1
|
Lundgren S, Myllymäki M, Järvinen T, Keränen MAI, Theodoropoulos J, Smolander J, Kim D, Salmenniemi U, Walldin G, Savola P, Kelkka T, Rajala H, Hellström-Lindberg E, Itälä-Remes M, Kankainen M, Mustjoki S. Somatic mutations associate with clonal expansion of CD8 + T cells. SCIENCE ADVANCES 2024; 10:eadj0787. [PMID: 38848368 PMCID: PMC11160466 DOI: 10.1126/sciadv.adj0787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 05/06/2024] [Indexed: 06/09/2024]
Abstract
Somatic mutations in T cells can cause cancer but also have implications for immunological diseases and cell therapies. The mutation spectrum in nonmalignant T cells is unclear. Here, we examined somatic mutations in CD4+ and CD8+ T cells from 90 patients with hematological and immunological disorders and used T cell receptor (TCR) and single-cell sequencing to link mutations with T cell expansions and phenotypes. CD8+ cells had a higher mutation burden than CD4+ cells. Notably, the biggest variant allele frequency (VAF) of non-synonymous variants was higher than synonymous variants in CD8+ T cells, indicating non-random occurrence. The non-synonymous VAF in CD8+ T cells strongly correlated with the TCR frequency, but not age. We identified mutations in pathways essential for T cell function and often affected lymphoid neoplasia. Single-cell sequencing revealed cytotoxic TEMRA phenotypes of mutated T cells. Our findings suggest that somatic mutations contribute to CD8+ T cell expansions without malignant transformation.
Collapse
Affiliation(s)
- Sofie Lundgren
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
| | - Mikko Myllymäki
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
| | - Timo Järvinen
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Mikko A. I. Keränen
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
| | - Jason Theodoropoulos
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
| | - Johannes Smolander
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
| | - Daehong Kim
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
| | - Urpu Salmenniemi
- Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Stem Cell Transplantation Unit, Turku University Hospital, Turku, Finland
| | - Gunilla Walldin
- Center for Hematology and Regenerative Medicine, Department of Medicine, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Paula Savola
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Department of Clinical Chemistry, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Tiina Kelkka
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
| | - Hanna Rajala
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
| | - Eva Hellström-Lindberg
- Center for Hematology and Regenerative Medicine, Department of Medicine, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Maija Itälä-Remes
- Stem Cell Transplantation Unit, Turku University Hospital, Turku, Finland
| | - Matti Kankainen
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Satu Mustjoki
- Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- ICAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| |
Collapse
|
2
|
Myers MA, Arnold BJ, Bansal V, Balaban M, Mullen KM, Zaccaria S, Raphael BJ. HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data. Genome Biol 2024; 25:130. [PMID: 38773520 PMCID: PMC11110434 DOI: 10.1186/s13059-024-03267-x] [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: 07/13/2023] [Accepted: 05/03/2024] [Indexed: 05/24/2024] Open
Abstract
Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.
Collapse
Affiliation(s)
- Matthew A Myers
- Department of Computer Science, Princeton University, Princeton, USA
| | - Brian J Arnold
- Center for Statistics and Machine Learning, Princeton University, Princeton, USA
| | - Vineet Bansal
- Princeton Research Computing, Princeton University, Princeton, NJ, USA
| | - Metin Balaban
- Department of Computer Science, Princeton University, Princeton, USA
| | - Katelyn M Mullen
- Human Oncology & Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simone Zaccaria
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK.
| | | |
Collapse
|
3
|
Shahrouzi P, Forouz F, Mathelier A, Kristensen VN, Duijf PHG. Copy number alterations: a catastrophic orchestration of the breast cancer genome. Trends Mol Med 2024:S1471-4914(24)00120-5. [PMID: 38772764 DOI: 10.1016/j.molmed.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 04/12/2024] [Accepted: 04/26/2024] [Indexed: 05/23/2024]
Abstract
Breast cancer (BCa) is a prevalent malignancy that predominantly affects women around the world. Somatic copy number alterations (CNAs) are tumor-specific amplifications or deletions of DNA segments that often drive BCa development and therapy resistance. Hence, the complex patterns of CNAs complement BCa classification systems. In addition, understanding the precise contributions of CNAs is essential for tailoring personalized treatment approaches. This review highlights how tumor evolution drives the acquisition of CNAs, which in turn shape the genomic landscapes of BCas. It also discusses advanced methodologies for identifying recurrent CNAs, studying CNAs in BCa and their clinical impact.
Collapse
Affiliation(s)
- Parastoo Shahrouzi
- Department of Medical Genetics, Institute of Basic Medical Science, Faculty of Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway.
| | - Farzaneh Forouz
- School of Pharmacy, University of Queensland, Woolloongabba, Brisbane, Australia
| | - Anthony Mathelier
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway; Center for Bioinformatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway; Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Vessela N Kristensen
- Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway; Division of Medicine, Department of Clinical Molecular Biology and Laboratory Science (EpiGen), Akershus University Hospital, Lørenskog, Norway; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Pascal H G Duijf
- Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway; Centre for Cancer Biology, UniSA Clinical and Health Sciences, University of South Australia and SA Pathology, Adelaide, Australia.
| |
Collapse
|
4
|
Curry RN, Ma Q, McDonald MF, Ko Y, Srivastava S, Chin PS, He P, Lozzi B, Athukuri P, Jing J, Wang S, Harmanci AO, Arenkiel B, Jiang X, Deneen B, Rao G, Harmanci AS. Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.02.583026. [PMID: 38496434 PMCID: PMC10942290 DOI: 10.1101/2024.03.02.583026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Prior studies have described the complex interplay that exists between glioma cells and neurons, however, the electrophysiological properties endogenous to tumor cells remain obscure. To address this, we employed Patch-sequencing on human glioma specimens and found that one third of patched cells in IDH mutant (IDH mut ) tumors demonstrate properties of both neurons and glia by firing single, short action potentials. To define these hybrid cells (HCs) and discern if they are tumor in origin, we developed a computational tool, Single Cell Rule Association Mining (SCRAM), to annotate each cell individually. SCRAM revealed that HCs represent tumor and non-tumor cells that feature GABAergic neuron and oligodendrocyte precursor cell signatures. These studies are the first to characterize the combined electrophysiological and molecular properties of human glioma cells and describe a new cell type in human glioma with unique electrophysiological and transcriptomic properties that are likely also present in the non-tumor mammalian brain.
