1
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Shahrouzi P, Forouz F, Mathelier A, Kristensen VN, Duijf PHG. Copy number alterations: a catastrophic orchestration of the breast cancer genome. Trends Mol Med 2024:S1471-4914(24)00120-5. [PMID: 38772764 DOI: 10.1016/j.molmed.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 04/12/2024] [Accepted: 04/26/2024] [Indexed: 05/23/2024]
Abstract
Breast cancer (BCa) is a prevalent malignancy that predominantly affects women around the world. Somatic copy number alterations (CNAs) are tumor-specific amplifications or deletions of DNA segments that often drive BCa development and therapy resistance. Hence, the complex patterns of CNAs complement BCa classification systems. In addition, understanding the precise contributions of CNAs is essential for tailoring personalized treatment approaches. This review highlights how tumor evolution drives the acquisition of CNAs, which in turn shape the genomic landscapes of BCas. It also discusses advanced methodologies for identifying recurrent CNAs, studying CNAs in BCa and their clinical impact.
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Affiliation(s)
- Parastoo Shahrouzi
- Department of Medical Genetics, Institute of Basic Medical Science, Faculty of Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway.
| | - Farzaneh Forouz
- School of Pharmacy, University of Queensland, Woolloongabba, Brisbane, Australia
| | - Anthony Mathelier
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway; Center for Bioinformatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway; Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Vessela N Kristensen
- Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway; Division of Medicine, Department of Clinical Molecular Biology and Laboratory Science (EpiGen), Akershus University Hospital, Lørenskog, Norway; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Pascal H G Duijf
- Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway; Centre for Cancer Biology, UniSA Clinical and Health Sciences, University of South Australia and SA Pathology, Adelaide, Australia.
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2
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Chavez-Pineda OG, Rodriguez-Moncayo R, Gonzalez-Suarez AM, Guevara-Pantoja PE, Maravillas-Montero JL, Garcia-Cordero JL. Portable platform for leukocyte extraction from blood using sheath-free microfluidic DLD. LAB ON A CHIP 2024; 24:2575-2589. [PMID: 38646820 DOI: 10.1039/d4lc00132j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Leukocyte count is routinely performed for diagnostic purposes and is rapidly emerging as a significant biomarker for a wide array of diseases. Additionally, leukocytes have demonstrated considerable promise in novel cell-based immunotherapies. However, the direct retrieval of leukocytes from whole blood is a significant challenge due to their low abundance compared to erythrocytes. Here, we introduce a microfluidic-based platform that isolates and recovers leukocytes from diluted whole blood in a single step. Our platform utilizes a novel, sheathless method to initially sediment and focus blood cells into a dense stream while flowing through a tubing before entering the microfluidic device. A hexagonal-shaped structure, patterned at the device's inlet, directs all the blood cells against the channel's outer walls. The focused cells are then separated based on their size using the deterministic lateral displacement (DLD) microfluidic technique. We evaluated various parameters that could influence leukocyte separation, including different focusing structures (assessed both computationally and experimentally), the orientation of the tubing-chip interface, the effects of blood sample hematocrit (dilution), and flow rate. Our device demonstrated the ability to isolate leukocytes from diluted blood with a separation efficiency of 100%, a recovery rate of 76%, and a purity of 80%, while maintaining a cell viability of 98%. The device operates for over 30 min at a flow rate of 2 μL min-1. Furthermore, we developed a handheld pressure controller to drive fluid flow, enhancing the operability of our platform outside of central laboratories and enabling near-patient testing. Our platform can be integrated with downstream cell-based assays and analytical methods that require high leukocyte purity (80%), ranging from cell counting to diagnostics and cell culture applications.
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Affiliation(s)
- Oriana G Chavez-Pineda
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB), Centro de Investigación y de Estudios Avanzados (Cinvestav), Monterrey, NL, Mexico
| | - Roberto Rodriguez-Moncayo
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB), Centro de Investigación y de Estudios Avanzados (Cinvestav), Monterrey, NL, Mexico
| | - Alan M Gonzalez-Suarez
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB), Centro de Investigación y de Estudios Avanzados (Cinvestav), Monterrey, NL, Mexico
| | - Pablo E Guevara-Pantoja
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB), Centro de Investigación y de Estudios Avanzados (Cinvestav), Monterrey, NL, Mexico
| | - Jose L Maravillas-Montero
- Red de Apoyo a la Investigación, Universidad Nacional Autónoma de México e Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City14080, Mexico
| | - Jose L Garcia-Cordero
- Laboratory of Microtechnologies Applied to Biomedicine (LMAB), Centro de Investigación y de Estudios Avanzados (Cinvestav), Monterrey, NL, Mexico
- Institute of Human Biology (IHB), Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel 4058, Switzerland.
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3
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Liu Y, Edrisi M, Yan Z, A Ogilvie H, Nakhleh L. NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model. Algorithms Mol Biol 2024; 19:18. [PMID: 38685065 PMCID: PMC11059640 DOI: 10.1186/s13015-024-00264-4] [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: 12/09/2023] [Accepted: 03/27/2024] [Indexed: 05/02/2024] Open
Abstract
Copy number aberrations (CNAs) are ubiquitous in many types of cancer. Inferring CNAs from cancer genomic data could help shed light on the initiation, progression, and potential treatment of cancer. While such data have traditionally been available via "bulk sequencing," the more recently introduced techniques for single-cell DNA sequencing (scDNAseq) provide the type of data that makes CNA inference possible at the single-cell resolution. We introduce a new birth-death evolutionary model of CNAs and a Bayesian method, NestedBD, for the inference of evolutionary trees (topologies and branch lengths with relative mutation rates) from single-cell data. We evaluated NestedBD's performance using simulated data sets, benchmarking its accuracy against traditional phylogenetic tools as well as state-of-the-art methods. The results show that NestedBD infers more accurate topologies and branch lengths, and that the birth-death model can improve the accuracy of copy number estimation. And when applied to biological data sets, NestedBD infers plausible evolutionary histories of two colorectal cancer samples. NestedBD is available at https://github.com/Androstane/NestedBD .
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Affiliation(s)
- Yushu Liu
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA.
| | - Mohammadamin Edrisi
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA
| | - Zhi Yan
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA
| | - Huw A Ogilvie
- Department of Genetics, University of Texas MD Anderson Cancer Center, TX, 77030, Houston, USA
| | - Luay Nakhleh
- Department of Computer Science, Rice University, 6100 Main St, Houston, 77005, TX, USA
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4
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Zhang N, Harbers L, Simonetti M, Diekmann C, Verron Q, Berrino E, Bellomo SE, Longo GMC, Ratz M, Schultz N, Tarish F, Su P, Han B, Wang W, Onorato S, Grassini D, Ballarino R, Giordano S, Yang Q, Sapino A, Frisén J, Alkass K, Druid H, Roukos V, Helleday T, Marchiò C, Bienko M, Crosetto N. High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue. Nat Commun 2024; 15:3475. [PMID: 38658552 PMCID: PMC11043350 DOI: 10.1038/s41467-024-47664-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 04/09/2024] [Indexed: 04/26/2024] Open
Abstract
Somatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we perform multi-region, single-cell DNA sequencing to characterize the SCNA landscape across tumor-rich and normal tissue in two male patients with localized prostate cancer. We identify two distinct karyotypes: 'pseudo-diploid' cells harboring few SCNAs and highly aneuploid cells. Pseudo-diploid cells form numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones. In contrast, aneuploid cells do not form subclones and are detected throughout the prostate, including normal tissue regions. Highly localized pseudo-diploid subclones are confined within tumor-rich regions and carry deletions in multiple tumor-suppressor genes. Our study reveals that SCNAs are widespread in normal and tumor regions across the prostate in localized prostate cancer patients and suggests that a subset of pseudo-diploid cells drive tumorigenesis in the aging prostate.
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Affiliation(s)
- Ning Zhang
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, 250012, China
| | - Luuk Harbers
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
| | - Michele Simonetti
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
| | - Constantin Diekmann
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
| | - Quentin Verron
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
| | - Enrico Berrino
- Candiolo Cancer Institute, FPO - IRCCS, Candiolo, SP142, km 3,95, 10060, Turin, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Sara E Bellomo
- Candiolo Cancer Institute, FPO - IRCCS, Candiolo, SP142, km 3,95, 10060, Turin, Italy
- Department of Oncology, University of Turin, Turin, Italy
| | | | - Michael Ratz
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, 17177, Sweden
| | - Niklas Schultz
- Science for Life Laboratory, Stockholm, 17177, Sweden
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, 17177, Sweden
| | | | - Peng Su
- Department of Pathology, Qilu Hospital of Shandong University, Ji'nan, 250012, China
| | - Bo Han
- Department of Pathology, Qilu Hospital of Shandong University, Ji'nan, 250012, China
| | - Wanzhong Wang
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, 17177, Sweden
| | - Sofia Onorato
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
| | - Dora Grassini
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Roberto Ballarino
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
| | - Silvia Giordano
- Candiolo Cancer Institute, FPO - IRCCS, Candiolo, SP142, km 3,95, 10060, Turin, Italy
- Department of Oncology, University of Turin, Turin, Italy
| | - Qifeng Yang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Ji'nan, 250012, China
| | - Anna Sapino
- Candiolo Cancer Institute, FPO - IRCCS, Candiolo, SP142, km 3,95, 10060, Turin, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Jonas Frisén
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, 17177, Sweden
| | - Kanar Alkass
- Department of Cell and Molecular Biology, Karolinska Institute, Stockholm, 17177, Sweden
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, 17177, Sweden
| | - Henrik Druid
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, 17177, Sweden
| | - Vassilis Roukos
- Institute of Molecular Biology (IMB), Mainz, 55128, Germany
- Department of General Biology, Medical School, University of Patras, Patras, Greece
| | - Thomas Helleday
- Science for Life Laboratory, Stockholm, 17177, Sweden
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, 17177, Sweden
| | - Caterina Marchiò
- Candiolo Cancer Institute, FPO - IRCCS, Candiolo, SP142, km 3,95, 10060, Turin, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Magda Bienko
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden
- Science for Life Laboratory, Stockholm, 17177, Sweden
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
| | - Nicola Crosetto
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17177, Sweden.
- Science for Life Laboratory, Stockholm, 17177, Sweden.
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy.
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5
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Jubran J, Slutsky R, Rozenblum N, Rokach L, Ben-David U, Yeger-Lotem E. Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes. Genome Biol 2024; 25:95. [PMID: 38622679 PMCID: PMC11020441 DOI: 10.1186/s13059-024-03225-7] [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: 07/05/2023] [Accepted: 03/26/2024] [Indexed: 04/17/2024] Open
Abstract
BACKGROUND Aneuploidy, an abnormal number of chromosomes within a cell, is a hallmark of cancer. Patterns of aneuploidy differ across cancers, yet are similar in cancers affecting closely related tissues. The selection pressures underlying aneuploidy patterns are not fully understood, hindering our understanding of cancer development and progression. RESULTS Here, we apply interpretable machine learning methods to study tissue-selective aneuploidy patterns. We define 20 types of features corresponding to genomic attributes of chromosome-arms, normal tissues, primary tumors, and cancer cell lines (CCLs), and use them to model gains and losses of chromosome arms in 24 cancer types. To reveal the factors that shape the tissue-specific cancer aneuploidy landscapes, we interpret the machine learning models by estimating the relative contribution of each feature to the models. While confirming known drivers of positive selection, our quantitative analysis highlights the importance of negative selection for shaping aneuploidy landscapes. This is exemplified by tumor suppressor gene density being a better predictor of gain patterns than oncogene density, and vice versa for loss patterns. We also identify the importance of tissue-selective features and demonstrate them experimentally, revealing KLF5 as an important driver for chr13q gain in colon cancer. Further supporting an important role for negative selection in shaping the aneuploidy landscapes, we find compensation by paralogs to be among the top predictors of chromosome arm loss prevalence and demonstrate this relationship for one paralog interaction. Similar factors shape aneuploidy patterns in human CCLs, demonstrating their relevance for aneuploidy research. CONCLUSIONS Our quantitative, interpretable machine learning models improve the understanding of the genomic properties that shape cancer aneuploidy landscapes.
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Affiliation(s)
- Juman Jubran
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel
| | - Rachel Slutsky
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Nir Rozenblum
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lior Rokach
- Department of Software & Information Systems Engineering, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel
| | - Uri Ben-David
- Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel.
- The National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, 84105, Beer Sheva, Israel.
