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Hakobyan A, Meyenberg M, Vardazaryan N, Hancock J, Vulliard L, Loizou JI, Menche J. Pan-cancer analysis of the interplay between mutational signatures and cellular signaling. iScience 2024; 27:109873. [PMID: 38783997 PMCID: PMC11112613 DOI: 10.1016/j.isci.2024.109873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 12/19/2023] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
Cancer is a multi-faceted disease with intricate relationships between mutagenic processes, alterations in cellular signaling, and the tissue microenvironment. To date, these processes have been largely studied in isolation. A systematic understanding of how they interact and influence each other is lacking. Here, we present a framework for systematically characterizing the interaction between pairs of mutational signatures and between signatures and signaling pathway alterations. We applied this framework to large-scale data from TCGA and PCAWG and identified multiple positive and negative interactions, both cross֊tissue and tissue֊specific, that provide new insights into the molecular routes observed in tumorigenesis and their respective drivers. This framework allows for a more fine-grained dissection of common and distinct etiology of mutational signatures. We further identified several interactions with both positive and negative impacts on patient survival, demonstrating their clinical relevance and potential for improving personalized cancer care.
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Affiliation(s)
- Anna Hakobyan
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT25.3, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
| | - Mathilde Meyenberg
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT25.3, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- Center for Cancer Research, Comprehensive Cancer Center, Medical University of Vienna, Spitalgasse 23, BT86/E 01, 1090 Vienna, Austria
| | - Nelli Vardazaryan
- Armenian Bioinformatics Institute, 3/6 Nelson Stepanyan, 0062 Yerevan, Armenia
| | - Joel Hancock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT25.3, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
| | - Loan Vulliard
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT25.3, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
| | - Joanna I. Loizou
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT25.3, 1090 Vienna, Austria
- Center for Cancer Research, Comprehensive Cancer Center, Medical University of Vienna, Spitalgasse 23, BT86/E 01, 1090 Vienna, Austria
| | - Jörg Menche
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT25.3, 1090 Vienna, Austria
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- University of Vienna, Center for Molecular Biology, Department of Structural and Computational Biology, Dr.-Bohr-Gasse 9, 1030 Vienna, Austria
- Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria
- Ludwig Boltzmann Institute for Network Medicine at the University of Vienna, Augasse 2-6, 1090 Vienna, Austria
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2
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Tam YB, Low K, Ps H, Chadha M, Burns J, Wilding CP, Arthur A, Chen TW, Thway K, Sadanandam A, Jones RL, Huang PH. Proteomic features of soft tissue tumours in adolescents and young adults. COMMUNICATIONS MEDICINE 2024; 4:93. [PMID: 38762630 PMCID: PMC11102500 DOI: 10.1038/s43856-024-00522-x] [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: 07/13/2023] [Accepted: 05/07/2024] [Indexed: 05/20/2024] Open
Abstract
BACKGROUND Adolescents and young adult (AYA) patients with soft tissue tumours including sarcomas are an underserved group with disparities in treatment outcomes. METHODS To define the molecular features between AYA and older adult (OA) patients, we analysed the proteomic profiles of a large cohort of soft tissue tumours across 10 histological subtypes (AYA n = 66, OA n = 243), and also analysed publicly available functional genomic data from soft tissue tumour cell lines (AYA n = 5, OA n = 8). RESULTS Biological hallmarks analysis demonstrates that OA tumours are significantly enriched in MYC targets compared to AYA tumours. By comparing the patient-level proteomic data with functional genomic profiles from sarcoma cell lines, we show that the mRNA splicing pathway is an intrinsic vulnerability in cell lines from OA patients and that components of the spliceosome complex are independent prognostic factors for metastasis free survival in AYA patients. CONCLUSIONS Our study highlights the importance of performing age-specific molecular profiling studies to identify risk stratification tools and targeted agents tailored for the clinical management of AYA patients.
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Affiliation(s)
- Yuen Bun Tam
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Kaan Low
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Hari Ps
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Madhumeeta Chadha
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Jessica Burns
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Christopher P Wilding
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Amani Arthur
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Tom W Chen
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Oncology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Khin Thway
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
- The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Anguraj Sadanandam
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom
| | - Robin L Jones
- The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Division of Clinical Studies, The Institute of Cancer Research, London, United Kingdom
| | - Paul H Huang
- Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom.
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3
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Al-Danakh A, Safi M, Jian Y, Yang L, Zhu X, Chen Q, Yang K, Wang S, Zhang J, Yang D. Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients. Front Immunol 2024; 15:1348189. [PMID: 38590525 PMCID: PMC11000233 DOI: 10.3389/fimmu.2024.1348189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 01/29/2024] [Indexed: 04/10/2024] Open
Abstract
Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.
