1
|
Russell ML, Trofimov A, Bradley P, Matsen FA. Statistical analysis of repertoire data demonstrates the influence of microhomology in V(D)J recombination. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.16.618753. [PMID: 39464162 PMCID: PMC11507937 DOI: 10.1101/2024.10.16.618753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
V(D)J recombination generates the diverse B and T cell receptors essential for recognizing a wide array of antigens. This diversity arises from the combinatorial assembly of V(D)J genes and the junctional deletion and insertion of nucleotides. While previous in vitro studies have shown that microhomology--short stretches of sequence homology between gene ends--can bias the recombination process, the extent of microhomology's impact in vivo, particularly in humans, remains unknown. In this paper, we assess how germline-encoded microhomology influences trimming and ligation during V(D)J recombination using statistical inference on previously-published high-throughput TCRα repertoire sequencing data. We find that microhomology increases both trimming and ligation probabilities, making it an important predictor of recombination outcomes. These effects are consistent across different receptor loci and sequence types. Further, we demonstrate that accounting for microhomology effects significantly alters sequence annotation probabilities and rankings, highlighting its practical importance for accurately inferring the V(D)J recombination events that generated an observed sequence. Together, these results enhance our understanding of how microhomologous nucleotides shape the human V(D)J recombination process.
Collapse
Affiliation(s)
- Magdalena L Russell
- Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195
| | - Assya Trofimov
- Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109
- Department of Physics, University of Washington, Seattle, WA 98195
| | - Philip Bradley
- Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109
- Institute for Protein Design, Department of Biochemistry, University of Washington, Seattle, WA 98195
| | - Frederick A Matsen
- Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109
- Department of Genome Sciences, University of Washington, Seattle, WA 98195
- Department of Statistics, University of Washington, Seattle, WA 98195
- Howard Hughes Medical Institute, Seattle, WA 98195
| |
Collapse
|
2
|
Ostmeyer J, Park JY, von Itzstein MS, Hsiehchen D, Fattah F, Gwin M, Catalan R, Khan S, Raj P, Wakeland EK, Xie Y, Gerber DE. T-cell tolerant fraction as a predictor of immune-related adverse events. J Immunother Cancer 2023; 11:e006437. [PMID: 37580069 PMCID: PMC10432621 DOI: 10.1136/jitc-2022-006437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND Immune checkpoint inhibitor (ICI) therapies may cause unpredictable and potentially severe autoimmune toxicities termed immune-related adverse events (irAEs). Because T cells mediate ICI effects, T cell profiling may provide insight into the risk of irAEs. Here we evaluate a novel metric-the T-cell tolerant fraction-as a predictor of future irAEs. METHODS We examined T-cell receptor beta (TRB) locus sequencing from baseline pretreatment samples from an institutional registry and previously published studies. For each patient, we used TRB sequences to calculate the T-cell tolerant fraction, which was then assessed as a predictor of future irAEs (classified as Common Terminology Criteria for Adverse Event grade 0-1 vs grade ≥2). We then compared the tolerant fraction to TRB clonality and diversity. Finally, the tolerant fraction was assessed on (1) T cells enriched against napsin A, a potential autoantigen of irAEs; (2) thymic versus peripheral blood T cells; and (3) TRBs specific for various infections and autoimmune diseases. RESULTS A total of 77 patients with cancer (22 from an institutional registry and 55 from published studies) receiving ICI therapy (43 CTLA4, 19 PD1/PDL1, 15 combination CTLA4+PD1/PDL1) were included in the study. The tolerant fraction was significantly lower in cases with clinically significant irAEs (p<0.001) and had an area under the receiver operating curve (AUC) of 0.79. The tolerant fraction was lower for each ICI treatment category, reaching statistical significance for CTLA4 (p<0.001) and demonstrating non-significant trends for PD1/PDL1 (p=0.21) and combination ICI (p=0.18). The tolerant fraction for T cells enriched against napsin A was lower than other samples. The tolerant fraction was also lower in thymic versus peripheral blood samples, and lower in some (multiple sclerosis) but not other (type 1 diabetes) autoimmune diseases. In our study cohort, TRB clonality had an AUC of 0.62, and TRB diversity had an AUC of 0.60 for predicting irAEs. CONCLUSIONS Among patients receiving ICI, the baseline T-cell tolerant fraction may serve as a predictor of clinically significant irAEs.
