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Xavier JM, Magno R, Russell R, de Almeida BP, Jacinta-Fernandes A, Besouro-Duarte A, Dunning M, Samarajiwa S, O'Reilly M, Maia AM, Rocha CL, Rosli N, Ponder BAJ, Maia AT. Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis. Sci Rep 2024; 14:22526. [PMID: 39341862 PMCID: PMC11438911 DOI: 10.1038/s41598-024-72163-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 09/04/2024] [Indexed: 10/01/2024] Open
Abstract
Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.
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Affiliation(s)
- Joana M Xavier
- Cintesis@Rise, Universidade do Algarve, Faro, Portugal.
- Centro de Ciências do Mar (CCMAR), Universidade do Algarve, Faro, Portugal.
| | - Ramiro Magno
- Cintesis@Rise, Universidade do Algarve, Faro, Portugal
- Pattern Institute PT, Faro, Portugal
| | - Roslin Russell
- Cambridge Institute - CRUK, University of Cambridge, Cambridge, UK
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Bernardo P de Almeida
- Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve, Faro, Portugal
- Faculdade de Medicina, Instituto de Medicina Molecular, Universidade de Lisboa, Lisbon, Portugal
- InstaDeep, Paris, France
| | - Ana Jacinta-Fernandes
- Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve, Faro, Portugal
| | | | - Mark Dunning
- Cambridge Institute - CRUK, University of Cambridge, Cambridge, UK
- Sheffield Bioinformatics Core, The School of Medicine and Population Health, The University of Sheffield, Sheffield, UK
| | - Shamith Samarajiwa
- Medical Research Council (MRC) Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, UK
- Genetics and Genomics Section, Imperial College London, London, UK
| | - Martin O'Reilly
- Cambridge Institute - CRUK, University of Cambridge, Cambridge, UK
| | | | - Cátia L Rocha
- Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve, Faro, Portugal
- Faculty of Medicine, Instituto de Saúde Ambiental (ISAMB), University of Lisbon, Lisbon, Portugal
| | - Nordiana Rosli
- Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve, Faro, Portugal
- Training Division, Ministry of Health Malaysia, Putrajaya, Malaysia
- Biometrology Group, Division of Chemical and Biological Metrology, Korea Research Institute of Standards and Science, Daejeon, South Korea
| | - Bruce A J Ponder
- Cambridge Institute - CRUK, University of Cambridge, Cambridge, UK
| | - Ana-Teresa Maia
- Cintesis@Rise, Universidade do Algarve, Faro, Portugal.
- Centro de Ciências do Mar (CCMAR), Universidade do Algarve, Faro, Portugal.
- Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve, Faro, Portugal.
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Saeliw T, Kanlayaprasit S, Thongkorn S, Songsritaya K, Sanannam B, Jindatip D, Hu VW, Sarachana T. Investigation of chimeric transcripts derived from LINE-1 and Alu retrotransposons in cerebellar tissues of individuals with autism spectrum disorder (ASD). Sci Rep 2024; 14:21889. [PMID: 39300110 DOI: 10.1038/s41598-024-72334-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Accepted: 09/05/2024] [Indexed: 09/22/2024] Open
Abstract
LINE-1 and Alu retrotransposons are components of the human genome and have been implicated in many human diseases. These elements can influence human transcriptome plasticity in various mechanisms. Chimeric transcripts derived from LINE-1 and Alu can also impact the human transcriptome, such as exonization and post-transcriptional modification. However, its specific role in ASD neuropathology remains unclear, particularly in the cerebellum tissues. We performed RNA-sequencing of post-mortem cerebellum tissues from ASD and unaffected individuals for transposable elements profiling and chimeric transcript identification. The majority of free transcripts of transposable elements were not changed in the cerebellum tissues of ASD compared with unaffected individuals. Nevertheless, we observed that chimeric transcripts derived from LINE-1 and Alu were embedded in the transcripts of differentially expressed genes in the cerebellum of ASD, and these genes were related to developments and abnormalities of the cerebellum. In addition, the expression levels of these genes were correlated with the significantly decreased thickness of the molecular layer in the cerebellum of ASD. We also found that global methylation and expression of LINE-1 and Alu elements were not changed in ASD, but observed in the ASD sub-phenotypes. Our findings showed associations between transposable elements and cerebellar abnormalities in ASD, particularly in distinct phenotypic subgroups. Further investigations using appropriate models are warranted to elucidate the structural and functional implications of LINE-1 and Alu elements in ASD neuropathology.
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Affiliation(s)
- Thanit Saeliw
- Chulalongkorn Autism Research and Innovation Center of Excellence (Chula ACE), Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Songphon Kanlayaprasit
- Chulalongkorn Autism Research and Innovation Center of Excellence (Chula ACE), Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Surangrat Thongkorn
- Department of Biotechnology and Biomedicine (DTU Bioengineering), Technical University of Denmark, 2800, Kongens Lyngby, Denmark
| | - Kwanjira Songsritaya
- The M.Sc. Program in Clinical Biochemistry and Molecular Medicine, Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Bumpenporn Sanannam
- Division of Anatomy, Department of Preclinical Science, Faculty of Medicine, Thammasat University, Pathumthani, 12120, Thailand
| | - Depicha Jindatip
- Chulalongkorn Autism Research and Innovation Center of Excellence (Chula ACE), Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand
- Department of Anatomy, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Valerie W Hu
- Department of Biochemistry and Molecular Medicine, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20052, USA
| | - Tewarit Sarachana
- Chulalongkorn Autism Research and Innovation Center of Excellence (Chula ACE), Department of Clinical Chemistry, Faculty of Allied Health Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.
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3
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Zhang Z, Xiao Y, Zhao S, Liu J, Zeng J, Xiao F, Liao B, Shan X, Zhu H, Guo H. FAM109B plays a tumorigenic role in low-grade gliomas and is associated with tumor-associated macrophages (TAMs). J Transl Med 2024; 22:833. [PMID: 39256832 PMCID: PMC11389277 DOI: 10.1186/s12967-024-05641-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 08/29/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND Family with sequence similarity 109, member B (FAM109B) is involved in endocytic transport and affects genetic variation in brain methylation. It is one of the important genes related to immune cell-associated diseases. In the tumor immune system, methylation can regulate tumor immunity and influence the maturation and functional response of immune cells. Whether FAM109B is involved in tumor progression and its correlation with the tumor immune microenvironment has not yet been disclosed. METHODS A comprehensive pan-cancer analysis of FAM109B expression, prognosis, immunity, and TMB was conducted. The expression, clinical features, and prognostic value of FAM109B in low-grade gliomas (LGG) were evaluated using TCGA, CGGA, and Gravendeel databases. The expression of FAM109B was validated by qRT-PCR, immunohistochemistry (IHC), and Western blotting (WB). The relationship between FAM109B and methylation, Copy Number Variation (CNV), prognosis, immune checkpoints (ICs), and common chemotherapy drug sensitivity in LGG was explored through Cox regression, Kaplan-Meier curves, and Spearman correlation analysis. FAM109B levels and their distribution were studied using the TIMER database and single-cell analysis. The potential role of FAM109B in gliomas was further investigated through in vitro and in vivo experiments. RESULTS FAM109B was significantly elevated in various tumor types and was associated with poor prognosis. Its expression was related to aggressive progression and poor prognosis in low-grade glioma patients, serving as an independent prognostic marker for LGG. Glioma grade was negatively correlated with FAM109B DNA promoter methylation. Immune infiltration and single-cell analysis showed significant expression of FAM109B in tumor-associated macrophages (TAMs). The expression of FAM109B was closely related to gene mutations, immune checkpoints (ICs), and chemotherapy drugs in LGG. In vitro studies showed increased FAM109B expression in LGG, closely related to cell proliferation. In vivo studies showed that mice in the sh-FAM109B group had slower tumor growth, slower weight loss, and longer survival times. CONCLUSIONS FAM109B, as a novel prognostic biomarker for low-grade gliomas, exhibits specific overexpression in TAMs and may be a potential therapeutic target for LGG patients.
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Affiliation(s)
- Zhe Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Yao Xiao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Siyi Zhao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Jun Liu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Jie Zeng
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Feng Xiao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Bin Liao
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Institute of Neuroscience, Nanchang University, Jiangxi, China
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China
| | - Xuesong Shan
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Hong Zhu
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China.
- Institute of Neuroscience, Nanchang University, Jiangxi, China.
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China.
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China.
| | - Hua Guo
- Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China.
- Institute of Neuroscience, Nanchang University, Jiangxi, China.
- Jiangxi Province Key Laboratory of Neurological Diseases, Jiangxi, China.
- JXHC Key Laboratory of Neurological Medicine, Jiangxi, China.
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Niharika, Ureka L, Roy A, Patra SK. Dissecting SOX2 expression and function reveals an association with multiple signaling pathways during embryonic development and in cancer progression. Biochim Biophys Acta Rev Cancer 2024; 1879:189136. [PMID: 38880162 DOI: 10.1016/j.bbcan.2024.189136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/03/2024] [Accepted: 06/10/2024] [Indexed: 06/18/2024]
Abstract
SRY (Sex Determining Region) box 2 (SOX2) is an essential transcription factor that plays crucial roles in activating genes involved in pre- and post-embryonic development, adult tissue homeostasis, and lineage specifications. SOX2 maintains the self-renewal property of stem cells and is involved in the generation of induced pluripotency stem cells. SOX2 protein contains a particular high-mobility group domain that enables SOX2 to achieve the capacity to participate in a broad variety of functions. The information about the involvement of SOX2 with gene regulatory elements, signaling networks, and microRNA is gradually emerging, and the higher expression of SOX2 is functionally relevant to various cancer types. SOX2 facilitates the oncogenic phenotype via cellular proliferation and enhancement of invasive tumor properties. Evidence are accumulating in favor of three dimensional (higher order) folding of chromatin and epigenetic control of the SOX2 gene by chromatin modifications, which implies that the expression level of SOX2 can be modulated by epigenetic regulatory mechanisms, specifically, via DNA methylation and histone H3 modification. In view of this, and to focus further insights into the roles SOX2 plays in physiological functions, involvement of SOX2 during development, precisely, the advances of our knowledge in pre- and post-embryonic development, and interactions of SOX2 in this scenario with various signaling pathways in tumor development and cancer progression, its potential as a therapeutic target against many cancers are summarized and discussed in this article.
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Affiliation(s)
- Niharika
- Epigenetics and Cancer Research Laboratory, Biochemistry and Molecular Biology Group, Department of Life Science, National Institute of Technology, Rourkela 769008, Odisha, India
| | - Lina Ureka
- Epigenetics and Cancer Research Laboratory, Biochemistry and Molecular Biology Group, Department of Life Science, National Institute of Technology, Rourkela 769008, Odisha, India
| | - Ankan Roy
- Epigenetics and Cancer Research Laboratory, Biochemistry and Molecular Biology Group, Department of Life Science, National Institute of Technology, Rourkela 769008, Odisha, India
| | - Samir Kumar Patra
- Epigenetics and Cancer Research Laboratory, Biochemistry and Molecular Biology Group, Department of Life Science, National Institute of Technology, Rourkela 769008, Odisha, India.
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5
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Shin T, Song JHT, Kosicki M, Kenny C, Beck SG, Kelley L, Antony I, Qian X, Bonacina J, Papandile F, Gonzalez D, Scotellaro J, Bushinsky EM, Andersen RE, Maury E, Pennacchio LA, Doan RN, Walsh CA. Rare variation in non-coding regions with evolutionary signatures contributes to autism spectrum disorder risk. CELL GENOMICS 2024; 4:100609. [PMID: 39019033 PMCID: PMC11406188 DOI: 10.1016/j.xgen.2024.100609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 03/11/2024] [Accepted: 06/24/2024] [Indexed: 07/19/2024]
Abstract
Little is known about the role of non-coding regions in the etiology of autism spectrum disorder (ASD). We examined three classes of non-coding regions: human accelerated regions (HARs), which show signatures of positive selection in humans; experimentally validated neural VISTA enhancers (VEs); and conserved regions predicted to act as neural enhancers (CNEs). Targeted and whole-genome analysis of >16,600 samples and >4,900 ASD probands revealed that likely recessive, rare, inherited variants in HARs, VEs, and CNEs substantially contribute to ASD risk in probands whose parents share ancestry, which enriches for recessive contributions, but modestly contribute, if at all, in simplex family structures. We identified multiple patient variants in HARs near IL1RAPL1 and in VEs near OTX1 and SIM1 and showed that they change enhancer activity. Our results implicate both human-evolved and evolutionarily conserved non-coding regions in ASD risk and suggest potential mechanisms of how regulatory changes can modulate social behavior.
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Affiliation(s)
- Taehwan Shin
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Janet H T Song
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Michael Kosicki
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Connor Kenny
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Samantha G Beck
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Lily Kelley
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA
| | - Irene Antony
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Xuyu Qian
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Julieta Bonacina
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA
| | - Frances Papandile
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Dilenny Gonzalez
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Julia Scotellaro
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Evan M Bushinsky
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Rebecca E Andersen
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Eduardo Maury
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA
| | - Len A Pennacchio
- Environmental Genomics & System Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Ryan N Doan
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA.
| | - Christopher A Walsh
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA; Allen Discovery Center for Human Brain Evolution, Boston, MA 02115, USA; Department of Neurology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA.
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Lawson ME, Hoffman A, Wellik IG, Thompson JS, Stamm J, Rele CP. Gene model for the ortholog of Myc in Drosophila eugracilis. MICROPUBLICATION BIOLOGY 2024; 2024:10.17912/micropub.biology.000912. [PMID: 39157808 PMCID: PMC11330573 DOI: 10.17912/micropub.biology.000912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 07/22/2024] [Accepted: 07/29/2024] [Indexed: 08/20/2024]
Abstract
Gene model for the ortholog of Myc ( Myc ) in the D. eugracilis Apr. 2013 (BCM-HGSC/Deug_2.0) (DeugGB2) Genome Assembly (GenBank Accession: GCA_000236325.2) of Drosophila eugracilis . This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.