Collapse
|
5
|
Williams CM, O'Connell J, Freyman WA, Gignoux CR, Ramachandran S, Williams AL. Phasing millions of samples achieves near perfect accuracy, enabling parent-of-origin classification of variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592816. [PMID: 38766004 PMCID: PMC11100733 DOI: 10.1101/2024.05.06.592816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Haplotype phasing, the process of determining which genetic variants are physically located on the same chromosome, is crucial for various genetic analyses. In this study, we first benchmark SHAPEIT and Beagle, two state-of-the-art phasing methods, on two large datasets: > 8 million diverse, research-consented 23andMe, Inc. customers and the UK Biobank (UKB). We find that both perform exceptionally well. Beagle's median switch error rate (SER) (after excluding single SNP switches) in white British trios from UKB is 0.026% compared to 0.00% for European ancestry 23andMe research participants; 55.6% of European ancestry 23andMe research participants have zero non-single SNP switches, compared to 42.4% of white British trios. South Asian ancestry 23andMe research participants have the highest median SER amongst the 23andMe populations, but it is still remarkably low at 0.46%. We also investigate the relationship between identity-by-descent (IBD) and SER, finding that switch errors tend to occur in regions of little or no IBD segment coverage. SHAPEIT and Beagle excel at 'intra-chromosomal' phasing, but lack the ability to phase across chromosomes, motivating us to develop an inter-chromosomal phasing method, called HAPTIC ( HAP lotype TI ling and C lustering), that assigns paternal and maternal variants discretely genome-wide. Our approach uses identity-by-descent (IBD) segments to phase blocks of variants on different chromosomes. HAPTIC represents the segments a focal individual shares with their relatives as nodes in a signed graph and performs bipartite clustering on the signed graph using spectral clustering. We test HAPTIC on 1022 UKB trios, yielding a median phase error of 0.08% in regions covered by IBD segments (33.5% of sites). We also ran HAPTIC in the 23andMe database and found a median phase error rate (the rate of mismatching alleles between the inferred and true phase) of 0.92% in Europeans (93.8% of sites) and 0.09% in admixed Africans (92.7% of sites). HAPTIC's precision depends heavily on data from relatives, so will increase as datasets grow larger and more diverse. HAPTIC enables analyses that require the parent-of-origin of variants, such as association studies and ancestry inference of untyped parents.
Collapse
|
6
|
Kurt S, Chen M, Toosi H, Chen X, Engblom C, Mold J, Hartman J, Lagergren J. CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics. Bioinformatics 2024; 40:btae284. [PMID: 38676578 PMCID: PMC11087824 DOI: 10.1093/bioinformatics/btae284] [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: 11/21/2023] [Revised: 03/06/2024] [Accepted: 04/25/2024] [Indexed: 04/29/2024] Open
Abstract
MOTIVATION Copy number variations (CNVs) are common genetic alterations in tumour cells. The delineation of CNVs holds promise for enhancing our comprehension of cancer progression. Moreover, accurate inference of CNVs from single-cell sequencing data is essential for unravelling intratumoral heterogeneity. However, existing inference methods face limitations in resolution and sensitivity. RESULTS To address these challenges, we present CopyVAE, a deep learning framework based on a variational autoencoder architecture. Through experiments, we demonstrated that CopyVAE can accurately and reliably detect CNVs from data obtained using single-cell RNA sequencing. CopyVAE surpasses existing methods in terms of sensitivity and specificity. We also discussed CopyVAE's potential to advance our understanding of genetic alterations and their impact on disease advancement. AVAILABILITY AND IMPLEMENTATION CopyVAE is implemented and freely available under MIT license at https://github.com/kurtsemih/copyVAE.
Collapse
Affiliation(s)
- Semih Kurt
- School of EECS and SciLifeLab, KTH Royal Institute of Technology, Stockholm, 100 44, Sweden
| | - Mandi Chen
- School of EECS and SciLifeLab, KTH Royal Institute of Technology, Stockholm, 100 44, Sweden
| | - Hosein Toosi
- School of EECS and SciLifeLab, KTH Royal Institute of Technology, Stockholm, 100 44, Sweden
| | - Xinsong Chen
- Department of Oncology and Pathology, Karolinska Institutet, Solna, 171 77, Sweden
| | - Camilla Engblom
- Department of Cell and Molecular Biology, Karolinska Institutet, Solna, 171 77, Sweden
| | - Jeff Mold
- Department of Cell and Molecular Biology, Karolinska Institutet, Solna, 171 77, Sweden
| | - Johan Hartman
- Department of Oncology and Pathology, Karolinska Institutet, Solna, 171 77, Sweden
- Department of Clinical Pathology and Cytology, Karolinska University Laboratory, Solna, 171 76, Sweden
| | - Jens Lagergren
- School of EECS and SciLifeLab, KTH Royal Institute of Technology, Stockholm, 100 44, Sweden
| |
Collapse
|
7
|
An M, Mehta A, Min BH, Heo YJ, Wright SJ, Parikh M, Bi L, Lee H, Kim TJ, Lee SY, Moon J, Park RJ, Strickland MR, Park WY, Kang WK, Kim KM, Kim ST, Klempner SJ, Lee J. Early Immune Remodeling Steers Clinical Response to First-Line Chemoimmunotherapy in Advanced Gastric Cancer. Cancer Discov 2024; 14:766-785. [PMID: 38319303 PMCID: PMC11061611 DOI: 10.1158/2159-8290.cd-23-0857] [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: 08/01/2023] [Revised: 11/28/2023] [Accepted: 02/02/2024] [Indexed: 02/07/2024]
Abstract
Adding anti-programmed cell death protein 1 (anti-PD-1) to 5-fluorouracil (5-FU)/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy, we conducted a phase II first-line trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab, we transcriptionally profiled 358,067 single cells to identify evolving multicellular tumor microenvironment (TME) networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab, we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in antitumor immune hub formation could expand the portion of patients benefiting from anti-PD-1 approaches. SIGNIFICANCE The benefit of 5-FU/platinum with anti-PD-1 in first-line advanced gastric cancer is limited to patient subgroups. Using a trial with sequential anti-PD-1, we show coordinated induction of multicellular TME hubs informs the ability of anti-PD-1 to potentiate T cell-driven responses. Differential TME hub development highlights features that underlie clinical outcomes. This article is featured in Selected Articles from This Issue, p. 695.
Collapse
Affiliation(s)
- Minae An
- Experimental Therapeutics Development Center, Samsung Medical Center, Seoul, Korea
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Arnav Mehta
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Byung Hoon Min
- Department of Medicine, Division of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | | | - Samuel J. Wright
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Milan Parikh
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Lynn Bi
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Hyuk Lee
- Department of Medicine, Division of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Tae Jun Kim
- Department of Medicine, Division of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Song-Yi Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jeonghyeon Moon
- Departments of Neurology and Immunology, Yale School of Medicine, New Haven, Connecticut
| | - Ryan J. Park
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Division of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Matthew R. Strickland
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | | | - Won Ki Kang
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Kyoung-Mee Kim
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Seung Tae Kim
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Samuel J. Klempner
- Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jeeyun Lee
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| |
Collapse
|
8
|
Muyas F, Sauer CM, Valle-Inclán JE, Li R, Rahbari R, Mitchell TJ, Hormoz S, Cortés-Ciriano I. De novo detection of somatic mutations in high-throughput single-cell profiling data sets. Nat Biotechnol 2024; 42:758-767. [PMID: 37414936 PMCID: PMC11098751 DOI: 10.1038/s41587-023-01863-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 06/07/2023] [Indexed: 07/08/2023]
Abstract
Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism and cell plasticity. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq (assay for transposase-accessible chromatin sequence) data sets directly without requiring matched bulk or single-cell DNA sequencing data. SComatic distinguishes somatic mutations from polymorphisms, RNA-editing events and artefacts using filters and statistical tests parameterized on non-neoplastic samples. Using >2.6 million single cells from 688 single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells accurately, even in differentiated cells from polyclonal tissues that are not amenable to mutation detection using existing methods. Validated against matched genome sequencing and scRNA-seq data, SComatic achieves F1 scores between 0.6 and 0.7 across diverse data sets, in comparison to 0.2-0.4 for the second-best performing method. In summary, SComatic permits de novo mutational signature analysis, and the study of clonal heterogeneity and mutational burdens at single-cell resolution.
