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Zinter MS, Dvorak CC, Mayday MY, Reyes G, Simon MR, Pearce EM, Kim H, Shaw PJ, Rowan CM, Auletta JJ, Martin PL, Godder K, Duncan CN, Lalefar NR, Kreml EM, Hume JR, Abdel-Azim H, Hurley C, Cuvelier GDE, Keating AK, Qayed M, Killinger JS, Fitzgerald JC, Hanna R, Mahadeo KM, Quigg TC, Satwani P, Castillo P, Gertz SJ, Moore TB, Hanisch B, Abdel-Mageed A, Phelan R, Davis DB, Hudspeth MP, Yanik GA, Pulsipher MA, Sulaiman I, Segal LN, Versluys BA, Lindemans CA, Boelens JJ, DeRisi JL. Pathobiological signatures of dysbiotic lung injury in pediatric patients undergoing stem cell transplantation. Nat Med 2024:10.1038/s41591-024-02999-4. [PMID: 38783139 DOI: 10.1038/s41591-024-02999-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 04/12/2024] [Indexed: 05/25/2024]
Abstract
Hematopoietic cell transplantation (HCT) uses cytotoxic chemotherapy and/or radiation followed by intravenous infusion of stem cells to cure malignancies, bone marrow failure and inborn errors of immunity, hemoglobin and metabolism. Lung injury is a known complication of the process, due in part to disruption in the pulmonary microenvironment by insults such as infection, alloreactive inflammation and cellular toxicity. How microorganisms, immunity and the respiratory epithelium interact to contribute to lung injury is uncertain, limiting the development of prevention and treatment strategies. Here we used 278 bronchoalveolar lavage (BAL) fluid samples to study the lung microenvironment in 229 pediatric patients who have undergone HCT treated at 32 children's hospitals between 2014 and 2022. By leveraging paired microbiome and human gene expression data, we identified high-risk BAL compositions associated with in-hospital mortality (P = 0.007). Disadvantageous profiles included bacterial overgrowth with neutrophilic inflammation, microbiome contraction with epithelial fibroproliferation and profound commensal depletion with viral and staphylococcal enrichment, lymphocytic activation and cellular injury, and were replicated in an independent cohort from the Netherlands (P = 0.022). In addition, a broad array of previously occult pathogens was identified, as well as a strong link between antibiotic exposure, commensal bacterial depletion and enrichment of viruses and fungi. Together these lung-immune system-microorganism interactions clarify the important drivers of fatal lung injury in pediatric patients who have undergone HCT. Further investigation is needed to determine how personalized interpretation of heterogeneous pulmonary microenvironments may be used to improve pediatric HCT outcomes.
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Affiliation(s)
- Matt S Zinter
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
- Division of Allergy, Immunology, and Bone Marrow Transplantation, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
| | - Christopher C Dvorak
- Division of Allergy, Immunology, and Bone Marrow Transplantation, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Madeline Y Mayday
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Departments of Laboratory Medicine and Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Gustavo Reyes
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Miriam R Simon
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Emma M Pearce
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Hanna Kim
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Peter J Shaw
- The Children's Hospital at Westmead, Sydney, New South Wales, Australia
| | - Courtney M Rowan
- Department of Pediatrics, Division of Critical Care Medicine, Indiana University, Indianapolis, IN, USA
| | - Jeffrey J Auletta
- Hematology/Oncology/BMT and Infectious Diseases, Nationwide Children's Hospital, Columbus, OH, USA
- Center for International Blood and Marrow Transplant Research, National Marrow Donor Program/Be The Match, Minneapolis, MN, USA
| | - Paul L Martin
- Division of Pediatric and Cellular Therapy, Duke University Medical Center, Durham, NC, USA
| | - Kamar Godder
- Cancer and Blood Disorders Center, Nicklaus Children's Hospital, Miami, FL, USA
| | - Christine N Duncan
- Division of Pediatric Oncology Harvard Medical School Department of Pediatrics, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA, USA
| | - Nahal R Lalefar
- Division of Pediatric Hematology/Oncology, Benioff Children's Hospital Oakland, University of California, San Francisco, Oakland, CA, USA
| | - Erin M Kreml
- Department of Child Health, Division of Critical Care Medicine, University of Arizona, Phoenix, AZ, USA
| | - Janet R Hume
- Department of Pediatrics, Division of Critical Care Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Hisham Abdel-Azim
- Department of Pediatrics, Division of Hematology/Oncology and Transplant and Cell Therapy, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Loma Linda University School of Medicine, Cancer Center, Children Hospital and Medical Center, Loma Linda, CA, USA
| | - Caitlin Hurley
- Department of Pediatric Medicine, Division of Critical Care, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Geoffrey D E Cuvelier
- CancerCare Manitoba, Manitoba Blood and Marrow Transplant Program, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Amy K Keating
- Division of Pediatric Oncology Harvard Medical School Department of Pediatrics, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA, USA
- Center for Cancer and Blood Disorders, Children's Hospital Colorado and University of Colorado, Aurora, CO, USA
| | - Muna Qayed
- Aflac Cancer & Blood Disorders Center, Children's Healthcare of Atlanta and Emory University, Atlanta, GA, USA
| | - James S Killinger
- Department of Pediatrics, Division of Pediatric Critical Care, Weill Cornell Medicine, New York, NY, USA
| | - Julie C Fitzgerald
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
| | - Rabi Hanna
- Department of Pediatric Hematology, Oncology and Blood and Marrow Transplantation, Pediatric Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Kris M Mahadeo
- Division of Pediatric and Cellular Therapy, Duke University Medical Center, Durham, NC, USA
- Department of Pediatrics, Division of Hematology/Oncology, MD Anderson Cancer Center, Houston, TX, USA
| | - Troy C Quigg
- Pediatric Blood and Marrow Transplantation Program, Texas Transplant Institute, Methodist Children's Hospital, San Antonio, TX, USA
- Section of Pediatric BMT and Cellular Therapy, Helen DeVos Children's Hospital, Grand Rapids, MI, USA
| | - Prakash Satwani
- Department of Pediatrics, Division of Pediatric Hematology, Oncology and Stem Cell Transplantation, Columbia University, New York, NY, USA
| | - Paul Castillo
- UF Health Shands Children's Hospital, University of Florida, Gainesville, FL, USA
| | - Shira J Gertz
- Department of Pediatrics, Division of Critical Care Medicine, Joseph M Sanzari Children's Hospital at Hackensack University Medical Center, Hackensack, NJ, USA
- Department of Pediatrics, Division of Critical Care Medicine, St. Barnabas Medical Center, Livingston, NJ, USA
| | - Theodore B Moore
- Department of Pediatric Hematology-Oncology, Mattel Children's Hospital, University of California, Los Angeles, Los Angeles, CA, USA
| | - Benjamin Hanisch
- Department of Pediatrics, Division of Infectious Diseases, Children's National Hospital, Washington DC, USA
| | - Aly Abdel-Mageed
- Section of Pediatric BMT and Cellular Therapy, Helen DeVos Children's Hospital, Grand Rapids, MI, USA
| | - Rachel Phelan
- Department of Pediatrics, Division of Pediatric Hematology/Oncology/BMT, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Dereck B Davis
- Department of Pediatrics, Hematology/Oncology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Michelle P Hudspeth
- Adult and Pediatric Blood & Marrow Transplantation, Pediatric Hematology/Oncology, Medical University of South Carolina Children's Hospital/Hollings Cancer Center, Charleston, SC, USA
| | - Greg A Yanik
- Pediatric Blood and Bone Marrow Transplantation, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Michael A Pulsipher
- Division of Hematology, Oncology, Transplantation, and Immunology, Primary Children's Hospital, Huntsman Cancer Institute, Spense Fox Eccles School of Medicine at the University of Utah, Salt Lake City, UT, USA
| | - Imran Sulaiman
- Department of Respiratory Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Laura and Isaac Perlmutter Cancer Center, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, USA
| | - Leopoldo N Segal
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Laura and Isaac Perlmutter Cancer Center, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, USA
| | - Birgitta A Versluys
- Department of Stem Cell Transplantation, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Division of Pediatrics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Caroline A Lindemans
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Laura and Isaac Perlmutter Cancer Center, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, USA
- Department of Stem Cell Transplantation, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Jaap J Boelens
- Department of Stem Cell Transplantation, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Division of Pediatrics, University Medical Center Utrecht, Utrecht, the Netherlands
- Transplantation and Cellular Therapy, MSK Kids, Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joseph L DeRisi
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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Song J, Kim D, Jung J, Choi E, Lee Y, Jeong Y, Lee B, Lee S, Shim Y, Won Y, Cho H, Jang DK, Kang HW, Joo JWJ, Jang W. Elucidating immunological characteristics of the adenoma-carcinoma sequence in colorectal cancer patients in South Korea using a bioinformatics approach. Sci Rep 2024; 14:10105. [PMID: 38698020 PMCID: PMC11066069 DOI: 10.1038/s41598-024-56078-2] [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: 08/03/2023] [Accepted: 03/01/2024] [Indexed: 05/05/2024] Open
Abstract
Colorectal cancer (CRC) is one of the top five most common and life-threatening malignancies worldwide. Most CRC develops from advanced colorectal adenoma (ACA), a precancerous stage, through the adenoma-carcinoma sequence. However, its underlying mechanisms, including how the tumor microenvironment changes, remain elusive. Therefore, we conducted an integrative analysis comparing RNA-seq data collected from 40 ACA patients who visited Dongguk University Ilsan Hospital with normal adjacent colons and tumor samples from 18 CRC patients collected from a public database. Differential expression analysis identified 21 and 79 sequentially up- or down-regulated genes across the continuum, respectively. The functional centrality of the continuum genes was assessed through network analysis, identifying 11 up- and 13 down-regulated hub-genes. Subsequently, we validated the prognostic effects of hub-genes using the Kaplan-Meier survival analysis. To estimate the immunological transition of the adenoma-carcinoma sequence, single-cell deconvolution and immune repertoire analyses were conducted. Significant composition changes for innate immunity cells and decreased plasma B-cells with immunoglobulin diversity were observed, along with distinctive immunoglobulin recombination patterns. Taken together, we believe our findings suggest underlying transcriptional and immunological changes during the adenoma-carcinoma sequence, contributing to the further development of pre-diagnostic markers for CRC.