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Affiliation(s)
| | | | | | | | - Joyce Stamm
- University of Evansville, Evansville, IN USA
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7
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Gao J, Gerstein M. Representing core gene expression activity relationships using the latent structure implicit in Bayesian networks. Bioinformatics 2024; 40:btae463. [PMID: 39051682 PMCID: PMC11316617 DOI: 10.1093/bioinformatics/btae463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 05/31/2024] [Accepted: 07/24/2024] [Indexed: 07/27/2024] Open
Abstract
MOTIVATION Many types of networks, such as co-expression or ChIP-seq-based gene-regulatory networks, provide useful information for biomedical studies. However, they are often too full of connections and difficult to interpret, forming "indecipherable hairballs." RESULTS To address this issue, we propose that a Bayesian network can summarize the core relationships between gene expression activities. This network, which we call the LatentDAG, is substantially simpler than conventional co-expression network and ChIP-seq networks (by two orders of magnitude). It provides clearer clusters, without extraneous cross-cluster connections, and clear separators between modules. Moreover, one can find a number of clear examples showing how it bridges the connection between steps in the transcriptional regulatory network and other networks (e.g. RNA-binding protein). In conjunction with a graph neural network, the LatentDAG works better than other biological networks in a variety of tasks, including prediction of gene conservation and clustering genes. AVAILABILITY AND IMPLEMENTATION Code is available at https://github.com/gersteinlab/LatentDAG.
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Affiliation(s)
- Jiahao Gao
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, United States
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, United States
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, United States
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, United States
- Department of Computer Science, Yale University, New Haven, CT 06520, United States
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8
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Wright MW, Thaxton CL, Nelson T, DiStefano MT, Savatt JM, Brush MH, Cheung G, Mandell ME, Wulf B, Ward TJ, Goehringer S, O'Neill T, Weller P, Preston CG, Keseler IM, Goldstein JL, Strande NT, McGlaughon J, Azzariti DR, Cordova I, Dziadzio H, Babb L, Riehle K, Milosavljevic A, Martin CL, Rehm HL, Plon SE, Berg JS, Riggs ER, Klein TE. Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms. Annu Rev Biomed Data Sci 2024; 7:31-50. [PMID: 38663031 DOI: 10.1146/annurev-biodatasci-102423-112456] [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] [Indexed: 08/25/2024]
Abstract
Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.
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Affiliation(s)
- Matt W Wright
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
| | - Courtney L Thaxton
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA;
| | | | - Marina T DiStefano
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | - Matthew H Brush
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Gloria Cheung
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
| | - Mark E Mandell
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
| | - Bryan Wulf
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
| | - T J Ward
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA;
| | | | - Terry O'Neill
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | - Christine G Preston
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
| | - Ingrid M Keseler
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
| | - Jennifer L Goldstein
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA;
| | | | - Jennifer McGlaughon
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA;
| | - Danielle R Azzariti
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | - Hannah Dziadzio
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Lawrence Babb
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Kevin Riehle
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | | | | | - Heidi L Rehm
- Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Sharon E Plon
- Department of Pediatrics, Division of Hematology-Oncology, Baylor College of Medicine, Houston, Texas, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Jonathan S Berg
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA;
| | | | - Teri E Klein
- Departments of Medicine (Biomedical Informatics Research) and Genetics, Stanford University School of Medicine, Stanford, California, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA; ,
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9
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Yang XJ, Xu YF, Zhu Q. SPOP expression is associated with tumor-infiltrating lymphocytes in pancreatic cancer. PLoS One 2024; 19:e0306994. [PMID: 39074086 DOI: 10.1371/journal.pone.0306994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 06/26/2024] [Indexed: 07/31/2024] Open
Abstract
BACKGROUND Speckle Type POZ Protein (SPOP), despite its tumor type-dependent role in tumorigenesis, primarily as a tumor suppressor gene is associated with a variety of different cancers. However, its function in pancreatic cancer remains uncertain. METHODS SPOP expression and the association between its expression and patient prognosis and immune function were evaluated using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), The Tumor Immune Estimation Resource 2.0 (TIMER2.0) database, cBioportal, and various bioinformatic databases. Enrichment analysis of SPOP and the association between SPOP expression with clinical stage and grade were analyzed using the R software package. Then immunohistochemistry (IHC) was used to estimate the correlation between SPOP and tumor-infiltrating lymphocytes (TILs) in patients with pancreatic cancer. RESULTS As part of our study, we assessed that SPOP was anomalously expressed in kinds of cancers, associated with clinical stage and outcomes. Meanwhile, SPOP also played a crucial role in the tumor microenvironment (TME). The expression level of SPOP was significantly correlated to tumor-infiltrating immune cells (TICs) in pancreatic cancer. CONCLUSIONS Our study uncovered the potential corrections in SPOP with TICs, suggesting that SPOP may act as a biomarker for immunotherapy in pancreatic cancer.
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Affiliation(s)
- Xiao Juan Yang
- Abdominal Oncology Ward, Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Yong Feng Xu
- Abdominal Oncology Ward, Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Qing Zhu
- Abdominal Oncology Ward, Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
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10
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Wang X, Heckel G. Genome-wide relaxation of selection and the evolution of the island syndrome in Orkney voles. Genome Res 2024; 34:851-862. [PMID: 38955466 PMCID: PMC11293545 DOI: 10.1101/gr.278487.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 05/14/2024] [Indexed: 07/04/2024]
Abstract
Island populations often experience different ecological and demographic conditions than their counterparts on the continent, resulting in divergent evolutionary forces affecting their genomes. Random genetic drift and selection both may leave their imprints on island populations, although the relative impact depends strongly on the specific conditions. Here we address their contributions to the island syndrome in a rodent with an unusually clear history of isolation. Common voles (Microtus arvalis) were introduced by humans on the Orkney archipelago north of Scotland >5000 years ago and rapidly evolved to exceptionally large size. Our analyses show that the genomes of Orkney voles were dominated by genetic drift, with extremely low diversity, variable Tajima's D, and very high divergence from continental conspecifics. Increased d N/d S ratios over a wide range of genes in Orkney voles indicated genome-wide relaxation of purifying selection. We found evidence of hard sweeps on key genes of the lipid metabolism pathway only in continental voles. The marked increase of body size in Orkney-a typical phenomenon of the island syndrome-may thus be associated to the relaxation of positive selection on genes related to this pathway. On the other hand, a hard sweep on immune genes of Orkney voles likely reflects the divergent ecological conditions and possibly the history of human introduction. The long-term isolated Orkney voles show that adaptive changes may still impact the evolutionary trajectories of such populations despite the pervasive consequences of genetic drift at the genome level.
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Affiliation(s)
- Xuejing Wang
- Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland
| | - Gerald Heckel
- Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland;
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
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11
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Mo M, LoBello L, Hassan Farah I, Agtang E, Ramos EL, Abdoli R, Santander Diaz L, Helena Schumann Ferreira L, Kokan N, Sadikot T, Sawa A, Arrigo C. Drosophila kikkawai - Sox102F. MICROPUBLICATION BIOLOGY 2024; 2024:10.17912/micropub.biology.001211. [PMID: 39100195 PMCID: PMC11297484 DOI: 10.17912/micropub.biology.001211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 07/18/2024] [Accepted: 07/19/2024] [Indexed: 08/06/2024]
Abstract
The Drosophila kikkawai feature with NCBI Gene ID 108084518 was determined to be an ortholog of Drosophila melanogaster Sox102F , a member of the FlyBase High Mobility Group Box Transcription Factors gene group (FBgg0000748). Five isoforms were constructed using the GEP F element annotation protocol, the longest being novel isoform Sox102F-PNE (identified using the XM_017180752 RefSeq prediction and RNA-seq data). Among the isoforms found in both D. melanogaster and D. kikkawai , Sox102F-PB is the longest and exhibits a 1.18x coding span expansion due to transposable element insertion into an intron. All D. kikkawai protein isoforms contain the conserved domain HMG_box_dom (IPR009071).
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Affiliation(s)
- Mia Mo
- Washington University in St. Louis, St. Louis, Missouri, United States
| | - Larissa LoBello
- Washington University in St. Louis, St. Louis, Missouri, United States
| | | | - Elwin Agtang
- College of the Desert, Palm Desert, California, United States
| | - Edith Luz Ramos
- College of the Desert, Palm Desert, California, United States
| | - Reza Abdoli
- College of the Desert, Palm Desert, California, United States
| | | | | | - Nighat Kokan
- Biology, Lakeland University, Plymouth, Wisconsin, United States
| | | | - Alexa Sawa
- Biology, College of the Desert, Palm Desert, California, United States
| | - Cindy Arrigo
- Biology, New Jersey City University, Jersey City, New Jersey, United States
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12
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Qiao X, Ma D, Zhang X. Identification of hub genes and potential molecular mechanisms in MSS/MSI classifier primary colorectal cancer based on multiple datasets. Discov Oncol 2024; 15:290. [PMID: 39023715 PMCID: PMC11258107 DOI: 10.1007/s12672-024-01148-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Accepted: 07/08/2024] [Indexed: 07/20/2024] Open
Abstract
OBJECTIVE MSI has a better prognosis than MSS in colorectal cancer patients, and the main objective of this study was to screen for differentially expressed molecules between MSI and MSS primary colorectal cancers using bioinformatics. MATERIAL AND METHODS Two gene expression datasets (GSE13294 and GSE13067) were downloaded from GEO, and differential expressed genes (DEGs) were analyzed using GEO2R. Gene Ontology, Kyoto Encyclopedia of Genomes, and Gene Set Enrichment Analysis were conducted using the DEGs. Furthermore, a Protein-Protein Interaction Networks (PPI) was constructed to screen for significant modules and identify hub genes. The hub genes were analyzed in colorectal cancer using GEPIA. The expression of hub genes in clinical samples was visualized using the online Human Protein Atlas (HPA). RESULTS A total of 265 common DEGs were identified in MSS primary colorectal cancer compared to MSI primary colorectal cancer. Among these, 178 DEGs were upregulated, and 87 DEGs were downregulated. Enrichment analysis showed that these DEGs were associated with the response to mechanical stimulus, regulation of cellular response to stress, G protein-coupled receptor binding, and other processes. A total of 5 hub genes was identified by cytoHubba: HNRNPL, RBM39, HNRNPH1, TRA2A, SRSF6. GEPIA software online analysis, 5 hub gene expression in colorectal cancer survival curve did not have significant differences. The expression of RBM39 was significantly different in different stages of colorectal cancer. The HPA online database results showed that the expression of the five hub proteins varied widely in CRC patients. CONCLUSION The hub genes, such as HNRNPH1and RBM39, and the spliceosome resulting from DEGs, which may provide novel insights and evidence for the future diagnosis and targeted therapy of MSS/MSI PCRC.
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Affiliation(s)
- Xia Qiao
- Institute of Medical Science, General Hospital of Ningxia Medical University, Yinchuan, 750004, China
| | - Duan Ma
- Institute of Medical Science, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
| | - Xu Zhang
- Institute of Medical Science, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
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13
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Meena D, Huang J, Dib M, Chirinos J, Jia M, Chauhan G, Gill D, Elliott P, Dehghan A, Tzoulaki I. Body Mass Index and Hypertension as Mediators of the Association Between Age at Menarche and Subclinical Atherosclerosis: A Sex-Specific Mendelian Randomization Analysis. J Am Heart Assoc 2024; 13:e032192. [PMID: 38979809 PMCID: PMC11292777 DOI: 10.1161/jaha.123.032192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 05/22/2024] [Indexed: 07/10/2024]
Abstract
BACKGROUND Early age at menarche (AAM) has been associated with a higher risk of carotid artery intima-media thickness (cIMT), an indicator of subclinical vascular disease, albeit the mechanisms underlying this association remain elusive. A better understanding of the relationship between AAM, modifiable cardiometabolic risk factors, and subclinical atherosclerosis may contribute to improved primary prevention and cardiovascular disease treatment. We aimed to investigate the putative causal role of AAM on cIMT, and to identify and quantify the potentially mediatory effects of cardiometabolic risk factors underlying this relationship. METHODS AND RESULTS We conducted linkage disequilibrium score regression analyses between our exposure of interest, AAM, our outcome of interest, cIMT and potential mediators of the AAM-cIMT association to gauge cross-trait genetic overlap. We considered as mediators the modifiable anthropometric risk factors body mass index (BMI), systolic blood pressure (SBP), lipid traits (total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol), and glycemic traits (fasting glucose). We then leveraged the paradigm of Mendelian randomization to infer causality between AAM and cIMT, and to identify whether cardiometabolic risk factors served as potential mediators of this effect. Our analyses showed that genetically predicted AAM was inversely associated with cIMT, BMI, SBP, and triglycerides, and positively associated with high-density lipoprotein, low-density lipoprotein, and total cholesterol. We showed that the effect of genetically predicted AAM on cIMT may be partially mediated through BMI (20.1% [95% CI, 1.4% to 38.9%]) and SBP (13.5% [95% CI, 0.5%-26.6%]). Our cluster-specific Mendelian randomization revealed heterogeneous causal effect estimates of age at menarche on BMI and SBP. CONCLUSIONS We highlight supporting evidence for a potential causal association between earlier AAM and cIMT, and almost one third of the effect of AAM on cIMT may be mediated by BMI and SBP. Early intervention aimed at lowering BMI and hypertension may be beneficial in reducing the risk of developing subclinical atherosclerosis due to earlier age at menarche.