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Affiliation(s)
- Abdullah Al-Danakh
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Mohammed Safi
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Yuli Jian
- Department of Biochemistry and Molecular Biology, Institute of Glycobiology, Dalian Medical University, Dalian, China
| | - Linlin Yang
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Xinqing Zhu
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Qiwei Chen
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Kangkang Yang
- Institute for Genome Engineered Animal Models of Human Diseases, National Center of Genetically Engineered Animal Models for International Research, Dalian Medical University, Dalian, Liaoning, China
| | - Shujing Wang
- Department of Biochemistry and Molecular Biology, Institute of Glycobiology, Dalian Medical University, Dalian, China
| | - Jianjun Zhang
- Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Deyong Yang
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
- Department of Surgery, Healinghands Clinic, Dalian, Liaoning, China
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4
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Huang F, Xu P, Yue Z, Song Y, Hu K, Zhao X, Gao M, Chong Z. Body Weight Correlates with Molecular Variances in Patients with Cancer. Cancer Res 2024; 84:757-770. [PMID: 38190709 PMCID: PMC10911806 DOI: 10.1158/0008-5472.can-23-1463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/27/2023] [Accepted: 01/03/2024] [Indexed: 01/10/2024]
Abstract
Overweight and obesity are identified by a high body mass index (BMI) and carry significant health risks due to associated comorbidities. Although epidemiologic data connect overweight/obesity with 13 cancer types, a better understanding of the molecular mechanisms underlying this correlation is needed to improve prevention and treatment strategies. In this study, we conducted a comprehensive analysis of molecular differences between overweight or obese patients and normal weight patients across 14 different cancer types from The Cancer Genome Atlas. Using the propensity score weighting algorithm to control for confounding factors, obesity-specific mutational features were identified, such as higher mutation burden in rectal cancer and biased mutational signatures in other cancers. Differentially expressed genes (DEG) in tumors from patients with overweight/obesity were predominantly upregulated and enriched in inflammatory and hormone-related pathways. These DEGs were significantly associated with survival rates in various cancer types, highlighting the impact of elevated body fat on gene expression profiles and clinical outcomes in patients with cancer. Interestingly, while high BMI seemed to have a negative impact on most cancer types, the normal weight-biased mutational and gene expression patterns indicated overweight/obesity may be beneficial in endometrial cancer, suggesting the presence of an "obesity paradox" in this context. Body fat also significantly impacted the tumor microenvironment by modulating immune cell infiltration, underscoring the importance of understanding the interplay between weight and immune response in cancer progression. Together, this study systematically elucidates the molecular differences corresponding to body weight in multiple cancer types, offering potentially critical insights for developing precision therapy for patients with cancer. SIGNIFICANCE Elucidation of the complex interplay between body weight and the molecular landscape of cancer could potentially guide tailored therapies and improve patient management amid the global obesity crisis.
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Affiliation(s)
- Fengyuan Huang
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Peng Xu
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Zongliang Yue
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Yuwei Song
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Kaili Hu
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Xinyang Zhao
- Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, Kansas
| | - Min Gao
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Zechen Chong
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- Department of Genetics, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama
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5
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Yin C, Wang R, Qiao J, Shi H, Duan H, Jiang X, Teng S, Wei L. NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection. Bioinformatics 2024; 40:btae046. [PMID: 38305428 PMCID: PMC10873575 DOI: 10.1093/bioinformatics/btae046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 02/15/2024] [Accepted: 01/30/2024] [Indexed: 02/03/2024] Open
Abstract
MOTIVATION 5-Methylcytosine (5mC), a fundamental element of DNA methylation in eukaryotes, plays a vital role in gene expression regulation, embryonic development, and other biological processes. Although several computational methods have been proposed for detecting the base modifications in DNA like 5mC sites from Nanopore sequencing data, they face challenges including sensitivity to noise, and ignoring the imbalanced distribution of methylation sites in real-world scenarios. RESULTS Here, we develop NanoCon, a deep hybrid network coupled with contrastive learning strategy to detect 5mC methylation sites from Nanopore reads. In particular, we adopted a contrastive learning module to alleviate the issues caused by imbalanced data distribution in nanopore sequencing, offering a more accurate and robust detection of 5mC sites. Evaluation results demonstrate that NanoCon outperforms existing methods, highlighting its potential as a valuable tool in genomic sequencing and methylation prediction. In addition, we also verified the effectiveness of our representation learning ability on two datasets by visualizing the dimension reduction of the features of methylation and nonmethylation sites from our NanoCon. Furthermore, cross-species and cross-5mC methylation motifs experiments indicated the robustness and the ability to perform transfer learning of our model. We hope this work can contribute to the community by providing a powerful and reliable solution for 5mC site detection in genomic studies. AVAILABILITY AND IMPLEMENTATION The project code is available at https://github.com/Challis-yin/NanoCon.
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Affiliation(s)
- Chenglin Yin
- School of Software, Shandong University, Jinan, China
- Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, China
| | - Ruheng Wang
- School of Software, Shandong University, Jinan, China
- Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, China
| | - Jianbo Qiao
- School of Software, Shandong University, Jinan, China
- Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, China
| | - Hua Shi
- School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China
| | - Hongliang Duan
- Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China
| | - Xinbo Jiang
- School of Qilu Transportation, Shandong University, Jinan, China
| | - Saisai Teng
- School of Software, Shandong University, Jinan, China
- Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, China
| | - Leyi Wei
- School of Software, Shandong University, Jinan, China
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6
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Taraszka K, Groha S, King D, Tell R, White K, Ziv E, Zaitlen N, Gusev A. A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden. Am J Hum Genet 2024; 111:242-258. [PMID: 38211585 PMCID: PMC10870141 DOI: 10.1016/j.ajhg.2023.12.010] [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: 07/18/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.
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Affiliation(s)
- Kodi Taraszka
- Department of Computer Science, University of California, Los Angeles, CA 90095, USA; Department of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA 02215, USA.