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Affiliation(s)
- Jaeseung Song
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Daeun Kim
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Junghyun Jung
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
- Division of AI Software Convergence, Dongguk University-Seoul, Seoul, 04620, South Korea
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA
| | - Eunyoung Choi
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Yubin Lee
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Yeonbin Jeong
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Byungjo Lee
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Sora Lee
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Yujeong Shim
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Youngtae Won
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea
| | - Hyeki Cho
- Department of Internal Medicine, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, 10326, South Korea
| | - Dong Kee Jang
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, 07061, South Korea
| | - Hyoun Woo Kang
- Department of Internal Medicine, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, 10326, South Korea.
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, 07061, South Korea.
| | - Jong Wha J Joo
- Division of AI Software Convergence, Dongguk University-Seoul, Seoul, 04620, South Korea.
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University, Seoul, 04620, South Korea.
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Nieuwenhuis TO, Giles HH, Arking JVA, Patil AH, Shi W, McCall MN, Halushka MK. Patterns of Unwanted Biological and Technical Expression Variation Among 49 Human Tissues. J Transl Med 2024; 104:102069. [PMID: 38670317 DOI: 10.1016/j.labinv.2024.102069] [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: 12/06/2023] [Revised: 03/21/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype-Tissue Expression data set (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores, and only the most variable 2% of transcripts were evaluated and clustered based on coexpression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median: 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations, and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens data set of single-cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single-cell RNA-seq data.
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Affiliation(s)
- Tim O Nieuwenhuis
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland; McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Hunter H Giles
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jeremy V A Arking
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Arun H Patil
- Lieber Institute for Brain Development, Baltimore, Maryland
| | - Wen Shi
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Matthew N McCall
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York; Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, New York
| | - Marc K Halushka
- Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio.
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Serebrovskaya EO, Bryushkova EA, Lukyanov DK, Mushenkova NV, Chudakov DM, Turchaninova MA. Toolkit for mapping the clonal landscape of tumor-infiltrating B cells. Semin Immunol 2024; 72:101864. [PMID: 38301345 DOI: 10.1016/j.smim.2024.101864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Accepted: 01/08/2024] [Indexed: 02/03/2024]
Abstract
Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.
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Affiliation(s)
- E O Serebrovskaya
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Current position: Miltenyi Biotec B.V. & Co. KG, Bergisch Gladbach, Germany
| | - E A Bryushkova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Department of Molecular Biology, Lomonosov Moscow State University, Moscow, Russia
| | - D K Lukyanov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - N V Mushenkova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Unicorn Capital Partners, 119049, Moscow, Russia
| | - D M Chudakov
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
| | - M A Turchaninova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia
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Kim D, Song J, Mancuso N, Mangul S, Jung J, Jang W. Large-scale integrative analysis of juvenile idiopathic arthritis for new insight into its pathogenesis. Arthritis Res Ther 2024; 26:47. [PMID: 38336809 PMCID: PMC10858498 DOI: 10.1186/s13075-024-03280-2] [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: 09/29/2023] [Accepted: 01/29/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Juvenile idiopathic arthritis (JIA) is one of the most prevalent rheumatic disorders in children and is classified as an autoimmune disease (AID). While a robust genetic contribution to JIA etiology has been established, the exact pathogenesis remains unclear. METHODS To prioritize biologically interpretable susceptibility genes and proteins for JIA, we conducted transcriptome-wide and proteome-wide association studies (TWAS/PWAS). Then, to understand the genetic architecture of JIA, we systematically analyzed single-nucleotide polymorphism (SNP)-based heritability, a signature of natural selection, and polygenicity. Next, we conducted HLA typing using multi-ethnicity RNA sequencing data. Additionally, we examined the T cell receptor (TCR) repertoire at a single-cell level to explore the potential links between immunity and JIA risk. RESULTS We have identified 19 TWAS genes and two PWAS proteins associated with JIA risks. Furthermore, we observe that the heritability and cell type enrichment analysis of JIA are enriched in T lymphocytes and HLA regions and that JIA shows higher polygenicity compared to other AIDs. In multi-ancestry HLA typing, B*45:01 is more prevalent in African JIA patients than in European JIA patients, whereas DQA1*01:01, DQA1*03:01, and DRB1*04:01 exhibit a higher frequency in European JIA patients. Using single-cell immune repertoire analysis, we identify clonally expanded T cell subpopulations in JIA patients, including CXCL13+BHLHE40+ TH cells which are significantly associated with JIA risks. CONCLUSION Our findings shed new light on the pathogenesis of JIA and provide a strong foundation for future mechanistic studies aimed at uncovering the molecular drivers of JIA.
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Affiliation(s)
- Daeun Kim
- Department of Life Sciences, Dongguk University-Seoul, Seoul, 04620, Republic of Korea
| | - Jaeseung Song
- Department of Life Sciences, Dongguk University-Seoul, Seoul, 04620, Republic of Korea
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
| | - Serghei Mangul
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Junghyun Jung
- Department of Life Sciences, Dongguk University-Seoul, Seoul, 04620, Republic of Korea.
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA.
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University-Seoul, Seoul, 04620, Republic of Korea.
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Zhang D, Zhang H, Lu J, Hu X. Multiomics Data Reveal the Important Role of ANXA2R in T Cell-mediated Rejection After Renal Transplantation. Transplantation 2024; 108:430-444. [PMID: 37677931 PMCID: PMC10798590 DOI: 10.1097/tp.0000000000004754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 06/14/2023] [Accepted: 06/29/2023] [Indexed: 09/09/2023]
Abstract
BACKGROUND T cell-mediated rejection (TCMR) is a severe issue after renal transplantation, but research on its T cell-receptor (TCR) repertoire is lacking. This study intended to elucidate the TCR repertoire landscape in TCMR and hence identify novel potential targets. METHODS A total of 12 multiomics data sets were collected. The TRUST4 algorithm was used to construct and analyze the TCR repertoire in renal allografts with TCMR and stable renal function. Then, novel TCR-related key genes were identified through various criteria and literature research. In bulk transcriptome, cell line, single-cell transcriptome data sets, multiple immune cell infiltration algorithms, and gene set enrichment analysis were used to analyze potential mechanisms of the identified key gene. Twenty-three pathological sections were collected for immunofluorescence staining in the clinical cohort. Finally, the diagnostic and prognostic values of ANXA2R were evaluated in multiple renal transplant data sets. RESULTS Allografts with TCMR showed significantly increased clonotype and specific clonal expansion. ANXA2R was found to be a novel key gene for TCMR and showed strong positive connections with the TCR complex and lymphocyte cells, especially CD8 + T cells. Immunofluorescence staining confirmed the existence of ANXA2R + CD8 + T cells, with their percentage significantly elevated in TCMR compared with stable renal function. Finally, both mRNA and protein levels of ANXA2R showed promising diagnostic and prognostic value for renal transplant recipients. CONCLUSIONS ANXA2R , identified as a novel TCR-related gene, had critical roles in clinicopathology, diagnosis, and prognosis in renal transplantation, which offered promising potential therapeutic targets.
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Affiliation(s)
- Di Zhang
- Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
- Institute of Urology, Capital Medical University, Beijing, China
| | - He Zhang
- Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
- Institute of Urology, Capital Medical University, Beijing, China
| | - Jun Lu
- Department of Pathology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xiaopeng Hu
- Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
- Institute of Urology, Capital Medical University, Beijing, China
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Wang L, Xu Z, Zhang W, Li L, Liu X, Zhang J. Comprehensive characterization and database construction of immune repertoire in the largest Chinese glioma cohort. iScience 2024; 27:108661. [PMID: 38205245 PMCID: PMC10777385 DOI: 10.1016/j.isci.2023.108661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/27/2023] [Accepted: 12/05/2023] [Indexed: 01/12/2024] Open
Abstract
Immune receptor repertoire is valuable for developing immunotherapeutic interventions, but remains poorly understood across glioma subtypes including IDH wild type, IDH mutation without 1p/19q codeletion (IDHmut-noncodel) and IDH mutation with 1p/19q codeletion (IDHmut-codel). We assembled over 320,000 TCR/BCR clonotypes from the largest glioma cohort of 913 RNA sequencing samples in the Chinese population, finding that immune repertoire diversity was more prominent in the IDH wild type (the most aggressive glioma). Fewer clonotypes were shared within each glioma subtype, indicating high heterogeneity of the immune repertoire. The TRA-CDR3 was longer in private than in public clonotypes in IDH wild type. CDR3 variable motifs had higher proportions of hydrophobic residues in private than in public clonotypes, suggesting private CDR3 sequences have greater potential for tumor antigen recognition. Finally, we developed GTABdb, a web-based database designed for hosting, exploring, visualizing, and analyzing glioma immune repertoire. Our study will facilitate developing glioma immunotherapy.
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Affiliation(s)
- Lu Wang
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Zhiyuan Xu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Wei Zhang
- Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, People’s Republic of China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring Road West, Fengtai District, Beijing 100070, People’s Republic of China
| | - Lin Li
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Xiao Liu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Jing Zhang
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
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Addala V, Newell F, Pearson JV, Redwood A, Robinson BW, Creaney J, Waddell N. Computational immunogenomic approaches to predict response to cancer immunotherapies. Nat Rev Clin Oncol 2024; 21:28-46. [PMID: 37907723 DOI: 10.1038/s41571-023-00830-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2023] [Indexed: 11/02/2023]
Abstract
Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data from bulk tissue or single cells and explore tumours and their microenvironment. The rapid growth in sequencing and computational approaches has resulted in the unmet need to understand their true potential and limitations in enabling improvements in the management of patients with cancer who are receiving immunotherapies. In this Review, we describe the computational approaches currently available to analyse bulk tissue and single-cell sequencing data from cancer, stromal and immune cells, as well as how best to select the most appropriate tool to address various clinical questions and, ultimately, improve patient outcomes.
