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Widman AJ, Shah M, Frydendahl A, Halmos D, Khamnei CC, Øgaard N, Rajagopalan S, Arora A, Deshpande A, Hooper WF, Quentin J, Bass J, Zhang M, Langanay T, Andersen L, Steinsnyder Z, Liao W, Rasmussen MH, Henriksen TV, Jensen SØ, Nors J, Therkildsen C, Sotelo J, Brand R, Schiffman JS, Shah RH, Cheng AP, Maher C, Spain L, Krause K, Frederick DT, den Brok W, Lohrisch C, Shenkier T, Simmons C, Villa D, Mungall AJ, Moore R, Zaikova E, Cerda V, Kong E, Lai D, Malbari MS, Marton M, Manaa D, Winterkorn L, Gelmon K, Callahan MK, Boland G, Potenski C, Wolchok JD, Saxena A, Turajlic S, Imielinski M, Berger MF, Aparicio S, Altorki NK, Postow MA, Robine N, Andersen CL, Landau DA. Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment. Nat Med 2024:10.1038/s41591-024-03040-4. [PMID: 38877116 DOI: 10.1038/s41591-024-03040-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 04/30/2024] [Indexed: 06/16/2024]
Abstract
In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.
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Affiliation(s)
- Adam J Widman
- New York Genome Center, New York, NY, USA.
- Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | | | - Amanda Frydendahl
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Daniel Halmos
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Cole C Khamnei
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Nadia Øgaard
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Srinivas Rajagopalan
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Anushri Arora
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Aditya Deshpande
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | | | - Jean Quentin
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jake Bass
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Mingxuan Zhang
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Theophile Langanay
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Laura Andersen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | | | - Will Liao
- New York Genome Center, New York, NY, USA
| | - Mads Heilskov Rasmussen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Tenna Vesterman Henriksen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Sarah Østrup Jensen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Jesper Nors
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Christina Therkildsen
- Gastro Unit, Copenhagen University Hospital, Amager - Hvidovre Hospital, Hvidovre, Denmark
| | - Jesus Sotelo
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Ryan Brand
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Joshua S Schiffman
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Ronak H Shah
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Colleen Maher
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
| | - Lavinia Spain
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
- Renal and Skin Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Kate Krause
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Dennie T Frederick
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Wendie den Brok
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Caroline Lohrisch
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Tamara Shenkier
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Christine Simmons
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Diego Villa
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Andrew J Mungall
- Michael Smith Genome Sciences Centre, Vancouver, British Columbia, Canada
| | - Richard Moore
- Michael Smith Genome Sciences Centre, Vancouver, British Columbia, Canada
| | - Elena Zaikova
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Viviana Cerda
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Esther Kong
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Daniel Lai
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | | | | | - Dina Manaa
- New York Genome Center, New York, NY, USA
| | | | - Karen Gelmon
- Department of Medical Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
| | | | - Genevieve Boland
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA, USA
| | - Catherine Potenski
- New York Genome Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Jedd D Wolchok
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Samra Turajlic
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
- Renal and Skin Unit, The Royal Marsden NHS Foundation Trust, London, UK
| | - Marcin Imielinski
- New York Genome Center, New York, NY, USA
- Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | | | - Sam Aparicio
- Department of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Michael A Postow
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | | | - Claus Lindbjerg Andersen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Dan A Landau
- New York Genome Center, New York, NY, USA.
- Weill Cornell Medicine, New York, NY, USA.
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2
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Wang P, Lin J, Zheng X, Xu X. RNase P: Beyond Precursor tRNA Processing. GENOMICS, PROTEOMICS & BIOINFORMATICS 2024; 22:qzae016. [PMID: 38862431 DOI: 10.1093/gpbjnl/qzae016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 09/18/2023] [Accepted: 10/11/2023] [Indexed: 06/13/2024]
Abstract
Ribonuclease P (RNase P) was first described in the 1970's as an endoribonuclease acting in the maturation of precursor transfer RNAs (tRNAs). More recent studies, however, have uncovered non-canonical roles for RNase P and its components. Here, we review the recent progress of its involvement in chromatin assembly, DNA damage response, and maintenance of genome stability with implications in tumorigenesis. The possibility of RNase P as a therapeutic target in cancer is also discussed.
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Affiliation(s)
- Peipei Wang
- Guangdong Key Laboratory for Genome Stability & Disease Prevention and Marshall Laboratory of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
| | - Juntao Lin
- Guangdong Key Laboratory for Genome Stability & Disease Prevention and Marshall Laboratory of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
- Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China
| | - Xiangyang Zheng
- Shenzhen University General Hospital-Dehua Hospital Joint Research Center on Precision Medicine, Dehua Hospital, Dehua 362500, China
| | - Xingzhi Xu
- Guangdong Key Laboratory for Genome Stability & Disease Prevention and Marshall Laboratory of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518060, China
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3
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Rückert T, Romagnani C. Extrinsic and intrinsic drivers of natural killer cell clonality. Immunol Rev 2024; 323:80-106. [PMID: 38506411 DOI: 10.1111/imr.13324] [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] [Indexed: 03/21/2024]
Abstract
Clonal expansion of antigen-specific lymphocytes is the fundamental mechanism enabling potent adaptive immune responses and the generation of immune memory. Accompanied by pronounced epigenetic remodeling, the massive proliferation of individual cells generates a critical mass of effectors for the control of acute infections, as well as a pool of memory cells protecting against future pathogen encounters. Classically associated with the adaptive immune system, recent work has demonstrated that innate immune memory to human cytomegalovirus (CMV) infection is stably maintained as large clonal expansions of natural killer (NK) cells, raising questions on the mechanisms for clonal selection and expansion in the absence of re-arranged antigen receptors. Here, we discuss clonal NK cell memory in the context of the mechanisms underlying clonal competition of adaptive lymphocytes and propose alternative selection mechanisms that might decide on the clonal success of their innate counterparts. We propose that the integration of external cues with cell-intrinsic sources of heterogeneity, such as variegated receptor expression, transcriptional states, and somatic variants, compose a bottleneck for clonal selection, contributing to the large size of memory NK cell clones.
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Affiliation(s)
- Timo Rückert
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Immunology, Berlin, Germany
| | - Chiara Romagnani
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Immunology, Berlin, Germany
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Selvam K, Wyrick JJ, Parra MA. DNA Repair in Nucleosomes: Insights from Histone Modifications and Mutants. Int J Mol Sci 2024; 25:4393. [PMID: 38673978 PMCID: PMC11050016 DOI: 10.3390/ijms25084393] [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: 02/17/2024] [Revised: 04/08/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
DNA repair pathways play a critical role in genome stability, but in eukaryotic cells, they must operate to repair DNA lesions in the compact and tangled environment of chromatin. Previous studies have shown that the packaging of DNA into nucleosomes, which form the basic building block of chromatin, has a profound impact on DNA repair. In this review, we discuss the principles and mechanisms governing DNA repair in chromatin. We focus on the role of histone post-translational modifications (PTMs) in repair, as well as the molecular mechanisms by which histone mutants affect cellular sensitivity to DNA damage agents and repair activity in chromatin. Importantly, these mechanisms are thought to significantly impact somatic mutation rates in human cancers and potentially contribute to carcinogenesis and other human diseases. For example, a number of the histone mutants studied primarily in yeast have been identified as candidate oncohistone mutations in different cancers. This review highlights these connections and discusses the potential importance of DNA repair in chromatin to human health.
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Affiliation(s)
- Kathiresan Selvam
- School of Molecular Biosciences, Washington State University, Pullman, WA 99164, USA
| | - John J. Wyrick
- School of Molecular Biosciences, Washington State University, Pullman, WA 99164, USA
| | - Michael A. Parra
- Department of Chemistry, Susquehanna University, Selinsgrove, PA 17870, USA
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5
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Serafim RB, Cardoso C, Storti CB, da Silva P, Qi H, Parasuram R, Navegante G, Peron JPS, Silva WA, Espreafico EM, Paçó-Larson ML, Price BD, Valente V. HJURP is recruited to double-strand break sites and facilitates DNA repair by promoting chromatin reorganization. Oncogene 2024; 43:804-820. [PMID: 38279062 DOI: 10.1038/s41388-024-02937-1] [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: 03/15/2023] [Revised: 12/21/2023] [Accepted: 01/04/2024] [Indexed: 01/28/2024]
Abstract
HJURP is overexpressed in several cancer types and strongly correlates with patient survival. However, the mechanistic basis underlying the association of HJURP with cancer aggressiveness is not well understood. HJURP promotes the loading of the histone H3 variant, CENP-A, at the centromeric chromatin, epigenetically defining the centromeres and supporting proper chromosome segregation. In addition, HJURP is associated with DNA repair but its function in this process is still scarcely explored. Here, we demonstrate that HJURP is recruited to DSBs through a mechanism requiring chromatin PARylation and promotes epigenetic alterations that favor the execution of DNA repair. Incorporation of HJURP at DSBs promotes turnover of H3K9me3 and HP1, facilitating DNA damage signaling and DSB repair. Moreover, HJURP overexpression in glioma cell lines also affected global structure of heterochromatin independently of DNA damage induction, promoting genome-wide reorganization and assisting DNA damage response. HJURP overexpression therefore extensively alters DNA damage signaling and DSB repair, and also increases radioresistance of glioma cells. Importantly, HJURP expression levels in tumors are also associated with poor response of patients to radiation. Thus, our results enlarge the understanding of HJURP involvement in DNA repair and highlight it as a promising target for the development of adjuvant therapies that sensitize tumor cells to irradiation.
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Affiliation(s)
- Rodolfo B Serafim
- Department of Cellular and Molecular Biology, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
- São Paulo State University (UNESP), School of Pharmaceutical Sciences, Rodovia Araraquara - Jaú, Km 01 - s/n, Campos Ville, Araraquara, SP, 14800-903, Brazil
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Center for Cell-Based Therapy-CEPID/FAPESP, Rua Tenente Catão Roxo, 2501, Ribeirão Preto, 14051-140, Brazil
| | - Cibele Cardoso
- Department of Cellular and Molecular Biology, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
- Center for Cell-Based Therapy-CEPID/FAPESP, Rua Tenente Catão Roxo, 2501, Ribeirão Preto, 14051-140, Brazil
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
| | - Camila B Storti
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
| | - Patrick da Silva
- Department of Immunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Hongyun Qi
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Ramya Parasuram
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Geovana Navegante
- São Paulo State University (UNESP), School of Pharmaceutical Sciences, Rodovia Araraquara - Jaú, Km 01 - s/n, Campos Ville, Araraquara, SP, 14800-903, Brazil
| | - Jean Pierre S Peron
- Department of Immunology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Wilson A Silva
- Center for Cell-Based Therapy-CEPID/FAPESP, Rua Tenente Catão Roxo, 2501, Ribeirão Preto, 14051-140, Brazil
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
| | - Enilza M Espreafico
- Department of Cellular and Molecular Biology, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
| | - Maria L Paçó-Larson
- Department of Cellular and Molecular Biology, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil
| | - Brendan D Price
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
| | - Valeria Valente
- Department of Cellular and Molecular Biology, Ribeirão Preto Medical School, University of São Paulo (USP), Avenida Bandeirantes, 3900, Ribeirão Preto, 14049-900, Brazil.
