="width:197px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;width:359px;">Magnetic stand</td>
			<td style="width:163px;">Life Technologies</td>
			<td align="right">4457858</td>
			<td></td>
		</tr>
		<tr height="41">
			<td height="41" style="height:41px;width:359px;">Gel imaging system</td>
			<td style="width:163px;">Bio-Rad Laboratories</td>
			<td>170-8370</td>
			<td></td>
		</tr>
	</tbody>
</table>

vdj-seq: deep sequencing analysis of rearranged immunoglobulin heavy chain gene to reveal clonal evolution patterns of b cell lymphoma

Understanding tumor clonality is critical to understanding the mechanisms involved in tumorigenesis and disease progression. In addition, understanding the clonal composition changes that occur within a tumor in response to certain micro-environment or treatments may lead to the design of more sophisticated and effective approaches to eradicate tumor cells. However, tracking tumor clonal sub-populations has been challenging due to the lack of distinguishable markers. To address this problem, a VDJ-seq protocol was created to trace the clonal evolution patterns of diffuse large B cell lymphoma (DLBCL) relapse by exploiting VDJ recombination and somatic hypermutation (SHM), two unique features of B cell lymphomas.
In this protocol, Next-Generation sequencing (NGS) libraries with indexing potential were constructed from amplified rearranged immunoglobulin heavy chain (IgH) VDJ region from pairs of primary diagnosis and relapse DLBCL samples. On average more than half million VDJ sequences per sample were obtained after sequencing, which contain both VDJ rearrangement and SHM information. In addition, customized bioinformatics pipelines were developed to fully utilize sequence information for the characterization of IgH-VDJ repertoire within these samples. Furthermore, the pipeline allows the reconstruction and comparison of the clonal architecture of individual tumors, which enables the examination of the clonal heterogeneity within the diagnosis tumors and deduction of clonal evolution patterns between diagnosis and relapse tumor pairs. When applying this analysis to several diagnosis-relapse pairs, we uncovered key evidence that multiple distinctive tumor evolutionary patterns could lead to DLBCL relapse. Additionally, this approach can be expanded into other clinical aspects, such as identification of minimal residual disease, monitoring relapse progress and treatment response, and investigation of immune repertoires in non-lymphoma contexts.

The overall procedure of VDJ sequencing (VDJ-seq), including DNA extraction, recombined VDJ region amplification and purification, sequencing library construction, reads processing, and phylogenetic analysis, is represented in Figure 1. Routinely 5-200 &#956;g DNA can be retrieved from frozen solid tissue sections or 0.5-20 &#956;g DNA from formalin-fixed paraffin-embedded tissue sections. Depending on the quality, rearrangement pattern, and SHM degree of individual samples, a variety of VDJ PCR products...

Watch this Scientific Journal Video about VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma at JoVE.com

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

This protocol describes an approach to interrogate the recombined immunoglobulin heavy chain VDJ regions of lymphomas by deep-sequencing and retrieve VDJ rearrangement and somatic hypermutation status to delineate clonal architecture of individual tumor. Comparing clonal architecture between paired diagnosis and relapse samples reveals lymphoma relapse clonal evolution modes.

Understanding tumor clonality is critical to understanding the mechanisms involved in tumorigenesis and disease progression. In addition, understanding ...

vdj-seq-deep-sequencing-analysis-rearranged-immunoglobulin-heavy

Research

JoVE Journal

Medicine

26.5K Views.  Weill Cornell Medical College. This protocol describes an approach to interrogate the recombined immunoglobulin heavy chain VDJ regions of lymphomas by deep-sequencing and retrieve VDJ rearrangement and somatic hypermutation status to delineate clonal architecture of individual tumor. Comparing clonal architecture between paired diagnosis and relapse samples reveals lymphoma relapse clonal evolution modes. 

Video: VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Dissection of Human Vitreous Body Elements for Proteomic Analysis

The vitreous is an optically clear, collagenous extracellular matrix that fills the inside of the eye and overlies the retina. 1,2 Abnormal interactions between vitreous substructures and the retina underlie several vitreoretinal diseases, including retinal tear and detachment, macular pucker, macular hole, age-related macular degeneration, vitreomacular traction, proliferative vitreoretinopathy, proliferative diabetic retinopathy, and inherited vitreoretinopathies. 1,2 The molecular composition of the vitreous substructures is not known. Since the vitreous body is transparent with limited surgical access, it has been difficult to study its substructures at the molecular level. We developed a method to separate and preserve these tissues for proteomic and biochemical analysis. The dissection technique in this experimental video shows how to isolate vitreous base, anterior hyaloid, vitreous core, and vitreous cortex from postmortem human eyes. One-dimensional SDS-PAGE analyses of each vitreous component showed that our dissection technique resulted in four unique protein profiles corresponding to each substructure of the human vitreous body. Identification of differentially compartmentalized proteins will reveal candidate molecules underlying various vitreoretinal diseases.

