1
|
Alan S, Kanter J. Advances in pharmacotherapy for sickle cell disease: what is the current state of play? Expert Opin Pharmacother 2024:1-10. [PMID: 38973339 DOI: 10.1080/14656566.2024.2377711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 07/04/2024] [Indexed: 07/09/2024]
Abstract
INTRODUCTION Despite over 100 years of neglect and insufficient funding, sickle cell disease has risen to the top of the discussions due to the recent approval of two new genetic therapies. Prior to these approvals, there were only four prior approved medications for sickle cell disease in spite of being the most common inherited blood disorder. The advent and expense of these new genetic therapies have finally brought the trials and tribulations associated with SCD including the suffering and early mortality of affected individuals to the much-needed limelight. Presently, questions about how these therapies will be used and what that means for ongoing pharmaceutical development remain. AREAS COVERED Here, we wish to highlight the current medications and treatments for SCD using already published literature as well as scrutinize the tedious process of implementation for these newly approved commercial genetic therapies. EXPERT OPINION In our expert opinion, despite the progress we have made, significant challenges remain and the most important requirement for any of these treatments is ensuring all affected individuals have access to a sickle cell specialist who can provide comprehensive care.
Collapse
Affiliation(s)
- Sheinei Alan
- Inova Adult Sickle Cell Center, University of Virginia School of Medicine, Inova Fairfax Medical Campus, Fairfax, VA, USA
| | - Julie Kanter
- Lifespan Comprehensive Sickle Cell Center, University of Alabama Birmingham, Birmingham, AL, USA
| |
Collapse
|
2
|
Dashti M, Malik MZ, Nizam R, Jacob S, Al-Mulla F, Thanaraj TA. Evaluation of HLA typing content of next-generation sequencing datasets from family trios and individuals of arab ethnicity. Front Genet 2024; 15:1407285. [PMID: 38859936 PMCID: PMC11163123 DOI: 10.3389/fgene.2024.1407285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 05/07/2024] [Indexed: 06/12/2024] Open
Abstract
Introduction: HLA typing is a critical tool in both clinical and research applications at the individual and population levels. Benchmarking studies have indicated HLA-HD as the preferred tool for accurate and comprehensive HLA allele calling. The advent of next-generation sequencing (NGS) has revolutionized genetic analysis by providing high-throughput sequencing data. This study aims to evaluate, using the HLA-HD tool, the HLA typing content of whole exome, whole genome, and HLA-targeted panel sequence data from the consanguineous population of Arab ethnicity, which has been underrepresented in prior benchmarking studies. Methods: We utilized sequence data from family trios and individuals, sequenced on one or more of the whole exome, whole genome, and HLA-targeted panel sequencing technologies. The performance and resolution across various HLA genes were evaluated. We incorporated a comparative quality control analysis, assessing the results obtained from HLA-HD by comparing them with those from the HLA-Twin tool to authenticate the accuracy of the findings. Results: Our analysis found that alleles across 29 HLA loci can be successfully and consistently typed from NGS datasets. Clinical-grade whole exome sequencing datasets achieved the highest consistency rate at three-field resolution, followed by targeted HLA panel, research-grade whole exome, and whole genome datasets. Discussion: The study catalogues HLA typing consistency across NGS datasets for a large array of HLA genes and highlights assessments regarding the feasibility of utilizing available NGS datasets in HLA allele studies. These findings underscore the reliability of HLA-HD for HLA typing in underrepresented populations and demonstrate the utility of various NGS technologies in achieving accurate HLA allele calling.
Collapse
Affiliation(s)
| | | | | | | | - Fahd Al-Mulla
- Department of Genetics and Bioinformatics, Dasman Diabetes Institute, Kuwait City, Kuwait
| | | |
Collapse
|
3
|
Sotirov S, Dimitrov I. Tumor-Derived Antigenic Peptides as Potential Cancer Vaccines. Int J Mol Sci 2024; 25:4934. [PMID: 38732150 PMCID: PMC11084719 DOI: 10.3390/ijms25094934] [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] [Received: 02/11/2024] [Revised: 04/25/2024] [Accepted: 04/28/2024] [Indexed: 05/13/2024] Open
Abstract
Peptide antigens derived from tumors have been observed to elicit protective immune responses, categorized as either tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs). Subunit cancer vaccines incorporating these antigens have shown promise in inducing protective immune responses, leading to cancer prevention or eradication. Over recent years, peptide-based cancer vaccines have gained popularity as a treatment modality and are often combined with other forms of cancer therapy. Several clinical trials have explored the safety and efficacy of peptide-based cancer vaccines, with promising outcomes. Advancements in techniques such as whole-exome sequencing, next-generation sequencing, and in silico methods have facilitated the identification of antigens, making it increasingly feasible. Furthermore, the development of novel delivery methods and a deeper understanding of tumor immune evasion mechanisms have heightened the interest in these vaccines among researchers. This article provides an overview of novel insights regarding advancements in the field of peptide-based vaccines as a promising therapeutic avenue for cancer treatment. It summarizes existing computational methods for tumor neoantigen prediction, ongoing clinical trials involving peptide-based cancer vaccines, and recent studies on human vaccination experiments.