- São Paulo State University (UNESP), School of Pharmaceutical Sciences, Rodovia Araraquara - Jaú, Km 01 - s/n, Campos Ville, Araraquara, SP, 14800-903, Brazil.
- Center for Cell-Based Therapy-CEPID/FAPESP, Rua Tenente Catão Roxo, 2501, Ribeirão Preto, 14051-140, Brazil.
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Morledge-Hampton B, Kalyanaraman A, Wyrick JJ. Analysis of cytosine deamination events in excision repair sequencing reads reveals mechanisms of incision site selection in NER. Nucleic Acids Res 2024; 52:1720-1735. [PMID: 38109317 PMCID: PMC10899786 DOI: 10.1093/nar/gkad1195] [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: 05/17/2023] [Revised: 11/28/2023] [Accepted: 12/01/2023] [Indexed: 12/20/2023] Open
Abstract
Nucleotide excision repair (NER) removes helix-distorting DNA lesions and is therefore critical for genome stability. During NER, DNA is unwound on either side of the lesion and excised, but the rules governing incision site selection, particularly in eukaryotic cells, are unclear. Excision repair-sequencing (XR-seq) sequences excised NER fragments, but analysis has been limited because the lesion location is unknown. Here, we exploit accelerated cytosine deamination rates in UV-induced CPD (cyclobutane pyrimidine dimer) lesions to precisely map their locations at C to T mismatches in XR-seq reads, revealing general and species-specific patterns of incision site selection during NER. Our data indicate that the 5' incision site occurs preferentially in HYV (i.e. not G; C/T; not T) sequence motifs, a pattern that can be explained by sequence preferences of the XPF-ERCC1 endonuclease. In contrast, the 3' incision site does not show strong sequence preferences, once truncated reads arising from mispriming events are excluded. Instead, the 3' incision is partially determined by the 5' incision site distance, indicating that the two incision events are coupled. Finally, our data reveal unique and coupled NER incision patterns at nucleosome boundaries. These findings reveal key principles governing NER incision site selection in eukaryotic cells.
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Affiliation(s)
| | - Ananth Kalyanaraman
- School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA
| | - John J Wyrick
- School of Molecular Biosciences, Washington State University, Pullman, WA 99164, USA
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7
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Waneka G, Pate B, Monroe JG, Sloan DB. Investigating low frequency somatic mutations in Arabidopsis with Duplex Sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578196. [PMID: 38352550 PMCID: PMC10862904 DOI: 10.1101/2024.01.31.578196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Mutations are the source of novel genetic diversity but can also lead to disease and maladaptation. The conventional view is that mutations occur randomly with respect to their environment-specific fitness consequences. However, intragenomic mutation rates can vary dramatically due to transcription coupled repair and based on local epigenomic modifications, which are non-uniformly distributed across genomes. One sequence feature associated with decreased mutation is higher expression level, which can vary depending on environmental cues. To understand whether the association between expression level and mutation rate creates a systematic relationship with environment-specific fitness effects, we perturbed expression through a heat treatment in Arabidopsis thaliana. We quantified gene expression to identify differentially expressed genes, which we then targeted for mutation detection using Duplex Sequencing. This approach provided a highly accurate measurement of the frequency of rare somatic mutations in vegetative plant tissues, which has been a recent source of uncertainty in plant mutation research. We included mutant lines lacking mismatch repair (MMR) and base excision repair (BER) capabilities to understand how repair mechanisms may drive biased mutation accumulation. We found wild type (WT) and BER mutant mutation frequencies to be very low (mean variant frequency 1.8×10-8 and 2.6×10-8, respectively), while MMR mutant frequencies were significantly elevated (1.13×10-6). These results show that somatic variant frequencies are extremely low in WT plants, indicating that larger datasets will be needed to address the fundamental evolutionary question as to whether environmental change leads to gene-specific changes in mutation rate.
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Affiliation(s)
- Gus Waneka
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
| | - Braden Pate
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
| | - J Grey Monroe
- Department of Plant Sciences, University of California, Davis, Davis, CA USA
| | - Daniel B Sloan
- Department of Biology, Colorado State University, Fort Collins, Colorado, USA
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8
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Ciriello G, Magnani L, Aitken SJ, Akkari L, Behjati S, Hanahan D, Landau DA, Lopez-Bigas N, Lupiáñez DG, Marine JC, Martin-Villalba A, Natoli G, Obenauf AC, Oricchio E, Scaffidi P, Sottoriva A, Swarbrick A, Tonon G, Vanharanta S, Zuber J. Cancer Evolution: A Multifaceted Affair. Cancer Discov 2024; 14:36-48. [PMID: 38047596 PMCID: PMC10784746 DOI: 10.1158/2159-8290.cd-23-0530] [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: 05/04/2023] [Revised: 08/29/2023] [Accepted: 10/23/2023] [Indexed: 12/05/2023]
Abstract
Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery. SIGNIFICANCE Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.
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Affiliation(s)
- Giovanni Ciriello
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Luca Magnani
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
- Breast Epigenetic Plasticity and Evolution Laboratory, Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Sarah J. Aitken
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, United Kingdom
- Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Leila Akkari
- Division of Tumor Biology and Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sam Behjati
- Wellcome Sanger Institute, Hinxton, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Douglas Hanahan
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, Lausanne, Switzerland
| | - Dan A. Landau
- New York Genome Center, New York, New York
- Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, New York
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Darío G. Lupiáñez
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Jean-Christophe Marine
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KULeuven, Leuven, Belgium
| | - Ana Martin-Villalba
- Department of Molecular Neurobiology, German Cancer Research Center (DFKZ), Heidelberg, Germany
| | - Gioacchino Natoli
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
| | - Anna C. Obenauf
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
| | - Elisa Oricchio
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
| | - Paola Scaffidi
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
- Cancer Epigenetic Laboratory, The Francis Crick Institute, London, United Kingdom
| | - Andrea Sottoriva
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
| | - Giovanni Tonon
- Vita-Salute San Raffaele University, Milan, Italy
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sakari Vanharanta
- Translational Cancer Medicine Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johannes Zuber
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
- Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria
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9
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Otlu B, Alexandrov LB. Evaluating topography of mutational signatures with SigProfilerTopography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.08.574683. [PMID: 38260507 PMCID: PMC10802511 DOI: 10.1101/2024.01.08.574683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.
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Affiliation(s)
- Burçak Otlu
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, 92093, USA
- Department of Bioengineering, UC San Diego, La Jolla, CA, 92093, USA
- Moores Cancer Center, UC San Diego, La Jolla, CA, 92037, USA
- Department of Health Informatics, Graduate School of Informatics, Middle East Technical University, 06800, Ankara, Turkey
| | - Ludmil B. Alexandrov
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, 92093, USA
- Department of Bioengineering, UC San Diego, La Jolla, CA, 92093, USA
- Moores Cancer Center, UC San Diego, La Jolla, CA, 92037, USA
- Sanford Stem Cell Institute, University of California San Diego, La Jolla, CA 92037
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10
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Arnedo-Pac C, Muiños F, Gonzalez-Perez A, Lopez-Bigas N. Hotspot propensity across mutational processes. Mol Syst Biol 2024; 20:6-27. [PMID: 38177930 PMCID: PMC10883281 DOI: 10.1038/s44320-023-00001-w] [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: 10/05/2023] [Revised: 10/30/2023] [Accepted: 11/09/2023] [Indexed: 01/06/2024] Open
Abstract
The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5-78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94-95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80-100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.
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Affiliation(s)
- Claudia Arnedo-Pac
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| | - Ferran Muiños
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| | - Abel Gonzalez-Perez
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain.
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
- Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra (UPF), Barcelona, Spain.
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11
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Kenchanmane Raju SK, Lensink M, Kliebenstein DJ, Niederhuth C, Monroe G. Epigenomic divergence correlates with sequence polymorphism in Arabidopsis paralogs. THE NEW PHYTOLOGIST 2023; 240:1292-1304. [PMID: 37614211 DOI: 10.1111/nph.19227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/26/2023] [Indexed: 08/25/2023]
Abstract
Processes affecting rates of sequence polymorphism are fundamental to the evolution of gene duplicates. The relationship between gene activity and sequence polymorphism can influence the likelihood that functionally redundant gene copies are co-maintained in stable evolutionary equilibria vs other outcomes such as neofunctionalization. Here, we investigate genic variation in epigenome-associated polymorphism rates in Arabidopsis thaliana and consider whether these affect the evolution of gene duplicates. We compared the frequency of sequence polymorphism and patterns of genetic differentiation between genes classified by exon methylation patterns: unmethylated (unM), gene-body methylated (gbM), and transposon-like methylated (teM) states, which reflect divergence in gene expression. We found that the frequency of polymorphism was higher in teM (transcriptionally repressed, tissue-specific) genes and lower in gbM (active, constitutively expressed) genes. Comparisons of gene duplicates were largely consistent with genome-wide patterns - gene copies that exhibit teM accumulate more variation, evolve faster, and are in chromatin states associated with reduced DNA repair. This relationship between expression, the epigenome, and polymorphism may lead to the breakdown of equilibrium states that would otherwise maintain genetic redundancies. Epigenome-mediated polymorphism rate variation may facilitate the evolution of novel gene functions in duplicate paralogs maintained over evolutionary time.
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Affiliation(s)
| | - Mariele Lensink
- Department of Plant Sciences, University of California, Davis, CA, 95616, USA
| | | | - Chad Niederhuth
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
- AgBioResearch, Michigan State University, East Lansing, MI, 48824, USA
| | - Grey Monroe
- Department of Plant Sciences, University of California, Davis, CA, 95616, USA
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12
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Mu Q, Chai R, Pang B, Yang Y, Liu H, Zhao Z, Bao Z, Song D, Zhu Z, Yan M, Jiang B, Mo Z, Tang J, Sa JK, Cho HJ, Chang Y, Chan KHY, Loi DSC, Tam SST, Chan AKY, Wu AR, Liu Z, Poon WS, Ng HK, Chan DTM, Iavarone A, Nam DH, Jiang T, Wang J. Identifying predictors of glioma evolution from longitudinal sequencing. Sci Transl Med 2023; 15:eadh4181. [PMID: 37792958 DOI: 10.1126/scitranslmed.adh4181] [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: 03/26/2023] [Accepted: 09/01/2023] [Indexed: 10/06/2023]
Abstract
Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.