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Affiliation(s)
- Devendra Meena
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
| | - Jian Huang
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR)Singapore
- Bioinformatics Institute (BII)Agency for Science, Technology and Research (A*STAR)SingaporeSingapore
| | - Marie‐Joe Dib
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
| | - Julio Chirinos
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
| | - Manyi Jia
- Department of Metabolism Digestion and Reproduction, Section of Computational and Systems MedicineImperial College LondonLondonUnited Kingdom
| | - Ganesh Chauhan
- Department of Genetics & GenomicsRajendra Institute of Medical Sciences (RIMS)RanchiIndia
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- British Heart Foundation Centre of Excellence, Imperial College LondonLondonUnited Kingdom
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- British Heart Foundation Centre of Excellence, Imperial College LondonLondonUnited Kingdom
- Dementia Research Institute, Imperial College LondonLondonUnited Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- Dementia Research Institute, Imperial College LondonLondonUnited Kingdom
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- British Heart Foundation Centre of Excellence, Imperial College LondonLondonUnited Kingdom
- Systems Biology, Biomedical Research Foundation Academy of AthensAthensGreece
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14
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Ye C, Jiang S, Zeng T, He S, Cao J, Xiao J. The role of LOXL2 in tumor progression, immune response and cellular senescence: a comprehensive analysis. Discov Oncol 2024; 15:245. [PMID: 38922489 PMCID: PMC11208360 DOI: 10.1007/s12672-024-01107-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 06/15/2024] [Indexed: 06/27/2024] Open
Abstract
LOXL2, an enzyme belonging to the LOX family, facilitates the cross-linking of extracellular matrix (ECM) elements. However, the roles of the LOXL2 gene in mechanisms of oncogenesis and tumor development have not been clearly defined. In this pan-cancer study, we examined the notable disparity in LOXL2 expression at the mRNA and protein levels among various cancer types and elucidated its interconnected roles in tumor progression, mutational profile, immune response, and cellular senescence. Apart from investigating the hyperexpression of LOXL2 being related to poorer prognosis in different types of tumors, this study also unveiled noteworthy connections between LOXL2 and genetic mutations, infiltration of tumor immune cells, and genes in immune checkpoint pathways. Further analysis revealed the participation of LOXL2 in multiple pathways related to cancer extracellular matrix remodeling and cellular senescence. Moreover, our investigation uncovered that the knockdown and inhibition of LOXL2 significantly attenuated the proliferation and migration of PC-9 and HCC-LM3 cells. The knock-down and inhibition of LOXL2 enhanced cellular senescence in lung and liver cancer cells, as confirmed by SA-β-Gal staining and quantitative RT-PCR analyses. This comprehensive analysis offers valuable insights on the functions of LOXL2 in different types of cancer and its role in regulating the senescence of cancer cells.
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Affiliation(s)
- Chen Ye
- School of Health Science and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China
- Spinal Tumor Center, Department of Orthopedic Oncology, Shanghai Changzheng Hospital, Naval Medical University, 415 Fengyang Road, Shanghai, 200003, China
| | - Sihan Jiang
- Graduate School, Naval Medical University, 800 Xiangyin Road, Shanghai, 200433, China
| | - Tanlun Zeng
- Graduate School, Naval Medical University, 800 Xiangyin Road, Shanghai, 200433, China
- Clinical Cancer Institute, Center for Translational Medicine, Naval Medical University, 800 Xiangyin Road, Shanghai, 200433, China
| | - Shaohui He
- Spinal Tumor Center, Department of Orthopedic Oncology, Shanghai Changzheng Hospital, Naval Medical University, 415 Fengyang Road, Shanghai, 200003, China
| | - Jinjin Cao
- School of Health Science and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China.
- Clinical Cancer Institute, Center for Translational Medicine, Naval Medical University, 800 Xiangyin Road, Shanghai, 200433, China.
| | - Jianru Xiao
- School of Health Science and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China.
- Spinal Tumor Center, Department of Orthopedic Oncology, Shanghai Changzheng Hospital, Naval Medical University, 415 Fengyang Road, Shanghai, 200003, China.
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15
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Lu X, Liu J, Feng L, Huang Y, Xu Y, Li C, Wang W, Kan Y, Yang J, Zhang M. BATF promotes tumor progression and association with FDG PET-derived parameters in colorectal cancer. J Transl Med 2024; 22:558. [PMID: 38862971 PMCID: PMC11165778 DOI: 10.1186/s12967-024-05367-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 05/30/2024] [Indexed: 06/13/2024] Open
Abstract
PURPOSE The purpose of the study was to evaluate the expression and function of basic leucine zipper ATF-like transcription factor (BATF) in colorectal cancer (CRC), and its correlation with 2-deoxy-2[18F]fluoro-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) parameters. METHODS The TIMER database, GEPIA database, TCGA, and GEO database were used to analyze the expression profile of BATF in human cancers. The reverse transcription‑quantitative PCR and western blot analyses were used to evaluate the mRNA level and protein expression in different CRC cell lines. The expression of BATF in SW620 and HCT116 cells was silenced and cell counting kit-8 assays and clonogenic assay were utilized to evaluate the role of BATF in CRC proliferation. The expression of tumor BATF and glucose transporter 1 (GLUT-1) were examined using immunohistochemical tools in 37 CRC patients undergoing preoperative 18F-FDG PET/CT imaging. The correlation between the PET/CT parameters and immunohistochemical result was evaluated. RESULTS In database, BATF was highly expressed in pan-cancer analyses, including CRC, and was associated with poor prognosis in CRC. In vitro, the results showed that knocking down of BATF expression could inhibit the proliferation of SW620 and HCT116 cells. In CRC patients, BATF expression was upregulated in tumor tissues compared with matched para-tumoral tissues, and was related with gender and Ki-67 levels. BATF expression was positively related to GLUT-1 expression and PET/CT parameters, including tumor size, maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis. The multiple logistic analyses showed that SUVmax was an independent predictor of BATF expression. With 15.96 g/cm3 as the cutoff, sensitivity was 85.71%, specificity 82.61%, and area-under-the-curve 0.854. CONCLUSION BATF may be an oncogene associated with 18F-FDG PET/CT parameters in CRC. SUVmax may be an independent predictor of BATF expression.
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Affiliation(s)
- Xia Lu
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Jun Liu
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Lijuan Feng
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Yan Huang
- Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, 226001, China
| | - Yanfeng Xu
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Cuicui Li
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Wei Wang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Yin Kan
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
| | - Jigang Yang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China.
| | - Mingyu Zhang
- Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China.
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16
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Singh A, Del-Valle-Anton L, de Juan Romero C, Zhang Z, Ortuño EF, Mahesh A, Espinós A, Soler R, Cárdenas A, Fernández V, Lusby R, Tiwari VK, Borrell V. Gene regulatory landscape of cerebral cortex folding. SCIENCE ADVANCES 2024; 10:eadn1640. [PMID: 38838158 DOI: 10.1126/sciadv.adn1640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 05/02/2024] [Indexed: 06/07/2024]
Abstract
Folding of the cerebral cortex is a key aspect of mammalian brain development and evolution, and defects are linked to severe neurological disorders. Primary folding occurs in highly stereotyped patterns that are predefined in the cortical germinal zones by a transcriptomic protomap. The gene regulatory landscape governing the emergence of this folding protomap remains unknown. We characterized the spatiotemporal dynamics of gene expression and active epigenetic landscape (H3K27ac) across prospective folds and fissures in ferret. Our results show that the transcriptomic protomap begins to emerge at early embryonic stages, and it involves cell-fate signaling pathways. The H3K27ac landscape reveals developmental cell-fate restriction and engages known developmental regulators, including the transcription factor Cux2. Manipulating Cux2 expression in cortical progenitors changed their proliferation and the folding pattern in ferret, caused by selective transcriptional changes as revealed by single-cell RNA sequencing analyses. Our findings highlight the key relevance of epigenetic mechanisms in defining the patterns of cerebral cortex folding.
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Affiliation(s)
- Aditi Singh
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry, and Biomedical Science, Queens University Belfast, Belfast BT9 7BL, UK
| | - Lucia Del-Valle-Anton
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Camino de Juan Romero
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Ziyi Zhang
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry, and Biomedical Science, Queens University Belfast, Belfast BT9 7BL, UK
| | - Eduardo Fernández Ortuño
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Arun Mahesh
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry, and Biomedical Science, Queens University Belfast, Belfast BT9 7BL, UK
- Institute for Molecular Medicine, University of Southern Denmark, Odense M, Denmark
| | - Alexandre Espinós
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Rafael Soler
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Adrián Cárdenas
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Virginia Fernández
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
| | - Ryan Lusby
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry, and Biomedical Science, Queens University Belfast, Belfast BT9 7BL, UK
| | - Vijay K Tiwari
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry, and Biomedical Science, Queens University Belfast, Belfast BT9 7BL, UK
- Institute for Molecular Medicine, University of Southern Denmark, Odense M, Denmark
- Danish Institute for Advanced Study (DIAS), Odense M, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark
| | - Víctor Borrell
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant 03550, Spain
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17
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Li JP, Liu YJ, Li Y, Yin Y, Ye QW, Lu ZH, Dong YW, Zhou JY, Zou X, Chen YG. Spatiotemporal heterogeneity of LMOD1 expression summarizes two modes of cell communication in colorectal cancer. J Transl Med 2024; 22:549. [PMID: 38849852 PMCID: PMC11161970 DOI: 10.1186/s12967-024-05369-3] [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: 02/13/2024] [Accepted: 05/30/2024] [Indexed: 06/09/2024] Open
Abstract
Cellular communication (CC) influences tumor development by mediating intercellular junctions between cells. However, the role and underlying mechanisms of CC in malignant transformation remain unknown. Here, we investigated the spatiotemporal heterogeneity of CC molecular expression during malignant transformation. It was found that although both tight junctions (TJs) and gap junctions (GJs) were involved in maintaining the tumor microenvironment (TME), they exhibited opposite characteristics. Mechanistically, for epithelial cells (parenchymal component), the expression of TJ molecules consistently decreased during normal-cancer transformation and is a potential oncogenic factor. For fibroblasts (mesenchymal component), the expression of GJs consistently increased during normal-cancer transformation and is a potential oncogenic factor. In addition, the molecular profiles of TJs and GJs were used to stratify colorectal cancer (CRC) patients, where subtypes characterized by high GJ levels and low TJ levels exhibited enhanced mesenchymal signals. Importantly, we propose that leiomodin 1 (LMOD1) is biphasic, with features of both TJs and GJs. LMOD1 not only promotes the activation of cancer-associated fibroblasts (CAFs) but also inhibits the Epithelial-mesenchymal transition (EMT) program in cancer cells. In conclusion, these findings demonstrate the molecular heterogeneity of CC and provide new insights into further understanding of TME heterogeneity.
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Affiliation(s)
- Jie-Pin Li
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Jiangsu Province Key Laboratory of Tumor Systems Biology and Chinese Medicine, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Yuan-Jie Liu
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Yang Li
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Yi Yin
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Qian-Wen Ye
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Zhi-Hua Lu
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Yu-Wei Dong
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China
- Nanjing University of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Jin-Yong Zhou
- Central Laboratory, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, Jiangsu, China
| | - Xi Zou
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China.
- Jiangsu Province Key Laboratory of Tumor Systems Biology and Chinese Medicine, Nanjing, 210029, Jiangsu, China.
- Institute of Chinese & Western Medicine and Oncology Clinical Research, Nanjing, 210029, Jiangsu, China.
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210029, Jiangsu, China.
| | - Yu-Gen Chen
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Hanzhong Road No.155, Nanjing, 210029, Jiangsu, China.
- Jiangsu Province Key Laboratory of Tumor Systems Biology and Chinese Medicine, Nanjing, 210029, Jiangsu, China.
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210029, Jiangsu, China.
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18
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Alsegehy S, Southey BR, Hernandez AG, Rund LA, Antonson AM, Nowak RA, Johnson RW, Rodriguez-Zas SL. Epigenetic disruptions in the offspring hypothalamus in response to maternal infection. Gene 2024; 910:148329. [PMID: 38431234 DOI: 10.1016/j.gene.2024.148329] [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: 01/11/2024] [Revised: 02/16/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024]
Abstract
DNA methylation is an epigenetic modification that can alter gene expression, and the incidence can vary across developmental stages, inflammatory conditions, and sexes. The effects of viral maternal viral infection and sex on the DNA methylation patterns were studied in the hypothalamus of a pig model of immune activation during development. DNA methylation at single-base resolution in regions of high CpG density was measured on 24 individual hypothalamus samples using reduced representation bisulfite sequencing. Differential over- and under-methylated sites were identified and annotated to proximal genes and corresponding biological processes. A total of 120 sites were differentially methylated (FDR-adjusted p-value < 0.05) between maternal infection or sex groups. Among the 66 sites differentially methylated between groups exposed to inflammatory signals and control, most sites were over-methylated in the challenged group and included sites in the promoter regions of genes SIRT3 and NRBP1. Among the 54 differentially methylated sites between females and males, most sites were over-methylated in females and included sites in the promoter region of genes TNC and EIF4G1. The analysis of the genes proximal to the differentially methylated sites suggested that biological processes potentially impacted include immune response, neuron migration and ensheathment, peptide signaling, adaptive thermogenesis, and tissue development. These results suggest that translational studies should consider that the prolonged effect of maternal infection during gestation may be enacted through epigenetic regulatory mechanisms that may differ between sexes.
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Affiliation(s)
- Samah Alsegehy
- Informatics Program, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA
| | - Bruce R Southey
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Alvaro G Hernandez
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Lauretta A Rund
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Adrienne M Antonson
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Romana A Nowak
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Rodney W Johnson
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Sandra L Rodriguez-Zas
- Informatics Program, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA; Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL 61820, USA.
