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Ullah A, Chen Y, Singla RK, Cao D, Shen B. Pro-inflammatory cytokines and CXC chemokines as game-changer in age-associated prostate cancer and ovarian cancer: Insights from preclinical and clinical studies' outcomes. Pharmacol Res 2024; 204:107213. [PMID: 38750677 DOI: 10.1016/j.phrs.2024.107213] [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: 01/29/2024] [Revised: 04/15/2024] [Accepted: 05/09/2024] [Indexed: 06/01/2024]
Abstract
Prostate cancer (PC) and Ovarian cancer (OC) are two of the most common types of cancer that affect the reproductive systems of older men and women. These cancers are associated with a poor quality of life among the aged population. Therefore, finding new and innovative ways to detect, treat, and prevent these cancers in older patients is essential. Finding biomarkers for these malignancies will increase the chance of early detection and effective treatment, subsequently improving the survival rate. Studies have shown that the prevalence and health of some illnesses are linked to an impaired immune system. However, the age-associated changes in the immune system during malignancies such as PC and OC are poorly understood. Recent research has suggested that the excessive production of inflammatory immune mediators, such as interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor (TGF), tumor necrosis factor (TNF), CXC motif chemokine ligand 1 (CXCL1), CXC motif chemokine ligand 12 (CXCL12), and CXC motif chemokine ligand 13 (CXCL13), etc., significantly impact the development of PC and OC in elderly patients. Our review focuses on the latest functional studies of pro-inflammatory cytokines (interleukins) and CXC chemokines, which serve as biomarkers in elderly patients with PC and OC. Thus, we aim to shed light on how these biomarkers affect the development of PC and OC in elderly patients. We also examine the current status and future perspective of cytokines (interleukins) and CXC chemokines-based therapeutic targets in OC and PC treatment for elderly patients.
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Affiliation(s)
- Amin Ullah
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Yongxiu Chen
- Gynecology Department, Guangdong Women and Children Hospital, No. 521, Xingnan Road, Panyu District, Guangzhou 511442, China
| | - Rajeev K Singla
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China; School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, Punjab 144411, India
| | - Dan Cao
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Bairong Shen
- Department of Abdominal Oncology, Cancer Center of West China Hospital and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
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Lee KY, Beatson EL, Steinberg SM, Chau CH, Price DK, Figg WD. Bridging Health Disparities: a Genomics and Transcriptomics Analysis by Race in Prostate Cancer. J Racial Ethn Health Disparities 2024; 11:492-504. [PMID: 36810713 PMCID: PMC10686215 DOI: 10.1007/s40615-023-01534-4] [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: 10/05/2022] [Revised: 01/28/2023] [Accepted: 02/03/2023] [Indexed: 02/23/2023]
Abstract
As the era of cancer genomics expands, disproportionate rates of prostate cancer incidence and mortality by race have demonstrated increasing relevance in clinical settings. While Black men are most particularly affected, as data has historically shown, the opposite is observed for Asian men, thus creating a basis for exploring genomic pathways potentially involved in mediating these opposing trends. Studies on racial differences are limited by sample size, but recent expanding collaborations between research institutions may improve these imbalances to enhance investigations on health disparities from the genomics front. In this study, we performed a race genomics analysis using GENIE v11, released in January 2022, to investigate mutation and copy number frequencies of select genes in both primary and metastatic patient tumor samples. Further, we investigate the TCGA race cohort to conduct an ancestry analysis and to identify differentially expressed genes highly upregulated in one race and subsequently downregulated in another. Our findings highlight pathway-oriented genetic mutation frequencies characterized by race, and further, we identify candidate gene transcripts that have differential expression between Black and Asian men.