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Affiliation(s)
- Quanhua Mu
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
- SIAT-HKUST Joint Laboratory of Cell Evolution and Digital Health, Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen, Guangdong 518045, China
| | - Ruichao Chai
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Bo Pang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yingxi Yang
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Hanjie Liu
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Zheng Zhao
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Zhaoshi Bao
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Dong Song
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Zhihan Zhu
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Mengli Yan
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Biaobin Jiang
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Zongchao Mo
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Jihong Tang
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Jason K Sa
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul 02841, Korea
| | - Hee Jin Cho
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea
| | - Yuzhou Chang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Kaitlin Hao Yi Chan
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Danson Shek Chun Loi
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Sindy Sing Ting Tam
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Aden Ka Yin Chan
- Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong, SAR 999077, China
| | - Angela Ruohao Wu
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
| | - Zhaoqi Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Wai Sang Poon
- CUHK Otto Wong Brain Tumour Centre, Department of Surgery, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Ho Keung Ng
- Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong, SAR 999077, China
| | - Danny Tat Ming Chan
- CUHK Otto Wong Brain Tumour Centre, Department of Surgery, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Antonio Iavarone
- Department of Neurological Surgery, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Do-Hyun Nam
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea
- Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 110745, Korea
- Department of Health Science and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University School of Medicine, Seoul 110745, Korea
- Chinese Glioma Genome Atlas (CGGA) and Asian Glioma Genome Atlas (AGGA) Research Networks
| | - Tao Jiang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Chinese Glioma Genome Atlas (CGGA) and Asian Glioma Genome Atlas (AGGA) Research Networks
- Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors, Chinese Academy of Medical Sciences, Beijing 100070, China
| | - Jiguang Wang
- Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, SAR 999077, China
- SIAT-HKUST Joint Laboratory of Cell Evolution and Digital Health, Shenzhen-Hong Kong Collaborative Innovation Research Institute, Futian, Shenzhen, Guangdong 518045, China
- Chinese Glioma Genome Atlas (CGGA) and Asian Glioma Genome Atlas (AGGA) Research Networks
- Hong Kong Center for Neurodegenerative Diseases, InnoHK, Hong Kong, SAR 999077, China
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13
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Liu C, Wang Z, Wang J, Liu C, Wang M, Ngo V, Wang W. Predicting regional somatic mutation rates using DNA motifs. PLoS Comput Biol 2023; 19:e1011536. [PMID: 37782656 PMCID: PMC10569533 DOI: 10.1371/journal.pcbi.1011536] [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: 04/02/2023] [Revised: 10/12/2023] [Accepted: 09/20/2023] [Indexed: 10/04/2023] Open
Abstract
How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.
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Affiliation(s)
- Cong Liu
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America
| | - Zengmiao Wang
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Jun Wang
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America
| | - Chengyu Liu
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America
| | - Mengchi Wang
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, United States of America
| | - Vu Ngo
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, United States of America
| | - Wei Wang
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, United States of America
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, United States of America
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, California, United States of America
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14
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Middelkamp S, Manders F, Peci F, van Roosmalen MJ, González DM, Bertrums EJ, van der Werf I, Derks LL, Groenen NM, Verheul M, Trabut L, Pleguezuelos-Manzano C, Brandsma AM, Antoniou E, Reinhardt D, Bierings M, Belderbos ME, van Boxtel R. Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox. CELL GENOMICS 2023; 3:100389. [PMID: 37719152 PMCID: PMC10504672 DOI: 10.1016/j.xgen.2023.100389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 05/30/2023] [Accepted: 08/02/2023] [Indexed: 09/19/2023]
Abstract
Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.
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Affiliation(s)
- Sjors Middelkamp
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Freek Manders
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Flavia Peci
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Markus J. van Roosmalen
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Diego Montiel González
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Eline J.M. Bertrums
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
- Department of Pediatric Oncology, Erasmus Medical Center – Sophia Children’s Hospital, Rotterdam, the Netherlands
| | - Inge van der Werf
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Lucca L.M. Derks
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Niels M. Groenen
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Mark Verheul
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Laurianne Trabut
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Cayetano Pleguezuelos-Manzano
- Oncode Institute, Utrecht, the Netherlands
- Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences (KNAW) and UMC Utrecht, Utrecht, the Netherlands
| | - Arianne M. Brandsma
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Evangelia Antoniou
- Department of Pediatric Hematology and Oncology, University Hospital Essen, Essen, Germany
| | - Dirk Reinhardt
- Department of Pediatric Hematology and Oncology, University Hospital Essen, Essen, Germany
| | - Marc Bierings
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | | | - Ruben van Boxtel
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
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15
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Alhatim H, Abdullah MNH, Abu Bakar S, Amer SA. Effect of Carcinomas on Autosomal Trait Screening: A Review Article. Curr Issues Mol Biol 2023; 45:7275-7285. [PMID: 37754244 PMCID: PMC10529457 DOI: 10.3390/cimb45090460] [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: 07/29/2023] [Revised: 08/23/2023] [Accepted: 08/31/2023] [Indexed: 09/28/2023] Open
Abstract
This review highlights the effect of carcinomas on the results of the examination of autosomal genetic traits for identification and paternity tests when carcinoid tissue is the only source and no other samples are available. In DNA typing or genetic fingerprinting, variable elements are isolated and identified within the base pair sequences that form the DNA. The person's probable identity can be determined by analysing nucleotide sequences in particular regions of DNA unique to everyone. Genetics plays an increasingly important role in the risk stratification and management of carcinoma patients. The available information from previous studies has indicated that in some incidents, including mass disasters and crimes such as terrorist incidents, biological evidence may not be available at the scene of the accident, except for some unknown human remains found in the form of undefined human tissues. If these tissues have cancerous tumours, it may affect the examination of the genetic traits derived from these samples, thereby resulting in a failure to identify the person. Pathology units, more often, verify the identity of the patients who were diagnosed with cancer in reference to their deceased tumorous relatives. Genetic fingerprinting (GF) is also used in paternity testing when the alleged parent disappeared or died and earlier was diagnosed and treated for cancer.
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Affiliation(s)
- Husein Alhatim
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; (H.A.); (S.A.B.)
| | - Muhammad Nazrul Hakim Abdullah
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; (H.A.); (S.A.B.)
| | - Suhaili Abu Bakar
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; (H.A.); (S.A.B.)
| | - Sayed Amin Amer
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 14812, Saudi Arabia
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16
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Bruhm DC, Mathios D, Foda ZH, Annapragada AV, Medina JE, Adleff V, Chiao EJ, Ferreira L, Cristiano S, White JR, Mazzilli SA, Billatos E, Spira A, Zaidi AH, Mueller J, Kim AK, Anagnostou V, Phallen J, Scharpf RB, Velculescu VE. Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer. Nat Genet 2023; 55:1301-1310. [PMID: 37500728 PMCID: PMC10412448 DOI: 10.1038/s41588-023-01446-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 06/19/2023] [Indexed: 07/29/2023]
Abstract
Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.
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Grants
- T32 GM136577 NIGMS NIH HHS
- R01 CA121113 NCI NIH HHS
- UG1 CA233259 NCI NIH HHS
- P50 CA062924 NCI NIH HHS
- P30 CA006973 NCI NIH HHS
- EIF | Stand Up To Cancer (SU2C)
- U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- This work was supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, SU2C in-Time Lung Cancer Interception Dream Team Grant, Stand Up to Cancer-Dutch Cancer Society International Translational Cancer Research Dream Team Grant (SU2C-AACR-DT1415), the Gray Foundation, the Commonwealth Foundation, the Mark Foundation for Cancer Research, the Cole Foundation, a research grant from Delfi Diagnostics, and US National Institutes of Health grants CA121113, CA006973, CA233259, CA062924, and 1T32GM136577.
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Affiliation(s)
- Daniel C Bruhm
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dimitrios Mathios
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zachariah H Foda
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akshaya V Annapragada
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jamie E Medina
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Vilmos Adleff
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Elaine Jiayuee Chiao
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Leonardo Ferreira
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephen Cristiano
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James R White
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sarah A Mazzilli
- Division of Computational Biomedicine, Department of Medicine, Boston University, Boston, MA, USA
| | - Ehab Billatos
- Division of Computational Biomedicine, Department of Medicine, Boston University, Boston, MA, USA
- Section of Pulmonary and Critical Care Medicine, Department of Medicine, Boston University, Boston, MA, USA
| | - Avrum Spira
- Division of Computational Biomedicine, Department of Medicine, Boston University, Boston, MA, USA
- Section of Pulmonary and Critical Care Medicine, Department of Medicine, Boston University, Boston, MA, USA
| | - Ali H Zaidi
- Allegheny Health Network Cancer Institute, Allegheny Health Network, Pittsburgh, PA, USA
| | - Jeffrey Mueller
- Allegheny Health Network Cancer Institute, Allegheny Health Network, Pittsburgh, PA, USA
| | - Amy K Kim
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Valsamo Anagnostou
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jillian Phallen
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert B Scharpf
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Victor E Velculescu
- The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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17
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Teterina AA, Willis JH, Lukac M, Jovelin R, Cutter AD, Phillips PC. Genomic diversity landscapes in outcrossing and selfing Caenorhabditis nematodes. PLoS Genet 2023; 19:e1010879. [PMID: 37585484 PMCID: PMC10461856 DOI: 10.1371/journal.pgen.1010879] [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: 12/28/2022] [Revised: 08/28/2023] [Accepted: 07/21/2023] [Indexed: 08/18/2023] Open
Abstract
Caenorhabditis nematodes form an excellent model for studying how the mode of reproduction affects genetic diversity, as some species reproduce via outcrossing whereas others can self-fertilize. Currently, chromosome-level patterns of diversity and recombination are only available for self-reproducing Caenorhabditis, making the generality of genomic patterns across the genus unclear given the profound potential influence of reproductive mode. Here we present a whole-genome diversity landscape, coupled with a new genetic map, for the outcrossing nematode C. remanei. We demonstrate that the genomic distribution of recombination in C. remanei, like the model nematode C. elegans, shows high recombination rates on chromosome arms and low rates toward the central regions. Patterns of genetic variation across the genome are also similar between these species, but differ dramatically in scale, being tenfold greater for C. remanei. Historical reconstructions of variation in effective population size over the past million generations echo this difference in polymorphism. Evolutionary simulations demonstrate how selection, recombination, mutation, and selfing shape variation along the genome, and that multiple drivers can produce patterns similar to those observed in natural populations. The results illustrate how genome organization and selection play a crucial role in shaping the genomic pattern of diversity whereas demographic processes scale the level of diversity across the genome as a whole.
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Affiliation(s)
- Anastasia A. Teterina
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, United States of America
- Center of Parasitology, Severtsov Institute of Ecology and Evolution RAS, Moscow, Russia
| | - John H. Willis
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, United States of America
| | - Matt Lukac
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, United States of America
| | - Richard Jovelin
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - Asher D. Cutter
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - Patrick C. Phillips
- Institute of Ecology and Evolution, University of Oregon, Eugene, Oregon, United States of America
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18
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Sanjaya P, Maljanen K, Katainen R, Waszak SM, Aaltonen LA, Stegle O, Korbel JO, Pitkänen E. Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping. Genome Med 2023; 15:47. [PMID: 37420249 DOI: 10.1186/s13073-023-01204-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 06/21/2023] [Indexed: 07/09/2023] Open
Abstract
BACKGROUND Cancer genome sequencing enables accurate classification of tumours and tumour subtypes. However, prediction performance is still limited using exome-only sequencing and for tumour types with low somatic mutation burden such as many paediatric tumours. Moreover, the ability to leverage deep representation learning in discovery of tumour entities remains unknown. METHODS We introduce here Mutation-Attention (MuAt), a deep neural network to learn representations of simple and complex somatic alterations for prediction of tumour types and subtypes. In contrast to many previous methods, MuAt utilizes the attention mechanism on individual mutations instead of aggregated mutation counts. RESULTS We trained MuAt models on 2587 whole cancer genomes (24 tumour types) from the Pan-Cancer Analysis of Whole Genomes (PCAWG) and 7352 cancer exomes (20 types) from the Cancer Genome Atlas (TCGA). MuAt achieved prediction accuracy of 89% for whole genomes and 64% for whole exomes, and a top-5 accuracy of 97% and 90%, respectively. MuAt models were found to be well-calibrated and perform well in three independent whole cancer genome cohorts with 10,361 tumours in total. We show MuAt to be able to learn clinically and biologically relevant tumour entities including acral melanoma, SHH-activated medulloblastoma, SPOP-associated prostate cancer, microsatellite instability, POLE proofreading deficiency, and MUTYH-associated pancreatic endocrine tumours without these tumour subtypes and subgroups being provided as training labels. Finally, scrunity of MuAt attention matrices revealed both ubiquitous and tumour-type specific patterns of simple and complex somatic mutations. CONCLUSIONS Integrated representations of somatic alterations learnt by MuAt were able to accurately identify histological tumour types and identify tumour entities, with potential to impact precision cancer medicine.