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19
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Rots D, Rooney K, Relator R, Kerkhof J, McConkey H, Pfundt R, Marcelis C, Willemsen MH, van Hagen JM, Zwijnenburg P, Alders M, Õunap K, Reimand T, Fjodorova O, Berland S, Liahjell EB, Bojovic O, Kriek M, Ruivenkamp C, Bonati MT, Brunner HG, Vissers LELM, Sadikovic B, Kleefstra T. Refining the 9q34.3 microduplication syndrome reveals mild neurodevelopmental features associated with a distinct global DNA methylation profile. Clin Genet 2024; 105:655-660. [PMID: 38384171 DOI: 10.1111/cge.14498] [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: 08/27/2023] [Revised: 01/19/2024] [Accepted: 01/27/2024] [Indexed: 02/23/2024]
Abstract
Precise regulation of gene expression is important for correct neurodevelopment. 9q34.3 deletions affecting the EHMT1 gene result in a syndromic neurodevelopmental disorder named Kleefstra syndrome. In contrast, duplications of the 9q34.3 locus encompassing EHMT1 have been suggested to cause developmental disorders, but only limited information has been available. We have identified 15 individuals from 10 unrelated families, with 9q34.3 duplications <1.5 Mb in size, encompassing EHMT1 entirely. Clinical features included mild developmental delay, mild intellectual disability or learning problems, autism spectrum disorder, and behavior problems. The individuals did not consistently display dysmorphic features, congenital anomalies, or growth abnormalities. DNA methylation analysis revealed a weak DNAm profile for the cases with 9q34.3 duplication encompassing EHMT1, which could segregate the majority of the affected cases from controls. This study shows that individuals with 9q34.3 duplications including EHMT1 gene present with mild non-syndromic neurodevelopmental disorders and DNA methylation changes different from Kleefstra syndrome.
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Affiliation(s)
- Dmitrijs Rots
- Department of Human Genetics, Radboudumc, Nijmegen, The Netherlands
- Department of Human Genetics Radboudumc, Donders Center for Medical Neuroscience, Nijmegen, The Netherlands
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- Genetics Laboratory, Children's Clinical University Hospital, Riga, Latvia
| | - Kathleen Rooney
- Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, Ontario, Canada
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Raissa Relator
- Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, Ontario, Canada
| | - Jennifer Kerkhof
- Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, Ontario, Canada
| | - Haley McConkey
- Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, Ontario, Canada
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Rolph Pfundt
- Department of Human Genetics, Radboudumc, Nijmegen, The Netherlands
| | - Carlo Marcelis
- Department of Human Genetics, Radboudumc, Nijmegen, The Netherlands
| | | | - Johanna M van Hagen
- Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Petra Zwijnenburg
- Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Marielle Alders
- Department of Human Genetics, Amsterdam Reproduction & development Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Katrin Õunap
- Department of Clinical Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Tiia Reimand
- Department of Clinical Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Olga Fjodorova
- Department of Laboratory Genetics, Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Siren Berland
- Department of Mental Health, Møre og Romsdal Hospital Trust, Ålesund, Norway
| | | | - Ognjen Bojovic
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Marjolein Kriek
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Claudia Ruivenkamp
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Maria Teresa Bonati
- Department of Genetics, Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy
| | - Han G Brunner
- Department of Human Genetics, Radboudumc, Nijmegen, The Netherlands
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Lisenka E L M Vissers
- Department of Human Genetics, Radboudumc, Nijmegen, The Netherlands
- Department of Human Genetics Radboudumc, Donders Center for Medical Neuroscience, Nijmegen, The Netherlands
| | - Bekim Sadikovic
- Verspeeten Clinical Genome Centre, London Health Sciences Centre, London, Ontario, Canada
| | - Tjitske Kleefstra
- Department of Human Genetics, Radboudumc, Nijmegen, The Netherlands
- Department of Human Genetics Radboudumc, Donders Center for Medical Neuroscience, Nijmegen, The Netherlands
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
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20
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Shorey-Kendrick LE, Davis B, Gao L, Park B, Vu A, Morris CD, Breton CV, Fry R, Garcia E, Schmidt RJ, O’Shea TM, Tepper RS, McEvoy CT, Spindel ER. Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:67005. [PMID: 38885141 PMCID: PMC11218700 DOI: 10.1289/ehp13838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/27/2024] [Accepted: 05/22/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established. OBJECTIVE Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost. METHODS We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 . RESULTS Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ). DISCUSSION To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.
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Affiliation(s)
- Lyndsey E. Shorey-Kendrick
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
| | - Brett Davis
- Department of Medicine, Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Lina Gao
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Byung Park
- Biostatistics Shared Resources, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Bioinformatics & Biostatistics Core, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Health & Science University–Portland State University School of Public Health, Portland, Oregon, USA
| | - Annette Vu
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
| | - Cynthia D. Morris
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Carrie V. Breton
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca Fry
- Department of Environmental Sciences and Engineering, UNC Gillings School of Public Health, Chapel Hill, North Carolina, USA
| | - Erika Garcia
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA
| | - Rebecca J. Schmidt
- Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California, USA
- MIND Institute, School of Medicine, University of California Davis, Davis, California, USA
| | - T. Michael O’Shea
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Robert S. Tepper
- Department of Pediatrics, Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Cindy T. McEvoy
- Department of Pediatrics, Oregon Health & Science University, Portland, Oregon, USA
| | - Eliot R. Spindel
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, USA
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21
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Ding Y, Zou M, Guo B. Genomic signatures associated with recurrent scale loss in cyprinid fish. Integr Zool 2024. [PMID: 38816909 DOI: 10.1111/1749-4877.12851] [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] [Indexed: 06/01/2024]
Abstract
Scale morphology represents a fundamental feature of fish and a key evolutionary trait underlying fish diversification. Despite frequent and recurrent scale loss throughout fish diversification, comprehensive genome-wide analyses of the genomic signatures associated with scale loss in divergent fish lineages remain scarce. In the current study, we investigated genome-wide signatures, specifically convergent protein-coding gene loss, amino acid substitutions, and cis-regulatory sequence changes, associated with recurrent scale loss in two divergent Cypriniformes lineages based on large-scale genomic, transcriptomic, and epigenetic data. Results demonstrated convergent changes in many genes related to scale formation in divergent scaleless fish lineages, including loss of P/Q-rich scpp genes (e.g. scpp6 and scpp7), accelerated evolution of non-coding elements adjacent to the fgf and fgfr genes, and convergent amino acid changes in genes (e.g. snap29) under relaxed selection. Collectively, these findings highlight the existence of a shared genetic architecture underlying recurrent scale loss in divergent fish lineages, suggesting that evolutionary outcomes may be genetically repeatable and predictable in the convergence of scale loss in fish.
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Affiliation(s)
- Yongli Ding
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ming Zou
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Baocheng Guo
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining, China
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22
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Li Y, Wang Z, Yang J, Sun Y, He Y, Wang Y, Chen X, Liang Y, Zhang N, Wang X, Zhao W, Hu G, Yang Q. CircTRIM1 encodes TRIM1-269aa to promote chemoresistance and metastasis of TNBC via enhancing CaM-dependent MARCKS translocation and PI3K/AKT/mTOR activation. Mol Cancer 2024; 23:102. [PMID: 38755678 PMCID: PMC11097450 DOI: 10.1186/s12943-024-02019-6] [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: 03/15/2024] [Accepted: 05/08/2024] [Indexed: 05/18/2024] Open
Abstract
Peptides and proteins encoded by noncanonical open reading frames (ORFs) of circRNAs have recently been recognized to play important roles in disease progression, but the biological functions and mechanisms of these peptides and proteins are largely unknown. Here, we identified a potential coding circular RNA, circTRIM1, that was upregulated in doxorubicin-resistant TNBC cells by intersecting transcriptome and translatome RNA-seq data, and its expression was correlated with clinicopathological characteristics and poor prognosis in patients with TNBC. CircTRIM1 possesses a functional IRES element along with an 810 nt ORF that can be translated into a novel endogenously expressed protein termed TRIM1-269aa. Functionally, we demonstrated that TRIM1-269aa, which is involved in the biological functions of circTRIM1, promoted chemoresistance and metastasis in TNBC cells both in vitro and in vivo. In addition, we found that TRIM1-269aa can be packaged into exosomes and transmitted between TNBC cells. Mechanistically, TRIM1-269aa enhanced the interaction between MARCKS and calmodulin, thus promoting the calmodulin-dependent translocation of MARCKS, which further initiated the activation of the PI3K/AKT/mTOR pathway. Overall, circTRIM1, which encodes TRIM1-269aa, promoted TNBC chemoresistance and metastasis by enhancing MARCKS translocation and PI3K/AKT/mTOR activation. Our investigation has yielded novel insights into the roles of protein-coding circRNAs and supported circTRIM1/TRIM1-269aa as a novel promising prognostic and therapeutic target for patients with TNBC.
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Affiliation(s)
- Yaming Li
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Zekun Wang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Jingwen Yang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Yuhan Sun
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Yinqiao He
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Yuping Wang
- School of Basic Medicine, Jining Medical College, Jining, Shandong, 272067, China
| | - Xi Chen
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Yiran Liang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Ning Zhang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Xiaolong Wang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Wenjing Zhao
- Pathology Tissue Bank, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Guohong Hu
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Qifeng Yang
- Department of Breast Surgery, General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China.
- Pathology Tissue Bank, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China.
- Research Institute of Breast Cancer, Shandong University, Jinan, Shandong, 250012, China.
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23
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Sharma V, Singh J, Kumar A, Kansara S, Akhtar MS, Khan MF, Aldosari SA, Mukherjee M, Sharma AK. Integrative experimental validation of concomitant miRNAs and transcription factors with differentially expressed genes in acute myocardial infarction. Eur J Pharmacol 2024; 971:176540. [PMID: 38552938 DOI: 10.1016/j.ejphar.2024.176540] [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: 01/09/2024] [Revised: 03/21/2024] [Accepted: 03/26/2024] [Indexed: 04/20/2024]
Abstract
Identification of concomitant miRNAs and transcription factors (TFs) with differential expression (DEGs) in MI is crucial for understanding holistic gene regulation, identifying key regulators, and precision in biomarker and therapeutic target discovery. We performed a comprehensive analysis using Affymetrix microarray data, advanced bioinformatic tools, and experimental validation to explore potential biomarkers associated with human pathology. The search strategy includes the identification of the GSE83500 dataset, comprising gene expression profiles from aortic wall punch biopsies of MI and non-MI patients, which were used in the present study. The analysis identified nine distinct genes exhibiting DEGs within the realm of MI. miRNA-gene/TF and TF-gene/miRNA regulatory relations were mapped to retrieve interacting hub genes to acquire an MI miRNA-TF co-regulatory network. Furthermore, an animal model of I/R-induced MI confirmed the involved gene based on quantitative RT-PCR and Western blot analysis. The consequences of the bioinformatic tool substantiate the inference regarding the presence of three key hub genes (UBE2N, TMEM106B, and CXADR), a central miRNA (hsa-miR-124-3p), and sixteen TFs. Animal studies support the involvement of predicted genes in the I/R-induced myocardial infarction assessed by RT-PCR and Western blotting. Thus, the final consequences suggest the involvement of promising molecular pathways regulated by TF (p53/NF-κB1), miRNA (hsa-miR-124-3p), and hub gene (UBE2N), which may play a key role in the pathogenesis of MI.
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Affiliation(s)
- Vikash Sharma
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India
| | - Jitender Singh
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India
| | - Ashish Kumar
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India
| | - Samarth Kansara
- Amity Institute of Biotechnology, Amity University Haryana, Panchgaon, Manesar, Haryana, 122413, India
| | - Md Sayeed Akhtar
- Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Alfara, Abha, 62223, Saudi Arabia
| | - Mohd Faiyaz Khan
- Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Saad A Aldosari
- Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Monalisa Mukherjee
- Molecular Sciences and Engineering Laboratory, Amity Institute of Click Chemistry Research and Studies, Amity University, Noida, Uttar Pradesh, 201303, India
| | - Arun K Sharma
- Department of Pharmacology, Amity Institute of Pharmacy, Amity University Haryana, Gurugram, India.
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24
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Ohanele C, Peoples JN, Karlstaedt A, Geiger JT, Gayle AD, Ghazal N, Sohani F, Brown ME, Davis ME, Porter GA, Faundez V, Kwong JQ. Mitochondrial citrate carrier SLC25A1 is a dosage-dependent regulator of metabolic reprogramming and morphogenesis in the developing heart. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.22.541833. [PMID: 37292906 PMCID: PMC10245819 DOI: 10.1101/2023.05.22.541833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The developing mammalian heart undergoes an important metabolic shift from glycolysis toward mitochondrial oxidation, such that oxidative phosphorylation defects may present with cardiac abnormalities. Here, we describe a new mechanistic link between mitochondria and cardiac morphogenesis, uncovered by studying mice with systemic loss of the mitochondrial citrate carrier SLC25A1. Slc25a1 null embryos displayed impaired growth, cardiac malformations, and aberrant mitochondrial function. Importantly, Slc25a1 heterozygous embryos, which are overtly indistinguishable from wild type, exhibited an increased frequency of these defects, suggesting Slc25a1 haploinsuffiency and dose-dependent effects. Supporting clinical relevance, we found a near-significant association between ultrarare human pathogenic SLC25A1 variants and pediatric congenital heart disease. Mechanistically, SLC25A1 may link mitochondria to transcriptional regulation of metabolism through epigenetic control of gene expression to promote metabolic remodeling in the developing heart. Collectively, this work positions SLC25A1 as a novel mitochondrial regulator of ventricular morphogenesis and cardiac metabolic maturation and suggests a role in congenital heart disease.
