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Chen X, Agustinus AS, Li J, DiBona M, Bakhoum SF. Chromosomal instability as a driver of cancer progression. Nat Rev Genet 2024:10.1038/s41576-024-00761-7. [PMID: 39075192 DOI: 10.1038/s41576-024-00761-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/25/2024] [Indexed: 07/31/2024]
Abstract
Chromosomal instability (CIN) refers to an increased propensity of cells to acquire structural and numerical chromosomal abnormalities during cell division, which contributes to tumour genetic heterogeneity. CIN has long been recognized as a hallmark of cancer, and evidence over the past decade has strongly linked CIN to tumour evolution, metastasis, immune evasion and treatment resistance. Until recently, the mechanisms by which CIN propels cancer progression have remained elusive. Beyond the generation of genomic copy number heterogeneity, recent work has unveiled additional tumour-promoting consequences of abnormal chromosome segregation. These mechanisms include complex chromosomal rearrangements, epigenetic reprogramming and the induction of cancer cell-intrinsic inflammation, emphasizing the multifaceted role of CIN in cancer.
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Affiliation(s)
- Xuelan Chen
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Albert S Agustinus
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Pharmacology Graduate Program, Weill Cornell Medicine, New York, NY, USA
| | - Jun Li
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Melody DiBona
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Samuel F Bakhoum
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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2
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Xiang H, Luo R, Wang Y, Yang B, Xu S, Huang W, Tang S, Fang R, Chen L, Zhu N, Yu Z, Akesu S, Wei C, Xu C, Zhou Y, Gu J, Zhao J, Hou Y, Ding C. Proteogenomic insights into the biology and treatment of pan-melanoma. Cell Discov 2024; 10:78. [PMID: 39039072 PMCID: PMC11263678 DOI: 10.1038/s41421-024-00688-7] [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: 08/04/2023] [Accepted: 05/03/2024] [Indexed: 07/24/2024] Open
Abstract
Melanoma is one of the most prevalent skin cancers, with high metastatic rates and poor prognosis. Understanding its molecular pathogenesis is crucial for improving its diagnosis and treatment. Integrated analysis of multi-omics data from 207 treatment-naïve melanomas (primary-cutaneous-melanomas (CM, n = 28), primary-acral-melanomas (AM, n = 81), primary-mucosal-melanomas (MM, n = 28), metastatic-melanomas (n = 27), and nevi (n = 43)) provides insights into melanoma biology. Multivariate analysis reveals that PRKDC amplification is a prognostic molecule for melanomas. Further proteogenomic analysis combined with functional experiments reveals that the cis-effect of PRKDC amplification may lead to tumor proliferation through the activation of DNA repair and folate metabolism pathways. Proteome-based stratification of primary melanomas defines three prognosis-related subtypes, namely, the ECM subtype, angiogenesis subtype (with a high metastasis rate), and cell proliferation subtype, which provides an essential framework for the utilization of specific targeted therapies for particular melanoma subtypes. The immune classification identifies three immune subtypes. Further analysis combined with an independent anti-PD-1 treatment cohort reveals that upregulation of the MAPK7-NFKB signaling pathway may facilitate T-cell recruitment and increase the sensitivity of patients to immunotherapy. In contrast, PRKDC may reduce the sensitivity of melanoma patients to immunotherapy by promoting DNA repair in melanoma cells. These results emphasize the clinical value of multi-omics data and have the potential to improve the understanding of melanoma treatment.
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Affiliation(s)
- Hang Xiang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Rongkui Luo
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yunzhi Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Bing Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Sha Xu
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Wen Huang
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shaoshuai Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Rundong Fang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lingli Chen
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Na Zhu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zixiang Yu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Sujie Akesu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chuanyuan Wei
- Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chen Xu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Yuhong Zhou
- Department of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Jianying Gu
- Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
- Department of Plastic and Reconstructive Surgery, Zhongshan Hospital (Xiamen), Fudan University, Shanghai, China.
| | - Jianyuan Zhao
- Institute for Developmental and Regenerative Cardiovascular Medicine, MOE-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yingyong Hou
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Chen Ding
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Department of Plastic and Reconstructive Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
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3
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Liu Z, Lu Q, Zhang Z, Feng Q, Wang X. TMPRSS2 is a tumor suppressor and its downregulation promotes antitumor immunity and immunotherapy response in lung adenocarcinoma. Respir Res 2024; 25:238. [PMID: 38862975 PMCID: PMC11167788 DOI: 10.1186/s12931-024-02870-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 06/06/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND TMPRSS2, a key molecule for SARS-CoV-2 invading human host cells, has an association with cancer. However, its association with lung cancer remains insufficiently unexplored. METHODS In five bulk transcriptomics datasets, one single-cell RNA sequencing (scRNA-seq) dataset and one proteomics dataset for lung adenocarcinoma (LUAD), we explored associations between TMPRSS2 expression and immune signatures, tumor progression phenotypes, genomic features, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we performed experimental validation of the bioinformatics findings. RESULTS TMPRSS2 expression levels correlated negatively with the enrichment levels of both immune-stimulatory and immune-inhibitory signatures, while they correlated positively with the ratios of immune-stimulatory/immune-inhibitory signatures. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor progression, and worse survival in LUAD. We further validated that TMPRSS2 was downregulated with tumor progression in the LUAD cohort we collected from Jiangsu Cancer Hospital, China. In vitro and in vivo experiments verified the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1. CONCLUSIONS TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a potential link between lung cancer and pneumonia caused by SARS-CoV-2 infection.
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Affiliation(s)
- Zhixian Liu
- Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China
| | - Qiqi Lu
- Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China
- Institute of Innovative Drug Discovery and Development, China Pharmaceutical University, Nanjing, 211198, China
- Big Data Research Institute, China Pharmaceutical University, Nanjing, 211198, China
| | - Zhilan Zhang
- Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China
- Institute of Innovative Drug Discovery and Development, China Pharmaceutical University, Nanjing, 211198, China
- Big Data Research Institute, China Pharmaceutical University, Nanjing, 211198, China
| | - Qiushi Feng
- Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China
- Institute of Innovative Drug Discovery and Development, China Pharmaceutical University, Nanjing, 211198, China
- Big Data Research Institute, China Pharmaceutical University, Nanjing, 211198, China
| | - Xiaosheng Wang
- Biomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
- Institute of Innovative Drug Discovery and Development, China Pharmaceutical University, Nanjing, 211198, China.
- Big Data Research Institute, China Pharmaceutical University, Nanjing, 211198, China.
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4
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Rajendra KC, Cheng R, Zhou S, Lizarazo S, Smith D, Van Bortle K. Evidence of RNA polymerase III recruitment and transcription at protein-coding gene promoters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.08.598009. [PMID: 38895345 PMCID: PMC11185800 DOI: 10.1101/2024.06.08.598009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
RNA polymerase (Pol) I, II, and III are most commonly described as having distinct roles in synthesizing ribosomal RNA (rRNA), messenger RNA (mRNA), and specific small noncoding (nc)RNAs, respectively. This delineation of transcriptional responsibilities is not definitive, however, as evidenced by instances of Pol II recruitment to genes conventionally transcribed by Pol III, including the co-transcription of RPPH1 - the catalytic RNA component of RNase P. A comprehensive understanding of the interplay between RNA polymerase complexes remains lacking, however, due to limited comparative analyses for all three enzymes. To address this gap, we applied a uniform framework for quantifying global Pol I, II, and III occupancies that integrates currently available human RNA polymerase ChIP-seq datasets. Occupancy maps are combined with a comprehensive multi-class promoter set that includes protein-coding genes, noncoding genes, and repetitive elements. While our genomic survey appropriately identifies recruitment of Pol I, II, and III to canonical target genes, we unexpectedly discover widespread recruitment of the Pol III machinery to promoters of specific protein-coding genes, supported by colocalization patterns observed for several Pol III-specific subunits. We show that Pol III-occupied Pol II promoters are enriched for small, nascent RNA reads terminating in a run of 4 Ts, a unique hallmark of Pol III transcription termination and evidence of active Pol III activity at these sites. Pol III disruption differentially modulates the expression of Pol III-occupied coding genes, which are functionally enriched for ribosomal proteins and genes broadly linked to unfavorable outcomes in cancer. Our map also identifies additional, currently unannotated genomic elements occupied by Pol III with clear signatures of nascent RNA species that are sensitive to disruption of La (SSB) - a Pol III-related RNA chaperone protein. These findings reshape our current understanding of the interplay between Pols II and III and identify potentially novel small ncRNAs with broad implications for gene regulatory paradigms and RNA biology.
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Affiliation(s)
- K C Rajendra
- Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Ruiying Cheng
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Sihang Zhou
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Simon Lizarazo
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
| | - Duncan Smith
- Department of Biology, New York University, New York, NY
| | - Kevin Van Bortle
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
- Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
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5
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Myers MA, Arnold BJ, Bansal V, Balaban M, Mullen KM, Zaccaria S, Raphael BJ. HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data. Genome Biol 2024; 25:130. [PMID: 38773520 PMCID: PMC11110434 DOI: 10.1186/s13059-024-03267-x] [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: 07/13/2023] [Accepted: 05/03/2024] [Indexed: 05/24/2024] Open
Abstract
Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.
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Affiliation(s)
- Matthew A Myers
- Department of Computer Science, Princeton University, Princeton, USA
| | - Brian J Arnold
- Center for Statistics and Machine Learning, Princeton University, Princeton, USA
| | - Vineet Bansal
- Princeton Research Computing, Princeton University, Princeton, NJ, USA
| | - Metin Balaban
- Department of Computer Science, Princeton University, Princeton, USA
| | - Katelyn M Mullen
- Human Oncology & Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simone Zaccaria
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK.
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6
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Bhatia S, Khanna KK, Duijf PHG. Targeting chromosomal instability and aneuploidy in cancer. Trends Pharmacol Sci 2024; 45:210-224. [PMID: 38355324 DOI: 10.1016/j.tips.2024.01.009] [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: 12/21/2023] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 02/16/2024]
Abstract
Cancer development and therapy resistance are driven by chromosomal instability (CIN), which causes chromosome gains and losses (i.e., aneuploidy) and structural chromosomal alterations. Technical limitations and knowledge gaps have delayed therapeutic targeting of CIN and aneuploidy in cancers. However, our toolbox for creating and studying aneuploidy in cell models has greatly expanded recently. Moreover, accumulating evidence suggests that seven conventional antimitotic chemotherapeutic drugs achieve clinical response by inducing CIN instead of mitotic arrest, although additional anticancer activities may also contribute in vivo. In this review, we discuss these recent developments. We also highlight new discoveries, which together show that 25 chromosome arm aneuploidies (CAAs) may be targetable by 36 drugs across 14 types of cancer. Collectively, these advances offer many new opportunities to improve cancer treatment.
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Affiliation(s)
- Sugandha Bhatia
- Queensland University of Technology (QUT), School of Biomedical Sciences, Centre for Genomics and Personalised Health and Centre for Biomedical Technologies at the Translational Research Institute, Woolloongabba, QLD 4102, Australia.
| | - Kum Kum Khanna
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006, Australia; Mater Research Institute, The University of Queensland, Translational Research Institute, Woolloongabba, QLD 4102, Australia
| | - Pascal H G Duijf
- Queensland University of Technology (QUT), School of Biomedical Sciences, Centre for Genomics and Personalised Health and Centre for Biomedical Technologies at the Translational Research Institute, Woolloongabba, QLD 4102, Australia; Centre for Cancer Biology, Clinical and Health Sciences, University of South Australia and SA Pathology, Adelaide, SA 5001, Australia; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.
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7
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Aljahdali MO, Molla MHR. Multi-omics prognostic signatures of IPO11 mRNA expression and clinical outcomes in colorectal cancer using bioinformatics approaches. Health Inf Sci Syst 2023; 11:57. [PMID: 38028961 PMCID: PMC10678892 DOI: 10.1007/s13755-023-00259-2] [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: 04/04/2023] [Accepted: 11/05/2023] [Indexed: 12/01/2023] Open
Abstract
The most prevalent malignant illness of the gastrointestinal system, colorectal cancer, is the third most prevalent cancer in males and the second most prevalent cancer in women. Importin-11 is a protein that acts as a regulator of cancer cell proliferation in colorectal tumours by conveying β -catenin to the cell nucleus. However, the IPO11 gene was found to encode a protein called Importin-11, which functions as a nucleus importer for the cell. As a result, preventing β -catenin from entering the nucleus requires blocking Importin-11. As a result, we conducted a multi-omics investigation to assess IPO11 gene potential as a therapeutic biomarker for human colorectal cancer (CC). Oncomine, GEPIA2, immunohisto-chemistry, and UALCAN databases were used to analyses the mRNA expression profiles of IPO11 in CC. The investigation has yielded clear evidence of the increase of IPO11 expression in CC subtypes, as indicated by the data acquired. Analysing CC research from the cBioPortal database, the study discovered three new missense mutations in the importin-11 protein sequence at a frequency of 0.00-1.50% copy number changes. Additionally, the Kaplan-Meier plots demonstrated a strong connection concerning IPO11 downregulation and a poorer CC patient survival rate. The co-expressed gene profile of IPO11 was likewise associated with the onset of CC. IPO11 co-expressed gene profile was also linked to CC development. Moreover, the correlation analysis using bc-GenExMiner and the UCSC Xena server identified KIF2A as the most positively co-expressed gene. The study found that KIF2A and its co-expressed genes were involved in a wide variety of cancer progression pathways using the Enrichr database. Cumulatively, this result will not only provide new information about the expression of IPO11 associated with CC progression and patient survival, but could also serve as a therapeutic biomarker for treating CC in a significant and worthwhile manner. Supplementary Information The online version contains supplementary material available at 10.1007/s13755-023-00259-2.
