1
|
Mulet-Lazaro R, van Herk S, Nuetzel M, Sijs-Szabo A, Díaz N, Kelly K, Erpelinck-Verschueren C, Schwarzfischer-Pfeilschifter L, Stanewsky H, Ackermann U, Glatz D, Raithel J, Fischer A, Pohl S, Rijneveld A, Vaquerizas JM, Thiede C, Plass C, Wouters BJ, Delwel R, Rehli M, Gebhard C. Epigenetic alterations affecting hematopoietic regulatory networks as drivers of mixed myeloid/lymphoid leukemia. Nat Commun 2024; 15:5693. [PMID: 38972954 PMCID: PMC11228033 DOI: 10.1038/s41467-024-49811-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 06/19/2024] [Indexed: 07/09/2024] Open
Abstract
Leukemias with ambiguous lineage comprise several loosely defined entities, often without a clear mechanistic basis. Here, we extensively profile the epigenome and transcriptome of a subgroup of such leukemias with CpG Island Methylator Phenotype. These leukemias exhibit comparable hybrid myeloid/lymphoid epigenetic landscapes, yet heterogeneous genetic alterations, suggesting they are defined by their shared epigenetic profile rather than common genetic lesions. Gene expression enrichment reveals similarity with early T-cell precursor acute lymphoblastic leukemia and a lymphoid progenitor cell of origin. In line with this, integration of differential DNA methylation and gene expression shows widespread silencing of myeloid transcription factors. Moreover, binding sites for hematopoietic transcription factors, including CEBPA, SPI1 and LEF1, are uniquely inaccessible in these leukemias. Hypermethylation also results in loss of CTCF binding, accompanied by changes in chromatin interactions involving key transcription factors. In conclusion, epigenetic dysregulation, and not genetic lesions, explains the mixed phenotype of this group of leukemias with ambiguous lineage. The data collected here constitute a useful and comprehensive epigenomic reference for subsequent studies of acute myeloid leukemias, T-cell acute lymphoblastic leukemias and mixed-phenotype leukemias.
Collapse
Affiliation(s)
- Roger Mulet-Lazaro
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Stanley van Herk
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Margit Nuetzel
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Aniko Sijs-Szabo
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Noelia Díaz
- Max Planck Institute for Molecular Biomedicine, Muenster, Germany
- Renewable Marine Resources Department, Institute of Marine Sciences (ICM-CSIC), Barcelona, Spain
| | - Katherine Kelly
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Claudia Erpelinck-Verschueren
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | | | - Hanna Stanewsky
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Ute Ackermann
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Dagmar Glatz
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Johanna Raithel
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Alexander Fischer
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
| | - Sandra Pohl
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany
- Department of Conservative Dentistry and Periodontology, University Hospital Regensburg, Regensburg, Germany
| | - Anita Rijneveld
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Juan M Vaquerizas
- Max Planck Institute for Molecular Biomedicine, Muenster, Germany
- MRC London Institute of Medical Sciences, London, United Kingdom
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital 8 Campus, London, United Kingdom
| | - Christian Thiede
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Christoph Plass
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bas J Wouters
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands.
- Oncode Institute, Utrecht, the Netherlands.
| | - Ruud Delwel
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands.
- Oncode Institute, Utrecht, the Netherlands.
| | - Michael Rehli
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany.
- Leibniz Institute for Immunotherapy (LIT), Regensburg, Germany.
| | - Claudia Gebhard
- Department of Internal Medicine III, University Hospital Regensburg, Regensburg, Germany.
- Leibniz Institute for Immunotherapy (LIT), Regensburg, Germany.
| |
Collapse
|
2
|
Zhong X, Luan J, Yu A, Lee-Hassett A, Miao Y, Yang L. SFyNCS detects oncogenic fusions involving non-coding sequences in cancer. Nucleic Acids Res 2023; 51:e96. [PMID: 37638762 PMCID: PMC10570049 DOI: 10.1093/nar/gkad705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/15/2023] [Accepted: 08/14/2023] [Indexed: 08/29/2023] Open
Abstract
Fusion genes are well-known cancer drivers. However, most known oncogenic fusions are protein-coding, and very few involve non-coding sequences due to lack of suitable detection tools. We develop SFyNCS to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. The main advantage of this study is that we use somatic structural variations detected from genomic data to validate fusions detected from transcriptomic data. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We show that SFyNCS has superior sensitivity and specificity over existing algorithms through extensive benchmarking in cancer cell lines and patient samples. We then apply SFyNCS to 9565 tumor samples across 33 tumor types in The Cancer Genome Atlas cohort and detect a total of 165,139 fusions. Among them, 72% of the fusions involve non-coding sequences. We find a long non-coding RNA to recurrently fuse with various oncogenes in 3% of prostate cancers. In addition, we discover fusions involving two non-coding RNAs in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.