| | - Stefan Groha
- Department of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA 02215, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - David King
- Tempus Labs, Inc, Chicago, IL 60654, USA
| | | | | | - Elad Ziv
- Department of Medicine, University of California San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, CA 94158, USA
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, CA 90095, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA 02215, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
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7
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Dotan E, Lynch SM, Ryan JC, Mitchell EP. Disparities in care of older adults of color with cancer: A narrative review. Cancer Med 2024; 13:e6790. [PMID: 38234214 PMCID: PMC10905558 DOI: 10.1002/cam4.6790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/06/2023] [Accepted: 11/23/2023] [Indexed: 01/19/2024] Open
Abstract
This review describes the barriers and challenges faced by older adults of color with cancer and highlights methods to improve their overall care. In the next decade, cancer incidence rates are expected to increase in the United States for people aged ≥65 years. A large proportion will be older adults of color who often have worse outcomes than older White patients. Many issues contribute to racial disparities in older adults, including biological factors and social determinants of health (SDOH) related to healthcare access, socioeconomic concerns, systemic racism, mistrust, and the neighborhood where a person lives. These disparities are exacerbated by age-related challenges often experienced by older adults, such as decreased functional status, impaired cognition, high rates of comorbidities and polypharmacy, poor nutrition, and limited social support. Additionally, underrepresentation of both patients of color and older adults in cancer clinical research results in a lack of adequate data to guide the management of these patients. Use of geriatric assessments (GA) can aid providers in uncovering age-related concerns and personalizing interventions for older patients. Research demonstrates the ability of GA-directed care to result in fewer treatment-related toxicities and improved quality of life, thus supporting the routine incorporation of validated GA into these patients' care. GA can be enhanced by including evaluation of SDOH, which can help healthcare providers understand and address the needs of older adults of color with cancer who face disparities related to their age and race.
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Affiliation(s)
- Efrat Dotan
- Department of Hematology/OncologyFox Chase Cancer CenterPhiladelphiaPennsylvaniaUSA
| | | | | | - Edith P. Mitchell
- Clinical Professor of Medicine and Medical OncologySidney Kimmel Cancer Center at JeffersonPhiladelphiaPennsylvaniaUSA
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8
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Nishida J, Cristea S, Bodapati S, Puleo J, Bai G, Patel A, Hughes M, Snow C, Borges V, Ruddy KJ, Collins LC, Feeney AM, Slowik K, Bossuyt V, Dillon D, Lin NU, Partridge AH, Michor F, Polyak K. Peripheral blood TCR clonotype diversity as an age-associated marker of breast cancer progression. Proc Natl Acad Sci U S A 2023; 120:e2316763120. [PMID: 38011567 DOI: 10.1073/pnas.2316763120] [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: 09/26/2023] [Accepted: 10/27/2023] [Indexed: 11/29/2023] Open
Abstract
Immune escape is a prerequisite for tumor growth. We previously described a decline in intratumor activated cytotoxic T cells and T cell receptor (TCR) clonotype diversity in invasive breast carcinomas compared to ductal carcinoma in situ (DCIS), implying a central role of decreasing T cell responses in tumor progression. To determine potential associations between peripheral immunity and breast tumor progression, here, we assessed the peripheral blood TCR clonotype of 485 breast cancer patients diagnosed with either DCIS or de novo stage IV disease at younger (<45) or older (≥45) age. TCR clonotype diversity was significantly lower in older compared to younger breast cancer patients regardless of tumor stage at diagnosis. In the younger age group, TCR-α clonotype diversity was lower in patients diagnosed with de novo stage IV breast cancer compared to those diagnosed with DCIS. In the older age group, DCIS patients with higher TCR-α clonotype diversity were more likely to have a recurrence compared to those with lower diversity. Whole blood transcriptome profiles were distinct depending on the TCR-α Chao1 diversity score. There were more CD8+ T cells and a more active immune environment in DCIS tumors of young patients with higher peripheral blood TCR-α Chao1 diversity than in those with lower diversity. These results provide insights into the role that host immunity plays in breast cancer development across different age groups.
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MESH Headings
- Humans
- Aged
- Female
- Breast Neoplasms/pathology
- Carcinoma, Intraductal, Noninfiltrating/genetics
- Carcinoma, Intraductal, Noninfiltrating/pathology
- CD8-Positive T-Lymphocytes/pathology
- Biomarkers, Tumor/genetics
- Receptors, Antigen, T-Cell/genetics
- Neoplastic Processes
- Receptors, Antigen, T-Cell, alpha-beta/genetics
- Carcinoma, Ductal, Breast/pathology
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Affiliation(s)
- Jun Nishida
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Simona Cristea
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Sudheshna Bodapati
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
| | - Julieann Puleo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Gali Bai
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Ashka Patel
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Melissa Hughes
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Craig Snow
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Virginia Borges
- Medicine-Medical Oncology, University of Colorado Comprehensive Cancer Center, Aurora, CO 80045
| | - Kathryn J Ruddy
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, MN 55905
| | - Laura C Collins
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115
| | - Anne-Marie Feeney
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
| | - Kara Slowik
- The Broad Institute of MIT and Harvard, Cambridge, MA 02138
| | - Veerle Bossuyt
- Mass General Pathology, Massachusetts General Hospital, Boston, MA 02114
| | - Deborah Dillon
- Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115
| | - Nancy U Lin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Ann H Partridge
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
| | - Franziska Michor
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
- The Broad Institute of MIT and Harvard, Cambridge, MA 02138
- The Ludwig Center at Harvard, Boston, MA 02115
- Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215
| | - Kornelia Polyak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115
- Department of Medicine, Harvard Medical School, Boston, MA 02115
- Mass General Pathology, Massachusetts General Hospital, Boston, MA 02114
- The Ludwig Center at Harvard, Boston, MA 02115
- Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215
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9
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Dos Santos GA, Chatsirisupachai K, Avelar RA, de Magalhães JP. Transcriptomic analysis reveals a tissue-specific loss of identity during ageing and cancer. BMC Genomics 2023; 24:644. [PMID: 37884865 PMCID: PMC10604446 DOI: 10.1186/s12864-023-09756-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 10/20/2023] [Indexed: 10/28/2023] Open
Abstract
INTRODUCTION Understanding changes in cell identity in cancer and ageing is of great importance. In this work, we analyzed how gene expression changes in human tissues are associated with tissue specificity during cancer and ageing using transcriptome data from TCGA and GTEx. RESULTS We found significant downregulation of tissue-specific genes during ageing in 40% of the tissues analyzed, which suggests loss of tissue identity with age. For most cancer types, we have noted a consistent pattern of downregulation in genes that are specific to the tissue from which the tumor originated. Moreover, we observed in cancer an activation of genes not usually expressed in the tissue of origin as well as an upregulation of genes specific to other tissues. These patterns in cancer were associated with patient survival. The age of the patient, however, did not influence these patterns. CONCLUSION We identified loss of cellular identity in 40% of the tissues analysed during human ageing, and a clear pattern in cancer, where during tumorigenesis cells express genes specific to other organs while suppressing the expression of genes from their original tissue. The loss of cellular identity observed in cancer is associated with prognosis and is not influenced by age, suggesting that it is a crucial stage in carcinogenesis.