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6
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Liu X, Zhang K, Kaya NA, Jia Z, Wu D, Chen T, Liu Z, Zhu S, Hillmer AM, Wuestefeld T, Liu J, Chan YS, Hu Z, Ma L, Jiang L, Zhai W. Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma. Nat Commun 2024; 15:3169. [PMID: 38609353 PMCID: PMC11015015 DOI: 10.1038/s41467-024-47541-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 03/26/2024] [Indexed: 04/14/2024] Open
Abstract
Solid tumors are complex ecosystems with heterogeneous 3D structures, but the spatial intra-tumor heterogeneity (sITH) at the macroscopic (i.e., whole tumor) level is under-explored. Using a phylogeographic approach, we sequence genomes and transcriptomes from 235 spatially informed sectors across 13 hepatocellular carcinomas (HCC), generating one of the largest datasets for studying sITH. We find that tumor heterogeneity in HCC segregates into spatially variegated blocks with large genotypic and phenotypic differences. By dissecting the transcriptomic heterogeneity, we discover that 30% of patients had a "spatially competing distribution" (SCD), where different spatial blocks have distinct transcriptomic subtypes co-existing within a tumor, capturing the critical transition period in disease progression. Interestingly, the tumor regions with more advanced transcriptomic subtypes (e.g., higher cell cycle) often take clonal dominance with a wider geographic range, rejecting neutral evolution for SCD patients. Extending the statistical tests for detecting natural selection to many non-SCD patients reveal varying levels of selective signal across different tumors, implying that many evolutionary forces including natural selection and geographic isolation can influence the overall pattern of sITH. Taken together, tumor phylogeography unravels a dynamic landscape of sITH, pinpointing important evolutionary and clinical consequences of spatial heterogeneity in cancer.
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Affiliation(s)
- Xiaodong Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Ke Zhang
- Department of General Surgery, Beijing Ditan Hospital, Capital Medical University, No. 8, Jingshun East Street, Chaoyang District, Beijing, P.R. China
| | - Neslihan A Kaya
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Zhe Jia
- Department of General Surgery, Beijing Ditan Hospital, Capital Medical University, No. 8, Jingshun East Street, Chaoyang District, Beijing, P.R. China
| | - Dafei Wu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Tingting Chen
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Zhiyuan Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Sinan Zhu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Centre for Quantitative Medicine, Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Axel M Hillmer
- Institute of Pathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Torsten Wuestefeld
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Jin Liu
- Centre for Quantitative Medicine, Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Yun Shen Chan
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, China
| | - Zheng Hu
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Liang Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
| | - Li Jiang
- Department of General Surgery, Beijing Ditan Hospital, Capital Medical University, No. 8, Jingshun East Street, Chaoyang District, Beijing, P.R. China.
| | - Weiwei Zhai
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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7
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Butler G, Amend SR, Axelrod R, Venditti C, Pienta KJ. Punctuational evolution is pervasive in distal site metastatic colonization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.08.588529. [PMID: 38645078 PMCID: PMC11030309 DOI: 10.1101/2024.04.08.588529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
The evolution of metastasis represents a lethal stage of cancer progression. Yet, the evolutionary kinetics of metastatic disease remain unresolved. Here, using single cell CRISPR-Cas9 lineage tracing data, we show that in metastatic disease, gradual molecular evolution is punctuated by episodes of rapid evolutionary change associated with lineage divergence. By measuring punctuational effects across the metastatic cascade, we show that punctuational effects contribute more to the molecular diversity at distal site metastases compared to the paired primary tumor, suggesting qualitatively different modes of evolution may drive primary and metastatic tumor progression. This is the first empirical evidence for distinct patterns of molecular evolution at early and late stages of metastasis and demonstrates the complex interplay of cell intrinsic and extrinsic factors that shape lethal cancer.
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8
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Merteroglu M, Santoro MM. Exploiting the metabolic vulnerability of circulating tumour cells. Trends Cancer 2024:S2405-8033(24)00053-0. [PMID: 38580535 DOI: 10.1016/j.trecan.2024.03.004] [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: 11/22/2023] [Revised: 03/11/2024] [Accepted: 03/12/2024] [Indexed: 04/07/2024]
Abstract
Metastasis has a major part in the severity of disease and lethality of cancer. Circulating tumour cells (CTCs) represent a reservoir of metastatic precursors in circulation, most of which cannot survive due to hostile conditions in the bloodstream. Surviving cells colonise a secondary site based on a combination of physical, metabolic, and oxidative stress protection states required for that environment. Recent advances in CTC isolation methods and high-resolution 'omics technologies are revealing specific metabolic pathways that support this selection of CTCs. In this review, we discuss recent advances in our understanding of CTC biology and discoveries of adaptations in metabolic pathways during their selection. Understanding these traits and delineating mechanisms by which they confer acquired resistance or vulnerability in CTCs is crucial for developing successful prognostic and therapeutic strategies in cancer.
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9
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Lynch A, Bradford S, Burkard ME. The reckoning of chromosomal instability: past, present, future. Chromosome Res 2024; 32:2. [PMID: 38367036 DOI: 10.1007/s10577-024-09746-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 01/11/2024] [Accepted: 01/27/2024] [Indexed: 02/19/2024]
Abstract
Quantitative measures of CIN are crucial to our understanding of its role in cancer. Technological advances have changed the way CIN is quantified, offering increased accuracy and insight. Here, we review measures of CIN through its rise as a field, discuss considerations for its measurement, and look forward to future quantification of CIN.
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Affiliation(s)
- Andrew Lynch
- UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA
- McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI, USA
- Division of Hematology/Oncology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Shermineh Bradford
- UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA
- McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI, USA
- Division of Hematology/Oncology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Mark E Burkard
- UW Carbone Cancer Center, University of Wisconsin, Madison, WI, USA.
- McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI, USA.
- Division of Hematology/Oncology, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
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10
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Gardi N, Chaubal R, Parab P, Pachakar S, Kulkarni S, Shet T, Joshi S, Kembhavi Y, Chandrani P, Quist J, Kowtal P, Grigoriadis A, Sarin R, Govindarajan R, Gupta S. Natural History of Germline BRCA1 Mutated and BRCA Wild-type Triple-negative Breast Cancer. CANCER RESEARCH COMMUNICATIONS 2024; 4:404-417. [PMID: 38315150 PMCID: PMC10865976 DOI: 10.1158/2767-9764.crc-23-0277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/09/2023] [Accepted: 01/26/2024] [Indexed: 02/07/2024]
Abstract
We report a deep next-generation sequencing analysis of 13 sequentially obtained tumor samples, eight sequentially obtained circulating tumor DNA (ctDNA) samples and three germline DNA samples over the life history of 3 patients with triple-negative breast cancer (TNBC), 2 of whom had germline pathogenic BRCA1 mutation, to unravel tumor evolution. Tumor tissue from all timepoints and germline DNA was subjected to whole-exome sequencing (WES), custom amplicon deep sequencing (30,000X) of a WES-derived somatic mutation panel, and SNP arrays for copy-number variation (CNV), while whole transcriptome sequencing (RNA-seq) was performed only on somatic tumor.There was enrichment of homologous recombination deficiency signature in all tumors and widespread CNV, which remained largely stable over time. Somatic tumor mutation numbers varied between patients and within each patient (range: 70-216, one outlier). There was minimal mutational overlap between patients with TP53 being the sole commonly mutated gene, but there was substantial overlap in sequential samples in each patient. Each patient's tumor contained a founding ("stem") clone at diagnosis, which persisted over time, from which all other clones ("subclone") were derived ("branching evolution"), which contained mutations in well-characterized cancer-related genes like PDGFRB, ARID2, TP53 (Patient_02), TP53, BRAF, BRIP1, CSF3R (Patient_04), and TP53, APC, EZH2 (Patient_07). Including stem and subclones, tumors from all patients were polyclonal at diagnosis and during disease progression. ctDNA recapitulated most tissue-derived stem clonal and subclonal mutations while detecting some additional subclonal mutations. RNA-seq revealed a stable basal-like pattern, with most highly expressed variants belonging to stem clone. SIGNIFICANCE In germline BRCA1 mutated and BRCA wild-type patients, TNBC shows a branching evolutionary pattern of mutations with a single founding clone, are polyclonal throughout their disease course, and have widespread copy-number aberrations. This evolutionary pattern may be associated with treatment resistance or sensitivity and could be therapeutically exploited.
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Affiliation(s)
- Nilesh Gardi
- Department of Medical Oncology, Tata Memorial Centre, Mumbai
- Clinician Scientist Laboratory, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai
- Homi Bhabha National Institute, Mumbai
| | - Rohan Chaubal
- Clinician Scientist Laboratory, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai
- Homi Bhabha National Institute, Mumbai
- Department of Surgical Oncology, Tata Memorial Centre, Mumbai
| | - Pallavi Parab
- Department of Medical Oncology, Tata Memorial Centre, Mumbai
- Homi Bhabha National Institute, Mumbai
| | - Sunil Pachakar
- Department of Medical Oncology, Tata Memorial Centre, Mumbai
- Clinician Scientist Laboratory, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai
- Homi Bhabha National Institute, Mumbai
| | - Suyash Kulkarni
- Homi Bhabha National Institute, Mumbai
- Department of Radiodiagnosis, Tata Memorial Centre, Mumbai
| | - Tanuja Shet
- Homi Bhabha National Institute, Mumbai
- Department of Pathology, Tata Memorial Centre, Mumbai
| | - Shalaka Joshi
- Homi Bhabha National Institute, Mumbai
- Department of Surgical Oncology, Tata Memorial Centre, Mumbai
| | - Yogesh Kembhavi
- Department of Medical Oncology, Tata Memorial Centre, Mumbai
- Homi Bhabha National Institute, Mumbai
| | - Pratik Chandrani
- Department of Medical Oncology, Tata Memorial Centre, Mumbai
- Homi Bhabha National Institute, Mumbai
| | - Jelmar Quist
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
- Breast Cancer Now Unit, School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Pradnya Kowtal
- Homi Bhabha National Institute, Mumbai
- DNA sequencing Facility, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai
| | - Anita Grigoriadis
- Cancer Bioinformatics, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
- School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
- Breast Cancer Now Unit, School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Rajiv Sarin
- Homi Bhabha National Institute, Mumbai
- Department of Radiation Oncology, Tata Memorial Centre, Mumbai
| | | | - Sudeep Gupta
- Department of Medical Oncology, Tata Memorial Centre, Mumbai
- Clinician Scientist Laboratory, Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai
- Homi Bhabha National Institute, Mumbai
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11
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Qin F, Cai G, Amos CI, Xiao F. A statistical learning method for simultaneous copy number estimation and subclone clustering with single-cell sequencing data. Genome Res 2024; 34:85-93. [PMID: 38290978 PMCID: PMC10903939 DOI: 10.1101/gr.278098.123] [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: 05/15/2023] [Accepted: 01/08/2024] [Indexed: 02/01/2024]
Abstract
The availability of single-cell sequencing (SCS) enables us to assess intra-tumor heterogeneity and identify cellular subclones without the confounding effect of mixed cells. Copy number aberrations (CNAs) have been commonly used to identify subclones in SCS data using various clustering methods, as cells comprising a subpopulation are found to share a genetic profile. However, currently available methods may generate spurious results (e.g., falsely identified variants) in the procedure of CNA detection, thereby diminishing the accuracy of subclone identification within a large, complex cell population. In this study, we developed a subclone clustering method based on a fused lasso model, referred to as FLCNA, which can simultaneously detect CNAs in single-cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering and CNA detection performance of FLCNA, benchmarking it against existing copy number estimation methods (SCOPE, HMMcopy) in combination with commonly used clustering methods. Application of FLCNA to a scDNA-seq data set of breast cancer revealed different genomic variation patterns in neoadjuvant chemotherapy-treated samples and pretreated samples. We show that FLCNA is a practical and powerful method for subclone identification and CNA detection with scDNA-seq data.
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Affiliation(s)
- Fei Qin
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina 29208, USA
| | - Guoshuai Cai
- Department of Environmental Health Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina 29208, USA
| | - Christopher I Amos
- Department of Quantitative Sciences, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Feifei Xiao
- Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida 32603, USA
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12
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Baker TM, Waise S, Tarabichi M, Van Loo P. Aneuploidy and complex genomic rearrangements in cancer evolution. NATURE CANCER 2024; 5:228-239. [PMID: 38286829 PMCID: PMC7616040 DOI: 10.1038/s43018-023-00711-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 12/14/2023] [Indexed: 01/31/2024]
Abstract
Mutational processes that alter large genomic regions occur frequently in developing tumors. They range from simple copy number gains and losses to the shattering and reassembly of entire chromosomes. These catastrophic events, such as chromothripsis, chromoplexy and the formation of extrachromosomal DNA, affect the expression of many genes and therefore have a substantial effect on the fitness of the cells in which they arise. In this review, we cover large genomic alterations, the mechanisms that cause them and their effect on tumor development and evolution.
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Affiliation(s)
- Toby M Baker
- The Francis Crick Institute, London, UK
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sara Waise
- The Francis Crick Institute, London, UK
- Cancer Sciences Unit, University of Southampton, Southampton, UK
| | - Maxime Tarabichi
- The Francis Crick Institute, London, UK
- Institute for Interdisciplinary Research (IRIBHM), Université Libre de Bruxelles, Brussels, Belgium
| | - Peter Van Loo
- The Francis Crick Institute, London, UK.