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Affiliation(s)
- Mohammed Othman Aljahdali
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah, 21598 Saudi Arabia
| | - Mohammad Habibur Rahman Molla
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah, 21598 Saudi Arabia
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8
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Lakhani AA, Thompson SL, Sheltzer JM. Aneuploidy in human cancer: new tools and perspectives. Trends Genet 2023; 39:968-980. [PMID: 37778926 PMCID: PMC10715718 DOI: 10.1016/j.tig.2023.09.002] [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: 05/25/2023] [Revised: 09/04/2023] [Accepted: 09/07/2023] [Indexed: 10/03/2023]
Abstract
Chromosome copy number imbalances, otherwise known as aneuploidies, are a common but poorly understood feature of cancer. Here, we describe recent advances in both detecting and manipulating aneuploidies that have greatly advanced our ability to study their role in tumorigenesis. In particular, new clustered regularly interspaced short palindromic repeats (CRISPR)-based techniques have been developed that allow the creation of isogenic cell lines with specific chromosomal changes, thereby facilitating experiments in genetically controlled backgrounds to uncover the consequences of aneuploidy. These approaches provide increasing evidence that aneuploidy is a key driver of cancer development and enable the identification of multiple dosage-sensitive genes encoded on aneuploid chromosomes. Consequently, measuring aneuploidy may inform clinical prognosis, while treatment strategies that target aneuploidy could represent a novel method to counter malignant growth.
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Affiliation(s)
- Asad A Lakhani
- Cold Spring Harbor Laboratory School of Biological Sciences, Cold Spring, Harbor, NY 11724, USA
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9
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Nulsen J, Hussain N, Al-Deka A, Yap J, Uddin K, Yau C, Ahmed AA. Completing a genomic characterisation of microscopic tumour samples with copy number. BMC Bioinformatics 2023; 24:453. [PMID: 38036971 PMCID: PMC10688092 DOI: 10.1186/s12859-023-05576-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 11/21/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Genomic insights in settings where tumour sample sizes are limited to just hundreds or even tens of cells hold great clinical potential, but also present significant technical challenges. We previously developed the DigiPico sequencing platform to accurately identify somatic mutations from such samples. RESULTS Here, we complete this genomic characterisation with copy number. We present a novel protocol, PicoCNV, to call allele-specific somatic copy number alterations from picogram quantities of tumour DNA. We find that PicoCNV provides exactly accurate copy number in 84% of the genome for even the smallest samples, and demonstrate its clinical potential in maintenance therapy. CONCLUSIONS PicoCNV complements our existing platform, allowing for accurate and comprehensive genomic characterisations of cancers in settings where only microscopic samples are available.
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Affiliation(s)
- Joel Nulsen
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Singula Bio Ltd., Oxford, UK
| | - Nosheen Hussain
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Singula Bio Ltd., Oxford, UK
| | - Aws Al-Deka
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Singula Bio Ltd., Oxford, UK
| | - Jason Yap
- University of Birmingham, Birmingham, UK
| | | | - Christopher Yau
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK
- Health Data Research UK, London, UK
| | - Ahmed Ashour Ahmed
- Weatherall Institute for Molecular Medicine, University of Oxford, Oxford, UK.
- Nuffield Department for Women's and Reproductive Health, University of Oxford, Oxford, UK.
- Singula Bio Ltd., Oxford, UK.
- Oxford Biomedical Research Centre, National Institute of Health Research, Oxford, UK.
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10
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Siddalingappa R, Kanagaraj S. K-nearest-neighbor algorithm to predict the survival time and classification of various stages of oral cancer: a machine learning approach. F1000Res 2023; 11:70. [PMID: 38046542 PMCID: PMC10690040 DOI: 10.12688/f1000research.75469.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/16/2023] [Indexed: 12/05/2023] Open
Abstract
Background:For years now, cancer treatments have entailed tried-and-true methods. Yet, oncologists and clinicians recommend a series of surgeries, chemotherapy, and radiation therapy. Yet, even amidst these treatments, the number of deaths due to cancer increases at an alarming rate. The prognosis of cancer patients is influenced by mutations, age, and various cancer stages. However, the association between these variables is unclear. Methods: The present work adopts a machine learning technique-k-nearest neighbor; for both regression and classification tasks, regression for predicting the survival time of oral cancer patients, and classification for classifying the patients into one of the predefined oral cancer stages. Two cross-validation approaches-hold-out and k-fold methods-have been used to examine the prediction results. Results: The experimental results show that the k-fold method performs better than the hold-out method, providing the least mean absolute error score of 0.015. Additionally, the model classifies patients into a valid group. Of the 429 records, 97 (out of 106), 99 (out of 119), 95 (out of 113), and 77 (out of 91) were classified to its correct label as stages - 1, 2, 3, and 4. The accuracy, recall, precision, and F-measure for each classification group obtained are 0.84, 0.85, 0.85, and 0.84. Conclusions: The study showed that aged patients with a higher number of mutations than young patients have a higher risk of short survival. Senior patients with a more significant number of mutations have an increased risk of getting into the last cancer stage.
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Affiliation(s)
- Rashmi Siddalingappa
- Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, 560012, India
| | - Sekar Kanagaraj
- Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, 560012, India
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11
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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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12
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Roche ME, Ko YH, Domingo-Vidal M, Lin Z, Whitaker-Menezes D, Birbe RC, Tuluc M, Győrffy B, Caro J, Philp NJ, Bartrons R, Martinez-Outschoorn U. TP53 Induced Glycolysis and Apoptosis Regulator and Monocarboxylate Transporter 4 drive metabolic reprogramming with c-MYC and NFkB activation in breast cancer. Int J Cancer 2023; 153:1671-1683. [PMID: 37497753 DOI: 10.1002/ijc.34660] [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: 12/20/2022] [Revised: 06/22/2023] [Accepted: 06/29/2023] [Indexed: 07/28/2023]
Abstract
Breast cancer is composed of metabolically coupled cellular compartments with upregulation of TP53 Induced Glycolysis and Apoptosis Regulator (TIGAR) in carcinoma cells and loss of caveolin 1 (CAV1) with upregulation of monocarboxylate transporter 4 (MCT4) in fibroblasts. The mechanisms that drive metabolic coupling are poorly characterized. The effects of TIGAR on fibroblast CAV1 and MCT4 expression and breast cancer aggressiveness was studied using coculture and conditioned media systems and in-vivo. Also, the role of cytokines in promoting tumor metabolic coupling via MCT4 on cancer aggressiveness was studied. TIGAR downregulation in breast carcinoma cells reduces tumor growth. TIGAR overexpression in carcinoma cells drives MCT4 expression and NFkB activation in fibroblasts. IL6 and TGFB drive TIGAR upregulation in carcinoma cells, reduce CAV1 and increase MCT4 expression in fibroblasts. Tumor growth is abrogated in the presence of MCT4 knockout fibroblasts and environment. We discovered coregulation of c-MYC and TIGAR in carcinoma cells driven by lactate. Metabolic coupling primes the tumor microenvironment allowing for production, uptake and utilization of lactate. In sum, aggressive breast cancer is dependent on metabolic coupling.
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Affiliation(s)
- Megan E Roche
- Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Ying-Hui Ko
- Department of Biochemistry and Molecular Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Marina Domingo-Vidal
- Immunology, Microenvironment & Metastasis Program, Wistar Institute, Philadelphia, Pennsylvania, USA
| | - Zhao Lin
- Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Diana Whitaker-Menezes
- Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Ruth C Birbe
- Department of Pathology, Cooper University Hospital, Camden, New Jersey, USA
| | - Madalina Tuluc
- Department of Pathology, Anatomy and Cell Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Balázs Győrffy
- MTA TTK Lendület Cancer Biomarker Research Group, Institute of Enzymology, Budapest, Hungary
- Semmelweis University 2nd Department of Pediatrics, Budapest, Hungary
| | - Jaime Caro
- Department of Medicine, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Nancy J Philp
- Department of Pathology, Anatomy and Cell Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Ramon Bartrons
- Department of Physiological Sciences, University of Barcelona, Barcelona, Spain
| | - Ubaldo Martinez-Outschoorn
- Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
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13
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Melillo N, Dickinson J, Tan L, Mistry HB, Huber HJ. Radius additivity score: a novel combination index for tumour growth inhibition in fixed-dose xenograft studies. Front Pharmacol 2023; 14:1272058. [PMID: 37900154 PMCID: PMC10603293 DOI: 10.3389/fphar.2023.1272058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 09/29/2023] [Indexed: 10/31/2023] Open
Abstract
The effect of combination therapies in many cancers has often been shown to be superior to that of monotherapies. This success is commonly attributed to drug synergies. Combinations of two (or more) drugs in xenograft tumor growth inhibition (TGI) studies are typically designed at fixed doses for each compound. The available methods for assessing synergy in such study designs are based on combination indices (CI) and model-based analyses. The former methods are suitable for screening exercises but are difficult to verify in in vivo studies, while the latter incorporate drug synergy in semi-mechanistic frameworks describing disease progression and drug action but are unsuitable for screening. In the current study, we proposed the empirical radius additivity (Rad-add) score, a novel CI for synergy detection in fixed-dose xenograft TGI combination studies. The Rad-add score approximates model-based analysis performed using the semi-mechanistic constant-radius growth TGI model. The Rad-add score was compared with response additivity, defined as the addition of the two response values, and the bliss independence model in combination studies derived from the Novartis PDX dataset. The results showed that the bliss independence and response additivity models predicted synergistic interactions with high and low probabilities, respectively. The Rad-add score predicted synergistic probabilities that appeared to be between those predicted with response additivity and the Bliss model. We believe that the Rad-add score is particularly suitable for assessing synergy in the context of xenograft combination TGI studies, as it combines the advantages of CI approaches suitable for screening exercises with those of semi-mechanistic TGI models based on a mechanistic understanding of tumor growth.
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Affiliation(s)
- Nicola Melillo
- Seda Pharmaceutical Developments Services Unit D Cheadle Royal Business Park, Stockport, United Kingdom
| | - Jake Dickinson
- Seda Pharmaceutical Developments Services Unit D Cheadle Royal Business Park, Stockport, United Kingdom
| | - Lu Tan
- Division Drug Discovery Sciences, Boehringer Ingelheim RCV GmbH & Co KG, Vienna, Austria
| | - Hitesh B. Mistry
- Seda Pharmaceutical Developments Services Unit D Cheadle Royal Business Park, Stockport, United Kingdom
- Division of Pharmacy, University of Manchester, Manchester, United Kingdom
| | - Heinrich J. Huber
- Division Drug Discovery Sciences, Boehringer Ingelheim RCV GmbH & Co KG, Vienna, Austria
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14
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Wang K, Li Z, Xuan Y, Zhao Y, Deng C, Wang M, Xie C, Yuan F, Pang Q, Mao W, Cai D, Zhong Z, Mei J. Pan-cancer analysis of NFE2L2 mutations identifies a subset of lung cancers with distinct genomic and improved immunotherapy outcomes. Cancer Cell Int 2023; 23:229. [PMID: 37794491 PMCID: PMC10552358 DOI: 10.1186/s12935-023-03056-9] [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: 01/26/2023] [Accepted: 09/06/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Mutations in the KEAP1-NFE2L2 signaling pathway were linked to increased tumorigenesis and aggressiveness. Interestingly, not all hotspot mutations on NFE2L2 were damaging; some even were activating. However, there was conflicting evidence about the association between NFE2L2 mutation and Nrf2-activating mutation and responsiveness to immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and other multiple cancers. METHODS The study with the largest sample size (n = 49,533) explored the landscape of NFE2L2 mutations and their impact response/resistance to ICIs using public cohorts. In addition, the in-house WXPH cohort was used to validate the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. RESULTS In two pan-cancer cohorts, Nrf2-activating mutation was associated with higher TMB value compared to wild-type. We identified a significant association between Nrf2-activating mutation and shorter overall survival in pan-cancer patients and NSCLC patients but not in those undergoing ICIs treatment. Similar findings were obtained in cancer patients carrying the NFE2L2 mutation. Furthermore, in NSCLC and other cancer cohorts, patients with NFE2L2 mutation demonstrated more objective responses to ICIs than patients with wild type. Our in-house WXPH cohort further confirmed the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. Lastly, decreased inflammatory signaling pathways and immune-depleted immunological microenvironments were enriched in Nrf2-activating mutation patients with NSCLC. CONCLUSIONS Our study found that patients with Nrf2-activating mutation had improved immunotherapy outcomes than patients with wild type in NSCLC and other tumor cohorts, implying that Nrf2-activating mutation defined a distinct subset of pan-cancers and might have implications as a biomarker for guiding ICI treatment, especially NSCLC.