Collapse
Affiliation(s)
- Xiaoming Zhong
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
| | - Jingyun Luan
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
| | - Anqi Yu
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
| | - Anna Lee-Hassett
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
| | - Yuxuan Miao
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
- University of Chicago Comprehensive Cancer Center, Chicago, IL, USA
| | - Lixing Yang
- Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA
- University of Chicago Comprehensive Cancer Center, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago IL, USA
| |
Collapse
|
3
|
Li X, Shao M. On de novo Bridging Paired-end RNA-seq Data. ACM-BCB ... ... : THE ... ACM CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY AND BIOMEDICINE. ACM CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY AND BIOMEDICINE 2023; 2023:41. [PMID: 38045531 PMCID: PMC10692976 DOI: 10.1145/3584371.3612987] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The high-throughput short-reads RNA-seq protocols often produce paired-end reads, with the middle portion of the fragments being unsequenced. We explore if the full-length fragments can be computationally reconstructed from the sequenced two ends in the absence of the reference genome-a problem here we refer to as de novo bridging. Solving this problem provides longer, more informative RNA-seq reads, and benefits downstream RNA-seq analysis such as transcript assembly, expression quantification, and splicing differential analysis. However, de novo bridging is a challenging and complicated task owing to alternative splicing, transcript noises, and sequencing errors. It remains unclear if the data provides sufficient information for accurate bridging, let alone efficient algorithms that determine the true bridges. Methods have been proposed to bridge paired-end reads in the presence of reference genome (called reference-based bridging), but the algorithms are far away from scaling for de novo bridging as the underlying compacted de Bruijn graph (cdBG) used in the latter task often contains millions of vertices and edges. We designed a new truncated Dijkstra's algorithm for this problem, and proposed a novel algorithm that reuses the shortest path tree to avoid running the truncated Dijkstra's algorithm from scratch for all vertices for further speeding up. These innovative techniques result in scalable algorithms that can bridge all paired-end reads in a cdBG with millions of vertices. Our experiments showed that paired-end RNA-seq reads can be accurately bridged to a large extent. The resulting tool is freely available at https://github.com/Shao-Group/rnabridge-denovo.
Collapse
Affiliation(s)
- Xiang Li
- Department of Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Mingfu Shao
- Department of Computer Science and Engineering, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA
| |
Collapse
|
4
|
da Costa MEM, Droit R, Khneisser P, Gomez-Brouchet A, Adam-de-Beaumais T, Nolla M, Signolles N, Torrejon J, Lombard B, Loew D, Ayrault O, Scoazec JY, Geoerger B, Vassal G, Marchais A, Gaspar N. Longitudinal characterization of primary osteosarcoma and derived subcutaneous and orthotopic relapsed patient-derived xenograft models. Front Oncol 2023; 13:1166063. [PMID: 37377921 PMCID: PMC10291137 DOI: 10.3389/fonc.2023.1166063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 04/25/2023] [Indexed: 06/29/2023] Open
Abstract
Osteosarcoma is a rare bone cancer in adolescents and young adults with a dismal prognosis because of metastatic disease and chemoresistance. Despite multiple clinical trials, no improvement in outcome has occurred in decades. There is an urgent need to better understand resistant and metastatic disease and to generate in vivo models from relapsed tumors. We developed eight new patient-derived xenograft (PDX) subcutaneous and orthotopic/paratibial models derived from patients with recurrent osteosarcoma and compared the genetic and transcriptomic landscapes of the disease progression at diagnosis and relapse with the matching PDX. Whole exome sequencing showed that driver and copy-number alterations are conserved from diagnosis to relapse, with the emergence of somatic alterations of genes mostly involved in DNA repair, cell cycle checkpoints, and chromosome organization. All PDX patients conserve most of the genetic alterations identified at relapse. At the transcriptomic level, tumor cells maintain their ossification, chondrocytic, and trans-differentiation programs during progression and implantation in PDX models, as identified at the radiological and histological levels. A more complex phenotype, like the interaction with immune cells and osteoclasts or cancer testis antigen expression, seemed conserved and was hardly identifiable by histology. Despite NSG mouse immunodeficiency, four of the PDX models partially reconstructed the vascular and immune-microenvironment observed in patients, among which the macrophagic TREM2/TYROBP axis expression, recently linked to immunosuppression. Our multimodal analysis of osteosarcoma progression and PDX models is a valuable resource to understand resistance and metastatic spread mechanisms, as well as for the exploration of novel therapeutic strategies for advanced osteosarcoma.
Collapse
Affiliation(s)
- Maria Eugenia Marques da Costa
- INSERM U1015, Université Paris-Saclay, Villejuif, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Robin Droit
- INSERM U1015, Université Paris-Saclay, Villejuif, France
| | - Pierre Khneisser
- Department of Medical Biology and Pathology, Gustave Roussy Cancer Campus, Villejuif, France
| | - Anne Gomez-Brouchet
- Department of Pathology, IUCT-Oncopole, CHU Toulouse and University Toulouse, Pharmacology and Structural Biology Institute, CNRS UMR5089, Toulouse, France
| | - Tiphaine Adam-de-Beaumais
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Marie Nolla
- Department of Pediatric Hemato-oncology, CHU Toulouse, Toulouse, France
| | - Nicolas Signolles
- Department of Medical Biology and Pathology, Gustave Roussy Cancer Campus, Villejuif, France
| | - Jacob Torrejon
- Institut Curie, PSL Research University, CNRS UMR, INSERM, Orsay, France
- Université Paris Sud, Université Paris-Saclay, CNRS UMR, INSERM, Orsay, France
| | - Bérangère Lombard
- Institut Curie, PSL Research University, Centre de Recherche, Laboratoire de Spectrométrie de Masse Protéomique, Paris, France
| | - Damarys Loew
- Institut Curie, PSL Research University, Centre de Recherche, Laboratoire de Spectrométrie de Masse Protéomique, Paris, France
| | - Olivier Ayrault
- Institut Curie, PSL Research University, CNRS UMR, INSERM, Orsay, France
- Université Paris Sud, Université Paris-Saclay, CNRS UMR, INSERM, Orsay, France
| | - Jean-Yves Scoazec
- Department of Medical Biology and Pathology, Gustave Roussy Cancer Campus, Villejuif, France
| | - Birgit Geoerger
- INSERM U1015, Université Paris-Saclay, Villejuif, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Gilles Vassal
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Antonin Marchais
- INSERM U1015, Université Paris-Saclay, Villejuif, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Nathalie Gaspar
- INSERM U1015, Université Paris-Saclay, Villejuif, France
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| |
Collapse
|
5
|
Zhong X, Luan J, Yu A, Lee-Hassett A, Miao Y, Yang L. SFyNCS detects oncogenic fusions involving non-coding sequences in cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.03.535462. [PMID: 37066382 PMCID: PMC10104044 DOI: 10.1101/2023.04.03.535462] [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: 06/19/2023]
Abstract
Fusion genes are well-known cancer drivers. However, very few known oncogenic fusions involve non-coding sequences. We develop SFyNCS with superior performance to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. We validate fusions using somatic structural variations detected from the genomes. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We detect 165,139 fusions in 9,565 tumor samples across 33 tumor types in the Cancer Genome Atlas cohort. Among them, 72% of the fusions involve non-coding sequences and many are recurrent. We discover two long non-coding RNAs recurrently fused with various partner genes in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.