Collapse
Affiliation(s)
- Jared Ostmeyer
- Peter O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jason Y Park
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Mitchell S von Itzstein
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - David Hsiehchen
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Harold C Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Farjana Fattah
- Harold C Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Mary Gwin
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Rodrigo Catalan
- Harold C Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Shaheen Khan
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Prithvi Raj
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Edward K Wakeland
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Yang Xie
- Peter O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Harold C Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - David E Gerber
- Peter O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Harold C Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| |
Collapse
|
3
|
Ostmeyer J, Cowell L, Greenberg B, Christley S. Reconstituting T cell receptor selection in-silico. Genes Immun 2021; 22:187-193. [PMID: 34127826 DOI: 10.1038/s41435-021-00141-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/13/2021] [Accepted: 05/26/2021] [Indexed: 11/09/2022]
Abstract
Each T cell receptor (TCR) gene is created without regard for which substances (antigens) the receptor can recognize. T cell selection culls developing T cells when their TCRs (i) fail to recognize major histocompatibility complexes (MHCs) that act as antigen presenting platforms or (ii) recognize with high affinity self-antigens derived from healthy cells and tissue. While T cell selection has been thoroughly studied, little is known about which TCRs are retained or removed by this process. Therefore, we develop an approach using TCR gene sequencing and machine learning to identify patterns in TCR protein sequences influencing the outcome of T cell receptor selection. We verify the trained models classify TCRs from developing T cells as being before selection and TCRs from mature T cells as being after selection. Our approach may provide future avenues for studying the relationship between T cell selection and conditions like autoimmune diseases.
Collapse
Affiliation(s)
- Jared Ostmeyer
- Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Lindsay Cowell
- Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, USA
| | - Benjamin Greenberg
- Department of Neurology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Scott Christley
- Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, TX, USA
| |
Collapse
|
4
|
Thomson DW, Shahrin NH, Wang PPS, Wadham C, Shanmuganathan N, Scott HS, Dinger ME, Hughes TP, Schreiber AW, Branford S. Aberrant RAG-mediated recombination contributes to multiple structural rearrangements in lymphoid blast crisis of chronic myeloid leukemia. Leukemia 2020; 34:2051-2063. [PMID: 32076119 DOI: 10.1038/s41375-020-0751-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 01/08/2020] [Accepted: 02/06/2020] [Indexed: 11/10/2022]
Abstract
Blast crisis of chronic myeloid leukemia is associated with poor survival and the accumulation of genomic lesions. Using whole-exome and/or RNA sequencing of patients at chronic phase (CP, n = 49), myeloid blast crisis (MBC, n = 19), and lymphoid blast crisis (LBC, n = 20), we found 25 focal gene deletions and 14 fusions in 24 patients in BC. Deletions predominated in LBC (83% of structural variants). Transcriptional analysis identified the upregulation of genes involved in V(D)J recombination, including RAG1/2 and DNTT in LBC. RAG recombination is a reported mediator of IKZF1 deletion. We investigated the extent of RAG-mediated genomic lesions in BC. Molecular hallmarks of RAG activity; DNTT-mediated nucleotide insertions and a RAG-binding motif at structural variants were exclusively found in patients with high RAG expression. Structural variants in 65% of patients in LBC displayed these hallmarks compared with only 5% in MBC. RAG-mediated events included focal deletion and novel fusion of genes associated with hematologic cancer: IKZF1, RUNX1, CDKN2A/B, and RB1. Importantly, 8/8 patients with elevated DNTT at CP diagnosis progressed to LBC by 12 months, potentially enabling early prediction of LBC. This work confirms the central mutagenic role of RAG in LBC and describes potential clinical utility in CML management.
Collapse
Affiliation(s)
- Daniel W Thomson
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Nur Hezrin Shahrin
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Paul P S Wang
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
- Australian Cancer Research Foundation Genomics Facility, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
| | - Carol Wadham
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
| | - Naranie Shanmuganathan
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
- School of Medicine, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Hamish S Scott
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
- Australian Cancer Research Foundation Genomics Facility, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Medicine, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Marcel E Dinger
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington Campus, Sydney, NSW, Australia
| | - Timothy P Hughes
- School of Medicine, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Andreas W Schreiber
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia
- Australian Cancer Research Foundation Genomics Facility, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Susan Branford
- Department of Genetics and Molecular Pathology, Centre for Cancer Biology, SA Pathology, Adelaide, SA, Australia.
- School of Pharmacy and Medical Science, Division of Health Sciences, University of South Australia, Adelaide, SA, Australia.
- School of Medicine, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia.
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia.
| |
Collapse
|