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25
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Wilson CA, Postlethwait JH. A maternal-to-zygotic-transition gene block on the zebrafish sex chromosome. G3 (BETHESDA, MD.) 2024; 14:jkae050. [PMID: 38466753 PMCID: PMC11075544 DOI: 10.1093/g3journal/jkae050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 02/22/2024] [Accepted: 03/01/2024] [Indexed: 03/13/2024]
Abstract
Wild zebrafish (Danio rerio) have a ZZ/ZW chromosomal sex-determination system with the major sex locus on the right arm of chromosome-4 (Chr4R) near the largest heterochromatic block in the genome, suggesting that Chr4R transcriptomics might differ from the rest of the genome. To test this hypothesis, we conducted an RNA-seq analysis of adult ZW ovaries and ZZ testes in the Nadia strain and identified 4 regions of Chr4 with different gene expression profiles. Unique in the genome, protein-coding genes in a 41.7 Mb section (Region-2) were expressed in testis but silent in ovary. The AB lab strain, which lacks sex chromosomes, verified this result, showing that testis-biased gene expression in Region-2 depends on gonad biology, not on sex-determining mechanism. RNA-seq analyses in female and male brains and livers validated reduced transcripts from Region-2 in somatic cells, but without sex specificity. Region-2 corresponds to the heterochromatic portion of Chr4R and its content of genes and repetitive elements distinguishes it from the rest of the genome. Region-2 lacks protein-coding genes with human orthologs; has zinc finger genes expressed early in zygotic genome activation; has maternal 5S rRNA genes, maternal spliceosome genes, a concentration of tRNA genes, and a distinct set of repetitive elements. The colocalization of (1) genes silenced in ovaries but not in testes that are (2) expressed in embryos briefly at the onset of zygotic genome activation; (3) maternal-specific genes for translation machinery; (4) maternal-specific spliceosome components; and (5) adjacent genes encoding miR-430, which mediates maternal transcript degradation, suggest that this is a maternal-to-zygotic-transition gene regulatory block.
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Kovlyagina I, Wierczeiko A, Todorov H, Jacobi E, Tevosian M, von Engelhardt J, Gerber S, Lutz B. Leveraging interindividual variability in threat conditioning of inbred mice to model trait anxiety. PLoS Biol 2024; 22:e3002642. [PMID: 38805548 PMCID: PMC11161093 DOI: 10.1371/journal.pbio.3002642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 06/07/2024] [Accepted: 04/25/2024] [Indexed: 05/30/2024] Open
Abstract
Trait anxiety is a major risk factor for stress-induced and anxiety disorders in humans. However, animal models accounting for the interindividual variability in stress vulnerability are largely lacking. Moreover, the pervasive bias of using mostly male animals in preclinical studies poorly reflects the increased prevalence of psychiatric disorders in women. Using the threat imminence continuum theory, we designed and validated an auditory aversive conditioning-based pipeline in both female and male mice. We operationalised trait anxiety by harnessing the naturally occurring variability of defensive freezing responses combined with a model-based clustering strategy. While sustained freezing during prolonged retrieval sessions was identified as an anxiety-endophenotype behavioral marker in both sexes, females were consistently associated with an increased freezing response. RNA-sequencing of CeA, BLA, ACC, and BNST revealed massive differences in phasic and sustained responders' transcriptomes, correlating with transcriptomic signatures of psychiatric disorders, particularly post-traumatic stress disorder (PTSD). Moreover, we detected significant alterations in the excitation/inhibition balance of principal neurons in the lateral amygdala. These findings provide compelling evidence that trait anxiety in inbred mice can be leveraged to develop translationally relevant preclinical models to investigate mechanisms of stress susceptibility in a sex-specific manner.
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Affiliation(s)
- Irina Kovlyagina
- Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Anna Wierczeiko
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Hristo Todorov
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Eric Jacobi
- Institute of Pathophysiology, and Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Margarita Tevosian
- Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
- Leibniz Institute for Resilience Research (LIR), Mainz, Germany
| | - Jakob von Engelhardt
- Institute of Pathophysiology, and Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Susanne Gerber
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Beat Lutz
- Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
- Leibniz Institute for Resilience Research (LIR), Mainz, Germany
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Cui Y, Ye W, Li JS, Li JJ, Vilain E, Sallam T, Li W. A genome-wide spectrum of tandem repeat expansions in 338,963 humans. Cell 2024; 187:2336-2341.e5. [PMID: 38582080 PMCID: PMC11065452 DOI: 10.1016/j.cell.2024.03.004] [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: 09/08/2023] [Revised: 01/23/2024] [Accepted: 03/05/2024] [Indexed: 04/08/2024]
Abstract
The Genome Aggregation Database (gnomAD), widely recognized as the gold-standard reference map of human genetic variation, has largely overlooked tandem repeat (TR) expansions, despite the fact that TRs constitute ∼6% of our genome and are linked to over 50 human diseases. Here, we introduce the TR-gnomAD (https://wlcb.oit.uci.edu/TRgnomAD), a biobank-scale reference of 0.86 million TRs derived from 338,963 whole-genome sequencing (WGS) samples of diverse ancestries (39.5% non-European samples). TR-gnomAD offers critical insights into ancestry-specific disease prevalence using disparities in TR unit number frequencies among ancestries. Moreover, TR-gnomAD is able to differentiate between common, presumably benign TR expansions, which are prevalent in TR-gnomAD, from those potentially pathogenic TR expansions, which are found more frequently in disease groups than within TR-gnomAD. Together, TR-gnomAD is an invaluable resource for researchers and physicians to interpret TR expansions in individuals with genetic diseases.
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Affiliation(s)
- Ya Cui
- Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA 92697, USA.
| | - Wenbin Ye
- Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA 92697, USA
| | - Jason Sheng Li
- Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA 92697, USA
| | - Jingyi Jessica Li
- Department of Statistics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Eric Vilain
- Institute for Clinical and Translational Science, University of California, Irvine, Irvine, CA 92697, USA; Department of Pediatrics, University of California, Irvine, Irvine, CA 92697, USA
| | - Tamer Sallam
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Wei Li
- Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, University of California, Irvine, Irvine, CA 92697, USA.
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Liu W, Chen W, Xia J, Lu Z, Fu Y, Li Y, Tan Z. Lymph node metastasis prediction and biological pathway associations underlying DCE-MRI deep learning radiomics in invasive breast cancer. BMC Med Imaging 2024; 24:91. [PMID: 38627678 PMCID: PMC11020672 DOI: 10.1186/s12880-024-01255-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 03/21/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND The relationship between the biological pathways related to deep learning radiomics (DLR) and lymph node metastasis (LNM) of breast cancer is still poorly understood. This study explored the value of DLR based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in LNM of invasive breast cancer. It also analyzed the biological significance of DLR phenotype based on genomics. METHODS Two cohorts from the Cancer Imaging Archive project were used, one as the training cohort (TCGA-Breast, n = 88) and one as the validation cohort (Breast-MRI-NACT Pilot, n = 57). Radiomics and deep learning features were extracted from preoperative DCE-MRI. After dual selection by principal components analysis (PCA) and relief methods, radiomics and deep learning models for predicting LNM were constructed by the random forest (RF) method. A post-fusion strategy was used to construct the DLR nomograms (DLRNs) for predicting LNM. The performance of the models was evaluated using the receiver operating characteristic (ROC) curve and Delong test. In the training cohort, transcriptome data were downloaded from the UCSC Xena online database, and biological pathways related to the DLR phenotypes were identified. Finally, hub genes were identified to obtain DLR gene expression (RadDeepGene) scores. RESULTS DLRNs were based on area under curve (AUC) evaluation (training cohort, AUC = 0.98; validation cohort, AUC = 0.87), which were higher than single radiomics models or GoogLeNet models. The Delong test (radiomics model, P = 0.04; GoogLeNet model, P = 0.01) also validated the above results in the training cohorts, but they were not statistically significant in the validation cohort. The GoogLeNet phenotypes were related to multiple classical tumor signaling pathways, characterizing the biological significance of immune response, signal transduction, and cell death. In all, 20 genes related to GoogLeNet phenotypes were identified, and the RadDeepGene score represented a high risk of LNM (odd ratio = 164.00, P < 0.001). CONCLUSIONS DLRNs combining radiomics and deep learning features of DCE-MRI images improved the preoperative prediction of LNM in breast cancer, and the potential biological characteristics of DLRN were identified through genomics.
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Affiliation(s)
- Wenci Liu
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China
| | - Wubiao Chen
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China
| | - Jun Xia
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China
| | - Zhendong Lu
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China
| | - Youwen Fu
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China
| | - Yuange Li
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China
| | - Zhi Tan
- Radiology Imaging Center, The Affiliated Hospital of Guangdong Medical University, 524001, Zhanjiang, Guangdong Province, P. R. China.
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Singh S, Shyamal S, Das A, Panda AC. Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq. Nucleic Acids Res 2024; 52:e29. [PMID: 38324478 PMCID: PMC11014417 DOI: 10.1093/nar/gkae058] [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: 02/01/2023] [Revised: 01/04/2024] [Accepted: 01/18/2024] [Indexed: 02/09/2024] Open
Abstract
Although the functional role of circular RNA (circRNA) interaction with microRNAs and proteins has been studied extensively, circRNA interactions with the protein-coding mRNAs in intact cells remain largely unknown. Here, by employing AMT-mediated proximity ligation of RNA-RNA duplexes followed by circRNA enrichment and deep sequencing, we report a novel Cross-Linking Poly(A) Pulldown RNase R Sequencing (CLiPPR-seq) technology which identified hundreds of mRNA-interacting circRNAs in three different cell types, including βTC6, C2C12 and HeLa cells. Furthermore, CLiPP-seq without RNase R treatment was also performed to identify the mRNA expression in these cells. BLAST analysis of circRNAs in CLiPPR-seq sample with the mRNAs in CLiPP-seq samples determined their potential complementary sequences for circRNA-mRNA interaction. Pulldown of circRNAs and poly(A) RNAs confirmed the direct interaction of circRNAs with target mRNAs. Silencing of mRNA-interacting circRNAs led to the altered expression of target mRNAs in βTC6 cells, suggesting the role of direct interaction of circRNAs with mRNAs in gene expression regulation. CLiPPR-seq thus represents a novel method for illuminating the myriad of uncharacterized circRNA-mRNA hybrids that may regulate gene expression.
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Affiliation(s)
- Suman Singh
- Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India
- Regional Center for Biotechnology, Faridabad, Haryana 121001, India
| | | | - Arundhati Das
- Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India
| | - Amaresh C Panda
- Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India
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30
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Tian M, Wang Z, Su Z, Shibata E, Shibata Y, Dutta A, Zang C. Integrative analysis of DNA replication origins and ORC-/MCM-binding sites in human cells reveals a lack of overlap. eLife 2024; 12:RP89548. [PMID: 38567819 PMCID: PMC10990492 DOI: 10.7554/elife.89548] [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] [Indexed: 04/05/2024] Open
Abstract
Based on experimentally determined average inter-origin distances of ~100 kb, DNA replication initiates from ~50,000 origins on human chromosomes in each cell cycle. The origins are believed to be specified by binding of factors like the origin recognition complex (ORC) or CTCF or other features like G-quadruplexes. We have performed an integrative analysis of 113 genome-wide human origin profiles (from five different techniques) and five ORC-binding profiles to critically evaluate whether the most reproducible origins are specified by these features. Out of ~7.5 million union origins identified by all datasets, only 0.27% (20,250 shared origins) were reproducibly obtained in at least 20 independent SNS-seq datasets and contained in initiation zones identified by each of three other techniques, suggesting extensive variability in origin usage and identification. Also, 21% of the shared origins overlap with transcriptional promoters, posing a conundrum. Although the shared origins overlap more than union origins with constitutive CTCF-binding sites, G-quadruplex sites, and activating histone marks, these overlaps are comparable or less than that of known transcription start sites, so that these features could be enriched in origins because of the overlap of origins with epigenetically open, promoter-like sequences. Only 6.4% of the 20,250 shared origins were within 1 kb from any of the ~13,000 reproducible ORC-binding sites in human cancer cells, and only 4.5% were within 1 kb of the ~11,000 union MCM2-7-binding sites in contrast to the nearly 100% overlap in the two comparisons in the yeast, Saccharomyces cerevisiae. Thus, in human cancer cell lines, replication origins appear to be specified by highly variable stochastic events dependent on the high epigenetic accessibility around promoters, without extensive overlap between the most reproducible origins and currently known ORC- or MCM-binding sites.
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Affiliation(s)
- Mengxue Tian
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Biochemistry and Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Zhenjia Wang
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
| | - Zhangli Su
- Department of Biochemistry and Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Genetics, University of Alabama at BirminghamBirminghamUnited States
| | - Etsuko Shibata
- Department of Biochemistry and Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Genetics, University of Alabama at BirminghamBirminghamUnited States
| | - Yoshiyuki Shibata
- Department of Biochemistry and Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Genetics, University of Alabama at BirminghamBirminghamUnited States
| | - Anindya Dutta
- Department of Biochemistry and Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Genetics, University of Alabama at BirminghamBirminghamUnited States
| | - Chongzhi Zang
- Center for Public Health Genomics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Biochemistry and Molecular Genetics, University of Virginia School of MedicineCharlottesvilleUnited States
- Department of Public Health Sciences, University of VirginiaCharlottesvilleUnited States
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31
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Mitra S, Malik R, Wong W, Rahman A, Hartemink AJ, Pritykin Y, Dey KK, Leslie CS. Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis. Nat Genet 2024; 56:627-636. [PMID: 38514783 PMCID: PMC11018525 DOI: 10.1038/s41588-024-01689-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 02/14/2024] [Indexed: 03/23/2024]
Abstract
We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.
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Affiliation(s)
- Sneha Mitra
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | | | - Wilfred Wong
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Tri-Institutional Training Program in Computational Biology and Medicine, New York City, NY, USA
| | - Afsana Rahman
- Hunter College, City University of New York, New York City, NY, USA
| | - Alexander J Hartemink
- Department of Computer Science, Duke University, Durham, NC, USA
- Program in Computational Biology and Bioinformatics, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Yuri Pritykin
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Kushal K Dey
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
| | - Christina S Leslie
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
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32
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Zhang E, Sun Q, Zhang C, Ma H, Zhang J, Ding Y, Wang G, Jin C, Jin C, Fu Y, Yan C, Zhu M, Wang C, Dai J, Jin G, Hu Z, Shen H, Ma H. Comprehensive functional interrogation of susceptibility loci in GWASs identified KIAA0391 as a novel oncogenic driver via regulating pyroptosis in NSCLC. Cancer Lett 2024; 585:216646. [PMID: 38262497 DOI: 10.1016/j.canlet.2024.216646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/23/2023] [Accepted: 01/05/2024] [Indexed: 01/25/2024]
Abstract
Approximately 51 non-small-cell lung cancer (NSCLC) risk loci have been identified by genome-wide association studies (GWASs). We conducted a high throughput RNA-interference (RNAi) screening to identify the candidate causal genes in NSCLC risk loci. KIAA0391 at 14q13.1 had the highest score and could promote proliferation and metastasis of NSCLC in vitro and in vivo. We next prioritized rs3783313 as a causal variant at 14q13.1, by integrating a large-scale population study consisting of 27,120 lung cancer cases and 27,355 controls, functional annotation, and expression quantitative trait locus (eQTL) analysis. Then we found that rs3783313 could facilitate a promoter-enhancer interaction to upregulate KIAA0391 expression by affecting the affinity of transcription factor NFYA. Mechanistically, KIAA0391 knockdown dramatically influenced pyroptosis-related pathways and increased the expression of CASP1. And KIAA0391 transcriptionally repressed CASP1 by binding to SMAD2 and induced an anti-pyroptosis phenotype, promoting tumorigenesis of NSCLC, which provides new insights and potential target for NSCLC.