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Affiliation(s)
- Kewei Wang
- Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Zixi Li
- Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Ying Xuan
- Department of Physiopathology, Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Yong Zhao
- Department of Thoracic Surgery, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Chao Deng
- Department of Physiopathology, Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Meidan Wang
- Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Chenjun Xie
- Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Fenglai Yuan
- Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China
| | - Qingfeng Pang
- Department of Physiopathology, Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Wenjun Mao
- Department of Thoracic Surgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, No. 299 Qingyang Road, Wuxi, 214023, China.
| | - Dongyan Cai
- Department of Oncology, Affiliated Hospital of Jiangnan University, 200 Huihe Road, Wuxi, 214122, China.
| | - Zhangfeng Zhong
- Macao Centre for Research and Development in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, 999078, SAR, China.
| | - Jie Mei
- Institute of Integrated Traditional Chinese and Western Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China.
- Department of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, No. 299 Qingyang Road, Wuxi, 214023, China.
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15
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Andrade JR, Gallagher AD, Maharaj J, McClelland SE. Disentangling the roles of aneuploidy, chromosomal instability and tumour heterogeneity in developing resistance to cancer therapies. Chromosome Res 2023; 31:28. [PMID: 37721639 PMCID: PMC10506951 DOI: 10.1007/s10577-023-09737-5] [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: 05/01/2023] [Revised: 07/26/2023] [Accepted: 08/29/2023] [Indexed: 09/19/2023]
Abstract
Aneuploidy is defined as the cellular state of having a number of chromosomes that deviates from a multiple of the normal haploid chromosome number of a given organism. Aneuploidy can be present in a static state: Down syndrome individuals stably maintain an extra copy of chromosome 21 in their cells. In cancer cells, however, aneuploidy is usually present in combination with chromosomal instability (CIN) which leads to a continual generation of new chromosomal alterations and the development of intratumour heterogeneity (ITH). The prevalence of cells with specific chromosomal alterations is further shaped by evolutionary selection, for example, during the administration of cancer therapies. Aneuploidy, CIN and ITH have each been individually associated with poor prognosis in cancer, and a wealth of evidence suggests they contribute, either alone or in combination, to cancer therapy resistance by providing a reservoir of potential resistant states, or the ability to rapidly evolve resistance. A full understanding of the contribution and interplay between aneuploidy, CIN and ITH is required to tackle therapy resistance in cancer patients. However, these characteristics often co-occur and are intrinsically linked, presenting a major challenge to defining their individual contributions. Moreover, their accurate measurement in both experimental and clinical settings is a technical hurdle. Here, we attempt to deconstruct the contribution of the individual and combined roles of aneuploidy, CIN and ITH to therapy resistance in cancer, and outline emerging approaches to measure and disentangle their roles as a step towards integrating these principles into cancer therapeutic strategy.
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Affiliation(s)
- Joana Reis Andrade
- Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M6BQ, England
| | - Annie Dinky Gallagher
- Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M6BQ, England
| | - Jovanna Maharaj
- Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M6BQ, England
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16
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Girish V, Lakhani AA, Thompson SL, Scaduto CM, Brown LM, Hagenson RA, Sausville EL, Mendelson BE, Kandikuppa PK, Lukow DA, Yuan ML, Stevens EC, Lee SN, Schukken KM, Akalu SM, Vasudevan A, Zou C, Salovska B, Li W, Smith JC, Taylor AM, Martienssen RA, Liu Y, Sun R, Sheltzer JM. Oncogene-like addiction to aneuploidy in human cancers. Science 2023; 381:eadg4521. [PMID: 37410869 PMCID: PMC10753973 DOI: 10.1126/science.adg4521] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 06/27/2023] [Indexed: 07/08/2023]
Abstract
Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses p53 signaling, and we show that TP53 mutations are mutually exclusive with 1q aneuploidy in human cancers. Thus, tumor cells can be dependent on specific aneuploidies, raising the possibility that these "aneuploidy addictions" could be targeted as a therapeutic strategy.
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Affiliation(s)
- Vishruth Girish
- Yale University School of Medicine, New Haven, CT 06511
- Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | | | | | | | | | | | | | | | | | | | - Monet Lou Yuan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | | | - Sophia N. Lee
- Yale University School of Medicine, New Haven, CT 06511
| | | | | | | | - Charles Zou
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Wenxue Li
- Yale University School of Medicine, New Haven, CT 06511
| | - Joan C. Smith
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Robert A. Martienssen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | - Yansheng Liu
- Yale University School of Medicine, New Haven, CT 06511
| | - Ruping Sun
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455
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17
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Myers MA, Arnold BJ, Bansal V, Mullen KM, Zaccaria S, Raphael BJ. HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.13.548855. [PMID: 37502835 PMCID: PMC10370020 DOI: 10.1101/2023.07.13.548855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Multi-region DNA sequencing of primary tumors and metastases from individual patients helps identify somatic aberrations driving cancer development. However, most methods to infer copy-number aberrations (CNAs) analyze individual samples. We introduce HATCHet2 to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 introduces a novel statistic, the mirrored haplotype B-allele frequency (mhBAF), to identify mirrored-subclonal CNAs having different numbers of copies of parental haplotypes in different tumor clones. HATCHet2 also has high accuracy in identifying focal CNAs and extends the earlier HATCHet method in several directions. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 50 prostate cancer samples from 10 patients reveals previously-unreported mirrored-subclonal CNAs affecting cancer genes.
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Affiliation(s)
- Matthew A. Myers
- Department of Computer Science, Princeton University, Princeton, USA
| | - Brian J. Arnold
- Center for Statistics and Machine Learning, Princeton University, Princeton, USA
| | - Vineet Bansal
- Princeton Research Computing, Princeton University, Princeton, NJ, USA
| | - Katelyn M. Mullen
- Human Oncology & Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simone Zaccaria
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK
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18
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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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19
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Wan L, Lin KT, Rahman MA, Ishigami Y, Wang Z, Jensen MA, Wilkinson JE, Park Y, Tuveson DA, Krainer AR. Splicing Factor SRSF1 Promotes Pancreatitis and KRASG12D-Mediated Pancreatic Cancer. Cancer Discov 2023; 13:1678-1695. [PMID: 37098965 PMCID: PMC10330071 DOI: 10.1158/2159-8290.cd-22-1013] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 02/14/2023] [Accepted: 03/22/2023] [Indexed: 04/27/2023]
Abstract
Inflammation is strongly associated with pancreatic ductal adenocarcinoma (PDAC), a highly lethal malignancy. Dysregulated RNA splicing factors have been widely reported in tumorigenesis, but their involvement in pancreatitis and PDAC is not well understood. Here, we report that the splicing factor SRSF1 is highly expressed in pancreatitis, PDAC precursor lesions, and tumors. Increased SRSF1 is sufficient to induce pancreatitis and accelerate KRASG12D-mediated PDAC. Mechanistically, SRSF1 activates MAPK signaling-partly by upregulating interleukin 1 receptor type 1 (IL1R1) through alternative-splicing-regulated mRNA stability. Additionally, SRSF1 protein is destabilized through a negative feedback mechanism in phenotypically normal epithelial cells expressing KRASG12D in mouse pancreas and in pancreas organoids acutely expressing KRASG12D, buffering MAPK signaling and maintaining pancreas cell homeostasis. This negative feedback regulation of SRSF1 is overcome by hyperactive MYC, facilitating PDAC tumorigenesis. Our findings implicate SRSF1 in the etiology of pancreatitis and PDAC, and point to SRSF1-misregulated alternative splicing as a potential therapeutic target. SIGNIFICANCE We describe the regulation of splicing factor SRSF1 expression in the context of pancreas cell identity, plasticity, and inflammation. SRSF1 protein downregulation is involved in a negative feedback cellular response to KRASG12D expression, contributing to pancreas cell homeostasis. Conversely, upregulated SRSF1 promotes pancreatitis and accelerates KRASG12D-mediated tumorigenesis through enhanced IL1 and MAPK signaling. This article is highlighted in the In This Issue feature, p. 1501.
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Affiliation(s)
- Ledong Wan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Kuan-Ting Lin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Yuma Ishigami
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Zhikai Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Mads A. Jensen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - John E. Wilkinson
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Youngkyu Park
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Lustgarten Foundation Pancreatic Cancer Research Laboratory, Cold Spring Harbor, NY 11724, USA
| | - David A. Tuveson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Lustgarten Foundation Pancreatic Cancer Research Laboratory, Cold Spring Harbor, NY 11724, USA
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20
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Dong Y, He Q, Chen X, Yang F, He L, Zheng Y. Extrachromosomal DNA (ecDNA) in cancer: mechanisms, functions, and clinical implications. Front Oncol 2023; 13:1194405. [PMID: 37448518 PMCID: PMC10338009 DOI: 10.3389/fonc.2023.1194405] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 06/05/2023] [Indexed: 07/15/2023] Open
Abstract
Extrachromosomal DNA (ecDNA) is circular DNA that plays an important role in the development and heterogeneity of cancer. The rapid evolution of methods to detect ecDNA, including microscopic and sequencing approaches, has greatly enhanced our knowledge of the role of ecDNA in cancer development and evolution. Here, we review the molecular characteristics, functions, mechanisms of formation, and detection methods of ecDNA, with a focus on the potential clinical implications of ecDNA in cancer. Specifically, we consider the role of ecDNA in acquired drug resistance, as a diagnostic and prognostic biomarker, and as a therapeutic target in the context of cancer. As the pathological and clinical significance of ecDNA continues to be explored, it is anticipated that ecDNA will have broad applications in the diagnosis, prognosis, and treatment of patients with cancer.
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Affiliation(s)
- Yucheng Dong
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qi He
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xinyu Chen
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fan Yang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Li He
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma, OK, United States
| | - Yongchang Zheng
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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21
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Pellegrini M. Accurate prognosis for localized prostate cancer through coherent voting networks with multi-omic and clinical data. Sci Rep 2023; 13:7875. [PMID: 37188913 DOI: 10.1038/s41598-023-35023-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 05/11/2023] [Indexed: 05/17/2023] Open
Abstract
Localized prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing stratifications of patients into risk classes remarkably challenging. In particular, it is important an early detection and discrimination of the indolent forms of the disease, from the aggressive ones, requiring post-surgery closer surveillance and timely treatment decisions. This work extends a recently developed supervised machine learning (ML) technique, called coherent voting networks (CVN) by incorporating a novel model-selection technique to counter the danger of model overfitting. For the challenging problem of discriminating between indolent and aggressive types of localized prostate cancer, accurate prognostic prediction of post-surgery progression-free survival with a granularity within a year is attained, improving accuracy with respect to the current state of the art. The development of novel ML techniques tailored to the problem of combining multi-omics and clinical prognostic biomarkers is a promising new line of attack for sharpening the capability to diversify and personalize cancer patient treatments. The proposed approach allows a finer post-surgery stratification of patients within the clinical high-risk category, with a potential impact on the surveillance regime and the timing of treatment decisions, complementing existing prognostic methods.
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Affiliation(s)
- Marco Pellegrini
- Institute of Informatics and Telematics (IIT), CNR, 56124, Pisa, Italy.
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22
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Trilla-Fuertes L, Gámez-Pozo A, Nogué M, Busquier I, Arias F, López-Campos F, Fernández-Montes A, Ruiz A, Velázquez C, Martín-Bravo C, Pérez-Ruiz E, Asensio E, Hernández-Yagüe X, Rodrigues A, Ghanem I, López-Vacas R, Hafez A, Arias P, Dapía I, Solís M, Dittmann A, Ramos R, Llorens C, Maurel J, Campos-Barros Á, Fresno Vara JÁ, Feliu J. Utility of CYP2D6 copy number variants as prognostic biomarker in localized anal squamous cell carcinoma. Cancer 2023. [PMID: 37096763 DOI: 10.1002/cncr.34797] [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: 01/17/2023] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND Anal squamous cell carcinoma (ASCC) is an infrequent tumor whose treatment has not changed since the 1970s. The aim of this study is the identification of biomarkers allowing personalized treatments and improvement of therapeutic outcomes. METHODS Forty-six paraffin tumor samples from ASCC patients were analyzed by whole-exome sequencing. Copy number variants (CNVs) were identified and their relation to disease-free survival (DFS) was studied and validated in an independent retrospective cohort of 101 ASCC patients from the Multidisciplinary Spanish Digestive Cancer Group (GEMCAD). GEMCAD cohort proteomics allowed assessing the biological features of these tumors. RESULTS On the discovery cohort, the median age was 61 years old, 50% were males, stages I/II/III: 3 (7%)/16 (35%)/27 (58%), respectively, median DFS was 33 months, and overall survival was 45 months. Twenty-nine genes whose duplication was related to DFS were identified. The most representative was duplications of the CYP2D locus, including CYP2D6, CYP2D7P, and CYP2D8P genes. Patients with CYP2D6 CNV had worse DFS at 5 years than those with two CYP2D6 copies (21% vs. 84%; p < .0002, hazard ratio [HR], 5.8; 95% confidence interval [CI], 2.7-24.9). In the GEMCAD validation cohort, patients with CYP2D6 CNV also had worse DFS at 5 years (56% vs. 87%; p = .02, HR = 3.6; 95% CI, 1.1-5.7). Mitochondria and mitochondrial cell-cycle proteins were overexpressed in patients with CYP2D6 CNV. CONCLUSIONS Tumor CYP2D6 CNV identified patients with a significantly worse DFS at 5 years among localized ASCC patients treated with 5-fluorouracil, mitomycin C, and radiotherapy. Proteomics pointed out mitochondria and mitochondrial cell-cycle genes as possible therapeutic targets for these high-risk patients. PLAIN LANGUAGE SUMMARY Anal squamous cell carcinoma is an infrequent tumor whose treatment has not been changed since the 1970s. However, disease-free survival in late staged tumors is between 40% and 70%. The presence of an alteration in the number of copies of CYP2D6 gene is a biomarker of worse disease-free survival. The analysis of the proteins in these high-risk patients pointed out mitochondria and mitochondrial cell-cycle genes as possible therapeutic targets. Therefore, the determination of the number of copies of CYP2D6 allows the identification of anal squamous carcinoma patients with a high-risk of relapse that could be redirected to a clinical trial. Additionally, this study may be useful to suggest new treatment strategies to increase current therapy efficacy.
