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Hayashi S, Imoto S. HLA Typing and Mutation Calling from Normal and Tumor Whole Genome Sequencing Data with ALPHLARD-NT. Methods Mol Biol 2024; 2809:101-113. [PMID: 38907893 DOI: 10.1007/978-1-0716-3874-3_7] [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
HLA somatic mutations can alter the expression and function of HLA molecules, which in turn affect the ability of the immune system to recognize and respond to cancer cells. Therefore, it is crucial to accurately identify HLA somatic mutations to enhance our understanding of the interaction between cancer and the immune system and improve cancer treatment strategies. ALPHLARD-NT is a reliable tool that can accurately identify HLA somatic mutations as well as HLA genotypes from whole genome sequencing data of paired normal and tumor samples. Here, we provide a comprehensive guide on how to use ALPHLARD-NT and interpret the results.
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Affiliation(s)
- Shuto Hayashi
- Department of Computational and Systems Biology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
| | - Seiya Imoto
- Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
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Claeys A, Merseburger P, Staut J, Marchal K, Van den Eynden J. Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data. BMC Genomics 2023; 24:247. [PMID: 37161318 PMCID: PMC10170851 DOI: 10.1186/s12864-023-09351-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 04/30/2023] [Indexed: 05/11/2023] Open
Abstract
BACKGROUND The Human Leukocyte Antigen (HLA) genes are a group of highly polymorphic genes that are located in the Major Histocompatibility Complex (MHC) region on chromosome 6. The HLA genotype affects the presentability of tumour antigens to the immune system. While knowledge of these genotypes is of utmost importance to study differences in immune responses between cancer patients, gold standard, PCR-derived genotypes are rarely available in large Next Generation Sequencing (NGS) datasets. Therefore, a variety of methods for in silico NGS-based HLA genotyping have been developed, bypassing the need to determine these genotypes with separate experiments. However, there is currently no consensus on the best performing tool. RESULTS We evaluated 13 MHC class I and/or class II HLA callers that are currently available for free academic use and run on either Whole Exome Sequencing (WES) or RNA sequencing data. Computational resource requirements were highly variable between these tools. Three orthogonal approaches were used to evaluate the accuracy on several large publicly available datasets: a direct benchmark using PCR-derived gold standard HLA calls, a correlation analysis with population-based allele frequencies and an analysis of the concordance between the different tools. The highest MHC-I calling accuracies were found for Optitype (98.0%) and arcasHLA (99.4%) on WES and RNA sequencing data respectively, while for MHC-II HLA-HD was the most accurate tool for both data types (96.2% and 99.4% on WES and RNA data respectively). CONCLUSION The optimal strategy for HLA genotyping from NGS data depends on the availability of either WES or RNA data, the size of the dataset and the available computational resources. If sufficient resources are available, we recommend Optitype and HLA-HD for MHC-I and MHC-II genotype calling respectively.
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Affiliation(s)
- Arne Claeys
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Peter Merseburger
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | - Jasper Staut
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Kathleen Marchal
- Cancer Research Institute Ghent, Ghent, Belgium
- Department of Information Technology, Ghent University, IDLab, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Jimmy Van den Eynden
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium.
- Cancer Research Institute Ghent, Ghent, Belgium.
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Anzar I, Sverchkova A, Samarakoon P, Ellingsen EB, Gaudernack G, Stratford R, Clancy T. Personalized
HLA
typing leads to the discovery of novel
HLA
alleles and tumor‐specific
HLA
variants. HLA 2022; 99:313-327. [PMID: 35073457 PMCID: PMC9546058 DOI: 10.1111/tan.14562] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 01/08/2022] [Accepted: 01/21/2022] [Indexed: 11/29/2022]
Abstract
Accurate and full‐length typing of the HLA region is important in many clinical and research settings. With the advent of next generation sequencing (NGS), several HLA typing algorithms have been developed, including many that are applicable to whole exome sequencing (WES). However, most of these solutions operate by providing the closest‐matched HLA allele among the known alleles in IPD‐IMGT/HLA Database. These database‐matching approaches have demonstrated very high performance when typing well characterized HLA alleles. However, as they rely on the completeness of the HLA database, they are not optimal for detecting novel or less well characterized alleles. Furthermore, the database‐matching approaches are also not adequate in the context of cancer, where a comprehensive characterization of somatic HLA variation and expression patterns of a tumor's HLA locus may guide therapy and clinical outcome, because of the pivotal role HLA alleles play in tumor antigen recognition and immune escape. Here, we describe a personalized HLA typing approach applied to WES data that leverages the strengths of database‐matching approaches while simultaneously allowing for the discovery of novel HLA alleles and tumor‐specific HLA variants, through the systematic integration of germline and somatic variant calling. We applied this approach on WES from 10 metastatic melanoma patients and validated the HLA typing results using HLA targeted NGS sequencing from patients where at least one HLA germline candidate was detected on Class I HLA. Targeted NGS sequencing confirmed 100% performance for the 1st and 2nd fields. In total, five out of the six detected HLA germline variants were because of Class I ambiguities at the third or fourth fields, and their detection recovered the correct HLA allele genotype. The sixth germline variant let to the formal discovery of a novel Class I allele. Finally, we demonstrated a substantially improved somatic variant detection accuracy in HLA alleles with a 91% of success rate in simulated experiments. The approach described here may allow the field to genotype more accurately using WES data, leading to the discovery of novel HLA alleles and help characterize the relationship between somatic variation in the HLA region and immunosurveillance.