Collapse
Affiliation(s)
- Xiaoming Zhong
- Ben May Department for Cancer Research, University of Chicago, Chicago IL, USA
| | - Jingyun Luan
- Ben May Department for Cancer Research, University of Chicago, Chicago IL, USA
| | - Anqi Yu
- Ben May Department for Cancer Research, University of Chicago, Chicago IL, USA
| | - Anna Lee-Hassett
- Ben May Department for Cancer Research, University of Chicago, Chicago IL, USA
| | - Yuxuan Miao
- Ben May Department for Cancer Research, University of Chicago, Chicago IL, USA
- University of Chicago Comprehensive Cancer Center, Chicago, IL, USA
| | - Lixing Yang
- Ben May Department for Cancer Research, University of Chicago, Chicago IL, USA
- University of Chicago Comprehensive Cancer Center, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago IL, USA
| |
Collapse
|
6
|
Sun Y, Li H. Chimeric RNAs Discovered by RNA Sequencing and Their Roles in Cancer and Rare Genetic Diseases. Genes (Basel) 2022; 13:741. [PMID: 35627126 PMCID: PMC9140685 DOI: 10.3390/genes13050741] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 04/13/2022] [Accepted: 04/20/2022] [Indexed: 12/30/2022] Open
Abstract
Chimeric RNAs are transcripts that are generated by gene fusion and intergenic splicing events, thus comprising nucleotide sequences from different parental genes. In the past, Northern blot analysis and RT-PCR were used to detect chimeric RNAs. However, they are low-throughput and can be time-consuming, labor-intensive, and cost-prohibitive. With the development of RNA-seq and transcriptome analyses over the past decade, the number of chimeric RNAs in cancer as well as in rare inherited diseases has dramatically increased. Chimeric RNAs may be potential diagnostic biomarkers when they are specifically expressed in cancerous cells and/or tissues. Some chimeric RNAs can also play a role in cell proliferation and cancer development, acting as tools for cancer prognosis, and revealing new insights into the cell origin of tumors. Due to their abilities to characterize a whole transcriptome with a high sequencing depth and intergenically identify spliced chimeric RNAs produced with the absence of chromosomal rearrangement, RNA sequencing has not only enhanced our ability to diagnose genetic diseases, but also provided us with a deeper understanding of these diseases. Here, we reviewed the mechanisms of chimeric RNA formation and the utility of RNA sequencing for discovering chimeric RNAs in several types of cancer and rare inherited diseases. We also discussed the diagnostic, prognostic, and therapeutic values of chimeric RNAs.
Collapse
Affiliation(s)
- Yunan Sun
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA;
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Hui Li
- Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA;
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| |
Collapse
|
7
|
Yurchenko AA, Pop OT, Ighilahriz M, Padioleau I, Rajabi F, Sharpe HJ, Poulalhon N, Dreno B, Khammari A, Delord M, Alberti A, Soufir N, Battistella M, Mourah S, Bouquet F, Savina A, Besse A, Mendez-Lopez M, Grange F, Monestier S, Mortier L, Meyer N, Dutriaux C, Robert C, Saiag P, Herms F, Lambert J, de Sauvage FJ, Dumaz N, Flatz L, Basset-Seguin N, Nikolaev SI. Frequency and Genomic Aspects of Intrinsic Resistance to Vismodegib in Locally Advanced Basal Cell Carcinoma. Clin Cancer Res 2022; 28:1422-1432. [PMID: 35078858 PMCID: PMC9365352 DOI: 10.1158/1078-0432.ccr-21-3764] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/03/2021] [Accepted: 01/20/2022] [Indexed: 01/07/2023]
Abstract
PURPOSE Vismodegib is approved for the treatment of locally advanced basal cell carcinoma (laBCC), but some cases demonstrate intrinsic resistance (IR) to the drug. We sought to assess the frequency of IR to vismodegib in laBCC and its underlying genomic mechanisms. EXPERIMENTAL DESIGN Response to vismodegib was evaluated in a cohort of 148 laBCC patients. Comprehensive genomic and transcriptomic profiling was performed in a subset of five intrinsically resistant BCC (IR-BCC). RESULTS We identified that IR-BCC represents 6.1% of laBCC in the studied cohort. Prior treatment with chemotherapy was associated with IR. Genetic events that were previously associated with acquired resistance (AR) in BCC or medulloblastoma were observed in three out of five IR-BCC. However, IR-BCCs were distinct by highly rearranged polyploid genomes. Functional analyses identified hyperactivation of the HIPPO-YAP and WNT pathways at RNA and protein levels in IR-BCC. In vitro assay on the BCC cell line further confirmed that YAP1 overexpression increases the cell proliferation rate. CONCLUSIONS IR to vismodegib is a rare event in laBCC. IR-BCCs frequently harbor resistance mutations in the Hh pathway, but also are characterized by hyperactivation of the HIPPO-YAP and WNT pathways.