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Affiliation(s)
| | - Angelo Gámez-Pozo
- Molecular Oncology Lab, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
- Biomedica Molecular Medicine SL, Madrid, Spain
| | - Miguel Nogué
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital de Granollers, Barcelona, Spain
| | - Isabel Busquier
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital Provincial de Castellón, Castellón, Spain
| | - Fernando Arias
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Radiotherapy Oncology Service, Complejo Hospitalario de Navarra, Navarra, Spain
| | - Fernando López-Campos
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Radiotherapy Oncology Service, Hospital Ramón y Cajal, Madrid, Spain
| | - Ana Fernández-Montes
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Complejo Hospitalario Universitario de Ourense, Ourense, Spain
| | - Ana Ruiz
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital Universitario Puerta de Hierro Majadahonda, IDIPHISA, Madrid, Spain
| | - Concepción Velázquez
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital Miguel Servet, Zaragoza, Spain
| | | | - Elisabeth Pérez-Ruiz
- Unidad de Gestión Clínica Intercentros de Oncología Médica, Hospitales Universitarios Regional y Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga, Hospitales Universitarios Regional y Virgen de la Victoria, Málaga, Spain
| | - Elena Asensio
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital General Universitario de Elche, Elche, Spain
| | - Xavier Hernández-Yagüe
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Instituto Catalán de Oncología-Girona, Girona, Spain
| | - Aline Rodrigues
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital Universitario de Salamanca, Salamanca, Spain
| | - Ismael Ghanem
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital Universitario La Paz, Madrid, Spain
| | - Rocío López-Vacas
- Molecular Oncology Lab, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
| | - Ahmed Hafez
- Biotechvana SL, Parque Científico de Madrid, Madrid, Spain
| | - Pedro Arias
- Pharmacogenetics Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - Irene Dapía
- Pharmacogenetics Lab, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Autonomous University of Madrid, Madrid, Spain
| | - Mario Solís
- Bioinformatics Unit, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain
| | - Antje Dittmann
- Functional Genomics Center Zurich, University of Zurich/ETH Zurich, Zurich, Switzerland
| | - Ricardo Ramos
- Genomics Unit, Parque Científico de Madrid, Madrid, Spain
| | - Carlos Llorens
- Biotechvana SL, Parque Científico de Madrid, Madrid, Spain
| | - Joan Maurel
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Department, Hospital Clínic of Barcelona, Translational Genomics and Targeted Therapeutics in Solid Tumors Group, IDIBAPS, University of Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Madrid, Spain
| | - Ángel Campos-Barros
- Institute of Medical and Molecular Genetics, IdiPAZ, Hospital Universitario La Paz/CIBERER Unit 753, ISCIII, Madrid, Spain
| | - Juan Ángel Fresno Vara
- Molecular Oncology Lab, Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
- Biomedica Molecular Medicine SL, Madrid, Spain
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
| | - Jaime Feliu
- Spanish Multidisciplinary Group of Digestive Cancer, Barcelona, Spain
- Medical Oncology Service, Hospital Universitario La Paz, Madrid, Spain
- Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Madrid, Spain
- Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Madrid, Spain
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23
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Santhanam B, Oikonomou P, Tavazoie S. Systematic assessment of prognostic molecular features across cancers. CELL GENOMICS 2023; 3:100262. [PMID: 36950380 PMCID: PMC10025453 DOI: 10.1016/j.xgen.2023.100262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/29/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023]
Abstract
Precision oncology promises accurate prediction of disease trajectories by utilizing molecular features of tumors. We present a systematic analysis of the prognostic potential of diverse molecular features across large cancer cohorts. We find that the mRNA expression of biologically coherent sets of genes (modules) is substantially more predictive of patient survival than single-locus genomic and transcriptomic aberrations. Extending our analysis beyond existing curated gene modules, we find a large novel class of highly prognostic DNA/RNA cis-regulatory modules associated with dynamic gene expression within cancers. Remarkably, in more than 82% of cancers, modules substantially improve survival stratification compared with conventional clinical factors and prominent genomic aberrations. The prognostic potential of cancer modules generalizes to external cohorts better than conventionally used single-gene features. Finally, a machine-learning framework demonstrates the combined predictive power of multiple modules, yielding prognostic models that perform substantially better than existing histopathological and clinical factors in common use.
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Affiliation(s)
- Balaji Santhanam
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10032, USA
| | - Panos Oikonomou
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10032, USA
| | - Saeed Tavazoie
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA
- Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10032, USA
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24
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Kinnaman MD, Zaccaria S, Makohon-Moore A, Arnold B, Levine M, Gundem G, Ossa JEA, Glodzik D, Rodríguez-Sánchez MI, Bouvier N, Li S, Stockfisch E, Dunigan M, Cobbs C, Bhanot U, You D, Mullen K, Melchor J, Ortiz MV, O'Donohue T, Slotkin E, Wexler LH, Dela Cruz FS, Hameed M, 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. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522765. [PMID: 36711976 PMCID: PMC9881990 DOI: 10.1101/2023.01.05.522765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however, little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. We performed whole-genome sequencing of 37 tumor samples from eight patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. We identified subclonal copy number alterations in all but one patient. We observed that in five patients, a subclonal copy number clone from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clone in 6 out of 7 patients with more than one clone. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy number clones. Our study sheds light on intratumor heterogeneity and the potential drivers of treatment resistance in osteosarcoma.
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Affiliation(s)
- Michael D Kinnaman
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Simone Zaccaria
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Computational Cancer Genomics Research Group, University College London Cancer Institute, London, UK
| | - Alvin Makohon-Moore
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Hackensack Meridian Health Center for Discovery and Innovation, Nutley, NJ, USA (current affiliation)
- Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC, USA (current affiliation)
| | - Brian Arnold
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Center for Statistics and Machine Learning, Princeton University, Princeton, NJ, USA
| | - Max Levine
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Isabl, New York, NY, USA (current affiliation)
| | - Gunes Gundem
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Juan E Arango Ossa
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dominik Glodzik
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA (current affiliation)
| | - M Irene Rodríguez-Sánchez
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Wunderman Thompson Health, New York, NY, USA (current affiliation)
| | - Nancy Bouvier
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- IT and Digital Initiatives, Memorial Sloan Kettering Cancer Center, New York, NY, USA (current affiliation)
| | - Shanita Li
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily Stockfisch
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marisa Dunigan
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Cassidy Cobbs
- Integrated Genomics Operation Core, Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Umesh Bhanot
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Precision Pathology Biobanking Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Daoqi You
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Katelyn Mullen
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, NY, USA
| | - Jerry Melchor
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael V Ortiz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Tara O'Donohue
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Emily Slotkin
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Leonard H Wexler
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Filemon S Dela Cruz
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Meera Hameed
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Julia L Glade Bender
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - William D Tap
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Paul A Meyers
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Elli Papaemmanuil
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew L Kung
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christine A Iacobuzio-Donahue
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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25
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Multiview Deep Forest for Overall Survival Prediction in Cancer. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2023; 2023:7931321. [PMID: 36714327 PMCID: PMC9876666 DOI: 10.1155/2023/7931321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 12/16/2022] [Accepted: 01/03/2023] [Indexed: 01/19/2023]
Abstract
Overall survival (OS) in cancer is crucial for cancer treatment. Many machine learning methods have been applied to predict OS, but there are still the challenges of dealing with multiview data and overfitting. To overcome these problems, we propose a multiview deep forest (MVDF) in this paper. MVDF can learn the features of each view and fuse them with integrated learning and multiple kernel learning. Then, a gradient boost forest based on the information bottleneck theory is proposed to reduce redundant information and avoid overfitting. In addition, a pruning strategy for a cascaded forest is used to limit the impact of outlier data. Comprehensive experiments have been carried out on a data set from West China Hospital of Sichuan University and two public data sets. Results have demonstrated that our method outperforms the compared methods in predicting overall survival.
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26
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Girish V, Lakhani AA, Scaduto CM, Thompson SL, Brown LM, Hagenson RA, Sausville EL, Mendelson BE, Lukow DA, Yuan ML, Kandikuppa PK, Stevens EC, Lee SN, Salovska B, Li W, Smith JC, Taylor AM, Martienssen RA, Liu Y, Sun R, Sheltzer JM. Oncogene-like addiction to aneuploidy in human cancers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.09.523344. [PMID: 36711674 PMCID: PMC9882055 DOI: 10.1101/2023.01.09.523344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses TP53 signaling, and we show that TP53 mutations are mutually-exclusive with 1q aneuploidy in human cancers. Thus, specific aneuploidies play essential roles in tumorigenesis, raising the possibility that targeting these "aneuploidy addictions" could represent a novel approach for cancer treatment.
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Affiliation(s)
- Vishruth Girish
- Yale University School of Medicine, New Haven, CT 06511
- Johns Hopkins University School of Medicine, Baltimore, MD 21205
| | | | | | | | | | | | | | | | | | - Monet Lou Yuan
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | | | | | - Sophia N. Lee
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Wenxue Li
- Yale University School of Medicine, New Haven, CT 06511
| | - Joan C. Smith
- Yale University School of Medicine, New Haven, CT 06511
| | | | - Robert A. Martienssen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Yansheng Liu
- Yale University School of Medicine, New Haven, CT 06511
| | - Ruping Sun
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455
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27
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Barriga FM, Tsanov KM, Ho YJ, Sohail N, Zhang A, Baslan T, Wuest AN, Del Priore I, Meškauskaitė B, Livshits G, Alonso-Curbelo D, Simon J, Chaves-Perez A, Bar-Sagi D, Iacobuzio-Donahue CA, Notta F, Chaligne R, Sharma R, Pe'er D, Lowe SW. MACHETE identifies interferon-encompassing chromosome 9p21.3 deletions as mediators of immune evasion and metastasis. NATURE CANCER 2022; 3:1367-1385. [PMID: 36344707 PMCID: PMC9701143 DOI: 10.1038/s43018-022-00443-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/13/2022] [Indexed: 11/09/2022]
Abstract
The most prominent homozygous deletions in cancer affect chromosome 9p21.3 and eliminate CDKN2A/B tumor suppressors, disabling a cell-intrinsic barrier to tumorigenesis. Half of 9p21.3 deletions, however, also encompass a type I interferon (IFN) gene cluster; the consequences of this co-deletion remain unexplored. To functionally dissect 9p21.3 and other large genomic deletions, we developed a flexible deletion engineering strategy, MACHETE (molecular alteration of chromosomes with engineered tandem elements). Applying MACHETE to a syngeneic mouse model of pancreatic cancer, we found that co-deletion of the IFN cluster promoted immune evasion, metastasis and immunotherapy resistance. Mechanistically, IFN co-deletion disrupted type I IFN signaling in the tumor microenvironment, leading to marked changes in infiltrating immune cells and escape from CD8+ T-cell surveillance, effects largely driven by the poorly understood interferon epsilon. These results reveal a chromosomal deletion that disables both cell-intrinsic and cell-extrinsic tumor suppression and provide a framework for interrogating large deletions in cancer and beyond.
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Affiliation(s)
- Francisco M Barriga
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kaloyan M Tsanov
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yu-Jui Ho
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Noor Sohail
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Amy Zhang
- PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Timour Baslan
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Alexandra N Wuest
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Isabella Del Priore
- Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, New York, NY, USA
| | - Brigita Meškauskaitė
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Geulah Livshits
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Direna Alonso-Curbelo
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Janelle Simon
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Almudena Chaves-Perez
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dafna Bar-Sagi
- Department of Biochemistry, New York University School of Medicine, New York, NY, USA
| | - Christine A Iacobuzio-Donahue
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Faiyaz Notta
- PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Division of Research, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Ronan Chaligne
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Roshan Sharma
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dana Pe'er
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Scott W Lowe
- Cancer Biology & Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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Wang D, Gao S, Qian H, Yuan P, Zhang B. Prognostic Value of Copy Number Alteration Burden in Early-Stage Breast Cancer and the Construction of an 11-Gene Copy Number Alteration Model. Cancers (Basel) 2022; 14:cancers14174145. [PMID: 36077687 PMCID: PMC9454926 DOI: 10.3390/cancers14174145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/20/2022] [Accepted: 08/23/2022] [Indexed: 11/16/2022] Open
Abstract
The increasing burden of breast cancer has prompted a wide range of researchers to search for new prognostic markers. Considering that tumor mutation burden (TMB) is low and copy number alteration burden (CNAB) is high in breast cancer, we built a CNAB-based model using a public database and validated it with a Chinese population. We collected formalin-fixed, paraffin-embedded (FFPE) tissue samples from 31 breast cancer patients who were treated between 2010 and 2014 at the National Cancer Center (CICAMS). METABRIC and TCGA data were downloaded via cBioPortal. In total, 2295 patients with early-stage breast cancer were enrolled in the study, including 1427 in the METABRIC cohort, 837 in the TCGA cohort, and 31 in the CICAMS cohort. Based on the ROC curve, we consider 2.2 CNA/MBp as the threshold for the CNAB-high and CNAB-low groupings. In both the TCGA cohort and the CICAMS cohort, CNAB-high had a worse prognosis than CNAB-low. We further simplified this model by establishing a prognostic nomogram for early breast cancer patients by 11 core genes, and this nomogram was highly effective in both the TCGA cohort and the CICAMS cohort. We hope that this model will subsequently help clinicians with prognostic assessments.