Collapse
Affiliation(s)
| | - Ivan Dimitrov
- Drug Design and Bioinformatics Lab, Faculty of Pharmacy, Medical University of Sofia, 2, Dunav Str., 1000 Sofia, Bulgaria;
| |
Collapse
|
4
|
Zhou Y, Song L, Li H. Full resolution HLA and KIR genes annotation for human genome assemblies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576452. [PMID: 38328160 PMCID: PMC10849470 DOI: 10.1101/2024.01.20.576452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The HLA (Human Leukocyte Antigen) genes and the KIR (Killer cell Immunoglobulin-like Receptor) genes are critical to immune responses and are associated with many immune-related diseases. Located in highly polymorphic regions, they are hard to be studied with traditional short-read alignment-based methods. Although modern long-read assemblers can often assemble these genes, using existing tools to annotate HLA and KIR genes in these assemblies remains a non-trivial task. Here, we describe Immuannot, a new computation tool to annotate the gene structures of HLA and KIR genes and to type the allele of each gene. Applying Immuannot to 56 regional and 212 whole-genome assemblies from previous studies, we annotated 9,931 HLA and KIR genes and found that almost half of these genes, 4,068, had novel sequences compared to the current Immuno Polymorphism Database (IPD). These novel gene sequences were represented by 2,664 distinct alleles, some of which contained non-synonymous variations resulting in 92 novel protein sequences. We demonstrated the complex haplotype structures at the two loci and reported the linkage between HLA/KIR haplotypes and gene alleles. We anticipate that Immuannot will speed up the discovery of new HLA/KIR alleles and enable the association of HLA/KIR haplotype structures with clinical outcomes in the future.
Collapse
Affiliation(s)
- Ying Zhou
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
| | - Li Song
- Department of Biomedical Data Science, Dartmouth College, Hanover, NH, 03755, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| |
Collapse
|
5
|
Yu D, Ayyala R, Sadek SH, Chittampalli L, Farooq H, Jung J, Nahid AA, Boldirev G, Jung M, Park S, Nguyen A, Zelikovsky A, Mancuso N, Joo JWJ, Thompson RF, Alachkar H, Mangul S. A rigorous benchmarking of alignment-based HLA typing algorithms for RNA-seq data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.22.541750. [PMID: 38293199 PMCID: PMC10827116 DOI: 10.1101/2023.05.22.541750] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Accurate identification of human leukocyte antigen (HLA) alleles is essential for various clinical and research applications, such as transplant matching and drug sensitivities. Recent advances in RNA-seq technology have made it possible to impute HLA types from sequencing data, spurring the development of a large number of computational HLA typing tools. However, the relative performance of these tools is unknown, limiting the ability for clinical and biomedical research to make informed choices regarding which tools to use. Here we report the study design of a comprehensive benchmarking of the performance of 12 HLA callers across 682 RNA-seq samples from 8 datasets with molecularly defined gold standard at 5 loci, HLA-A, -B, -C, -DRB1, and -DQB1. For each HLA typing tool, we will comprehensively assess their accuracy, compare default with optimized parameters, and examine for discrepancies in accuracy at the allele and loci levels. We will also evaluate the computational expense of each HLA caller measured in terms of CPU time and RAM. We also plan to evaluate the influence of read length over the HLA region on accuracy for each tool. Most notably, we will examine the performance of HLA callers across European and African groups, to determine discrepancies in accuracy associated with ancestry. We hypothesize that RNA-Seq HLA callers are capable of returning high-quality results, but the tools that offer a good balance between accuracy and computational expensiveness for all ancestry groups are yet to be developed. We believe that our study will provide clinicians and researchers with clear guidance to inform their selection of an appropriate HLA caller.