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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13
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Wang RY, Kimmel M. A Countable-Type Branching Process Model for the Tug-of-War Cancer Cell Dynamics. Bull Math Biol 2024; 86:18. [PMID: 38236346 DOI: 10.1007/s11538-023-01245-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 12/13/2023] [Indexed: 01/19/2024]
Abstract
We consider a time-continuous Markov branching process of proliferating cells with a countable collection of types. Among-type transitions are inspired by the Tug-of-War process introduced by McFarland et al. (Proc Natl Acad Sci 111(42):15138-15143, 2014) as a mathematical model for competition of advantageous driver mutations and deleterious passenger mutations in cancer cells. We introduce a version of the model in which a driver mutation pushes the type of the cell L-units up, while a passenger mutation pulls it 1-unit down. The distribution of time to divisions depends on the type (fitness) of cell, which is an integer. The extinction probability given any initial cell type is strictly less than 1, which allows us to investigate the transition between types (type transition) in an infinitely long cell lineage of cells. The analysis leads to the result that under driver dominance, the type transition process escapes to infinity, while under passenger dominance, it leads to a limit distribution. Implications in cancer cell dynamics and population genetics are discussed.
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Affiliation(s)
- Ren-Yi Wang
- Department of Statistics, Rice University, Houston, TX, 77005, USA.
| | - Marek Kimmel
- Department of Statistics, Rice University, Houston, TX, 77005, USA
- Department of Systems Biology and Engineering, Silesian University of Technology, 44-100, Gliwice, Poland
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14
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Guo Y, Deng X, Wang S, Yuan Y, Guo Z, Hao H, Jiao Y, Li P, Han S. SILAC proteomics based on 3D cell spheroids unveils the role of RAC2 in regulating the crosstalk between triple-negative breast cancer cells and tumor-associated macrophages. Int J Biol Macromol 2024; 254:127639. [PMID: 37879580 DOI: 10.1016/j.ijbiomac.2023.127639] [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: 05/10/2023] [Revised: 09/29/2023] [Accepted: 10/21/2023] [Indexed: 10/27/2023]
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and is characterized by a high infiltration of tumor-associated macrophages (TAMs). TAMs contribute significantly to tumor progression by intricately interacting with tumor cells. Deeply investigating the interaction between TNBC cells and TAMs is of great importance for finding potential biomarkers and developing novel therapeutic strategies to further improve the clinical outcomes of TNBC patients. In this study, we confirmed the interplay using both 3D and 2D co-culture models. The stable-isotype labeling by amino acids in cell culture (SILAC)-based quantitative proteomics was conducted on 3D cell spheroids containing TNBC cells and macrophages to identify the potential candidate in regulating the crosstalk between TNBC and TAMs. Ras-related C3 botulinum toxin substrate 2 (RAC2) was identified as a potential molecule for further exploration, given its high expression in TNBC and positive correlation with M2 macrophage infiltration. The suppression of RAC2 inhibited TNBC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro. Meanwhile, knocking down RAC2 in TNBC cells impaired macrophage recruitment and M2 polarization. Mechanistically, RAC2 exerted its roles in TNBC cells and TAMs by regulating the activation of P65 NF-κB and P38 MAPK, while TAMs further elevated RAC2 expression and P65 NF-κB activation by secreting soluble mediators including IL-10. These findings highlight the significance of RAC2 as a crucial molecule in the crosstalk between TNBC and TAMs, suggesting it could be a promising therapeutic target in TNBC.
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Affiliation(s)
- Yang Guo
- Department of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking University, Beijing, PR China; Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Xinxin Deng
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Shan Wang
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Yuan Yuan
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Zhengwang Guo
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Huifeng Hao
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Yanna Jiao
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China
| | - Pingping Li
- Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China.
| | - Shuyan Han
- Department of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking University, Beijing, PR China; Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Department of Integration of Chinese and Western Medicine, Peking University Cancer Hospital and Institute, Beijing 100142, PR China.
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15
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Nguyen MTN, Rajavuori A, Huhtinen K, Hietanen S, Hynninen J, Oikkonen J, Hautaniemi S. Circulating tumor DNA-based copy-number profiles enable monitoring treatment effects during therapy in high-grade serous carcinoma. Biomed Pharmacother 2023; 168:115630. [PMID: 37806091 DOI: 10.1016/j.biopha.2023.115630] [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: 07/25/2023] [Revised: 09/23/2023] [Accepted: 10/03/2023] [Indexed: 10/10/2023] Open
Abstract
Circulating tumor DNA (ctDNA) analysis has emerged as a promising tool for detecting and profiling longitudinal genomics changes in cancer. While copy-number alterations (CNAs) play a major role in cancers, treatment effect monitoring using copy-number profiles has received limited attention as compared to mutations. A major reason for this is the insensitivity of CNA analysis for the real-life tumor-fraction ctDNA samples. We performed copy-number analysis on 152 plasma samples obtained from 29 patients with high-grade serous ovarian cancer (HGSC) using a sequencing panel targeting over 500 genes. Twenty-one patients had temporally matched tissue and plasma sample pairs, which enabled assessing concordance with tissues sequenced with the same panel or whole-genome sequencing and to evaluate sensitivity. Our approach could detect concordant CNA profiles in most plasma samples with as low as 5% tumor content and highly amplified regions in samples with ∼1% of tumor content. Longitudinal profiles showed changes in the CNA profiles in seven out of 11 patients with high tumor-content plasma samples at relapse. These changes included focal acquired or lost copy-numbers, even though most of the genome remained stable. Two patients displayed major copy-number profile changes during therapy. Our analysis revealed ctDNA-detectable subclonal selection resulting from both surgical operations and chemotherapy. Overall, longitudinal ctDNA data showed acquired and diminished CNAs at relapse when compared to pre-treatment samples. These results highlight the importance of genomic profiling during treatment as well as underline the usability of ctDNA.
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Affiliation(s)
- Mai T N Nguyen
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00291, Finland
| | - Anna Rajavuori
- Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4, Turku 20521, Finland
| | - Kaisa Huhtinen
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00291, Finland; Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, Turku 20014, Finland
| | - Sakari Hietanen
- Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4, Turku 20521, Finland
| | - Johanna Hynninen
- Department of Obstetrics and Gynecology, Turku University Hospital, Kiinamyllynkatu 4, Turku 20521, Finland
| | - Jaana Oikkonen
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00291, Finland.
| | - Sampsa Hautaniemi
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki 00291, Finland.
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16
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Herrera-Orozco H, García-Castillo V, López-Urrutia E, Martinez-Gutierrez AD, Pérez-Yepez E, Millán-Catalán O, Cantú de León D, López-Camarillo C, Jacobo-Herrera NJ, Rodríguez-Dorantes M, Ramos-Payán R, Pérez-Plasencia C. Somatic Copy Number Alterations in Colorectal Cancer Lead to a Differentially Expressed ceRNA Network (ceRNet). Curr Issues Mol Biol 2023; 45:9549-9565. [PMID: 38132443 PMCID: PMC10742218 DOI: 10.3390/cimb45120597] [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: 10/20/2023] [Revised: 11/14/2023] [Accepted: 11/21/2023] [Indexed: 12/23/2023] Open
Abstract
Colorectal cancer (CRC) represents the second deadliest malignancy worldwide. Around 75% of CRC patients exhibit high levels of chromosome instability that result in the accumulation of somatic copy number alterations. These alterations are associated with the amplification of oncogenes and deletion of tumor-ppressor genes and contribute to the tumoral phenotype in different malignancies. Even though this relationship is well known, much remains to be investigated regarding the effect of said alterations in long non-coding RNAs (lncRNAs) and, in turn, the impact these alterations have on the tumor phenotype. The present study aimed to evaluate the role of differentially expressed lncRNAs coded in regions with copy number alterations in colorectal cancer patient samples. We downloaded RNA-seq files of the Colorectal Adenocarcinoma Project from the The Cancer Genome Atlas (TCGA) repository (285 sequenced tumor tissues and 41 non-tumor tissues), evaluated differential expression, and mapped them over genome sequencing data with regions presenting copy number alterations. We obtained 78 differentially expressed (LFC > 1|< -1, padj < 0.05) lncRNAs, 410 miRNAs, and 5028 mRNAs and constructed a competing endogenous RNA (ceRNA) network, predicting significant lncRNA-miRNA-mRNA interactions. Said network consisted of 30 lncRNAs, 19 miRNAs, and 77 mRNAs. To understand the role that our ceRNA network played, we performed KEGG and GO analysis and found several oncogenic and anti-oncogenic processes enriched by the molecular players in our network. Finally, to evaluate the clinical relevance of the lncRNA expression, we performed survival analysis and found that C5orf64, HOTAIR, and RRN3P3 correlated with overall patient survival. Our results showed that lncRNAs coded in regions affected by SCNAs form a complex gene regulatory network in CCR.
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Affiliation(s)
- Héctor Herrera-Orozco
- Laboratorio de Genómica, FES-Iztacala, Universidad Nacional Autónoma de México. Av. De los Barrios 1, Los Reyes Iztacala, Tlalnepantla 54090, Mexico; (H.H.-O.); (V.G.-C.); (E.L.-U.)
- Posgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Edificio D. Circuito de Posgrados, Ciudad Universitaria, Coyoacán, Mexico City 04510, Mexico
| | - Verónica García-Castillo
- Laboratorio de Genómica, FES-Iztacala, Universidad Nacional Autónoma de México. Av. De los Barrios 1, Los Reyes Iztacala, Tlalnepantla 54090, Mexico; (H.H.-O.); (V.G.-C.); (E.L.-U.)
| | - Eduardo López-Urrutia
- Laboratorio de Genómica, FES-Iztacala, Universidad Nacional Autónoma de México. Av. De los Barrios 1, Los Reyes Iztacala, Tlalnepantla 54090, Mexico; (H.H.-O.); (V.G.-C.); (E.L.-U.)
| | - Antonio Daniel Martinez-Gutierrez
- Laboratorio de Genómica, Instituto Nacional de Cancerología, Av. San Fernando 22, Tlalpan, Mexico City 14080, Mexico; (A.D.M.-G.); (E.P.-Y.); (O.M.-C.); (D.C.d.L.)
| | - Eloy Pérez-Yepez
- Laboratorio de Genómica, Instituto Nacional de Cancerología, Av. San Fernando 22, Tlalpan, Mexico City 14080, Mexico; (A.D.M.-G.); (E.P.-Y.); (O.M.-C.); (D.C.d.L.)
| | - Oliver Millán-Catalán
- Laboratorio de Genómica, Instituto Nacional de Cancerología, Av. San Fernando 22, Tlalpan, Mexico City 14080, Mexico; (A.D.M.-G.); (E.P.-Y.); (O.M.-C.); (D.C.d.L.)
| | - David Cantú de León
- Laboratorio de Genómica, Instituto Nacional de Cancerología, Av. San Fernando 22, Tlalpan, Mexico City 14080, Mexico; (A.D.M.-G.); (E.P.-Y.); (O.M.-C.); (D.C.d.L.)
| | - César López-Camarillo
- Posgrado en Ciencias Genómicas, Universidad Autónoma de la Ciudad de México, Calle Dr. García Diego 168, Cuauhtémoc, Mexico City 06720, Mexico;
| | - Nadia J. Jacobo-Herrera
- Unidad de Bioquímica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Av. Vasco de Quiroga 15, Tlalpan, Mexico City 14080, Mexico;
| | | | - Rosalío Ramos-Payán
- Faculty of Chemical and Biological Sciences, Autonomous University of Sinaloa, Culiacan 80030, Mexico;
| | - Carlos Pérez-Plasencia
- Laboratorio de Genómica, FES-Iztacala, Universidad Nacional Autónoma de México. Av. De los Barrios 1, Los Reyes Iztacala, Tlalnepantla 54090, Mexico; (H.H.-O.); (V.G.-C.); (E.L.-U.)
- Laboratorio de Genómica, Instituto Nacional de Cancerología, Av. San Fernando 22, Tlalpan, Mexico City 14080, Mexico; (A.D.M.-G.); (E.P.-Y.); (O.M.-C.); (D.C.d.L.)