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Affiliation(s)
- Dingyuan Wang
- Department of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Songlin Gao
- Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Haili Qian
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Peng Yuan
- Department of VIP Medical Services, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
- Correspondence: (P.Y.); (B.Z.)
| | - Bailin Zhang
- Department of Breast Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
- Correspondence: (P.Y.); (B.Z.)
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Concerted Regulation of Glycosylation Factors Sustains Tissue Identity and Function. Biomedicines 2022; 10:biomedicines10081805. [PMID: 36009354 PMCID: PMC9404854 DOI: 10.3390/biomedicines10081805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 06/27/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022] Open
Abstract
Glycosylation is a fundamental cellular process affecting human development and health. Complex machinery establishes the glycan structures whose heterogeneity provides greater structural diversity than other post-translational modifications. Although known to present spatial and temporal diversity, the evolution of glycosylation and its role at the tissue-specific level is poorly understood. In this study, we combined genome and transcriptome profiles of healthy and diseased tissues to uncover novel insights into the complex role of glycosylation in humans. We constructed a catalogue of human glycosylation factors, including transferases, hydrolases and other genes directly involved in glycosylation. These were categorized as involved in N-, O- and lipid-linked glycosylation, glypiation, and glycosaminoglycan synthesis. Our data showed that these glycosylation factors constitute an ancient family of genes, where evolutionary constraints suppressed large gene duplications, except for genes involved in O-linked and lipid glycosylation. The transcriptome profiles of 30 healthy human tissues revealed tissue-specific expression patterns preserved across mammals. In addition, clusters of tightly co-expressed genes suggest a glycosylation code underlying tissue identity. Interestingly, several glycosylation factors showed tissue-specific profiles varying with age, suggesting a role in ageing-related disorders. In cancer, our analysis revealed that glycosylation factors are highly perturbed, at the genome and transcriptome levels, with a strong predominance of copy number alterations. Moreover, glycosylation factor dysregulation was associated with distinct cellular compositions of the tumor microenvironment, reinforcing the impact of glycosylation in modulating the immune system. Overall, this work provides genome-wide evidence that the glycosylation machinery is tightly regulated in healthy tissues and impaired in ageing and tumorigenesis, unveiling novel potential roles as prognostic biomarkers or therapeutic targets.
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Suelmann BBM, Rademaker A, van Dooijeweert C, van der Wall E, van Diest PJ, Moelans CB. Genomic copy number alterations as biomarkers for triple negative pregnancy-associated breast cancer. Cell Oncol (Dordr) 2022; 45:591-600. [PMID: 35792986 PMCID: PMC9424154 DOI: 10.1007/s13402-022-00685-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2022] [Indexed: 11/28/2022] Open
Abstract
Abstract
Background
PABC, commonly defined as breast cancer diagnosed during or ≤ 1 year after pregnancy, accounts for 7% of all breast cancers in women ≤ 45 years. Compared to age-matched non-PABC patients, PABC is characterized by a particularly aggressive histopathologic profile with poorly differentiated and estrogen- and progesterone receptor negative tumors and associated high mortality rates. This study assessed the genomic background of triple-negative PABC tumors by detection of copy number alterations (CNAs).
Methods
MLPA was used to compare CNAs in breast cancer-associated chromosomal loci between triple-negative PABC- and subtype-matched non-PABC patients. Both CNA patterns were evaluated by cluster analysis; associations between individual gene CNAs, pathological characteristics and survival were explored.
Results
Triple-negative PABC tumors exhibited unique CNAs compared to non-PABC tumors, including enrichment for TOP2A copy number loss, an independent predictor of worse overall survival (HR 8.96, p = 0.020). Cluster analysis based on CNA profiles identified a triple-negative PABC-subgroup with a particularly poor prognosis, characterized by chromosome 8p copy number loss. Individual gene CNAs analysis revealed that FGFR1 copy number loss on chromosome 8p11.23 was an independent predictor of poor outcome in multivariate analysis (HR 3.59, p = 0.053) and predicted the development of distant metastases (p = 0.048).
Conclusion
This study provides novel insights into the biology of triple-negative PABC tumors suggesting that CNAs, particularly 8p loss and TOP2A loss, are involved in the development of breast cancer during pregnancy. FGFR1 loss and TOP2A loss seem to be promising new biomarkers that independently identify subgroups of PABC patients with poor prognosis. These genomic biomarkers may provide clues for personalized therapy.
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Affiliation(s)
- B B M Suelmann
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - A Rademaker
- Department of Pathology, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
| | - C van Dooijeweert
- Department of Pathology, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
| | - E van der Wall
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - P J van Diest
- Department of Pathology, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
| | - C B Moelans
- Department of Pathology, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands.
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31
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Mazzocchetti G, Poletti A, Solli V, Borsi E, Martello M, Vigliotta I, Armuzzi S, Taurisano B, Zamagni E, Cavo M, Terragna C. BoBafit: a copy number clustering tool designed to refit and recalibrate the baseline region of tumors’ profiles. Comput Struct Biotechnol J 2022; 20:3718-3728. [PMID: 35891790 PMCID: PMC9294200 DOI: 10.1016/j.csbj.2022.06.062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 11/16/2022] Open
Abstract
Tools generating CN profiles derive the baseline region from samples’ median CN signal. This canonical approach might cause wrongly estimated CN profile in complex karyotypes. CNAs call is crucial for patients’ risk stratification aimed at personalized treatment. BoBafit computes the correct baseline region and the CN profile, taking into account tumor genomic complexity and samples-specific alterations. BoBafit should be implemented within CN analysis pipelines especially for clinical aims.
Human cancer arises from a population of cells that have acquired a wide range of genetic alterations, most of which are targets of therapeutic treatments or are used as prognostic factors for patient’s risk stratification. Among these, copy number alterations (CNAs) are quite frequent. Currently, several molecular biology technologies, such as microarrays, NGS and single-cell approaches are used to define the genomic profile of tumor samples. Output data need to be analyzed with bioinformatic approaches and particularly by employing computational algorithms. Molecular biology tools estimate the baseline region by comparing either the mean probe signals, or the number of reads to the reference genome. However, when tumors display complex karyotypes, this type of approach could fail the baseline region estimation and consequently cause errors in the CNAs call. To overcome this issue, we designed an R-package, BoBafit, able to check and, eventually, to adjust the baseline region, according to both the tumor-specific alterations’ context and the sample-specific clustered genomic lesions. Several databases have been chosen to set up and validate the designed package, thus demonstrating the potential of BoBafit to adjust copy number (CN) data from different tumors and analysis techniques. Relevantly, the analysis highlighted that up to 25% of samples need a baseline region adjustment and a redefinition of CNAs calls, thus causing a change in the prognostic risk classification of the patients. We support the implementation of BoBafit within CN analysis bioinformatics pipelines to ensure a correct patient’s stratification in risk categories, regardless of the tumor type.
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Schukken KM, Sheltzer JM. Extensive protein dosage compensation in aneuploid human cancers. Genome Res 2022; 32:1254-1270. [PMID: 35701073 PMCID: PMC9341510 DOI: 10.1101/gr.276378.121] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 06/01/2022] [Indexed: 01/03/2023]
Abstract
Aneuploidy is a hallmark of human cancers, but the effects of aneuploidy on protein expression remain poorly understood. To uncover how chromosome copy number changes influence the cancer proteome, we conducted an analysis of hundreds of human cancer cell lines and tumors with matched copy number, RNA expression, and protein expression data. We found that a majority of proteins show dosage compensation and fail to change by the degree expected based on chromosome copy number alone. We uncovered a variety of gene groups that were recurrently buffered upon both chromosome gain and loss, including protein complex subunits and cell cycle genes. Several genetic and biophysical factors were predictive of protein buffering, highlighting complex post-translational regulatory mechanisms that maintain appropriate gene product dosage. Finally, we established that chromosomal aneuploidy has a moderate effect on the expression of oncogenes and tumor suppressors, showing that these key cancer drivers can be subject to dosage compensation as well. In total, our comprehensive analysis of aneuploidy and dosage compensation across cancers will help identify the key driver genes encoded on altered chromosomes and will shed light on the overall consequences of aneuploidy during tumor development.
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33
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Crawford J, Christensen BC, Chikina M, Greene CS. Widespread redundancy in -omics profiles of cancer mutation states. Genome Biol 2022; 23:137. [PMID: 35761387 PMCID: PMC9238138 DOI: 10.1186/s13059-022-02705-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 06/14/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal remains unclear. RESULTS We consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem that presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. From the TCGA Pan-Cancer Atlas that contains genetic alteration data, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts. Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. We find that one or more other data types for many of the genes are approximately equally effective predictors. Performance is more variable between mutations than that between data types for the same mutation, and there is little difference between the top data types. We also find that combining data types into a single multi-omics model provides little or no improvement in predictive ability over the best individual data type. CONCLUSIONS Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.
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Affiliation(s)
- Jake Crawford
- grid.25879.310000 0004 1936 8972Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Brock C. Christensen
- grid.254880.30000 0001 2179 2404Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH USA ,grid.254880.30000 0001 2179 2404Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH USA
| | - Maria Chikina
- grid.21925.3d0000 0004 1936 9000Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
| | - Casey S. Greene
- grid.430503.10000 0001 0703 675XDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO USA ,grid.430503.10000 0001 0703 675XCenter for Health AI, University of Colorado School of Medicine, Aurora, CO USA
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34
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Ravi VM, Will P, Kueckelhaus J, Sun N, Joseph K, Salié H, Vollmer L, Kuliesiute U, von Ehr J, Benotmane JK, Neidert N, Follo M, Scherer F, Goeldner JM, Behringer SP, Franco P, Khiat M, Zhang J, Hofmann UG, Fung C, Ricklefs FL, Lamszus K, Boerries M, Ku M, Beck J, Sankowski R, Schwabenland M, Prinz M, Schüller U, Killmer S, Bengsch B, Walch AK, Delev D, Schnell O, Heiland DH. Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma. Cancer Cell 2022; 40:639-655.e13. [PMID: 35700707 DOI: 10.1016/j.ccell.2022.05.009] [Citation(s) in RCA: 167] [Impact Index Per Article: 83.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 09/30/2021] [Accepted: 05/13/2022] [Indexed: 12/11/2022]
Abstract
Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments.
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Affiliation(s)
- Vidhya M Ravi
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany; Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg, Freiburg, Germany; Center of Advanced Surgical Tissue Analysis (CAST), University of Freiburg, Freiburg, Germany
| | - Paulina Will
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Jan Kueckelhaus
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany; Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Department of Neurosurgery, RWTH University of Aachen, Aachen, Germany
| | - Na Sun
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Kevin Joseph
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany; Center of Advanced Surgical Tissue Analysis (CAST), University of Freiburg, Freiburg, Germany
| | - Henrike Salié
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Medicine II: Gastroenterology, Hepatology, Endocrinology, and Infectious Disease, Medical Center - University of Freiburg, Freiburg, Germany
| | - Lea Vollmer
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Ugne Kuliesiute
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany; The Institute of Biosciences, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Jasmin von Ehr
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Jasim K Benotmane
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Nicolas Neidert
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Marie Follo
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany
| | - Florian Scherer
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Medicine I, Medical Center - University of Freiburg, Freiburg, Germany
| | - Jonathan M Goeldner
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Simon P Behringer
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Pamela Franco
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Mohammed Khiat
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Junyi Zhang
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany
| | - Ulrich G Hofmann
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Neuroelectronic Systems, Medical Center - University of Freiburg, Freiburg, Germany
| | - Christian Fung
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Franz L Ricklefs
- Department of Neurosurgery, University Hospital Eppendorf, Hamburg, Germany; Laboratory for Brain Tumor Biology, University Hospital Eppendorf, Hamburg, Germany
| | - Katrin Lamszus
- Department of Neurosurgery, University Hospital Eppendorf, Hamburg, Germany; Laboratory for Brain Tumor Biology, University Hospital Eppendorf, Hamburg, Germany
| | - Melanie Boerries
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Medical Bioinformatics and Systems Medicine, Medical Center-University of Freiburg, Freiburg, Germany; Comprehensive Cancer Center Freiburg (CCCF), Medical Center - University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), partner site Freiburg, Freiburg, Germany
| | - Manching Ku
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Pediatrics and Adolescent Medicine, Division of Pediatric Hematology and Oncology, Medical Center - University of Freiburg, Freiburg, Germany
| | - Jürgen Beck
- Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center for NeuroModulation (NeuroModul), University of Freiburg, Freiburg, Germany; Center of Advanced Surgical Tissue Analysis (CAST), University of Freiburg, Freiburg, Germany
| | - Roman Sankowski
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Neuropathology, Medical Center - University of Freiburg, Freiburg, German
| | - Marius Schwabenland
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Neuropathology, Medical Center - University of Freiburg, Freiburg, German
| | - Marco Prinz
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center for NeuroModulation (NeuroModul), University of Freiburg, Freiburg, Germany; Institute of Neuropathology, Medical Center - University of Freiburg, Freiburg, German; Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Ulrich Schüller
- Institute of Neuropathology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany; Research Institute Children's Cancer Center, Hamburg, Germany; Department of Pediatric Hematology and Oncology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Saskia Killmer
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Medicine II: Gastroenterology, Hepatology, Endocrinology, and Infectious Disease, Medical Center - University of Freiburg, Freiburg, Germany
| | - Bertram Bengsch
- Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Medicine II: Gastroenterology, Hepatology, Endocrinology, and Infectious Disease, Medical Center - University of Freiburg, Freiburg, Germany; Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Axel K Walch
- Research Unit Analytical Pathology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Daniel Delev
- Neurosurgical Artificial Intelligence Laboratory Aachen (NAILA), Department of Neurosurgery, RWTH University of Aachen, Aachen, Germany; Department of Neurosurgery, RWTH University of Aachen, Aachen, Germany
| | - Oliver Schnell
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Translational NeuroOncology Research Group, Medical Center - University of Freiburg, Freiburg, Germany; Center of Advanced Surgical Tissue Analysis (CAST), University of Freiburg, Freiburg, Germany
| | - Dieter Henrik Heiland
- Microenvironment and Immunology Research Laboratory, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Faculty of Medicine, University of Freiburg, Freiburg, Germany; Comprehensive Cancer Center Freiburg (CCCF), Medical Center - University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK), partner site Freiburg, Freiburg, Germany; Center of Advanced Surgical Tissue Analysis (CAST), University of Freiburg, Freiburg, Germany.