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Affiliation(s)
- Venkateswar Addala
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
| | - Felicity Newell
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - John V Pearson
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Alec Redwood
- National Centre for Asbestos Related Diseases, University of Western Australia, Perth, Western Australia, Australia
- Institute of Respiratory Health, Perth, Western Australia, Australia
- School of Biomedical Science, University of Western Australia, Perth, Western Australia, Australia
| | - Bruce W Robinson
- National Centre for Asbestos Related Diseases, University of Western Australia, Perth, Western Australia, Australia
- Institute of Respiratory Health, Perth, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
- Medical School, University of Western Australia, Perth, Western Australia, Australia
| | - Jenette Creaney
- National Centre for Asbestos Related Diseases, University of Western Australia, Perth, Western Australia, Australia
- Institute of Respiratory Health, Perth, Western Australia, Australia
- School of Biomedical Science, University of Western Australia, Perth, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Nicola Waddell
- Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
- Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
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9
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Yang JO, Zinter MS, Pellegrini M, Wong MY, Gala K, Markovic D, Nadel B, Peng K, Do N, Mangul S, Nadkarni VM, Karlsberg A, Deshpande D, Butte MJ, Asaro L, Agus M, Sapru A. Whole blood transcriptomics identifies subclasses of pediatric septic shock. Crit Care 2023; 27:486. [PMID: 38066613 PMCID: PMC10709863 DOI: 10.1186/s13054-023-04689-y] [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: 08/15/2023] [Accepted: 10/14/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. METHODS The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. RESULTS Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires. CONCLUSIONS Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.
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Affiliation(s)
- Jamie O Yang
- UCLA Department of Internal Medicine, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Matt S Zinter
- UCSF Department of Pediatrics, San Francisco, CA, USA
| | - Matteo Pellegrini
- UCLA Department of Molecular, Cell, and Developmental Biology, Los Angeles, CA, USA
| | - Man Yee Wong
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA
| | - Kinisha Gala
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA
| | - Daniela Markovic
- UCLA Department of Medicine Statistics Core, Los Angeles, CA, USA
| | - Brian Nadel
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Kerui Peng
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Nguyen Do
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA
| | - Serghei Mangul
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, Los Angeles, CA, USA
| | - Vinay M Nadkarni
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron Karlsberg
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Dhrithi Deshpande
- USC Department of Clinical Pharmacy, USC Alfred E Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, USA
| | - Manish J Butte
- Division of Immunology, Allergy, and Rheumatology, UCLA Department of Pediatrics, Los Angeles, CA, USA
| | - Lisa Asaro
- Department of Pediatrics, Division of Medical Critical Care, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael Agus
- Department of Pediatrics, Division of Medical Critical Care, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Anil Sapru
- Division of Pediatric Critical Care, UCLA Department of Pediatrics, UCLA Mattel Children's Hospital, Los Angeles, CA, USA.
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10
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Budeus B, Kibler A, Küppers R. Human IgM-expressing memory B cells. Front Immunol 2023; 14:1308378. [PMID: 38143767 PMCID: PMC10748387 DOI: 10.3389/fimmu.2023.1308378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 11/27/2023] [Indexed: 12/26/2023] Open
Abstract
A hallmark of T cell dependent (TD) humoral immune responses is the generation of long-lived memory B cells. The generation of these cells occurs primarily in the germinal center (GC) reaction, where antigen-activated B cells undergo affinity maturation as a major consequence of the combined processes of proliferation, somatic hypermutation of their immunoglobulin V (IgV) region genes, and selection for improved affinity of their B-cell antigen receptors. As many B cells also undergo class-switching to IgG or IgA in these TD responses, there was traditionally a focus on class-switched memory B cells in both murine and human studies on memory B cells. However, it has become clear that there is also a large subset of IgM-expressing memory B cells, which have important phenotypic and functional similarities but also differences to class-switched memory B cells. There is an ongoing discussion about the origin of distinct subsets of human IgM+ B cells with somatically mutated IgV genes. We argue here that the vast majority of human IgM-expressing B cells with somatically mutated IgV genes in adults is indeed derived from GC reactions, even though a generation of some mostly lowly mutated IgM+ B cells from other differentiation pathways, mainly in early life, may exist.
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Affiliation(s)
| | | | - Ralf Küppers
- Institute of Cell Biology (Cancer Research), Medical Faculty, University of Duisburg–Essen, Essen, Germany
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11
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Zinter MS, Dvorak CC, Mayday MY, Reyes G, Simon MR, Pearce EM, Kim H, Shaw PJ, Rowan CM, Auletta JJ, Martin PL, Godder K, Duncan CN, Lalefar NR, Kreml EM, Hume JR, Abdel-Azim H, Hurley C, Cuvelier GDE, Keating AK, Qayed M, Killinger JS, Fitzgerald JC, Hanna R, Mahadeo KM, Quigg TC, Satwani P, Castillo P, Gertz SJ, Moore TB, Hanisch B, Abdel-Mageed A, Phelan R, Davis DB, Hudspeth MP, Yanik GA, Pulsipher MA, Sulaiman I, Segal LN, Versluys BA, Lindemans CA, Boelens JJ, DeRisi JL. Pulmonary microbiome and transcriptome signatures reveal distinct pathobiologic states associated with mortality in two cohorts of pediatric stem cell transplant patients. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.29.23299130. [PMID: 38077035 PMCID: PMC10705623 DOI: 10.1101/2023.11.29.23299130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Lung injury is a major determinant of survival after pediatric hematopoietic cell transplantation (HCT). A deeper understanding of the relationship between pulmonary microbes, immunity, and the lung epithelium is needed to improve outcomes. In this multicenter study, we collected 278 bronchoalveolar lavage (BAL) samples from 229 patients treated at 32 children's hospitals between 2014-2022. Using paired metatranscriptomes and human gene expression data, we identified 4 patient clusters with varying BAL composition. Among those requiring respiratory support prior to sampling, in-hospital mortality varied from 22-60% depending on the cluster (p=0.007). The most common patient subtype, Cluster 1, showed a moderate quantity and high diversity of commensal microbes with robust metabolic activity, low rates of infection, gene expression indicating alveolar macrophage predominance, and low mortality. The second most common cluster showed a very high burden of airway microbes, gene expression enriched for neutrophil signaling, frequent bacterial infections, and moderate mortality. Cluster 3 showed significant depletion of commensal microbes, a loss of biodiversity, gene expression indicative of fibroproliferative pathways, increased viral and fungal pathogens, and high mortality. Finally, Cluster 4 showed profound microbiome depletion with enrichment of Staphylococci and viruses, gene expression driven by lymphocyte activation and cellular injury, and the highest mortality. BAL clusters were modeled with a random forest classifier and reproduced in a geographically distinct validation cohort of 57 patients from The Netherlands, recapitulating similar cluster-based mortality differences (p=0.022). Degree of antibiotic exposure was strongly associated with depletion of BAL microbes and enrichment of fungi. Potential pathogens were parsed from all detected microbes by analyzing each BAL microbe relative to the overall microbiome composition, which yielded increased sensitivity for numerous previously occult pathogens. These findings support personalized interpretation of the pulmonary microenvironment in pediatric HCT, which may facilitate biology-targeted interventions to improve outcomes.