Collapse
Affiliation(s)
- Andrey A. Yurchenko
- INSERM U981, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Oltin T. Pop
- Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | | | - Ismael Padioleau
- INSERM U981, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | - Fatemeh Rajabi
- INSERM U981, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | | | - Nicolas Poulalhon
- Service de dermatologie, Hôpital Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Brigitte Dreno
- Department of Dermato-Oncology, CHU Nantes, Nantes Université, CIC 1413, Inserm UMR 1302/EMR6001 INCIT, F-44000 Nantes, France
| | - Amir Khammari
- Department of Dermato-Oncology, CHU Nantes, Nantes Université, CIC 1413, Inserm UMR 1302/EMR6001 INCIT, F-44000 Nantes, France
| | - Marc Delord
- Université de Paris, Hôpital Saint-Louis, Paris, France.,Department of Population Health Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | | | | | - Maxime Battistella
- INSERM U976, Hôpital Saint-Louis, Paris, France.,Université de Paris, Hôpital Saint-Louis, Paris, France.,Service d'anatomie pathologique, Hôpital Saint-Louis, Claude Vellefaux, Paris, France
| | - Samia Mourah
- INSERM U976, Hôpital Saint-Louis, Paris, France.,Université de Paris, Hôpital Saint-Louis, Paris, France.,Département de Génomique des Tumeurs Solides, Hôpital Saint-Louis, Claude Vellefaux, Paris, France
| | | | | | - Andrej Besse
- Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Max Mendez-Lopez
- Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Florent Grange
- Service de dermatologie, CHU Reims, Rue du general Koenig, Reims, France.,Service de Dermatologie, centre hospitalier de Valence, Valence, France
| | | | - Laurent Mortier
- Service de dermatologie, CHU Lille, Clin Dermato Hop Huriez, Rue Michel Polonovski, Lille, France
| | - Nicolas Meyer
- Service de dermatologie, Institut Univeristaire du Cancer et CHU de Toulouse, Hôpital Larrey, Toulouse, France
| | | | - Caroline Robert
- INSERM U981, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France.,Department of Medical Oncology, Gustave Roussy and Paris-Saclay University, Villejuif, France
| | - Philippe Saiag
- Department of General and Oncologic Dermatology, Ambroise-Paré hospital, APHP, and EA 4340 “Biomarkers in Cancerology and Hemato-oncology,” UVSQ, Université Paris-Saclay, Boulogne-Billancourt, France
| | - Florian Herms
- Service de dermatologie, Hôpital Saint-Louis, Paris, France
| | - Jerome Lambert
- Université de Paris, Hôpital Saint-Louis, Paris, France.,Service de Biostatistique et Information Médicale, Hôpital Saint-Louis, Paris, France
| | | | | | - Lukas Flatz
- Institute of Immunobiology, Kantonsspital St. Gallen, St. Gallen, Switzerland.,Department of Dermatology, University Hospital Tübingen, Tübingen, Germany
| | - Nicole Basset-Seguin
- INSERM U976, Hôpital Saint-Louis, Paris, France.,Université de Paris, Hôpital Saint-Louis, Paris, France.,Service de dermatologie, Hôpital Saint-Louis, Paris, France.,Corresponding Authors: Sergey I. Nikolaev, U981 INSERM, Institut Gustave Roussy, 114 rue Edouard Vaillant, 94800 Villejuif, France. Phone: 33-142115775; E-mail: ; and Nicole Basset-Seguin, Service de dermatologie, unité d'oncodermatologie, Hôpital Saint-Louis, 1 avenue Claude Vellefaux, 75010 Paris. Phone: 33-153722066; Fax: 33-142355310; E-mail:
| | - Sergey I. Nikolaev
- INSERM U981, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France.,Corresponding Authors: Sergey I. Nikolaev, U981 INSERM, Institut Gustave Roussy, 114 rue Edouard Vaillant, 94800 Villejuif, France. Phone: 33-142115775; E-mail: ; and Nicole Basset-Seguin, Service de dermatologie, unité d'oncodermatologie, Hôpital Saint-Louis, 1 avenue Claude Vellefaux, 75010 Paris. Phone: 33-153722066; Fax: 33-142355310; E-mail:
| |
Collapse
|
8
|
Marwaha S, Knowles JW, Ashley EA. A guide for the diagnosis of rare and undiagnosed disease: beyond the exome. Genome Med 2022; 14:23. [PMID: 35220969 PMCID: PMC8883622 DOI: 10.1186/s13073-022-01026-w] [Citation(s) in RCA: 113] [Impact Index Per Article: 56.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/10/2022] [Indexed: 02/07/2023] Open
Abstract
Rare diseases affect 30 million people in the USA and more than 300-400 million worldwide, often causing chronic illness, disability, and premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with the medical literature. A large number of rare disease patients remain undiagnosed for years and many even die without an accurate diagnosis. In recent years, gene panels, microarrays, and exome sequencing have helped to identify the molecular cause of such rare and undiagnosed diseases. These technologies have allowed diagnoses for a sizable proportion (25-35%) of undiagnosed patients, often with actionable findings. However, a large proportion of these patients remain undiagnosed. In this review, we focus on technologies that can be adopted if exome sequencing is unrevealing. We discuss the benefits of sequencing the whole genome and the additional benefit that may be offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, and methyl profiling. We highlight computational methods to help identify regionally distant patients with similar phenotypes or similar genetic mutations. Finally, we describe approaches to automate and accelerate genomic analysis. The strategies discussed here are intended to serve as a guide for clinicians and researchers in the next steps when encountering patients with non-diagnostic exomes.
Collapse
Affiliation(s)
- Shruti Marwaha
- Department of Medicine, Division of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA.
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA.
| | - Joshua W Knowles
- Department of Medicine, Division of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Medicine, Diabetes Research Center, Cardiovascular Institute and Prevention Research Center, Stanford, CA, USA
| | - Euan A Ashley
- Department of Medicine, Division of Cardiovascular Medicine, School of Medicine, Stanford University, Stanford, CA, USA.
- Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA, USA.
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA.
| |
Collapse
|
9
|
Hedges DJ. RNA-seq Fusion Detection in Clinical Oncology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1361:163-175. [DOI: 10.1007/978-3-030-91836-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
|
10
|
Cmero M, Schmidt B, Majewski IJ, Ekert PG, Oshlack A, Davidson NM. MINTIE: identifying novel structural and splice variants in transcriptomes using RNA-seq data. Genome Biol 2021; 22:296. [PMID: 34686194 PMCID: PMC8532352 DOI: 10.1186/s13059-021-02507-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 09/27/2021] [Indexed: 12/13/2022] Open
Abstract
Calling fusion genes from RNA-seq data is well established, but other transcriptional variants are difficult to detect using existing approaches. To identify all types of variants in transcriptomes we developed MINTIE, an integrated pipeline for RNA-seq data. We take a reference-free approach, combining de novo assembly of transcripts with differential expression analysis to identify up-regulated novel variants in a case sample. We compare MINTIE with eight other approaches, detecting > 85% of variants while no other method is able to achieve this. We posit that MINTIE will be able to identify new disease variants across a range of disease types.
Collapse
Affiliation(s)
- Marek Cmero
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia
| | - Breon Schmidt
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, Australia
- School of BioSciences, University of Melbourne, Parkville, Australia
| | - Ian J Majewski
- Walter and Eliza Hall Institute, Parkville, Australia
- Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
| | - Paul G Ekert
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Parkville, Australia
- Children's Cancer Institute, UNSW, Sydney, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Australia
| | - Alicia Oshlack
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
- Murdoch Children's Research Institute, Parkville, Australia.
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Australia.
- School of BioSciences, University of Melbourne, Parkville, Australia.
| | - Nadia M Davidson
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
- Murdoch Children's Research Institute, Parkville, Australia.
- School of BioSciences, University of Melbourne, Parkville, Australia.
| |
Collapse
|
11
|
Ji G, Ren R, Fang X. Identification and Characterization of Non-Coding RNAs in Thymoma. Med Sci Monit 2021; 27:e929727. [PMID: 34219124 PMCID: PMC8268976 DOI: 10.12659/msm.929727] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Accepted: 03/10/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Thymoma is the most common tumor of the anterior mediastinum, and can be caused by infrequent malignancies arising from the epithelial cells of the thymus. Unfortunately, blood-based diagnostic markers are not currently available. High-throughput sequencing technologies, such as RNA-seq with next-generation sequencing, have facilitated the detection and characterization of both coding and non-coding RNAs (ncRNAs), which play significant roles in genomic regulation, transcriptional and post-transcriptional regulation, and imprinting and epigenetic modification. The knowledge about fusion genes and ncRNAs in thymomas is scarce. MATERIAL AND METHODS For this study, we gathered large-scale RNA-seq data belonging to samples from 25 thymomas and 25 healthy thymus specimens and analyzed them to identify fusion genes, lncRNAs, and miRNAs. RESULTS We found 21 fusion genes, including KMT2A-MAML2, HADHB-REEP1, COQ3-CGA, MCM4-SNTB1, and IFT140-ACTN4, as the most frequent and significant in thymomas. We also detected 65 differentially-expressed lncRNAs in thymomas, including AFAP1-AS1, LINC00324, ADAMTS9-AS1, VLDLR-AS1, LINC00968, and NEAT1, that have been validated with the TCGA database. Moreover, we identified 1695 miRNAs from small RNA-seq data that were overexpressed in thymomas. Our network analysis of the lncRNA-mRNA-miRNA regulation axes identified a cluster of miRNAs upregulated in thymomas, that can trigger the expression of target protein-coding genes, and lead to the disruption of several biological pathways, including the PI3K-Akt signaling pathway, FoxO signaling pathway, and HIF-1 signaling pathway. CONCLUSIONS Our results show that overexpression of this miRNA cluster activates PI3K-Akt, FoxO, HIF-1, and Rap-1 signaling pathways, suggesting pathway inhibitors may be therapeutic candidates against thymoma.
Collapse
Affiliation(s)
- Guanglei Ji
- First Department of Thoracic Surgery, Linyi Cancer Hospital, Linyi, Shandong, PR China
| | - Rongrong Ren
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, PR China
| | - Xichao Fang
- Second Department of Thoracic Surgery, Linyi Cancer Hospital, Linyi, Shandong, PR China
| |
Collapse
|
12
|
Yang M, Shang X, Zhou Y, Wang C, Wei G, Tang J, Zhang M, Liu Y, Cao J, Zhang Q. Full-Length Transcriptome Analysis of Plasmodium falciparum by Single-Molecule Long-Read Sequencing. Front Cell Infect Microbiol 2021; 11:631545. [PMID: 33708645 PMCID: PMC7942025 DOI: 10.3389/fcimb.2021.631545] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 01/05/2021] [Indexed: 11/25/2022] Open
Abstract
Malaria, an infectious disease caused by Plasmodium parasites, still accounts for amounts of deaths annually in last decades. Despite the significance of Plasmodium falciparum as a model organism of malaria parasites, our understanding of gene expression of this parasite remains largely elusive since lots of progress on its genome and transcriptome are based on assembly with short sequencing reads. Herein, we report the new version of transcriptome dataset containing all full-length transcripts over the whole asexual blood stages by adopting a full-length sequencing approach with optimized experimental conditions of cDNA library preparation. We have identified a total of 393 alternative splicing (AS) events, 3,623 long non-coding RNAs (lncRNAs), 1,555 alternative polyadenylation (APA) events, 57 transcription factors (TF), 1,721 fusion transcripts in P. falciparum. Furthermore, the shotgun proteome was performed to validate the full-length transcriptome of P. falciparum. More importantly, integration of full-length transcriptomic and proteomic data identified 160 novel small proteins in lncRNA regions. Collectively, this full-length transcriptome dataset with high quality and accuracy and the shotgun proteome analyses shed light on the complex gene expression in malaria parasites and provide a valuable resource for related functional and mechanistic researches on P. falciparum genes.