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Affiliation(s)
- Gabriel Arantes Dos Santos
- Laboratory of Medical Investigation (LIM55), Urology Department, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, B15 2WB, UK
| | - Kasit Chatsirisupachai
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L7 8TX, UK
| | - Roberto A Avelar
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L7 8TX, UK
| | - João Pedro de Magalhães
- Genomics of Ageing and Rejuvenation Lab, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, B15 2WB, UK.
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10
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Hudson KM, Klimczak LJ, Sterling JF, Burkholder AB, Kazanov M, Saini N, Mieczkowski PA, Gordenin DA. Glycidamide-induced hypermutation in yeast single-stranded DNA reveals a ubiquitous clock-like mutational motif in humans. Nucleic Acids Res 2023; 51:9075-9100. [PMID: 37471042 PMCID: PMC10516655 DOI: 10.1093/nar/gkad611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 06/28/2023] [Accepted: 07/10/2023] [Indexed: 07/21/2023] Open
Abstract
Mutagens often prefer specific nucleotides or oligonucleotide motifs that can be revealed by studying the hypermutation spectra in single-stranded (ss) DNA. We utilized a yeast model to explore mutagenesis by glycidamide, a simple epoxide formed endogenously in humans from the environmental toxicant acrylamide. Glycidamide caused ssDNA hypermutation in yeast predominantly in cytosines and adenines. The most frequent mutations in adenines occurred in the nAt→nGt trinucleotide motif. Base substitutions A→G in this motif relied on Rev1 translesion polymerase activity. Inactivating Rev1 did not alter the nAt trinucleotide preference, suggesting it may be an intrinsic specificity of the chemical reaction between glycidamide and adenine in the ssDNA. We found this mutational motif enriched in published sequencing data from glycidamide-treated mouse cells and ubiquitous in human cancers. In cancers, this motif was positively correlated with the single base substitution (SBS) smoking-associated SBS4 signature, with the clock-like signatures SBS1, SBS5, and was strongly correlated with smoking history and with age of tumor donors. Clock-like feature of the motif was also revealed in cells of human skin and brain. Given its pervasiveness, we propose that this mutational motif reflects mutagenic lesions to adenines in ssDNA from a potentially broad range of endogenous and exogenous agents.
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Affiliation(s)
- Kathleen M Hudson
- Genome Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, US National Institutes of Health, Durham, NC 27709, USA
| | - Leszek J Klimczak
- Integrative Bioinformatics Support Group, National Institute of Environmental Health Sciences, US National Institutes of Health, Durham, NC 27709, USA
| | - Joan F Sterling
- Genome Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, US National Institutes of Health, Durham, NC 27709, USA
| | - Adam B Burkholder
- Office of Environmental Science Cyberinfrastructure, National Institute of Environmental Health Sciences, US National Institutes of Health, Durham, NC 27709, USA
| | - Marat D Kazanov
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, 34956, Turkey
- Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Natalie Saini
- Department of Biochemistry & Molecular Biology, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Piotr A Mieczkowski
- Department of Genetics, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Dmitry A Gordenin
- Genome Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, US National Institutes of Health, Durham, NC 27709, USA
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11
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Rojas-Díaz D, Puerta-Yepes ME, Medina-Gaspar D, Botero JA, Rodríguez A, Rojas N. Mathematical Modeling for the Assessment of Public Policies in the Cancer Health-Care System Implemented for the Colombian Case. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6740. [PMID: 37754600 PMCID: PMC10531264 DOI: 10.3390/ijerph20186740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 06/28/2023] [Accepted: 07/20/2023] [Indexed: 09/28/2023]
Abstract
The incidence of cancer has been constantly growing worldwide, placing pressure on health systems and increasing the costs associated with the treatment of cancer. In particular, low- and middle-income countries are expected to face serious challenges related to caring for the majority of the world's new cancer cases in the next 10 years. In this study, we propose a mathematical model that allows for the simulation of different strategies focused on public policies by combining spending and epidemiological indicators. In this way, strategies aimed at efficient spending management with better epidemiological indicators can be determined. For validation and calibration of the model, we use data from Colombia-which, according to the World Bank, is an upper-middle-income country. The results of the simulations using the proposed model, calibrated and validated for Colombia, indicate that the most effective strategy for reducing mortality and financial burden consists of a combination of early detection and greater efficiency of treatment in the early stages of cancer. This approach is found to present a 38% reduction in mortality rate and a 20% reduction in costs (% GDP) when compared to the baseline scenario. Hence, Colombia should prioritize comprehensive care models that focus on patient-centered care, prevention, and early detection.
