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Cowell LG. The Diagnostic, Prognostic, and Therapeutic Potential of Adaptive Immune Receptor Repertoire Profiling in Cancer. Cancer Res 2019; 80:643-654. [PMID: 31888887 DOI: 10.1158/0008-5472.can-19-1457] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 10/14/2019] [Accepted: 12/17/2019] [Indexed: 11/16/2022]
Abstract
Lymphocytes play a critical role in antitumor immune responses. They are directly targeted by some therapies, and the composition and spatial organization of intratumor T-cell populations is prognostic in some cancer types. A better understanding of lymphocyte population dynamics over the course of disease and in response to therapy is urgently needed to guide therapy decisions and to develop new therapy targets. Deep sequencing of the repertoire of antigen receptor-encoding genes expressed in a lymphocyte population has become a widely used approach for profiling the population's immune status. Lymphocyte antigen receptor repertoire deep sequencing data can be used to assess the clonal richness and diversity of lymphocyte populations; to track clone members over time, between tissues, and across lymphocyte subsets; to detect clonal expansion; and to detect the recruitment of new clones into a tissue. Repertoire sequencing is thus a critical complement to other methods of lymphocyte and immune profiling in cancer. This review describes the current state of knowledge based on repertoire sequencing studies conducted on human cancer patients, with a focus on studies of the T-cell receptor beta chain locus. The review then outlines important questions left unanswered and suggests future directions for the field.
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Affiliation(s)
- Lindsay G Cowell
- Department of Population and Data Sciences, Department of Immunology, UT Southwestern Medical Center, Dallas, Texas.
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52
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Olson BJ, Moghimi P, Schramm CA, Obraztsova A, Ralph D, Vander Heiden JA, Shugay M, Shepherd AJ, Lees W, Matsen FA. sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation. Front Immunol 2019; 10:2533. [PMID: 31736960 PMCID: PMC6838214 DOI: 10.3389/fimmu.2019.02533] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 10/11/2019] [Indexed: 12/28/2022] Open
Abstract
The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.
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Affiliation(s)
- Branden J Olson
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States.,Department of Statistics, University of Washington, Seattle, WA, United States
| | - Pejvak Moghimi
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
| | - Chaim A Schramm
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Anna Obraztsova
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Duncan Ralph
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Jason A Vander Heiden
- Department of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, CA, United States
| | - Mikhail Shugay
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Adrian J Shepherd
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
| | - William Lees
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
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53
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Guo Y, Chen K, Kwong PD, Shapiro L, Sheng Z. cAb-Rep: A Database of Curated Antibody Repertoires for Exploring Antibody Diversity and Predicting Antibody Prevalence. Front Immunol 2019; 10:2365. [PMID: 31649674 PMCID: PMC6794461 DOI: 10.3389/fimmu.2019.02365] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 09/20/2019] [Indexed: 12/18/2022] Open
Abstract
The diversity of B cell receptors provides a basis for recognizing numerous pathogens. Antibody repertoire sequencing has revealed relationships between B cell receptor sequences, their diversity, and their function in infection, vaccination, and disease. However, many repertoire datasets have been deposited without annotation or quality control, limiting their utility. To accelerate investigations of B cell immunoglobulin sequence repertoires and to facilitate development of algorithms for their analysis, we constructed a comprehensive public database of curated human B cell immunoglobulin sequence repertoires, cAb-Rep (https://cab-rep.c2b2.columbia.edu), which currently includes 306 immunoglobulin repertoires from 121 human donors, who were healthy, vaccinated, or had autoimmune disease. The database contains a total of 267.9 million V(D)J heavy chain and 72.9 million VJ light chain transcripts. These transcripts are full-length or near full-length, have been annotated with gene origin, antibody isotype, somatic hypermutations, and other biological characteristics, and are stored in FASTA format to facilitate their direct use by most current repertoire-analysis programs. We describe a website to search cAb-Rep for similar antibodies along with methods for analysis of the prevalence of antibodies with specific genetic signatures, for estimation of reproducibility of somatic hypermutation patterns of interest, and for delineating frequencies of somatically introduced N-glycosylation. cAb-Rep should be useful for investigating attributes of B cell sequence repertoires, for understanding characteristics of affinity maturation, and for identifying potential barriers to the elicitation of effective neutralizing antibodies in infection or by vaccination.
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Affiliation(s)
- Yicheng Guo
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Kevin Chen
- College of Arts and Science, Stony Brook University, Stony Brook, NY, United States
| | - Peter D Kwong
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, United States
| | - Lawrence Shapiro
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States.,Vaccine Research Center, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, MD, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, United States
| | - Zizhang Sheng
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
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54
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Zhuang Y, Zhang C, Wu Q, Zhang J, Ye Z, Qian Q. Application of immune repertoire sequencing in cancer immunotherapy. Int Immunopharmacol 2019; 74:105688. [PMID: 31276974 DOI: 10.1016/j.intimp.2019.105688] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Revised: 05/05/2019] [Accepted: 06/05/2019] [Indexed: 12/21/2022]
Abstract
With the prominent breakthrough in the field of tumor immunology, diverse cancer immunotherapies have attracted great attention in the last decade. The immune checkpoint inhibitors, adoptive cell therapies, and therapeutic cancer vaccines have already achieved impressive clinical success. However, the fact that only a small subset of patients with specific tumor types can benefit from these treatments limits the application of cancer immunotherapy. To seek out the molecular mechanisms behind this challenge and to select cancer precision medicine for different individuals, researchers apply the immune repertoire sequencing (IRS) to evaluate genetic responses of each patient to current immunotherapies. This review summarizes the technical advances and recent applications of IRS in cancer immunotherapy, indicates the limitations of this technique, and predicts future perspectives both in basic studies and clinical trials.
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Affiliation(s)
- Yuan Zhuang
- Shanghai Baize Medical Laboratory, Shanghai, China
| | - Changzheng Zhang
- Shanghai Baize Medical Laboratory, Shanghai, China; Shanghai Engineering Research Center for Cell Therapy, Shanghai, China
| | - Qiong Wu
- Shanghai Baize Medical Laboratory, Shanghai, China
| | - Jing Zhang
- Shanghai Baize Medical Laboratory, Shanghai, China
| | - Zhenlong Ye
- Shanghai Baize Medical Laboratory, Shanghai, China; Shanghai Cell Therapy Research Institute, Shanghai, China; Shanghai Engineering Research Center for Cell Therapy, Shanghai, China.
| | - Qijun Qian
- Shanghai Baize Medical Laboratory, Shanghai, China; Shanghai Cell Therapy Research Institute, Shanghai, China; Shanghai Engineering Research Center for Cell Therapy, Shanghai, China.
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