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Gomez F, Fisk B, McMichael JF, Mosior M, Foltz JA, Skidmore ZL, Duncavage EJ, Miller CA, Abel H, Li YS, Russler-Germain DA, Krysiak K, Watkins MP, Ramirez CA, Schmidt A, Martins Rodrigues F, Trani L, Khanna A, Wagner JA, Fulton RS, Fronick CC, O'Laughlin MD, Schappe T, Cashen AF, Mehta-Shah N, Kahl BS, Walker J, Bartlett NL, Griffith M, Fehniger TA, Griffith OL. Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma. CANCER RESEARCH COMMUNICATIONS 2023; 3:2312-2330. [PMID: 37910143 PMCID: PMC10648575 DOI: 10.1158/2767-9764.crc-23-0140] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/27/2023] [Accepted: 10/24/2023] [Indexed: 11/03/2023]
Abstract
The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL. SIGNIFICANCE Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.
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Affiliation(s)
- Felicia Gomez
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri
| | - Bryan Fisk
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Joshua F. McMichael
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Matthew Mosior
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Jennifer A. Foltz
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Zachary L. Skidmore
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Eric J. Duncavage
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, Missouri
| | - Christopher A. Miller
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Haley Abel
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Yi-Shan Li
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, Missouri
| | - David A. Russler-Germain
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Kilannin Krysiak
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, Missouri
| | - Marcus P. Watkins
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Cody A. Ramirez
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Alina Schmidt
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Fernanda Martins Rodrigues
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Lee Trani
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Ajay Khanna
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Julia A. Wagner
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Robert S. Fulton
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Catrina C. Fronick
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Michelle D. O'Laughlin
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Timothy Schappe
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Amanda F. Cashen
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Neha Mehta-Shah
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Brad S. Kahl
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Jason Walker
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
| | - Nancy L. Bartlett
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
| | - Malachi Griffith
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri
- Department of Genetics, Washington University School of Medicine, St Louis, Missouri
| | - Todd A. Fehniger
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri
| | - Obi L. Griffith
- Department of Medicine, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- McDonnell Genome Institute, Department of Medicine, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, Washington University School of Medicine, St Louis, Missouri
- Department of Genetics, Washington University School of Medicine, St Louis, Missouri
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Bracht JWP, Mayo-de-Las-Casas C, Berenguer J, Karachaliou N, Rosell R. The Present and Future of Liquid Biopsies in Non-Small Cell Lung Cancer: Combining Four Biosources for Diagnosis, Prognosis, Prediction, and Disease Monitoring. Curr Oncol Rep 2018; 20:70. [PMID: 30030656 DOI: 10.1007/s11912-018-0720-z] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE OF REVIEW Liquid biopsies have potential as tools for diagnosis, prognosis, and prediction of response to therapy. Herein, we will extensively review four liquid biosources, tumor-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumor cells (CTCs), and extracellular vesicles (EVs) and we will clarify their optimal application in non-small cell lung cancer (NSCLC) diagnosis and therapy. RECENT FINDINGS Liquid biopsies are a minimally invasive alternative to tissue biopsies-especially important in NSCLC patients-since tumor tissue is often unavailable or insufficient for complete genetic analysis. The main advantages of liquid biopsies include the possibility for repeated sampling, the lower cost, and the fact that they can reflect the complete molecular status of the patient better than a single-site biopsy. This is specifically important for lung adenocarcinoma patients since the detection of specific genetic alterations can predict response to targeted therapies. Molecular analysis is currently cardinal for therapy decision-making and disease monitoring in lung cancer patients. Liquid biopsies can make easier our daily clinical practice and if prospectively tested and validated may serve as a means for lung cancer early detection.