This video shows an effective technique for differentiating and dissecting the various semi-transparent structures of the human vitreous body in post mortem eyes.

The vitreous is an optically clear, collagenous extracellular matrix that fills the inside of the eye and overlies the retina. 1,2 Abnormal interactions ...

Establishment and Propagation of Human Retinoblastoma Tumors in Immune Deficient Mice

Culturing retinoblastoma tumor cells in defined stem cell media gives rise to primary tumorspheres that can be grown and maintained for only a limited time. These cultured tumorspheres may exhibit markedly different cellular phenotypes when compared to the original tumors. Demonstration that cultured cells have the capability of forming new tumors is important to ensure that cultured cells model the biology of the original tumor. 
Here we present a protocol for propagating human retinoblastoma tumors in vivo using Rag2-/- immune deficient mice. Cultured human retinoblastoma tumorspheres of low passage or cells obtained from freshly harvested human retinoblastoma tumors injected directly into the vitreous cavity of murine eyes form tumors within 2-4 weeks. These tumors can be harvested and either further passaged into murine eyes in vivo or grown as tumorspheres in vitro. Propagation has been successfully carried out for at least three passages thus establishing a continuing source of human retinoblastoma tissue for further experimentation. 
Wesley S. Bond and Lalita Wadhwa are co-first authors.

A method is described to propagate human retinoblastoma tumors in mice. Tumor cells are directly injected into the eyes of immune deficient mice. Secondary tumors have been successfully established using both cells directly harvested from human tumors and cultured tumorspheres.

Culturing retinoblastoma tumor cells in defined stem cell media gives rise to primary tumorspheres that can be grown and maintained for only a limited ...

Production and Detection of Reactive Oxygen Species (ROS) in Cancers

Reactive oxygen species include a number of molecules that damage DNA and RNA and oxidize proteins and lipids (lipid peroxydation). These reactive molecules contain an oxygen and include H2O2 (hydrogen peroxide), NO (nitric oxide), O2- (oxide anion), peroxynitrite (ONOO-), hydrochlorous acid (HOCl), and hydroxyl radical (OH-).
Oxidative species are produced not only under pathological situations (cancers, ischemic/reperfusion, neurologic and cardiovascular pathologies, infectious diseases, inflammatory diseases 1, autoimmune diseases 2, etc&hellip;) but also during physiological (non-pathological) situations such as cellular metabolism 3, 4. Indeed, ROS play important roles in many cellular signaling pathways (proliferation, cell activation 5, 6, migration 7 etc..). ROS can be detrimental (it is then referred to as "oxidative and nitrosative stress") when produced in high amounts in the intracellular compartments and cells generally respond to ROS by upregulating antioxidants such as superoxide dismutase (SOD) and catalase (CAT), glutathione peroxidase (GPx) and glutathione (GSH) that protects them by converting dangerous free radicals to harmless molecules (i.e. water). Vitamins C and E have also been described as ROS scavengers (antioxidants).
Free radicals are beneficial in low amounts 3. Macrophage and neutrophils-mediated immune responses involve the production and release of NO, which inhibits viruses, pathogens and tumor proliferation 8. NO also reacts with other ROS and thus, also has a role as a detoxifier (ROS scavenger). Finally NO acts on vessels to regulate blood flow which is important for the adaptation of muscle to prolonged exercise 9, 10. Several publications have also demonstrated that ROS are involved in insulin sensitivity 11, 12.
Numerous methods to evaluate ROS production are available. In this article we propose several simple, fast, and affordable assays; these assays have been validated by many publications and are routinely used to detect ROS or its effects in mammalian cells. While some of these assays detect multiple ROS, others detect only a single ROS.

Production and Detection of Reactive Oxygen Species ROS in Cancers

Here we propose simple methods to test and evaluate the presence of reactive oxygen species in cells.

Reactive oxygen species include a number of molecules that damage DNA and RNA and oxidize proteins and lipids (lipid peroxydation). These reactive ...

