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Terlecki-Zaniewicz L, Lämmermann I, Latreille J, Bobbili MR, Pils V, Schosserer M, Weinmüllner R, Dellago H, Skalicky S, Pum D, Almaraz JCH, Scheideler M, Morizot F, Hackl M, Gruber F, Grillari J. Small extracellular vesicles and their miRNA cargo are anti-apoptotic members of the senescence-associated secretory phenotype. Aging (Albany NY) 2019; 10:1103-1132. [PMID: 29779019 PMCID: PMC5990398 DOI: 10.18632/aging.101452] [Citation(s) in RCA: 157] [Impact Index Per Article: 26.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Accepted: 05/10/2018] [Indexed: 12/15/2022]
Abstract
Loss of functionality during aging of cells and organisms is caused and accompanied by altered cell-to-cell communication and signalling. One factor thereby is the chronic accumulation of senescent cells and the concomitant senescence-associated secretory phenotype (SASP) that contributes to microenvironment remodelling and a pro-inflammatory status. While protein based SASP factors have been well characterized, little is known about small extracellular vesicles (sEVs) and their miRNA cargo. Therefore, we analysed secretion of sEVs from senescent human dermal fibroblasts and catalogued the therein contained miRNAs. We observed a four-fold increase of sEVs, with a concomitant increase of >80% of all cargo miRNAs. The most abundantly secreted miRNAs were predicted to collectively target mRNAs of pro-apoptotic proteins, and indeed, senescent cell derived sEVs exerted anti-apoptotic activity. In addition, we identified senescence-specific differences in miRNA composition of sEVs, with an increase of miR-23a-5p and miR-137 and a decrease of miR-625-3p, miR-766-3p, miR-199b-5p, miR-381-3p, miR-17-3p. By correlating intracellular and sEV-miRNAs, we identified miRNAs selectively retained in senescent cells (miR-21-3p and miR-17-3p) or packaged specifically into senescent cell derived sEVs (miR-15b-5p and miR-30a-3p). Therefore, we suggest sEVs and their miRNA cargo to be novel, members of the SASP that are selectively secreted or retained in cellular senescence.
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Higareda-Almaraz JC, Karbiener M, Giroud M, Pauler FM, Gerhalter T, Herzig S, Scheideler M. Norepinephrine triggers an immediate-early regulatory network response in primary human white adipocytes. BMC Genomics 2018; 19:794. [PMID: 30390616 PMCID: PMC6215669 DOI: 10.1186/s12864-018-5173-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 10/16/2018] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Norepinephrine (NE) signaling has a key role in white adipose tissue (WAT) functions, including lipolysis, free fatty acid liberation and, under certain conditions, conversion of white into brite (brown-in-white) adipocytes. However, acute effects of NE stimulation have not been described at the transcriptional network level. RESULTS We used RNA-seq to uncover a broad transcriptional response. The inference of protein-protein and protein-DNA interaction networks allowed us to identify a set of immediate-early genes (IEGs) with high betweenness, validating our approach and suggesting a hierarchical control of transcriptional regulation. In addition, we identified a transcriptional regulatory network with IEGs as master regulators, including HSF1 and NFIL3 as novel NE-induced IEG candidates. Moreover, a functional enrichment analysis and gene clustering into functional modules suggest a crosstalk between metabolic, signaling, and immune responses. CONCLUSIONS Altogether, our network biology approach explores for the first time the immediate-early systems level response of human adipocytes to acute sympathetic activation, thereby providing a first network basis of early cell fate programs and crosstalks between metabolic and transcriptional networks required for proper WAT function.