Collapse
Affiliation(s)
- Dottie Yu
- Department of Quantitative and Computational Biology, Dornsife College of Letters, Arts and Sciences, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA
| | - Ram Ayyala
- Department of Quantitative and Computational Biology, Dornsife College of Letters, Arts and Sciences, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA
| | - Sarah Hany Sadek
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Biology, and Department of Computer Science, California State University, Fullerton, Fullerton, CA 92831
| | - Likhitha Chittampalli
- Department of Computer Science, Viterbi School of Engineering University of Southern California, Los Angeles, CA, USA
| | - Hafsa Farooq
- Department of Computer Science, Georgia State University Atlanta, GA 30303 USA
| | - Junghyun Jung
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Abdullah Al Nahid
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
| | - Grigore Boldirev
- Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Mina Jung
- Department of Quantitative and Computational Biology, Dornsife College of Letters, Arts and Sciences, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, US
| | - Sungmin Park
- Department of Computer Science and Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea
| | - Austin Nguyen
- Computational Biologist, Immune Monitoring & Cancer Omics Oregon Health & Science University, Biomedical Engineering, 3181 S.W. Sam Jackson Park Road Portland, OR 97239-3098
| | - Alex Zelikovsky
- Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Nicholas Mancuso
- Assistant Professor of Population and Public Health Sciences, Keck School of Medicina, University of Southern California, 1845 N. Soto Street, USA
| | - Jong Wha J Joo
- Department of Computer Science and Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea
- Division of AI Software Convergence, Dongguk University-Seoul, Seoul, 04620, South Korea
| | - Reid F Thompson
- Assistant Professor of Radiation Medicine, School of Medicine, OHSU, Portland, OR 97239
- Assistant Professor of Biomedical Engineering, School of Medicine, OHSU, Portland, OR 97239
- Staff Physician, VA Portland Healthcare System, Portland OR 97239
| | - Houda Alachkar
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, CA, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles
| |
Collapse
|
6
|
Ricker CA, Meli K, Van Allen EM. Historical perspective and future directions: computational science in immuno-oncology. J Immunother Cancer 2024; 12:e008306. [PMID: 38191244 PMCID: PMC10826578 DOI: 10.1136/jitc-2023-008306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2023] [Indexed: 01/10/2024] Open
Abstract
Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, underscoring the importance of elucidating molecular mechanisms responsible for response and resistance to inform the development and selection of treatments. Breakthroughs in molecular sequencing technologies have led to the generation of an immense amount of genomic and transcriptomic sequencing data that can be mined to uncover complex tumor-immune interactions using computational tools. In this review, we discuss existing and emerging computational methods that contextualize the composition and functional state of the tumor microenvironment, infer the reactivity and clonal dynamics from reconstructed immune cell receptor repertoires, and predict the antigenic landscape for immune cell recognition. We further describe the advantage of multi-omics analyses for capturing multidimensional relationships and artificial intelligence techniques for integrating omics data with histopathological and radiological images to encapsulate patterns of treatment response and tumor-immune biology. Finally, we discuss key challenges impeding their widespread use and clinical application and conclude with future perspectives. We are hopeful that this review will both serve as a guide for prospective researchers seeking to use existing tools for scientific discoveries and inspire the optimization or development of novel tools to enhance precision, ultimately expediting advancements in immunotherapy that improve patient survival and quality of life.