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Affiliation(s)
- Daniel Rojas-Díaz
- Area of Fundamental Sciences, School of Applied Sciences and Engineering, Universidad EAFIT, Medellin 050022, Colombia
| | - María Eugenia Puerta-Yepes
- Area of Fundamental Sciences, School of Applied Sciences and Engineering, Universidad EAFIT, Medellin 050022, Colombia
| | - Daniel Medina-Gaspar
- School of Finance, Economics, and Government, Universidad EAFIT, Medellin 050022, Colombia
| | - Jesús Alonso Botero
- School of Finance, Economics, and Government, Universidad EAFIT, Medellin 050022, Colombia
| | - Anwar Rodríguez
- Center for Economic Studies, National Association of Financial Institutions (ANIF), Bogota 110231, Colombia
| | - Norberto Rojas
- Center for Economic Studies, National Association of Financial Institutions (ANIF), Bogota 110231, Colombia
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12
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Al Shihabi A, Tebon PJ, Nguyen HTL, Chantharasamee J, Sartini S, Davarifar A, Jensen AY, Diaz-Infante M, Cox H, Gonzalez AE, Swearingen S, Tavanaie N, Dry S, Singh A, Chmielowski B, Crompton JG, Kalbasi A, Eilber FC, Hornicek F, Bernthal N, Nelson SD, Boutros PC, Federman N, Yanagawa J, Soragni A. The landscape of drug sensitivity and resistance in sarcoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.25.542375. [PMID: 37292676 PMCID: PMC10245988 DOI: 10.1101/2023.05.25.542375] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Sarcomas are a family of rare malignancies composed of over 100 distinct histological subtypes. The rarity of sarcoma poses significant challenges in conducting clinical trials to identify effective therapies, to the point that many rarer subtypes of sarcoma do not have standard-of-care treatment. Even for established regimens, there can be substantial heterogeneity in responses. Overall, novel, personalized approaches for identifying effective treatments are needed to improve patient out-comes. Patient-derived tumor organoids (PDTOs) are clinically relevant models representative of the physiological behavior of tumors across an array of malignancies. Here, we use PDTOs as a tool to better understand the biology of individual tumors and characterize the landscape of drug resistance and sensitivity in sarcoma. We collected n=194 specimens from n=126 sarcoma patients, spanning 24 distinct subtypes. We characterized PDTOs established from over 120 biopsy, resection, and metastasectomy samples. We leveraged our organoid high-throughput drug screening pipeline to test the efficacy of chemotherapeutics, targeted agents, and combination therapies, with results available within a week from tissue collection. Sarcoma PDTOs showed patient-specific growth characteristics and subtype-specific histopathology. Organoid sensitivity correlated with diagnostic subtype, patient age at diagnosis, lesion type, prior treatment history, and disease trajectory for a subset of the compounds screened. We found 90 biological pathways that were implicated in response to treatment of bone and soft tissue sarcoma organoids. By comparing functional responses of organoids and genetic features of the tumors, we show how PDTO drug screening can provide an orthogonal set of information to facilitate optimal drug selection, avoid ineffective therapies, and mirror patient outcomes in sarcoma. In aggregate, we were able to identify at least one effective FDA-approved or NCCN-recommended regimen for 59% of the specimens tested, providing an estimate of the proportion of immediately actionable information identified through our pipeline. Highlights Standardized organoid culture preserve unique sarcoma histopathological featuresDrug screening on patient-derived sarcoma organoids provides sensitivity information that correlates with clinical features and yields actionable information for treatment guidanceHigh-throughput screenings provide orthogonal information to genetic sequencingSarcoma organoid response to treatment correlates with patient response to therapyLarge scale, functional precision medicine programs for rare cancers are feasible within a single institution.
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13
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Kumar V, Stewart JH. Immunometabolic reprogramming, another cancer hallmark. Front Immunol 2023; 14:1125874. [PMID: 37275901 PMCID: PMC10235624 DOI: 10.3389/fimmu.2023.1125874] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 05/02/2023] [Indexed: 06/07/2023] Open
Abstract
Molecular carcinogenesis is a multistep process that involves acquired abnormalities in key biological processes. The complexity of cancer pathogenesis is best illustrated in the six hallmarks of the cancer: (1) the development of self-sufficient growth signals, (2) the emergence of clones that are resistant to apoptosis, (3) resistance to the antigrowth signals, (4) neo-angiogenesis, (5) the invasion of normal tissue or spread to the distant organs, and (6) limitless replicative potential. It also appears that non-resolving inflammation leads to the dysregulation of immune cell metabolism and subsequent cancer progression. The present article delineates immunometabolic reprogramming as a critical hallmark of cancer by linking chronic inflammation and immunosuppression to cancer growth and metastasis. We propose that targeting tumor immunometabolic reprogramming will lead to the design of novel immunotherapeutic approaches to cancer.
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Affiliation(s)
- Vijay Kumar
- Department of Interdisciplinary Oncology, Stanley S. Scott Cancer Center, School of Medicine, Louisiana State University Health Science Center (LSUHSC), New Orleans, LA, United States
| | - John H. Stewart
- Department of Interdisciplinary Oncology, Stanley S. Scott Cancer Center, School of Medicine, Louisiana State University Health Science Center (LSUHSC), New Orleans, LA, United States
- Louisiana State University- Louisiana Children’s Medical Center, Stanley S. Scott, School of Medicine, Louisiana State University Health Science Center (LSUHSC), New Orleans, LA, United States
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14
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Koka H, Bodelon C, Horvath S, Lee PMY, Wang D, Song L, Zhang T, Hurson AN, Guida JL, Zhu B, Bailey-Whyte M, Wang F, Wu C, Tsang KH, Tsoi YK, Chan WC, Law SH, Hung RKW, Tse GM, Yuen KKW, Karlins E, Jones K, Vogt A, Zhu B, Hutchinson A, Hicks B, Garcia-Closas M, Chanock S, Barnholtz-Sloan J, Tse LA, Yang XR. DNA methylation age in paired tumor and adjacent normal breast tissue in Chinese women with breast cancer. Clin Epigenetics 2023; 15:55. [PMID: 36991516 PMCID: PMC10062015 DOI: 10.1186/s13148-023-01465-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 03/13/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong. METHODS We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors. RESULTS DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA. CONCLUSIONS Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.