DNA Vector-based RNA Interference to Study Gene Function in Cancer

RNA interference (RNAi) inhibits gene expression by specifically degrading target mRNAs. Since the discovery of double-stranded small interference RNA (siRNA) in gene silencing1, RNAi has become a powerful research tool in gene function studies. Compared to genetic deletion, RNAi-mediated gene silencing possesses many advantages, such as the ease with which it is carried out and its suitability to most cell lines. Multiple studies have demonstrated the applications of RNAi technology in cancer research. In particular, the development of the DNA vector-based technology to produce small hairpin RNA (shRNA) driven by the U6 or H1 promoter has made long term and inducible gene silencing possible2,3. Its use in combination with genetically engineered viral vectors, such as lentivirus, facilitates high efficiencies of shRNA delivery and/or integration into genomic DNA for stable shRNA expression. 
We describe a detailed procedure using the DNA vector-based RNAi technology to determine gene function, including construction of lentiviral vectors expressing shRNA, lentivirus production and cell infection, and functional studies using a mouse xenograft model. 
Various strategies have been reported in generating shRNA constructs. The protocol described here employing PCR amplification and a 3-fragment ligation can be used to directly and efficiently generate shRNA-containing lentiviral constructs without leaving any extra nucleotide adjacent to a shRNA coding sequence. Since the shRNA-expression cassettes created by this strategy can be cut out by restriction enzymes, they can be easily moved to other vectors with different fluorescent or antibiotic markers. Most commercial transfection reagents can be used in lentivirus production. However, in this report, we provide an economic method using calcium phosphate precipitation that can achieve over 90% transfection efficiency in 293T cells. Compared to constitutive shRNA expression vectors, an inducible shRNA system is particularly suitable to knocking down a gene essential to cell proliferation. We demonstrate the gene silencing of Yin Yang 1 (YY1), a potential oncogene in breast cancer4,5, by a Tet-On inducible shRNA system and its effects on tumor formation. Research using lentivirus requires review and approval of a biosafety protocol by the Biosafety Committee of a researcher's institution. Research using animal models requires review and approval of an animal protocol by the Animal Care and Use Committee (ACUC) of a researcher's institution.

RNA interference (RNAi) possesses many advantages over gene knockout and has been broadly used as a tool in gene functional studies. The invention of DNA vector-based RNAi technology has made long term and inducible gene knockdown possible, and also increased the feasibility of gene silencing in vivo.

RNA interference (RNAi) inhibits gene expression by specifically degrading target mRNAs. Since the discovery of double-stranded small interference RNA ...

Deep Neuromuscular Blockade Leads to a Larger Intraabdominal Volume During Laparoscopy

Shoulder pain is a commonly reported symptom following laparoscopic procedures such as myomectomy or hysterectomy, and recent studies have shown that lowering the insufflation pressure during surgery may reduce the risk of post-operative pain. In this pilot study, a method is presented for measuring the intra-abdominal space available to the surgeon during laproscopy, in order to examine whether the relaxation produced by deep neuromuscular blockade can increase the working surgical space sufficiently to permit a reduction in the CO2 insufflation pressure. Using the laproscopic grasper, the distance from the promontory to the skin is measured at two different insufflation pressures: 8 mm Hg and 12 mm Hg. After the initial measurements, a neuromuscular blocking agent (rocuronium) is administered to the patient and the intra-abdominal volume is measured again. Pilot data collected from 15 patients shows that the intra-abdominal space at 8 mm Hg with blockade is comparable to the intra-abdominal space measured at 12 mm Hg without blockade. The impact of neuromuscular blockade was not correlated with patient height, weight, BMI, and age. Thus, using neuromuscular blockade to maintain a steady volume while reducing insufflation pressure may produce improved patient outcomes.

This article presents a method for measuring the working abdominal volume during laproscopic myomectomy using the surgical grasper, and applies this technique to obtain pilot data on whether deep neuromuscular blockade (NMB) can enable the use of lower insufflation pressure. Reduced insufflation pressure during laproscopic surgery has been shown to reduce post-operative pain, and thus the use of NMB during surgery may enable improved patient outcomes.

Shoulder pain is a commonly reported symptom following laparoscopic procedures such as myomectomy or hysterectomy, and recent studies have shown that ...

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.
Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

We demonstrate methods for the detection of architectural distortion in prior mammograms. Oriented structures are analyzed using Gabor filters and phase portraits to detect sites of radiating tissue patterns. Each site is characterized and classified using measures to represent spiculating patterns. The methods should assist in the detection of breast cancer.

We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of ...

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

Lipoxygenase (LOX) activity has been implicated in neurodegenerative disorders such as Alzheimer&#39;s disease, but its effects in Parkinson&#39;s disease (PD) pathogenesis are less understood. Gene-environment interaction models have utility in unmasking the impact of specific cellular pathways in toxicity that may not be observed using a solely genetic or toxicant disease model alone.&#160;To evaluate if distinct LOX isozymes selectively contribute to PD-related neurodegeneration, transgenic (i.e. 5-LOX and 12/15-LOX deficient) mice can be challenged with a toxin that mimics cell injury and death in the disorder.&#160;Here we describe the use of a neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which produces a nigrostriatal lesion to elucidate the distinct contributions of LOX isozymes to neurodegeneration related to PD. The use of MPTP in mouse, and nonhuman primate, is well-established to recapitulate the nigrostriatal damage in PD.&#160;The extent of MPTP-induced lesioning is measured by HPLC analysis of dopamine and its metabolites and semi-quantitative Western blot analysis of striatum for tyrosine hydroxylase (TH), the rate-limiting enzyme for the synthesis of dopamine. To assess inflammatory markers, which may demonstrate LOX isozyme-selective sensitivity, glial fibrillary acidic protein (GFAP) and Iba-1 immunohistochemistry are performed on brain sections containing substantia nigra, and GFAP Western blot analysis is performed on striatal homogenates.&#160;This experimental approach can provide novel insights into gene-environment interactions underlying nigrostriatal degeneration and PD.