Collapse
Affiliation(s)
- Francesc Muyas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Carolin M Sauer
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Jose Espejo Valle-Inclán
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Ruoyan Li
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Raheleh Rahbari
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Thomas J Mitchell
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust and NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Department of Surgery, University of Cambridge, Cambridge, UK
| | - Sahand Hormoz
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Isidro Cortés-Ciriano
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK.
| |
Collapse
|
9
|
Nadeem O, Aranha MP, Redd R, Timonian M, Magidson S, Lightbody ED, Alberge JB, Bertamini L, Dutta AK, El-Khoury H, Bustoros M, Laubach JP, Bianchi G, O'Donnell E, Wu T, Tsuji J, Anderson K, Getz G, Trippa L, Richardson PG, Sklavenitis-Pistofidis R, Ghobrial IM. Long-Term Follow-Up Defines the Population That Benefits from Early Interception in a High-Risk Smoldering Multiple Myeloma Clinical Trial Using the Combination of Ixazomib, Lenalidomide, and Dexamethasone. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.19.24306082. [PMID: 38699307 PMCID: PMC11064995 DOI: 10.1101/2024.04.19.24306082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background Early therapeutic intervention in high-risk SMM (HR-SMM) has demonstrated benefit in previous studies of lenalidomide with or without dexamethasone. Triplets and quadruplet studies have been examined in this same population. However, to date, none of these studies examined the impact of depth of response on long-term outcomes of participants treated with lenalidomide-based therapy, and whether the use of the 20/2/20 model or the addition of genomic alterations can further define the population that would benefit the most from early therapeutic intervention. Here, we present the results of the phase II study of the combination of ixazomib, lenalidomide, and dexamethasone in patients with HR-SMM with long-term follow-up and baseline single-cell tumor and immune sequencing that help refine the population to be treated for early intervention studies. Methods This is a phase II trial of ixazomib, lenalidomide, and dexamethasone (IRD) in HR-SMM. Patients received 9 cycles of induction therapy with ixazomib 4mg on days 1, 8, and 15; lenalidomide 25mg on days 1-21; and dexamethasone 40mg on days 1, 8, 15, and 22. The induction phase was followed by maintenance with ixazomib 4mg on days 1, 8, and 15; and lenalidomide 15mg d1-21 for 15 cycles for 24 months of treatment. The primary endpoint was progression-free survival after 2 years of therapy. Secondary endpoints included depth of response, biochemical progression, and correlative studies included single-cell RNA sequencing and/or whole-genome sequencing of the tumor and single-cell sequencing of immune cells at baseline. Results Fifty-five patients, with a median age of 64, were enrolled in the study. The overall response rate was 93%, with 31% of patients achieving a complete response and 45% achieving a very good partial response or better. The most common grade 3 or greater treatment-related hematologic toxicities were neutropenia (16 patients; 29%), leukopenia (10 patients; 18%), lymphocytopenia (8 patients; 15%), and thrombocytopenia (4 patients; 7%). Non-hematologic grade 3 or greater toxicities included hypophosphatemia (7 patients; 13%), rash (5 patients; 9%), and hypokalemia (4 patients; 7%). After a median follow-up of 50 months, the median progression-free survival (PFS) was 48.6 months (95% CI: 39.9 - not reached; NR) and median overall survival has not been reached. Patients achieving VGPR or better had a significantly better progression-free survival (p<0.001) compared to those who did not achieve VGPR (median PFS 58.2 months vs. 31.3 months). Biochemical progression preceded or was concurrent with the development of SLiM-CRAB criteria in eight patients during follow-up, indicating that biochemical progression is a meaningful endpoint that correlates with the development of end-organ damage. High-risk 20/2/20 participants had the worst PFS compared to low- and intermediate-risk participants. The use of whole genome or single-cell sequencing of tumor cells identified high-risk aberrations that were not identified by FISH alone and aided in the identification of participants at risk of progression. scRNA-seq analysis revealed a positive correlation between MHC class I expression and response to proteasome inhibition and at the same time a decreased proportion of GZMB+ T cells within the clonally expanded CD8+ T cell population correlated with suboptimal response. Conclusions Ixazomib, lenalidomide and dexamethasone in HR-SMM demonstrates significant clinical activity with an overall favorable safety profile. Achievement of VGPR or greater led to significant improvement in time to progression, suggesting that achieving deep response is beneficial in HR-SMM. Biochemical progression correlates with end-organ damage. Patients with high-risk FISH and lack of deep response had poor outcomes. ClinicalTrials.gov identifier: ( NCT02916771 ).
Collapse
|
10
|
Xiong K, Fang Y, Qiu B, Chen C, Huang N, Liang F, Huang C, Lu T, Zheng L, Zhao J, Zhu B. Investigation of cellular communication and signaling pathways in tumor microenvironment for high TP53-expressing osteosarcoma cells through single-cell RNA sequencing. Med Oncol 2024; 41:93. [PMID: 38526643 DOI: 10.1007/s12032-024-02318-4] [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: 12/18/2023] [Accepted: 01/29/2024] [Indexed: 03/27/2024]
Abstract
Osteosarcoma (OS) stands as the most prevalent primary bone cancer in children and adolescents, and its limited treatment options often result in unsatisfactory outcomes, particularly for metastatic cases. The tumor microenvironment (TME) has been recognized as a crucial determinant in OS progression. However, the intercellular dynamics between high TP53-expressing OS cells and neighboring cell types within the TME are yet to be thoroughly understood. In our study, we harnessed the single-cell RNA sequencing (scRNA-seq) technology in combination with the computational tool-Cellchat, aiming to elucidate the intercellular communication networks present within OS. Through meticulous quantitative inference and subsequent analysis of these networks, we succeeded in identifying significant signaling pathways connecting high TP53-expressing OS cells with proximate cell types, namely Macrophages, Monocytes, Endothelial Cells, and PVLs. This research brings forth a nuanced understanding of the intricate patterns and coordination involved in the TME's intercellular communication signals. These findings not only provide profound insights into the molecular mechanisms underpinning OS but also indicate potential therapeutic targets that could revolutionize treatment strategies.
