1
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Yin Z(S, Wang Z. Strategies for engineering oncolytic viruses to enhance cancer immunotherapy. Front Pharmacol 2024; 15:1450203. [PMID: 39309012 PMCID: PMC11413971 DOI: 10.3389/fphar.2024.1450203] [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: 06/17/2024] [Accepted: 07/30/2024] [Indexed: 09/25/2024] Open
Abstract
Non-small cell lung cancer (NSCLC) is the predominant form of lung cancer and is characterized by rapid metastasis and high mortality, presenting a challenge for early-stage treatment modalities. The heterogeneity of NSCLC's tumor microenvironment (TME) significantly influences the efficacy of anti-PD-1 immune checkpoint inhibitors (ICIs) therapy, leading to varied patient responses. This review characterized different strains of oncolytic viruses in NSCLC and the different gene edits in pre-existing oncolytic viruses. This study also aimed to provide strategies to enhance anti-PD-1 therapy in NSCLC by engineering oncolytic viruses (OVs). This study offers insights into the genomic adaptations necessary for OVs targeting NSCLC, identify genetic determinants of anti-PD-1 response variability, and propose genomic edits to bolster therapy effectiveness. The primary goal of this study is to present a theoretically designed OV with a detailed genomic framework capable of enhancing the response to anti-PD-1 therapy, thereby advancing the field of cancer immunotherapy.
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Affiliation(s)
| | - Zhengfeng Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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2
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Dietzen M, Zhai H, Lucas O, Pich O, Barrington C, Lu WT, Ward S, Guo Y, Hynds RE, Zaccaria S, Swanton C, McGranahan N, Kanu N. Replication timing alterations are associated with mutation acquisition during breast and lung cancer evolution. Nat Commun 2024; 15:6039. [PMID: 39019871 PMCID: PMC11255325 DOI: 10.1038/s41467-024-50107-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 07/01/2024] [Indexed: 07/19/2024] Open
Abstract
During each cell cycle, the process of DNA replication timing is tightly regulated to ensure the accurate duplication of the genome. The extent and significance of alterations in this process during malignant transformation have not been extensively explored. Here, we assess the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find that 6%-18% of the cancer genome exhibits ART, with regions with a change from early to late replication displaying an increased mutation rate and distinct mutational signatures. Whereas regions changing from late to early replication contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART occurs relatively early during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.
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Affiliation(s)
- Michelle Dietzen
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Haoran Zhai
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Olivia Lucas
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK
- Department of Oncology, University College London Hospitals, London, UK
| | - Oriol Pich
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Christopher Barrington
- Bioinformatics and Biostatistics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Wei-Ting Lu
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Sophia Ward
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Advanced Sequencing Facility, The Francis Crick Institute, London, UK
| | - Yanping Guo
- CRUK Flow Cytometry Translational Technology Platform, UCL Cancer Institute, London, UK
| | - Robert E Hynds
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Simone Zaccaria
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Department of Oncology, University College London Hospitals, London, UK
| | - Nicholas McGranahan
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
| | - Nnennaya Kanu
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
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3
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Németh E, Szüts D. The mutagenic consequences of defective DNA repair. DNA Repair (Amst) 2024; 139:103694. [PMID: 38788323 DOI: 10.1016/j.dnarep.2024.103694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/10/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
Multiple separate repair mechanisms safeguard the genome against various types of DNA damage, and their failure can increase the rate of spontaneous mutagenesis. The malfunction of distinct repair mechanisms leads to genomic instability through different mutagenic processes. For example, defective mismatch repair causes high base substitution rates and microsatellite instability, whereas homologous recombination deficiency is characteristically associated with deletions and chromosome instability. This review presents a comprehensive collection of all mutagenic phenotypes associated with the loss of each DNA repair mechanism, drawing on data from a variety of model organisms and mutagenesis assays, and placing greatest emphasis on systematic analyses of human cancer datasets. We describe the latest theories on the mechanism of each mutagenic process, often explained by reliance on an alternative repair pathway or the error-prone replication of unrepaired, damaged DNA. Aided by the concept of mutational signatures, the genomic phenotypes can be used in cancer diagnosis to identify defective DNA repair pathways.
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Affiliation(s)
- Eszter Németh
- Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary
| | - Dávid Szüts
- Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.
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4
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Yaacov A, Ben Cohen G, Landau J, Hope T, Simon I, Rosenberg S. Cancer mutational signatures identification in clinical assays using neural embedding-based representations. Cell Rep Med 2024; 5:101608. [PMID: 38866015 PMCID: PMC11228799 DOI: 10.1016/j.xcrm.2024.101608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 03/28/2024] [Accepted: 05/16/2024] [Indexed: 06/14/2024]
Abstract
While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.