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Affiliation(s)
- Juan Carlos Higareda-Almaraz
- Institute for Diabetes and Cancer (IDC), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Joint Heidelberg-IDC Translational Diabetes Program, Heidelberg University Hospital, Heidelberg, Germany
- Molecular Metabolic Control, Medical Faculty, Technical University, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- NMR laboratory, Institute of Myology, Hopital Universitaire Pitie Salpetriere, Paris, France
| | - Michael Karbiener
- Department of Phoniatrics, ENT University Hospital, Medical University of Graz, Graz, Austria
| | - Maude Giroud
- Institute for Diabetes and Cancer (IDC), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Joint Heidelberg-IDC Translational Diabetes Program, Heidelberg University Hospital, Heidelberg, Germany
- Molecular Metabolic Control, Medical Faculty, Technical University, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Florian M. Pauler
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
- Present Address: Institute of Science and Technology (IST) Austria, Klosterneuburg, Austria
| | - Teresa Gerhalter
- Present Address: Institute of Science and Technology (IST) Austria, Klosterneuburg, Austria
| | - Stephan Herzig
- Institute for Diabetes and Cancer (IDC), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Joint Heidelberg-IDC Translational Diabetes Program, Heidelberg University Hospital, Heidelberg, Germany
- Molecular Metabolic Control, Medical Faculty, Technical University, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Marcel Scheideler
- Institute for Diabetes and Cancer (IDC), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Joint Heidelberg-IDC Translational Diabetes Program, Heidelberg University Hospital, Heidelberg, Germany
- Molecular Metabolic Control, Medical Faculty, Technical University, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- NMR laboratory, Institute of Myology, Hopital Universitaire Pitie Salpetriere, Paris, France
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Systems-level effects of ectopic galectin-7 reconstitution in cervical cancer and its microenvironment. BMC Cancer 2016; 16:680. [PMID: 27558259 PMCID: PMC4997669 DOI: 10.1186/s12885-016-2700-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 08/09/2016] [Indexed: 12/20/2022] Open
Abstract
Background Galectin-7 (Gal-7) is negatively regulated in cervical cancer, and appears to be a link between the apoptotic response triggered by cancer and the anti-tumoral activity of the immune system. Our understanding of how cervical cancer cells and their molecular networks adapt in response to the expression of Gal-7 remains limited. Methods Meta-analysis of Gal-7 expression was conducted in three cervical cancer cohort studies and TCGA. In silico prediction and bisulfite sequencing were performed to inquire epigenetic alterations. To study the effect of Gal-7 on cervical cancer, we ectopically re-expressed it in the HeLa and SiHa cervical cancer cell lines, and analyzed their transcriptome and SILAC-based proteome. We also examined the tumor and microenvironment host cell transcriptomes after xenotransplantation into immunocompromised mice. Differences between samples were assessed with the Kruskall-Wallis, Dunn’s Multiple Comparison and T tests. Kaplan–Meier and log-rank tests were used to determine overall survival. Results Gal-7 was constantly downregulated in our meta-analysis (p < 0.0001). Tumors with combined high Gal-7 and low galectin-1 expression (p = 0.0001) presented significantly better prognoses (p = 0.005). In silico and bisulfite sequencing assays showed de novo methylation in the Gal-7 promoter and first intron. Cells re-expressing Gal-7 showed a high apoptosis ratio (p < 0.05) and their xenografts displayed strong growth retardation (p < 0.001). Multiple gene modules and transcriptional regulators were modulated in response to Gal-7 reconstitution, both in cervical cancer cells and their microenvironments (FDR < 0.05 %). Most of these genes and modules were associated with tissue morphogenesis, metabolism, transport, chemokine activity, and immune response. These functional modules could exert the same effects in vitro and in vivo, even despite different compositions between HeLa and SiHa samples. Conclusions Gal-7 re-expression affects the regulation of molecular networks in cervical cancer that are involved in diverse cancer hallmarks, such as metabolism, growth control, invasion and evasion of apoptosis. The effect of Gal-7 extends to the microenvironment, where networks involved in its configuration and in immune surveillance are particularly affected. Electronic supplementary material The online version of this article (doi:10.1186/s12885-016-2700-8) contains supplementary material, which is available to authorized users.