Collapse
Affiliation(s)
- Mengquan Yang
- Research Center for Translational Medicine, Key Laboratory of Arrhythmias of the Ministry of Education of China, East Hospital, Tongji University School of Medicine, Shanghai, China.,State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.,CAS Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xiaomin Shang
- Research Center for Translational Medicine, Key Laboratory of Arrhythmias of the Ministry of Education of China, East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yiqing Zhou
- CAS Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Changhong Wang
- Research Center for Translational Medicine, Key Laboratory of Arrhythmias of the Ministry of Education of China, East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Guiying Wei
- Research Center for Translational Medicine, Key Laboratory of Arrhythmias of the Ministry of Education of China, East Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jianxia Tang
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China
| | - Meihua Zhang
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China
| | - Yaobao Liu
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China
| | - Jun Cao
- National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China.,Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qingfeng Zhang
- Research Center for Translational Medicine, Key Laboratory of Arrhythmias of the Ministry of Education of China, East Hospital, Tongji University School of Medicine, Shanghai, China
| |
Collapse
|
13
|
Onoyama I, Nakayama S, Shimizu H, Nakayama KI. Loss of Fbxw7 Impairs Development of and Induces Heterogeneous Tumor Formation in the Mouse Mammary Gland. Cancer Res 2020; 80:5515-5530. [PMID: 33234509 DOI: 10.1158/0008-5472.can-20-0271] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 08/17/2020] [Accepted: 10/22/2020] [Indexed: 11/16/2022]
Abstract
Fbxw7 is an F-box protein that contributes to regulation of cell proliferation and cell fate determination as well as to tumor suppression in various tissues. In this study, we generated mice with mammary gland-specific ablation of Fbxw7 (Blg-Cre/Fbxw7 F/F mice) and found that most neonates born to mutant dams die soon after birth as a result of defective maternal lactation. The mammary gland of mutant dams was markedly atrophic and manifested both excessive cell proliferation and apoptosis in association with the accumulation of Notch1 and p63. Despite the hypoplastic nature of the mutant mammary gland, Blg-Cre/Fbxw7 F/F mice spontaneously developed mammary tumors that resembled basal-like carcinoma with marked intratumoral heterogeneity. Additional inactivation of Trp53 in Blg-Cre/Fbxw7 F/F mice further promoted onset and development of mammary tumors, suggesting that spontaneous mutation of Trp53 may facilitate transition of hypoplastic mammary lesions to aggressive cancer in mice lacking Fbxw7. RNA-sequencing analysis of epithelial- and mesenchymal-like cell lines from a Blg-Cre/Fbxw7 F/F mouse tumor revealed an increased mutation rate and structural alterations in the tumor and differential expression of upstream transcription factors including known targets of Fbxw7. Together, our results implicate Fbxw7 in the regulation of cell differentiation and in tumor suppression in the mammary gland. Loss of Fbxw7 increases mutation rate and chromosome instability, activates signaling pathways governed by transcription factors regulated by Fbxw7, and triggers the development of mammary tumors with prominent heterogeneity. SIGNIFICANCE: Mammary gland-specific ablation of Fbxw7 in mice results in defective gland development and spontaneous mammary tumor formation reminiscent of human basal-like carcinoma with intratumoral heterogeneity. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/24/5515/F1.large.jpg.
Collapse
Affiliation(s)
- Ichiro Onoyama
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Fukuoka Japan
| | - Shogo Nakayama
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Fukuoka Japan
| | - Hideyuki Shimizu
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Fukuoka Japan
| | - Keiichi I Nakayama
- Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Fukuoka Japan.
| |
Collapse
|
14
|
Brueffer C, Gladchuk S, Winter C, Vallon‐Christersson J, Hegardt C, Häkkinen J, George AM, Chen Y, Ehinger A, Larsson C, Loman N, Malmberg M, Rydén L, Borg Å, Saal LH. The mutational landscape of the SCAN-B real-world primary breast cancer transcriptome. EMBO Mol Med 2020; 12:e12118. [PMID: 32926574 PMCID: PMC7539222 DOI: 10.15252/emmm.202012118] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 08/08/2020] [Accepted: 08/13/2020] [Indexed: 12/12/2022] Open
Abstract
Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN-B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA-seq pipeline for detection of SNVs/indels and profiled a real-world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population-based cohort and relate it to patient survival. We demonstrate that RNA-seq can be used to call mutations in genes such as PIK3CA, TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN-B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA-seq as a clinical tool, where both gene expression- and mutation-based biomarkers can be interrogated in real-time within 1 week of tumor sampling.