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Affiliation(s)
- Kristi Y Lee
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Erica L Beatson
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Seth M Steinberg
- Biostatistics and Data Management Section, Office of the Clinical Director, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Cindy H Chau
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Douglas K Price
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - William D Figg
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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Reynolds SR, Zhang Z, Salas LA, Christensen BC. Tumor microenvironment deconvolution identifies cell-type-independent aberrant DNA methylation and gene expression in prostate cancer. Clin Epigenetics 2024; 16:5. [PMID: 38173042 PMCID: PMC10765773 DOI: 10.1186/s13148-023-01609-3] [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: 08/18/2023] [Accepted: 11/25/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Among men, prostate cancer (PCa) is the second most common cancer and the second leading cause of cancer death. Etiologic factors associated with both prostate carcinogenesis and somatic alterations in tumors are incompletely understood. While genetic variants associated with PCa have been identified, epigenetic alterations in PCa are relatively understudied. To date, DNA methylation (DNAm) and gene expression (GE) in PCa have been investigated; however, these studies did not correct for cell-type proportions of the tumor microenvironment (TME), which could confound results. METHODS The data (GSE183040) consisted of DNAm and GE data from both tumor and adjacent non-tumor prostate tissue of 56 patients who underwent radical prostatectomies prior to any treatment. This study builds upon previous studies that examined methylation patterns and GE in PCa patients by using a novel tumor deconvolution approach to identify and correct for cell-type proportions of the TME in its epigenome-wide association study (EWAS) and differential expression analysis (DEA). RESULTS The inclusion of cell-type proportions in EWASs and DEAs reduced the scope of significant alterations associated with PCa. We identified 2,093 significantly differentially methylated CpGs (DMC), and 51 genes associated with PCa, including PCA3, SPINK1, and AMACR. CONCLUSIONS This work illustrates the importance of correcting for cell types of the TME when performing EWASs and DEAs on PCa samples, and establishes a more confounding-adverse methodology. We identified a more tumor-cell-specific set of altered genes and epigenetic marks that can be further investigated as potential biomarkers of disease or potential therapeutic targets.
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Affiliation(s)
- Samuel R Reynolds
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
| | - Ze Zhang
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
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Li J, Huang HY, Lin YCD, Zuo H, Tang Y, Huang HD. Cinnamomi ramulus inhibits cancer cells growth by inducing G2/M arrest. Front Pharmacol 2023; 14:1121799. [PMID: 37007025 PMCID: PMC10063822 DOI: 10.3389/fphar.2023.1121799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/13/2023] [Indexed: 03/19/2023] Open
Abstract
Introduction:Cinnamomi ramulus (CR) is one of the most widely used traditional Chinese medicine (TCM) with anti-cancer effects. Analyzing transcriptomic responses of different human cell lines to TCM treatment is a promising approach to understand the unbiased mechanism of TCM.Methods: This study treated ten cancer cell lines with different CR concentrations, followed by mRNA sequencing. Differential expression (DE) analysis and gene set enrichment analysis (GSEA) were utilized to analyze transcriptomic data. Finally, the in silico screening results were verified by in vitro experiments.Results: Both DE and GSEA analysis suggested the Cell cycle pathway was the most perturbated pathway by CR across these cell lines. By analyzing the clinical significance and prognosis of G2/M related genes (PLK1, CDK1, CCNB1, and CCNB2) in various cancer tissues, we found that they were up-regulated in most cancer types, and their down-regulation showed better overall survival rates in cancer patients. Finally, in vitro experiments validation on A549, Hep G2, and HeLa cells suggested that CR can inhibit cell growth by suppressing the PLK1/CDK1/ Cyclin B axis.Discussion: This is the first study to apply transcriptomic analysis to investigate the cancer cell growth inhibition of CR on various human cancer cell lines. The core effect of CR on ten cancer cell lines is to induce G2/M arrest by inhibiting the PLK1/CDK1/Cyclin B axis.