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17
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He F, Bandyopadhyay AM, Klesse LJ, Rogojina A, Chun SH, Butler E, Hartshorne T, Holland T, Garcia D, Weldon K, Prado LNP, Langevin AM, Grimes AC, Sugalski A, Shah S, Assanasen C, Lai Z, Zou Y, Kurmashev D, Xu L, Xie Y, Chen Y, Wang X, Tomlinson GE, Skapek SX, Houghton PJ, Kurmasheva RT, Zheng S. Genomic profiling of subcutaneous patient-derived xenografts reveals immune constraints on tumor evolution in childhood solid cancer. Nat Commun 2023; 14:7600. [PMID: 37990009 PMCID: PMC10663468 DOI: 10.1038/s41467-023-43373-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 11/07/2023] [Indexed: 11/23/2023] Open
Abstract
Subcutaneous patient-derived xenografts (PDXs) are an important tool for childhood cancer research. Here, we describe a resource of 68 early passage PDXs established from 65 pediatric solid tumor patients. Through genomic profiling of paired PDXs and patient tumors (PTs), we observe low mutational similarity in about 30% of the PT/PDX pairs. Clonal analysis in these pairs show an aggressive PT minor subclone seeds the major clone in the PDX. We show evidence that this subclone is more immunogenic and is likely suppressed by immune responses in the PT. These results suggest interplay between intratumoral heterogeneity and antitumor immunity may underlie the genetic disparity between PTs and PDXs. We further show that PDXs generally recapitulate PTs in copy number and transcriptomic profiles. Finally, we report a gene fusion LRPAP1-PDGFRA. In summary, we report a childhood cancer PDX resource and our study highlights the role of immune constraints on tumor evolution.
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Affiliation(s)
- Funan He
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
| | - Abhik M Bandyopadhyay
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Laura J Klesse
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Gill Center for Cancer and Blood Disorders, Children's Health Children's Medical Center, Dallas, TX, USA
| | - Anna Rogojina
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Sang H Chun
- Department of Biochemistry and Structural Biology, University of Texas Health Science Center, San Antonio, TX, USA
| | - Erin Butler
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Gill Center for Cancer and Blood Disorders, Children's Health Children's Medical Center, Dallas, TX, USA
| | - Taylor Hartshorne
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Trevor Holland
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Dawn Garcia
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Korri Weldon
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Luz-Nereida Perez Prado
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Anne-Marie Langevin
- Department of Pediatrics, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Allison C Grimes
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Pediatrics, University of Texas Health Science Center, San Antonio, TX, USA
| | - Aaron Sugalski
- Department of Pediatrics, University of Texas Health Science Center, San Antonio, TX, USA
| | - Shafqat Shah
- Department of Pediatrics, University of Texas Health Science Center, San Antonio, TX, USA
| | - Chatchawin Assanasen
- Department of Pediatrics, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Zhao Lai
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Yi Zou
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Dias Kurmashev
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Lin Xu
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yang Xie
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yidong Chen
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Xiaojing Wang
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Gail E Tomlinson
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Pediatrics, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
| | - Stephen X Skapek
- Department of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Gill Center for Cancer and Blood Disorders, Children's Health Children's Medical Center, Dallas, TX, USA
| | - Peter J Houghton
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Raushan T Kurmasheva
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA.
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA.
- Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX, USA.
| | - Siyuan Zheng
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX, USA.
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA.
- Mays Cancer Center, University of Texas Health Science Center, San Antonio, TX, USA.
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18
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Kinnaman MD, Zaccaria S, Makohon-Moore A, Arnold B, Levine MF, Gundem G, Arango Ossa JE, Glodzik D, Rodríguez-Sánchez MI, Bouvier N, Li S, Stockfisch E, Dunigan M, Cobbs C, Bhanot UK, You D, Mullen K, Melchor JP, Ortiz MV, O'Donohue TJ, Slotkin EK, Wexler LH, Dela Cruz FS, Hameed MR, Glade Bender JL, Tap WD, Meyers PA, Papaemmanuil E, Kung AL, Iacobuzio-Donahue CA. Subclonal Somatic Copy-Number Alterations Emerge and Dominate in Recurrent Osteosarcoma. Cancer Res 2023; 83:3796-3812. [PMID: 37812025 PMCID: PMC10646480 DOI: 10.1158/0008-5472.can-23-0385] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 07/14/2023] [Accepted: 09/01/2023] [Indexed: 10/10/2023]
Abstract
Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. We conducted longitudinal whole-genome sequencing of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. Subclonal copy-number alterations were identified in all patients except one. In 5 patients, subclones from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clones in 6 of 7 patients with multiple clones. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy-number clones. A chromosomal duplication timing analysis revealed that complex genomic rearrangements typically occurred prior to diagnosis, supporting a macroevolutionary model of evolution, where a large number of genomic aberrations are acquired over a short period of time followed by clonal selection, as opposed to ongoing evolution. A mutational signature analysis of recurrent tumors revealed that homologous repair deficiency (HRD)-related SBS3 increases at each time point in patients with recurrent disease, suggesting that HRD continues to be an active mutagenic process after diagnosis. Overall, by examining the clonal relationships between temporally and spatially separated samples from patients with relapsed/refractory osteosarcoma, this study sheds light on the intratumor heterogeneity and potential drivers of treatment resistance in this disease. SIGNIFICANCE The chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.
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Affiliation(s)
- Michael D. Kinnaman
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Regeneron Pharmaceuticals, Inc., Tarrytown, New York
| | - Simone Zaccaria
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, United Kingdom
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, United Kingdom
| | - Alvin Makohon-Moore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Brian Arnold
- Department of Computer Science, Princeton University, Princeton, New Jersey
- Center for Statistics and Machine Learning, Princeton University, Princeton, New Jersey
| | - Max F. Levine
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Gunes Gundem
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Juan E. Arango Ossa
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Dominik Glodzik
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - Nancy Bouvier
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Shanita Li
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Emily Stockfisch
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Marisa Dunigan
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Cassidy Cobbs
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Umesh K. Bhanot
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
- Precision Pathology Biobanking Center, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Daoqi You
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Katelyn Mullen
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, New York
| | - Jerry P. Melchor
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Michael V. Ortiz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Tara J. O'Donohue
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Emily K. Slotkin
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Leonard H. Wexler
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Filemon S. Dela Cruz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Meera R. Hameed
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Julia L. Glade Bender
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - William D. Tap
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Paul A. Meyers
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Elli Papaemmanuil
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Andrew L. Kung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Christine A. Iacobuzio-Donahue
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York
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19
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Chen S, Zhou Z, Li Y, Du Y, Chen G. Application of single-cell sequencing to the research of tumor microenvironment. Front Immunol 2023; 14:1285540. [PMID: 37965341 PMCID: PMC10641410 DOI: 10.3389/fimmu.2023.1285540] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 10/17/2023] [Indexed: 11/16/2023] Open
Abstract
Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.
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Affiliation(s)
| | | | | | | | - Guoan Chen
- Department of Human Cell Biology and Genetics, Joint Laboratory of Guangdong-Hong Kong Universities for Vascular Homeostasis and Diseases, School of Medicine, Southern University of Science and Technology, Shenzhen, China
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20
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Niu M, Zhang Y, Luo J, Sinson JC, Thompson AM, Zong C. Characterization of Cancer Evolution Landscape Based on Accurate Detection of Somatic Mutations in Single Tumor Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561356. [PMID: 37873375 PMCID: PMC10592685 DOI: 10.1101/2023.10.09.561356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution.
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21
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Ryser MD, Greenwald MA, Sorribes IC, King LM, Hall A, Geradts J, Weaver DL, Mallo D, Holloway S, Monyak D, Gumbert G, Vaez-Ghaemi S, Wu E, Murgas K, Grimm LJ, Maley CC, Marks JR, Shibata D, Hwang ES. Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.01.560370. [PMID: 37873488 PMCID: PMC10592867 DOI: 10.1101/2023.10.01.560370] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.
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Affiliation(s)
- Marc D. Ryser
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
- Department of Mathematics, Duke University, Durham, NC, USA
| | | | | | - Lorraine M. King
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Allison Hall
- Department of Pathology, Duke University School of Medicine, Durham, NC, USA
| | - Joseph Geradts
- Department of Pathology, East Carolina University School of Medicine, Greenville, NC, USA
| | - Donald L. Weaver
- Larner College of Medicine, University of Vermont and UVM Cancer Center, Burlington, VT, USA
| | - Diego Mallo
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Shannon Holloway
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Daniel Monyak
- Trinity College of Arts and Sciences, Duke University, Durham, NC
| | - Graham Gumbert
- Trinity College of Arts and Sciences, Duke University, Durham, NC
| | | | - Ethan Wu
- Trinity College of Arts and Sciences, Duke University, Durham, NC
| | - Kevin Murgas
- Department of Biomedical Informatics, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Lars J. Grimm
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Carlo C. Maley
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Jeffrey R. Marks
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
| | - Darryl Shibata
- Department of Pathology, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - E. Shelley Hwang
- Department of Surgery, Duke University School of Medicine, Durham, NC, USA
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22
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Wang Y, Zhang M, Shi J, Zhu Y, Wang X, Zhang S, Wang F. Cracking the pattern of tumor evolution based on single-cell copy number alterations. Brief Bioinform 2023; 24:bbad341. [PMID: 37791583 DOI: 10.1093/bib/bbad341] [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: 05/13/2023] [Revised: 09/02/2023] [Accepted: 09/11/2023] [Indexed: 10/05/2023] Open
Abstract
Copy number alterations (CNAs) are a key characteristic of tumor development and progression. The accumulation of various CNAs during tumor development plays a critical role in driving tumor evolution. Heterogeneous clones driven by distinct CNAs have different selective advantages, leading to differential patterns of tumor evolution that are essential for developing effective cancer therapies. Recent advances in single-cell sequencing technology have enabled genome-wide copy number profiling of tumor cell populations at single-cell resolution. This has made it possible to explore the evolutionary patterns of CNAs and accurately discover the mechanisms of intra-tumor heterogeneity. Here, we propose a two-step statistical approach that distinguishes neutral, linear, branching and punctuated evolutionary patterns for a tumor cell population based on single-cell copy number profiles. We assessed our approach using a variety of simulated and real single-cell genomic and transcriptomic datasets, demonstrating its high accuracy and robustness in predicting tumor evolutionary patterns. We applied our approach to single-cell DNA sequencing data from 20 breast cancer patients and observed that punctuated evolution is the dominant evolutionary pattern in breast cancer. Similar conclusions were drawn when applying the approach to single-cell RNA sequencing data obtained from 132 various cancer patients. Moreover, we found that differential immune cell infiltration is associated with specific evolutionary patterns. The source code of our study is available at https://github.com/FangWang-SYSU/PTEM.
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Affiliation(s)
- Ying Wang
- Guangdong Cardiovascular Institute,Guangdong Provincial People's Hospital,Guangdong Academy of Medical Sciences and Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Min Zhang
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yan-Sen University
| | - Jian Shi
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-Sen University
| | - Yue Zhu
- Department of Breast Surgery at Harbin Medical University Cancer Hospital and the Medical Research Institute of Guangdong Provincial People's Hospital
| | - Xin Wang
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yan-Sen University
| | - Shaojun Zhang
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University
| | - Fang Wang
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yan-Sen University
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23
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Yi D, Nam JW, Jeong H. Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches. Brief Bioinform 2023; 24:bbad297. [PMID: 37587831 PMCID: PMC10516374 DOI: 10.1093/bib/bbad297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/05/2023] [Accepted: 07/23/2023] [Indexed: 08/18/2023] Open
Abstract
Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.
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Affiliation(s)
- Dohun Yi
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Jin-Wu Nam
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Research Institute for Convergence of Basic Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Bio-BigData Center, Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Hyobin Jeong
- Department of Life Science, College of Natural Sciences, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Bio-BigData Center, Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
- Hanyang Institute of Advanced BioConvergence, Hanyang University, Wangsimni-ro 222, Seongdong-gu, Seoul 04763, Republic of Korea
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24
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Zhang L, Chen L, Li SC, Wang M, Li C, Song T, Ni Y, Yang Y, Liu Z, Yao M, Shen B, Li W. Heterogeneity in lung cancers by single-cell DNA sequencing. Clin Transl Med 2023; 13:e1388. [PMID: 37649132 PMCID: PMC10468563 DOI: 10.1002/ctm2.1388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 09/01/2023] Open
Affiliation(s)
- Li Zhang
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
| | - Lingxi Chen
- Department of Computer ScienceCity University of Hong KongKowloonChina
| | - Shuai Cheng Li
- Department of Computer ScienceCity University of Hong KongKowloonChina
| | - Mengyao Wang
- Department of Computer ScienceCity University of Hong KongKowloonChina
| | - Chaohui Li
- Department of Computer ScienceCity University of Hong KongKowloonChina
| | - Tingting Song
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
| | - Yinyun Ni
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
| | - Ying Yang
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
| | - Zhiqiang Liu
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
| | - Menglin Yao
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
| | - Bairong Shen
- Institutes for Systems GeneticsFrontiers Science Center for Disease‐Related Molecular NetworkWest China HospitalSichuan UniversityChengduChina
| | - Weimin Li
- Department of Pulmonary and Critical Care MedicineInstitute of Respiratory HealthState Key Laboratory of Respiratory Health and MultimorbidityFrontiers Science Center for Disease‐related Molecular NetworkPrecision Medicine Key Laboratory of Sichuan ProvinceWest China HospitalWest China School of MedicineSichuan UniversityChengduChina
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25
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Lazebnik T, Simon-Keren L. Cancer-inspired genomics mapper model for the generation of synthetic DNA sequences with desired genomics signatures. Comput Biol Med 2023; 164:107221. [PMID: 37478715 DOI: 10.1016/j.compbiomed.2023.107221] [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: 05/08/2023] [Revised: 06/16/2023] [Accepted: 06/30/2023] [Indexed: 07/23/2023]
Abstract
Genome data are crucial in modern medicine, offering significant potential for diagnosis and treatment. Thanks to technological advancements, many millions of healthy and diseased genomes have already been sequenced; however, obtaining the most suitable data for a specific study, and specifically for validation studies, remains challenging with respect to scale and access. Therefore, in silico genomics sequence generators have been proposed as a possible solution. However, the current generators produce inferior data using mostly shallow (stochastic) connections, detected with limited computational complexity in the training data. This means they do not take the appropriate biological relations and constraints, that originally caused the observed connections, into consideration. To address this issue, we propose cancer-inspired genomics mapper model (CGMM), that combines genetic algorithm (GA) and deep learning (DL) methods to tackle this challenge. CGMM mimics processes that generate genetic variations and mutations to transform readily available control genomes into genomes with the desired phenotypes. We demonstrate that CGMM can generate synthetic genomes of selected phenotypes such as ancestry and cancer that are indistinguishable from real genomes of such phenotypes, based on unsupervised clustering. Our results show that CGMM outperforms four current state-of-the-art genomics generators on two different tasks, suggesting that CGMM will be suitable for a wide range of purposes in genomic medicine, especially for much-needed validation studies.