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Affiliation(s)
- Erbao Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Qi Sun
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Chang Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical University, Nanjing 211166, China
| | - Huimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Jing Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Yue Ding
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Guoqing Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Chen Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Chenying Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Yating Fu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100142, China.
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100142, China.
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Salinas-Pena M, Rebollo E, Jordan A. Imaging analysis of six human histone H1 variants reveals universal enrichment of H1.2, H1.3, and H1.5 at the nuclear periphery and nucleolar H1X presence. eLife 2024; 12:RP91306. [PMID: 38530350 DOI: 10.7554/elife.91306] [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] [Indexed: 03/27/2024] Open
Abstract
Histone H1 participates in chromatin condensation and regulates nuclear processes. Human somatic cells may contain up to seven histone H1 variants, although their functional heterogeneity is not fully understood. Here, we have profiled the differential nuclear distribution of the somatic H1 repertoire in human cells through imaging techniques including super-resolution microscopy. H1 variants exhibit characteristic distribution patterns in both interphase and mitosis. H1.2, H1.3, and H1.5 are universally enriched at the nuclear periphery in all cell lines analyzed and co-localize with compacted DNA. H1.0 shows a less pronounced peripheral localization, with apparent variability among different cell lines. On the other hand, H1.4 and H1X are distributed throughout the nucleus, being H1X universally enriched in high-GC regions and abundant in the nucleoli. Interestingly, H1.4 and H1.0 show a more peripheral distribution in cell lines lacking H1.3 and H1.5. The differential distribution patterns of H1 suggest specific functionalities in organizing lamina-associated domains or nucleolar activity, which is further supported by a distinct response of H1X or phosphorylated H1.4 to the inhibition of ribosomal DNA transcription. Moreover, H1 variants depletion affects chromatin structure in a variant-specific manner. Concretely, H1.2 knock-down, either alone or combined, triggers a global chromatin decompaction. Overall, imaging has allowed us to distinguish H1 variants distribution beyond the segregation in two groups denoted by previous ChIP-Seq determinations. Our results support H1 variants heterogeneity and suggest that variant-specific functionality can be shared between different cell types.
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Affiliation(s)
| | - Elena Rebollo
- Molecular Biology Institute of Barcelona (IBMB-CSIC), Barcelona, Spain
| | - Albert Jordan
- Molecular Biology Institute of Barcelona (IBMB-CSIC), Barcelona, Spain
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34
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Wang F, Li Z, Xu T, Zhang Q, Ma T, Li S, Wang X. A comprehensive multi-omics analysis identifies a robust scoring system for cancer-associated fibroblasts and intervention targets in colorectal cancer. J Cancer Res Clin Oncol 2024; 150:124. [PMID: 38478111 PMCID: PMC10937804 DOI: 10.1007/s00432-023-05548-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 11/15/2023] [Indexed: 03/17/2024]
Abstract
BACKGROUND Cancer-associated fibroblasts (CAF) play a critical role in promoting tumor growth, metastasis, and immune evasion. While numerous studies have investigated CAF, there remains a paucity of research on their clinical application in colorectal cancer (CRC). METHODS In this study, we collected differentially expressed genes between CAF and normal fibroblasts (NF) from previous CRC studies, and utilized machine learning analysis to differentiate two distinct subtypes of CAF in CRC. To enable practical application, a CAF-related genes (CAFGs) scoring system was developed based on multivariate Cox regression. We then conducted functional enrichment analysis, Kaplan-Meier plot, consensus molecular subtypes (CMS) classification, and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to investigate the relationship between the CAFGs scoring system and various biological mechanisms, prognostic value, tumor microenvironment, and response to immune checkpoint blockade (ICB) therapy. Moreover, single-cell transcriptomics and proteomics analyses have been employed to validate the significance of scoring system-related molecules in the identity and function of CAF. RESULTS We unveiled significant distinctions in tumor immune status and prognosis not only between the CAF clusters, but also across high and low CAFGs groups. Specifically, patients in CAF cluster 2 or with high CAFGs scores exhibited higher CAF markers and were enriched for CAF-related biological pathways such as epithelial-mesenchymal transition (EMT) and angiogenesis. In addition, CAFGs score was identified as a risk index and correlated with poor overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and recurrence-free survival (RFS). High CAFGs scores were observed in patients with advanced stages, CMS4, as well as lymphatic invasion. Furthermore, elevated CAFG scores in patients signified a suppressive tumor microenvironment characterized by the upregulation of programmed death-ligand 1 (PD-L1), T-cell dysfunction, exclusion, and TIDE score. And high CAFGs scores can differentiate patients with lower response rates and poor prognosis under ICB therapy. Notably, single-cell transcriptomics and proteomics analyses identified several molecules related to CAF identity and function, such as FSTL1, IGFBP7, and FBN1. CONCLUSION We constructed a robust CAFGs score system with clinical significance using multiple CRC cohorts. In addition, we identified several molecules related to CAF identity and function that could be potential intervention targets for CRC patients.
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Affiliation(s)
- Feng Wang
- Department of Gastrointestinal Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
| | - Zhenlin Li
- Department of Surgical Clinical, School of Heze Medical College, Heze, China
| | - Tianlei Xu
- Department of Gastrointestinal Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Qian Zhang
- Department of Gastrointestinal Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Tianyi Ma
- Department of Gastrointestinal Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Sijia Li
- Department of Gastrointestinal Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Xiaohui Wang
- Department of General Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
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Juan CX, Mao Y, Han X, Qian HY, Chu KK. EGR1 Regulates SHANK3 Transcription at Different Stages of Brain Development. Neuroscience 2024; 540:27-37. [PMID: 38218401 DOI: 10.1016/j.neuroscience.2024.01.006] [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: 06/11/2023] [Revised: 01/04/2024] [Accepted: 01/09/2024] [Indexed: 01/15/2024]
Abstract
The expression levels of SHANK3 are associated with autism spectrum disorder (ASD). The dynamic changes in SHANK3 expression during different stages of brain development may impact the progression of ASD. However, no studies or detailed analyses exploring the upstream mechanisms that regulate SHANK3 expression have been reported. In this study, we employed immunofluorescence to examine the expression of SHANK3 in brain organoids at various stages. Our results revealed elevated levels of SHANK3 expression in brain-like organoids at Day 60. Additionally, we utilized bioinformatics software to predict and analyze the SHANK3 gene's transcription start site. Through the dual luciferase reporter gene technique, we identified core transcription elements within the SHANK3 promoter. Site-directed mutations were used to identify specific transcription sites of SHANK3. To determine the physical binding of potential transcription factors to the SHANK3 promoter, we employed electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP). Our findings demonstrated that the transcription factor EGR1 regulates SHANK3 expression by binding to the transcription site of the SHANK3 promoter. Although this study did not investigate the pathological phenotypes of human brain organoids or animal model brains with EGR1 deficiency, which could potentially substantiate the findings observed for SHANK3 mutants, our findings provide valuable insights into the relationship between the transcription factor, EGR1, and SHANK3. This study contributes to the molecular understanding of ASD and offers potential foundations for precise targeted therapy.
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Affiliation(s)
- Chen-Xia Juan
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210004, China; Child Mental Health Research Center, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Yan Mao
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210004, China
| | - Xiao Han
- Institute for Stem Cell and Neural Regeneration, School of Pharmacy, State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Hua-Ying Qian
- Child Mental Health Research Center, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Kang-Kang Chu
- Child Mental Health Research Center, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China.
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Malta TM, Sabedot TS, Morosini NS, Datta I, Garofano L, Vallentgoed W, Varn FS, Aldape K, D'Angelo F, Bakas S, Barnholtz-Sloan JS, Gan HK, Hasanain M, Hau AC, Johnson KC, Cazacu S, deCarvalho AC, Khasraw M, Kocakavuk E, Kouwenhoven MC, Migliozzi S, Niclou SP, Niers JM, Ormond DR, Paek SH, Reifenberger G, Sillevis Smitt PA, Smits M, Stead LF, van den Bent MJ, Van Meir EG, Walenkamp A, Weiss T, Weller M, Westerman BA, Ylstra B, Wesseling P, Lasorella A, French PJ, Poisson LM, Verhaak RG, Iavarone A, Noushmehr H. The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen. Cancer Res 2024; 84:741-756. [PMID: 38117484 PMCID: PMC10911804 DOI: 10.1158/0008-5472.can-23-2093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 09/15/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023]
Abstract
Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype. SIGNIFICANCE Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.
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Affiliation(s)
- Tathiane M. Malta
- School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
| | - Thais S. Sabedot
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | | | - Indrani Datta
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | - Luciano Garofano
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | - Wies Vallentgoed
- Neurology Department, The Brain Tumour Center, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Frederick S. Varn
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut
| | | | - Fulvio D'Angelo
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, Florida
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Hui K. Gan
- Olivia Newton-John Cancer Research Institute, Austin Health, Heidelberg, Melbourne, Australia
| | - Mohammad Hasanain
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | | | - Kevin C. Johnson
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut
| | - Simona Cazacu
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | - Ana C. deCarvalho
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | | | - Emre Kocakavuk
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut
- Department of Hematology and Stem Cell Transplantation, West German Cancer Center (WTZ), National Center for Tumor Diseases (NCT) West, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Mathilde C.M. Kouwenhoven
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Simona Migliozzi
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
| | | | - Johanna M. Niers
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - D. Ryan Ormond
- University of Colorado School of Medicine, Department of Neurosurgery, Aurora, Colorado
| | - Sun Ha Paek
- Department of Neurosurgery, Cancer Research Institute, Hypoxia Ischemia Disease Institute, Seoul National University, Seoul, Republic of Korea (South)
| | - Guido Reifenberger
- Institute of Neuropathology, Heinrich Heine University, Dusseldorf, Germany
| | - Peter A. Sillevis Smitt
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- The Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Lucy F. Stead
- Leeds Institute of Medical Research, University of Leeds, Leeds, United Kingdom
| | - Martin J. van den Bent
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- The Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Erwin G. Van Meir
- Department of Neurosurgery and O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama
| | | | - Tobias Weiss
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Bart A. Westerman
- Department of Neurology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Bauke Ylstra
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Pieter Wesseling
- Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center, Amsterdam, the Netherlands
- Laboratory for Childhood Cancer Pathology, Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Anna Lasorella
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
- Department of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, Miami, Florida
| | - Pim J. French
- Neurology Department, The Brain Tumour Center, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Laila M. Poisson
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
| | - Roel G.W. Verhaak
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut
- Department of Neurosurgery, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Antonio Iavarone
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, Florida
| | - Houtan Noushmehr
- Hermelin Brain Tumor Center, Henry Ford Health System, Detroit, Michigan
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Linnerbauer M, Lößlein L, Vandrey O, Peter A, Han Y, Tsaktanis T, Wogram E, Needhamsen M, Kular L, Nagel L, Zissler J, Andert M, Meszaros L, Hanspach J, Zuber F, Naumann UJ, Diebold M, Wheeler MA, Beyer T, Nirschl L, Cirac A, Laun FB, Günther C, Winkler J, Bäuerle T, Jagodic M, Hemmer B, Prinz M, Quintana FJ, Rothhammer V. The astrocyte-produced growth factor HB-EGF limits autoimmune CNS pathology. Nat Immunol 2024; 25:432-447. [PMID: 38409259 PMCID: PMC10907300 DOI: 10.1038/s41590-024-01756-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 01/12/2024] [Indexed: 02/28/2024]
Abstract
Central nervous system (CNS)-resident cells such as microglia, oligodendrocytes and astrocytes are gaining increasing attention in respect to their contribution to CNS pathologies including multiple sclerosis (MS). Several studies have demonstrated the involvement of pro-inflammatory glial subsets in the pathogenesis and propagation of inflammatory events in MS and its animal models. However, it has only recently become clear that the underlying heterogeneity of astrocytes and microglia can not only drive inflammation, but also lead to its resolution through direct and indirect mechanisms. Failure of these tissue-protective mechanisms may potentiate disease and increase the risk of conversion to progressive stages of MS, for which currently available therapies are limited. Using proteomic analyses of cerebrospinal fluid specimens from patients with MS in combination with experimental studies, we here identify Heparin-binding EGF-like growth factor (HB-EGF) as a central mediator of tissue-protective and anti-inflammatory effects important for the recovery from acute inflammatory lesions in CNS autoimmunity. Hypoxic conditions drive the rapid upregulation of HB-EGF by astrocytes during early CNS inflammation, while pro-inflammatory conditions suppress trophic HB-EGF signaling through epigenetic modifications. Finally, we demonstrate both anti-inflammatory and tissue-protective effects of HB-EGF in a broad variety of cell types in vitro and use intranasal administration of HB-EGF in acute and post-acute stages of autoimmune neuroinflammation to attenuate disease in a preclinical mouse model of MS. Altogether, we identify astrocyte-derived HB-EGF and its epigenetic regulation as a modulator of autoimmune CNS inflammation and potential therapeutic target in MS.