Collapse
Affiliation(s)
- Cora A Ricker
- Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Kevin Meli
- Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | | |
Collapse
|
7
|
Shigemizu D, Fukunaga K, Yamakawa A, Suganuma M, Fujita K, Kimura T, Watanabe K, Mushiroda T, Sakurai T, Niida S, Ozaki K. The HLA-DRB1*09:01-DQB1*03:03 haplotype is associated with the risk for late-onset Alzheimer's disease in APOE [Formula: see text]4-negative Japanese adults. NPJ AGING 2024; 10:3. [PMID: 38167405 PMCID: PMC10761915 DOI: 10.1038/s41514-023-00131-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 11/22/2023] [Indexed: 01/05/2024]
Abstract
Late-onset Alzheimer's disease (LOAD) is the most common cause of dementia among those older than 65 years. The onset of LOAD is influenced by neuroinflammation. The human leukocyte antigen (HLA) system is involved in regulating inflammatory responses. Numerous HLA alleles and their haplotypes have shown varying associations with LOAD in diverse populations, yet their impact on the Japanese population remains to be elucidated. Here, we conducted a comprehensive investigation into the associations between LOAD and HLA alleles within the Japanese population. Using whole-genome sequencing (WGS) data from 303 LOAD patients and 1717 cognitively normal (CN) controls, we identified four-digit HLA class I alleles (A, B, and C) and class II alleles (DRB1, DQB1, and DPB1). We found a significant association between the HLA-DRB1*09:01-DQB1*03:03 haplotype and LOAD risk in APOE [Formula: see text]4-negative samples (odds ratio = 1.81, 95% confidence interval = 1.38-2.38, P = 2.03[Formula: see text]). These alleles not only showed distinctive frequencies specific to East Asians but demonstrated a high degree of linkage disequilibrium in APOE [Formula: see text]4-negative samples (r2 = 0.88). Because HLA class II molecules interact with T-cell receptors (TCRs), we explored potential disparities in the diversities of TCR α chain (TRA) and β chain (TRB) repertoires between APOE [Formula: see text]4-negative LOAD and CN samples. Lower diversity of TRA repertoires was associated with LOAD in APOE [Formula: see text]4-negative samples, irrespective of the HLA DRB1*09:01-DQB1*03:03 haplotype. Our study enhances the understanding of the etiology of LOAD in the Japanese population and provides new insights into the underlying mechanisms of its pathogenesis.
Collapse
Affiliation(s)
- Daichi Shigemizu
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan.
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, 734-8551, Japan.
| | - Koya Fukunaga
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Akiko Yamakawa
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Mutsumi Suganuma
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Kosuke Fujita
- Department of Prevention and Care Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
- Japan Society for the Promotion of Science, Tokyo, 102-0083, Japan
| | - Tetsuaki Kimura
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Ken Watanabe
- NCGG Biobank, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Taisei Mushiroda
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan
| | - Takashi Sakurai
- Department of Prevention and Care Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Aichi, 474-8511, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan.
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, 230-0045, Japan.
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, 734-8551, Japan.
| |
Collapse
|
8
|
Thuesen NH, Klausen MS. Benchmarking NGS-Based HLA Typing Algorithms. Methods Mol Biol 2024; 2809:87-99. [PMID: 38907892 DOI: 10.1007/978-1-0716-3874-3_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2024]
Abstract
Knowledge of the expected accuracy of HLA typing algorithms is important when choosing between algorithms and when evaluating the HLA typing predictions of an algorithm. This chapter guides the reader through an example benchmarking study that evaluates the performances of four NGS-based HLA typing algorithms as well as outlining factors to consider, when designing and running such a benchmarking study. The code related to this benchmarking workflow can be found at https://github.com/nikolasthuesen/springers-hla-benchmark/ .
Collapse
|
9
|
Butler-Laporte G, Farjoun J, Nakanishi T, Lu T, Abner E, Chen Y, Hultström M, Metspalu A, Milani L, Mägi R, Nelis M, Hudjashov G, Yoshiji S, Ilboudo Y, Liang KYH, Su CY, Willet JDS, Esko T, Zhou S, Forgetta V, Taliun D, Richards JB. HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases. Commun Biol 2023; 6:1113. [PMID: 37923823 PMCID: PMC10624861 DOI: 10.1038/s42003-023-05496-5] [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] [Received: 06/09/2023] [Accepted: 10/20/2023] [Indexed: 11/06/2023] Open
Abstract
The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.
Collapse
Affiliation(s)
- Guillaume Butler-Laporte
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada.
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada.