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Affiliation(s)
| | - Clara Mayo-de-Las-Casas
- Pangaea Oncology, Laboratory of Molecular Biology, Quirón-Dexeus University Institute, Sabino Arana 5-19, 08028, Barcelona, Spain
| | - Jordi Berenguer
- Pangaea Oncology, Laboratory of Molecular Biology, Quirón-Dexeus University Institute, Sabino Arana 5-19, 08028, Barcelona, Spain
| | - Niki Karachaliou
- Pangaea Oncology, Laboratory of Molecular Biology, Quirón-Dexeus University Institute, Sabino Arana 5-19, 08028, Barcelona, Spain. .,Instituto Oncológico Dr Rosell (IOR), University Hospital Sagrat Cor, QuironSalud Group, Viladomat 288, 08029, Barcelona, Spain.
| | - Rafael Rosell
- Pangaea Oncology, Laboratory of Molecular Biology, Quirón-Dexeus University Institute, Sabino Arana 5-19, 08028, Barcelona, Spain. .,Institut Català d'Oncologia, Hospital Germans Trias i Pujol, Carretera de Canyet, s/n, 08916, Badalona, Barcelona, Spain. .,Institut d'Investigació en Ciències Germans Trias i Pujol, Camí de les Escoles, s/n, 08916, Badalona, Barcelona, Spain. .,Instituto Oncológico Dr Rosell (IOR), Quirón-Dexeus University Institute, Sabino Arana 5-19, 08028, Barcelona, Spain.
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Stasik S, Schuster C, Ortlepp C, Platzbecker U, Bornhäuser M, Schetelig J, Ehninger G, Folprecht G, Thiede C. An optimized targeted Next-Generation Sequencing approach for sensitive detection of single nucleotide variants. BIOMOLECULAR DETECTION AND QUANTIFICATION 2018; 15:6-12. [PMID: 29349042 PMCID: PMC5766748 DOI: 10.1016/j.bdq.2017.12.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Revised: 11/27/2017] [Accepted: 12/18/2017] [Indexed: 01/06/2023]
Abstract
NGS based detection of low-level SNVs is feasible with sensitivities up to 10−4. PCR-induced bias could be significantly reduced by the choice of adequate enzymes. The prevalent transition vs. transversion bias affects site-specific detection limits. Results from clinical data validated the feasibility of NGS-based MRD detection. Results help to select suitable biomarkers for MRD quantification.
Monitoring of minimal residual disease (MRD) has become an important clinical aspect for early relapse detection during follow-up care after cancer treatment. Still, the sensitive detection of single base pair point mutations via Next-Generation Sequencing (NGS) is hampered mainly due to high substitution error rates. We evaluated the use of NGS for the detection of low-level variants on an Ion Torrent PGM system. As a model case we used the c.1849G > T (p.Val617Phe) mutation of the JAK2-gene. Several reaction parameters (e.g. choice of DNA-polymerase) were evaluated and a comprehensive analysis of substitution errors was performed. Using optimized conditions, we reliably detected JAK2 c.1849G > T VAFs in the range of 0.01–0.0015% which, in combination with results obtained from clinical data, validated the feasibility of NGS-based MRD detection. Particularly, PCR-induced transitions (mainly G > A and C > T) were the major source of error, which could be significantly reduced by the application of proofreading enzymes. The integration of NGS results for several common point mutations in various oncogenes (i.e. IDH1 and 2, c-KIT, DNMT3A, NRAS, KRAS, BRAF) revealed that the prevalent transition vs. transversion bias (3.57:1) has an impact on site-specific detection limits of low-level mutations. These results may help to select suitable markers for MRD detection and to identify individual cut-offs for detection and quantification.
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Affiliation(s)
- S. Stasik
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
- National Center for Tumor Diseases (NCT), Heidelberg, Partner Site Dresden, Germany
| | | | | | - U. Platzbecker
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
| | - M. Bornhäuser
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
- National Center for Tumor Diseases (NCT), Heidelberg, Partner Site Dresden, Germany
| | - J. Schetelig
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
| | - G. Ehninger
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
| | - G. Folprecht
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
| | - C. Thiede
- Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Dresden, Germany
- Corresponding author: Universitätsklinikum Carl Gustav Carus, Medizinische Klinik und Poliklinik I, Fetscherstraße 74, 01307 Dresden, Germany.