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Affiliation(s)
- Mathias Linnerbauer
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Lena Lößlein
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Oliver Vandrey
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Anne Peter
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Yanan Han
- Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Center for Molecular Medicine, Stockholm, Sweden
| | - Thanos Tsaktanis
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Emile Wogram
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Maria Needhamsen
- Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Center for Molecular Medicine, Stockholm, Sweden
| | - Lara Kular
- Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Center for Molecular Medicine, Stockholm, Sweden
| | - Lisa Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Julia Zissler
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Marie Andert
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Lisa Meszaros
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Jannis Hanspach
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Finnja Zuber
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Ulrike J Naumann
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Martin Diebold
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael A Wheeler
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Tobias Beyer
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Lucy Nirschl
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Ana Cirac
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Claudia Günther
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Jürgen Winkler
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Tobias Bäuerle
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Maja Jagodic
- Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Center for Molecular Medicine, Stockholm, Sweden
| | - Bernhard Hemmer
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Marco Prinz
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Francisco J Quintana
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Veit Rothhammer
- Department of Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany.
- Deutsches Zentrum Immuntherapie (DZI), University Hospital Erlangen, Erlangen, Germany.
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Xu Q, Bao X, Lin Z, Tang L, He LN, Ren J, Zuo Z, Hu K. AStruct: detection of allele-specific RNA secondary structure in structuromic probing data. BMC Bioinformatics 2024; 25:91. [PMID: 38429654 PMCID: PMC11264973 DOI: 10.1186/s12859-024-05704-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/14/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND Uncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking. RESULTS Here, we develop a computational tool called 'AStruct' that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease. CONCLUSIONS AStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct .
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Affiliation(s)
- Qingru Xu
- State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510060, China
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Xiaoqiong Bao
- State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510060, China
| | - Zhuobin Lin
- Guangdong Key Laboratory of Liver Disease Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lin Tang
- State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510060, China
| | - Li-Na He
- State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510060, China
| | - Jian Ren
- State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510060, China
| | - Zhixiang Zuo
- State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510060, China.
| | - Kunhua Hu
- Guangdong Key Laboratory of Liver Disease Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
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Yang S, Huan R, Deng M, Luo T, Peng S, Xiong Y, Han G, Liu J, Zhang J, Tan Y. Pan-cancer analysis revealed prognosis value and immunological relevance of RAMPs. Heliyon 2024; 10:e24849. [PMID: 38317990 PMCID: PMC10838762 DOI: 10.1016/j.heliyon.2024.e24849] [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: 05/26/2023] [Revised: 12/09/2023] [Accepted: 01/16/2024] [Indexed: 02/07/2024] Open
Abstract
Whether receptor activity-modifying proteins (RAMPs) play a key role in human cancer prognosis and immunity remains unknown. We used data from the public databases, The Cancer Genome Atlas, Therapeutically Applicable Research to Generate Effective Treatments, and the Genotype-Tissue Expression project. We utilized bioinformatics methods, R software, and a variety of online databases to analyze RAMPs. In general, RAMPs were significantly and differentially expressed in multiple tumors, and RAMP expression was closely associated with prognosis, immune checkpoints, RNA-editing genes, tumor mutational burden, microsatellite instability, ploidy, and stemness indices. In addition, the expression of RAMPs is strongly correlated with tumor-infiltrating lymphocytes in human cancers. Moreover, the RAMP co-expression network is largely involved in many immune-related biological processes. Quantitative reverse transcription polymerase chain reaction and Western blot proved that RAMP3 was highly expressed in glioma, and RAMP3 promoted tumor proliferation and migration. RAMPs exhibit potential as prognostic and immune-related biomarkers in human cancers. Moreover, RAMPs can be potentially developed as therapeutic targets or used to enhance the efficacy of immunotherapy.
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Affiliation(s)
- Sha Yang
- Guizhou University Medical College, Guiyang, 550025, Guizhou Province, China
| | - Renzheng Huan
- Department of Neurosurgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Mei Deng
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Tao Luo
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Shuo Peng
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Yunbiao Xiong
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Guoqiang Han
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Jian Liu
- Guizhou University Medical College, Guiyang, 550025, Guizhou Province, China
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
| | - Jiqin Zhang
- Department of Anesthesiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Ying Tan
- Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China
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40
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Adams M, Vollmers C. Generation and analysis of a mouse multi-tissue genome annotation atlas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578267. [PMID: 38352519 PMCID: PMC10862843 DOI: 10.1101/2024.01.31.578267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Generating an accurate and complete genome annotation for an organism is complex because the cells within each tissue can express a unique set of transcript isoforms from a unique set of genes. A comprehensive genome annotation should contain information on what tissues express what transcript isoforms at what level. This tissue-level isoform information can then inform a wide range of research questions as well as experiment designs. Long-read sequencing technology combined with advanced full-length cDNA library preparation methods has now achieved throughput and accuracy where generating these types of annotations is achievable. Here, we show this by generating a genome annotation of the mouse (Mus musculus). We used the nanopore-based R2C2 long-read sequencing method to generate 64 million highly accurate full length cDNA consensus reads - averaging 5.4 million reads per tissue for a dozen tissues. Using the Mandalorion tool we processed these reads to generate the Tissue-level Atlas of Mouse Isoforms (TAMI - available at https://genome.ucsc.edu/s/vollmers/TAMI) which we believe will be a valuable complement to conventional, manually curated reference genome annotations.
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Affiliation(s)
- Matthew Adams
- Department of Molecular, Cellular, and Developmental Biology, University of California Santa Cruz
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Chen C, Xu J, Zhang J, Chen L, Wei Y, Zhang W, Shao P, Xu H. CD2AP is a potential prognostic biomarker of renal clear cell carcinoma. Cancer Med 2024; 13:e7055. [PMID: 38457255 PMCID: PMC10923042 DOI: 10.1002/cam4.7055] [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: 09/30/2023] [Revised: 01/04/2024] [Accepted: 01/10/2024] [Indexed: 03/10/2024] Open
Abstract
BACKGROUND CD2-associated protein (CD2AP) is a podocyte-associated gene and its reduced expression is associated with the development of proteinuria and glomerulosclerosis. However, few studies have focused on the correlation between the expression and prognosis of CD2AP in renal clear cell carcinoma (ccRCC). Therefore, we aimed to assess the regulation of CD2AP expression and prognostic value in ccRCC. METHODS Multiple databases were employed to examine the expression of CD2AP in ccRCC. RT-qPCR, Western Blot and immunohistochemistry were used to validate CD2AP expression in different cell lines and tissue samples. Kaplan-Meier analysis and ROC curve analysis were performed on the predictive prognostic performance of CD2AP. COX regression was used to construct CD2AP-related prognostic models. The TIMER and TISIDB databases were used to analyze the correlation of tumor-infiltrating immune cells with gene expression, mutations, somatic copy number variation, and immune molecules. Mass spectrometry was used to detect methylation status of the promoter CpG site of CD2AP in multiple cells. RESULTS We found that CD2AP expression was downregulated in ccRCC and its lower expression level was correlation with worse patient prognosis, higher tumor stage and grade and distant metastasis through analysis of databases, ccRCC cell lines and clinical tissue samples. Moreover, database and mass spectrometry techniques identified and validated cg12968598 hypermethylation as one of the key reasons for the downregulation of CD2AP expression. CD2AP expression was also associated with macrophage and neutrophil infiltration. CONCLUSIONS Taken together, our results suggest that CD2AP can be used as a diagnostic and prognostic biomarker in ccRCC patients and that DNA hypermethylation plays an important role in reducing CD2AP expression.
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Affiliation(s)
- Can Chen
- Department of Laboratory Medicinethe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Branch of National Clinical Research Center for Laboratory MedicineNanjingChina
| | - Jia Xu
- Department of Laboratory Medicinethe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Branch of National Clinical Research Center for Laboratory MedicineNanjingChina
| | - Jie‐Xin Zhang
- Department of Laboratory Medicinethe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Branch of National Clinical Research Center for Laboratory MedicineNanjingChina
| | - Lin‐Yuan Chen
- Department of Laboratory Medicinethe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Branch of National Clinical Research Center for Laboratory MedicineNanjingChina
| | - Yu‐Ang Wei
- Department of Urologythe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Wei‐Ming Zhang
- Department of Pathologythe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Peng‐Fei Shao
- Department of Urologythe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Hua‐Guo Xu
- Department of Laboratory Medicinethe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Branch of National Clinical Research Center for Laboratory MedicineNanjingChina
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Wang T, Peng J, Fan J, Tang N, Hua R, Zhou X, Wang Z, Wang L, Bai Y, Quan X, Wang Z, Zhang L, Luo C, Zhang W, Kang X, Liu J, Li L, Li L. Single-cell multi-omics profiling of human preimplantation embryos identifies cytoskeletal defects during embryonic arrest. Nat Cell Biol 2024; 26:263-277. [PMID: 38238450 DOI: 10.1038/s41556-023-01328-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 12/01/2023] [Indexed: 02/16/2024]
Abstract
Human in vitro fertilized embryos exhibit low developmental capabilities, and the mechanisms that underlie embryonic arrest remain unclear. Here using a single-cell multi-omics sequencing approach, we simultaneously analysed alterations in the transcriptome, chromatin accessibility and the DNA methylome in human embryonic arrest due to unexplained reasons. Arrested embryos displayed transcriptome disorders, including a distorted microtubule cytoskeleton, increased genomic instability and impaired glycolysis, which were coordinated with multiple epigenetic reprogramming defects. We identified Aurora A kinase (AURKA) repression as a cause of embryonic arrest. Mechanistically, arrested embryos induced through AURKA inhibition resembled the reprogramming abnormalities of natural embryonic arrest in terms of the transcriptome, the DNA methylome, chromatin accessibility and H3K4me3 modifications. Mitosis-independent sequential activation of the zygotic genome in arrested embryos showed that YY1 contributed to human major zygotic genome activation. Collectively, our study decodes the reprogramming abnormalities and mechanisms of human embryonic arrest and the key regulators of zygotic genome activation.
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Affiliation(s)
- Teng Wang
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Junhua Peng
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Jiaqi Fan
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Ni Tang
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
| | - Rui Hua
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, P. R. China
| | - Xueliang Zhou
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
| | - Zhihao Wang
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Longfei Wang
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Yanling Bai
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
| | - Xiaowan Quan
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Zimeng Wang
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Li Zhang
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China
| | - Chen Luo
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, P. R. China
| | - Weiqing Zhang
- Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, P. R. China
| | - Xiangjin Kang
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
| | - Jianqiao Liu
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
- Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China
| | - Lei Li
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China.
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China.
- Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China.
- Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, P. R. China.
| | - Lin Li
- Guangdong Provincial Key Laboratory of Proteomics, Department of Pathophysiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P. R. China.
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Liang Z, Ye H, Ma J, Wei Z, Wang Y, Zhang Y, Huang D, Song B, Meng J, Rigden DJ, Chen K. m6A-Atlas v2.0: updated resources for unraveling the N6-methyladenosine (m6A) epitranscriptome among multiple species. Nucleic Acids Res 2024; 52:D194-D202. [PMID: 37587690 PMCID: PMC10768109 DOI: 10.1093/nar/gkad691] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/02/2023] [Accepted: 08/10/2023] [Indexed: 08/18/2023] Open
Abstract
N 6-Methyladenosine (m6A) is one of the most abundant internal chemical modifications on eukaryote mRNA and is involved in numerous essential molecular functions and biological processes. To facilitate the study of this important post-transcriptional modification, we present here m6A-Atlas v2.0, an updated version of m6A-Atlas. It was expanded to include a total of 797 091 reliable m6A sites from 13 high-resolution technologies and two single-cell m6A profiles. Additionally, three methods (exomePeaks2, MACS2 and TRESS) were used to identify >16 million m6A enrichment peaks from 2712 MeRIP-seq experiments covering 651 conditions in 42 species. Quality control results of MeRIP-seq samples were also provided to help users to select reliable peaks. We also estimated the condition-specific quantitative m6A profiles (i.e. differential methylation) under 172 experimental conditions for 19 species. Further, to provide insights into potential functional circuitry, the m6A epitranscriptomics were annotated with various genomic features, interactions with RNA-binding proteins and microRNA, potentially linked splicing events and single nucleotide polymorphisms. The collected m6A sites and their functional annotations can be freely queried and downloaded via a user-friendly graphical interface at: http://rnamd.org/m6a.
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Affiliation(s)
- Zhanmin Liang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Haokai Ye
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Jiongming Ma
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Zhen Wei
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 7ZB, UK
| | - Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, UK
| | - Yuxin Zhang
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Daiyun Huang
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, Liverpool L69 7ZB, UK
| | - Bowen Song
- Department of Public Health, School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, Liverpool, UK
| | - Kunqi Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, Fujian 350004, China
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Wang H, Su M, Xing J, Zhou J, Wang J, Chen L, Dong H, Xue W, Liu Y, Wu Q, Zhang Y. HHCDB: a database of human heterochromatin regions. Nucleic Acids Res 2024; 52:D145-D153. [PMID: 37897357 PMCID: PMC10767959 DOI: 10.1093/nar/gkad954] [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: 08/03/2023] [Revised: 10/08/2023] [Accepted: 10/12/2023] [Indexed: 10/30/2023] Open
Abstract
Heterochromatin plays essential roles in eukaryotic genomes, such as regulating genes, maintaining genome integrity and silencing repetitive DNA elements. Identifying genome-wide heterochromatin regions is crucial for studying transcriptional regulation. We propose the Human Heterochromatin Chromatin Database (HHCDB) for archiving heterochromatin regions defined by specific or combined histone modifications (H3K27me3, H3K9me2, H3K9me3) according to a unified pipeline. 42 839 743 heterochromatin regions were identified from 578 samples derived from 241 cell-types/cell lines and 92 tissue types. Genomic information is provided in HHCDB, including chromatin location, gene structure, transcripts, distance from transcription start site, neighboring genes, CpG islands, transposable elements, 3D genomic structure and functional annotations. Furthermore, transcriptome data from 73 single cells were analyzed and integrated to explore cell type-specific heterochromatin-related genes. HHCDB affords rich visualization through the UCSC Genome Browser and our self-developed tools. We have also developed a specialized online analysis platform to mine differential heterochromatin regions in cancers. We performed several analyses to explore the function of cancer-specific heterochromatin-related genes, including clinical feature analysis, immune cell infiltration analysis and the construction of drug-target networks. HHCDB is a valuable resource for studying epigenetic regulation, 3D genomics and heterochromatin regulation in development and disease. HHCDB is freely accessible at http://hhcdb.edbc.org/.