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
| | - Joseph Farjoun
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
| | - Tomoko Nakanishi
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Research Fellow, Japan Society for the Promotion of Science, Tokyo, Japan
| | - Tianyuan Lu
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
| | - Erik Abner
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yiheng Chen
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
| | - Michael Hultström
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Integrative Physiology, Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden
- Anaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mari Nelis
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Georgi Hudjashov
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Satoshi Yoshiji
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Research Fellow, Japan Society for the Promotion of Science, Tokyo, Japan
| | - Yann Ilboudo
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
| | - Kevin Y H Liang
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
| | - Chen-Yang Su
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
| | - Julian D S Willet
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Sirui Zhou
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Vincenzo Forgetta
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
| | - Daniel Taliun
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - J Brent Richards
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
- Department of Twin Research, King's College London, London, UK
- Infectious Diseases and Immunity in Global Health Program, Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| |
Collapse
|
10
|
Weiss S, Holtfreter S, Meyer TC, Schmiedeke F, Cammann C, Dörr M, Felix SB, Grabe HJ, Homuth G, Kohler C, Mahncke C, Michalik S, Nauck M, Friedrich N, Samietz S, Völzke H, Völker U, Bröker BM. Toxin exposure and HLA alleles determine serum antibody binding to toxic shock syndrome toxin 1 (TSST-1) of Staphylococcus aureus. Front Immunol 2023; 14:1229562. [PMID: 37731490 PMCID: PMC10507260 DOI: 10.3389/fimmu.2023.1229562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 07/31/2023] [Indexed: 09/22/2023] Open
Abstract
Life-threatening toxic shock syndrome is often caused by the superantigen toxic shock syndrome toxin-1 (TSST-1) produced by Staphylococcus aureus. A well-known risk factor is the lack of neutralizing antibodies. To identify determinants of the anti-TSST-1 antibody response, we examined 976 participants of the German population-based epidemiological Study of Health in Pomerania (SHIP-TREND-0). We measured anti-TSST-1 antibody levels, analyzed the colonization with TSST-1-encoding S. aureus strains, and performed a genome-wide association analysis of genetic risk factors. TSST-1-specific serum IgG levels varied over a range of 4.2 logs and were elevated by a factor of 12.3 upon nasal colonization with TSST-1-encoding S. aureus. Moreover, the anti-TSST-1 antibody levels were strongly associated with HLA class II gene loci. HLA-DRB1*03:01 and HLA-DQB1*02:01 were positively, and HLA-DRB1*01:01 as well as HLA-DQB1*05:01 negatively associated with the anti-TSST-1 antibody levels. Thus, both toxin exposure and HLA alleles affect the human antibody response to TSST-1.
Collapse
Affiliation(s)
- Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Silva Holtfreter
- Institute of Immunology, University Medicine Greifswald, Greifswald, Germany
| | - Tanja C. Meyer
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Frieder Schmiedeke
- Institute of Immunology, University Medicine Greifswald, Greifswald, Germany
| | - Clemens Cammann
- Friedrich Loeffler Institute of Medical Microbiology, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Stephan B. Felix
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Christian Kohler
- Friedrich Loeffler Institute of Medical Microbiology, University Medicine Greifswald, Greifswald, Germany
| | - Cedric Mahncke
- Friedrich Loeffler Institute of Medical Microbiology, University Medicine Greifswald, Greifswald, Germany
| | - Stephan Michalik
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Matthias Nauck
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Nele Friedrich
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Stefanie Samietz
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Barbara M. Bröker
- Institute of Immunology, University Medicine Greifswald, Greifswald, Germany
| |
Collapse
|
11
|
Kalomoiri M, Prakash CR, Lagström S, Hauschulz K, Ewing E, Shchetynsky K, Kular L, Needhamsen M, Jagodic M. Simultaneous detection of DNA variation and methylation at HLA class II locus and immune gene promoters using targeted SureSelect Methyl-Sequencing. Front Immunol 2023; 14:1251772. [PMID: 37691926 PMCID: PMC10484099 DOI: 10.3389/fimmu.2023.1251772] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 08/02/2023] [Indexed: 09/12/2023] Open
Abstract
The Human Leukocyte Antigen (HLA) locus associates with a variety of complex diseases, particularly autoimmune and inflammatory conditions. The HLA-DR15 haplotype, for example, confers the major risk for developing Multiple Sclerosis in Caucasians, pinpointing an important role in the etiology of this chronic inflammatory disease of the central nervous system. In addition to the protein-coding variants that shape the functional HLA-antigen-T cell interaction, recent studies suggest that the levels of HLA molecule expression, that are epigenetically controlled, also play a role in disease development. However, deciphering the exact molecular mechanisms of the HLA association has been hampered by the tremendous genetic complexity of the locus and a lack of robust approaches to investigate it. Here, we developed a method to specifically enrich the genomic DNA from the HLA class II locus (chr6:32,426,802-34,167,129) and proximal promoters of 2,157 immune-relevant genes, utilizing the Agilent RNA-based SureSelect Methyl-Seq Capture related method, followed by sequencing to detect genetic and epigenetic variation. We demonstrated successful simultaneous detection of the genetic variation and quantification of DNA methylation levels in HLA locus. Moreover, by the detection of differentially methylated positions in promoters of immune-related genes, we identified relevant pathways following stimulation of cells. Taken together, we present a method that can be utilized to study the interplay between genetic variance and epigenetic regulation in the HLA class II region, potentially, in a wide disease context.