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Affiliation(s)
- Matt S Zinter
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Division of Allergy, Immunology, and Bone Marrow Transplantation, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Christopher C Dvorak
- Division of Allergy, Immunology, and Bone Marrow Transplantation, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Madeline Y Mayday
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
- Departments of Laboratory Medicine and Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Gustavo Reyes
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Miriam R Simon
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Emma M Pearce
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Hanna Kim
- Division of Critical Care Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Peter J Shaw
- The Children`s Hospital at Westmead, Sydney, Australia
| | - Courtney M Rowan
- Indiana University, Department of Pediatrics, Division of Critical Care Medicine, Indianapolis, IN, USA
| | - Jeffrey J Auletta
- Hematology/Oncology/BMT and Infectious Diseases, Nationwide Children's Hospital, Columbus, OH, USA
- CIBMTR (Center for International Blood and Marrow Transplant Research), National Marrow Donor Program/Be The Match, Minneapolis, MN, USA
| | - Paul L Martin
- Division of Pediatric and Cellular Therapy, Duke University Medical Center, Durham, NC, USA
| | - Kamar Godder
- Cancer and Blood Disorders Center, Nicklaus Children's Hospital, Miami, FL, USA
| | - Christine N Duncan
- Harvard Medical School, Boston, Massachusetts; Division of Pediatric Oncology, Department of Pediatrics, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA, USA
| | - Nahal R Lalefar
- Division of Pediatric Hematology/Oncology, UCSF Benioff Children's Hospital Oakland, University of California San Francisco, Oakland, CA, USA
| | - Erin M Kreml
- Department of Child Health, Division of Critical Care Medicine, University of Arizona, Phoenix, AZ, USA
| | - Janet R Hume
- University of Minnesota, Department of Pediatrics, Division of Critical Care Medicine, Minneapolis, MN, USA
| | - Hisham Abdel-Azim
- Department of Pediatrics, Division of Hematology/Oncology and Transplant and Cell Therapy, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Loma Linda University School of Medicine, Cancer Center, Children Hospital and Medical Center, Loma Linda, CA, USA
| | - Caitlin Hurley
- Division of Critical Care, Department of Pediatric Medicine, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Geoffrey D E Cuvelier
- CancerCare Manitoba, Manitoba Blood and Marrow Transplant Program, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Amy K Keating
- Center for Cancer and Blood Disorders, Children's Hospital Colorado and University of Colorado, Aurora, CO, USA
- Harvard Medical School, Boston, Massachusetts; Division of Pediatric Oncology, Department of Pediatrics, Dana-Farber Cancer Institute and Boston Children's Hospital, Boston, MA, USA
| | - Muna Qayed
- Aflac Cancer & Blood Disorders Center, Children's Healthcare of Atlanta and Emory University, Atlanta, GA, USA
| | - James S Killinger
- Division of Pediatric Critical Care, Department of Pediatrics, Weill Cornell Medicine, New York, NY, USA
| | - Julie C Fitzgerald
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
| | - Rabi Hanna
- Department of Pediatric Hematology, Oncology and Blood and Marrow Transplantation, Pediatric Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Kris M Mahadeo
- Department of Pediatrics, Division of Hematology/Oncology, MD Anderson Cancer Center, Houston, TX, USA
- Division of Pediatric and Cellular Therapy, Duke University Medical Center, Durham, NC, USA
| | - Troy C Quigg
- Pediatric Blood and Marrow Transplantation Program, Texas Transplant Institute, Methodist Children's Hospital, San Antonio, TX, USA
- Section of Pediatric BMT and Cellular Therapy, Helen DeVos Children's Hospital, Grand Rapids, MI, USA
| | - Prakash Satwani
- Division of Pediatric Hematology, Oncology and Stem Cell Transplantation, Department of Pediatrics, Columbia University, New York, NY, USA
| | - Paul Castillo
- University of Florida, Gainesville, UF Health Shands Children's Hospital, Gainesville, FL, USA
| | - Shira J Gertz
- Department of Pediatrics, Division of Critical Care Medicine, Joseph M Sanzari Children's Hospital at Hackensack University Medical Center, Hackensack, NJ, USA
- Department of Pediatrics, St. Barnabas Medical Center, Livingston, NJ, USA
| | - Theodore B Moore
- Department of Pediatric Hematology-Oncology, Mattel Children's Hospital, University of California, Los Angeles, CA, USA
| | - Benjamin Hanisch
- Children's National Hospital, Washington, District of Columbia, USA
| | - Aly Abdel-Mageed
- Section of Pediatric BMT and Cellular Therapy, Helen DeVos Children's Hospital, Grand Rapids, MI, USA
| | - Rachel Phelan
- Division of Pediatric Hematology/Oncology/BMT, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Dereck B Davis
- Department of Pediatrics, Hematology/Oncology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Michelle P Hudspeth
- Adult and Pediatric Blood & Marrow Transplantation, Pediatric Hematology/Oncology, Medical University of South Carolina Children's Hospital/Hollings Cancer Center, Charleston, SC, USA
| | - Greg A Yanik
- Pediatric Blood and Bone Marrow Transplantation, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Michael A Pulsipher
- Division of Hematology, Oncology, Transplantation, and Immunology, Primary Children's Hospital, Huntsman Cancer Institute, Spense Fox Eccles School of Medicine at the University of Utah, Salt Lake City, UT, USA
| | - Imran Sulaiman
- Departments of Respiratory Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Laura and Isaac Perlmutter Cancer Center, New York University Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, USA
| | - Leopoldo N Segal
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Laura and Isaac Perlmutter Cancer Center, New York University Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, USA
| | - Birgitta A Versluys
- Department of Stem Cell Transplantation, Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
- Division of Pediatrics, University Medical Center Utrecht, Utrecht, Netherlands
| | - Caroline A Lindemans
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Laura and Isaac Perlmutter Cancer Center, New York University Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, USA
- Department of Stem Cell Transplantation, Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
| | - Jaap J Boelens
- Department of Stem Cell Transplantation, Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
- Division of Pediatrics, University Medical Center Utrecht, Utrecht, Netherlands
- Transplantation and Cellular Therapy, MSK Kids, Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joseph L DeRisi
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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12
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Davydov AN, Bolotin DA, Poslavsky SV, Chudakov DM. Comment on 'rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing'. Brief Bioinform 2023; 24:bbad354. [PMID: 37824737 PMCID: PMC10569745 DOI: 10.1093/bib/bbad354] [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] [Received: 08/14/2023] [Revised: 09/14/2023] [Accepted: 09/17/2023] [Indexed: 10/14/2023] Open
Abstract
Transcriptome sequencing has become common in cancer research, resulting in the generation of a substantial volume of RNA sequencing (RNA-Seq) data. The ability to extract immune repertoires from these data is crucial for obtaining information on infiltrating T- and B-lymphocyte clones when dedicated amplicon T-cell/B-cell receptors sequencing (TCR-Seq/BCR-Seq) methods are unavailable. In response to this demand, several dedicated computational methods have been developed, including MiXCR, TRUST and ImRep. In the recent publication in Briefings in Bioinformatics, Peng et al. have conducted an intensive, systematic comparison of the three previously mentioned tools. Although their effort is commendable, we do have a few constructive critiques regarding technical elements of their analysis.
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Affiliation(s)
- Alexey N Davydov
- MiLaboratories Inc, San Francisco, CA, USA
- Central European Institute of Technology, Brno, Czech Republic
| | | | | | - Dmitry M Chudakov
- MiLaboratories Inc, San Francisco, CA, USA
- Central European Institute of Technology, Brno, Czech Republic
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13
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Yang JO, Zinter MS, Pellegrini M, Wong MY, Gala K, Markovic D, Nadel B, Peng K, Do N, Mangul S, Nadkarni VM, Karlsberg A, Deshpande D, Butte MJ, Asaro L, Agus M, Sapru A. Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock. RESEARCH SQUARE 2023:rs.3.rs-3267057. [PMID: 37693502 PMCID: PMC10491329 DOI: 10.21203/rs.3.rs-3267057/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background Sepsis is a highly heterogeneous syndrome, that has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. Methods The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA-sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. Results Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells, and less diverse T-Cell receptor repertoires. Conclusions Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF PINT ancillary of the HALF PINT study (NCT01565941). Registered 29 March 2012.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Nguyen Do
- University of California, Los Angeles
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14
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Chatterjee A, Chaudhary A, Ghosh A, Arun P, Mukherjee G, Arun I, Maitra A, Biswas N, Majumder PP. Overexpression of CD73 is associated with recurrence and poor prognosis of gingivobuccal oral cancer as revealed by transcriptome and deep immune profiling of paired tumor and margin tissues. Cancer Med 2023; 12:16774-16787. [PMID: 37392167 PMCID: PMC10501293 DOI: 10.1002/cam4.6299] [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: 03/10/2023] [Revised: 06/16/2023] [Accepted: 06/18/2023] [Indexed: 07/03/2023] Open
Abstract
BACKGROUND For various cancers, differences in response to treatment and subsequent survival period have been reported to be associated with variation in immune contextures. AIM We sought to identify whether such association exists in respect of gingivobuccal oral cancer. MATERIALS AND METHODS We performed deep immune profiling of tumor and margin tissues collected from 46 treatment naïve, Human Papillomavirus (HPV) negative, patients. Each patient was followed for 24 months and prognosis (recurrence/death) noted. Key findings were validated by comparing with TCGA-HNSC cohort data. RESULTS About 28% of patients showed poor post-treatment prognosis. These patients exhibited a high probability of recurrence even within 1 year and death within 2 years. There was restricted immune cell infiltration in tumor, but not in margin, among these patients. Reduced expression of eight immune-related genes (IRGs) (NT5E, THRA, RBP1, TLR4, ITGA6, BMPR1B, ITGAV, SSTR1) in tumor strongly predicted better quality of prognosis, both in our patient cohort and in TCGA-HNSC cohort. Tumors of patients with better prognosis were associated with (a) lower CD73+ cells with concomitant lower expression level of NT5E/CD73, (b) higher proportions of CD4+ and CD8+ T cells, B cells, NK cells, M1 macrophages, (c) higher %Granzyme+ cells, (d) higher TCR and BCR repertoire diversities. CD73 expression in tumor was associated with low CD8+ and CD4+ T cells, low immune repertoire diversity, and advanced cancer stage. DISCUSSION AND CONCLUSION High infiltration of anti-tumor immune cells in both tumors and margins results in good prognosis, while in patients with minimal infiltration in tumors in spite of high infiltration in margins results in poor prognosis. Targeted CD73 immune-checkpoint inhibition may improve clinical outcome.
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Affiliation(s)
- Ankita Chatterjee
- National Institute of Biomedical GenomicsKalyaniIndia
- John C. Martin Centre for Liver Research and InnovationsKolkataIndia
| | | | - Arnab Ghosh
- National Institute of Biomedical GenomicsKalyaniIndia
| | | | | | | | | | - Nidhan Biswas
- National Institute of Biomedical GenomicsKalyaniIndia
| | - Partha P. Majumder
- National Institute of Biomedical GenomicsKalyaniIndia
- John C. Martin Centre for Liver Research and InnovationsKolkataIndia
- Indian Statistical InstituteKolkataIndia
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15
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Peng K, Nowicki TS, Campbell K, Vahed M, Peng D, Meng Y, Nagareddy A, Huang YN, Karlsberg A, Miller Z, Brito J, Nadel B, Pak VM, Abedalthagafi MS, Burkhardt AM, Alachkar H, Ribas A, Mangul S. Rigorous benchmarking of T-cell receptor repertoire profiling methods for cancer RNA sequencing. Brief Bioinform 2023; 24:bbad220. [PMID: 37291798 PMCID: PMC10359085 DOI: 10.1093/bib/bbad220] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 05/02/2023] [Accepted: 05/24/2023] [Indexed: 06/10/2023] Open
Abstract
The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.