Collapse
Affiliation(s)
- Kai Xiong
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The Third Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530031, China
| | - Yuqi Fang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
| | - Boyuan Qiu
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
| | - Chaotao Chen
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
| | - Nanchang Huang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
| | - Feiyuan Liang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
| | - Chuangming Huang
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Department of Bone and Soft Tissue Surgery, Guangxi Medical University Cancer Hospital, Guangxi Medical University, Nanning, 530021, China
| | - Tiantian Lu
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China
| | - Li Zheng
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
- International Joint Laboratory of Ministry of Education for Regeneration of Bone and Soft Tissues, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
| | - Jinmin Zhao
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
- Department of Orthopaedics Trauma and HandSurgery, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- International Joint Laboratory of Ministry of Education for Regeneration of Bone and Soft Tissues, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Guangxi Key Laboratory of Regenerative Medicine, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
| | - Bo Zhu
- Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
- Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, 530021, China.
- Guangxi Key Laboratory of Regenerative Medicine, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
| |
Collapse
|
11
|
Shi H, Williams MJ, Satas G, Weiner AC, McPherson A, Shah SP. Allele-specific transcriptional effects of subclonal copy number alterations enable genotype-phenotype mapping in cancer cells. Nat Commun 2024; 15:2482. [PMID: 38509111 PMCID: PMC10954741 DOI: 10.1038/s41467-024-46710-0] [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: 01/18/2023] [Accepted: 03/01/2024] [Indexed: 03/22/2024] Open
Abstract
Subclonal copy number alterations are a prevalent feature in tumors with high chromosomal instability and result in heterogeneous cancer cell populations with distinct phenotypes. However, the extent to which subclonal copy number alterations contribute to clone-specific phenotypes remains poorly understood. We develop TreeAlign, which computationally integrates independently sampled single-cell DNA and RNA sequencing data from the same cell population. TreeAlign accurately encodes dosage effects from subclonal copy number alterations, the impact of allelic imbalance on allele-specific transcription, and obviates the need to define genotypic clones from a phylogeny a priori, leading to highly granular definitions of clones with distinct expression programs. These improvements enable clone-clone gene expression comparisons with higher resolution and identification of expression programs that are genomically independent. Our approach sets the stage for dissecting the relative contribution of fixed genomic alterations and dynamic epigenetic processes on gene expression programs in cancer.
Collapse
Affiliation(s)
- Hongyu Shi
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, NY, USA
| | - Marc J Williams
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gryte Satas
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Adam C Weiner
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andrew McPherson
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sohrab P Shah
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| |
Collapse
|
12
|
Dondi A, Borgsmüller N, Ferreira PF, Haas BJ, Jacob F, Heinzelmann-Schwarz V, Beerenwinkel N. De novo detection of somatic variants in long-read single-cell RNA sequencing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.06.583775. [PMID: 38496441 PMCID: PMC10942462 DOI: 10.1101/2024.03.06.583775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
In cancer, genetic and transcriptomic variations generate clonal heterogeneity, possibly leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging LR scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), copy-number alterations (CNAs), and gene fusions to reconstruct the tumor clonal heterogeneity. For SNV calling, LongSom distinguishes somatic SNVs from germline polymorphisms by reannotating marker gene expression-based cell types using called variants and applying strict filters. Applying LongSom to ovarian cancer samples, we detected clinically relevant somatic SNVs that were validated against single-cell and bulk panel DNA-seq data and could not be detected with short-read (SR) scRNA-seq. Leveraging somatic SNVs and fusions, LongSom found subclones with different predicted treatment outcomes. In summary, LongSom enables de novo SNVs, CNAs, and fusions detection, thus enabling the study of cancer evolution, clonal heterogeneity, and treatment resistance.
Collapse
Affiliation(s)
- Arthur Dondi
- ETH Zurich, Department of Biosystems Science and Engineering, Schanzenstrasse 44, 4056 Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Schanzenstrasse 44, 4056 Basel, Switzerland
| | - Nico Borgsmüller
- ETH Zurich, Department of Biosystems Science and Engineering, Schanzenstrasse 44, 4056 Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Schanzenstrasse 44, 4056 Basel, Switzerland
| | - Pedro F. Ferreira
- ETH Zurich, Department of Biosystems Science and Engineering, Schanzenstrasse 44, 4056 Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Schanzenstrasse 44, 4056 Basel, Switzerland
| | - Brian J. Haas
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
| | - Francis Jacob
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031 Basel, Switzerland
| | - Viola Heinzelmann-Schwarz
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031 Basel, Switzerland
| | | | - Niko Beerenwinkel
- ETH Zurich, Department of Biosystems Science and Engineering, Schanzenstrasse 44, 4056 Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Schanzenstrasse 44, 4056 Basel, Switzerland
| |
Collapse
|
13
|
Maurer K, Park CY, Mani S, Borji M, Penter L, Jin Y, Zhang JY, Shin C, Brenner JR, Southard J, Krishna S, Lu W, Lyu H, Abbondanza D, Mangum C, Olsen LR, Neuberg DS, Bachireddy P, Farhi SL, Li S, Livak KJ, Ritz J, Soiffer RJ, Wu CJ, Azizi E. Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.09.579677. [PMID: 38405900 PMCID: PMC10888840 DOI: 10.1101/2024.02.09.579677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.
Collapse
|
14
|
Huang AY, Zhou Z, Talukdar M, Miller MB, Chhouk B, Enyenihi L, Rosen I, Stronge E, Zhao B, Kim D, Choi J, Khoshkhoo S, Kim J, Ganz J, Travaglini K, Gabitto M, Hodge R, Kaplan E, Lein E, De Jager PL, Bennett DA, Lee EA, Walsh CA. Somatic cancer driver mutations are enriched and associated with inflammatory states in Alzheimer's disease microglia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.03.574078. [PMID: 38260600 PMCID: PMC10802273 DOI: 10.1101/2024.01.03.574078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alzheimer's disease (AD) is an age-associated neurodegenerative disorder characterized by progressive neuronal loss and pathological accumulation of the misfolded proteins amyloid-β and tau1,2. Neuroinflammation mediated by microglia and brain-resident macrophages plays a crucial role in AD pathogenesis1-5, though the mechanisms by which age, genes, and other risk factors interact remain largely unknown. Somatic mutations accumulate with age and lead to clonal expansion of many cell types, contributing to cancer and many non-cancer diseases6,7. Here we studied somatic mutation in normal aged and AD brains by three orthogonal methods and in three independent AD cohorts. Analysis of bulk RNA sequencing data from 866 samples from different brain regions revealed significantly higher (~two-fold) overall burdens of somatic single-nucleotide variants (sSNVs) in AD brains compared to age-matched controls. Molecular-barcoded deep (>1000X) gene panel sequencing of 311 prefrontal cortex samples showed enrichment of sSNVs and somatic insertions and deletions (sIndels) in cancer driver genes in AD brain compared to control, with recurrent, and often multiple, mutations in genes implicated in clonal hematopoiesis (CH)8,9. Pathogenic sSNVs were enriched in CSF1R+ microglia of AD brains, and the high proportion of microglia (up to 40%) carrying some sSNVs in cancer driver genes suggests mutation-driven microglial clonal expansion (MiCE). Analysis of single-nucleus RNA sequencing (snRNAseq) from temporal neocortex of 62 additional AD cases and controls exhibited nominally increased mosaic chromosomal alterations (mCAs) associated with CH10,11. Microglia carrying mCA showed upregulated pro-inflammatory genes, resembling the transcriptomic features of disease-associated microglia (DAM) in AD. Our results suggest that somatic driver mutations in microglia are common with normal aging but further enriched in AD brain, driving MiCE with inflammatory and DAM signatures. Our findings provide the first insights into microglial clonal dynamics in AD and identify potential new approaches to AD diagnosis and therapy.