Collapse
Affiliation(s)
- Christian Brueffer
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
| | - Sergii Gladchuk
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
| | - Christof Winter
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- Present address:
Institut für Klinische Chemie und PathobiochemieKlinikum rechts der IsarTechnische Universität MünchenMünchenGermany
| | - Johan Vallon‐Christersson
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- CREATE Health Strategic Center for Translational Cancer ResearchLund UniversityLundSweden
| | - Cecilia Hegardt
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- CREATE Health Strategic Center for Translational Cancer ResearchLund UniversityLundSweden
| | - Jari Häkkinen
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
| | - Anthony M George
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
| | - Yilun Chen
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
| | - Anna Ehinger
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- Department of PathologySkåne University HospitalLundSweden
| | - Christer Larsson
- Lund University Cancer CenterLundSweden
- Division of Molecular PathologyDepartment of Laboratory MedicineLund UniversityLundSweden
| | - Niklas Loman
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- Department of OncologySkåne University HospitalLundSweden
| | | | - Lisa Rydén
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- Department of SurgerySkåne University HospitalLundSweden
| | - Åke Borg
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- CREATE Health Strategic Center for Translational Cancer ResearchLund UniversityLundSweden
| | - Lao H Saal
- Division of OncologyDepartment of Clinical SciencesLund UniversityLundSweden
- Lund University Cancer CenterLundSweden
- CREATE Health Strategic Center for Translational Cancer ResearchLund UniversityLundSweden
| |
Collapse
|
15
|
Chiu R, Nip KM, Birol I. Fusion-Bloom: fusion detection in assembled transcriptomes. Bioinformatics 2020; 36:2256-2257. [PMID: 31790154 PMCID: PMC7141844 DOI: 10.1093/bioinformatics/btz902] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 11/13/2019] [Accepted: 11/27/2019] [Indexed: 11/13/2022] Open
Abstract
Summary Presence or absence of gene fusions is one of the most important diagnostic markers in many cancer types. Consequently, fusion detection methods using various genomics data types, such as RNA sequencing (RNA-seq) are valuable tools for research and clinical applications. While information-rich RNA-seq data have proven to be instrumental in discovery of a number of hallmark fusion events, bioinformatics tools to detect fusions still have room for improvement. Here, we present Fusion-Bloom, a fusion detection method that leverages recent developments in de novo transcriptome assembly and assembly-based structural variant calling technologies (RNA-Bloom and PAVFinder, respectively). We benchmarked Fusion-Bloom against the performance of five other state-of-the-art fusion detection tools using multiple datasets. Overall, we observed Fusion-Bloom to display a good balance between detection sensitivity and specificity. We expect the tool to find applications in translational research and clinical genomics pipelines. Availability and implementation Fusion-Bloom is implemented as a UNIX Make utility, available at https://github.com/bcgsc/pavfinder and released under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Readman Chiu
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada
| | - Ka Ming Nip
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada.,Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC V6H 3N1, Canada
| | - Inanc Birol
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada
| |
Collapse
|
16
|
Liao D, Zhong L, Yin J, Zeng C, Wang X, Huang X, Chen J, Zhang H, Zhang R, Guan XY, Shuai X, Sui J, Gao S, Deng W, Zeng YX, Shen JN, Chen J, Kang T. Chromosomal translocation-derived aberrant Rab22a drives metastasis of osteosarcoma. Nat Cell Biol 2020; 22:868-881. [PMID: 32483387 DOI: 10.1038/s41556-020-0522-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 04/16/2020] [Indexed: 01/04/2023]
Abstract
Osteosarcoma is a type of aggressive malignant bone tumour that frequently metastasizes to lungs, resulting in poor prognosis. However, the molecular mechanisms of lung metastasis of osteosarcoma remain poorly understood. Here we identify exon-intron fusion genes in osteosarcoma cell lines and tissues. These fusion genes are derived from chromosomal translocations that juxtapose the coding region for amino acids 1-38 of Rab22a (Rab22a1-38) with multiple inverted introns and untranslated regions of chromosome 20. The resulting translation products, designated Rab22a-NeoFs, acquire the ability to drive lung metastasis of osteosarcoma. The Rab22a1-38 moiety governs the function of Rab22a-NeoFs by binding to SmgGDS-607, a GTP-GDP exchange factor of RhoA. This association facilitates the release of GTP-bound RhoA from SmgGDS-607, which induces increased activity of RhoA and promotes metastasis. Disrupting the interaction between Rab22a-NeoF1 and SmgGDS-607 with a synthetic peptide prevents lung metastasis in an orthotopic model of osteosarcoma. Our findings may provide a promising strategy for a subset of osteosarcoma patients with lung metastases.
Collapse
Affiliation(s)
- Dan Liao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Li Zhong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Junqiang Yin
- Department of Musculoskeletal Oncology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Cuiling Zeng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xin Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | | | - Jinna Chen
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Hong Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Ruhua Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xin-Yuan Guan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
- Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Xintao Shuai
- School of Materials Science and Engineering, Sun Yat-sen University, Guangzhou, China
| | - Jianhua Sui
- National Institute of Biological Sciences, Beijing, China
| | - Song Gao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wuguo Deng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yi-Xin Zeng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jing-Nan Shen
- Department of Musculoskeletal Oncology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Jian Chen
- Institute of Functional Nano and Soft Materials (FUNSOM) and Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou, China.
| | - Tiebang Kang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
| |
Collapse
|
17
|
Qiu Y, Ma C, Xie H, Kingsford C. Detecting transcriptomic structural variants in heterogeneous contexts via the Multiple Compatible Arrangements Problem. Algorithms Mol Biol 2020; 15:9. [PMID: 32467720 PMCID: PMC7227063 DOI: 10.1186/s13015-020-00170-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 04/28/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Transcriptomic structural variants (TSVs)-large-scale transcriptome sequence change due to structural variation - are common in cancer. TSV detection from high-throughput sequencing data is a computationally challenging problem. Among all the confounding factors, sample heterogeneity, where each sample contains multiple distinct alleles, poses a critical obstacle to accurate TSV prediction. RESULTS To improve TSV detection in heterogeneous RNA-seq samples, we introduce the Multiple Compatible Arrangements Problem (MCAP), which seeks k genome arrangements that maximize the number of reads that are concordant with at least one arrangement. This models a heterogeneous or diploid sample. We prove that MCAP is NP-complete and provide a 1 4 -approximation algorithm for k = 1 and a 3 4 -approximation algorithm for the diploid case ( k = 2 ) assuming an oracle for k = 1 . Combining these, we obtain a 3 16 -approximation algorithm for MCAP when k = 2 (without an oracle). We also present an integer linear programming formulation for general k. We characterize the conflict structures in the graph that require k > 1 alleles to satisfy read concordancy and show that such structures are prevalent. CONCLUSIONS We show that the solution to MCAP accurately addresses sample heterogeneity during TSV detection. Our algorithms have improved performance on TCGA cancer samples and cancer cell line samples compared to a TSV calling tool, SQUID. The software is available at https://github.com/Kingsford-Group/diploidsquid.