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson&#039;s Disease

Lipoxygenase (LOX) isozymes can generate products that may increase or decrease neuroinflammation and neurodegeneration.&#160;A gene-environment interaction study could identify LOX isozyme-specific effects. Using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of nigrostriatal damage in two LOX isozyme-deficient transgenic lines allows for comparison of the contribution of LOX isozymes on dopaminergic integrity and inflammation.

Lipoxygenase (LOX) activity has been implicated in neurodegenerative disorders such as Alzheimer&#39;s disease, but its effects in Parkinson&#39;s disease ...

Focus Formation: A Cell-based Assay to Determine the Oncogenic Potential of a Gene

Malignant transformation of cells is typically associated with increased proliferation, loss of contact inhibition, acquisition of anchorage-independent growth potential, and the ability to form tumors in experimental animals1. In NIH 3T3 cells, the Ras signal transduction pathway is known to trigger many of these events, what is known as Ras transformation. The introduction of an overexpressed gene in NIH 3T3 cells may promote morphological transformation and loss of contact inhibition, which can help determine the oncogenic potential of that gene of interest. An assay that provides a straightforward method to assess one aspect of the transforming potential of an oncogene is the Focus Formation Assay (FFA)2. When NIH 3T3 cells divide normally in culture, they do so until they reach a confluent monolayer. However, in the presence of an overexpressed oncogene, these cells can begin to grow in dense, multilayered foci1 that can be visualized and quantified by crystal violet or Hema 3 staining. In this article we describe the FFA protocol with retroviral transduction of the gene of interest into NIH 3T3 cells, and how to quantify the number of foci through staining. Retroviral transduction offers a more efficient method of gene delivery than transfection, and the use of an ecotropic murine retrovirus provides a biosafety control when working with potential human oncogenes.

The Focus Formation Assay provides a straightforward method to assess the transforming potential of a candidate oncogene.

Malignant transformation of cells is typically associated with increased proliferation, loss of contact inhibition, acquisition of anchorage-independent ...

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Here we outline a next-generation RNA sequencing protocol that enables de novo assemblies and intra-host variant calls of viral genomes collected from clinical and biological sources. The method is unbiased and universal; it uses random primers for cDNA synthesis and requires no prior knowledge of the viral sequence content. Before library construction, selective RNase H-based digestion is used to deplete unwanted RNA &#8212; including poly(rA) carrier and ribosomal RNA &#8212; from the viral RNA sample. Selective depletion improves both the data quality and the number of unique reads in viral RNA sequencing libraries. Moreover, a transposase-based &#39;tagmentation&#39; step is used in the protocol as it reduces overall library construction time. The protocol has enabled rapid deep sequencing of over 600 Lassa and Ebola virus samples-including collections from both blood and tissue isolates-and is broadly applicable to other microbial genomics studies.

This protocol describes a rapid and broadly applicable method for unbiased RNA-sequencing of viral samples from human clinical isolates.

Here we outline a next-generation RNA sequencing protocol that enables de novo assemblies and intra-host variant calls of viral genomes collected from ...

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E (sIgE)

Allergic disease is common in both adults and children. Identification of the causative allergens is significant in disease management and prevention. However, a specific immunoglobulin E (IgE) measurement system with a high price-performance ratio is lacking in mainland China, especially in the primary care hospitals. This paper describes the principle and operation procedures of using a microfluidic cartridge-based chemiluminescence system to detect allergen-specific IgE in serum. The results were compared with those from ImmunoCAP (System 1), the industrial standard, and the reproducibility of the system to detect patients sensitized to common allergens is evaluated. The results showed that in comparison with ImmunoCAP (System 1), the BioIC System (System 2) has good precision and sensitivity in detecting serum-specific IgE against various inhalant and food allergens but with a significantly lower cost. It can serve as a good alternative to System 1 in primary care hospitals in mainland China who have lower financial affordability.

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E sIgE

This paper presents a protocol for detecting serum-specific immunoglobulin E with a microfluidic cartridge-based chemiluminescence system and the evaluation of its usefulness in allergy diagnoses.

Allergic disease is common in both adults and children. Identification of the causative allergens is significant in disease management and prevention. ...