Collapse
Affiliation(s)
- August Yue Huang
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zinan Zhou
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maya Talukdar
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT MD/PhD Program, Boston, MA, USA
| | - Michael B. Miller
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Neuropathology, Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Brian Chhouk
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
| | - Liz Enyenihi
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT MD/PhD Program, Boston, MA, USA
| | - Ila Rosen
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
| | - Edward Stronge
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT MD/PhD Program, Boston, MA, USA
| | - Boxun Zhao
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dachan Kim
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Department of Otorhinolaryngology, Severance Hospital, Yonsei University Health System, Yonsei University College of Medicine, Seoul, South Korea
| | - Jaejoon Choi
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sattar Khoshkhoo
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Junho Kim
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Sciences, Sungkyunkwan University, Suwon, South Korea
| | - Javier Ganz
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | | | - Eitan Kaplan
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Philip L. De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical College, Chicago, IL, USA
| | - Eunjung Alice Lee
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christopher A. Walsh
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute, Boston, MA USA
- Departments of Neurology, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
15
|
Brierley CK, Yip BH, Orlando G, Goyal H, Wen S, Wen J, Levine MF, Jakobsdottir GM, Rodriguez-Meira A, Adamo A, Bashton M, Hamblin A, Clark SA, O'Sullivan J, Murphy L, Olijnik AA, Cotton A, Narina S, Pruett-Miller SM, Enshaei A, Harrison C, Drummond M, Knapper S, Tefferi A, Antony-Debré I, Thongjuea S, Wedge DC, Constantinescu S, Papaemmanuil E, Psaila B, Crispino JD, Mead AJ. Chromothripsis orchestrates leukemic transformation in blast phase MPN through targetable amplification of DYRK1A. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.08.570880. [PMID: 38106192 PMCID: PMC10723394 DOI: 10.1101/2023.12.08.570880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Chromothripsis, the process of catastrophic shattering and haphazard repair of chromosomes, is a common event in cancer. Whether chromothripsis might constitute an actionable molecular event amenable to therapeutic targeting remains an open question. We describe recurrent chromothripsis of chromosome 21 in a subset of patients in blast phase of a myeloproliferative neoplasm (BP-MPN), which alongside other structural variants leads to amplification of a region of chromosome 21 in ∼25% of patients ('chr21amp'). We report that chr21amp BP-MPN has a particularly aggressive and treatment-resistant phenotype. The chr21amp event is highly clonal and present throughout the hematopoietic hierarchy. DYRK1A , a serine threonine kinase and transcription factor, is the only gene in the 2.7Mb minimally amplified region which showed both increased expression and chromatin accessibility compared to non-chr21amp BP-MPN controls. We demonstrate that DYRK1A is a central node at the nexus of multiple cellular functions critical for BP-MPN development, including DNA repair, STAT signalling and BCL2 overexpression. DYRK1A is essential for BP-MPN cell proliferation in vitro and in vivo , and DYRK1A inhibition synergises with BCL2 targeting to induce BP-MPN cell apoptosis. Collectively, these findings define the chr21amp event as a prognostic biomarker in BP-MPN and link chromothripsis to a druggable target.
Collapse
|
16
|
Chen L, Chang D, Tandukar B, Deivendran D, Pozniak J, Cruz-Pacheco N, Cho RJ, Cheng J, Yeh I, Marine C, Bastian BC, Ji AL, Shain AH. STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer. Genome Biol 2023; 24:273. [PMID: 38037084 PMCID: PMC10688493 DOI: 10.1186/s13059-023-03121-6] [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: 01/08/2023] [Accepted: 11/22/2023] [Indexed: 12/02/2023] Open
Abstract
Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes.
Collapse
Affiliation(s)
- Limin Chen
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Darwin Chang
- Department of Immunology, H. Lee Moffitt Cancer Center, Tampa, USA
| | - Bishal Tandukar
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Delahny Deivendran
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Joanna Pozniak
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Louvain, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Louvain, Belgium
| | - Noel Cruz-Pacheco
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Raymond J Cho
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Jeffrey Cheng
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
| | - Iwei Yeh
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
- Department of Pathology, University of California, San Francisco, San Francisco, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, USA
| | - Chris Marine
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Louvain, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Louvain, Belgium
| | - Boris C Bastian
- Department of Dermatology, University of California, San Francisco, San Francisco, USA
- Department of Pathology, University of California, San Francisco, San Francisco, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, USA
| | - Andrew L Ji
- Department of Dermatology, Department of Oncological Sciences, Black Family Stem Cell Institute, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York City, USA
| | - A Hunter Shain
- Department of Dermatology, University of California, San Francisco, San Francisco, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, USA.
| |
Collapse
|
17
|
Becchi T, Beltrame L, Mannarino L, Calura E, Marchini S, Romualdi C. A pan-cancer landscape of pathogenic somatic copy number variations. J Biomed Inform 2023; 147:104529. [PMID: 37858853 DOI: 10.1016/j.jbi.2023.104529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 09/13/2023] [Accepted: 10/16/2023] [Indexed: 10/21/2023]
Abstract
OBJECTIVE Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions. METHODS Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival. RESULTS Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression. CONCLUSION This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.
Collapse
Affiliation(s)
- Tommaso Becchi
- Department of Biology, University of Padova, 35131 Padova, Italy
| | - Luca Beltrame
- Laboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089 Rozzano - Milan, Italy
| | - Laura Mannarino
- Laboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089 Rozzano - Milan, Italy; Department of Biomedical Sciences, Humanitas University, via Rita Levi Montalcini 4, 20072 Pieve Emanuele - Milan, Italy
| | - Enrica Calura
- Department of Biology, University of Padova, 35131 Padova, Italy
| | - Sergio Marchini
- Laboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089 Rozzano - Milan, Italy
| | - Chiara Romualdi
- Department of Biology, University of Padova, 35131 Padova, Italy.
| |
Collapse
|
18
|
Derrien J, Gastineau S, Frigout A, Giordano N, Cherkaoui M, Gaborit V, Boinon R, Douillard E, Devic M, Magrangeas F, Moreau P, Minvielle S, Touzeau C, Letouzé E. Acquired resistance to a GPRC5D-directed T-cell engager in multiple myeloma is mediated by genetic or epigenetic target inactivation. NATURE CANCER 2023; 4:1536-1543. [PMID: 37653140 DOI: 10.1038/s43018-023-00625-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 07/28/2023] [Indexed: 09/02/2023]
Abstract
Bispecific antibodies targeting GPRC5D demonstrated promising efficacy in multiple myeloma, but acquired resistance usually occurs within a few months. Using a single-nucleus multi-omic strategy in three patients from the MYRACLE cohort (ClinicalTrials.gov registration: NCT03807128 ), we identified two resistance mechanisms, by bi-allelic genetic inactivation of GPRC5D or by long-range epigenetic silencing of its promoter and enhancer regions. Molecular profiling of target genes may help to guide the choice of immunotherapy and early detection of resistance in multiple myeloma.