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Affiliation(s)
- Adar Yaacov
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel; The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel; Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Gil Ben Cohen
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel; The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Jakob Landau
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel; The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tom Hope
- School of Computer Science and Engineering, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Itamar Simon
- Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shai Rosenberg
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel; The Wohl Institute for Translational Medicine, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
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5
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Salvadores M, Supek F. Cell cycle gene alterations associate with a redistribution of mutation risk across chromosomal domains in human cancers. NATURE CANCER 2024; 5:330-346. [PMID: 38200245 DOI: 10.1038/s43018-023-00707-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 12/11/2023] [Indexed: 01/12/2024]
Abstract
Mutations in human cells exhibit increased burden in heterochromatic, late DNA replication time (RT) chromosomal domains, with variation in mutation rates between tissues mirroring variation in heterochromatin and RT. We observed that regional mutation risk further varies between individual tumors in a manner independent of cell type, identifying three signatures of domain-scale mutagenesis in >4,000 tumor genomes. The major signature reflects remodeling of heterochromatin and of the RT program domains seen across tumors, tissues and cultured cells, and is robustly linked with higher expression of cell proliferation genes. Regional mutagenesis is associated with loss of activity of the tumor-suppressor genes RB1 and TP53, consistent with their roles in cell cycle control, with distinct mutational patterns generated by the two genes. Loss of regional heterogeneity in mutagenesis is associated with deficiencies in various DNA repair pathways. These mutation risk redistribution processes modify the mutation supply towards important genes, diverting the course of somatic evolution.
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Affiliation(s)
- Marina Salvadores
- Genome Data Science, Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Fran Supek
- Genome Data Science, Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain.
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain.
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6
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Weiner AC, Williams MJ, Shi H, Vázquez-García I, Salehi S, Rusk N, Aparicio S, Shah SP, McPherson A. Single-cell DNA replication dynamics in genomically unstable cancers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.10.536250. [PMID: 37090647 PMCID: PMC10120671 DOI: 10.1101/2023.04.10.536250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Dysregulated DNA replication is both a cause and a consequence of aneuploidy, yet the dynamics of DNA replication in aneuploid cell populations remains understudied. We developed a new method, PERT, for inferring cell-specific DNA replication states from single-cell whole genome sequencing, and investigated clone-specific DNA replication dynamics in >50,000 cells obtained from a collection of aneuploid and clonally heterogeneous cell lines, xenografts and primary cancer tissues. Clone replication timing (RT) profiles correlated with future copy number changes in serially passaged cell lines. Cell type was the strongest determinant of RT heterogeneity, while whole genome doubling and mutational process were associated with accumulation of late S-phase cells and weaker RT associations. Copy number changes affecting chromosome X had striking impact on RT, with loss of the inactive X allele shifting replication earlier, and loss of inactive Xq resulting in reactivation of Xp. Finally, analysis of time series xenografts illustrate how cell cycle distributions approximate clone proliferation, recapitulating expected relationships between proliferation and fitness in treatment-naive and chemotherapeutic contexts.
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Affiliation(s)
- Adam C Weiner
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Marc J Williams
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hongyu Shi
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ignacio Vázquez-García
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sohrab Salehi
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nicole Rusk
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Samuel Aparicio
- Department of Molecular Oncology, British Columbia Cancer, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Sohrab P Shah
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew McPherson
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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7
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Vardi-Yaacov O, Yaacov A, Rosenberg S, Simon I. Both cell autonomous and non-autonomous processes modulate the association between replication timing and mutation rate. Sci Rep 2023; 13:13143. [PMID: 37573368 PMCID: PMC10423235 DOI: 10.1038/s41598-023-39463-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 07/26/2023] [Indexed: 08/14/2023] Open
Abstract
Cancer somatic mutations are the product of multiple mutational and repair processes, some of which are tightly associated with DNA replication. Mutation rates (MR) are known to be higher in late replication timing (RT) regions, but different processes can affect this association. Systematic analysis of the mutational landscape of 2787 tumors from 32 tumor types revealed that approximately one third of the tumor samples show weak association between replication timing and mutation rate. Further analyses revealed that those samples have unique mutational signatures and are enriched with mutations in genes involved in DNA replication, DNA repair and chromatin structure. Surprisingly, analysis of differentially expressed genes between weak and strong RT-MR association groups revealed that tumors with weak association are enriched with genes associated with cell-cell communication and the immune system, suggesting a non-autonomous response to DNA damage.
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Affiliation(s)
- Oriya Vardi-Yaacov
- Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Adar Yaacov
- Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- Sharett Institute for Oncology, The Gaffin Center for Neuro-Oncology, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
- The Wohl Institute for Translational Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Shai Rosenberg
- Sharett Institute for Oncology, The Gaffin Center for Neuro-Oncology, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
- The Wohl Institute for Translational Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Itamar Simon
- Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
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8
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Caballero M, Koren A. The landscape of somatic mutations in lymphoblastoid cell lines. CELL GENOMICS 2023; 3:100305. [PMID: 37388907 PMCID: PMC10300552 DOI: 10.1016/j.xgen.2023.100305] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/03/2023] [Accepted: 03/28/2023] [Indexed: 07/01/2023]
Abstract
Somatic mutations have important biological ramifications while exerting substantial rate, type, and genomic location heterogeneity. Yet, their sporadic occurrence makes them difficult to study at scale and across individuals. Lymphoblastoid cell lines (LCLs), a model system for human population and functional genomics, harbor large numbers of somatic mutations and have been extensively genotyped. By comparing 1,662 LCLs, we report that the mutational landscape of the genome varies across individuals in terms of the number of mutations, their genomic locations, and their spectra; this variation may itself be modulated by somatic trans-acting mutations. Mutations attributed to the translesion DNA polymerase η follow two different modes of formation, with one mode accounting for the hypermutability of the inactive X chromosome. Nonetheless, the distribution of mutations along the inactive X chromosome appears to follow an epigenetic memory of the active form.