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Affiliation(s)
- Teddy Lazebnik
- Department of Cancer Biology, Cancer Institute, University College London, London, UK.
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26
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Wang K, Kumar T, Wang J, Minussi DC, Sei E, Li J, Tran TM, Thennavan A, Hu M, Casasent AK, Xiao Z, Bai S, Yang L, King LM, Shah V, Kristel P, van der Borden CL, Marks JR, Zhao Y, Zurita AJ, Aparicio A, Chapin B, Ye J, Zhang J, Gibbons DL, Sawyer E, Thompson AM, Futreal A, Hwang ES, Wesseling J, Lips EH, Navin NE. Archival single-cell genomics reveals persistent subclones during DCIS progression. Cell 2023; 186:3968-3982.e15. [PMID: 37586362 DOI: 10.1016/j.cell.2023.07.024] [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: 01/08/2023] [Revised: 05/09/2023] [Accepted: 07/17/2023] [Indexed: 08/18/2023]
Abstract
Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer. Our understanding of its genomic progression to recurrent disease remains poor, partly due to challenges associated with the genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. Here, we developed Arc-well, a high-throughput single-cell DNA-sequencing method that is compatible with FFPE materials. We validated our method by profiling 40,330 single cells from cell lines, a frozen tissue, and 27 FFPE samples from breast, lung, and prostate tumors stored for 3-31 years. Analysis of 10 patients with matched DCIS and cancers that recurred 2-16 years later show that many primary DCIS had already undergone whole-genome doubling and clonal diversification and that they shared genomic lineages with persistent subclones in the recurrences. Evolutionary analysis suggests that most DCIS cases in our cohort underwent an evolutionary bottleneck, and further identified chromosome aberrations in the persistent subclones that were associated with recurrence.
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Affiliation(s)
- Kaile Wang
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Tapsi Kumar
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Junke Wang
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
| | - Darlan Conterno Minussi
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
| | - Emi Sei
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jianzhuo Li
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Tuan M Tran
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Aatish Thennavan
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Min Hu
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Anna K Casasent
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Zhenna Xiao
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Shanshan Bai
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Lei Yang
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA
| | - Lorraine M King
- Department of Surgery, Duke University School of Medicine, Durham, NC 27707, USA
| | - Vandna Shah
- School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, Guy's Cancer Centre, King's College London, London WC2R 2LS, UK
| | - Petra Kristel
- Division of Molecular Pathology, the Netherlands Cancer Institute, Amsterdam 1066 CX, the Netherlands
| | - Carolien L van der Borden
- Division of Molecular Pathology, the Netherlands Cancer Institute, Amsterdam 1066 CX, the Netherlands
| | - Jeffrey R Marks
- Department of Surgery, Duke University School of Medicine, Durham, NC 27707, USA
| | - Yuehui Zhao
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Amado J Zurita
- Department of Genitourinary Medical Oncology, UT MD Anderson Cancer Center, Houston, TX, USA
| | - Ana Aparicio
- Department of Genitourinary Medical Oncology, UT MD Anderson Cancer Center, Houston, TX, USA
| | - Brian Chapin
- Department of Urology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jie Ye
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Department of Thoracic/Head and Neck Medical Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jianjun Zhang
- Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Thoracic/Head and Neck Medical Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Don L Gibbons
- Department of Thoracic/Head and Neck Medical Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ellinor Sawyer
- School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, Guy's Cancer Centre, King's College London, London WC2R 2LS, UK
| | - Alastair M Thompson
- Department of Surgery, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Andrew Futreal
- Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - E Shelley Hwang
- Department of Surgery, Duke University School of Medicine, Durham, NC 27707, USA
| | - Jelle Wesseling
- Department of Pathology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam 1066 CX, the Netherlands; Department of Pathology, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands
| | - Esther H Lips
- Department of Pathology, the Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam 1066 CX, the Netherlands; Department of Pathology, Leiden University Medical Center, Leiden 2333 ZC, the Netherlands
| | - Nicholas E Navin
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA; MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030, USA; Department of Bioinformatics, UT MD Anderson Cancer Center, Houston, TX 77030, USA.
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Fan Y, Zou L, Zhong X, Wang Z, Wang Y, Luo C, Zheng H, Wang Y. Characteristics of DNA macro-alterations in breast cancer with liver metastasis before treatment. BMC Genomics 2023; 24:391. [PMID: 37434117 DOI: 10.1186/s12864-023-09497-w] [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: 06/20/2022] [Accepted: 06/30/2023] [Indexed: 07/13/2023] Open
Abstract
BACKGROUND Whole-genome doubling (WGD) has been observed in 30% of cancers, followed by a highly complex rearranged karyotype unfavourable to breast cancer's outcome. However, the macro-alterations that characterise liver metastasis in breast cancer(BC) are poorly understood. Here, we conducted a whole-genome sequencing analysis of liver metastases to explore the status and the time frame model of these macro-alterations in pre-treatment patients with metastatic breast cancer. RESULTS Whole-genome sequencing was conducted in 11 paired primary tumours, lymph node metastasis, and liver metastasis fresh samples from four patients with late-stage breast cancer. We also chose five postoperative frozen specimens from patients with early-stage breast cancer before any treatment as control. Surprisingly, all four liver metastasis samples were classified as WGD + . However, the previous study reported that WGD happened in 30% of cancers and 2/5 in our early-stage samples. WGD was not observed in the two separate primary tumours and one lymph node metastasis of one patient with metastatic BC, but her liver metastasis showed an early burst of bi-allelic copy number gain. The phylogenetic tree proves her 4 tumour samples were the polyclonal origin and only one WGD + clone metastasis to the liver. Another 3 metastatic BC patients' primary tumour and lymph node metastasis experienced WGD as well as liver metastasis, and they all showed similar molecular time-frame of copy number(CN) gain across locations within the same patient. These patients' tumours were of monoclonal origin, and WGD happened in a founding clone before metastasis, explaining that all samples share the CN-gain time frame. After WGD, the genomes usually face instability to evolve other macro-alterations. For example, a greater quantity and variety of complex structural variations (SVs) were detected in WGD + samples. The breakpoints were enriched in the chr17: 39 Mb-40 Mb tile, which contained the HER2 gene, resulting in the formation of tyfonas, breakage-fusion-bridge cycles, and double minutes. These complex SVs may be involved in the evolutionary mechanisms of the dramatic increase of HER2 copy number. CONCLUSION Our work revealed that the WGD + clone might be a critical evolution step for liver metastasis and favoured following complex SV of breast cancer.
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Affiliation(s)
- Yu Fan
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China
| | - Linglin Zou
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China
| | - Xiaorong Zhong
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China
| | - Zhu Wang
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China
| | - Yu Wang
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China
| | - Chuanxu Luo
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China
| | - Hong Zheng
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China.
| | - Yanping Wang
- Breast Center and Multi-Omics Laboratory of Breast Diseases, West China Hospital, Sichuan University, 5 Gongxing Street, Wuhou District, Chengdu, 610041, China.
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28
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Perelli L, Carbone F, Zhang L, Huang JK, Le C, Khan H, Citron F, Del Poggetto E, Gutschner T, Tomihara H, Soeung M, Minelli R, Srinivasan S, Peoples M, Lam TNA, Lundgren S, Xia R, Zhu C, Mohamed AMT, Zhang J, Sircar K, Sgambato A, Gao J, Jonasch E, Draetta GF, Futreal A, Bakouny Z, Van Allen EM, Choueiri T, Signoretti S, Msaouel P, Litchfield K, Turajlic S, Wang L, Chen YB, Di Natale RG, Hakimi AA, Giuliani V, Heffernan TP, Viale A, Bristow CA, Tannir NM, Carugo A, Genovese G. Interferon signaling promotes tolerance to chromosomal instability during metastatic evolution in renal cancer. NATURE CANCER 2023; 4:984-1000. [PMID: 37365326 PMCID: PMC10368532 DOI: 10.1038/s43018-023-00584-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 05/18/2023] [Indexed: 06/28/2023]
Abstract
Molecular routes to metastatic dissemination are critical determinants of aggressive cancers. Through in vivo CRISPR-Cas9 genome editing, we generated somatic mosaic genetically engineered models that faithfully recapitulate metastatic renal tumors. Disruption of 9p21 locus is an evolutionary driver to systemic disease through the rapid acquisition of complex karyotypes in cancer cells. Cross-species analysis revealed that recurrent patterns of copy number variations, including 21q loss and dysregulation of the interferon pathway, are major drivers of metastatic potential. In vitro and in vivo genomic engineering, leveraging loss-of-function studies, along with a model of partial trisomy of chromosome 21q, demonstrated a dosage-dependent effect of the interferon receptor genes cluster as an adaptive mechanism to deleterious chromosomal instability in metastatic progression. This work provides critical knowledge on drivers of renal cell carcinoma progression and defines the primary role of interferon signaling in constraining the propagation of aneuploid clones in cancer evolution.
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Affiliation(s)
- Luigi Perelli
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Federica Carbone
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Nerviano Medical Sciences, NMS Group Spa, Milan, Italy
| | - Li Zhang
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Justin K Huang
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Courtney Le
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Hania Khan
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Francesca Citron
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Edoardo Del Poggetto
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tony Gutschner
- Junior Research Group 'RNA Biology and Pathogenesis', Medical Faculty, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Hideo Tomihara
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Melinda Soeung
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rosalba Minelli
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sanjana Srinivasan
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael Peoples
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Truong Nguyen Anh Lam
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sebastian Lundgren
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ruohan Xia
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cihui Zhu
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alaa M T Mohamed
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jianhua Zhang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kanishka Sircar
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alessandro Sgambato
- Dipartimento Universitario di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy
| | - JianJun Gao
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Eric Jonasch
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Giulio F Draetta
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andrew Futreal
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ziad Bakouny
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Eliezer M Van Allen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Toni Choueiri
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sabina Signoretti
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Pavlos Msaouel
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Center for Precision Environmental Health, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Linghua Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ying Bei Chen
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Renzo G Di Natale
- Department of Urology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - A Ari Hakimi
- Department of Urology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Virginia Giuliani
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Timothy P Heffernan
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Andrea Viale
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Christopher A Bristow
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nizar M Tannir
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Alessandro Carugo
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Biology, IRBM S.p.A., Rome, Italy.
| | - Giannicola Genovese
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- TRACTION platform, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- David H. Koch Center for Applied Research of Genitourinary Cancers, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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29
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Qiu MZ, Chen Q, Zheng DY, Zhao Q, Wu QN, Zhou ZW, Yang LQ, Luo QY, Sun YT, Lai MY, Yuan SS, Wang FH, Luo HY, Wang F, Li YH, Zhang HZ, Xu RH. Precise microdissection of gastric mixed adeno-neuroendocrine carcinoma dissects its genomic landscape and evolutionary clonal origins. Cell Rep 2023; 42:112576. [PMID: 37285266 DOI: 10.1016/j.celrep.2023.112576] [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: 09/22/2022] [Revised: 03/02/2023] [Accepted: 05/15/2023] [Indexed: 06/09/2023] Open
Abstract
Gastric mixed adenoneuroendocrine carcinoma (MANEC) is a clinically aggressive and heterogeneous tumor composed of adenocarcinoma (ACA) and neuroendocrine carcinoma (NEC). The genomic properties and evolutionary clonal origins of MANEC remain unclear. We conduct whole-exome and multiregional sequencing on 101 samples from 33 patients to elucidate their evolutionary paths. We identify four significantly mutated genes, TP53, RB1, APC, and CTNNB1. MANEC resembles chromosomal instability stomach adenocarcinoma in that whole-genome doubling in MANEC is predominant and occurs earlier than most copy-number losses. All tumors are of monoclonal origin, and NEC components show more aggressive genomic properties than their ACA counterparts. The phylogenetic trees show two tumor divergence patterns, including sequential and parallel divergence. Furthermore, ACA-to-NEC rather than NEC-to-ACA transition is confirmed by immunohistochemistry on 6 biomarkers in ACA- and NEC-dominant regions. These results provide insights into the clonal origin and tumor differentiation of MANEC.