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Affiliation(s)
- Irantzu Anzar
- NEC OncoImmunity AS, Oslo Cancer Cluster, Ullernchausseen 64/66, 0379 Oslo Norway
| | - Angelina Sverchkova
- NEC OncoImmunity AS, Oslo Cancer Cluster, Ullernchausseen 64/66, 0379 Oslo Norway
| | - Pubudu Samarakoon
- NEC OncoImmunity AS, Oslo Cancer Cluster, Ullernchausseen 64/66, 0379 Oslo Norway
| | | | - Gustav Gaudernack
- Ultimovacs ASA, Oslo Cancer Cluster, Ullernchausseen 64/66 Oslo Norway
| | - Richard Stratford
- NEC OncoImmunity AS, Oslo Cancer Cluster, Ullernchausseen 64/66, 0379 Oslo Norway
| | - Trevor Clancy
- NEC OncoImmunity AS, Oslo Cancer Cluster, Ullernchausseen 64/66, 0379 Oslo Norway
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Douillard V, Castelli EC, Mack SJ, Hollenbach JA, Gourraud PA, Vince N, Limou S. Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research. Front Genet 2021; 12:774916. [PMID: 34925459 PMCID: PMC8677840 DOI: 10.3389/fgene.2021.774916] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/08/2021] [Indexed: 01/11/2023] Open
Abstract
The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.
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Affiliation(s)
- Venceslas Douillard
- Centre de Recherche en Transplantation et Immunologie, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, Université de Nantes, Nantes, France
| | | | - Steven J. Mack
- Division of Allergy, Immunology and Bone Marrow Transplantation, Department of Pediatrics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Jill A. Hollenbach
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
| | - Pierre-Antoine Gourraud
- Centre de Recherche en Transplantation et Immunologie, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, Université de Nantes, Nantes, France
| | - Nicolas Vince
- Centre de Recherche en Transplantation et Immunologie, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, Université de Nantes, Nantes, France
| | - Sophie Limou
- Centre de Recherche en Transplantation et Immunologie, CHU Nantes, Inserm, Centre de Recherche en Transplantation et Immunologie, Université de Nantes, Nantes, France
- Ecole Centrale de Nantes, Department of Computer Sciences and Mathematics in Biology, Nantes, France
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Stokidis S, Fortis SP, Kogionou P, Anagnostou T, Perez SA, Baxevanis CN. HLA Class I Allele Expression and Clinical Outcome in De Novo Metastatic Prostate Cancer. Cancers (Basel) 2020; 12:cancers12061623. [PMID: 32570992 PMCID: PMC7352811 DOI: 10.3390/cancers12061623] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/09/2020] [Accepted: 06/11/2020] [Indexed: 12/15/2022] Open
Abstract
The prognostic value of human leukocyte antigen (HLA) class I molecules in prostate cancer (PCa) remains unclear. Herein, we investigated the prognostic relevance of the most frequently expressed HLA-A alleles in Greece (A*02:01 and HLA-A*24:02) in de novo metastatic hormone-sensitive PCa (mPCa), which is a rare and aggressive disease characterized by a rapid progression to castration-resistance (CR) and poor overall survival (OS), contributing to almost 50% of PCa-related deaths. We identified 56 patients who had either progressed to CR (these patients were retrospectively analyzed for the time to the progression of CR and prospectively for OS) or had at least three months’ follow-up postdiagnosis without CR progression and, thus, were prospectively analyzed for both CR and OS. Patients expressing HLA-A*02:01 showed poor clinical outcomes vs. HLA-A*02:01−negative patients. HLA-A*24:02−positive patients progressed slower to CR and had increased OS. Homozygous HLA-A*02:01 patients progressed severely to CR, with very short OS. Multivariate analyses ascribed to both HLA alleles significant prognostic values for the time to progression (TTP) to CR and OS. The presence of HLA-A*02:01 and HLA-A*24:02 alleles in de novo mPCa patients are significantly and independently associated with unfavorable or favorable clinical outcomes, respectively, suggesting their possible prognostic relevance for treatment decision-making in the context of precision medicine.
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Affiliation(s)
- Savvas Stokidis
- Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, 171 Alexandras avenue, 11522 Athens, Greece; (S.S.); (S.P.F.); (P.K.); (S.A.P.)
| | - Sotirios P. Fortis
- Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, 171 Alexandras avenue, 11522 Athens, Greece; (S.S.); (S.P.F.); (P.K.); (S.A.P.)
| | - Paraskevi Kogionou
- Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, 171 Alexandras avenue, 11522 Athens, Greece; (S.S.); (S.P.F.); (P.K.); (S.A.P.)
| | - Theodoros Anagnostou
- Department of Urology, Saint Savas Cancer Hospital, 171 Alexandras avenue, 11522 Athens, Greece;
| | - Sonia A. Perez
- Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, 171 Alexandras avenue, 11522 Athens, Greece; (S.S.); (S.P.F.); (P.K.); (S.A.P.)
| | - Constantin N. Baxevanis
- Cancer Immunology and Immunotherapy Center, Saint Savas Cancer Hospital, 171 Alexandras avenue, 11522 Athens, Greece; (S.S.); (S.P.F.); (P.K.); (S.A.P.)
- Correspondence: ; Tel.: +30-210-640-9624
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