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Affiliation(s)
- Madison Caballero
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Amnon Koren
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
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9
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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] [Grants] [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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10
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Yaacov A, Rosenberg S, Simon I. Mutational signatures association with replication timing in normal cells reveals similarities and differences with matched cancer tissues. Sci Rep 2023; 13:7833. [PMID: 37188696 DOI: 10.1038/s41598-023-34631-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 05/04/2023] [Indexed: 05/17/2023] Open
Abstract
Mutational signatures' association with replication timing (RT) has been studied in cancer samples, but the RT distribution of somatic mutations in non-cancerous cells was only minimally explored. Here, we performed comprehensive analyses of mutational signatures in 2.9 million somatic mutations across multiple non-cancerous tissues, stratified by early and late RT regions. We found that many mutational processes are active mainly or solely in early RT, such as SBS16 in hepatocytes and SBS88 in the colon, or in late RT, such as SBS4 in lung and hepatocytes, and SBS18 across many tissues. The two ubiquitous signatures, SBS1 and SBS5, showed late and early bias, respectively, across multiple tissues and in mutations representing germ cells. We also performed a direct comparison with cancer samples in 4 matched tissue-cancer types. Unexpectedly, while for most signatures the RT bias was consistent in normal tissue and in cancer, we found that SBS1's late RT bias is lost in cancer.
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Affiliation(s)
- Adar Yaacov
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
- The Wohl Institute for Translational Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
- Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shai Rosenberg
- Gaffin Center for Neuro-Oncology, Sharett Institute for Oncology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
- The Wohl Institute for Translational Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Itamar Simon
- Department of Microbiology and Molecular Genetics, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
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11
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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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12
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The comparison of cancer gene mutation frequencies in Chinese and U.S. patient populations. Nat Commun 2022; 13:5651. [PMID: 36163440 PMCID: PMC9512793 DOI: 10.1038/s41467-022-33351-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 09/12/2022] [Indexed: 12/24/2022] Open
Abstract
Knowing the mutation frequency of cancer genes in China is crucial for reducing the global health burden. We integrate the tumor epidemiological statistics with cancer gene mutation rates identified in 11,948 cancer patients to determine their weighted proportions within a Chinese cancer patient cohort. TP53 (51.4%), LRP1B (13.4%), PIK3CA (11.6%), KRAS (11.1%), EGFR (10.6%), and APC (10.5%) are identified as the top mutated cancer genes in China. Additionally, 18 common cancer types from both China and U.S. cohorts are analyzed and classified into three patterns principally based upon TP53 mutation rates: TP53-Top, TP53-Plus, and Non-TP53. Next, corresponding similarities and prominent differences are identified upon comparing the mutational profiles from both cohorts. Finally, the potential population-specific and environmental risk factors underlying the disparities in cancer gene mutation rates between the U.S. and China are analyzed. Here, we show and compare the mutation rates of cancer genes in Chinese and U.S. population cohorts, for a better understanding of the associated etiological and epidemiological factors, which are important for cancer prevention and therapy.
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13
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KIF26B in the Prognosis and Immune Biomarking of Various Cancers: A Pan-Cancer Study. JOURNAL OF ONCOLOGY 2022; 2022:4829697. [PMID: 35359341 PMCID: PMC8964195 DOI: 10.1155/2022/4829697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 01/08/2022] [Accepted: 01/12/2022] [Indexed: 11/26/2022]
Abstract
KIF26B has been identified as an oncogene in several tumors; however, its utility as a prognostic indicator for various cancers has not yet been comprehensively evaluated. Here, we first examined how KIF26B intervenes in thirty-three cancers within the TCGA database, including potential immunological functions, and how it affects the prognosis. Based on the open databases TCGA, TIMER2, GEPIA2, GTEx, CPTAC, and HPA, we found that, when compared with normal tissues, KIF26B is overexpressed in 22 tumor tissues. Following a survival analysis, a relationship between the expression of KIF26B and the prognosis of various cancers was observed. Among the genetic alterations assessed, mutations were the most frequent. On the contrary, high phosphorylation levels of S977 were detected in breast cancer, KIRC, LUAD, and UCEC. We also found positive or negative correlations between KIF26B and the immune infiltration of endothelial cells and cancer-associated fibroblast infiltration. This could imply that patients may benefit from immunotherapy. Finally, KEGG pathways and GO enrichment analyses were implemented to identify the molecular mechanisms of KIF26B. This study illustrates the function of KIF26B from a pan-cancer perspective and offers a new horizon for cancer prognostic and immunotherapeutic investigations.
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