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Affiliation(s)
- Prima Sanjaya
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Katri Maljanen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Riku Katainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sebastian M Waszak
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, Oslo, Norway
- Swiss Institute for Experimental Cancer Research School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco, CA, USA
| | - Lauri A Aaltonen
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Oliver Stegle
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jan O Korbel
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Esa Pitkänen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland.
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
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19
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Vijayraghavan S, Saini N. Aldehyde-Associated Mutagenesis─Current State of Knowledge. Chem Res Toxicol 2023. [PMID: 37363863 DOI: 10.1021/acs.chemrestox.3c00045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023]
Abstract
Aldehydes are widespread in the environment, with multiple sources such as food and beverages, industrial effluents, cigarette smoke, and additives. The toxic effects of exposure to several aldehydes have been observed in numerous studies. At the molecular level, aldehydes damage DNA, cross-link DNA and proteins, lead to lipid peroxidation, and are associated with increased disease risk including cancer. People genetically predisposed to aldehyde sensitivity exhibit severe health outcomes. In various diseases such as Fanconi's anemia and Cockayne syndrome, loss of aldehyde-metabolizing pathways in conjunction with defects in DNA repair leads to widespread DNA damage. Importantly, aldehyde-associated mutagenicity is being explored in a growing number of studies, which could offer key insights into how they potentially contribute to tumorigenesis. Here, we review the genotoxic effects of various aldehydes, focusing particularly on the DNA adducts underlying the mutagenicity of environmentally derived aldehydes. We summarize the chemical structures of the aldehydes and their predominant DNA adducts, discuss various methodologies, in vitro and in vivo, commonly used in measuring aldehyde-associated mutagenesis, and highlight some recent studies looking at aldehyde-associated mutation signatures and spectra. We conclude the Review with a discussion on the challenges and future perspectives of investigating aldehyde-associated mutagenesis.
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Affiliation(s)
- Sriram Vijayraghavan
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, South Carolina 29425, United States
| | - Natalie Saini
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, South Carolina 29425, United States
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20
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Caballero M, Boos D, Koren A. Cell-type specificity of the human mutation landscape with respect to DNA replication dynamics. CELL GENOMICS 2023; 3:100315. [PMID: 37388911 PMCID: PMC10300547 DOI: 10.1016/j.xgen.2023.100315] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 03/24/2023] [Accepted: 04/03/2023] [Indexed: 07/01/2023]
Abstract
The patterns of genomic mutations are associated with various genomic features, most notably late replication timing, yet it remains contested which mutation types and signatures relate to DNA replication dynamics and to what extent. Here, we perform high-resolution comparisons of mutational landscapes between lymphoblastoid cell lines, chronic lymphocytic leukemia tumors, and three colon adenocarcinoma cell lines, including two with mismatch repair deficiency. Using cell-type-matched replication timing profiles, we demonstrate that mutation rates exhibit heterogeneous replication timing associations among cell types. This cell-type heterogeneity extends to the underlying mutational pathways, as mutational signatures show inconsistent replication timing bias between cell types. Moreover, replicative strand asymmetries exhibit similar cell-type specificity, albeit with different relationships to replication timing than mutation rates. Overall, we reveal an underappreciated complexity and cell-type specificity of mutational pathways and their relationship to replication timing.
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Affiliation(s)
- Madison Caballero
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Dominik Boos
- Vertebrate DNA Replication Lab, Center of Medical Biotechnology, University of Duisburg-Essen, 45117 Essen, Germany
| | - Amnon Koren
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
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21
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Selvam K, Sivapragasam S, Poon GMK, Wyrick JJ. Detecting recurrent passenger mutations in melanoma by targeted UV damage sequencing. Nat Commun 2023; 14:2702. [PMID: 37169747 PMCID: PMC10175485 DOI: 10.1038/s41467-023-38265-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 04/21/2023] [Indexed: 05/13/2023] Open
Abstract
Sequencing of melanomas has identified hundreds of recurrent mutations in both coding and non-coding DNA. These include a number of well-characterized oncogenic driver mutations, such as coding mutations in the BRAF and NRAS oncogenes, and non-coding mutations in the promoter of telomerase reverse transcriptase (TERT). However, the molecular etiology and significance of most of these mutations is unknown. Here, we use a new method known as CPD-capture-seq to map UV-induced cyclobutane pyrimidine dimers (CPDs) with high sequencing depth and single nucleotide resolution at sites of recurrent mutations in melanoma. Our data reveal that many previously identified drivers and other recurrent mutations in melanoma occur at CPD hotspots in UV-irradiated melanocytes, often associated with an overlapping binding site of an E26 transformation-specific (ETS) transcription factor. In contrast, recurrent mutations in the promoters of a number of known or suspected cancer genes are not associated with elevated CPD levels. Our data indicate that a subset of recurrent protein-coding mutations are also likely caused by ETS-induced CPD hotspots. This analysis indicates that ETS proteins profoundly shape the mutation landscape of melanoma and reveals a method for distinguishing potential driver mutations from passenger mutations whose recurrence is due to elevated UV damage.
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Affiliation(s)
- Kathiresan Selvam
- School of Molecular Biosciences, Washington State University, Pullman, WA, 99164, USA
| | - Smitha Sivapragasam
- School of Molecular Biosciences, Washington State University, Pullman, WA, 99164, USA
| | - Gregory M K Poon
- Department of Chemistry and Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, 30303, USA
| | - John J Wyrick
- School of Molecular Biosciences, Washington State University, Pullman, WA, 99164, USA.
- Center for Reproductive Biology, Washington State University, Pullman, WA, 99164, USA.
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22
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Tomkova M, Tomek J, Chow J, McPherson JD, Segal DJ, Hormozdiari F. Dr.Nod: computational framework for discovery of regulatory non-coding drivers in tissue-matched distal regulatory elements. Nucleic Acids Res 2023; 51:e23. [PMID: 36625266 PMCID: PMC9976879 DOI: 10.1093/nar/gkac1251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 12/07/2022] [Accepted: 12/19/2022] [Indexed: 01/11/2023] Open
Abstract
The discovery of cancer driver mutations is a fundamental goal in cancer research. While many cancer driver mutations have been discovered in the protein-coding genome, research into potential cancer drivers in the non-coding regions showed limited success so far. Here, we present a novel comprehensive framework Dr.Nod for detection of non-coding cis-regulatory candidate driver mutations that are associated with dysregulated gene expression using tissue-matched enhancer-gene annotations. Applying the framework to data from over 1500 tumours across eight tissues revealed a 4.4-fold enrichment of candidate driver mutations in regulatory regions of known cancer driver genes. An overarching conclusion that emerges is that the non-coding driver mutations contribute to cancer by significantly altering transcription factor binding sites, leading to upregulation of tissue-matched oncogenes and down-regulation of tumour-suppressor genes. Interestingly, more than half of the detected cancer-promoting non-coding regulatory driver mutations are over 20 kb distant from the cancer-associated genes they regulate. Our results show the importance of tissue-matched enhancer-gene maps, functional impact of mutations, and complex background mutagenesis model for the prediction of non-coding regulatory drivers. In conclusion, our study demonstrates that non-coding mutations in enhancers play a previously underappreciated role in cancer and dysregulation of clinically relevant target genes.
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Affiliation(s)
- Marketa Tomkova
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA.,Ludwig Cancer Research, University of Oxford, Oxford, OX3 7DQ, UK.,UC Davis Genome Center, University of California, Davis, CA 95616, USA
| | - Jakub Tomek
- Department of Pharmacology, University of California, Davis, CA 95616, USA
| | - Julie Chow
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA
| | - John D McPherson
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA
| | - David J Segal
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA.,UC Davis Genome Center, University of California, Davis, CA 95616, USA.,UC Davis MIND Institute, University of California, Davis, CA 95616, USA
| | - Fereydoun Hormozdiari
- Department of Biochemistry and Molecular Medicine, University of California, Davis, CA 95616, USA.,UC Davis Genome Center, University of California, Davis, CA 95616, USA.,UC Davis MIND Institute, University of California, Davis, CA 95616, USA
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23
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Zhu Y, Tan Y, Li L, Xiang Y, Huang Y, Zhang X, Yin J, Li J, Lan F, Qian M, Hu J. Genome-wide mapping of protein-DNA damage interaction by PADD-seq. Nucleic Acids Res 2023; 51:e32. [PMID: 36715337 PMCID: PMC10085696 DOI: 10.1093/nar/gkad008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/26/2022] [Accepted: 01/03/2023] [Indexed: 01/31/2023] Open
Abstract
Protein-DNA damage interactions are critical for understanding the mechanism of DNA repair and damage response. However, due to the relatively random distributions of UV-induced damage and other DNA bulky adducts, it is challenging to measure the interactions between proteins and these lesions across the genome. To address this issue, we developed a new method named Protein-Associated DNA Damage Sequencing (PADD-seq) that uses Damage-seq to detect damage distribution in chromatin immunoprecipitation-enriched DNA fragments. It is possible to delineate genome-wide protein-DNA damage interactions at base resolution with this strategy. Using PADD-seq, we observed that RNA polymerase II (Pol II) was blocked by UV-induced damage on template strands, and the interaction declined within 2 h in transcription-coupled repair-proficient cells. On the other hand, Pol II was clearly restrained at damage sites in the absence of the transcription-repair coupling factor CSB during the same time course. Furthermore, we used PADD-seq to examine local changes in H3 acetylation at lysine 9 (H3K9ac) around cisplatin-induced damage, demonstrating the method's broad utility. In conclusion, this new method provides a powerful tool for monitoring the dynamics of protein-DNA damage interaction at the genomic level, and it encourages comprehensive research into DNA repair and damage response.