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Affiliation(s)
- Kerui Peng
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Theodore S Nowicki
- Department of Pediatrics, Division of Pediatric Hematology/Oncology, University of California, Los Angeles, CA, USA
- Department of Microbiology, Immunology, & Molecular Genetics, University of California, Los Angeles, CA, USA
| | - Katie Campbell
- Department of Medicine, Division of Hematology-Oncology, University of California, Los Angeles, CA, USA
| | - Mohammad Vahed
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Dandan Peng
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
| | - Yiting Meng
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Anish Nagareddy
- Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Yu-Ning Huang
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Aaron Karlsberg
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Zachary Miller
- Department of Pharmaceutical Sciences, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Jaqueline Brito
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Brian Nadel
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, CA, USA
| | - Victoria M Pak
- Emory Nell Hodgson School of Nursing, Emory University, Atlanta, GA, USA
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Malak S Abedalthagafi
- Department of Pathology & Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
- King Salman Center for Disability Research, Riyadh, Saudi Arabia
| | - Amanda M Burkhardt
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Houda Alachkar
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Antoni Ribas
- Departments of Medicine (Hematology-Oncology), Surgery (Surgical Oncology) and Molecular & Medical Pharmacology, University of California, Los Angeles, CA, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
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16
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Pan X, López Acevedo SN, Cuziol C, De Tavernier E, Fahad AS, Longjam PS, Rao SP, Aguilera-Rodríguez D, Rezé M, Bricault CA, Gutiérrez-González MF, de Souza MO, DiNapoli JM, Vigne E, Shahsavarian MA, DeKosky BJ. Large-scale antibody immune response mapping of splenic B cells and bone marrow plasma cells in a transgenic mouse model. Front Immunol 2023; 14:1137069. [PMID: 37346047 PMCID: PMC10280637 DOI: 10.3389/fimmu.2023.1137069] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/30/2023] [Indexed: 06/23/2023] Open
Abstract
Molecular characterization of antibody immunity and human antibody discovery is mainly carried out using peripheral memory B cells, and occasionally plasmablasts, that express B cell receptors (BCRs) on their cell surface. Despite the importance of plasma cells (PCs) as the dominant source of circulating antibodies in serum, PCs are rarely utilized because they do not express surface BCRs and cannot be analyzed using antigen-based fluorescence-activated cell sorting. Here, we studied the antibodies encoded by the entire mature B cell populations, including PCs, and compared the antibody repertoires of bone marrow and spleen compartments elicited by immunization in a human immunoglobulin transgenic mouse strain. To circumvent prior technical limitations for analysis of plasma cells, we applied single-cell antibody heavy and light chain gene capture from the entire mature B cell repertoires followed by yeast display functional analysis using a cytokine as a model immunogen. We performed affinity-based sorting of antibody yeast display libraries and large-scale next-generation sequencing analyses to follow antibody lineage performance, with experimental validation of 76 monoclonal antibodies against the cytokine antigen that identified three antibodies with exquisite double-digit picomolar binding affinity. We observed that spleen B cell populations generated higher affinity antibodies compared to bone marrow PCs and that antigen-specific splenic B cells had higher average levels of somatic hypermutation. A degree of clonal overlap was also observed between bone marrow and spleen antibody repertoires, indicating common origins of certain clones across lymphoid compartments. These data demonstrate a new capacity to functionally analyze antigen-specific B cell populations of different lymphoid organs, including PCs, for high-affinity antibody discovery and detailed fundamental studies of antibody immunity.
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Affiliation(s)
- Xiaoli Pan
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS, United States
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), and Harvard, Cambridge, MA, United States
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Sheila N. López Acevedo
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS, United States
| | - Camille Cuziol
- Large Molecule Research, Sanofi, Vitry sur Seine, France
| | | | - Ahmed S. Fahad
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), and Harvard, Cambridge, MA, United States
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | | | | | | | - Mathilde Rezé
- Large Molecule Research, Sanofi, Vitry sur Seine, France
| | | | - Matías F. Gutiérrez-González
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), and Harvard, Cambridge, MA, United States
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Matheus Oliveira de Souza
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS, United States
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), and Harvard, Cambridge, MA, United States
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | | | | | | | - Brandon J. DeKosky
- Department of Pharmaceutical Chemistry, The University of Kansas, Lawrence, KS, United States
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), and Harvard, Cambridge, MA, United States
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Chemical Engineering, The University of Kansas, Lawrence, KS, United States
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17
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Tippalagama R, Chihab LY, Kearns K, Lewis S, Panda S, Willemsen L, Burel JG, Lindestam Arlehamn CS. Antigen-specificity measurements are the key to understanding T cell responses. Front Immunol 2023; 14:1127470. [PMID: 37122719 PMCID: PMC10140422 DOI: 10.3389/fimmu.2023.1127470] [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: 12/19/2022] [Accepted: 03/30/2023] [Indexed: 05/02/2023] Open
Abstract
Antigen-specific T cells play a central role in the adaptive immune response and come in a wide range of phenotypes. T cell receptors (TCRs) mediate the antigen-specificities found in T cells. Importantly, high-throughput TCR sequencing provides a fingerprint which allows tracking of specific T cells and their clonal expansion in response to particular antigens. As a result, many studies have leveraged TCR sequencing in an attempt to elucidate the role of antigen-specific T cells in various contexts. Here, we discuss the published approaches to studying antigen-specific T cells and their specific TCR repertoire. Further, we discuss how these methods have been applied to study the TCR repertoire in various diseases in order to characterize the antigen-specific T cells involved in the immune control of disease.
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18
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Kibler A, Seifert M, Budeus B. Age-related changes of the human splenic marginal zone B cell compartment. Immunol Lett 2023; 256-257:59-65. [PMID: 37044264 DOI: 10.1016/j.imlet.2023.04.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/24/2023] [Accepted: 04/07/2023] [Indexed: 04/14/2023]
Abstract
In this review, we will summarize the growing body of knowledge on the age-related changes of human splenic B cell composition and molecular evidence of immune maturation and discuss the contribution of these changes on splenic protective function. From birth on, the splenic marginal zone (sMZ) contains a specialized B cell subpopulation, which recruits and archives memory B cells from immune responses throughout the organism. The quality of sMZ B cell responses is augmented by germinal center (GC)-dependent maturation of memory B cells during childhood, however, in old age, these mechanisms likely contribute to waning of splenic protective function.
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Affiliation(s)
- Artur Kibler
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Marc Seifert
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany; Department of Hematology, Oncology and Clinical Immunology, Heinrich-Heine University, Düsseldorf, Germany.
| | - Bettina Budeus
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
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19
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Deshpande D, Chhugani K, Chang Y, Karlsberg A, Loeffler C, Zhang J, Muszyńska A, Munteanu V, Yang H, Rotman J, Tao L, Balliu B, Tseng E, Eskin E, Zhao F, Mohammadi P, P. Łabaj P, Mangul S. RNA-seq data science: From raw data to effective interpretation. Front Genet 2023; 14:997383. [PMID: 36999049 PMCID: PMC10043755 DOI: 10.3389/fgene.2023.997383] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 02/24/2023] [Indexed: 03/14/2023] Open
Abstract
RNA sequencing (RNA-seq) has become an exemplary technology in modern biology and clinical science. Its immense popularity is due in large part to the continuous efforts of the bioinformatics community to develop accurate and scalable computational tools to analyze the enormous amounts of transcriptomic data that it produces. RNA-seq analysis enables genes and their corresponding transcripts to be probed for a variety of purposes, such as detecting novel exons or whole transcripts, assessing expression of genes and alternative transcripts, and studying alternative splicing structure. It can be a challenge, however, to obtain meaningful biological signals from raw RNA-seq data because of the enormous scale of the data as well as the inherent limitations of different sequencing technologies, such as amplification bias or biases of library preparation. The need to overcome these technical challenges has pushed the rapid development of novel computational tools, which have evolved and diversified in accordance with technological advancements, leading to the current myriad of RNA-seq tools. These tools, combined with the diverse computational skill sets of biomedical researchers, help to unlock the full potential of RNA-seq. The purpose of this review is to explain basic concepts in the computational analysis of RNA-seq data and define discipline-specific jargon.
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Affiliation(s)
- Dhrithi Deshpande
- Department of Pharmacology and Pharmaceutical Sciences, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, United States
| | - Karishma Chhugani
- Department of Pharmacology and Pharmaceutical Sciences, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, United States
| | - Yutong Chang
- Department of Pharmacology and Pharmaceutical Sciences, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, United States
| | - Aaron Karlsberg
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, United States
| | - Caitlin Loeffler
- Department of Computer Science, University of California, Los Angeles, CA, United States
| | - Jinyang Zhang
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, China
| | - Agata Muszyńska
- Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Institute of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland
| | - Viorel Munteanu
- Department of Computers, Informatics and Microelectronics, Technical University of Moldova, Chisinau, Moldova
| | - Harry Yang
- Department of Microbiology, Immunology and Molecular Genetics, University of California Los Angeles, Los Angeles, CA, United States
| | - Jeremy Rotman
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, United States
| | - Laura Tao
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, CHS, Los Angeles, CA, United States
| | - Brunilda Balliu
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, CHS, Los Angeles, CA, United States
| | | | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, CA, United States
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, CHS, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
| | - Pejman Mohammadi
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, United States
| | - Paweł P. Łabaj
- Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Department of Biotechnology, Boku University Vienna, Vienna, Austria
| | - Serghei Mangul
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, CA, United States
- Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, Los Angeles, CA, United States
- *Correspondence: Serghei Mangul,
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20
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Nieuwenhuis TO, Giles HH, McCall MN, Halushka MK. Patterns of unwanted biological and technical expression variation across 49 human tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.09.531935. [PMID: 36945408 PMCID: PMC10028996 DOI: 10.1101/2023.03.09.531935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2023]
Abstract
All tissue-based gene expression studies are impacted by biological and technical sources of variation. Numerous methods are used to normalize and batch correct these datasets. A more accurate understanding of all causes of variation could further optimize these approaches. We used 17,282 samples from 49 tissues in the Genotype Tissue Expression (GTEx) dataset (v8) to investigate patterns and causes of expression variation. Transcript expression was normalized to Z-scores and only the most variable 2% of transcripts were evaluated and clustered based on co-expression patterns. Clustered gene sets were solved to different biological or technical causes related to metadata elements and histologic images. We identified 522 variable transcript clusters (median 11 per tissue) across the samples. Of these, 64% were confidently explained, 15% were likely explained, 7% were low confidence explanations and 14% had no clear cause. Common causes included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), muscle atrophy, diabetes status, and menopause. Technical causes included brain pH and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens dataset of single cell expression. This is the largest exploration of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression. These identified sources of variation will inform which metadata to acquire with tissue harvesting and can be used to improve normalization, batch correction, and analysis of both bulk and single cell RNA-seq data.