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Affiliation(s)
- Hongli Wang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Mu Su
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Jie Xing
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Jie Zhou
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Jinzhang Wang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Long Chen
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Haomin Dong
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Wenhui Xue
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Yubo Liu
- The Leicester International Institute, Dalian University of Technology, Dalian 116000, China
| | - Qiong Wu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Yan Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
- College of Pathology, Qiqihar Medical University, Qiqihar 161042, China
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Song C, Zhang G, Mu X, Feng C, Zhang Q, Song S, Zhang Y, Yin M, Zhang H, Tang H, Li C. eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse. Nucleic Acids Res 2024; 52:D81-D91. [PMID: 37889077 PMCID: PMC10767853 DOI: 10.1093/nar/gkad925] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/26/2023] [Accepted: 10/12/2023] [Indexed: 10/28/2023] Open
Abstract
Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.
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Affiliation(s)
- Chao Song
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Guorui Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Xinxin Mu
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Chenchen Feng
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
| | - Qinyi Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Shuang Song
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Yuexin Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Mingxue Yin
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Hang Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Huifang Tang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Clinical Research Center for Myocardial Injury in Hunan Province, Hengyang, Hunan, 421001, China
| | - Chunquan Li
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Maternal and Child Health Care Hospital, National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
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Ye F, Wang L, Li Y, Dong C, Zhou L, Xu J. IL4I1 in M2-like macrophage promotes glioma progression and is a promising target for immunotherapy. Front Immunol 2024; 14:1338244. [PMID: 38250074 PMCID: PMC10799346 DOI: 10.3389/fimmu.2023.1338244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 12/12/2023] [Indexed: 01/23/2024] Open
Abstract
Background Glioma is the prevailing malignant intracranial tumor, characterized by an abundance of macrophages. Specifically, the infiltrating macrophages often display the M2 subtype and are known as tumor-associated macrophages (TAMs). They have a critical role in promoting the oncogenic properties of tumor cells. Interleukin-4-induced-1 (IL4I1) functions as an L-phenylalanine oxidase, playing a key part in regulating immune responses and the progression of various tumors. However, there is limited understanding of the IL4I1-mediated cross-talk function between TAMs and glioma cell in the glioma microenvironment. Methods TCGA, GTEx, and HPA databases were applied to assess the IL4I1 expression, clinical characteristics, and prognostic value of pan-cancer. The link between IL4I1 levels and the prognosis, methylation, and immune checkpoints (ICs) in gliomas were explored through Kaplan-Meier curve, Cox regression, and Spearman correlation analyses. The IL4I1 levels and their distribution were investigated by single-cell analysis and the TIMER 2 database. Additionally, validation of IL4I1 expression was performed by WB, RT-qPCR, IHC, and IF. Co-culture models between glioma cells and M2-like macrophages were used to explore the IL4I1-mediated effects on tumor growth, invasion, and migration of glioma cells. Moreover, the function of IL4I1 on macrophage polarization was evaluated by ELISA, RT-qPCR, WB, and siRNA transfection. Results Both transcriptome and protein levels of IL4I1 were increased obviously in various tumor types, and correlated with a dismal prognosis. Specifically, IL4I1 was implicated in aggressive progression and a dismal prognosis for patients with glioma. A negative association was noticed between the glioma grade and DNA promoter methylation of IL4I1. Enrichment analyses in glioma patients suggested that IL4I1 was linked to cytokine and immune responses, and was positively correlated with ICs. Single-cell analysis, molecular experiments, and in vitro assays showed that IL4I1 was significantly expressed in TAMs. Importantly, co-culture models proved that IL4I1 significantly promoted the invasion and migration of glioma cells, and induced the polarization of M2-like macrophages. Conclusion IL4I1 could be a promising immunotherapy target for selective modulation of TAMs and stands as a novel macrophage-related prognostic biomarker in glioma.
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Affiliation(s)
| | | | | | | | - Liangxue Zhou
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Jianguo Xu
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
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Rauluseviciute I, Riudavets-Puig R, Blanc-Mathieu R, Castro-Mondragon J, Ferenc K, Kumar V, Lemma RB, Lucas J, Chèneby J, Baranasic D, Khan A, Fornes O, Gundersen S, Johansen M, Hovig E, Lenhard B, Sandelin A, Wasserman W, Parcy F, Mathelier A. JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Res 2024; 52:D174-D182. [PMID: 37962376 PMCID: PMC10767809 DOI: 10.1093/nar/gkad1059] [Citation(s) in RCA: 72] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/20/2023] [Accepted: 10/31/2023] [Indexed: 11/15/2023] Open
Abstract
JASPAR (https://jaspar.elixir.no/) is a widely-used open-access database presenting manually curated high-quality and non-redundant DNA-binding profiles for transcription factors (TFs) across taxa. In this 10th release and 20th-anniversary update, the CORE collection has expanded with 329 new profiles. We updated three existing profiles and provided orthogonal support for 72 profiles from the previous release's UNVALIDATED collection. Altogether, the JASPAR 2024 update provides a 20% increase in CORE profiles from the previous release. A trimming algorithm enhanced profiles by removing low information content flanking base pairs, which were likely uninformative (within the capacity of the PFM models) for TFBS predictions and modelling TF-DNA interactions. This release includes enhanced metadata, featuring a refined classification for plant TFs' structural DNA-binding domains. The new JASPAR collections prompt updates to the genomic tracks of predicted TF binding sites (TFBSs) in 8 organisms, with human and mouse tracks available as native tracks in the UCSC Genome browser. All data are available through the JASPAR web interface and programmatically through its API and the updated Bioconductor and pyJASPAR packages. Finally, a new TFBS extraction tool enables users to retrieve predicted JASPAR TFBSs intersecting their genomic regions of interest.
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Affiliation(s)
- Ieva Rauluseviciute
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Rafael Riudavets-Puig
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Romain Blanc-Mathieu
- Laboratoire Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CNRS, CEA, INRAE, IRIG-DBSCI-LPCV, 17 avenue des martyrs, F-38054, Grenoble, France
| | - Jaime A Castro-Mondragon
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Katalin Ferenc
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Vipin Kumar
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Roza Berhanu Lemma
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
| | - Jérémy Lucas
- Laboratoire Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CNRS, CEA, INRAE, IRIG-DBSCI-LPCV, 17 avenue des martyrs, F-38054, Grenoble, France
| | - Jeanne Chèneby
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Damir Baranasic
- MRC London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
- Division of Electronics, Ruđer Bošković Institute, Bijenička cesta, 10000 Zagreb, Croatia
| | - Aziz Khan
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Oriol Fornes
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 W 28th Ave, Vancouver, BC V5Z 4H4, Canada
| | - Sveinung Gundersen
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Morten Johansen
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Eivind Hovig
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway
| | - Boris Lenhard
- MRC London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK
| | - Albin Sandelin
- Department of Biology and Biotech Research and Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK2200 Copenhagen N, Denmark
| | - Wyeth W Wasserman
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, BC Children's Hospital Research Institute, University of British Columbia, 950 W 28th Ave, Vancouver, BC V5Z 4H4, Canada
| | - François Parcy
- Laboratoire Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CNRS, CEA, INRAE, IRIG-DBSCI-LPCV, 17 avenue des martyrs, F-38054, Grenoble, France
| | - Anthony Mathelier
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Oslo, Norway
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48
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Jin Q, Feng J, Yan Y, Kuang Y. Prognostic and immunological role of adaptor related protein complex 3 subunit mu2 in colon cancer. Sci Rep 2024; 14:483. [PMID: 38177168 PMCID: PMC10767120 DOI: 10.1038/s41598-023-50452-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 12/20/2023] [Indexed: 01/06/2024] Open
Abstract
The expression levels and prognostic role of AP3M2 in colorectal adenocarcinoma (CRAC) have yet to be fully unveiled. Our study comprehensively investigated the clinical significance of AP3M2 in colorectal cancer through an extensive bioinformatics data mining process (TCGA, GEO, GEPIA, Timer, Ualcan, ROCPLOT, and David), followed by experimental validation. We found AP3M2 is a cancer gene, which can be used to distinguish between colorectal cancer and colorectal adenomas, liver metastasis, lung metastasis, colorectal polyp. Higher AP3M2 expression levels were associated with longer overall survival in colon adenocarcinoma. AP3M2 might be the primary biomarker for oxaliplatin in colon cancer and an acquired resistance biomarker for oxaliplatin and 5-fu. AP3M2 was positively associated with CD274, CTLA4. AP3M2 might be associated with T-cell, NF-kappaB transcription factor activity, and response to hypoxia. AP3M2 could predict chemotherapy effectiveness and prognosis for colon cancer patients. AP3M2 might inhibit tumor growth via influencing tumor-infiltrating immune cells in the context of Tumor microenvironment. AP3M2 plays as an oncogene in CRAC and is suggested as a new potential biotarget for therapy.
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Affiliation(s)
- Qianqian Jin
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, P. R. China
| | - Jiahao Feng
- Research Centre, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China
| | - Yang Yan
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, P. R. China.
| | - Yong Kuang
- Digestive Disease Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, China.
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Masuda LHP, Sabino AU, Reinitz J, Ramos AF, Machado-Lima A, Andrioli LP. Global repression by tailless during segmentation. Dev Biol 2024; 505:11-23. [PMID: 37879494 PMCID: PMC10949167 DOI: 10.1016/j.ydbio.2023.09.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 09/26/2023] [Accepted: 09/28/2023] [Indexed: 10/27/2023]
Abstract
The orphan nuclear receptor Tailless (Tll) exhibits conserved roles in brain formation and maintenance that are shared, for example, with vertebrate orthologous forms (Tlx). However, the early expression of tll in two gap domains in the segmentation cascade of Drosophila is unusual even for most other insects. Here we investigate tll regulation on pair-rule stripes. With ectopic misexpression of tll we detected unexpected repression of almost all pair-rule stripes of hairy (h), even-skipped (eve), runt (run), and fushi-tarazu (ftz). Examining Tll embryonic ChIP-chip data with regions mapped as Cis-Regulatory Modules (CRMs) of pair-rule stripes we verified Tll interactions to these regions. With the ChIP-chip data we also verified Tll interactions to the CRMs of gap domains and in the misexpression assay, Tll-mediated repression on Kruppel (Kr), kni (kni) and giant (gt) according to their differential sensitivity to Tll. These results with gap genes confirmed previous data from the literature and argue against indirect repression roles of Tll in the striped pattern. Moreover, the prediction of Tll binding sites in the CRMs of eve stripes and the mathematical modeling of their removal using an experimentally validated theoretical framework shows effects on eve stripes compatible with the absence of a repressor binding to the CRMs. In addition, modeling increased tll levels in the embryo results in the differential repression of eve stripes, agreeing well with the results of the misexpression assay. In genetic assays we investigated eve 5, that is strongly repressed by the ectopic domain and representative of more central stripes not previously implied to be under direct regulation of tll. While this stripe is little affected in tll-, its posterior border is expanded in gt- but detected with even greater expansion in gt-;tll-. We end up by discussing tll with key roles in combinatorial repression mechanisms to contain the expression of medial patterns of the segmentation cascade in the extremities of the embryo.
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Affiliation(s)
| | - Alan Utsuni Sabino
- Departamento de Radiologia e Oncologia, Instituto do Câncer do Estado de São Paulo, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - John Reinitz
- Departments of Statistics, Ecology and Evolution, Molecular Genetics & Cell Biology, Institute of Genomics and Systems Biology, University of Chicago, Chicago, IL, USA
| | | | - Ariane Machado-Lima
- Escola de Artes, Ciências e Humanidades da Universidade de São Paulo, São Paulo, Brazil
| | - Luiz Paulo Andrioli
- Escola de Artes, Ciências e Humanidades da Universidade de São Paulo, São Paulo, Brazil.
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50
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Kondoh H. Enhancer Activation by Transcription Factors and Underlying Mechanisms. Results Probl Cell Differ 2024; 72:167-191. [PMID: 38509258 DOI: 10.1007/978-3-031-39027-2_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Enhancers are classified into two classes based on various criteria. Class I enhancers participate primarily in finely tuned cell-specific regulation, as exemplified by the neural enhancers discussed in Chap. 9 . They are activated by simultaneous binding of transcription factors (TFs) to adjacent sites in the core sequence and are marked by moderate levels of H3K27ac modification. Class II enhancers are activated by the reiterated binding of the same TFs at multiple sites and are marked by high levels of H3K27ac modification. Class II enhancers are exemplified by enhancers in the SCR downstream of the Sox2 gene, as also discussed in Chap. 9 . Both classes of enhancers activate transcription similarly with low selectivity toward the promoters.The genomic loci broadly covered by high-level H3K27ac modification were once dubbed "Super-enhancers," implying that they are densely packed enhancers with superpowers in gene regulation. However, marking with H3K27ac modification does not predict the enhancer activity of a sequence; a "Super enhancer" region includes a few ordinary Class II enhancers. Currently, the most reliable criterion for enhancer prediction is cross-species sequence conservation.The mechanism by which transcription factors find and stay on the target enhancer site remains elusive. Results from two approaches, single-molecule live imaging and kinetic analysis using FRAP, are discussed.
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Affiliation(s)
- Hisato Kondoh
- Osaka University, Suita, Osaka, Japan
- Biohistory Research Hall, Takatsuki, Osaka, Japan
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