Collapse
Affiliation(s)
- Jennifer Derrien
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Sarah Gastineau
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Antoine Frigout
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Nils Giordano
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Mia Cherkaoui
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Victor Gaborit
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Rémi Boinon
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
| | - Elise Douillard
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Magali Devic
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Florence Magrangeas
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Philippe Moreau
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- Hematology Department, University Hospital Hôtel-Dieu, Nantes, France
| | - Stéphane Minvielle
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- University Hospital Hôtel-Dieu, Nantes, France
| | - Cyrille Touzeau
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France
- Hematology Department, University Hospital Hôtel-Dieu, Nantes, France
| | - Eric Letouzé
- Nantes Université, INSERM, CNRS, Université d'Angers, CRCI2NA, Nantes, France.
- University Hospital Hôtel-Dieu, Nantes, France.
| |
Collapse
|
19
|
Gao T, Kastriti ME, Ljungström V, Heinzel A, Tischler AS, Oberbauer R, Loh PR, Adameyko I, Park PJ, Kharchenko PV. A pan-tissue survey of mosaic chromosomal alterations in 948 individuals. Nat Genet 2023; 55:1901-1911. [PMID: 37904053 PMCID: PMC10838621 DOI: 10.1038/s41588-023-01537-1] [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: 03/17/2023] [Accepted: 09/18/2023] [Indexed: 11/01/2023]
Abstract
Genetic mutations accumulate in an organism's body throughout its lifetime. While somatic single-nucleotide variants have been well characterized in the human body, the patterns and consequences of large chromosomal alterations in normal tissues remain largely unknown. Here, we present a pan-tissue survey of mosaic chromosomal alterations (mCAs) in 948 healthy individuals from the Genotype-Tissue Expression project, augmenting RNA-based allelic imbalance estimation with haplotype phasing. We found that approximately a quarter of the individuals carry a clonally-expanded mCA in at least one tissue, with incidence strongly correlated with age. The prevalence and genome-wide patterns of mCAs vary considerably across tissue types, suggesting tissue-specific mutagenic exposure and selection pressures. The mCA landscapes in normal adrenal and pituitary glands resemble those in tumors arising from these tissues, whereas the same is not true for the esophagus and skin. Together, our findings show a widespread age-dependent emergence of mCAs across normal human tissues with intricate connections to tumorigenesis.
Collapse
Affiliation(s)
- Teng Gao
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Maria Eleni Kastriti
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
- Department of Physiology and Pharmacology, Karolinska Institutet, Solna, Sweden
| | - Viktor Ljungström
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Andreas Heinzel
- Department of Nephrology, Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Arthur S Tischler
- Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, MA, USA
| | - Rainer Oberbauer
- Department of Nephrology, Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Igor Adameyko
- Department of Neuroimmunology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
- Department of Physiology and Pharmacology, Karolinska Institutet, Solna, Sweden
| | - Peter J Park
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA.
| |
Collapse
|
20
|
Cheng D, Zhang Z, Mi Z, Tao W, Liu D, Fu J, Fan H. Deciphering the heterogeneity and immunosuppressive function of regulatory T cells in osteosarcoma using single-cell RNA transcriptome. Comput Biol Med 2023; 165:107417. [PMID: 37669584 DOI: 10.1016/j.compbiomed.2023.107417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 08/03/2023] [Accepted: 08/28/2023] [Indexed: 09/07/2023]
Abstract
Osteosarcoma (OS) is a highly invasive malignant neoplasm with poor prognosis. The tumor microenvironment (TME) plays an essential role in the occurrence and development of OS. Regulatory T cells (Tregs) are known to facilitate immunosuppression, tumor progression, invasion, and metastasis. However, the effect of Tregs in the TME of OS remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) data was used to identify Tregs and various other cell clusters in the TME of OS. Gene set variation analysis (GSVA) was used to investigate the signaling pathways in Tregs from OS and adjacent tissues. The CellChat and iTALK packages were used to analyze cellular communication. In addition, a prognostic model was established based on the Tregs-specific genes using bulk RNA-seq from the TARGET database, and it was verified using a Gene Expression Omnibus dataset. The pRRophetic package was used to predict drug sensitivity. Immunohistochemistry was used to verify the expression of candidate genes in OS. Based on the above methods, we showed that the OS samples were highly infiltrated with Tregs. GSVA revealed that oxidative phosphorylation, angiogenesis and mammalian target of rapamycin complex 1 (mTORC1) were highly activated in Tregs from OS compared with those from adjacent tissues. Using cellular communication analysis, we found that Tregs interacted with osteoblastic, endothelial, and myeloid cells via C-X-C motif chemokine ligand (CXCL) signaling; particularly, they strongly affected the expression of C-X-C motif chemokine receptor 4 (CXCR4) and interacted with other cell clusters through CXCL12/transforming growth factor β1 (TGFB1) to collectively enable tumor growth and progression. Subsequently, two Tregs-specific genes-CD320 and MAF-were screened through univariate, least absolute shrinkage and selection operator regression (LASSO) and multivariate analysis to construct a prognostic model, which showed excellent prognostic accuracy in two independent cohorts. In addition, drug sensitivity analysis demonstrated that OS patients at high Tregs risk were sensitive to sunitinib, sorafenib, and axitinib. We also used immunohistochemistry to validate that CD320 and MAF were significantly upregulated in OS tissues compared with adjacent tissues. Overall, this study reveals the heterogeneity of Tregs in the OS TME, providing new insights into the invasion and treatment of this cancer.
Collapse
Affiliation(s)
- Debin Cheng
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Zhao Zhang
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Zhenzhou Mi
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Weidong Tao
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Dong Liu
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Jun Fu
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Hongbin Fan
- Department of Orthopaedic Surgery, Xi Jing Hospital, The Fourth Military Medical University, Xi'an, China.
| |
Collapse
|
21
|
Dileep V, Boix CA, Mathys H, Marco A, Welch GM, Meharena HS, Loon A, Jeloka R, Peng Z, Bennett DA, Kellis M, Tsai LH. Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration. Cell 2023; 186:4404-4421.e20. [PMID: 37774679 PMCID: PMC10697236 DOI: 10.1016/j.cell.2023.08.038] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 04/02/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Persistent DNA double-strand breaks (DSBs) in neurons are an early pathological hallmark of neurodegenerative diseases including Alzheimer's disease (AD), with the potential to disrupt genome integrity. We used single-nucleus RNA-seq in human postmortem prefrontal cortex samples and found that excitatory neurons in AD were enriched for somatic mosaic gene fusions. Gene fusions were particularly enriched in excitatory neurons with DNA damage repair and senescence gene signatures. In addition, somatic genome structural variations and gene fusions were enriched in neurons burdened with DSBs in the CK-p25 mouse model of neurodegeneration. Neurons enriched for DSBs also had elevated levels of cohesin along with progressive multiscale disruption of the 3D genome organization aligned with transcriptional changes in synaptic, neuronal development, and histone genes. Overall, this study demonstrates the disruption of genome stability and the 3D genome organization by DSBs in neurons as pathological steps in the progression of neurodegenerative diseases.