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Affiliation(s)
- Tim O Nieuwenhuis
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hunter H Giles
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Matthew N McCall
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Biomedical Genetics, University of Rochester Medical Center, Rochester, NY, USA
| | - Marc K Halushka
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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21
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Valpione S, Campana LG, Weightman J, Salih Z, Galvani E, Mundra PA, De Rosa F, Gupta A, Serra-Bellver P, Lorigan P, Germetaki T, Dynowski M, Kitcatt S, Sahoo S, Lee D, Dhomen N, Lord G, Marais R. Tumour infiltrating B cells discriminate checkpoint blockade-induced responses. Eur J Cancer 2022; 177:164-174. [PMID: 36347135 DOI: 10.1016/j.ejca.2022.09.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Immune cell-driven anti-cancer activity is paramount for effective responses to checkpoint inhibitors (ICB). However, the contribution of the different immune cell subsets in the circulation and within the tumour is poorly understood. MATERIALS AND METHODS To elucidate the role of the different cell subsets in anti-tumour responses elicited by ICB, we performed single-cell analysis of the transcriptome and surface proteome of paired pre- and early on-treatment metastatic melanoma tumour biopsies and matched peripheral blood mononuclear cell samples. We next compared the survival of metastatic melanoma patients treated with ICB according to the abundance of pre-treatment tumour-infiltrating B cell clonotypes. RESULTS We identified cell clusters associated with disease control or progression, defined differential expression of biological pathways likely involved in the immune awakening against the tumour and examined how cell-cell communication patterns between the tumour cell subsets change during treatment. Furthermore, we discovered that B cells (immunoglobulin expression and abundance of B cell clonotypes) discriminate the clinical response after ICB and propose that B cells likely contribute to anti-tumour immunity by antigen presentation through major histocompatibility complex molecules. Finally, we demonstrated that the abundance of tumour-infiltrating B cell clonotypes at baseline identifies two distinct risk groups, a finding that we confirmed in an independent cohort. CONCLUSIONS Our exploratory translational study provides new insights on the mechanistic role of B cells in anti-melanoma immunity during treatment with ICB. Additionally, we support pre-treatment B cell tumour infiltration as a promising prognostic biomarker to be further validated as a tool for clinical risk stratification.
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Affiliation(s)
- Sara Valpione
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom; The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, United Kingdom.
| | - Luca G Campana
- Department of Surgery, Manchester University NHS Foundation Trust, Manchester, United Kingdom
| | - John Weightman
- Molecular Biology Core Facility, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Zena Salih
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom; The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, United Kingdom
| | - Elena Galvani
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Piyushkumar A Mundra
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Francesco De Rosa
- Immunotherapy and Rare Tumours Unit, Istituto Scientifico Romagnolo per Lo Studio e La Cura Dei Tumori (IRST) "Dino Amadori" IRCCS, Meldola (FC) 47014, Italy
| | - Avinash Gupta
- The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, United Kingdom
| | - Patricio Serra-Bellver
- The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, United Kingdom
| | - Paul Lorigan
- The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, United Kingdom
| | - Theodora Germetaki
- The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester M20 4BX, United Kingdom
| | - Marek Dynowski
- Scientific Computing, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Stephen Kitcatt
- Scientific Computing, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Sudhakar Sahoo
- Computational Biology Support Team, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Dave Lee
- Computational Biology Support Team, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Nathalie Dhomen
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom
| | - Graham Lord
- School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, United Kingdom
| | - Richard Marais
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, United Kingdom.
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22
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Forst CV, Chung M, Hockman M, Lashua L, Adney E, Hickey A, Carlock M, Ross T, Ghedin E, Gresham D. Vaccination History, Body Mass Index, Age, and Baseline Gene Expression Predict Influenza Vaccination Outcomes. Viruses 2022; 14:2446. [PMID: 36366544 PMCID: PMC9697051 DOI: 10.3390/v14112446] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
Seasonal influenza is a primary public health burden in the USA and globally. Annual vaccination programs are designed on the basis of circulating influenza viral strains. However, the effectiveness of the seasonal influenza vaccine is highly variable between seasons and among individuals. A number of factors are known to influence vaccination effectiveness including age, sex, and comorbidities. Here, we sought to determine whether whole blood gene expression profiling prior to vaccination is informative about pre-existing immunological status and the immunological response to vaccine. We performed whole transcriptome analysis using RNA sequencing (RNAseq) of whole blood samples obtained prior to vaccination from 275 participants enrolled in an annual influenza vaccine trial. Serological status prior to vaccination and 28 days following vaccination was assessed using the hemagglutination inhibition assay (HAI) to define baseline immune status and the response to vaccination. We find evidence that genes with immunological functions are increased in expression in individuals with higher pre-existing immunity and in those individuals who mount a greater response to vaccination. Using a random forest model, we find that this set of genes can be used to predict vaccine response with a performance similar to a model that incorporates physiological and prior vaccination status alone. A model using both gene expression and physiological factors has the greatest predictive power demonstrating the potential utility of molecular profiling for enhancing prediction of vaccine response. Moreover, expression of genes that are associated with enhanced vaccination response may point to additional biological pathways that contribute to mounting a robust immunological response to the seasonal influenza vaccine.
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Affiliation(s)
- Christian V. Forst
- Department of Genetics and Genomic Sciences, Department of Microbiology, Icahn School of Medicine at Mt Sinai, One Gustave L. Levy Place, Box 1498, New York, NY 10029-6574, USA
| | - Matthew Chung
- Systems Genomics Section, Laboratory of Parasitic Diseases, NIAID, NIH, Bethesda, MD 20894, USA
| | - Megan Hockman
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Lauren Lashua
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Emily Adney
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Angela Hickey
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Michael Carlock
- Center for Vaccines and Immunology, University of Georgia, Athens, GA 30602, USA
- Department of Infectious Diseases, University of Georgia, Athens, GA 30602, USA
| | - Ted Ross
- Center for Vaccines and Immunology, University of Georgia, Athens, GA 30602, USA
- Department of Infectious Diseases, University of Georgia, Athens, GA 30602, USA
| | - Elodie Ghedin
- Systems Genomics Section, Laboratory of Parasitic Diseases, NIAID, NIH, Bethesda, MD 20894, USA
| | - David Gresham
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
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23
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Nakamura K, Okuyama R. Changes in the Immune Cell Repertoire for the Treatment of Malignant Melanoma. Int J Mol Sci 2022; 23:12991. [PMID: 36361781 PMCID: PMC9658693 DOI: 10.3390/ijms232112991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 10/26/2022] [Indexed: 10/10/2023] Open
Abstract
Immune checkpoint inhibitors (ICIs) have been used for the treatment of various types of cancers, including malignant melanoma. Mechanistic exploration of tumor immune responses is essential to improve the therapeutic efficacy of ICIs. Since tumor immune responses are based on antigen-specific immune responses, investigators have focused on T cell receptors (TCRs) and have analyzed changes in the TCR repertoire. The proliferation of T cell clones against tumor antigens is detected in patients who respond to treatment with ICIs. The proliferation of these T cell clones is observed within tumors as well as in the peripheral blood. Clonal proliferation has been detected not only in CD8-positive T cells but also in CD4-positive T cells, resident memory T cells, and B cells. Moreover, changes in the repertoire at an early stage of treatment seem to be useful for predicting the therapeutic efficacy of ICIs. Further analyses of the repertoire of immune cells are desirable to improve and predict the therapeutic efficacy of ICIs.
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Affiliation(s)
- Kenta Nakamura
- Department of Dermatology, Shinshu University School of Medicine, Matsumoto 390-8621, Japan
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24
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Mikelov AI, Alekseeva EI, Komech EA, Staroverov DB, Turchaninova MA, Shugay M, Chudakov DM, Bazykin GA, Zvyagin IV. Memory persistence and differentiation into antibody-secreting cells accompanied by positive selection in longitudinal BCR repertoires. eLife 2022; 11:79254. [PMID: 36107479 PMCID: PMC9525062 DOI: 10.7554/elife.79254] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 09/11/2022] [Indexed: 11/18/2022] Open
Abstract
The stability and plasticity of B cell-mediated immune memory ensures the ability to respond to the repeated challenges. We have analyzed the longitudinal dynamics of immunoglobulin heavy chain repertoires from memory B cells, plasmablasts, and plasma cells from the peripheral blood of generally healthy volunteers. We reveal a high degree of clonal persistence in individual memory B cell subsets, with inter-individual convergence in memory and antibody-secreting cells (ASCs). ASC clonotypes demonstrate clonal relatedness to memory B cells, and are transient in peripheral blood. We identify two clusters of expanded clonal lineages with differing prevalence of memory B cells, isotypes, and persistence. Phylogenetic analysis revealed signs of reactivation of persisting memory B cell-enriched clonal lineages, accompanied by new rounds of affinity maturation during proliferation and differentiation into ASCs. Negative selection contributes to both persisting and reactivated lineages, preserving the functionality and specificity of B cell receptors (BCRs) to protect against current and future pathogens.