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35
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Hercules SM, Liu X, Bassey-Archibong BBI, Skeete DHA, Smith Connell S, Daramola A, Banjo AA, Ebughe G, Agan T, Ekanem IO, Udosen J, Obiorah C, Ojule AC, Misauno MA, Dauda AM, Egbujo EC, Hercules JC, Ansari A, Brain I, MacColl C, Xu Y, Jin Y, Chang S, Carpten JD, Bédard A, Pond GR, Blenman KRM, Manojlovic Z, Daniel JM. Analysis of the genomic landscapes of Barbadian and Nigerian women with triple negative breast cancer. Cancer Causes Control 2022; 33:831-841. [PMID: 35384527 PMCID: PMC9085672 DOI: 10.1007/s10552-022-01574-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 03/12/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that disproportionately affects women of African ancestry (WAA) and is often associated with poor survival. Although there is a high prevalence of TNBC across West Africa and in women of the African diaspora, there has been no comprehensive genomics study to investigate the mutational profile of ancestrally related women across the Caribbean and West Africa. METHODS This multisite cross-sectional study used 31 formalin-fixed paraffin-embedded (FFPE) samples from Barbadian and Nigerian TNBC participants. High-resolution whole exome sequencing (WES) was performed on the Barbadian and Nigerian TNBC samples to identify their mutational profiles and comparisons were made to African American, European American and Asian American sequencing data obtained from The Cancer Genome Atlas (TCGA). Whole exome sequencing was conducted on tumors with an average of 382 × coverage and 4335 × coverage for pooled germline non-tumor samples. RESULTS Variants detected at high frequency in our WAA cohorts were found in the following genes NBPF12, PLIN4, TP53 and BRCA1. In the TCGA TNBC cases, these genes had a lower mutation rate, except for TP53 (32% in our cohort; 63% in TCGA-African American; 67% in TCGA-European American; 63% in TCGA-Asian). For all altered genes, there were no differences in frequency of mutations between WAA TNBC groups including the TCGA-African American cohort. For copy number variants, high frequency alterations were observed in PIK3CA, TP53, FGFR2 and HIF1AN genes. CONCLUSION This study provides novel insights into the underlying genomic alterations in WAA TNBC samples and shines light on the importance of inclusion of under-represented populations in cancer genomics and biomarker studies.
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Affiliation(s)
- Shawn M. Hercules
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
- African Caribbean Cancer Consortium, Philadelphia, PA USA
| | - Xiyu Liu
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | | | - Desiree H. A. Skeete
- African Caribbean Cancer Consortium, Philadelphia, PA USA
- grid.412886.10000 0004 0592 769XFaculty of Medical Sciences, University of the West Indies at Cave Hill, Bridgetown, Barbados
- grid.415521.60000 0004 0570 5165Department of Pathology, Queen Elizabeth Hospital, Bridgetown, Barbados
| | - Suzanne Smith Connell
- grid.412886.10000 0004 0592 769XFaculty of Medical Sciences, University of the West Indies at Cave Hill, Bridgetown, Barbados
- grid.415521.60000 0004 0570 5165Department of Radiation Oncology, Queen Elizabeth Hospital, Bridgetown, Barbados
- Present Address: Cancer Specialists Inc, Bridgetown, Barbados
| | - Adetola Daramola
- grid.411283.d0000 0000 8668 7085Department of Anatomic and Molecular Pathology, Lagos University Teaching Hospital, Lagos, Nigeria
| | - Adekunbiola A. Banjo
- grid.411283.d0000 0000 8668 7085Department of Anatomic and Molecular Pathology, Lagos University Teaching Hospital, Lagos, Nigeria
| | - Godwin Ebughe
- grid.413097.80000 0001 0291 6387Department of Pathology, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Thomas Agan
- grid.413097.80000 0001 0291 6387Department of Obstetrics & Gynaecology, College of Medical Sciences, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Ima-Obong Ekanem
- grid.413097.80000 0001 0291 6387Department of Pathology, College of Medical Sciences, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Joe Udosen
- grid.413097.80000 0001 0291 6387Division of General and Breast Surgery, University of Calabar Teaching Hospital, Calabar, Nigeria
| | - Christopher Obiorah
- grid.412738.bDepartment of Anatomical Pathology, University of Port Harcourt Teaching Hospital, Port Harcourt, Nigeria
| | - Aaron C. Ojule
- grid.412738.bDepartment of Chemical Pathology, University of Port Harcourt Teaching Hospital, Port Harcourt, Nigeria
| | - Michael A. Misauno
- grid.411946.f0000 0004 1783 4052Department of Surgery, Jos University Teaching Hospital, Jos, Nigeria
| | - Ayuba M. Dauda
- grid.411946.f0000 0004 1783 4052Department of Pathology, Jos University Teaching Hospital, Jos, Nigeria
| | | | - Jevon C. Hercules
- grid.12916.3d0000 0001 2322 4996Department of Mathematics, University of the West Indies at Mona, Kingston, Jamaica
- grid.12955.3a0000 0001 2264 7233Present Address: Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China
| | - Amna Ansari
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
| | - Ian Brain
- grid.25073.330000 0004 1936 8227Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON Canada
| | - Christine MacColl
- grid.25073.330000 0004 1936 8227Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON Canada
| | - Yili Xu
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Yuxin Jin
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Sharon Chang
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - John D. Carpten
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - André Bédard
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
| | - Greg R. Pond
- grid.25073.330000 0004 1936 8227Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON Canada
- grid.25073.330000 0004 1936 8227Department of Oncology, McMaster University, Hamilton, ON Canada
| | - Kim R. M. Blenman
- grid.433818.5Department of Internal Medicine, Section of Medical Oncology, Yale Cancer Center, School of Medicine, New Haven, CT USA
- grid.47100.320000000419368710Department of Computer Science, School of Engineering and Applied Science, Yale University, New Haven, CT USA
| | - Zarko Manojlovic
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Juliet M. Daniel
- grid.25073.330000 0004 1936 8227Department of Biology, McMaster University, Hamilton, ON Canada
- African Caribbean Cancer Consortium, Philadelphia, PA USA
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36
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Bowers RR, Jones CM, Paz EA, Barrows JK, Armeson K, Long D, Delaney J. SWAN pathway-network identification of common aneuploidy-based oncogenic drivers. Nucleic Acids Res 2022; 50:3673-3692. [PMID: 35380699 PMCID: PMC9023287 DOI: 10.1093/nar/gkac200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 02/26/2022] [Accepted: 03/14/2022] [Indexed: 02/07/2023] Open
Abstract
Haploinsufficiency drives Darwinian evolution. Siblings, while alike in many aspects, differ due to monoallelic differences inherited from each parent. In cancer, solid tumors exhibit aneuploid genetics resulting in hundreds to thousands of monoallelic gene-level copy-number alterations (CNAs) in each tumor. Aneuploidy patterns are heterogeneous, posing a challenge to identify drivers in this high-noise genetic environment. Here, we developed Shifted Weighted Annotation Network (SWAN) analysis to assess biology impacted by cumulative monoallelic changes. SWAN enables an integrated pathway-network analysis of CNAs, RNA expression, and mutations via a simple web platform. SWAN is optimized to best prioritize known and novel tumor suppressors and oncogenes, thereby identifying drivers and potential druggable vulnerabilities within cancer CNAs. Protein homeostasis, phospholipid dephosphorylation, and ion transport pathways are commonly suppressed. An atlas of CNA pathways altered in each cancer type is released. These CNA network shifts highlight new, attractive targets to exploit in solid tumors.
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Affiliation(s)
- Robert R Bowers
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Christian M Jones
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Edwin A Paz
- Departments of Neurology, Neurobiology, and Cell Biology, and the Duke Center for Neurodegeneration & Neurotherapeutics, Duke University School of Medicine, Durham, NC, USA
| | - John K Barrows
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Kent E Armeson
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - David T Long
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
| | - Joe R Delaney
- Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA
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37
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Smith JC, Sheltzer JM. Genome-wide identification and analysis of prognostic features in human cancers. Cell Rep 2022; 38:110569. [PMID: 35354049 DOI: 10.1016/j.celrep.2022.110569] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/30/2022] [Accepted: 03/03/2022] [Indexed: 12/12/2022] Open
Abstract
Clinical decisions in cancer rely on precisely assessing patient risk. To improve our ability to identify the most aggressive malignancies, we constructed genome-wide survival models using gene expression, copy number, methylation, and mutation data from 10,884 patients. We identified more than 100,000 significant prognostic biomarkers and demonstrate that these genomic features can predict patient outcomes in clinically ambiguous situations. While adverse biomarkers are commonly believed to represent cancer driver genes and promising therapeutic targets, we show that cancer features associated with shorter survival times are not enriched for either oncogenes or for successful drug targets. Instead, the strongest adverse biomarkers represent widely expressed cell-cycle and housekeeping genes, and, correspondingly, nearly all therapies directed against these features have failed in clinical trials. In total, our analysis establishes a rich resource for prognostic biomarker analysis and clarifies the use of patient survival data in preclinical cancer research and therapeutic development.
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Affiliation(s)
- Joan C Smith
- Yale University School of Medicine, New Haven, CT 06511, USA; Google, Inc., New York, NY 10011, USA
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38
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Early Breast Cancer Evolution by Autosomal Broad Copy Number Alterations. Int J Genomics 2022; 2022:9332922. [PMID: 35252434 PMCID: PMC8896957 DOI: 10.1155/2022/9332922] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 02/08/2022] [Indexed: 12/13/2022] Open
Abstract
The availability of comprehensive genomic datasets across patient populations enables the application of novel methods for reconstructing tumor evolution within individual patients. To this end, we propose studying autosomal broad copy number alterations (CNAs) as a framework to better understand early tumor evolution. We compared the broad CNAs and somatic mutations of patients with 1 to 10 autosomal broad CNAs against the full set of patients, using data from The Cancer Genome Atlas breast cancer project. We reveal here that the frequency of a chromosome arm obtaining a broad CNA and a genome acquiring somatic mutations changes as autosomal broad CNAs accumulate. Therefore, we propose that the number of autosomal broad CNAs is an important characteristic of breast tumors that needs to be taken into consideration when studying breast tumors. To investigate this idea more in-depth, we next studied the frequency that specific chromosome arms acquire broad CNAs in patients with 1 to 10 broad CNAs. With this process, we identified the broad CNAs that exhibit the fastest rates of accumulation across all patients. This finding suggests a likely order of occurrence of these alterations in patients, which is apparent when we consider a subset of patients with few broad CNAs. Here, we lay the foundation for future studies to build upon our findings and use autosomal broad CNAs as a method to monitor breast tumor progression in vivo to further our understanding of how early tumor evolution unfolds.
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39
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Migliaccio I, Paoli M, Risi E, Biagioni C, Biganzoli L, Benelli M, Malorni L. PIK3CA co-occurring mutations and copy-number gain in hormone receptor positive and HER2 negative breast cancer. NPJ Breast Cancer 2022; 8:24. [PMID: 35181669 PMCID: PMC8857304 DOI: 10.1038/s41523-022-00382-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 01/11/2022] [Indexed: 12/31/2022] Open
Abstract
We aim to elucidate the prognostic value of PIK3CA mutations and copy number (CN) gain (PIK3CA-mut/gain) in hormone receptor-positive and HER2-negative (HR + /HER2−) breast cancer (BC). We analyzed primary HR + /HER2− BC from three publicly available datasets comprising over 2000 samples and assessed the associations with tumoral and clinical characteristics and outcome. Clinical benefit (CB) in alpelisib-treated patients from two studies including 46 patients was analyzed. About 8–10% of HR + /HER2− primary BC had PIK3CA-mut/gain. In two of the datasets analyzed, among patients with PIK3CA mutant tumors, those with mut/gain had significantly worse outcome compared to those with CN neutral (PIK3CA-mut/neut) and PIK3CA-mut/gain remained an independent prognostic factor. CB of alpelisib-treated patients with PIK3CA-mut/gain and PIK3CA-mut/neut tumors was comparable. PIK3CA CN might help clarifying the prognostic and predictive role of PIK3CA mutations. Further studies are warranted.