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Affiliation(s)
- Yongchang Zhu
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yuanqing Tan
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Lin Li
- Institute of Pediatrics and Department of Hematology and Oncology, Children's Hospital of Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yuening Xiang
- Institute of Pediatrics and Department of Hematology and Oncology, Children's Hospital of Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yanchao Huang
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Xiping Zhang
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Jiayong Yin
- Institute of Pediatrics and Department of Hematology and Oncology, Children's Hospital of Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Jie Li
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Fei Lan
- Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, and Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Maoxiang Qian
- Institute of Pediatrics and Department of Hematology and Oncology, Children's Hospital of Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Jinchuan Hu
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
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24
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Evo-devo perspectives on cancer. Essays Biochem 2022; 66:797-815. [PMID: 36250956 DOI: 10.1042/ebc20220041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/22/2022] [Accepted: 09/26/2022] [Indexed: 12/13/2022]
Abstract
The integration of evolutionary and developmental approaches into the field of evolutionary developmental biology has opened new areas of inquiry- from understanding the evolution of development and its underlying genetic and molecular mechanisms to addressing the role of development in evolution. For the last several decades, the terms 'evolution' and 'development' have been increasingly linked to cancer, in many different frameworks and contexts. This mini-review, as part of a special issue on Evolutionary Developmental Biology, discusses the main areas in cancer research that have been addressed through the lenses of both evolutionary and developmental biology, though not always fully or explicitly integrated in an evo-devo framework. First, it briefly introduces the current views on carcinogenesis that invoke evolutionary and/or developmental perspectives. Then, it discusses the main mechanisms proposed to have specifically evolved to suppress cancer during the evolution of multicellularity. Lastly, it considers whether the evolution of multicellularity and development was shaped by the threat of cancer (a cancer-evo-devo perspective), and/or whether the evolution of developmental programs and life history traits can shape cancer resistance/risk in various lineages (an evo-devo-cancer perspective). A proper evolutionary developmental framework for cancer, both as a disease and in terms of its natural history (in the context of the evolution of multicellularity and development as well as life history traits), could bridge the currently disparate evolutionary and developmental perspectives and uncover aspects that will provide new insights for cancer prevention and treatment.
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25
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Castro-Mondragon JA, Aure M, Lingjærde O, Langerød A, Martens JWM, Børresen-Dale AL, Kristensen V, Mathelier A. Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers. Nucleic Acids Res 2022; 50:12131-12148. [PMID: 36477895 PMCID: PMC9757053 DOI: 10.1093/nar/gkac1143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 11/03/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022] Open
Abstract
Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.
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Affiliation(s)
- Jaime A Castro-Mondragon
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Miriam Ragle Aure
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway,Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Ole Christian Lingjærde
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway,Centre for Bioinformatics, Department of Informatics, University of Oslo, Gaustadalléen 23 B, N-0373 Oslo, Norway,KG Jebsen Centre for B-cell malignancies, Institute for Clinical Medicine, University of Oslo, Ullernchausseen 70, N-0372 Oslo, Norway
| | - Anita Langerød
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
| | - John W M Martens
- Erasmus MC Cancer Institute and Cancer Genomics Netherlands, University Medical Center Rotterdam, Department of Medical Oncology, 3015GD Rotterdam, The Netherlands
| | - Anne-Lise Børresen-Dale
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway
| | - Vessela N Kristensen
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway,Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
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26
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Timmons C, Morris Q, Harrigan CF. Regional mutational signature activities in cancer genomes. PLoS Comput Biol 2022; 18:e1010733. [PMID: 36469539 PMCID: PMC9754594 DOI: 10.1371/journal.pcbi.1010733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 12/15/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022] Open
Abstract
Cancer genomes harbor a catalog of somatic mutations. The type and genomic context of these mutations depend on their causes and allow their attribution to particular mutational signatures. Previous work has shown that mutational signature activities change over the course of tumor development, but investigations of genomic region variability in mutational signatures have been limited. Here, we expand upon this work by constructing regional profiles of mutational signature activities over 2,203 whole genomes across 25 tumor types, using data aggregated by the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium. We present GenomeTrackSig as an extension to the TrackSig R package to construct regional signature profiles using optimal segmentation and the expectation-maximization (EM) algorithm. We find that 426 genomes from 20 tumor types display at least one change in mutational signature activities (changepoint), and 306 genomes contain at least one of 54 recurrent changepoints shared by seven or more genomes of the same tumor type. Five recurrent changepoint locations are shared by multiple tumor types. Within these regions, the particular signature changes are often consistent across samples of the same type and some, but not all, are characterized by signatures associated with subclonal expansion. The changepoints we found cannot strictly be explained by gene density, mutation density, or cell-of-origin chromatin state. We hypothesize that they reflect a confluence of factors including evolutionary timing of mutational processes, regional differences in somatic mutation rate, large-scale changes in chromatin state that may be tissue type-specific, and changes in chromatin accessibility during subclonal expansion. These results provide insight into the regional effects of DNA damage and repair processes, and may help us localize genomic and epigenomic changes that occur during cancer development.
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Affiliation(s)
- Caitlin Timmons
- Computational and Systems Biology Program, Sloan Kettering Institute, New York, New York, United States of America
- Department of Biological Sciences, Smith College, Northampton, Massachusetts, United States of America
| | - Quaid Morris
- Computational and Systems Biology Program, Sloan Kettering Institute, New York, New York, United States of America
- Vector Institute for Artificial Intelligence, Toronto, Canada
| | - Caitlin F. Harrigan
- Vector Institute for Artificial Intelligence, Toronto, Canada
- Department of Computer Science, University of Toronto, Toronto, Canada
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27
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Abstract
Mutations in genes that confer a selective advantage to hematopoietic stem cells (HSCs) drive clonal hematopoiesis (CH). While some CH drivers have been identified, the compendium of all genes able to drive CH upon mutations in HSCs remains incomplete. Exploiting signals of positive selection in blood somatic mutations may be an effective way to identify CH driver genes, analogously to cancer. Using the tumor sample in blood/tumor pairs as reference, we identify blood somatic mutations across more than 12,000 donors from two large cancer genomics cohorts. The application of IntOGen, a driver discovery pipeline, to both cohorts, and more than 24,000 targeted sequenced samples yields a list of close to 70 genes with signals of positive selection in CH, available at http://www.intogen.org/ch. This approach recovers known CH genes, and discovers other candidates. Identifying the genetic drivers of clonal haematopoiesis (CH) has been challenging due to their low frequencies and a lack of adequate tools. Here, the authors use a reverse calling to detect blood somatic mutations and the IntOGen pipeline to identify CH drivers in large cancer genomics data sets based on signals of positive selection.
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28
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Boström M, Larsson E. Somatic mutation distribution across tumour cohorts provides a signal for positive selection in cancer. Nat Commun 2022; 13:7023. [PMID: 36396655 PMCID: PMC9671924 DOI: 10.1038/s41467-022-34746-z] [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: 04/05/2022] [Accepted: 11/04/2022] [Indexed: 11/18/2022] Open
Abstract
Cancer gene discovery is reliant on distinguishing driver mutations from a multitude of passenger mutations in tumour genomes. While driver genes may be revealed based on excess mutation recurrence or clustering, there is a need for orthogonal principles. Here, we take advantage of the fact that non-cancer genes, containing only passenger mutations under neutral selection, exhibit a likelihood of mutagenesis in a given tumour determined by the tumour's mutational signature and burden. This relationship can be disrupted by positive selection, leading to a difference in the distribution of mutated cases across a cohort for driver and passenger genes. We apply this principle to detect cancer drivers independently of recurrence in large pan-cancer cohorts, and show that our method (SEISMIC) performs comparably to traditional approaches and can provide resistance to known confounding mutational phenomena. Being based on a different principle, the approach provides a much-needed complement to existing methods for detecting signals of selection.
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Affiliation(s)
- Martin Boström
- grid.8761.80000 0000 9919 9582Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-405 30 Gothenburg, Sweden
| | - Erik Larsson
- grid.8761.80000 0000 9919 9582Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, SE-405 30 Gothenburg, Sweden
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29
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Murat P, Perez C, Crisp A, van Eijk P, Reed SH, Guilbaud G, Sale JE. DNA replication initiation shapes the mutational landscape and expression of the human genome. SCIENCE ADVANCES 2022; 8:eadd3686. [PMID: 36351018 PMCID: PMC9645720 DOI: 10.1126/sciadv.add3686] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/21/2022] [Indexed: 06/16/2023]
Abstract
The interplay between active biological processes and DNA repair is central to mutagenesis. Here, we show that the ubiquitous process of replication initiation is mutagenic, leaving a specific mutational footprint at thousands of early and efficient replication origins. The observed mutational pattern is consistent with two distinct mechanisms, reflecting the two-step process of origin activation, triggering the formation of DNA breaks at the center of origins and local error-prone DNA synthesis in their immediate vicinity. We demonstrate that these replication initiation-dependent mutational processes exert an influence on phenotypic diversity in humans that is disproportionate to the origins' genomic size: By increasing mutational loads at gene promoters and splice junctions, the presence of an origin significantly influences both gene expression and mRNA isoform usage. Last, we show that mutagenesis at origins not only drives the evolution of origin sequences but also contributes to sculpting regulatory domains of the human genome.
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Affiliation(s)
- Pierre Murat
- Division of Protein & Nucleic Acid Chemistry, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Consuelo Perez
- Division of Protein & Nucleic Acid Chemistry, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Alastair Crisp
- Division of Protein & Nucleic Acid Chemistry, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Patrick van Eijk
- Broken String Biosciences Ltd., BioData Innovation Centre, Unit AB3-03, Level 3, Wellcome Genome Campus, Hinxton, Cambridge CB10 1DR, UK
- Division of Cancer & Genetics School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK
| | - Simon H. Reed
- Broken String Biosciences Ltd., BioData Innovation Centre, Unit AB3-03, Level 3, Wellcome Genome Campus, Hinxton, Cambridge CB10 1DR, UK
- Division of Cancer & Genetics School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK
| | - Guillaume Guilbaud
- Division of Protein & Nucleic Acid Chemistry, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
| | - Julian E. Sale
- Division of Protein & Nucleic Acid Chemistry, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK
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30
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Fang H, Bertl J, Zhu X, Lam TC, Wu S, Shih DJ, Wong JW. Tumour mutational burden is overestimated by target cancer gene panels. JOURNAL OF THE NATIONAL CANCER CENTER 2022. [DOI: 10.1016/j.jncc.2022.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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31
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Ocsenas O, Reimand J. Chromatin accessibility of primary human cancers ties regional mutational processes and signatures with tissues of origin. PLoS Comput Biol 2022; 18:e1010393. [PMID: 35947558 PMCID: PMC9365152 DOI: 10.1371/journal.pcbi.1010393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 07/15/2022] [Indexed: 11/19/2022] Open
Abstract
Somatic mutations in cancer genomes are associated with DNA replication timing (RT) and chromatin accessibility (CA), however these observations are based on normal tissues and cell lines while primary cancer epigenomes remain uncharacterised. Here we use machine learning to model megabase-scale mutation burden in 2,500 whole cancer genomes and 17 cancer types via a compendium of 900 CA and RT profiles covering primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than those of normal tissues, are most predictive of regional mutagenesis in most cancer types. Feature prioritisation shows that the epigenomes of matching cancer types and organ systems are often the strongest predictors of regional mutation burden, highlighting disease-specific associations of mutational processes. The genomic distributions of mutational signatures are also shaped by the epigenomes of matched cancer and tissue types, with SBS5/40, carcinogenic and unknown signatures most accurately predicted by our models. In contrast, fewer associations of RT and regional mutagenesis are found. Lastly, the models highlight genomic regions with overrepresented mutations that dramatically exceed epigenome-derived expectations and show a pan-cancer convergence to genes and pathways involved in development and oncogenesis, indicating the potential of this approach for coding and non-coding driver discovery. The association of regional mutational processes with the epigenomes of primary cancers suggests that the landscape of passenger mutations is predominantly shaped by the epigenomes of cancer cells after oncogenic transformation.