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Affiliation(s)
| | | | | | | | | | | | | | - Georgii A Bazykin
- Institute of Translational Medicine, Pirogov Russian National Research Medical University
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25
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Andreani T, Slot LM, Gabillard S, Strübing C, Reimertz C, Yaligara V, Bakker AM, Olfati-Saber R, Toes REM, Scherer HU, Augé F, Šimaitė D. Benchmarking computational methods for B-cell receptor reconstruction from single-cell RNA-seq data. NAR Genom Bioinform 2022; 4:lqac049. [PMID: 35855325 PMCID: PMC9278041 DOI: 10.1093/nargab/lqac049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/30/2022] [Accepted: 06/21/2022] [Indexed: 11/12/2022] Open
Abstract
Multiple methods have recently been developed to reconstruct full-length B-cell receptors (BCRs) from single-cell RNA sequencing (scRNA-seq) data. This need emerged from the expansion of scRNA-seq techniques, the increasing interest in antibody-based drug development and the importance of BCR repertoire changes in cancer and autoimmune disease progression. However, a comprehensive assessment of performance-influencing factors such as the sequencing depth, read length or number of somatic hypermutations (SHMs) as well as guidance regarding the choice of methodology is still lacking. In this work, we evaluated the ability of six available methods to reconstruct full-length BCRs using one simulated and three experimental SMART-seq datasets. In addition, we validated that the BCRs assembled in silico recognize their intended targets when expressed as monoclonal antibodies. We observed that methods such as BALDR, BASIC and BRACER showed the best overall performance across the tested datasets and conditions, whereas only BASIC demonstrated acceptable results on very short read libraries. Furthermore, the de novo assembly-based methods BRACER and BALDR were the most accurate in reconstructing BCRs harboring different degrees of SHMs in the variable domain, while TRUST4, MiXCR and BASIC were the fastest. Finally, we propose guidelines to select the best method based on the given data characteristics.
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Affiliation(s)
- Tommaso Andreani
- AI & Deep Analytics—Omics Data Science, Sanofi , Frankfurt am Main 65926, Germany
| | - Linda M Slot
- Department of Rheumatology, Leiden University Medical Center , 2333 RC Leiden, The Netherlands
| | | | - Carsten Strübing
- Immunology & Inflammation Research, Sanofi , Frankfurt am Main 65926, Germany
| | - Claus Reimertz
- Immunology & Inflammation Research, Sanofi , Frankfurt am Main 65926, Germany
| | - Veeranagouda Yaligara
- Molecular Biology & Genomics, Translational Science Unit, Sanofi , Chilly-Mazarin 91385, France
| | - Aleida M Bakker
- Department of Rheumatology, Leiden University Medical Center , 2333 RC Leiden, The Netherlands
| | | | - René E M Toes
- Department of Rheumatology, Leiden University Medical Center , 2333 RC Leiden, The Netherlands
| | - Hans U Scherer
- Department of Rheumatology, Leiden University Medical Center , 2333 RC Leiden, The Netherlands
| | - Franck Augé
- AI & Deep Analytics—Omics Data Science, Sanofi , Paris 91385, France
| | - Deimantė Šimaitė
- AI & Deep Analytics—Omics Data Science, Sanofi , Frankfurt am Main 65926, Germany
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26
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Song L, Ouyang Z, Cohen D, Cao Y, Altreuter J, Bai G, Hu X, Livak KJ, Li H, Tang M, Li B, Shirley Liu X. Comprehensive Characterizations of Immune Receptor Repertoire in Tumors and Cancer Immunotherapy Studies. Cancer Immunol Res 2022; 10:788-799. [PMID: 35605261 PMCID: PMC9299271 DOI: 10.1158/2326-6066.cir-21-0965] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/17/2022] [Accepted: 05/20/2022] [Indexed: 01/03/2023]
Abstract
We applied our computational algorithm TRUST4 to assemble immune receptor (T-cell receptor/B-cell receptor) repertoires from approximately 12,000 RNA sequencing samples from The Cancer Genome Atlas and seven immunotherapy studies. From over 35 million assembled complete complementary-determining region 3 sequences, we observed that the expression of CCL5 and MZB1 is the most positively correlated genes with T-cell clonal expansion and B-cell clonal expansion, respectively. We analyzed amino acid evolution during B-cell receptor somatic hypermutation and identified tyrosine as the preferred residue. We found that IgG1+IgG3 antibodies together with FcRn were associated with complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity or phagocytosis. In addition to B-cell infiltration, we discovered that B-cell clonal expansion and IgG1+IgG3 antibodies are also correlated with better patient outcomes. Finally, we created a website, VisualizIRR, for users to interactively explore and visualize the immune repertoires in this study. See related Spotlight by Liu and Han, p. 786.
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Affiliation(s)
- Li Song
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhangyi Ouyang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Experimental Hematology and Biochemistry, Beijing Institute of Radiation Medicine, Beijing, China
| | - David Cohen
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Yang Cao
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- College of Life Sciences, Sichuan University, Chengdu, Sichuan, China
| | - Jennifer Altreuter
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Gali Bai
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Xihao Hu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Current affiliation: GV20 Therapeutics, Cambridge, MA, USA
| | - Kenneth J. Livak
- Department of Medical, Dana-Farber Cancer Institute, Boston, MA, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Ming Tang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Bo Li
- Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - X. Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
- Current affiliation: GV20 Therapeutics, Cambridge, MA, USA
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27
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Abstract
High-throughput sequencing for B cell receptor (BCR) repertoire provides useful insights for the adaptive immune system. With the continuous development of the BCR-seq technology, many efforts have been made to develop methods for analyzing the ever-increasing BCR repertoire data. In this review, we comprehensively outline different BCR repertoire library preparation protocols and summarize three major steps of BCR-seq data analysis, i. e., V(D)J sequence annotation, clonal phylogenetic inference, and BCR repertoire profiling and mining. Different from other reviews in this field, we emphasize background intuition and the statistical principle of each method to help biologists better understand it. Finally, we discuss data mining problems for BCR-seq data and with a highlight on recently emerging multiple-sample analysis.
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28
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Neoantigens – the next frontier in precision immunotherapy for B-cell lymphoproliferative disorders. Blood Rev 2022; 56:100969. [DOI: 10.1016/j.blre.2022.100969] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 12/20/2022]
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29
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Wang Y, Xue H, Aglave M, Lainé A, Gallopin M, Gautheret D. The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma. NAR Cancer 2022; 4:zcac001. [PMID: 35118386 PMCID: PMC8807116 DOI: 10.1093/narcan/zcac001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 11/18/2021] [Accepted: 01/10/2022] [Indexed: 11/12/2022] Open
Abstract
The identity of cancer cells is defined by the interplay between genetic, epigenetic transcriptional and post-transcriptional variation. A lot of this variation is present in RNA-seq data and can be captured at once using reference-free, k-mer analysis. An important issue with k-mer analysis, however, is the difficulty of distinguishing signal from noise. Here, we use two independent lung adenocarcinoma datasets to identify all reproducible events at the k-mer level, in a tumor versus normal setting. We find reproducible events in many different locations (introns, intergenic, repeats) and forms (spliced, polyadenylated, chimeric etc.). We systematically analyze events that are ignored in conventional transcriptomics and assess their value as biomarkers and for tumor classification, survival prediction, neoantigen prediction and correlation with the immune microenvironment. We find that unannotated lincRNAs, novel splice variants, endogenous HERV, Line1 and Alu repeats and bacterial RNAs each contribute to different, important aspects of tumor identity. We argue that differential RNA-seq analysis of tumor/normal sample collections would benefit from this type k-mer analysis to cast a wider net on important cancer-related events. The code is available at https://github.com/Transipedia/dekupl-lung-cancer-inter-cohort.
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Affiliation(s)
- Yunfeng Wang
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France
- Annoroad Gene Technology Co., Ltd, 100176 Beijing, China
| | - Haoliang Xue
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France
| | - Marine Aglave
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France
- Gustave Roussy, 114 rue Edouard Vaillant, 94800, Villejuif, France
| | - Antoine Lainé
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France
| | - Mélina Gallopin
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France
| | - Daniel Gautheret
- Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France
- Gustave Roussy, 114 rue Edouard Vaillant, 94800, Villejuif, France
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30
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Yu K, Ravoor A, Malats N, Pineda S, Sirota M. A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires. Front Immunol 2022; 12:790119. [PMID: 35069569 PMCID: PMC8767103 DOI: 10.3389/fimmu.2021.790119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/06/2021] [Indexed: 12/22/2022] Open
Abstract
Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.
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Affiliation(s)
- Katharine Yu
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco (UCSF), San Francisco, CA, United States
| | - Akshay Ravoor
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), San Francisco, CA, United States
| | - Núria Malats
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), and Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Silvia Pineda
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), and Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco (UCSF), San Francisco, CA, United States
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31
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Gong X, Yan H, Ma J, Zhu Z, Zhang S, Xu W, Huang J, Qiu X. Macrophage-Derived Immunoglobulin M Inhibits Inflammatory Responses via Modulating Endoplasmic Reticulum Stress. Cells 2021; 10:cells10112812. [PMID: 34831038 PMCID: PMC8616491 DOI: 10.3390/cells10112812] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/16/2021] [Accepted: 10/18/2021] [Indexed: 12/23/2022] Open
Abstract
Immunoglobulin (Ig), a characteristic marker of B cells, is a multifunctional evolutionary conserved antibody critical for maintaining tissue homeostasis and developing fully protective humoral responses to pathogens. Increasing evidence revealed that Ig is widely expressed in non-immune cells; moreover, Ig produced by different lineages cells plays different biological roles. Recently, it has been reported that monocytes or macrophages also express Ig. However, its function remains unclear. In this study, we further identified that Ig, especially Ig mu heavy chain (IgM), was mainly expressed in mice macrophages. We also analyzed the IgM repertoire characteristic in macrophages and found that the VHDJH rearrangements of macrophage-derived IgM showed a restricted and conservative VHDJH pattern, which differed from the diverse VHDJH rearrangement pattern of the B cell-expressed IgM in an individual. Functional investigation showed that IgM knockdown significantly promoted macrophage migration and FAK/Src-Akt axis activation. Furthermore, some inflammatory cytokines such as MCP1 and IL-6 increased after IgM knockdown under LPS stimulation. A mechanism study revealed that the IgM interacted with binding immunoglobulin protein (Bip) and inhibited inflammatory response and unfolded protein response (UPR) activation in macrophages. Our data elucidate a previously unknown function of IgM in macrophages that explains its ability to act as a novel regulator of Bip to participate in endoplasmic reticulum stress and further regulate the inflammatory response.
