CapTCR-seq: hybrid capture for T-cell receptor repertoire profiling.
David T MulderEtienne R MahéMark DowarYoustina HannaTiantian LiLinh T NguyenMarcus O ButlerNaoto HiranoJan DelabiePamela S OhashiTrevor J PughPublished in: Blood advances (2019)
Mature T-cell lymphomas consisting of an expanded clonal population of T cells that possess common rearrangements of the T-cell receptor (TCR) encoding genes can be identified and monitored using molecular methods of T-cell repertoire analysis. We have developed a hybrid-capture method that enriches DNA sequencing libraries for fragments encoding rearranged TCR genes from all 4 loci in a single reaction. We use this method to describe the TCR repertoires of 63 putative lymphoma clinical isolates, 7 peripheral blood mononuclear cell (PBMC) populations, and a collection of tumor infiltrating lymphocytes. Dominant Variable (V) and Joining (J) gene pair rearrangements in cancer cells were confirmed by polymerase chain reaction (PCR) amplification and Sanger sequencing; clonality assessment of clinical isolates using BIOMED-2 methods showed agreement for 73% and 77% of samples at the β and γ loci, respectively, whereas β locus V and J allele prevalence in PBMCs were well correlated with results from commercial PCR-based DNA sequencing assays (r 2 = 0.94 with Adaptive ImmunoSEQ, 0.77-0.83 with Invivoscribe LymphoTrack TRB Assay). CapTCR-seq allows for rapid, high-throughput and flexible characterization of dominant clones within TCR repertoire that will facilitate quantitative analysis of patient samples and enhance sensitivity of tumor surveillance over time.
Keyphrases
- single cell
- high throughput
- genome wide
- peripheral blood
- rna seq
- regulatory t cells
- dna methylation
- circulating tumor
- genome wide identification
- single molecule
- genome wide association study
- nucleic acid
- cell free
- high throughput sequencing
- copy number
- public health
- risk factors
- diffuse large b cell lymphoma
- high resolution
- case report
- circulating tumor cells
- bioinformatics analysis
- genome wide association
- dna damage