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Affiliation(s)
- Ilenia Migliaccio
- "Sandro Pitigliani" Translational Research Unit, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy.
| | - Marta Paoli
- Bioinformatics Unit, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy
| | - Emanuela Risi
- "Sandro Pitigliani" Department of Medical Oncology, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy
| | - Chiara Biagioni
- Bioinformatics Unit, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy.,"Sandro Pitigliani" Department of Medical Oncology, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy
| | - Laura Biganzoli
- "Sandro Pitigliani" Department of Medical Oncology, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy
| | - Matteo Benelli
- Bioinformatics Unit, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy
| | - Luca Malorni
- "Sandro Pitigliani" Translational Research Unit, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy.,"Sandro Pitigliani" Department of Medical Oncology, Hospital of Prato, Azienda USL Toscana Centro, 59100, Prato, Italy
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40
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A gene signature consisting of ubiquitin ligases and deubiquitinating enzymes of SKP2 is associated with clinical outcome in breast cancer. Sci Rep 2022; 12:2478. [PMID: 35169199 PMCID: PMC8847659 DOI: 10.1038/s41598-022-06451-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 01/31/2022] [Indexed: 11/11/2022] Open
Abstract
The ubiquitination of SKP2, an oncoprotein, is controlled by its E3 ligases, including APC/CFZR1 and deubiquitinases such as USP10. We identified a two-gene signature for the ubiquitination of SKP2, consisting of the copy number of FZR1 compared to the copy number of USP10. The signature reflects the level of SKP2 activity, stratifying BC patients into two groups with significantly different protein levels of SKP2 ubiquitination substrate p27 (t-test p < 0.01) and recapitulating the expression patterns of SKP2 between tumor and normal tissue (Spearman’s ρ = 0.39.) The signature is also highly associated with clinical outcome in luminal BC but not other subtypes, characterizing patients into two groups with significantly different overall survival times (log-rank p = 0.006). In addition, it is dramatically associated with tumor grade (Chi-squared p = 6.7 × 10−3), stage (Chi-squared p = 1.6 × 10−11), and the number of positive lymph nodes (negative binomial regression coefficient p = 2.0 × 10−3). Our study provides a rationale for targeting the SKP2 ubiquitination pathway in luminal BC and for further investigation of the use of ubiquitinase/deubiquitinase genes as prognosis and treatment biomarkers.
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41
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Testa U, Pelosi E, Castelli G. Molecular charcterization of lung adenocarcinoma combining whole exome sequencing, copy number analysis and gene expression profiling. Expert Rev Mol Diagn 2021; 22:77-100. [PMID: 34894979 DOI: 10.1080/14737159.2022.2017774] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
INTRODUCTION Lung cancer is the leading cause of cancer mortality worldwide; lung adenocarcinoma (LUAD) corresponds to about 40% of lung cancers. LUAD is a genetically heterogeneous disease and the definition of this heterogeneity is of fundamental importance for prognosis and treatment. AREAS COVERED Based on primary literature, this review provides an updated analysis of multiomics studies based on the study of mutation profiling, copy number alterations and gene expression allowing for definition of molecular subgroups, prognostic factors based on molecular biomarkers, and identification of therapeutic targets. The authors sum up by providing the reader with their expert opinion on the potentialities of multiomics analysis of LUADs. EXPERT OPINION A detailed and comprehensive study of the co-occurring genetic abnormalities characterizing different LUAD subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of LUADs may provide a fundamental contribution to improve the survival of LUAD patients.
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Affiliation(s)
- Ugo Testa
- Department of Oncology, Istituto Superiore di Sanità, Rome, Italy
| | - Elvira Pelosi
- Department of Oncology, Istituto Superiore di Sanità, Rome, Italy
| | - Germana Castelli
- Department of Oncology, Istituto Superiore di Sanità, Rome, Italy
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42
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Marazioti A, Krontira AC, Behrend SJ, Giotopoulou GA, Ntaliarda G, Blanquart C, Bayram H, Iliopoulou M, Vreka M, Trassl L, Pepe MAA, Hackl CM, Klotz LV, Weiss SAI, Koch I, Lindner M, Hatz RA, Behr J, Wagner DE, Papadaki H, Antimisiaris SG, Jean D, Deshayes S, Grégoire M, Kayalar Ö, Mortazavi D, Dilege Ş, Tanju S, Erus S, Yavuz Ö, Bulutay P, Fırat P, Psallidas I, Spella M, Giopanou I, Lilis I, Lamort AS, Stathopoulos GT. KRAS signaling in malignant pleural mesothelioma. EMBO Mol Med 2021; 14:e13631. [PMID: 34898002 PMCID: PMC8819314 DOI: 10.15252/emmm.202013631] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 10/28/2021] [Accepted: 11/15/2021] [Indexed: 12/20/2022] Open
Abstract
Malignant pleural mesothelioma (MPM) arises from mesothelial cells lining the pleural cavity of asbestos‐exposed individuals and rapidly leads to death. MPM harbors loss‐of‐function mutations in BAP1, NF2, CDKN2A, and TP53, but isolated deletion of these genes alone in mice does not cause MPM and mouse models of the disease are sparse. Here, we show that a proportion of human MPM harbor point mutations, copy number alterations, and overexpression of KRAS with or without TP53 changes. These are likely pathogenic, since ectopic expression of mutant KRASG12D in the pleural mesothelium of conditional mice causes epithelioid MPM and cooperates with TP53 deletion to drive a more aggressive disease form with biphasic features and pleural effusions. Murine MPM cell lines derived from these tumors carry the initiating KRASG12D lesions, secondary Bap1 alterations, and human MPM‐like gene expression profiles. Moreover, they are transplantable and actionable by KRAS inhibition. Our results indicate that KRAS alterations alone or in accomplice with TP53 alterations likely play an important and underestimated role in a proportion of patients with MPM, which warrants further exploration.
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Affiliation(s)
- Antonia Marazioti
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Anthi C Krontira
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Sabine J Behrend
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Georgia A Giotopoulou
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece.,German Center for Lung Research (DZL), Gießen, Germany
| | - Giannoula Ntaliarda
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | | | - Hasan Bayram
- Department of Pulmonary Medicine, Koc University School of Medicine, Istanbul, Turkey.,Koc University Research Center for Translational Medicine (KUTTAM), Koc University School of Medicine, Istanbul, Turkey
| | - Marianthi Iliopoulou
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Malamati Vreka
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece.,German Center for Lung Research (DZL), Gießen, Germany
| | - Lilith Trassl
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Mario A A Pepe
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Caroline M Hackl
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Laura V Klotz
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Stefanie A I Weiss
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Ina Koch
- German Center for Lung Research (DZL), Gießen, Germany.,Center for Thoracic Surgery Munich, Ludwig-Maximilian-University (LMU) Munich and Asklepios Medical Center, Gauting, Germany
| | - Michael Lindner
- German Center for Lung Research (DZL), Gießen, Germany.,Center for Thoracic Surgery Munich, Ludwig-Maximilian-University (LMU) Munich and Asklepios Medical Center, Gauting, Germany
| | - Rudolph A Hatz
- German Center for Lung Research (DZL), Gießen, Germany.,Center for Thoracic Surgery Munich, Ludwig-Maximilian-University (LMU) Munich and Asklepios Medical Center, Gauting, Germany
| | - Juergen Behr
- German Center for Lung Research (DZL), Gießen, Germany.,Department of Medicine V, University Hospital, Ludwig-Maximilian-University (LMU) Munich, Munich, Germany
| | - Darcy E Wagner
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany.,Lung Bioengineering and Regeneration, Department of Experimental Medical Sciences, Lund Stem Cell Center, Wallenberg Molecular Medicine Center, Faculty of Medicine, Lund University, Lund, Sweden
| | - Helen Papadaki
- Department of Anatomy, Faculty of Medicine, University of Patras, Rio, Greece
| | - Sophia G Antimisiaris
- Laboratory for Pharmaceutical Technology, Department of Pharmacy, School of Health Sciences, University of Patras, Rio, Greece.,Foundation for Research and Technology Hellas, Institute of Chemical Engineering, FORTH/ICE-HT, Rio, Greece
| | - Didier Jean
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Functional Genomics of Solid Tumors, Paris, France
| | | | - Marc Grégoire
- Université de Nantes, CNRS, INSERM, CRCINA, Nantes, France
| | - Özgecan Kayalar
- Koc University Research Center for Translational Medicine (KUTTAM), Koc University School of Medicine, Istanbul, Turkey
| | - Deniz Mortazavi
- Koc University Research Center for Translational Medicine (KUTTAM), Koc University School of Medicine, Istanbul, Turkey
| | - Şükrü Dilege
- Department of Thoracic Surgery, Koc University School of Medicine, Istanbul, Turkey
| | - Serhan Tanju
- Department of Thoracic Surgery, Koc University School of Medicine, Istanbul, Turkey
| | - Suat Erus
- Department of Thoracic Surgery, Koc University School of Medicine, Istanbul, Turkey
| | - Ömer Yavuz
- Department of Thoracic Surgery, Koc University School of Medicine, Istanbul, Turkey
| | - Pınar Bulutay
- Department of Pathology, Koc University School of Medicine, Istanbul, Turkey
| | - Pınar Fırat
- Department of Pathology, Koc University School of Medicine, Istanbul, Turkey
| | - Ioannis Psallidas
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Magda Spella
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Ioanna Giopanou
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Ioannis Lilis
- Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece
| | - Anne-Sophie Lamort
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,German Center for Lung Research (DZL), Gießen, Germany
| | - Georgios T Stathopoulos
- Comprehensive Pneumology Center (CPC) and Institute for Lung Biology and Disease (iLBD), Helmholtz Center Munich-German Research Center for Environmental Health (HMGU) and Ludwig-Maximilian-University (LMU) Munich, Munich, Germany.,Laboratory for Molecular Respiratory Carcinogenesis, Department of Physiology, Faculty of Medicine, University of Patras, Rio, Greece.,German Center for Lung Research (DZL), Gießen, Germany
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43
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Thomas A, do Canto Alvim LM, Rainho CA, Juengel E, Blaheta RA, Spiess PE, Rogatto SR, Tsaur I. Systemic treatment of penile squamous cell carcinoma-hurdles and hopes of preclinical models and clinical regimens: a narrative review. Transl Androl Urol 2021; 10:4085-4098. [PMID: 34804850 PMCID: PMC8575571 DOI: 10.21037/tau-20-945] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 10/07/2020] [Indexed: 01/06/2023] Open
Abstract
Despite contemporary research efforts, the prognosis of penile squamous cell carcinoma (PeSCC) has not significantly improved over the past decade. Despite frequently encountered patient-related delayed medical consultations impairing outcomes, several other aspects contribute to the lack of advancement in the treatment of this condition. One essential reason is that translational research, a prerequisite for the clinically successful disease management, is still at an early stage in PeSCC as compared to many other malignancies. Preclinical experimental models are indispensable for the evaluation of tumor biology and identification of genomic alterations. However, since neither commercial PeSCC cell lines are available nor xenograft models sustainably established, such analyses are challenging in this field of research. In addition, systemic therapies are less effective and toxic without decisive breakthroughs over recent years. Current systemic management of PeSCC is based on protocols that have been investigated in small series of only up to 30 patients. Thus, there is an unmet medical need for new approaches necessitating research efforts to develop more efficacious systemic strategies. This review aims to highlight the current state of knowledge in the molecular alterations involved in the etiology and ensuing steps for cancer progression, existing preclinical models of translational research, clinically relevant systemic protocols, and ongoing clinical trials.
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Affiliation(s)
- Anita Thomas
- Department of Urology and Pediatric Urology, University Medicine Mainz, Mainz, Germany
| | - Luisa Matos do Canto Alvim
- Department of Clinical Genetics, University Hospital of Southern Denmark, Vejle, Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Claudia Aparecida Rainho
- Department of Chemical and Biological Sciences, Institute of Biosciences, São Paulo State University (UNESP), Botucatu, São Paulo, Brazil
| | - Eva Juengel
- Department of Urology and Pediatric Urology, University Medicine Mainz, Mainz, Germany
| | | | - Philippe E Spiess
- Department of Genitourinary Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Silvia Regina Rogatto
- Department of Clinical Genetics, University Hospital of Southern Denmark, Vejle, Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Igor Tsaur
- Department of Urology and Pediatric Urology, University Medicine Mainz, Mainz, Germany
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44
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Sen O, Harrison JU, Burroughs NJ, McAinsh AD. Kinetochore life histories reveal an Aurora-B-dependent error correction mechanism in anaphase. Dev Cell 2021; 56:3082-3099.e5. [PMID: 34758290 PMCID: PMC8629432 DOI: 10.1016/j.devcel.2021.10.007] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 07/26/2021] [Accepted: 10/06/2021] [Indexed: 12/30/2022]
Abstract
Chromosome mis-segregation during mitosis leads to aneuploidy, which is a hallmark of cancer and linked to cancer genome evolution. Errors can manifest as "lagging chromosomes" in anaphase, although their mechanistic origins and likelihood of correction are incompletely understood. Here, we combine lattice light-sheet microscopy, endogenous protein labeling, and computational analysis to define the life history of >104 kinetochores. By defining the "laziness" of kinetochores in anaphase, we reveal that chromosomes are at a considerable risk of mis-segregation. We show that the majority of lazy kinetochores are corrected rapidly in anaphase by Aurora B; if uncorrected, they result in a higher rate of micronuclei formation. Quantitative analyses of the kinetochore life histories reveal a dynamic signature of metaphase kinetochore oscillations that forecasts their anaphase fate. We propose that in diploid human cells chromosome segregation is fundamentally error prone, with an additional layer of anaphase error correction required for stable karyotype propagation.
