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Zhang N, Zhang P, Deng X, Zhu M, Hu Y, Ji D, Li L, Liu Y, Zeng W, Ke M. Protective Effect of Nicotinamide Riboside on Glucocorticoid-Induced Glaucoma: Mitigating Mitochondrial Damage and Extracellular Matrix Deposition. Invest Ophthalmol Vis Sci 2024; 65:1. [PMID: 38949632 PMCID: PMC11221610 DOI: 10.1167/iovs.65.8.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 06/12/2024] [Indexed: 07/02/2024] Open
Abstract
Purpose Glucocorticoid-induced glaucoma (GIG) is a prevalent complication associated with glucocorticoids (GCs), resulting in irreversible blindness. GIG is characterized by the abnormal deposition of extracellular matrix (ECM) in the trabecular meshwork (TM), elevation of intraocular pressure (IOP), and loss of retinal ganglion cells (RGCs). The objective of this study is to investigate the effects of nicotinamide riboside (NR) on TM in GIG. Methods Primary human TM cells (pHTMs) and C57BL/6J mice responsive to GCs were utilized to establish in vitro and in vivo GIG models, respectively. The study assessed the expression of ECM-related proteins in TM and the functions of pHTMs to reflect the effects of NR. Mitochondrial morphology and function were also examined in the GIG cell model. GIG progression was monitored through IOP, RGCs, and mitochondrial morphology. Intracellular nicotinamide adenine dinucleotide (NAD+) levels of pHTMs were enzymatically assayed. Results NR significantly prevented the expression of ECM-related proteins and alleviated dysfunction in pHTMs after dexamethasone treatment. Importantly, NR protected damaged ATP synthesis, preventing overexpression of mitochondrial reactive oxygen species (ROS), and also protect against decreased mitochondrial membrane potential induced by GCs in vitro. In the GIG mouse model, NR partially prevented the elevation of IOP and the loss of RGCs. Furthermore, NR effectively suppressed the excessive expression of ECM-associated proteins and mitigated mitochondrial damage in vivo. Conclusions Based on the results, NR effectively enhances intracellular levels of NAD+, thereby mitigating abnormal ECM deposition and TM dysfunction in GIG by attenuating mitochondrial damage induced by GCs. Thus, NR has promising potential as a therapeutic candidate for GIG treatment.
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Affiliation(s)
- Nan Zhang
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Pengyu Zhang
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Xizhi Deng
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Min Zhu
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Yixin Hu
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Dongxiao Ji
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
- Department of Ophthalmology, Huaihai Hospital of Henan University, Kaifeng, Henan, China
| | - Lufan Li
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Yang Liu
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Wen Zeng
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Min Ke
- Department of Ophthalmology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
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Qin Q, Zhou Y, Guo J, Chen Q, Tang W, Li Y, You J, Li Q. Conserved methylation signatures associate with the tumor immune microenvironment and immunotherapy response. Genome Med 2024; 16:47. [PMID: 38566132 PMCID: PMC10985907 DOI: 10.1186/s13073-024-01318-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 03/20/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Aberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes. METHODS We performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts. RESULTS We identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment. CONCLUSIONS Our findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.
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Affiliation(s)
- Qingqing Qin
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Ying Zhou
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Jintao Guo
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Qinwei Chen
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
| | - Weiwei Tang
- Department of Medical Oncology, School of Medicine, The First Affiliated Hospital of Xiamen University and Institute of Hematology, Xiamen University, Xiamen, 361003, China
- Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, The School of Clinical Medicine of Fujian, Medical University, Xiamen, 361003, China
| | - Yuchen Li
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China
| | - Jun You
- Department of Gastrointestinal Oncology Surgery, The First Affiliated Hospital of Xiamen University, Cancer Center, Xiamen, 361003, China
| | - Qiyuan Li
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, China.
- School of Medicine, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, China.
- Department of Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, 361003, China.