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Affiliation(s)
- Jing Li
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
| | - Hsi-Yuan Huang
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
| | - Yang-Chi-Dung Lin
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
| | - Huali Zuo
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
| | - Yun Tang
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
| | - Hsien-Da Huang
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
- *Correspondence: Hsien-Da Huang,
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Identification of Transcription Factors Regulating SARS-CoV-2 Tropism Factor Expression by Inferring Cell-Type-Specific Transcriptional Regulatory Networks in Human Lungs. Viruses 2022; 14:v14040837. [PMID: 35458567 PMCID: PMC9026071 DOI: 10.3390/v14040837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/02/2022] [Accepted: 04/05/2022] [Indexed: 02/04/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that caused the coronavirus disease 2019 (COVID-19) pandemic. Though previous studies have suggested that SARS-CoV-2 cellular tropism depends on the host-cell-expressed proteins, whether transcriptional regulation controls SARS-CoV-2 tropism factors in human lung cells remains unclear. In this study, we used computational approaches to identify transcription factors (TFs) regulating SARS-CoV-2 tropism for different types of lung cells. We constructed transcriptional regulatory networks (TRNs) controlling SARS-CoV-2 tropism factors for healthy donors and COVID-19 patients using lung single-cell RNA-sequencing (scRNA-seq) data. Through differential network analysis, we found that the altered regulatory role of TFs in the same cell types of healthy and SARS-CoV-2-infected networks may be partially responsible for differential tropism factor expression. In addition, we identified the TFs with high centralities from each cell type and proposed currently available drugs that target these TFs as potential candidates for the treatment of SARS-CoV-2 infection. Altogether, our work provides valuable cell-type-specific TRN models for understanding the transcriptional regulation and gene expression of SARS-CoV-2 tropism factors.
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Transcriptome study of receptive endometrium in overweight and obese women shows important expression differences in immune response and inflammatory pathways in women who do not conceive. PLoS One 2021; 16:e0261873. [PMID: 34941965 PMCID: PMC8699967 DOI: 10.1371/journal.pone.0261873] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 12/12/2021] [Indexed: 12/15/2022] Open
Abstract
Obesity and being overweight are growing worldwide health problems that also affect women of reproductive age. They impair women’s fertility and are associated with lower IVF success rates. The mechanism by which increased body weight disrupts fertility has not yet been established. One possibility is that it affects the process of embryo implantation on the endometrial level. The purpose of our study was to determine the differences in enriched biological pathways in the endometrium of overweight and obese women undergoing IVF procedures. For this purpose, 14 patients (5 pregnant, 9 non-pregnant) were included in the study. Endometrial samples were obtained during the window of implantation and RNA sequencing was performed. There were no differences in general patient’s and IVF cycle characteristics between pregnant and non-pregnant women. In the endometrial samples of women who did not conceive, pathways related to the immune response, inflammation, and reactive oxygen species production were over-expressed. Our findings show that the reason for implantation failure in overweight and obese women could lie in the excessive immune and inflammatory response at the endometrial level.
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Shah A, Shah AA, K N, Lobo R. Mechanistic targets for BPH and prostate cancer-a review. REVIEWS ON ENVIRONMENTAL HEALTH 2021; 36:261-270. [PMID: 32960781 DOI: 10.1515/reveh-2020-0051] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 09/02/2020] [Indexed: 05/26/2023]
Abstract
All men, almost, suffer from prostatic disorders in average life expectancy. In the year of 1950s, the first autopsy of prostate gland discovered the link between Benign prostatic hyperplasia (BPH) and Prostate Cancer (PCa). After that, many histology, biochemistry, epidemiology studies explained the association and associated risk factor for the same. From the various scientific evidence, it is proved that both diseases share some common transcription factors and signalling pathways. Still, BPH cannot be considered as the first step of PCa progression. To define, the relationship between both of the diseases, a well-defined large epidemiological study is needed. Along with androgen signalling, imbalanced apoptosis, oxidative stress, and microbial infection also crucial factors that significantly affect the pathogenesis of BPH. Various signalling pathways are involved in the progression of BPH. Androgen signalling is the driving force for the progress of PCa. In PCa androgen signalling is upregulated as compared to a healthy prostate. Some dominant Androgen-regulated genes and their functions have been discussed in this work.