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Affiliation(s)
- Onur Sen
- Centre for Mechanochemical Cell Biology, University of Warwick, Coventry, UK; Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Jonathan U Harrison
- Centre for Mechanochemical Cell Biology, University of Warwick, Coventry, UK; Mathematics Institute and Zeeman Institute, University of Warwick, Coventry, UK
| | - Nigel J Burroughs
- Centre for Mechanochemical Cell Biology, University of Warwick, Coventry, UK; Mathematics Institute and Zeeman Institute, University of Warwick, Coventry, UK.
| | - Andrew D McAinsh
- Centre for Mechanochemical Cell Biology, University of Warwick, Coventry, UK; Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK; University Hospital Coventry and Warwickshire NHS Trust, Coventry, UK.
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45
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Zerdes I, Simonetti M, Matikas A, Harbers L, Acs B, Boyaci C, Zhang N, Salgkamis D, Agartz S, Moreno-Ruiz P, Bai Y, Rimm DL, Hartman J, Mezheyeuski A, Bergh J, Crosetto N, Foukakis T. Interplay between copy number alterations and immune profiles in the early breast cancer Scandinavian Breast Group 2004-1 randomized phase II trial: results from a feasibility study. NPJ Breast Cancer 2021; 7:144. [PMID: 34799582 PMCID: PMC8604966 DOI: 10.1038/s41523-021-00352-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 10/21/2021] [Indexed: 12/12/2022] Open
Abstract
Emerging data indicate that genomic alterations can shape immune cell composition in early breast cancer. However, there is a need for complementary imaging and sequencing methods for the quantitative assessment of combined somatic copy number alteration (SCNA) and immune profiling in pathological samples. Here, we tested the feasibility of three approaches-CUTseq, for high-throughput low-input SCNA profiling, multiplexed fluorescent immunohistochemistry (mfIHC) and digital-image analysis (DIA) for quantitative immuno-profiling- in archival formalin-fixed paraffin-embedded (FFPE) tissue samples from patients enrolled in the randomized SBG-2004-1 phase II trial. CUTseq was able to reproducibly identify amplification and deletion events with a resolution of 100 kb using only 6 ng of DNA extracted from FFPE tissue and pooling together 77 samples into the same sequencing library. In the same samples, mfIHC revealed that CD4 + T-cells and CD68 + macrophages were the most abundant immune cells and they mostly expressed PD-L1 and PD-1. Combined analysis showed that the SCNA burden was inversely associated with lymphocytic infiltration. Our results set the basis for further applications of CUTseq, mfIHC and DIA to larger cohorts of early breast cancer patients.
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Affiliation(s)
- Ioannis Zerdes
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Breast Center, Theme Cancer, Karolinska University Hospital, Stockholm, Sweden
| | - Michele Simonetti
- Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Stockholm, Sweden
| | - Alexios Matikas
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Breast Center, Theme Cancer, Karolinska University Hospital, Stockholm, Sweden
| | - Luuk Harbers
- Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Stockholm, Sweden
| | - Balazs Acs
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Department of Pathology and Cytology, Karolinska University Hospital, Stockholm, Sweden
| | - Ceren Boyaci
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Department of Pathology and Cytology, Karolinska University Hospital, Stockholm, Sweden
| | - Ning Zhang
- Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Stockholm, Sweden
| | | | - Susanne Agartz
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Pablo Moreno-Ruiz
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Yalai Bai
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - David L Rimm
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Johan Hartman
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
- Department of Pathology and Cytology, Karolinska University Hospital, Stockholm, Sweden
| | - Artur Mezheyeuski
- Department of Immunology, Genetics, and Pathology, Uppsala University, Uppsala, Sweden
| | - Jonas Bergh
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
- Breast Center, Theme Cancer, Karolinska University Hospital, Stockholm, Sweden.
| | - Nicola Crosetto
- Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
- Science for Life Laboratory, Stockholm, Sweden.
| | - Theodoros Foukakis
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
- Breast Center, Theme Cancer, Karolinska University Hospital, Stockholm, Sweden.
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46
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Bejar JF, DiSanza Z, Quartuccio SM. The oncogenic role of meiosis-specific Aurora kinase C in mitotic cells. Exp Cell Res 2021; 407:112803. [PMID: 34461108 DOI: 10.1016/j.yexcr.2021.112803] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/27/2021] [Accepted: 08/23/2021] [Indexed: 02/07/2023]
Abstract
Aberrant expression of meiosis-specific genes in cancer has recently emerged as a driver of some cancer formation. Aurora kinase C (AURKC) is a member of the Aurora kinase family of proteins known to regulate chromosome segregation during cell divisions. AURKC is normally expressed in meiotic cells; however, elevated levels of AURKC mRNA and protein are frequently measured in cancer cells. To understand the function of AURKC in cancer cells, expression was induced in noncancerous, human retina pigmented epithelial cells. While AURKC expression did not alter cell proliferation over 72 h, it did increase cell migration and anchorage independent growth in soft agar suggesting an oncogenic role in mitotically dividing cells. To evaluate AURKC as a potential therapeutic target, a frameshift mutation in the gene was introduced in U2OS osteosarcoma cells using CRISPR-Cas9 technology resulting in a premature stop codon. Cancer cells lacking AURKC displayed no change in cell proliferation over 72 h but did migrate less and formed fewer colonies in soft agar. Whole transcriptome sequencing analysis uncovered over 400 differentially expressed genes in U2OS cells with and without AURKC. GO analysis revealed alterations in proteinaceous extracellular matrix genes including COL1A1. These data indicate that therapeutics targeting AURKC could decrease cancer cell metastasis and disease progression. Because AURKC is transcriptionally silenced in normal mitotic cells, its disruption could specifically target cancer cells limiting the toxic side effects associated with current therapeutics.
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Affiliation(s)
- Justin F Bejar
- Department of Biological Sciences, Seton Hall University, South Orange, NJ, USA
| | - Zachary DiSanza
- Department of Biological Sciences, Seton Hall University, South Orange, NJ, USA
| | - Suzanne M Quartuccio
- Department of Biological Sciences, Seton Hall University, South Orange, NJ, USA.
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47
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Lukow DA, Sheltzer JM. Chromosomal instability and aneuploidy as causes of cancer drug resistance. Trends Cancer 2021; 8:43-53. [PMID: 34593353 DOI: 10.1016/j.trecan.2021.09.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/02/2021] [Accepted: 09/07/2021] [Indexed: 01/08/2023]
Abstract
High levels of aneuploidy and chromosomal instability (CIN) are correlated with poor patient outcomes, though the mechanism(s) underlying this relationship have not been established. Recent evidence has demonstrated that chromosome copy number changes can function as point mutation-independent sources of drug resistance in cancer, which may partially explain this clinical association. CIN generates intratumoral heterogeneity in the form of gene dosage alterations, upon which the selective pressures induced by drug treatments can act. Thus, although CIN and aneuploidy impair cell fitness under most conditions, CIN can augment cellular adaptability, establishing CIN as a bet-hedging mechanism in tumor evolution. CIN may also endow cancers with unique vulnerabilities, which could be exploited therapeutically to achieve better patient outcomes.
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Affiliation(s)
- Devon A Lukow
- Yale University, New Haven, CT 06511, USA; Stony Brook University, Stony Brook, NY 11794, USA
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48
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Vendramin R, Litchfield K, Swanton C. Cancer evolution: Darwin and beyond. EMBO J 2021; 40:e108389. [PMID: 34459009 PMCID: PMC8441388 DOI: 10.15252/embj.2021108389] [Citation(s) in RCA: 109] [Impact Index Per Article: 36.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 06/04/2021] [Accepted: 06/25/2021] [Indexed: 12/16/2022] Open
Abstract
Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.
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Affiliation(s)
- Roberto Vendramin
- Cancer Research UK Lung Cancer Centre of ExcellenceUniversity College London Cancer InstituteLondonUK
| | - Kevin Litchfield
- Cancer Research UK Lung Cancer Centre of ExcellenceUniversity College London Cancer InstituteLondonUK
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of ExcellenceUniversity College London Cancer InstituteLondonUK
- Cancer Evolution and Genome Instability LaboratoryThe Francis Crick InstituteLondonUK
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49
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Wang J, Luo FF, Huang TJ, Mei Y, Peng LX, Qian CN, Huang BJ. The upregulated expression of RFC4 and GMPS mediated by DNA copy number alteration is associated with the early diagnosis and immune escape of ESCC based on a bioinformatic analysis. Aging (Albany NY) 2021; 13:21758-21777. [PMID: 34520390 PMCID: PMC8457608 DOI: 10.18632/aging.203520] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 08/31/2021] [Indexed: 12/24/2022]
Abstract
Esophageal squamous cell carcinoma (ESCC) is a malignant tumor that commonly occurs worldwide. Usually, Asia, especially China, has a high incidence of esophageal cancer. ESCC often has a poor outcome because of a late diagnosis and lack of effective treatments. To build foundations for the early diagnosis and treatment of ESCC, we used the gene expression datasets GSE20347 and GSE17351 from the GEO database and a private dataset to uncover differentially expressed genes (DEGs) and key genes in ESCC. Notably, we found that replication factor C subunit 4 (RFC4) and guanine monophosphate synthase (GMPS) were upregulated but have been rarely studied in ESCC. In particular, to the best of our knowledge, our study is the first to explore GMPS and ESCC. Furthermore, we found that high levels of RFC4 and GMPS expression may result from an increase in DNA copy number alterations. Furthermore, RFC4 and GMPS were both upregulated in the early stage and early nodal metastases of esophageal carcinoma. The expression of RFC4 was strongly correlated with GMPS. In addition, we explored the relationship between RFC4 and GMPS expression and tumor-infiltrating immune cells (TILs) in esophageal carcinoma. The results showed that the levels of RFC4 and GMPS increased with a decrease in some tumor-infiltrating cells. Upregulated RFC4 and GMPS with high TILs indicate a worse prognosis. In summary, our study shows that RFC4 and GMPS have potential as biomarkers for the early diagnosis of ESCC and may played a crucial role in the process of tumor immunity in ESCC.
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Affiliation(s)
- Jing Wang
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China
| | - Fei-Fei Luo
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China
| | - Tie-Jun Huang
- Department of Nuclear Medicine, The Second People's Hospital of Shenzhen, Shenzhen 518037, People's Republic of China
| | - Yan Mei
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China
| | - Li-Xia Peng
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China
| | - Chao-Nan Qian
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China.,Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China
| | - Bi-Jun Huang
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, People's Republic of China
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50
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Lukow DA, Sausville EL, Suri P, Chunduri NK, Wieland A, Leu J, Smith JC, Girish V, Kumar AA, Kendall J, Wang Z, Storchova Z, Sheltzer JM. Chromosomal instability accelerates the evolution of resistance to anti-cancer therapies. Dev Cell 2021; 56:2427-2439.e4. [PMID: 34352222 PMCID: PMC8933054 DOI: 10.1016/j.devcel.2021.07.009] [Citation(s) in RCA: 96] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 05/09/2021] [Accepted: 07/15/2021] [Indexed: 12/20/2022]
Abstract
Aneuploidy is a ubiquitous feature of human tumors, but the acquisition of aneuploidy typically antagonizes cellular fitness. To investigate how aneuploidy could contribute to tumor growth, we triggered periods of chromosomal instability (CIN) in human cells and then exposed them to different culture environments. We discovered that transient CIN reproducibly accelerates the acquisition of resistance to anti-cancer therapies. Single-cell sequencing revealed that these resistant populations develop recurrent aneuploidies, and independently deriving one chromosome-loss event that was frequently observed in paclitaxel-resistant cells was sufficient to decrease paclitaxel sensitivity. Finally, we demonstrated that intrinsic levels of CIN correlate with poor responses to numerous therapies in human tumors. Our results show that, although CIN generally decreases cancer cell fitness, it also provides phenotypic plasticity to cancer cells that can allow them to adapt to diverse stressful environments. Moreover, our findings suggest that aneuploidy may function as an under-explored cause of therapy failure.
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Affiliation(s)
- Devon A Lukow
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Stony Brook University, Stony Brook, NY 11794, USA
| | - Erin L Sausville
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Pavit Suri
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Narendra Kumar Chunduri
- European Research Institute for the Biology of Aging, 9713 AV Groningen, the Netherlands; Department of Molecular Genetics, TU Kaiserslautern, Paul-Ehrlich Str. 24, 67663 Kaiserslautern, Germany
| | - Angela Wieland
- Department of Molecular Genetics, TU Kaiserslautern, Paul-Ehrlich Str. 24, 67663 Kaiserslautern, Germany
| | - Justin Leu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Joan C Smith
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Google, Inc., New York, NY 10011, USA
| | - Vishruth Girish
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Ankith A Kumar
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Jude Kendall
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Zihua Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Zuzana Storchova
- Department of Molecular Genetics, TU Kaiserslautern, Paul-Ehrlich Str. 24, 67663 Kaiserslautern, Germany
| | - Jason M Sheltzer
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
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