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Affiliation(s)
- Hela Koka
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Clara Bodelon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- San Diego Institute of Science, Alto Labs, San Diego, CA, USA
| | - Priscilla Ming Yi Lee
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong., Prince of Wales Hospital, Sha Tin, N.T., Hong Kong SAR, China
| | - Difei Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Lei Song
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Amber N Hurson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Jennifer Lyn Guida
- Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Bin Zhu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Maeve Bailey-Whyte
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- School of Medicine, University of Limerick, Limerick, Ireland
| | - Feng Wang
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong., Prince of Wales Hospital, Sha Tin, N.T., Hong Kong SAR, China
| | - Cherry Wu
- Department of Pathology, North District Hospital, Hong Kong, China
| | - Koon Ho Tsang
- Department of Pathology, Yan Chai Hospital, Hong Kong, China
| | - Yee-Kei Tsoi
- Department of Surgery, North District Hospital, Hong Kong, China
| | - W C Chan
- Department of Surgery, North District Hospital, Hong Kong, China
| | - Sze Hong Law
- Department of Surgery, North District Hospital, Hong Kong, China
| | - Ray Ka Wai Hung
- Department of Surgery, North District Hospital, Hong Kong, China
| | - Gary M Tse
- Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong, China
| | | | - Eric Karlins
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Kristine Jones
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Aurelie Vogt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Bin Zhu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Amy Hutchinson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Belynda Hicks
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Montserrat Garcia-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Stephen Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Jill Barnholtz-Sloan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA
| | - Lap Ah Tse
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong., Prince of Wales Hospital, Sha Tin, N.T., Hong Kong SAR, China.
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
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Zhu J, Cao K, Zhang P, Ma J. LINC00669 promotes lung adenocarcinoma growth by stimulating the Wnt/β-catenin signaling pathway. Cancer Med 2023; 12:9005-9023. [PMID: 36621836 PMCID: PMC10134358 DOI: 10.1002/cam4.5604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 12/12/2022] [Accepted: 12/21/2022] [Indexed: 01/10/2023] Open
Abstract
Lung cancer poses severe threats to human health. It is indispensable to discover more druggable molecular targets. We identified a novel dysregulated long non-coding RNA (lncRNA), LINC00669, in lung adenocarcinoma (LUAD) by analyzing the TCGA and GEO databases. Pan-cancer analysis indicated significantly upregulated LINC00669 across 33 cancer types. GSEA revealed a tight association of LINC00669 with the cell cycle. We next attempted to improve the prognostic accuracy of this lncRNA by establishing a risk signature in reliance on cell cycle genes associated with LINC00669. The resulting risk score combined with LINC00669 and stage showed an AUC of 0.746. The risk score significantly stratified LUAD patients into low- and high-risk subgroups, independently predicting prognosis. Its performance was verified by nomogram (C-index = 0.736) and decision curve analysis. Gene set variation analysis disclosed the two groups' molecular characteristics. We also evaluated the tumor immune microenvironment by dissecting 28 infiltrated immune cells, 47 immune checkpoint gene expressions, and immunophenoscore within the two subgroups. Furthermore, the risk signature could predict sensitivity to immune checkpoint inhibitors and other anticancer therapies. Eventually, in vitro and in vivo experiments were conducted to validate LINC00669's function using qRT-PCR, CCK8, flow cytometry, western blot, and immunofluorescence staining. The gain- and loss-of-function study substantiated LINC00669's oncogenic effects, which stimulated non-small cell lung cancer cell proliferation but reduced apoptosis via activating the Wnt/β-catenin pathway. Its oncogenic potentials were validated in the xenograft mouse model. Overall, we identified a novel oncogenic large intergenic non-coding RNA (lincRNA), LINC00669. The resulting signature may facilitate predicting prognosis and therapy responses in LUAD.
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Affiliation(s)
- Jinhong Zhu
- Department of Clinical Laboratory, Biobank, Harbin Medical University Cancer Hospital, Harbin, China
| | - Kui Cao
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ping Zhang
- Department of Clinical Laboratory, Biobank, Harbin Medical University Cancer Hospital, Harbin, China
| | - Jianqun Ma
- Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, China
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16
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Zhou CD, Pettersson A, Plym A, Tyekucheva S, Penney KL, Sesso HD, Kantoff PW, Mucci LA, Stopsack KH. Differences in Prostate Cancer Transcriptomes by Age at Diagnosis: Are Primary Tumors from Older Men Inherently Different? Cancer Prev Res (Phila) 2022; 15:815-825. [PMID: 36125434 PMCID: PMC9722523 DOI: 10.1158/1940-6207.capr-22-0212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 08/03/2022] [Accepted: 09/01/2022] [Indexed: 01/31/2023]
Abstract
Older age at diagnosis is consistently associated with worse clinical outcomes in prostate cancer. We sought to characterize gene expression profiles of prostate tumor tissue by age at diagnosis. We conducted a discovery analysis in The Cancer Genome Atlas prostate cancer dataset (n = 320; 29% of men >65 years at diagnosis), using linear regressions of age at diagnosis and mRNA expression and adjusting for TMPRSS2:ERG fusion status and race. This analysis identified 13 age-related candidate genes at FDR < 0.1, six of which were also found in an analysis additionally adjusted for Gleason score. We then validated the 13 age-related genes in a transcriptome study nested in the Health Professionals Follow-up Study and Physicians' Health Study (n = 374; 53% of men >65 years). Gene expression differences by age in the 13 candidate genes were directionally consistent, and age at diagnosis was weakly associated with the 13-gene score. However, the age-related genes were not consistently associated with risk of metastases and prostate cancer-specific death. Collectively, these findings argue against tumor genomic differences as a main explanation for age-related differences in prostate cancer prognosis. PREVENTION RELEVANCE Older age at diagnosis is consistently associated with worse clinical outcomes in prostate cancer. This study with independent discovery and validation sets and long-term follow-up suggests that prevention of lethal prostate cancer should focus on implementing appropriate screening, staging, and treatment among older men without expecting fundamentally different tumor biology.