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Shi Y, Shen H. DNA cytosine deamination is associated with recurrent Somatic Copy Number Alterations in stomach adenocarcinoma. Front Genet 2023; 14:1231415. [PMID: 37867602 PMCID: PMC10587545 DOI: 10.3389/fgene.2023.1231415] [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: 05/30/2023] [Accepted: 09/05/2023] [Indexed: 10/24/2023] Open
Abstract
Stomach Adenocarcinoma (STAD) is a leading cause of death worldwide. Somatic Copy Number Alterations (SCNAs), which result in Homologous recombination (HR) deficiency in double-strand break repair, are associated with the progression of STAD. However, the landscape of frequent breakpoints of SCNAs (hotspots) and their functional impacts remain poorly understood. In this study, we aimed to explore the frequency and impact of these hotspots in 332 STAD patients and 1,043 cancer cells using data from the Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). We studied the rates of DSB (Double-Strand Breaks) loci in STAD patients by employing the Non-Homogeneous Poisson Distribution (λ), based on which we identified 145 DSB-hotspots with genes affected. We further verified DNA cytosine deamination as a critical process underlying the burden of DSB in STAD. Finally, we illustrated the clinical impact of the significant biological processes. Our findings highlighted the relationship between DNA cytosine deamination and SCNA in cancer was associated with recurrent Somatic Copy Number Alterations in STAD.
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Affiliation(s)
- Yilin Shi
- The College of Letters & Science, University of Wisconsin–Madison, Madison, WI, United States
| | - Huangxuan Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
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Sanjaya P, Maljanen K, Katainen R, Waszak SM, Aaltonen LA, Stegle O, Korbel JO, Pitkänen E. Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping. Genome Med 2023; 15:47. [PMID: 37420249 PMCID: PMC10326961 DOI: 10.1186/s13073-023-01204-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 06/21/2023] [Indexed: 07/09/2023] Open
Abstract
BACKGROUND Cancer genome sequencing enables accurate classification of tumours and tumour subtypes. However, prediction performance is still limited using exome-only sequencing and for tumour types with low somatic mutation burden such as many paediatric tumours. Moreover, the ability to leverage deep representation learning in discovery of tumour entities remains unknown. METHODS We introduce here Mutation-Attention (MuAt), a deep neural network to learn representations of simple and complex somatic alterations for prediction of tumour types and subtypes. In contrast to many previous methods, MuAt utilizes the attention mechanism on individual mutations instead of aggregated mutation counts. RESULTS We trained MuAt models on 2587 whole cancer genomes (24 tumour types) from the Pan-Cancer Analysis of Whole Genomes (PCAWG) and 7352 cancer exomes (20 types) from the Cancer Genome Atlas (TCGA). MuAt achieved prediction accuracy of 89% for whole genomes and 64% for whole exomes, and a top-5 accuracy of 97% and 90%, respectively. MuAt models were found to be well-calibrated and perform well in three independent whole cancer genome cohorts with 10,361 tumours in total. We show MuAt to be able to learn clinically and biologically relevant tumour entities including acral melanoma, SHH-activated medulloblastoma, SPOP-associated prostate cancer, microsatellite instability, POLE proofreading deficiency, and MUTYH-associated pancreatic endocrine tumours without these tumour subtypes and subgroups being provided as training labels. Finally, scrunity of MuAt attention matrices revealed both ubiquitous and tumour-type specific patterns of simple and complex somatic mutations. CONCLUSIONS Integrated representations of somatic alterations learnt by MuAt were able to accurately identify histological tumour types and identify tumour entities, with potential to impact precision cancer medicine.
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Affiliation(s)
- Prima Sanjaya
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Katri Maljanen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Riku Katainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sebastian M Waszak
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, Oslo, Norway
- Swiss Institute for Experimental Cancer Research School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco, CA, USA
| | - Lauri A Aaltonen
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Medical and Clinical Genetics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Oliver Stegle
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jan O Korbel
- Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Esa Pitkänen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
- Applied Tumor Genomics Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland.