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Affiliation(s)
- Miao-Zhen Qiu
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Qingjian Chen
- Department of Basic Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China; State Key Laboratory of Systems Medicine for Cancer, Department of Oncology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, P.R. China
| | - Dan-Yang Zheng
- Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China; Department of Clinical Oncology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Qi Zhao
- Department of Basic Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Qi-Nian Wu
- Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Zhi-Wei Zhou
- Department of Gastric Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Li-Qiong Yang
- Department of Basic Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Qiu-Yun Luo
- Department of Basic Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Yu-Ting Sun
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Ming-Yu Lai
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Sha-Sha Yuan
- Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Feng-Hua Wang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Hui-Yan Luo
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Feng Wang
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Yu-Hong Li
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Hui-Zhong Zhang
- Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China
| | - Rui-Hua Xu
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510060, P.R. China; Research Unit of Precision Diagnosis and Treatment for Gastrointestinal Cancer, Chinese Academy of Medical Sciences, Guangzhou 510060, P.R. China.
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30
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Lu B, Curtius K, Graham TA, Yang Z, Barnes CP. CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples. Genome Biol 2023; 24:144. [PMID: 37340508 DOI: 10.1186/s13059-023-02983-0] [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: 03/24/2022] [Accepted: 06/08/2023] [Indexed: 06/22/2023] Open
Abstract
Phylogenetic trees based on copy number profiles from multiple samples of a patient are helpful to understand cancer evolution. Here, we develop a new maximum likelihood method, CNETML, to infer phylogenies from such data. CNETML is the first program to jointly infer the tree topology, node ages, and mutation rates from total copy numbers of longitudinal samples. Our extensive simulations suggest CNETML performs well on copy numbers relative to ploidy and under slight violation of model assumptions. The application of CNETML to real data generates results consistent with previous discoveries and provides novel early copy number events for further investigation.
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Affiliation(s)
- Bingxin Lu
- Department of Cell and Developmental Biology, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
| | - Kit Curtius
- Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Trevor A Graham
- Barts Cancer Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Ziheng Yang
- Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
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31
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Guo S, Liu X, Zhang J, Huang Z, Ye P, Shi J, Stalin A, Wu C, Lu S, Zhang F, Gao Y, Jin Z, Tao X, Huang J, Zhai Y, Shi R, Guo F, Zhou W, Wu J. Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast cancer. Comput Biol Med 2023; 161:107066. [PMID: 37263064 DOI: 10.1016/j.compbiomed.2023.107066] [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: 04/12/2023] [Revised: 05/04/2023] [Accepted: 05/27/2023] [Indexed: 06/03/2023]
Abstract
BACKGROUND Triple negative breast cancer (TNBC) is an aggressive and fatal malignancy. The current success of tumor immunotherapy has focused attention on intermediate T-cell subsets and the tumor microenvironment, which are essential for activation of the anti-tumor response. Therefore, both areas require further research to accelerate progress in developing tailored immunotherapeutic approaches for patients with TNBC. METHODS We obtained scRNA-seq data of TNBC from the GEO database. A multiplex strategy was used to analyze and identify the T-cell heterogeneity of TNBC. By combining the METABRIC and GEO databases, a prognostic risk model for T-cell marker genes was constructed and validated. In addition, the immune-infiltrating cells of TNBC was analyzed using CIBERSORT, and the association between the risk model and response to immunotherapy was investigated. RESULTS Based on scRNA-seq data, 25,932 cells were identified for multiple analyzes. T cells were studied with a focus on 2 subtypes, including CD8+ and CD4+. There were also communication relationships between T cells and multiple cell types. The results of the enrichment analysis showed that the T-cell marker genes were focused in pathways related to the immune system. In addition, OPTN, TMEM176A, PKM and HES1 deserve attention as prognostic markers in TNBC. The immune infiltration results showed that the high-risk group had significant immune cell infiltration and immunosuppression status. CONCLUSION This study provides a resource for understanding T-cell heterogeneity and the associated prognostic risk model for TNBC. The results show that the model helps predict prognosis and response to treatment in breast cancer.
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Affiliation(s)
- Siyu Guo
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Xinkui Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jingyuan Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Zhihong Huang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Peizhi Ye
- National Cancer Center/National Clinical Research Center for Cancer/Chinese Medicine Department of the Caner Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jian Shi
- Department of Medical Oncology, The Fourth Hospital of Hebei Medical University, Hebei Tumor Hospital, Shijiazhuang, 050000, China
| | - Antony Stalin
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Chao Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Shan Lu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Fanqin Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Yifei Gao
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Zhengseng Jin
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Xiaoyu Tao
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jiaqi Huang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Yiyan Zhai
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Rui Shi
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Fengying Guo
- School of Management, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Wei Zhou
- China-Japan Friendship Hospital, Beijing, 100029, China.
| | - Jiarui Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
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32
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Comaills V, Castellano-Pozo M. Chromosomal Instability in Genome Evolution: From Cancer to Macroevolution. BIOLOGY 2023; 12:biology12050671. [PMID: 37237485 DOI: 10.3390/biology12050671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 04/21/2023] [Accepted: 04/25/2023] [Indexed: 05/28/2023]
Abstract
The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures, and for this purpose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanisms leading to the creation of genomic heterogeneity by altering the number of chromosomes and changing their structures. In this review, we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, the human genome shows an induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as the whole genome doubling to more discrete changes as the complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double-strand breaks (DSBs) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs, and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar patterns observed during tumorigenesis. Then, we will also list several diseases associated with CIN, resulting in fertility issues, miscarriage, rare genetic diseases, and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.
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Affiliation(s)
- Valentine Comaills
- Andalusian Center for Molecular Biology and Regenerative Medicine-CABIMER, University of Pablo de Olavide-University of Seville-CSIC, Junta de Andalucía, 41092 Seville, Spain
| | - Maikel Castellano-Pozo
- Andalusian Center for Molecular Biology and Regenerative Medicine-CABIMER, University of Pablo de Olavide-University of Seville-CSIC, Junta de Andalucía, 41092 Seville, Spain
- Genetic Department, Faculty of Biology, University of Seville, 41080 Seville, Spain
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33
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Qin F, Cai G, Xiao F. A statistical learning method for simultaneous copy number estimation and subclone clustering with single cell sequencing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.18.537346. [PMID: 37131674 PMCID: PMC10153109 DOI: 10.1101/2023.04.18.537346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The availability of single cell sequencing (SCS) enables us to assess intra-tumor heterogeneity and identify cellular subclones without the confounding effect of mixed cells. Copy number aberrations (CNAs) have been commonly used to identify subclones in SCS data using various clustering methods, since cells comprising a subpopulation are found to share genetic profile. However, currently available methods may generate spurious results (e.g., falsely identified CNAs) in the procedure of CNA detection, hence diminishing the accuracy of subclone identification from a large complex cell population. In this study, we developed a CNA detection method based on a fused lasso model, referred to as FLCNA, which can simultaneously identify subclones in single cell DNA sequencing (scDNA-seq) data. Spike-in simulations were conducted to evaluate the clustering and CNA detection performance of FLCNA benchmarking to existing copy number estimation methods (SCOPE, HMMcopy) in combination with the existing and commonly used clustering methods. Interestingly, application of FLCNA to a real scDNA-seq dataset of breast cancer revealed remarkably different genomic variation patterns in neoadjuvant chemotherapy treated samples and pre-treated samples. We show that FLCNA is a practical and powerful method in subclone identification and CNA detection with scDNA-seq data.
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34
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Woodward EL, Yang M, Moura-Castro LH, van den Bos H, Gunnarsson R, Olsson-Arvidsson L, Spierings DCJ, Castor A, Duployez N, Zaliova M, Zuna J, Johansson B, Foijer F, Paulsson K. Clonal origin and development of high hyperdiploidy in childhood acute lymphoblastic leukaemia. Nat Commun 2023; 14:1658. [PMID: 36966135 PMCID: PMC10039905 DOI: 10.1038/s41467-023-37356-5] [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: 04/19/2022] [Accepted: 03/14/2023] [Indexed: 03/27/2023] Open
Abstract
High hyperdiploid acute lymphoblastic leukemia (HeH ALL), one of the most common childhood malignancies, is driven by nonrandom aneuploidy (abnormal chromosome numbers) mainly comprising chromosomal gains. In this study, we investigate how aneuploidy in HeH ALL arises. Single cell whole genome sequencing of 2847 cells from nine primary cases and one normal bone marrow reveals that HeH ALL generally display low chromosomal heterogeneity, indicating that they are not characterized by chromosomal instability and showing that aneuploidy-driven malignancies are not necessarily chromosomally heterogeneous. Furthermore, most chromosomal gains are present in all leukemic cells, suggesting that they arose early during leukemogenesis. Copy number data from 577 primary cases reveals selective pressures that were used for in silico modeling of aneuploidy development. This shows that the aneuploidy in HeH ALL likely arises by an initial tripolar mitosis in a diploid cell followed by clonal evolution, in line with a punctuated evolution model.
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Affiliation(s)
- Eleanor L Woodward
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Minjun Yang
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Larissa H Moura-Castro
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Hilda van den Bos
- European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rebeqa Gunnarsson
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Linda Olsson-Arvidsson
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
- Department of Clinical Genetics, Pathology, and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
| | - Diana C J Spierings
- European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anders Castor
- Department of Pediatrics, Skåne University Hospital, Lund University, Lund, Sweden
| | - Nicolas Duployez
- Laboratory of Hematology, Centre Hospitalier Universitaire (CHU) Lille, Lille, France
- Unité Mixte de Recherche en Santé (UMR-S) 1172, INSERM/University of Lille, Lille, France
| | - Marketa Zaliova
- Department of Pediatric Hematology and Oncology, Second Faculty of Medicine, Charles University/University Hospital Motol, Prague, Czech Republic
- Childhood Leukaemia Investigation Prague (CLIP), Prague, Czech Republic
| | - Jan Zuna
- Department of Pediatric Hematology and Oncology, Second Faculty of Medicine, Charles University/University Hospital Motol, Prague, Czech Republic
- Childhood Leukaemia Investigation Prague (CLIP), Prague, Czech Republic
| | - Bertil Johansson
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
- Department of Clinical Genetics, Pathology, and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
| | - Floris Foijer
- European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Kajsa Paulsson
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden.
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35
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Maeser N, Khan A, Sun R. Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline. STAR Protoc 2023; 4:101927. [PMID: 36586123 PMCID: PMC9816983 DOI: 10.1016/j.xpro.2022.101927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/23/2022] [Accepted: 11/21/2022] [Indexed: 12/30/2022] Open
Abstract
A common technique for uncovering intra-tumor genomic heterogeneity (ITH) is variant detection. However, it can be challenging to reliably characterize ITH given uneven sample quality (e.g., depth of coverage, tumor purity, and subclonality). We describe a protocol for calling point mutations and copy number alterations using sequencing of multiple related clinical patient samples across diverse tissue, optimizing for sensitivity with specificity. The ith.Variant pipeline can be run on single- or multi-region whole-genome and whole-exome sequencing. For complete details on the use and execution of this protocol, please refer to Sun et al. (2017).1.
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Affiliation(s)
- Nicole Maeser
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA; Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA
| | - Aziz Khan
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ruping Sun
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA; Masonic Cancer Center, University of Minnesota, Minneapolis, MN 55455, USA.
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36
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Nolan E, Lindeman GJ, Visvader JE. Deciphering breast cancer: from biology to the clinic. Cell 2023; 186:1708-1728. [PMID: 36931265 DOI: 10.1016/j.cell.2023.01.040] [Citation(s) in RCA: 58] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 01/14/2023] [Accepted: 01/30/2023] [Indexed: 03/17/2023]
Abstract
Breast cancer remains a leading cause of cancer-related mortality in women, reflecting profound disease heterogeneity, metastasis, and therapeutic resistance. Over the last decade, genomic and transcriptomic data have been integrated on an unprecedented scale and revealed distinct cancer subtypes, critical molecular drivers, clonal evolutionary trajectories, and prognostic signatures. Furthermore, multi-dimensional integration of high-resolution single-cell and spatial technologies has highlighted the importance of the entire breast cancer ecosystem and the presence of distinct cellular "neighborhoods." Clinically, a plethora of new targeted therapies has emerged, now being rapidly incorporated into routine care. Resistance to therapy, however, remains a crucial challenge for the field.