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Pongor L, Harami-Papp H, Méhes E, Czirók A, Győrffy B. Cell Dispersal Influences Tumor Heterogeneity and Introduces a Bias in NGS Data Interpretation. Sci Rep 2017; 7:7358. [PMID: 28779157 PMCID: PMC5544774 DOI: 10.1038/s41598-017-07487-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 06/27/2017] [Indexed: 01/09/2023] Open
Abstract
Short and long distance cell dispersal can have a marked effect on tumor structure, high cellular motility could lead to faster cell mixing and lower observable intratumor heterogeneity. Here we evaluated a model for cell mixing that investigates how short-range dispersal and cell turnover will account for mutational proportions. We show that cancer cells can penetrate neighboring and distinct areas in a matter of days. In next generation sequencing runs, higher proportions of a given cell line generated frequencies with higher precision, while mixtures with lower amounts of each cell line had lower precision manifesting in higher standard deviations. When multiple cell lines were co-cultured, cellular movement altered observed mutation frequency by up to 18.5%. We propose that some of the shared mutations detected at low allele frequencies represent highly motile clones that appear in multiple regions of a tumor owing to dispersion throughout the tumor. In brief, cell movement will lead to a significant technical (sampling) bias when using next generation sequencing to determine clonal composition. A possible solution to this drawback would be to radically decrease detection thresholds and increase coverage in NGS analyses.
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Affiliation(s)
- Lőrinc Pongor
- MTA TTK Lendület Cancer Biomarker Research Group, Institute of Enzymology, Budapest, Hungary.,Semmelweis University 2nd Department of Pediatrics, Budapest, Hungary
| | - Hajnalka Harami-Papp
- MTA TTK Lendület Cancer Biomarker Research Group, Institute of Enzymology, Budapest, Hungary.,Semmelweis University 2nd Department of Pediatrics, Budapest, Hungary
| | - Előd Méhes
- Department of Biological Physics, Eötvös Loránd University, Budapest, Hungary
| | - András Czirók
- Department of Biological Physics, Eötvös Loránd University, Budapest, Hungary.,Department of Anatomy and Cell Biology, University of Kansas Medical Center, Kansas, USA
| | - Balázs Győrffy
- MTA TTK Lendület Cancer Biomarker Research Group, Institute of Enzymology, Budapest, Hungary. .,Semmelweis University 2nd Department of Pediatrics, Budapest, Hungary.
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Köhn L, Johansson M, Grankvist K, Nilsson J. Liquid biopsies in lung cancer-time to implement research technologies in routine care? ANNALS OF TRANSLATIONAL MEDICINE 2017; 5:278. [PMID: 28758104 DOI: 10.21037/atm.2017.04.12] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Lung cancer is the leading cause of cancer mortality. A substantial progress in the understanding of lung cancer biology has resulted in several promising targeted therapies for advanced disease. Druggable targets today include point mutations such as EGFR, BRAF and re-arrangements in genes such as ALK and ROS1. Liquid biopsies collecting e.g., circulating tumor DNA (ctDNA) reflects overall tumor information and is not biased by analyzing of only a small fraction of the tumor and is always accessible in contrast to the lung cancer tissue. Technological advances in detection of low frequency mutation variants in ctDNA have made it the dominating liquid biopsy platform in terms of utility and sensitivity. Circulating DNA or RNA may possible be used to define populations with higher risk of developing lung cancer, thus reducing screening cohorts and increasing the positive predictive value of screening. Blood based-tests may also aid to identify genetic alterations several weeks prior to radiologically verified recurrence and may be of great value in the follow-up of lung cancer patients. Besides being an alternative to invasive biopsies in selected cases, liquid biopsies offer a unique possibility to monitor treatment response following medical treatment as well as treatment response and resistance development after targeted therapy, giving a possibility to modify the treatment after the genetic profile of the tumor. Ideally, genetic alterations found in ctDNA could be tracked in real-time discriminating between fast-growing life-threatening tumors from more indolent slow growing tumors or premalignant growth that are of no concern for the wellbeing of the patient. This review focuses on future perspectives of liquid biopsies in lung cancer care for different clinical settings and present current technological platforms for further discussion of possible strategies for implementation of liquid biopsies in lung cancer.
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Affiliation(s)
- Linda Köhn
- Department of Radiation Sciences, Oncology, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - Jonas Nilsson
- Department of Radiation Sciences, Oncology, Clinical Chemistry, Umeå University, Umeå, Sweden
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