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IPA Analysis of Cervicovaginal Fluid from Precancerous Women Points to the Presence of Biomarkers for the Precancerous State of Cervical Carcinoma. Proteomes 2014; 2:426-450. [PMID: 28250389 PMCID: PMC5302755 DOI: 10.3390/proteomes2030426] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2014] [Revised: 04/07/2014] [Accepted: 08/05/2014] [Indexed: 01/08/2023] Open
Abstract
Despite large gaps in our knowledge on the intracellular mechanism leading to cervical cancer, the pathways induced by oncogenic high-risk Human Papilloma Virus (HPV) and those finally causing cervical cancer are increasingly being unraveled. Assuming that precancerous tissue is recognized and lysed by the immune system—which is in many cases incomplete because of the counteraction by the HPV virus—we hypothesize that several intracellular factors, involved in induction and development of precancerous lesions and/or cervical cancer are being released into the cervicovaginal fluid (CVF). These factors can then be seen as markers for the precancerous state, and when they persist they are indicative for an increased risk for cervical carcinoma. In a previous study, we analyzed the proteomic profiles of six CVF samples from women with different stages of precancerous lesions and compared these with the CVF proteomes from healthy women. Here, we extend these observations by investigating these proteomes by Ingenuity Pathway Analysis (IPA). We show that proteins in CVF from precancerous women are clearly more involved in pathways that make up the ‘hallmarks of cancer’, as compared to CVF proteins from healthy persons. Moreover, after literature search, proteins classified by IPA in the ‘cancer’ category, were more correlated with cervical cancer when they originated from CVF from precancerous women. Many of these proteins formed a network with angiotensin II as central mediator. The search for ‘network biomarkers’, rather than single biomarkers, could drastically increase specificity, sensitivity and prognostic value of cervical cancer diagnosis, making use of an easy to handle fluid, the CVF.
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Ciesielski TH, Pendergrass SA, White MJ, Kodaman N, Sobota RS, Huang M, Bartlett J, Li J, Pan Q, Gui J, Selleck SB, Amos CI, Ritchie MD, Moore JH, Williams SM. Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors. BioData Min 2014; 7:10. [PMID: 25071867 PMCID: PMC4112852 DOI: 10.1186/1756-0381-7-10] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2013] [Accepted: 06/08/2014] [Indexed: 11/10/2022] Open
Abstract
In omic research, such as genome wide association studies, researchers seek to repeat their results in other datasets to reduce false positive findings and thus provide evidence for the existence of true associations. Unfortunately this standard validation approach cannot completely eliminate false positive conclusions, and it can also mask many true associations that might otherwise advance our understanding of pathology. These issues beg the question: How can we increase the amount of knowledge gained from high throughput genetic data? To address this challenge, we present an approach that complements standard statistical validation methods by drawing attention to both potential false negative and false positive conclusions, as well as providing broad information for directing future research. The Diverse Convergent Evidence approach (DiCE) we propose integrates information from multiple sources (omics, informatics, and laboratory experiments) to estimate the strength of the available corroborating evidence supporting a given association. This process is designed to yield an evidence metric that has utility when etiologic heterogeneity, variable risk factor frequencies, and a variety of observational data imperfections might lead to false conclusions. We provide proof of principle examples in which DiCE identified strong evidence for associations that have established biological importance, when standard validation methods alone did not provide support. If used as an adjunct to standard validation methods this approach can leverage multiple distinct data types to improve genetic risk factor discovery/validation, promote effective science communication, and guide future research directions.
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Affiliation(s)
- Timothy H Ciesielski
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Sarah A Pendergrass
- Center for Systems Genomics, Pennsylvania State University, University Park, PA 16802, USA.,Department of Biochemistry & Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Marquitta J White
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.,Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232-0700, USA
| | - Nuri Kodaman
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.,Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232-0700, USA
| | - Rafal S Sobota
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.,Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232-0700, USA
| | - Minjun Huang
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | - Jacquelaine Bartlett
- Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Jing Li
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | - Qinxin Pan
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | - Jiang Gui
- Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.,Community and Family Medicine, Section of Biostatistics & Epidemiology, Geisel School of Medicine, Hanover, NH 03766, USA
| | - Scott B Selleck
- Department of Biochemistry & Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Christopher I Amos
- Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.,Community and Family Medicine, Section of Biostatistics & Epidemiology, Geisel School of Medicine, Hanover, NH 03766, USA
| | - Marylyn D Ritchie
- Center for Systems Genomics, Pennsylvania State University, University Park, PA 16802, USA.,Department of Biochemistry & Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Jason H Moore
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA.,Community and Family Medicine, Section of Biostatistics & Epidemiology, Geisel School of Medicine, Hanover, NH 03766, USA
| | - Scott M Williams
- Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA.,Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, NH 03755, USA
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