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Affiliation(s)
- Oliver Ocsenas
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
- * E-mail:
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32
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Machado HE, Mitchell E, Øbro NF, Kübler K, Davies M, Leongamornlert D, Cull A, Maura F, Sanders MA, Cagan ATJ, McDonald C, Belmonte M, Shepherd MS, Vieira Braga FA, Osborne RJ, Mahbubani K, Martincorena I, Laurenti E, Green AR, Getz G, Polak P, Saeb-Parsy K, Hodson DJ, Kent DG, Campbell PJ. Diverse mutational landscapes in human lymphocytes. Nature 2022; 608:724-732. [PMID: 35948631 PMCID: PMC9402440 DOI: 10.1038/s41586-022-05072-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 07/05/2022] [Indexed: 11/25/2022]
Abstract
The lymphocyte genome is prone to many threats, including programmed mutation during differentiation1, antigen-driven proliferation and residency in diverse microenvironments. Here, after developing protocols for expansion of single-cell lymphocyte cultures, we sequenced whole genomes from 717 normal naive and memory B and T cells and haematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells, with higher burdens in memory cells than in naive cells, and with T cells accumulating mutations at a higher rate throughout life. Off-target effects of immunological diversification accounted for approximately half of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every on-target IGHV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than in stem cells, with around 15% of deletions being attributable to off-target recombinase-activating gene activity. DNA damage from ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory cells. The mutation burden and signatures of normal B cells were broadly similar to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes that are active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.
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Affiliation(s)
| | - Emily Mitchell
- Wellcome Sanger Institute, Hinxton, UK
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Nina F Øbro
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Kirsten Kübler
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Megan Davies
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- Cambridge Molecular Diagnostics, Milton Road, Cambridge, United Kingdom
| | | | - Alyssa Cull
- York Biomedical Research Institute, University of York, Wentworth Way, York, United Kingdom
| | | | - Mathijs A Sanders
- Wellcome Sanger Institute, Hinxton, UK
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | | | - Craig McDonald
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- York Biomedical Research Institute, University of York, Wentworth Way, York, United Kingdom
| | - Miriam Belmonte
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
- York Biomedical Research Institute, University of York, Wentworth Way, York, United Kingdom
| | - Mairi S Shepherd
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | | | - Robert J Osborne
- Wellcome Sanger Institute, Hinxton, UK
- Biofidelity, 330 Cambridge Science Park, Milton Road, Cambridge, United Kingdom
| | - Krishnaa Mahbubani
- Department of Haematology, University of Cambridge, Cambridge, UK
- Department of Surgery, University of Cambridge, Cambridge, United Kingdom
- NIHR Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | | | - Elisa Laurenti
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Anthony R Green
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Paz Polak
- Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Kourosh Saeb-Parsy
- Department of Surgery, University of Cambridge, Cambridge, United Kingdom
- NIHR Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Daniel J Hodson
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
| | - David G Kent
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
- Department of Haematology, University of Cambridge, Cambridge, UK.
- York Biomedical Research Institute, University of York, Wentworth Way, York, United Kingdom.
| | - Peter J Campbell
- Wellcome Sanger Institute, Hinxton, UK.
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
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33
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The shaping of cancer genomes with the regional impact of mutation processes. EXPERIMENTAL & MOLECULAR MEDICINE 2022; 54:1049-1060. [PMID: 35902761 PMCID: PMC9355972 DOI: 10.1038/s12276-022-00808-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/03/2022] [Accepted: 04/28/2022] [Indexed: 11/09/2022]
Abstract
Mutation signature analysis has been used to infer the contributions of various DNA mutagenic-repair events in individual cancer genomes. Here, we build a statistical framework using a multinomial distribution to assign individual mutations to their cognate mutation signatures. We applied it to 47 million somatic mutations in 1925 publicly available cancer genomes to obtain a mutation signature map at the resolution of individual somatic mutations. Based on mutation signature-level genetic-epigenetic correlative analyses, mutations with transcriptional and replicative strand asymmetries show different enrichment patterns across genomes, and “transcribed” chromatin states and gene boundaries are particularly vulnerable to transcription-coupled repair activities. While causative processes of cancer-driving mutations can be diverse, as shown for converging effects of multiple mutational processes on TP53 mutations, the substantial fraction of recurrently mutated amino acids points to specific mutational processes, e.g., age-related C-to-T transition for KRAS p.G12 mutations. Our investigation of evolutionary trajectories with respect to mutation signatures further revealed that candidate pairs of early- vs. late-operative mutation processes in cancer genomes represent evolutionary dynamics of multiple mutational processes in the shaping of cancer genomes. We also observed that the local mutation clusters of kataegis often include mutations arising from multiple mutational processes, suggestive of a locally synchronous impact of multiple mutational processes on cancer genomes. Taken together, our examination of the genome-wide landscape of mutation signatures at the resolution of individual somatic mutations shows the spatially and temporally distinct mutagenesis-repair-replication histories of various mutational processes and their effects on shaping cancer genomes. A statistical model that assigns non-hereditary DNA alterations known as somatic mutations to mutation “signatures” (groups of mutations arising from a specific biological process) on cancer genomes provides novel insights into disease evolution. Somatic mutations result from exposure to factors often linked to cancer development, such as tobacco or ultraviolet radiation. However, assigning a somatic mutation to a particular mutation “signature” remains challenging. The model created by Ruibin Xi (Peking University, China) and Tae-Min Kim (Catholic University of Korea, Seoul, South Korea) and co-workers grouped 47 million somatic mutations in 1925 cancer genomes into localized clusters before connecting them with mutation signatures. This strategy highlights the spatial and temporal patterns related to the origins of mutations, how the DNA strands are repaired and replicated, and how this influences the emerging cancer genome.
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34
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Recurrent somatic mutations as predictors of immunotherapy response. Nat Commun 2022; 13:3938. [PMID: 35803911 PMCID: PMC9270330 DOI: 10.1038/s41467-022-31055-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/25/2022] [Indexed: 11/08/2022] Open
Abstract
Immune checkpoint blockade (ICB) has transformed the treatment of metastatic cancer but is hindered by variable response rates. A key unmet need is the identification of biomarkers that predict treatment response. To address this, we analyzed six whole exome sequencing cohorts with matched disease outcomes to identify genes and pathways predictive of ICB response. To increase detection power, we focus on genes and pathways that are significantly mutated following correction for epigenetic, replication timing, and sequence-based covariates. Using this technique, we identify several genes (BCLAF1, KRAS, BRAF, and TP53) and pathways (MAPK signaling, p53 associated, and immunomodulatory) as predictors of ICB response and develop the Cancer Immunotherapy Response CLassifiEr (CIRCLE). Compared to tumor mutational burden alone, CIRCLE led to superior prediction of ICB response with a 10.5% increase in sensitivity and a 11% increase in specificity. We envision that CIRCLE and more broadly the analysis of recurrently mutated cancer genes will pave the way for better prognostic tools for cancer immunotherapy.
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35
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Abstract
Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.
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36
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Kikutake C, Suyama M. Pan-cancer analysis of mutations in open chromatin regions and their possible association with cancer pathogenesis. Cancer Med 2022; 11:3902-3916. [PMID: 35416406 PMCID: PMC9582691 DOI: 10.1002/cam4.4749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/29/2022] [Accepted: 04/01/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Open chromatin is associated with gene transcription. Previous studies have shown that the density of mutations in open chromatin regions is lower than that in flanking regions because of the higher accessibility of DNA repair machinery. However, in several cancer types, open chromatin regions show an increased local density of mutations in activated regulatory regions. Although the mutation distribution within open chromatin regions in cancer cells has been investigated, only few studies have focused on their functional implications in cancer. To reveal the impact of highly mutated open chromatin regions on cancer, we investigated the association between mutations in open chromatin regions and their possible functions. METHODS Whole-genome sequencing data of 18 cancer types were downloaded from the PanCancer Analysis of Whole Genomes and Catalog of Somatic Mutations in Cancer. We quantified the mutations located in open chromatin regions defined by The Cancer Genome Atlas and classified open chromatin regions into three categories based on the number of mutations. Then, we investigated the chromatin state, amplification, and possible target genes of the open chromatin regions with a high number of mutations. We also analyzed the association between the number of mutations in open chromatin regions and patient prognosis. RESULTS In some cancer types, the proportion of promoter or enhancer chromatin state in open chromatin regions with a high number of mutations was significantly higher than that in the regions with a low number of mutations. The possible target genes of open chromatin regions with a high number of mutations were more strongly associated with cancer than those of other open chromatin regions. Moreover, a high number of mutations in open chromatin regions was significantly associated with a poor prognosis in some cancer types. CONCLUSIONS These results suggest that highly mutated open chromatin regions play an important role in cancer pathogenesis and can be effectively used to predict patient prognosis.
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Affiliation(s)
- Chie Kikutake
- Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Mikita Suyama
- Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
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37
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Georgakopoulos-Soares I, Victorino J, Parada GE, Agarwal V, Zhao J, Wong HY, Umar MI, Elor O, Muhwezi A, An JY, Sanders SJ, Kwok CK, Inoue F, Hemberg M, Ahituv N. High-throughput characterization of the role of non-B DNA motifs on promoter function. CELL GENOMICS 2022; 2:100111. [PMID: 35573091 PMCID: PMC9105345 DOI: 10.1016/j.xgen.2022.100111] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 10/21/2021] [Accepted: 02/18/2022] [Indexed: 12/24/2022]
Abstract
lternative DNA conformations, termed non-B DNA structures, can affect transcription, but the underlying mechanisms and their functional impact have not been systematically characterized. Here, we used computational genomic analyses coupled with massively parallel reporter assays (MPRAs) to show that certain non-B DNA structures have a substantial effect on gene expression. Genomic analyses found that non-B DNA structures at promoters harbor an excess of germline variants. Analysis of multiple MPRAs, including a promoter library specifically designed to perturb non-B DNA structures, functionally validated that Z-DNA can significantly affect promoter activity. We also observed that biophysical properties of non-B DNA motifs, such as the length of Z-DNA motifs and the orientation of G-quadruplex structures relative to transcriptional direction, have a significant effect on promoter activity. Combined, their higher mutation rate and functional effect on transcription implicate a subset of non-B DNA motifs as major drivers of human gene-expression-associated phenotypes.