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Affiliation(s)
- Emma Nolan
- Auckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand
| | - Geoffrey J Lindeman
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC 3050, Australia; Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia
| | - Jane E Visvader
- ACRF Cancer Biology and Stem Cells Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, University of Melbourne, Parkville, VIC 3010, Australia.
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37
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Wessels PH, Boelens MC, Monkhorst K, Sonke GS, van den Broek D, Brandsma D. A review on genetic alterations in CNS metastases related to breast cancer treatment. Is there a role for liquid biopsies in CSF? J Neurooncol 2023; 162:1-13. [PMID: 36820955 DOI: 10.1007/s11060-023-04261-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 02/07/2023] [Indexed: 02/24/2023]
Abstract
Acquired mutations or altered gene expression patterns in brain metastases (BM) and/or leptomeningeal metastases (LM) of breast cancer may play a role in therapy-resistance and offer new molecular targets and treatment options. Despite expanding knowledge of genetic alterations in breast cancer and their metastases, clinical applications for patients with central nervous system (CNS) metastases are currently limited. An emerging tool are DNA-techniques that may detect genetic alterations of the CNS metastases in the cerebrospinal fluid (CSF). In this review we discuss genetic studies in breast cancer and CNS metastases and the role of liquid biopsies in CSF.
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Affiliation(s)
- Peter H Wessels
- Department of Neuro-Oncology, Netherlands Cancer Institute, Antoni Van Leeuwenhoek, Amsterdam, The Netherlands. .,Department of Neurology, St. Antonius Hospital, Utrecht, Nieuwegein, The Netherlands.
| | - Mirjam C Boelens
- Department of Pathology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Kim Monkhorst
- Department of Pathology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Gabe S Sonke
- Department of Medical Oncology, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Daan van den Broek
- Department of Laboratory Medicine, Netherlands Cancer Institute-Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Dieta Brandsma
- Department of Neuro-Oncology, Netherlands Cancer Institute, Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
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38
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Winnard PT, Morsberger L, Yonescu R, Jiang L, Zou YS, Raman V. Isogenic Cell Lines Derived from Specific Organ Metastases Exhibit Divergent Cytogenomic Aberrations. Cancers (Basel) 2023; 15:cancers15051420. [PMID: 36900209 PMCID: PMC10000985 DOI: 10.3390/cancers15051420] [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: 01/24/2023] [Revised: 02/16/2023] [Accepted: 02/17/2023] [Indexed: 03/12/2023] Open
Abstract
Aneuploidy, a deviation in chromosome numbers from the normal diploid set, is now recognized as a fundamental characteristic of all cancer types and is found in 70-90% of all solid tumors. The majority of aneuploidies are generated by chromosomal instability (CIN). CIN/aneuploidy is an independent prognostic marker of cancer survival and is a cause of drug resistance. Hence, ongoing research has been directed towards the development of therapeutics aimed at targeting CIN/aneuploidy. However, there are relatively limited reports on the evolution of CIN/aneuploidies within or across metastatic lesions. In this work, we built on our previous studies using a human xenograft model system of metastatic disease in mice that is based on isogenic cell lines derived from the primary tumor and specific metastatic organs (brain, liver, lung, and spine). As such, these studies were aimed at exploring distinctions and commonalities between the karyotypes; biological processes that have been implicated in CIN; single-nucleotide polymorphisms (SNPs); losses, gains, and amplifications of chromosomal regions; and gene mutation variants across these cell lines. Substantial amounts of inter- and intra-heterogeneity were found across karyotypes, along with distinctions between SNP frequencies across each chromosome of each metastatic cell line relative the primary tumor cell line. There were disconnects between chromosomal gains or amplifications and protein levels of the genes in those regions. However, commonalities across all cell lines provide opportunities to select biological processes as druggable targets that could have efficacy against the primary tumor, as well as metastases.
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Affiliation(s)
- Paul T. Winnard
- Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Laura Morsberger
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Raluca Yonescu
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Liqun Jiang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Ying S. Zou
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Correspondence: (Y.S.Z.); (V.R.); Tel.: +1-410-955-7492 (V.R.); Fax: +1-410-955-0484 (V.R.)
| | - Venu Raman
- Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Pathology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Correspondence: (Y.S.Z.); (V.R.); Tel.: +1-410-955-7492 (V.R.); Fax: +1-410-955-0484 (V.R.)
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39
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Li X, Zhong Y, Zhang X, Sood AK, Liu J. Spatiotemporal view of malignant histogenesis and macroevolution via formation of polyploid giant cancer cells. Oncogene 2023; 42:665-678. [PMID: 36596845 PMCID: PMC9957731 DOI: 10.1038/s41388-022-02588-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 01/04/2023]
Abstract
To understand how malignant tumors develop, we tracked cell membrane, nuclear membrane, spindle, and cell cycle dynamics in polyploid giant cancer cells (PGCCs) during the formation of high-grade serous carcinoma organoids using long-term time-lapse imaging. Single cells underwent traditional mitosis to generate tissue with uniform nuclear size, while others formed PGCCs via asymmetric mitosis, endoreplication, multipolar endomitosis, nuclear fusion, and karyokinesis without cytokinesis. PGCCs underwent restitution multipolar endomitosis, nuclear fragmentation, and micronuclei formation to increase nuclear contents and heterogeneity. At the cellular level, the development of PGCCs was associated with forming transient intracellular cells, termed fecundity cells. The fecundity cells can be decellularized to facilitate nuclear fusion and synchronized with other nuclei for subsequent nuclear replication. PGCCs can undergo several rounds of entosis to form complex tissue structures, termed fecundity structures. The formation of PGCCs via multiple modes of nuclear replication in the absence of cytokinesis leads to an increase in the nuclear-to-cytoplasmic (N/C) ratio and intracellular cell reproduction, which is remarkably similar to the mode of nuclear division during pre-embryogenesis. Our data support that PGCCs may represent a central regulator in malignant histogenesis, intratumoral heterogeneity, immune escape, and macroevolution via the de-repression of suppressed pre-embryogenic program in somatic cells.
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Affiliation(s)
- Xiaoran Li
- Department of Anatomical Pathology, Division of Pathology and Laboratory Medicine, Houston, TX, USA
| | - Yanping Zhong
- Department of Anatomical Pathology, Division of Pathology and Laboratory Medicine, Houston, TX, USA
- Department of Pathology, The First Hospital of Jilin University, Changchun, 130021, Jilin, China
| | - Xudong Zhang
- Department of Anatomical Pathology, Division of Pathology and Laboratory Medicine, Houston, TX, USA
| | - Anil K Sood
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030-4095, USA
| | - Jinsong Liu
- Department of Anatomical Pathology, Division of Pathology and Laboratory Medicine, Houston, TX, USA.
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40
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Leighton J, Hu M, Sei E, Meric-Bernstam F, Navin NE. Reconstructing mutational lineages in breast cancer by multi-patient-targeted single-cell DNA sequencing. CELL GENOMICS 2023; 3:100215. [PMID: 36777188 PMCID: PMC9903705 DOI: 10.1016/j.xgen.2022.100215] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 07/21/2022] [Accepted: 10/18/2022] [Indexed: 11/11/2022]
Abstract
Single-cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells; however, most genomic regions sequenced in single cells are non-informative. To overcome this issue, we developed a multi-patient-targeted (MPT) scDNA-seq method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 patients with triple negative-breast cancer (TNBC), which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From these data, we reconstructed mutational lineages and identified early mutational and copy-number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggest that MPT can overcome a major technical obstacle for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.
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Affiliation(s)
- Jake Leighton
- Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Graduate School of Biological Sciences, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Min Hu
- Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Emi Sei
- Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Funda Meric-Bernstam
- Graduate School of Biological Sciences, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Precision Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Nicholas E. Navin
- Department of Genetics, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Graduate School of Biological Sciences, UT MD Anderson Cancer Center, Houston, TX 77030, USA
- Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA
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41
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Guo L, Kong D, Liu J, Zhan L, Luo L, Zheng W, Zheng Q, Chen C, Sun S. Breast cancer heterogeneity and its implication in personalized precision therapy. Exp Hematol Oncol 2023; 12:3. [PMID: 36624542 PMCID: PMC9830930 DOI: 10.1186/s40164-022-00363-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 12/29/2022] [Indexed: 01/11/2023] Open
Abstract
Breast cancer heterogeneity determines cancer progression, treatment effects, and prognosis. However, the precise mechanism for this heterogeneity remains unknown owing to its complexity. Here, we summarize the origins of breast cancer heterogeneity and its influence on disease progression, recurrence, and therapeutic resistance. We review the possible mechanisms of heterogeneity and the research methods used to analyze it. We also highlight the importance of cell interactions for the origins of breast cancer heterogeneity, which can be further categorized into cooperative and competitive interactions. Finally, we provide new insights into precise individual treatments based on heterogeneity.
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Affiliation(s)
- Liantao Guo
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China
| | - Deguang Kong
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China
| | - Jianhua Liu
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China
| | - Ling Zhan
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China
| | - Lan Luo
- Department of Breast Surgery, The Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Road, Yunyan District, Guiyang, 550001, Guizhou, China
| | - Weijie Zheng
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China
| | - Qingyuan Zheng
- Department of Urology, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China
| | - Chuang Chen
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China.
| | - Shengrong Sun
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China.
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42
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Yu L, Wang X, Mu Q, Tam SST, Loi DSC, Chan AKY, Poon WS, Ng HK, Chan DTM, Wang J, Wu AR. scONE-seq: A single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors. SCIENCE ADVANCES 2023; 9:eabp8901. [PMID: 36598983 PMCID: PMC9812385 DOI: 10.1126/sciadv.abp8901] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Single-cell multi-omics can provide a unique perspective on tumor cellular heterogeneity. Most previous single-cell whole-genome RNA sequencing (scWGS-RNA-seq) methods demonstrate utility with intact cells from fresh samples. Among them, many are not applicable to frozen samples that cannot produce intact single-cell suspensions. We have developed scONE-seq, a versatile scWGS-RNA-seq method that amplifies single-cell DNA and RNA without separating them from each other and hence is compatible with frozen biobanked samples. We benchmarked scONE-seq against existing methods using fresh and frozen samples to demonstrate its performance in various aspects. We identified a unique transcriptionally normal-like tumor clone by analyzing a 2-year frozen astrocytoma sample, demonstrating that performing single-cell multi-omics interrogation on biobanked tissue by scONE-seq could enable previously unidentified discoveries in tumor biology.
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Affiliation(s)
- Lei Yu
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
| | - Xinlei Wang
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
| | - Quanhua Mu
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
| | - Sindy Sing Ting Tam
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
| | - Danson Shek Chun Loi
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
| | - Aden K. Y. Chan
- Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong S.A.R., China
| | - Wai Sang Poon
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong S.A.R., China
| | - Ho-Keung Ng
- Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong S.A.R., China
| | - Danny T. M. Chan
- Department of Surgery, The Chinese University of Hong Kong, Hong Kong S.A.R., China
| | - Jiguang Wang
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong S.A.R., China
| | - Angela Ruohao Wu
- Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- Hong Kong Branch of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- Center for Aging Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R., China
- Corresponding author.
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43
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Kaufmann TL, Petkovic M, Watkins TBK, Colliver EC, Laskina S, Thapa N, Minussi DC, Navin N, Swanton C, Van Loo P, Haase K, Tarabichi M, Schwarz RF. MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution. Genome Biol 2022; 23:241. [PMID: 36376909 PMCID: PMC9661799 DOI: 10.1186/s13059-022-02794-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 10/12/2022] [Indexed: 11/16/2022] Open
Abstract
Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.
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Affiliation(s)
- Tom L Kaufmann
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany.
- Department of Electrical Engineering & Computer Science, Technische Universität Berlin, Marchstr. 23, 10587, Berlin, Germany.
- BIFOLD, Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.
| | - Marina Petkovic
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany
- Department of Biology, Humboldt University of Berlin, Unter den Linden 6, 10099, Berlin, Germany
- Division of Oncology and Hematology, Department of Pediatrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | | | | | - Sofya Laskina
- Department of Mathematics and Computer Science, Free University of Berlin, Berlin, Germany
| | - Nisha Thapa
- UCL Medical School, University College London, London, UK
| | - Darlan C Minussi
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nicholas Navin
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Charles Swanton
- The Francis Crick Institute, London, UK
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Department of Medical Oncology, University College London Hospitals, London, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kerstin Haase
- Division of Oncology and Hematology, Department of Pediatrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Maxime Tarabichi
- The Francis Crick Institute, London, UK
- Institute for Interdisciplinary Research, Université Libre de Bruxelles, Brussels, Belgium
| | - Roland F Schwarz
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125, Berlin, Germany.
- BIFOLD, Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.