Collapse
Affiliation(s)
- Yutong Qiu
- Computational Biology Department, Carnegie Mellon University, 5000 Forbes Ave, 15213 Pittsburgh, PA USA
| | - Cong Ma
- Computational Biology Department, Carnegie Mellon University, 5000 Forbes Ave, 15213 Pittsburgh, PA USA
| | - Han Xie
- Computational Biology Department, Carnegie Mellon University, 5000 Forbes Ave, 15213 Pittsburgh, PA USA
| | - Carl Kingsford
- Computational Biology Department, Carnegie Mellon University, 5000 Forbes Ave, 15213 Pittsburgh, PA USA
| |
Collapse
|
18
|
Balachandran P, Beck CR. Structural variant identification and characterization. Chromosome Res 2020; 28:31-47. [PMID: 31907725 PMCID: PMC7131885 DOI: 10.1007/s10577-019-09623-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 10/15/2019] [Accepted: 11/24/2019] [Indexed: 01/06/2023]
Abstract
Structural variant (SV) differences between human genomes can cause germline and mosaic disease as well as inter-individual variation. De-regulation of accurate DNA repair and genomic surveillance mechanisms results in a large number of SVs in cancer. Analysis of the DNA sequences at SV breakpoints can help identify pathways of mutagenesis and regions of the genome that are more susceptible to rearrangement. Large-scale SV analyses have been enabled by high-throughput genome-level sequencing on humans in the past decade. These studies have shed light on the mechanisms and prevalence of complex genomic rearrangements. Recent advancements in both sequencing and other mapping technologies as well as calling algorithms for detection of genomic rearrangements have helped propel SV detection into population-scale studies, and have begun to elucidate previously inaccessible regions of the genome. Here, we discuss the genomic organization of simple and complex SVs, the molecular mechanisms of their formation, and various ways to detect them. We also introduce methods for characterizing SVs and their consequences on human genomes.
Collapse
Affiliation(s)
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, 06030, USA.
| |
Collapse
|
19
|
Mahmoud M, Gobet N, Cruz-Dávalos DI, Mounier N, Dessimoz C, Sedlazeck FJ. Structural variant calling: the long and the short of it. Genome Biol 2019; 20:246. [PMID: 31747936 PMCID: PMC6868818 DOI: 10.1186/s13059-019-1828-7] [Citation(s) in RCA: 309] [Impact Index Per Article: 61.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 09/19/2019] [Indexed: 02/08/2023] Open
Abstract
Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution-giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, we review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.
Collapse
Affiliation(s)
- Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA
| | - Nastassia Gobet
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Diana Ivette Cruz-Dávalos
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Ninon Mounier
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Christophe Dessimoz
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution & Environment, University College London, London, UK.
- Department of Computer Science, University College London, London, UK.
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.
| |
Collapse
|
20
|
Chen CY, Chuang TJ. NCLcomparator: systematically post-screening non-co-linear transcripts (circular, trans-spliced, or fusion RNAs) identified from various detectors. BMC Bioinformatics 2019; 20:3. [PMID: 30606103 PMCID: PMC6318855 DOI: 10.1186/s12859-018-2589-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 12/21/2018] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Non-co-linear (NCL) transcripts consist of exonic sequences that are topologically inconsistent with the reference genome in an intragenic fashion (circular or intragenic trans-spliced RNAs) or in an intergenic fashion (fusion or intergenic trans-spliced RNAs). On the basis of RNA-seq data, numerous NCL event detectors have been developed and detected thousands of NCL events in diverse species. However, there are great discrepancies in the identification results among detectors, indicating a considerable proportion of false positives in the detected NCL events. Although several helpful guidelines for evaluating the performance of NCL event detectors have been provided, a systematic guideline for measurement of NCL events identified by existing tools has not been available. RESULTS We develop a software, NCLcomparator, for systematically post-screening the intragenic or intergenic NCL events identified by various NCL detectors. NCLcomparator first examine whether the input NCL events are potentially false positives derived from ambiguous alignments (i.e., the NCL events have an alternative co-linear explanation or multiple matches against the reference genome). To evaluate the reliability of the identified NCL events, we define the NCL score (NCLscore) based on the variation in the number of supporting NCL junction reads identified by the tools examined. Of the input NCL events, we show that the ambiguous alignment-derived events have relatively lower NCLscore values than the other events, indicating that an NCL event with a higher NCLscore has a higher level of reliability. To help selecting highly expressed NCL events, NCLcomparator also provides a series of useful measurements such as the expression levels of the detected NCL events and their corresponding host genes and the junction usage of the co-linear splice junctions at both NCL donor and acceptor sites. CONCLUSION NCLcomparator provides useful guidelines, with the input of identified NCL events from various detectors and the corresponding paired-end RNA-seq data only, to help users selecting potentially high-confidence NCL events for further functional investigation. The software thus helps to facilitate future studies into NCL events, shedding light on the fundamental biology of this important but understudied class of transcripts. NCLcomparator is freely accessible at https://github.com/TreesLab/NCLcomparator .
Collapse
Affiliation(s)
- Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, 11529 Taiwan
| | | |
Collapse
|