Title | VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma. |
Publication Type | Journal Article |
Year of Publication | 2015 |
Authors | Jiang Y, Nie K, Redmond D, Melnick AM, Tam W, Elemento O |
Journal | J Vis Exp |
Issue | 106 |
Pagination | e53215 |
Date Published | 2015 Dec 28 |
ISSN | 1940-087X |
Keywords | Clonal Evolution, Clone Cells, Genes, Immunoglobulin Heavy Chain, High-Throughput Nucleotide Sequencing, Humans, Immunoglobulin Heavy Chains, Lymphoma, B-Cell, Neoplasm Recurrence, Local, V(D)J Recombination |
Abstract | 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. |
DOI | 10.3791/53215 |
Alternate Journal | J Vis Exp |
PubMed ID | 26780364 |
PubMed Central ID | PMC4780861 |