Collapse
Affiliation(s)
- Vishnu Dileep
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hansruedi Mathys
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Asaf Marco
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gwyneth M Welch
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hiruy S Meharena
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anjanet Loon
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ritika Jeloka
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Zhuyu Peng
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| |
Collapse
|
22
|
Yi D, Nam JW, Jeong H. Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches. Brief Bioinform 2023; 24:bbad297. [PMID: 37587831 PMCID: PMC10516374 DOI: 10.1093/bib/bbad297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/05/2023] [Accepted: 07/23/2023] [Indexed: 08/18/2023] Open
Abstract
Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.
Collapse
Affiliation(s)
- Dohun Yi
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Jin-Wu Nam
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Research Institute for Convergence of Basic Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Bio-BigData Center, Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Hyobin Jeong
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Bio-BigData Center, Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| |
Collapse
|
23
|
Truong MA, Cané-Gasull P, Lens SMA. Modeling specific aneuploidies: from karyotype manipulations to biological insights. Chromosome Res 2023; 31:25. [PMID: 37640903 PMCID: PMC10462580 DOI: 10.1007/s10577-023-09735-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/11/2023] [Accepted: 08/09/2023] [Indexed: 08/31/2023]
Abstract
An abnormal chromosome number, or aneuploidy, underlies developmental disorders and is a common feature of cancer, with different cancer types exhibiting distinct patterns of chromosomal gains and losses. To understand how specific aneuploidies emerge in certain tissues and how they contribute to disease development, various methods have been developed to alter the karyotype of mammalian cells and mice. In this review, we provide an overview of both classic and novel strategies for inducing or selecting specific chromosomal gains and losses in human and murine cell systems. We highlight how these customized aneuploidy models helped expanding our knowledge of the consequences of specific aneuploidies to (cancer) cell physiology.
Collapse
Affiliation(s)
- My Anh Truong
- Oncode Institute and Center for Molecular Medicine, University Medical Center Utrecht, Universiteitsweg 100, 3584, CG, Utrecht, The Netherlands
| | - Paula Cané-Gasull
- Oncode Institute and Center for Molecular Medicine, University Medical Center Utrecht, Universiteitsweg 100, 3584, CG, Utrecht, The Netherlands
| | - Susanne M A Lens
- Oncode Institute and Center for Molecular Medicine, University Medical Center Utrecht, Universiteitsweg 100, 3584, CG, Utrecht, The Netherlands.
| |
Collapse
|
24
|
Arora R, Cao C, Kumar M, Sinha S, Chanda A, McNeil R, Samuel D, Arora RK, Matthews TW, Chandarana S, Hart R, Dort JC, Biernaskie J, Neri P, Hyrcza MD, Bose P. Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response. Nat Commun 2023; 14:5029. [PMID: 37596273 PMCID: PMC10439131 DOI: 10.1038/s41467-023-40271-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/19/2023] [Indexed: 08/20/2023] Open
Abstract
The spatial organization of the tumor microenvironment has a profound impact on biology and therapy response. Here, we perform an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions. We demonstrate that the gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific, highlighting common mechanisms underlying tumor progression and invasion. Additionally, we find our LE gene signature is associated with worse clinical outcomes while TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and interactive spatial atlases ( http://www.pboselab.ca/spatial_OSCC/ ; http://www.pboselab.ca/dynamo_OSCC/ ) that can be foundational for developing novel targeted therapies.
Collapse
Affiliation(s)
- Rohit Arora
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Christian Cao
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Mehul Kumar
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Sarthak Sinha
- Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
| | - Ayan Chanda
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Reid McNeil
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Divya Samuel
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Rahul K Arora
- Center for Health Informatics, University of Calgary, Calgary, AB, Canada
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - T Wayne Matthews
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shamir Chandarana
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Robert Hart
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joseph C Dort
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Ohlson Research Initiative, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Section of Otolaryngology Head & Neck Surgery, Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Jeff Biernaskie
- Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Paola Neri
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Division of Hematology, Department of Oncology, University of Calgary, Calgary, AB, Canada
| | - Martin D Hyrcza
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, Canada
| | - Pinaki Bose
- Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
- Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom.
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
| |
Collapse
|
25
|
Sklavenitis-Pistofidis R, Lightbody ED, Reidy M, Tsuji J, Aranha MP, Heilpern-Mallory D, Huynh D, Chong SJF, Hackett L, Haradhvala NJ, Wu T, Su NK, Berrios B, Alberge JB, Dutta A, Davids MS, Papaioannou M, Getz G, Ghobrial IM, Manier S. Systematic characterization of therapeutic vulnerabilities in Multiple Myeloma with Amp1q reveals increased sensitivity to the combination of MCL1 and PI3K inhibitors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.01.551480. [PMID: 37577538 PMCID: PMC10418223 DOI: 10.1101/2023.08.01.551480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
The development of targeted therapy for patients with Multiple Myeloma (MM) is hampered by the low frequency of actionable genetic abnormalities. Gain or amplification of chr1q (Amp1q) is the most frequent arm-level copy number gain in patients with MM, and it is associated with higher risk of progression and death despite recent advances in therapeutics. Thus, developing targeted therapy for patients with MM and Amp1q stands to benefit a large portion of patients in need of more effective management. Here, we employed large-scale dependency screens and drug screens to systematically characterize the therapeutic vulnerabilities of MM with Amp1q and showed increased sensitivity to the combination of MCL1 and PI3K inhibitors. Using single-cell RNA sequencing, we compared subclones with and without Amp1q within the same patient tumors and showed that Amp1q is associated with higher levels of MCL1 and the PI3K pathway. Furthermore, by isolating isogenic clones with different copy number for part of the chr1q arm, we showed increased sensitivity to MCL1 and PI3K inhibitors with arm-level gain. Lastly, we demonstrated synergy between MCL1 and PI3K inhibitors and dissected their mechanism of action in MM with Amp1q.