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Affiliation(s)
- Ilias Georgakopoulos-Soares
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Jesus Victorino
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain
- Departamento de Bioquímica, Facultad de Medicina, Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain
| | - Guillermo E. Parada
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
- Wellcome Trust Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge CB2 1QN, UK
| | | | - Jingjing Zhao
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Hei Yuen Wong
- Department of Chemistry and State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China
| | - Mubarak Ishaq Umar
- Department of Chemistry and State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China
| | - Orry Elor
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Allan Muhwezi
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Joon-Yong An
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea
| | - Stephan J. Sanders
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Chun Kit Kwok
- Department of Chemistry and State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China
- Shenzhen Research Institute of City University of Hong Kong, Shenzhen, China
| | - Fumitaka Inoue
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Martin Hemberg
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
- Wellcome Trust Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge CB2 1QN, UK
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
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38
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Dietlein F, Wang AB, Fagre C, Tang A, Besselink NJM, Cuppen E, Li C, Sunyaev SR, Neal JT, Van Allen EM. Genome-wide analysis of somatic noncoding mutation patterns in cancer. Science 2022; 376:eabg5601. [PMID: 35389777 PMCID: PMC9092060 DOI: 10.1126/science.abg5601] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We established a genome-wide compendium of somatic mutation events in 3949 whole cancer genomes representing 19 tumor types. Protein-coding events captured well-established drivers. Noncoding events near tissue-specific genes, such as ALB in the liver or KLK3 in the prostate, characterized localized passenger mutation patterns and may reflect tumor-cell-of-origin imprinting. Noncoding events in regulatory promoter and enhancer regions frequently involved cancer-relevant genes such as BCL6, FGFR2, RAD51B, SMC6, TERT, and XBP1 and represent possible drivers. Unlike most noncoding regulatory events, XBP1 mutations primarily accumulated outside the gene's promoter, and we validated their effect on gene expression using CRISPR-interference screening and luciferase reporter assays. Broadly, our study provides a blueprint for capturing mutation events across the entire genome to guide advances in biological discovery, therapies, and diagnostics.
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Affiliation(s)
- Felix Dietlein
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.,Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA.,Corresponding author. (E.M.V.A.); (F.D.)
| | - Alex B. Wang
- Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Christian Fagre
- Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Anran Tang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.,Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Nicolle J. M. Besselink
- Center for Molecular Medicine and Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands
| | - Edwin Cuppen
- Center for Molecular Medicine and Oncode Institute, University Medical Center Utrecht, 3584 CX Utrecht, Netherlands.,Hartwig Medical Foundation, 1098 XH Amsterdam, Netherlands
| | - Chunliang Li
- Department of Tumor Cell Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Shamil R. Sunyaev
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - James T. Neal
- Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Eliezer M. Van Allen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.,Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA.,Corresponding author. (E.M.V.A.); (F.D.)
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39
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Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification. Nat Commun 2022; 13:1640. [PMID: 35347147 PMCID: PMC8960760 DOI: 10.1038/s41467-022-29336-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 03/09/2022] [Indexed: 12/17/2022] Open
Abstract
Studies have revealed key genomic aberrations in pediatric acute myeloid leukemia (AML) based on Western populations. It is unknown to what extent the current genomic findings represent populations with different ethnic backgrounds. Here we present the genomic landscape of driver alterations of Chinese pediatric AML and discover previously undescribed genomic aberrations, including the XPO1-TNRC18 fusion. Comprehensively comparing between the Chinese and Western AML cohorts reveal a substantially distinct genomic alteration profile. For example, Chinese AML patients more commonly exhibit mutations in KIT and CSF3R, and less frequently mutated of genes in the RAS signaling pathway. These differences in mutation frequencies lead to the detection of previously uncharacterized co-occurring mutation pairs. Importantly, the distinct driver profile is clinical relevant. We propose a refined prognosis risk classification model which better reflected the adverse event risk for Chinese AML patients. These results emphasize the importance of genetic background in precision medicine. The genomic landscape of pediatric acute myeloid leukemia (AML) has mostly been characterised for Western populations. Here, the authors identify potential driver alterations in Chinese pediatric AML, which differ from Western populations, and propose a prognostic risk classification model.
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40
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Wu S, Huang Y, Selby CP, Gao M, Sancar A, Hu J. A new technique for genome-wide mapping of nucleotide excision repair without immunopurification of damaged DNA. J Biol Chem 2022; 298:101863. [PMID: 35339490 PMCID: PMC9034098 DOI: 10.1016/j.jbc.2022.101863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 12/03/2022] Open
Abstract
Nucleotide excision repair functions to protect genome integrity, and ongoing studies using excision repair sequencing (XR-seq) have contributed to our understanding of how cells prioritize repair across the genome. In this method, the products of excision repair bearing damaged DNA are captured, sequenced, and then mapped genome-wide at single-nucleotide resolution. However, reagent requirements and complex procedures have limited widespread usage of this technique. In addition to the expense of these reagents, it has been hypothesized that the immunoprecipitation step using antibodies directed against damaged DNA may introduce bias in different sequence contexts. Here, we describe a newly developed adaptation called dA-tailing and adaptor ligation (ATL)–XR-seq, a relatively simple XR-seq method that avoids the use of immunoprecipitation targeting damaged DNA. ATL-XR-seq captures repair products by 3′-dA-tailing and 5′-adapter ligation instead of the original 5′- and 3′-dual adapter ligation. This new approach avoids adapter dimer formation during subsequent PCR, omits inefficient and time-consuming purification steps, and is very sensitive. In addition, poly(dA) tail length heterogeneity can serve as a molecular identifier, allowing more repair hotspots to be mapped. Importantly, a comparison of both repair mapping methods showed that no major bias is introduced by the anti-UV damage antibodies used in the original XR-seq procedure. Finally, we also coupled the described dA-tailing approach with quantitative PCR in a new method to quantify repair products. These new methods provide powerful and user-friendly tools to qualitatively and quantitatively measure excision repair.
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Affiliation(s)
- Sizhong Wu
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yanchao Huang
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Christopher P Selby
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599-7260, USA
| | - Meng Gao
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Aziz Sancar
- Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599-7260, USA.
| | - Jinchuan Hu
- Shanghai Fifth People's Hospital, Fudan University, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism (Ministry of Science and Technology), Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
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41
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Kim S, Hwang S. G-Quadruplex Matters in Tissue-Specific Tumorigenesis by BRCA1 Deficiency. Genes (Basel) 2022; 13:genes13030391. [PMID: 35327946 PMCID: PMC8948836 DOI: 10.3390/genes13030391] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 12/14/2022] Open
Abstract
How and why distinct genetic alterations, such as BRCA1 mutation, promote tumorigenesis in certain tissues, but not others, remain an important issue in cancer research. The underlying mechanisms may reveal tissue-specific therapeutic vulnerabilities. Although the roles of BRCA1, such as DNA damage repair and stalled fork stabilization, obviously contribute to tumor suppression, these ubiquitously important functions cannot explain tissue-specific tumorigenesis by BRCA1 mutations. Recent advances in our understanding of the cancer genome and fundamental cellular processes on DNA, such as transcription and DNA replication, have provided new insights regarding BRCA1-associated tumorigenesis, suggesting that G-quadruplex (G4) plays a critical role. In this review, we summarize the importance of G4 structures in mutagenesis of the cancer genome and cell type-specific gene regulation, and discuss a recently revealed molecular mechanism of G4/base excision repair (BER)-mediated transcriptional activation. The latter adequately explains the correlation between the accumulation of unresolved transcriptional regulatory G4s and multi-level genomic alterations observed in BRCA1-associated tumors. In summary, tissue-specific tumorigenesis by BRCA1 deficiency can be explained by cell type-specific levels of transcriptional regulatory G4s and the role of BRCA1 in resolving it. This mechanism would provide an integrated understanding of the initiation and development of BRCA1-associated tumors.
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Affiliation(s)
- Sanghyun Kim
- Department of Biomedical Science, College of Life Science, CHA University, Sungnam 13488, Korea;
| | - Sohyun Hwang
- Department of Biomedical Science, College of Life Science, CHA University, Sungnam 13488, Korea;
- Department of Pathology, CHA Bundang Medical Center, CHA University School of Medicine, Sungnam 13496, Korea
- Correspondence:
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42
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Somatic structural variant formation is guided by and influences genome architecture. Genome Res 2022; 32:643-655. [PMID: 35177558 PMCID: PMC8997353 DOI: 10.1101/gr.275790.121] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 02/11/2022] [Indexed: 11/25/2022]
Abstract
The occurrence and formation of genomic structural variants (SVs) is known to be influenced by the 3D chromatin architecture, but the extent and magnitude have been challenging to study. Here, we apply Hi-C to study chromatin organization before and after induction of chromothripsis in human cells. We use Hi-C to manually assemble the derivative chromosomes following the occurrence of massive complex rearrangements, which allows us to study the sources of SV formation and their consequences on gene regulation. We observe an action–reaction interplay whereby the 3D chromatin architecture directly impacts the location and formation of SVs. In turn, the SVs reshape the chromatin organization to alter the local topologies, replication timing, and gene regulation in cis. We show that SVs have a strong tendency to occur between similar chromatin compartments and replication timing regions. Moreover, we find that SVs frequently occur at 3D loop anchors, that SVs can cause a switch in chromatin compartments and replication timing, and that this is a major source of SV-mediated effects on nearby gene expression changes. Finally, we provide evidence for a general mechanistic bias of the 3D chromatin on SV occurrence using data from more than 2700 patient-derived cancer genomes.
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43
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Manders F, Brandsma AM, de Kanter J, Verheul M, Oka R, van Roosmalen MJ, van der Roest B, van Hoeck A, Cuppen E, van Boxtel R. MutationalPatterns: the one stop shop for the analysis of mutational processes. BMC Genomics 2022; 23:134. [PMID: 35168570 PMCID: PMC8845394 DOI: 10.1186/s12864-022-08357-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 02/01/2022] [Indexed: 01/01/2023] Open
Abstract
Background The collective of somatic mutations in a genome represents a record of mutational processes that have been operative in a cell. These processes can be investigated by extracting relevant mutational patterns from sequencing data. Results Here, we present the next version of MutationalPatterns, an R/Bioconductor package, which allows in-depth mutational analysis of catalogues of single and double base substitutions as well as small insertions and deletions. Major features of the package include the possibility to perform regional mutation spectra analyses and the possibility to detect strand asymmetry phenomena, such as lesion segregation. On top of this, the package also contains functions to determine how likely it is that a signature can cause damaging mutations (i.e., mutations that affect protein function). This updated package supports stricter signature refitting on known signatures in order to prevent overfitting. Using simulated mutation matrices containing varied signature contributions, we showed that reliable refitting can be achieved even when only 50 mutations are present per signature. Additionally, we incorporated bootstrapped signature refitting to assess the robustness of the signature analyses. Finally, we applied the package on genome mutation data of cell lines in which we deleted specific DNA repair processes and on large cancer datasets, to show how the package can be used to generate novel biological insights. Conclusions This novel version of MutationalPatterns allows for more comprehensive analyses and visualization of mutational patterns in order to study the underlying processes. Ultimately, in-depth mutational analyses may contribute to improved biological insights in mechanisms of mutation accumulation as well as aid cancer diagnostics. MutationalPatterns is freely available at http://bioconductor.org/packages/MutationalPatterns. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08357-3.