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Affiliation(s)
- Xiaoting Gong
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Huige Yan
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Junfan Ma
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Zhu Zhu
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Shenghua Zhang
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Weiyan Xu
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
| | - Jing Huang
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
- Correspondence: (J.H.); (X.Q.); Tel.: +86-108-280-2846 (J.H.); +86-108-280-5477 (X.Q.)
| | - Xiaoyan Qiu
- Department of Immunology, School of Basic Medical Sciences, Peking University, Beijing 100191, China; (X.G.); (H.Y.); (J.M.); (Z.Z.); (S.Z.); (W.X.)
- NHC Key Laboratory of Medical Immunology, Peking University, Beijing 100191, China
- Key Laboratory of Molecular Immunology, Chinese Academy of Medical Sciences, Beijing 100191, China
- Correspondence: (J.H.); (X.Q.); Tel.: +86-108-280-2846 (J.H.); +86-108-280-5477 (X.Q.)
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32
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Ghraichy M, von Niederhäusern V, Kovaltsuk A, Galson JD, Deane CM, Trück J. Different B cell subpopulations show distinct patterns in their IgH repertoire metrics. eLife 2021; 10:73111. [PMID: 34661527 PMCID: PMC8560093 DOI: 10.7554/elife.73111] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/17/2021] [Indexed: 12/11/2022] Open
Abstract
Several human B cell subpopulations are recognised in the peripheral blood, which play distinct roles in the humoral immune response. These cells undergo developmental and maturational changes involving VDJ recombination, somatic hypermutation and class switch recombination, altogether shaping their immunoglobulin heavy chain (IgH) repertoire. Here, we sequenced the IgH repertoire of naïve, marginal zone, switched and plasma cells from 10 healthy adults along with matched unsorted and in silico separated CD19+ bulk B cells. Using advanced bioinformatic analysis and machine learning, we show that sorted B cell subpopulations are characterised by distinct repertoire characteristics on both the individual sequence and the repertoire level. Sorted subpopulations shared similar repertoire characteristics with their corresponding in silico separated subsets. Furthermore, certain IgH repertoire characteristics correlated with the position of the constant region on the IgH locus. Overall, this study provides unprecedented insight over mechanisms of B cell repertoire control in peripherally circulating B cell subpopulations.
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Affiliation(s)
- Marie Ghraichy
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
| | - Valentin von Niederhäusern
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
| | | | - Jacob D Galson
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland.,Alchemab Therapeutics Ltd, London, United Kingdom
| | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Johannes Trück
- Division of Immunology, University Children's Hospital and Children's Research Center, University of Zurich (UZH), Zurich, Switzerland
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33
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Kibler A, Budeus B, Homp E, Bronischewski K, Berg V, Sellmann L, Murke F, Heinold A, Heinemann FM, Lindemann M, Bekeredjian-Ding I, Horn PA, Kirschning CJ, Küppers R, Seifert M. Systematic memory B cell archiving and random display shape the human splenic marginal zone throughout life. J Exp Med 2021; 218:211756. [PMID: 33538775 PMCID: PMC7868796 DOI: 10.1084/jem.20201952] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/02/2020] [Accepted: 12/21/2020] [Indexed: 12/19/2022] Open
Abstract
Human memory B cells (MBCs) are generated and diversified in secondary lymphoid tissues throughout the organism. A paired immunoglobulin (Ig)-gene repertoire analysis of peripheral blood (PB) and splenic MBCs from infant, adult, and elderly humans revealed that throughout life, circulating MBCs are comprehensively archived in the spleen. Archive MBC clones are systematically preserved and uncoupled from class-switching. Clonality in the spleen increases steadily, but boosts at midlife, thereby outcompeting small clones. The splenic marginal zone (sMZ) represents a primed MBC compartment, generated from a stochastic exchange within the archive memory pool. This is supported by functional assays, showing that PB and splenic CD21+ MBCs acquire transient CD21high expression upon NOTCH2-stimulation. Our study provides insight that the human MBC system in PB and spleen is composed of three interwoven compartments: the dynamic relationship of circulating, archive, and its subset of primed (sMZ) memory changes with age, thereby contributing to immune aging.
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Affiliation(s)
- Artur Kibler
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Bettina Budeus
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Ekaterina Homp
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Kevin Bronischewski
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Victoria Berg
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Ludger Sellmann
- Department of Haematology, University Hospital Essen, Essen, Germany
| | - Florian Murke
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Andreas Heinold
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Falko M Heinemann
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Monika Lindemann
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Peter A Horn
- Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Ralf Küppers
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
| | - Marc Seifert
- Institute of Cell Biology (Cancer Research), University of Duisburg-Essen, Essen, Germany
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34
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Valpione S, Mundra PA, Galvani E, Campana LG, Lorigan P, De Rosa F, Gupta A, Weightman J, Mills S, Dhomen N, Marais R. The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival. Nat Commun 2021; 12:4098. [PMID: 34215730 PMCID: PMC8253860 DOI: 10.1038/s41467-021-24343-x] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 06/09/2021] [Indexed: 12/13/2022] Open
Abstract
Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes could therefore be indicative of the functional state of these cells and determine disease course at different stages in cancer progression. Here we show that the diversity of the TCR of tumor infiltrating T cell at baseline is prognostic in various cancers, whereas the TCR clonality of T cell infiltrating metastatic melanoma pre-treatment is predictive for activity and efficacy of PD1 blockade immunotherapy.
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Affiliation(s)
- Sara Valpione
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Macclesfield, Cheshire, UK
- Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Piyushkumar A Mundra
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Macclesfield, Cheshire, UK
| | - Elena Galvani
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Macclesfield, Cheshire, UK
| | - Luca G Campana
- Department of Surgery, The Christie NHS Foundation Trust, previously Department of Surgical Oncological and Gastroenterological Sciences DISCOG (University of Padova), The Christie NHS Foundation Trust, Manchester, UK
| | - Paul Lorigan
- Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - Francesco De Rosa
- Immunotherapy - Cell Therapy and Biobank, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) "Dino Amadori" IRCCS, Meldola, Italy
| | - Avinash Gupta
- Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | - John Weightman
- Molecular Biology Core Facility, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Macclesfield, Cheshire, UK
| | - Sarah Mills
- Manchester Cancer Research Centre Biobank, The Christie NHS Foundation Trust, Manchester, UK
| | - Nathalie Dhomen
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Macclesfield, Cheshire, UK
| | - Richard Marais
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Macclesfield, Cheshire, UK.
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35
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Riquier S, Bessiere C, Guibert B, Bouge AL, Boureux A, Ruffle F, Audoux J, Gilbert N, Xue H, Gautheret D, Commes T. Kmerator Suite: design of specific k-mer signatures and automatic metadata discovery in large RNA-seq datasets. NAR Genom Bioinform 2021; 3:lqab058. [PMID: 34179780 PMCID: PMC8221386 DOI: 10.1093/nargab/lqab058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 05/10/2021] [Accepted: 06/17/2021] [Indexed: 11/12/2022] Open
Abstract
The huge body of publicly available RNA-sequencing (RNA-seq) libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large dataset characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor gene-specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualized through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non-coding RNAs for human health applications.
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Affiliation(s)
- Sébastien Riquier
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
| | - Chloé Bessiere
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
| | - Benoit Guibert
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
| | | | - Anthony Boureux
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
| | - Florence Ruffle
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
| | | | - Nicolas Gilbert
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
| | - Haoliang Xue
- Institute for Integrative Biology of the Cell, CEA, CNRS, Université Paris-Saclay, 91198, Gif sur Yvette, France
| | - Daniel Gautheret
- Institute for Integrative Biology of the Cell, CEA, CNRS, Université Paris-Saclay, 91198, Gif sur Yvette, France
| | - Thérèse Commes
- IRMB, University of Montpellier, INSERM, 80 rue Augustin Fliche, 34295, Montpellier, France
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36
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Song L, Cohen D, Ouyang Z, Cao Y, Hu X, Liu XS. TRUST4: immune repertoire reconstruction from bulk and single-cell RNA-seq data. Nat Methods 2021; 18:627-630. [PMID: 33986545 PMCID: PMC9328942 DOI: 10.1038/s41592-021-01142-2] [Citation(s) in RCA: 108] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 04/02/2021] [Indexed: 02/02/2023]
Abstract
We introduce the TRUST4 open-source algorithm for reconstruction of immune receptor repertoires in αβ/γδ T cells and B cells from RNA-sequencing (RNA-seq) data. Compared with competing methods, TRUST4 supports both FASTQ and BAM format and is faster and more sensitive in assembling longer-even full-length-receptor repertoires. TRUST4 can also call repertoire sequences from single-cell RNA-seq (scRNA-seq) data without V(D)J enrichment, and is compatible with both SMART-seq and 5' 10x Genomics platforms.
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Affiliation(s)
- Li Song
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - David Cohen
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Zhangyi Ouyang
- Department of Biotechnology, Beijing Institue of Radiation Medicine, Beijing, China
| | - Yang Cao
- College of Life Sciences, Sichuan University, Chengdu, Sichuan, China
| | - Xihao Hu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - X. Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA,Harvard T.H. Chan School of Public Health, Boston, MA, USA,Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA,: Corresponding author.
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