Collapse
Affiliation(s)
- Maria Kalomoiri
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Chandana Rao Prakash
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sonja Lagström
- Diagnostics and Genomics Group, Agilent Technologies Sweden AB, Sundbyberg, Sweden
| | - Kai Hauschulz
- Diagnostics and Genomics Group, Agilent Technologies Deutschland GmbH, Waldbronn, Germany
| | - Ewoud Ewing
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Klementy Shchetynsky
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lara Kular
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maria Needhamsen
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maja Jagodic
- Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
12
|
Biswas N, Chakrabarti S, Padul V, Jones LD, Ashili S. Designing neoantigen cancer vaccines, trials, and outcomes. Front Immunol 2023; 14:1105420. [PMID: 36845151 PMCID: PMC9947792 DOI: 10.3389/fimmu.2023.1105420] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/30/2023] [Indexed: 02/11/2023] Open
Abstract
Neoantigen vaccines are based on epitopes of antigenic parts of mutant proteins expressed in cancer cells. These highly immunogenic antigens may trigger the immune system to combat cancer cells. Improvements in sequencing technology and computational tools have resulted in several clinical trials of neoantigen vaccines on cancer patients. In this review, we have looked into the design of the vaccines which are undergoing several clinical trials. We have discussed the criteria, processes, and challenges associated with the design of neoantigens. We searched different databases to track the ongoing clinical trials and their reported outcomes. We observed, in several trials, the vaccines boost the immune system to combat the cancer cells while maintaining a reasonable margin of safety. Detection of neoantigens has led to the development of several databases. Adjuvants also play a catalytic role in improving the efficacy of the vaccine. Through this review, we can conclude that the efficacy of vaccines can make it a potential treatment across different types of cancers.
Collapse
Affiliation(s)
- Nupur Biswas
- Rhenix Lifesciences, Hyderabad, India,*Correspondence: Nupur Biswas, ;
| | | | | | | | | |
Collapse
|
13
|
Lybaert L, Lefever S, Fant B, Smits E, De Geest B, Breckpot K, Dirix L, Feldman SA, van Criekinge W, Thielemans K, van der Burg SH, Ott PA, Bogaert C. Challenges in neoantigen-directed therapeutics. Cancer Cell 2023; 41:15-40. [PMID: 36368320 DOI: 10.1016/j.ccell.2022.10.013] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 08/19/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
A fundamental prerequisite for the efficacy of cancer immunotherapy is the presence of functional, antigen-specific T cells within the tumor. Neoantigen-directed therapy is a promising strategy that aims at targeting the host's immune response against tumor-specific antigens, thereby eradicating cancer cells. Initial forays have been made in clinical environments utilizing vaccines and adoptive cell therapy; however, many challenges lie ahead. We provide an in-depth overview of the current state of the field with an emphasis on in silico neoantigen discovery and the clinical aspects that need to be addressed to unlock the full potential of this therapy.
Collapse
Affiliation(s)
| | | | | | - Evelien Smits
- Center for Oncological Research, University of Antwerp, 2610 Wilrijk, Belgium
| | - Bruno De Geest
- Department of Pharmaceutics, Ghent University, 9000 Ghent, Belgium
| | - Karine Breckpot
- Laboratory of Molecular and Cellular Therapy, Department of Biomedical Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Luc Dirix
- Translational Cancer Research Unit, Center for Oncological Research, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Steven A Feldman
- Center for Cancer Cell Therapy, Stanford University School of Medicine, Stanford, CA, USA
| | - Wim van Criekinge
- Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
| | - Kris Thielemans
- Laboratory of Molecular and Cellular Therapy, Department of Biomedical Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Sjoerd H van der Burg
- Medical Oncology, Oncode Institute, Leiden University Medical Center, Leiden, the Netherlands
| | - Patrick A Ott
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | | |
Collapse
|
14
|
Thuesen NH, Klausen MS, Gopalakrishnan S, Trolle T, Renaud G. Benchmarking freely available HLA typing algorithms across varying genes, coverages and typing resolutions. Front Immunol 2022; 13:987655. [PMID: 36426357 PMCID: PMC9679531 DOI: 10.3389/fimmu.2022.987655] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 10/10/2022] [Indexed: 11/02/2023] Open
Abstract
Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial in organ donation, risk assessment of autoimmune and infectious diseases and cancer immunotherapy. However, due to the high genetic polymorphism in this region, HLA typing requires specialized methods. We investigated the performance of five next-generation sequencing (NGS) based HLA typing tools with a non-restricted license namely HLA*LA, Optitype, HISAT-genotype, Kourami and STC-Seq. This evaluation was done for the five HLA loci, HLA-A, -B, -C, -DRB1 and -DQB1 using whole-exome sequencing (WES) samples from 829 individuals. The robustness of the tools to lower depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype's typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools' robustness to lower DOC data varied widely and further depended on the specific HLA locus. For all Class I loci, Optitype had a typing accuracy above 95% (according to the modification of the amino acids in the functionally relevant portion of the HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA's typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype's typing accuracy is not notably impaired by short read length or by DNA damage, which is typical of aDNA, as long as the DOC is sufficiently high.