- Institute for Computational Cancer Biology, Center for Integrated Oncology (CIO) and Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
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Genomic Profiling Identifies Putative Pathogenic Alterations in NSCLC Brain Metastases. JTO Clin Res Rep 2022; 3:100435. [PMID: 36561283 PMCID: PMC9763853 DOI: 10.1016/j.jtocrr.2022.100435] [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: 11/07/2022] [Accepted: 11/07/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction Brain metastases (BM) severely affect the prognosis and quality of life of patients with NSCLC. Recently, molecularly targeted agents were found to have promising activity against BM in patients with NSCLC whose primary tumors carry "druggable" mutations. Nevertheless, it remains critical to identify specific pathogenic alterations that drive NSCLC-BM and that can provide novel and more effective therapeutic targets. Methods To identify potentially targetable pathogenic alterations in NSCLC-BM, we profiled somatic copy number alterations (SCNAs) in 51 matched pairs of primary NSCLC and BM samples from 33 patients with lung adenocarcinoma and 18 patients with lung squamous cell carcinoma. In addition, we performed multiregion copy number profiling on 15 BM samples and whole-exome sequencing on 40 of 51 NSCLC-BM pairs. Results BM consistently had a higher burden of SCNAs compared with the matched primary tumors, and SCNAs were typically homogeneously distributed within BM, suggesting BM do not undergo extensive evolution once formed. By comparing focal SCNAs in matched NSCLC-BM pairs, we identified putative BM-driving alterations affecting multiple cancer genes, including several potentially targetable alterations in genes such as CDK12, DDR2, ERBB2, and NTRK1, which we validated in an independent cohort of 84 BM samples. Finally, we identified putative pathogenic alterations in multiple cancer genes, including genes involved in epigenome editing and 3D genome organization, such as EP300, CTCF, and STAG2, which we validated by targeted sequencing of an independent cohort of 115 BM samples. Conclusions Our study represents the most comprehensive genomic characterization of NSCLC-BM available to date, paving the way to functional studies aimed at assessing the potential of the identified pathogenic alterations as clinical biomarkers and targets.
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van den Bosch T, Derks S, Miedema DM. Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity. Cancers (Basel) 2022; 14:cancers14204986. [PMID: 36291770 PMCID: PMC9600040 DOI: 10.3390/cancers14204986] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/07/2022] [Accepted: 10/09/2022] [Indexed: 12/03/2022] Open
Abstract
Simple Summary Each cancer consists of billions of cells. These cells are far from identical; hence, the population of cells that constitute a tumor is heterogeneous. A salient property that varies between cells in a tumor is their karyotype, the number and configuration of the chromosomes. The level of karyotype heterogeneity can be used to predict the survival of a patient. In this review, we describe the processes that shape the level of karyotype heterogeneity in a cancer. Abstract Intra-tumor heterogeneity (ITH) is a pan-cancer predictor of survival, with high ITH being correlated to a dismal prognosis. The level of ITH is, hence, a clinically relevant characteristic of a malignancy. ITH of karyotypes is driven by chromosomal instability (CIN). However, not all new karyotypes generated by CIN are viable or competitive, which limits the amount of ITH. Here, we review the cellular processes and ecological properties that determine karyotype ITH. We propose a framework to understand karyotype ITH, in which cells with new karyotypes emerge through CIN, are selected by cell intrinsic and cell extrinsic selective pressures, and propagate through a cancer in competition with other malignant cells. We further discuss how CIN modulates the cell phenotype and immune microenvironment, and the implications this has for the subsequent selection of karyotypes. Together, we aim to provide a comprehensive overview of the biological processes that shape the level of karyotype heterogeneity.
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Affiliation(s)
- Tom van den Bosch
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centers—Location AMC, 1105 AZ Amsterdam, The Netherlands
- Oncode Institute, 1105 AZ Amsterdam, The Netherlands
| | - Sarah Derks
- Oncode Institute, 1105 AZ Amsterdam, The Netherlands
- Department of Medical Oncology, Amsterdam University Medical Centers—Location VUmc, 1081 HV Amsterdam, The Netherlands
- Correspondence: (S.D.); (D.M.M.)
| | - Daniël M. Miedema
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam and Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam University Medical Centers—Location AMC, 1105 AZ Amsterdam, The Netherlands
- Oncode Institute, 1105 AZ Amsterdam, The Netherlands
- Correspondence: (S.D.); (D.M.M.)
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46
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Gofrit ON, Gofrit B, Roditi Y, Popovtzer A, Frank S, Sosna J, Goldberg SN. Patterns of metastases progression- The linear parallel ratio. PLoS One 2022; 17:e0274942. [PMID: 36129954 PMCID: PMC9491615 DOI: 10.1371/journal.pone.0274942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 09/08/2022] [Indexed: 11/25/2022] Open
Abstract
Background Linear and parallel are the two leading models of metastatic progression. In this study we propose a simple way to differentiate between them. While the linear model predicts accumulation of genetic and epigenetic alterations within the primary tumor by founder cells before spreading as waves of metastases, the parallel model suggests preclinical distribution of less advanced disseminated tumor cells with independent selection and expansion at the ectopic sites. Due to identical clonal origin and time of dispatching, linear metastases are expected to have comparable diameters in any specific organ while parallel metastases are expected to appear in variable sizes. Methods and findings Retrospective revision of chest CT of oncological patients with lung metastases was performed. Metastasis number and largest diameters were recorded. The sum number of metastases with a similar diameter (c) and those without (i) was counted and the linear/parallel ratio (LPR) was calculated for each patient using the formula (∑c-∑i)/(∑c+∑i). A LPR ratio of 1 implies pure linear progression pattern and -1 pure parallel. 12,887 metastases were measured in 503 patients with nine malignancy types. The median LPR of the entire group was 0.71 (IQR 0.14–0.93). In carcinomas of the pancreas, prostate, and thyroid the median LPR was 1. Median LPRs were 0.91, 0.65, 0.60, 0.58, 0.50 and 0.43 in renal cell carcinomas, melanomas, colorectal, breast, bladder, and sarcomas, respectively. Conclusions Metastatic spread of thyroid, pancreas, and prostate tumors is almost exclusively by a linear route. The spread of kidney, melanoma, colorectal, breast, bladder and sarcoma is both linear and parallel with increasing dominance of the parallel route in this order. These findings can explain and predict the clinical and genomic features of these tumors and can potentially be used for evaluation of metastatic origin in the individual patient.
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Affiliation(s)
- Ofer N. Gofrit
- Department of Urology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- * E-mail:
| | - Ben Gofrit
- School of Engineering and Computer Science, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yuval Roditi
- School of Engineering and Computer Science, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aron Popovtzer
- Department of Oncology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Steve Frank
- Department of Oncology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Jacob Sosna
- Department of Radiology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - S. Nahum Goldberg
- Department of Radiology, Hadassah Medical Center, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
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Havas A, Yin S, Adams PD. The role of aging in cancer. Mol Oncol 2022; 16:3213-3219. [PMID: 36128609 PMCID: PMC9490134 DOI: 10.1002/1878-0261.13302] [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] [Indexed: 11/15/2022] Open
Abstract
Many cancers show an increase in incidence with age, and age is the biggest single risk factor for many cancers. However, the molecular basis of this relationship is poorly understood. Through a collection of review articles, our thematic issue discusses the link between aging and cancer in aspects including somatic mutations, proteostasis, mitochondria, metabolism, senescence, epigenetic regulation, immune regulation, DNA damage, and telomere function.
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Affiliation(s)
- Aaron Havas
- Sanford Burnham Prebys Medical Discovery InstituteLa JollaCAUSA
| | - Shanshan Yin
- Sanford Burnham Prebys Medical Discovery InstituteLa JollaCAUSA
| | - P. D. Adams
- Sanford Burnham Prebys Medical Discovery InstituteLa JollaCAUSA
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Kurpas MK, Kimmel M. Modes of Selection in Tumors as Reflected by Two Mathematical Models and Site Frequency Spectra. Front Ecol Evol 2022; 10:889438. [PMID: 37333691 PMCID: PMC10275603 DOI: 10.3389/fevo.2022.889438] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024] Open
Abstract
The tug-of-war model was developed in a series of papers of McFarland and co-authors to account for existence of mutually counteracting rare advantageous driver mutations and more frequent slightly deleterious passenger mutations in cancer. In its original version, it was a state-dependent branching process. Because of its formulation, the tug-of-war model is of importance for tackling the problem as to whether evolution of cancerous tumors is "Darwinian" or "non-Darwinian." We define two Time-Continuous Markov Chain versions of the model, including identical mutation processes but adopting different drift and selection components. In Model A, drift and selection process preserves expected fitness whereas in Model B it leads to non-decreasing expected fitness. We investigate these properties using mathematical analysis and extensive simulations, which detect the effect of the so-called drift barrier in Model B but not in Model A. These effects are reflected in different structure of clone genealogies in the two models. Our work is related to the past theoretical work in the field of evolutionary genetics, concerning the interplay among mutation, drift and selection, in absence of recombination (asexual reproduction), where epistasis plays a major role. Finally, we use the statistics of mutation frequencies known as the Site Frequency Spectra (SFS), to compare the variant frequencies in DNA of sequenced HER2+ breast cancers, to those based on Model A and B simulations. The tumor-based SFS are better reproduced by Model A, pointing out a possible selection pattern of HER2+ tumor evolution. To put our models in context, we carried out an exploratory study of how publicly accessible data from breast, prostate, skin and ovarian cancers fit a range of models found in the literature.
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Affiliation(s)
- Monika K. Kurpas
- Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Marek Kimmel
- Department of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
- Department of Statistics and Bioengineering, Rice University, Houston, TX, United States
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Li Z, Seehawer M, Polyak K. Untangling the web of intratumour heterogeneity. Nat Cell Biol 2022; 24:1192-1201. [PMID: 35941364 DOI: 10.1038/s41556-022-00969-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 06/27/2022] [Indexed: 02/06/2023]
Abstract
Intratumour heterogeneity (ITH) is a hallmark of cancer that drives tumour evolution and disease progression. Technological and computational advances have enabled us to assess ITH at unprecedented depths, yet this accumulating knowledge has not had a substantial clinical impact. This is in part due to a limited understanding of the functional relevance of ITH and the inadequacy of preclinical experimental models to reproduce it. Here, we discuss progress made in these areas and illuminate future directions.
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Affiliation(s)
- Zheqi Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.,Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Marco Seehawer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.,Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kornelia Polyak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. .,Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. .,Department of Medicine, Harvard Medical School, Boston, MA, USA.
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Angaroni F, Guidi A, Ascolani G, d'Onofrio A, Antoniotti M, Graudenzi A. J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments. BMC Bioinformatics 2022; 23:269. [PMID: 35804300 PMCID: PMC9270769 DOI: 10.1186/s12859-022-04779-8] [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: 02/23/2022] [Accepted: 06/09/2022] [Indexed: 11/15/2022] Open
Abstract
Background The combined effects of biological variability and measurement-related errors on cancer sequencing data remain largely unexplored. However, the spatio-temporal simulation of multi-cellular systems provides a powerful instrument to address this issue. In particular, efficient algorithmic frameworks are needed to overcome the harsh trade-off between scalability and expressivity, so to allow one to simulate both realistic cancer evolution scenarios and the related sequencing experiments, which can then be used to benchmark downstream bioinformatics methods. Result We introduce a Julia package for SPAtial Cancer Evolution (J-SPACE), which allows one to model and simulate a broad set of experimental scenarios, phenomenological rules and sequencing settings.Specifically, J-SPACE simulates the spatial dynamics of cells as a continuous-time multi-type birth-death stochastic process on a arbitrary graph, employing different rules of interaction and an optimised Gillespie algorithm. The evolutionary dynamics of genomic alterations (single-nucleotide variants and indels) is simulated either under the Infinite Sites Assumption or several different substitution models, including one based on mutational signatures. After mimicking the spatial sampling of tumour cells, J-SPACE returns the related phylogenetic model, and allows one to generate synthetic reads from several Next-Generation Sequencing (NGS) platforms, via the ART read simulator. The results are finally returned in standard FASTA, FASTQ, SAM, ALN and Newick file formats. Conclusion J-SPACE is designed to efficiently simulate the heterogeneous behaviour of a large number of cancer cells and produces a rich set of outputs. Our framework is useful to investigate the emergent spatial dynamics of cancer subpopulations, as well as to assess the impact of incomplete sampling and of experiment-specific errors. Importantly, the output of J-SPACE is designed to allow the performance assessment of downstream bioinformatics pipelines processing NGS data. J-SPACE is freely available at: https://github.com/BIMIB-DISCo/J-Space.jl.
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Affiliation(s)
- Fabrizio Angaroni
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy.
| | - Alessandro Guidi
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy
| | - Gianluca Ascolani
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy
| | - Alberto d'Onofrio
- Department of Mathematics and Geosciences, Univ. of Trieste, Trieste, Italy
| | - Marco Antoniotti
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy.,Bicocca Bioinformatics, Biostatistics and Bioimaging Centre (B4), Milan, Italy
| | - Alex Graudenzi
- Dept. of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy.,Bicocca Bioinformatics, Biostatistics and Bioimaging Centre (B4), Milan, Italy.,Inst. of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Segrate, Italy
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