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
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Hua T, Zhang XC, Wang W, Tian YJ, Chen SB. Deciphering the expression patterns of homologous recombination-related lncRNAs identifies new molecular subtypes and emerging therapeutic opportunities in epithelial ovarian cancer. Front Genet 2022; 13:901424. [PMID: 36246624 PMCID: PMC9557066 DOI: 10.3389/fgene.2022.901424] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
Epithelial ovarian cancer (EOC) is the leading killer among women with gynecologic malignancies. Homologous recombination deficiency (HRD) has attracted increasing attention due to its significant implication in the prediction of prognosis and response to treatments. In addition to the germline and somatic mutations of homologous recombination (HR) repair genes, to widely and deeply understand the molecular characteristics of HRD, we sought to screen the long non-coding RNAs (lncRNAs) with regard to HR repair genes and to establish a prognostic risk model for EOC. Herein, we retrieved the transcriptome data from the Genotype-Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA) databases. HR-related lncRNAs (HRRlncRNAs) associated with prognosis were identified by co-expression and univariate Cox regression analyses. The least absolute shrinkage and selection operator (LASSO) and multivariate stepwise Cox regression were performed to construct an HRRlncRNA risk model containing AC138904.1, AP001001.1, AL603832.1, AC138932.1, and AC040169.1. Next, Kaplan−Meier analysis, time-dependent receiver operating characteristics (ROC), nomogram, calibration, and DCA curves were made to verify and evaluate the model. Gene set enrichment analysis (GSEA), immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) in the risk groups were also analyzed. The calibration plots showed a good concordance with the prognosis prediction. ROCs of 1-, 3-, and 5-year survival confirmed the well-predictive efficacy of this model in EOC. The risk score was used to divide the patients into high-risk and low-risk subgroups. The low-risk group patients tended to exhibit a lower immune infiltration status and a higher HRD score. Furthermore, consensus clustering analysis was employed to divide patients with EOC into three clusters based on the expression of the five HRRlncRNAs, which exhibited a significant difference in checkpoints’ expression levels and the tumor microenvironment (TME) status. Taken together, the results of this project supported that the five HRRlncRNA models might function as a biomarker and prognostic indicator with respect to predicting the PARP inhibitor and immune treatment in EOC.
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Affiliation(s)
- Tian Hua
- Department of Gynecology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China
| | - Xiao-Chong Zhang
- Department of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China
| | - Wei Wang
- Department of Obstetrics and Gynecology, Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yun-Jie Tian
- Department of Obstetrics and Gynecology, Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Shu-Bo Chen
- Department of Oncology, Affiliated Xingtai People Hospital of Hebei Medical University, Xingtai, China
- *Correspondence: Shu-Bo Chen,
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6
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Li Q, Xu B, Shen Z. Editorial: The Molecular Basis of Somatic Evolution. Front Oncol 2022; 12:906068. [PMID: 35734593 PMCID: PMC9207474 DOI: 10.3389/fonc.2022.906068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 04/26/2022] [Indexed: 11/24/2022] Open
Affiliation(s)
- Qiyuan Li
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, China.,National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China.,School of Medicine, Xiamen University, Xiamen, China
| | - Bing Xu
- Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, China.,Department of Hematology, Key Laboratory of Xiamen for Diagnosis and Treatment of Hematological Malignancy, Xiamen, China
| | - Zhanlong Shen
- Laboratory of Surgical Oncology, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Beijing, China
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Zhong F, Lin Y, Jing X, Ye Y, Wang S, Shen Z. Innate tumor killers in colorectal cancer. Cancer Lett 2021; 527:115-126. [PMID: 34952144 DOI: 10.1016/j.canlet.2021.12.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/11/2021] [Accepted: 12/18/2021] [Indexed: 12/12/2022]
Abstract
Standard treatment of colorectal cancer (CRC) improves the prognosis of CRC patients, but it is still intractable to control the progression of metastatic CRC. Immune microenvironment and immunotherapies of CRC have received extensive attention in recent years, but present immunotherapies of CRC have mainly focused on T cells and therapeutic response is only observed in a small proportion of patients. Innate immune cells are the first-line of defense in the development of malignancies. Natural killer (NK) cells, NKT cells and γδT cells are three types of innate cells of lymphoid origin and show cytotoxicity against various tumor cells including CRC. Besides, in the development of CRC, they can also be inhibited or express regulatory type, promoting tumor progression. Researches about anti-tumorigenic and pro-tumorigenic mechanisms of these cells are ongoing and regulation of these cells is also being unearthed. Meanwhile, immunotherapies using these cells more or less have shown efficacy in animal models and some of them are under exploration in clinical trials. This review provides an overview of intrinsic properties of NK cell, NKT cell and γδT cell, and summarizes current related promising treatment strategies.
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Affiliation(s)
- Fengyun Zhong
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, PR China; Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, 100044, PR China.
| | - Yilin Lin
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, PR China; Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, 100044, PR China.
| | - Xiangxiang Jing
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, PR China; Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, 100044, PR China.
| | - Yingjiang Ye
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, PR China; Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, 100044, PR China.
| | - Shan Wang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, PR China; Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, 100044, PR China.
| | - Zhanlong Shen
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, PR China; Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, 100044, PR China.
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