Collapse
Affiliation(s)
- Nikolas Hallberg Thuesen
- Evaxion Biotech, Copenhagen, Denmark
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, Lyngby, Denmark
| | | | - Shyam Gopalakrishnan
- Section for Hologenomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | | | - Gabriel Renaud
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, Lyngby, Denmark
| |
Collapse
|
15
|
Dashti M, Al-Matrouk A, Channanath A, Hebbar P, Al-Mulla F, Thanaraj TA. Distribution of HLA-B Alleles and Haplotypes in Qatari: Recommendation for Establishing Pharmacogenomic Markers Screening for Drug Hypersensitivity. Front Pharmacol 2022; 13:891838. [PMID: 36003520 PMCID: PMC9393242 DOI: 10.3389/fphar.2022.891838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 06/14/2022] [Indexed: 11/18/2022] Open
Abstract
Human leukocyte antigen (HLA) proteins are present at the cellular surface of antigen-presenting cells and play a crucial role in the adaptive immune response. Class I genes, specifically certain HLA-B alleles, are associated with adverse drug reactions (ADRs) and are used as pharmacogenetic markers. Although ADRs are a common causes of hospitalization and mortality, the data on the prevalence of HLA-B pharmacogenetics markers in Arab countries are scarce. In this study, we investigated the frequencies of major HLA-B pharmacogenomics markers in the Qatari population. Next-generation sequencing data from 1,098 Qatari individuals were employed for HLA-B typing using HLA-HD version 1.4.0 and IPD-IMGT/HLA database. In addition, HLA-B pharmacogenetics markers were obtained from the HLA Adverse Drug Reaction Database. In total, 469 major HLA-B pharmacogenetic markers were identified, with HLA-B*51:01 being the most frequent pharmacogenetic marker (26.67%) in the Qatari population. Moreover, HLA-B*51:01 is associated with phenytoin- and clindamycin-induced ADRs. The second most frequent pharmacogenetic marker was the HLA-B*58:01 allele (6.56%), which is associated with allopurinol-induced ADRs. The third most frequent pharmacogenetic marker was the HLA-B*44:03 allele, which is associated with phenytoin-induced ADRs. The establishment of a pharmacogenetics screening program in Qatar for cost effective interventions aimed at preventing drug-induced hypersensitivity can be aided by the highly prevalent HLA-B pharmacogenetic markers detected here.
Collapse
Affiliation(s)
- Mohammed Dashti
- Genetics and Bioinformatics Department, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Abdullah Al-Matrouk
- Narcotic and Psychotropic Department, Ministry of Interior, Farwaniya, Kuwait
| | - Arshad Channanath
- Genetics and Bioinformatics Department, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Prashantha Hebbar
- Genetics and Bioinformatics Department, Dasman Diabetes Institute, Kuwait City, Kuwait
| | - Fahd Al-Mulla
- Genetics and Bioinformatics Department, Dasman Diabetes Institute, Kuwait City, Kuwait
- *Correspondence: Fahd Al-Mulla, ; Thangavel Alphonse Thanaraj,
| | - Thangavel Alphonse Thanaraj
- Genetics and Bioinformatics Department, Dasman Diabetes Institute, Kuwait City, Kuwait
- *Correspondence: Fahd Al-Mulla, ; Thangavel Alphonse Thanaraj,
| |
Collapse
|