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Affiliation(s)
- Charlie D. Zhou
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Andreas Pettersson
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Anna Plym
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Department of Urology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Svitlana Tyekucheva
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kathryn L. Penney
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Howard D. Sesso
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Division of Preventative Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Philip W. Kantoff
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA,Convergent Therapeutics Inc., Cambridge, MA, USA
| | - Lorelei A. Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Konrad H. Stopsack
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA,Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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Wang X, Langevin AM, Houghton PJ, Zheng S. Genomic disparities between cancers in adolescent and young adults and in older adults. Nat Commun 2022; 13:7223. [PMID: 36433963 PMCID: PMC9700745 DOI: 10.1038/s41467-022-34959-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 11/11/2022] [Indexed: 11/27/2022] Open
Abstract
Cancers cause significant mortality and morbidity in adolescents and young adults (AYAs), but their biological underpinnings are incompletely understood. Here, we analyze clinical and genomic disparities between AYAs and older adults (OAs) in more than 100,000 cancer patients. We find significant differences in clinical presentation between AYAs and OAs, including sex, metastasis rates, race and ethnicity, and cancer histology. In most cancer types, AYA tumors show lower mutation burden and less genome instability. Accordingly, most cancer genes show less mutations and copy number changes in AYAs, including the noncoding TERT promoter mutations. However, CTNNB1 and BRAF mutations are consistently overrepresented in AYAs across multiple cancer types. AYA tumors also exhibit more driver gene fusions that are frequently observed in pediatric cancers. We find that histology is an important contributor to genetic disparities between AYAs and OAs. Mutational signature analysis of hypermutators shows stronger endogenous mutational processes such as MMR-deficiency but weaker exogenous processes such as tobacco exposure in AYAs. Finally, we demonstrate a panoramic view of clinically actionable genetic events in AYA tumors.
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Affiliation(s)
- Xiaojing Wang
- grid.267309.90000 0001 0629 5880Greehey Children’s Cancer Research Institute, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880MD Anderson Mays Cancer Center, UT Health San Antonio, San Antonio, TX USA
| | - Anne-Marie Langevin
- grid.267309.90000 0001 0629 5880MD Anderson Mays Cancer Center, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880Department of Pediatrics, UT Health San Antonio, San Antonio, TX USA
| | - Peter J. Houghton
- grid.267309.90000 0001 0629 5880Greehey Children’s Cancer Research Institute, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880MD Anderson Mays Cancer Center, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880Department of Molecular Medicine, UT Health San Antonio, San Antonio, TX USA
| | - Siyuan Zheng
- grid.267309.90000 0001 0629 5880Greehey Children’s Cancer Research Institute, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880MD Anderson Mays Cancer Center, UT Health San Antonio, San Antonio, TX USA
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Chatsirisupachai K, Lagger C, de Magalhães JP. Age-associated differences in the cancer molecular landscape. Trends Cancer 2022; 8:962-971. [PMID: 35811230 DOI: 10.1016/j.trecan.2022.06.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/11/2022] [Accepted: 06/13/2022] [Indexed: 12/24/2022]
Abstract
Cancer is an age-related disease, as incidence and mortality for most types of cancer increase with age. However, how molecular alterations in tumors differ among patients of different ages remains poorly understood. Recent studies have shed light on the age-associated molecular landscapes in cancer. Here, we summarize the main findings of these current studies, highlighting major differences in the genomic, transcriptomic, epigenetic, and immunological landscapes between cancer in younger and older patients. Importantly, some cancer driver genes are mutated more frequently in younger or older patients. We discuss the potential roles of aging-related processes in shaping these age-related differences in cancer. We further emphasize the remaining unsolved questions that could provide important insights that will have implications in personalized medicine.
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Affiliation(s)
- Kasit Chatsirisupachai
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK.
| | - Cyril Lagger
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - João Pedro de Magalhães
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK.
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How Genetics and Genomics Advances Are Rewriting Pediatric Cancer Research and Clinical Care. Medicina (B Aires) 2022; 58:medicina58101386. [PMID: 36295546 PMCID: PMC9610804 DOI: 10.3390/medicina58101386] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/28/2022] [Accepted: 09/28/2022] [Indexed: 11/17/2022] Open
Abstract
In the last two decades, thanks to the data that have been obtained from the Human Genome Project and the development of next-generation sequencing (NGS) technologies, research in oncology has produced extremely important results in understanding the genomic landscape of pediatric cancers, which are the main cause of death during childhood. NGS has provided significant advances in medicine by detecting germline and somatic driver variants that determine the development and progression of many types of cancers, allowing a distinction between hereditary and non-hereditary cancers, characterizing resistance mechanisms that are also related to alterations of the epigenetic apparatus, and quantifying the mutational burden of tumor cells. A combined approach of next-generation technologies allows us to investigate the numerous molecular features of the cancer cell and the effects of the environment on it, discovering and following the path of personalized therapy to defeat an "ancient" disease that has had victories and defeats. In this paper, we provide an overview of the results that have been obtained in the last decade from genomic studies that were carried out on pediatric cancer and their contribution to the more accurate and faster diagnosis in the stratification of patients and the development of new precision therapies.
