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Method Article
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 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.
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.
1. VDJ Amplification
1.1) DNA Extraction from Tumor Samples
1.2) DNA Quality Assessment
1.3) VDJ PCR
1.3.1) Amplify Recombined IgH VDJ Segment from Framework Region 1 (IgVHFR1)
1.3.2) Amplify Recombined IgH VDJ Segment from Framework Region 2 (IgVHFR2)
1.4) Optimize VDJ PCR
2. VDJ Amplicon Library Preparation and Sequencing
2.1) Library Preparation
2.1.1) End-repair
2.1.2) A-tailing
2.1.3) Adaptor Ligation
2.1.4) Amplify DNA Fragments
2.1.5) Library Validation
2.2) VDJ-PCR Library Pooling and Sequencing
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
3.2) SHM Profile Identification
3.3) Graphical Representation of Results
3.4) Heterogeneity (Entropy) Measurement
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 μg DNA can be retrieved from frozen solid tissue sections or 0.5-20 μg 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...
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...
The authors have no conflicts of interest to disclose.
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.
Name | Company | Catalog Number | Comments |
Ethanol | VWR | 89125-170 | 200 proof, for molecular biology |
TE buffer | Life Technologies | 12090-015 | 10 mM Tris·Cl, pH 8.0; 10mM EDTA |
Xylenes | VWR | EM-XX0055-6 | 500 ml |
Proteinase K | Life Technonogies | 25530-015 | 100 mg |
Deoxynucleotide triphosphate (dNTP) Solution Mix | Promega | U1515 | 10 mM each nucleotide |
10x PCR Buffer | Roche | 11699105001 | Without MgCl2 |
AmpliTaq Gold DNA Polymerase with Gold Buffer and MgCl2 | Life Technonogies | 4311806 | 50 µl at 5 U/µl |
Specimen Control Size Ladder | Invivoscribe Technologies | 2-096-0020 | 33 reactions |
IGH Somatic Hypermutation Assay v2.0 - Gel Detection | Invivoscribe Technologies | 5-101-0030 | 33 reactions, Mix 2 for IGVHFR1 detection |
IGH Gene Clonality Assay - Gel Detection | Invivoscribe Technologies | 1-101-0020 | 33 reactions, Tube B for IGVHFR2 detection |
GoTaq Flexi DNA Polymerase | Promega | M8291 | 20 µl at 5 U/µl |
10X Tris-Borate-EDTA (TBE) buffer | Corning (cellgro) | 46-011-CM | 6x1 L |
50X TAE BUFFER | VWR | 101414-298 | 1 L |
Ethidium bromide solution | Sigma-Aldrich | E1510 | 10 mg/ml |
25 bp DNA Ladder | Life Technologies | 10597011 | 1 µg/µl |
100 bp DNA Ladder | Life Technologies | 15628-019 | 1 µg/µl |
UltraPure Agarose | Life Technologies | 16500-500 | 500 g |
40% Acrylamide/Bis Solution | Bio-Rad Laboratories | 1610144 | 500 ml |
QIAquick Gel Extraction Kit | Qiagen | 28704 | 50 columns |
Agencourt AMPure XP | Beckman Coulter | A63881 | |
Qubit dsDNA High Sensitivity Assay Kit | Life Technologies | Q32854 | |
High Sensitivity DNA Kit | Agilent Technologies | 5067-4626 | |
2100 Bioanalyzer | Agilent Technologies | ||
PhiX Control v3 | Illumina | FC-110-3001 | |
MiSeq | Illumina | ||
Qubit 2.0 Fluorometer | Life Technologies | Q32872 | |
Resuspension buffer (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
End repair mix (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
A-tailing mix (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
Ligation mix (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
DNA adaptor index (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
Stop ligation buffer (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
PCR primer cocktail (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
PCR master mix (Illumina TruSeq DNA Sample Preparation Kit v2) | Illumina | FC-121-2001 | |
Magnetic stand | Life Technologies | 4457858 | |
Gel imaging system | Bio-Rad Laboratories | 170-8370 |
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