Collapse
Affiliation(s)
- Romanos Sklavenitis-Pistofidis
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Elizabeth D. Lightbody
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Mairead Reidy
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Junko Tsuji
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Michelle P. Aranha
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Daniel Heilpern-Mallory
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Daisy Huynh
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Stephen J. F. Chong
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Liam Hackett
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Nicholas J. Haradhvala
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Ting Wu
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Nang K. Su
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Brianna Berrios
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jean-Baptiste Alberge
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Ankit Dutta
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Matthew S. Davids
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Maria Papaioannou
- Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Hematology Unit, 1st Internal Medicine Department, AHEPA University Hospital, Thessaloniki, Greece
| | - Gad Getz
- Harvard Medical School, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Irene M. Ghobrial
- Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
| | - Salomon Manier
- INSERM UMRS1277, CNRS UMR9020, Lille University, 59000, France
- Department of Hematology, CHU Lille, Lille University, 59000, France
| |
Collapse
|
26
|
Samur MK, Szalat R, Munshi NC. Single-cell profiling in multiple myeloma: insights, problems, and promises. Blood 2023; 142:313-324. [PMID: 37196627 PMCID: PMC10485379 DOI: 10.1182/blood.2022017145] [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: 01/19/2023] [Revised: 04/05/2023] [Accepted: 05/11/2023] [Indexed: 05/19/2023] Open
Abstract
In a short time, single-cell platforms have become the norm in many fields of research, including multiple myeloma (MM). In fact, the large amount of cellular heterogeneity in MM makes single-cell platforms particularly attractive because bulk assessments can miss valuable information about cellular subpopulations and cell-to-cell interactions. The decreasing cost and increasing accessibility of single-cell platform, combined with breakthroughs in obtaining multiomics data for the same cell and innovative computational programs for analyzing data, have allowed single-cell studies to make important insights into MM pathogenesis; yet, there is still much to be done. In this review, we will first focus on the types of single-cell profiling and the considerations for designing a single-cell profiling experiment. Then, we will discuss what have learned from single-cell profiling about myeloma clonal evolution, transcriptional reprogramming, and drug resistance, and about the MM microenvironment during precursor and advanced disease.
Collapse
Affiliation(s)
- Mehmet Kemal Samur
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Raphael Szalat
- Department of Hematology and Medical Oncology, Boston University Medical Center, Boston, MA
| | - Nikhil C. Munshi
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
- VA Boston Healthcare System, Boston, MA
| |
Collapse
|
27
|
Beneyto-Calabuig S, Merbach AK, Kniffka JA, Antes M, Szu-Tu C, Rohde C, Waclawiczek A, Stelmach P, Gräßle S, Pervan P, Janssen M, Landry JJM, Benes V, Jauch A, Brough M, Bauer M, Besenbeck B, Felden J, Bäumer S, Hundemer M, Sauer T, Pabst C, Wickenhauser C, Angenendt L, Schliemann C, Trumpp A, Haas S, Scherer M, Raffel S, Müller-Tidow C, Velten L. Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia. Cell Stem Cell 2023; 30:706-721.e8. [PMID: 37098346 DOI: 10.1016/j.stem.2023.04.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 02/05/2023] [Accepted: 03/30/2023] [Indexed: 04/27/2023]
Abstract
Inter-patient variability and the similarity of healthy and leukemic stem cells (LSCs) have impeded the characterization of LSCs in acute myeloid leukemia (AML) and their differentiation landscape. Here, we introduce CloneTracer, a novel method that adds clonal resolution to single-cell RNA-seq datasets. Applied to samples from 19 AML patients, CloneTracer revealed routes of leukemic differentiation. Although residual healthy and preleukemic cells dominated the dormant stem cell compartment, active LSCs resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors constituted a highly aberrant, disease-defining compartment: their gene expression and differentiation state affected both the chemotherapy response and leukemia's ability to differentiate into transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers misregulated specifically in leukemic cells. Taken together, CloneTracer reveals a differentiation landscape that mimics its healthy counterpart and may determine biology and therapy response in AML.
Collapse
Affiliation(s)
- Sergi Beneyto-Calabuig
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Anne Kathrin Merbach
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Jonas-Alexander Kniffka
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Magdalena Antes
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Chelsea Szu-Tu
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Christian Rohde
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Alexander Waclawiczek
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Patrick Stelmach
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Sarah Gräßle
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany; Charité-Universitätsmedizin, 10117 Berlin, Germany; Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
| | - Philip Pervan
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Maike Janssen
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Jonathan J M Landry
- Genomics Core Facility, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Vladimir Benes
- Genomics Core Facility, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
| | - Anna Jauch
- Institute of Human Genetics, University of Heidelberg, 69120 Heidelberg, Germany
| | - Michaela Brough
- Institute of Human Genetics, University of Heidelberg, 69120 Heidelberg, Germany
| | - Marcus Bauer
- Institute of Pathology, University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg, 06112 Halle, Germany
| | - Birgit Besenbeck
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Julia Felden
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Sebastian Bäumer
- Department of Medicine A, Hematology and Oncology, University Hospital, Muenster, Germany
| | - Michael Hundemer
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Tim Sauer
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Caroline Pabst
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany
| | - Claudia Wickenhauser
- Institute of Pathology, University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg, 06112 Halle, Germany
| | - Linus Angenendt
- Department of Medicine A, Hematology and Oncology, University Hospital, Muenster, Germany; Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Christoph Schliemann
- Department of Medicine A, Hematology and Oncology, University Hospital, Muenster, Germany
| | - Andreas Trumpp
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany
| | - Simon Haas
- Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ) and DKFZ-ZMBH Alliance, 69120 Heidelberg, Germany; Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany; Charité-Universitätsmedizin, 10117 Berlin, Germany; Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
| | - Michael Scherer
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Simon Raffel
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Carsten Müller-Tidow
- Department of Medicine, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, 69120 Heidelberg, Germany; Molecular Medicine Partnership Unit, European Molecular Biology Laboratory (EMBL), University of Heidelberg, 69117 Heidelberg, Germany.
| | - Lars Velten
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| |
Collapse
|
28
|
Shi H, Williams MJ, Satas G, Weiner AC, McPherson A, Shah SP. Exploiting allele-specific transcriptional effects of subclonal copy number alterations for genotype-phenotype mapping in cancer cell populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.10.523464. [PMID: 36711951 PMCID: PMC9882029 DOI: 10.1101/2023.01.10.523464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Somatic copy number alterations drive aberrant gene expression in cancer cells. In tumors with high levels of chromosomal instability, subclonal copy number alterations (CNAs) are a prevalent feature which often result in heterogeneous cancer cell populations with distinct phenotypes1. However, the extent to which subclonal CNAs contribute to clone-specific phenotypes remains poorly understood, in part due to the lack of methods to quantify how CNAs influence gene expression at a subclone level. We developed TreeAlign, which computationally integrates independently sampled single-cell DNA and RNA sequencing data from the same cell population and explicitly models gene dosage effects from subclonal alterations. We show through quantitative benchmarking data and application to human cancer data with single cell DNA and RNA libraries that TreeAlign accurately encodes clone-specific transcriptional effects of subclonal CNAs, the impact of allelic imbalance on allele-specific transcription, and obviates the need to arbitrarily define genotypic clones from a phylogenetic tree a priori. Combined, these advances lead to highly granular definitions of clones with distinct copy-number driven expression programs with increased resolution and accuracy over competing methods. The resulting improvement in assignment of transcriptional phenotypes to genomic clones enables clone-clone gene expression comparisons and explicit inference of genes that are mechanistically altered through CNAs, and identification of expression programs that are genomically independent. Our approach sets the stage for dissecting the relative contribution of fixed genomic alterations and dynamic epigenetic processes on gene expression programs in cancer.
Collapse
Affiliation(s)
- Hongyu Shi
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, NY, USA
| | - Marc J. Williams
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gryte Satas
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Adam C. Weiner
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Andrew McPherson
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sohrab P. Shah
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| |
Collapse
|