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Affiliation(s)
- Freek Manders
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands.,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands
| | - Arianne M Brandsma
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands.,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands
| | - Jurrian de Kanter
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands.,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands
| | - Mark Verheul
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands.,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands
| | - Rurika Oka
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands.,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands
| | - Markus J van Roosmalen
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands.,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands
| | - Bastiaan van der Roest
- Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands.,Center for Molecular Medicine, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Arne van Hoeck
- Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands.,Center for Molecular Medicine, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Edwin Cuppen
- Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands.,Center for Molecular Medicine, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584 CG, Utrecht, The Netherlands
| | - Ruben van Boxtel
- Princess Máxima Center for Pediatric Oncology, Heidelberglaan 25, 3584CS, Utrecht, The Netherlands. .,Oncode Institute, Jaarbeursplein 6, 3521 AL, Utrecht, The Netherlands.
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44
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Demeulemeester J, Dentro SC, Gerstung M, Van Loo P. Biallelic mutations in cancer genomes reveal local mutational determinants. Nat Genet 2022; 54:128-133. [PMID: 35145300 PMCID: PMC8837546 DOI: 10.1038/s41588-021-01005-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 12/14/2021] [Indexed: 12/31/2022]
Abstract
The infinite sites model of molecular evolution posits that every position in the genome is mutated at most once1. By restricting the number of possible mutation histories, haplotypes and alleles, it forms a cornerstone of tumor phylogenetic analysis2 and is often implied when calling, phasing and interpreting variants3,4 or studying the mutational landscape as a whole5. Here we identify 18,295 biallelic mutations, where the same base is mutated independently on both parental copies, in 559 (21%) bulk sequencing samples from the Pan-Cancer Analysis of Whole Genomes study. Biallelic mutations reveal ultraviolet light damage hotspots at E26 transformation-specific (ETS) and nuclear factor of activated T cells (NFAT) binding sites, and hypermutable motifs in POLE-mutant and other cancers. We formulate recommendations for variant calling and provide frameworks to model and detect biallelic mutations. These results highlight the need for accurate models of mutation rates and tumor evolution, as well as their inference from sequencing data.
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Affiliation(s)
- Jonas Demeulemeester
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK.
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
| | - Stefan C Dentro
- European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Moritz Gerstung
- European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Peter Van Loo
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK.
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45
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Stark B, Poon GM, Wyrick JJ. Molecular mechanism of UV damage modulation in nucleosomes. Comput Struct Biotechnol J 2022; 20:5393-5400. [PMID: 36212527 PMCID: PMC9529667 DOI: 10.1016/j.csbj.2022.08.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 08/31/2022] [Accepted: 08/31/2022] [Indexed: 12/02/2022] Open
Abstract
Exposure to ultraviolet (UV) light causes the formation of mutagenic cyclobutane pyrimidine dimers (CPDs) in cellular DNA. Previous studies have revealed that CPD formation in nucleosomes, the building blocks of chromatin, shows a striking ∼10 base pair (bp) periodic pattern. CPD formation is suppressed at positions where the DNA minor groove faces toward the histone octamer (minor-in) and elevated CPD formation at positions where the minor groove faces away from the histone octamer (minor-out). However, the molecular mechanism underlying this nucleosome photofootprint is unclear. Here, we analyzed ∼180 high-resolution nucleosome structures to characterize whether differences in DNA mobility or conformation are responsible for the CPD modulation in nucleosomes. Our results indicate that differences in DNA mobility cannot explain CPD modulation in nucleosome. Instead, we find that the sharp DNA bending around the histone octamer results in DNA conformations with structural parameters more susceptible to UV damage formation at minor-out positions and more resistant to CPD formation at minor-in positions. This analysis reveals the molecular mechanism responsible for periodic modulation of CPD formation and UV mutagenesis in nucleosomal DNA.
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46
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El Ghamrasni S, Quevedo R, Hawley J, Mazrooei P, Hanna Y, Cirlan I, Zhu H, Bruce JP, Oldfield LE, Yang SYC, Guilhamon P, Reimand J, Cescon DW, Done SJ, Lupien M, Pugh TJ. Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer. Mol Cancer Res 2022; 20:102-113. [PMID: 34556523 PMCID: PMC9398156 DOI: 10.1158/1541-7786.mcr-21-0471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/31/2021] [Accepted: 09/17/2021] [Indexed: 01/07/2023]
Abstract
Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)+ progesterone receptor (PR)+ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit. IMPLICATIONS: Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.
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Affiliation(s)
- Samah El Ghamrasni
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Rene Quevedo
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - James Hawley
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Parisa Mazrooei
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Genentech, South San Francisco, California
| | - Youstina Hanna
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Iulia Cirlan
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Helen Zhu
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Vector Institute, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Jeff P Bruce
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Leslie E Oldfield
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - S Y Cindy Yang
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Paul Guilhamon
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- Arthur and Sonia Labatt Brain Tumor Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jüri Reimand
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Dave W Cescon
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Susan J Done
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Mathieu Lupien
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Trevor J Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
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47
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Stark B, Poon GMK, Wyrick JJ. CTCF puts a new twist on UV damage and repair in skin cancer. Mol Cell Oncol 2021; 8:2009424. [PMID: 35419468 PMCID: PMC8997251 DOI: 10.1080/23723556.2021.2009424] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/15/2021] [Accepted: 11/17/2021] [Indexed: 05/26/2023]
Abstract
Somatic mutations in skin cancers are highly enriched at binding sites for CCCTC-binding factor (CTCF). We have discovered that CTCF binding alters the DNA structure to render it more susceptible to UV damage. Elevated UV damage formation at CTCF binding sites, in conjunction with subsequent repair inhibition, promotes UV mutagenesis.
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Affiliation(s)
- Bastian Stark
- School of Molecular Biosciences, Washington State University, Pullman, WA, USA
| | - Gregory M. K. Poon
- Department of Chemistry and Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, USA
| | - John J. Wyrick
- School of Molecular Biosciences, Washington State University, Pullman, WA, USA
- Center for Reproductive Biology, Washington State University, Pullman, WA, USA
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48
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Killcoyne S, Fitzgerald RC. Evolution and progression of Barrett's oesophagus to oesophageal cancer. Nat Rev Cancer 2021; 21:731-741. [PMID: 34545238 DOI: 10.1038/s41568-021-00400-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/12/2021] [Indexed: 02/07/2023]
Abstract
Cancer cells are shaped through an evolutionary process of DNA mutation, cell selection and population expansion. Early steps in this process are driven by a set of mutated driver genes and structural alterations to the genome through copy number gains or losses. Oesophageal adenocarcinoma (EAC) and the pre-invasive tissue, Barrett's oesophagus (BE), provide an ideal example in which to observe and study this evolution. BE displays early genomic instability, specifically in copy number changes that may later be observed in EAC. Furthermore, these early changes result in patterns of progression (that is, 'born bad', gradual or catastrophic) that may help to describe the evolution of EAC. As only a small proportion of patients with BE will go on to develop cancer, a better understanding of these patterns and the resulting genomic changes should improve early detection in EAC and may provide clues for the evolution of cancer more broadly.
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Affiliation(s)
- Sarah Killcoyne
- Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Rebecca C Fitzgerald
- Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge, UK.
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49
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Lucena-Perez M, Kleinman-Ruiz D, Marmesat E, Saveljev AP, Schmidt K, Godoy JA. Bottleneck-associated changes in the genomic landscape of genetic diversity in wild lynx populations. Evol Appl 2021; 14:2664-2679. [PMID: 34815746 PMCID: PMC8591332 DOI: 10.1111/eva.13302] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/17/2021] [Accepted: 09/08/2021] [Indexed: 01/06/2023] Open
Abstract
Demographic bottlenecks generally reduce genetic diversity through more intense genetic drift, but their net effect may vary along the genome due to the random nature of genetic drift and to local effects of recombination, mutation, and selection. Here, we analyzed the changes in genetic diversity following a bottleneck by comparing whole-genome diversity patterns in populations with and without severe recent documented declines of Iberian (Lynx pardinus, n = 31) and Eurasian lynx (Lynx lynx, n = 29). As expected, overall genomic diversity correlated negatively with bottleneck intensity and/or duration. Correlations of genetic diversity with divergence, chromosome size, gene or functional site content, GC content, or recombination were observed in nonbottlenecked populations, but were weaker in bottlenecked populations. Also, functional features under intense purifying selection and the X chromosome showed an increase in the observed density of variants, even resulting in higher θ W diversity than in nonbottlenecked populations. Increased diversity seems to be related to both a higher mutational input in those regions creating a large collection of low-frequency variants, a few of which increase in frequency during the bottleneck to the point they become detectable with our limited sample, and the reduced efficacy of purifying selection, which affects not only protein structure and function but also the regulation of gene expression. The results of this study alert to the possible reduction of fitness and adaptive potential associated with the genomic erosion in regulatory elements. Further, the detection of a gain of diversity in ultra-conserved elements can be used as a sensitive and easy-to-apply signature of genetic erosion in wild populations.
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Affiliation(s)
- Maria Lucena-Perez
- Departamento de Ecología Integrativa Estación Biológica de Doñana (CSIC) Sevilla Spain
| | - Daniel Kleinman-Ruiz
- Departamento de Ecología Integrativa Estación Biológica de Doñana (CSIC) Sevilla Spain
- Departamento de Genética Facultad de Biología Universidad Complutense Madrid Spain
| | - Elena Marmesat
- Departamento de Ecología Integrativa Estación Biológica de Doñana (CSIC) Sevilla Spain
| | - Alexander P Saveljev
- Department of Animal Ecology Russian Research Institute of Game Management and Fur Farming Kirov Russia
| | - Krzysztof Schmidt
- Mammal Research Institute Polish Academy of Sciences Białowieża Poland
| | - José A Godoy
- Departamento de Ecología Integrativa Estación Biológica de Doñana (CSIC) Sevilla Spain
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50
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Kaiser VB, Talmane L, Kumar Y, Semple F, MacLennan M, FitzPatrick DR, Taylor MS, Semple CA. Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome. Genome Res 2021; 31:1994-2007. [PMID: 34417209 PMCID: PMC8559717 DOI: 10.1101/gr.275407.121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 08/19/2021] [Indexed: 12/03/2022]
Abstract
Mutation in the germline is the ultimate source of genetic variation, but little is known about the influence of germline chromatin structure on mutational processes. Using ATAC-seq, we profile the open chromatin landscape of human spermatogonia, the most proliferative cell type of the germline, identifying transcription factor binding sites (TFBSs) and PRDM9 binding sites, a subset of which will initiate meiotic recombination. We observe an increase in rare structural variant (SV) breakpoints at PRDM9-bound sites, implicating meiotic recombination in the generation of structural variation. Many germline TFBSs, such as NRF1, are also associated with increased rates of SV breakpoints, apparently independent of recombination. Singleton short insertions (≥5 bp) are highly enriched at TFBSs, particularly at sites bound by testis active TFs, and their rates correlate with those of structural variant breakpoints. Short insertions often duplicate the TFBS motif, leading to clustering of motif sites near regulatory regions in this male-driven evolutionary process. Increased mutation loads at germline TFBSs disproportionately affect neural enhancers with activity in spermatogonia, potentially altering neurodevelopmental regulatory architecture. Local chromatin structure in spermatogonia is thus pervasive in shaping both evolution and disease.
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Affiliation(s)
- Vera B Kaiser
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - Lana Talmane
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - Yatendra Kumar
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - Fiona Semple
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - Marie MacLennan
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - David R FitzPatrick
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - Martin S Taylor
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - Colin A Semple
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, The University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
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