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Wang QQ, Zhou YC, Zhou Ge YJ, Qin G, Yin TF, Zhao DY, Tan C, Yao SK. Comprehensive proteomic signature and identification of CDKN2A as a promising prognostic biomarker and therapeutic target of colorectal cancer. World J Clin Cases 2022; 10:7686-7697. [PMID: 36158487 PMCID: PMC9372836 DOI: 10.12998/wjcc.v10.i22.7686] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/19/2022] [Accepted: 06/26/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The carcinogenesis of colorectal cancer (CRC) involves many different molecules and multiple pathways, and the specific mechanism has not been elucidated until now. Existing studies on the proteomic signature profiles of CRC are relatively limited. Therefore, we herein aimed to provide a more comprehensive proteomic signature profile and discover new prognostic markers and therapeutic targets by performing proteomic analysis of CRC and paired normal tissues.
AIM To investigate the proteomic signature and identify novel protein prognostic biomarkers of CRC.
METHODS Cancer tissues and paired normal tissues were collected from 48 patients who underwent surgical removal at the China-Japan Friendship Hospital from January 2020 to June 2021. Data independent acquisition (DIA) quantitative proteomic analysis was performed using high-performance liquid chromatography–mass spectrometry/mass spectrometry (nano-UHPLC–MS/MS) to identify differentially expressed proteins, among which those with a P adj value (t test, BH correction) < 0.05 and an absolute fold change (|log2FC|) > 2 were identified as potential markers. Differentially expressed proteins were selected by bioinformatics analysis and validated by immunohistochemical tissue microarrays, and their association with prognosis was further analyzed with the Gene Expression Profiling Interactive Analysis database to identify prognostic protein biomarkers of CRC.
RESULTS Significantly differential protein expression was observed between cancer tissues and normal tissues. Compared with normal tissues, 1115 proteins were upregulated and 705 proteins were downregulated in CRC based on P adj < 0.05 and |log2FC| > 2, and bioinformatics analysis revealed that the differentially expressed proteins were involved in multiple biological processes associated with tumorigenesis, including ribosome biogenesis in eukaryotes, focal adhesion, extracellular matrix-receptor interactions and other tumor metabolism processes. Moreover, cyclin-dependent kinase inhibitor 2A (CDKN2A) expression was markedly upregulated in CRC, as validated by immunohistochemistry (0.228 vs 0.364, P = 0.0044), and was significantly enriched in tumor proliferation and signal transduction pathways such as the cell cycle and p53 signaling pathways. High CDKN2A expression was significantly correlated with poor prognosis (P = 0.021). These results demonstrated that CDKN2A functions as a driver of CRC.
CONCLUSION Our study provides a comprehensive proteomic signature of CRC and highlights CDKN2A as a potential powerful prognostic marker and precision therapeutic target.
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Affiliation(s)
- Qian-Qian Wang
- Graduate School, Peking University China-Japan Friendship School of Clinical Medicine, Beijing 10029, China
| | - Yuan-Chen Zhou
- Graduate School, Peking University China-Japan Friendship School of Clinical Medicine, Beijing 10029, China
| | - Yu-Jia Zhou Ge
- Graduate School, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Geng Qin
- Department of Gastroenterology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Teng-Fei Yin
- Graduate School, Peking University China-Japan Friendship School of Clinical Medicine, Beijing 100029, China
| | - Dong-Yan Zhao
- Graduate School, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Chang Tan
- Graduate School, Peking University China-Japan Friendship School of Clinical Medicine, Beijing 100029, China
| | - Shu-Kun Yao
- Department of Gastroenterology, China-Japan Friendship Hospital, Beijing 100029, China
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Abstract
Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages1. The contributing genetic and non-genetic factors, and associated mutational processes, are unknown2,3. Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2, STK19, DDX11L1, PCAT1 and SETBP1. Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African-European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene-environment interaction-defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa-we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.
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Ruiz E, Kandil E, Alhassan S, Toraih E, Errami Y, Elmageed ZYA, Zerfaoui M. An Integrative Multi-Omics Analysis of The Molecular Links between Aging and Aggressiveness in Thyroid Cancers. Aging Dis 2022; 14:992-1012. [PMID: 37191407 DOI: 10.14336/ad.2022.1021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/21/2022] [Indexed: 11/19/2022] Open
Abstract
Aging modifies risk in all cancers, but age is used as a clinical staging criterion uniquely in thyroid cancer (TC). The molecular drivers of age-dependent TC onset and aggressiveness remain poorly understood. We applied an integrative, multi-omics data analysis approach to characterize these signatures. Our analysis reveals that aging, independent of BRAFV600E mutational status, drives a significant accumulation of aggressiveness-related markers and poorer survival outcomes, most noticeably at age 55 and over. We identified that chromosomal alterations in loci 1p/1q as aging-associated drivers of aggressiveness, and that depleted infiltration with tumor surveillant CD8+T and follicular helper T cells, dysregulation of proteostasis- and senescence-related processes, and ERK1/2 signaling cascade are key features of the aging thyroid and TC onset/progression and aggressiveness in aging patients but not in young individuals. A panel of 23 genes, including those related to cell division such as CENPF, ERCC6L, and the kinases MELK and NEK2, were identified and rigorously characterized as aging-dependent and aggressiveness-specific markers. These genes effectively stratified patients into aggressive clusters with distinct phenotypic enrichment and genomic/transcriptomic profiles. This panel also showed excellent performance in predicting metastasis stage, BRAFV600E, TERT promoter mutation, and survival outcomes and was superior to the American Thyroid Association (ATA) methodology in predicting aggressiveness risk. Our analysis established clinically relevant biomarkers for TC aggressiveness factoring in aging as an important component.
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