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Affiliation(s)
- Abhishek Shah
- Department of Pharmacognosy, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Aarti Abhishek Shah
- Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Nandakumar K
- Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Richard Lobo
- Department of Pharmacognosy, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
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Cangiano M, Grudniewska M, Salji MJ, Nykter M, Jenster G, Urbanucci A, Granchi Z, Janssen B, Hamilton G, Leung HY, Beumer IJ. Gene Regulation Network Analysis on Human Prostate Orthografts Highlights a Potential Role for the JMJD6 Regulon in Clinical Prostate Cancer. Cancers (Basel) 2021; 13:cancers13092094. [PMID: 33925994 PMCID: PMC8123677 DOI: 10.3390/cancers13092094] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 04/09/2021] [Accepted: 04/21/2021] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Prostate cancer is a very common malignancy worldwide. Treatment resistant prostate cancer poses a big challenge to clinicians and is the second most common cause of premature death in men with cancer. Gene expression analysis has been performed on clinical tumours but to date none of the gene expression-based biomarkers for prostate cancer have been successfully integrated to into clinical practice to improve patient management and treatment choice. We applied a novel laboratory prostate cancer model to mimic clinical hormone responsive and resistant prostate cancer and tested whether a network of genes similarly regulated by transcription factors (gene products that control the expression of target genes) are associated with patient outcome. We identified regulons (networks of genes similarly regulated) from our preclinical prostate cancer models and further evaluated the top ranked JMJD6 gene related regulated network in three independent clinical patient cohorts. Abstract Background: Prostate cancer (PCa) is the second most common tumour diagnosed in men. Tumoral heterogeneity in PCa creates a significant challenge to develop robust prognostic markers and novel targets for therapy. An analysis of gene regulatory networks (GRNs) in PCa may provide insight into progressive PCa. Herein, we exploited a graph-based enrichment score to integrate data from GRNs identified in preclinical prostate orthografts and differentially expressed genes in clinical resected PCa. We identified active regulons (transcriptional regulators and their targeted genes) associated with PCa recurrence following radical prostatectomy. Methods: The expression of known transcription factors and co-factors was analysed in a panel of prostate orthografts (n = 18). We searched for genes (as part of individual GRNs) predicted to be regulated by the highest number of transcriptional factors. Using differentially expressed gene analysis (on a per sample basis) coupled with gene graph enrichment analysis, we identified candidate genes and associated GRNs in PCa within the UTA cohort, with the most enriched regulon being JMJD6, which was further validated in two additional cohorts, namely EMC and ICGC cohorts. Cox regression analysis was performed to evaluate the association of the JMJD6 regulon activity with disease-free survival time in the three clinical cohorts as well as compared to three published prognostic gene signatures (TMCC11, BROMO-10 and HYPOXIA-28). Results: 1308 regulons were correlated to transcriptomic data from the three clinical prostatectomy cohorts. The JMJD6 regulon was identified as the top enriched regulon in the UTA cohort and again validated in the EMC cohort as the top-ranking regulon. In both UTA and EMC cohorts, the JMJD6 regulon was significantly associated with cancer recurrence. Active JMJD6 regulon also correlated with disease recurrence in the ICGC cohort. Furthermore, Kaplan–Meier analysis confirmed shorter time to recurrence in patients with active JMJD6 regulon for all three clinical cohorts (UTA, EMC and ICGC), which was not the case for three published prognostic gene signatures (TMCC11, BROMO-10 and HYPOXIA-28). In multivariate analysis, the JMJD6 regulon status significantly predicted disease recurrence in the UTA and EMC, but not ICGC datasets, while none of the three published signatures significantly prognosticate for cancer recurrence. Conclusions: We have characterised gene regulatory networks from preclinical prostate orthografts and applied transcriptomic data from three clinical cohorts to evaluate the prognostic potential of the JMJD6 regulon.
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Affiliation(s)
- Mario Cangiano
- GenomeScan B.V. Plesmanlaan 1D, 2333 BZ Leiden, The Netherlands; (M.C.); (M.G.); (Z.G.); (B.J.)
| | - Magda Grudniewska
- GenomeScan B.V. Plesmanlaan 1D, 2333 BZ Leiden, The Netherlands; (M.C.); (M.G.); (Z.G.); (B.J.)
| | - Mark J. Salji
- Institute of Cancer Sciences, University of Glasgow, Glasgow G61 1QH, UK;
- CRUK Beatson Institute, Glasgow G61 1BD, UK
| | - Matti Nykter
- Laboratory of Computational Biology, Institute of Biomedical Technology, Arvo Ylpön katu 34, 33520 Tampere, Finland;
| | - Guido Jenster
- Department of Urology, Erasmus Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, The Netherlands;
| | - Alfonso Urbanucci
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, 0424 Oslo, Norway;
| | - Zoraide Granchi
- GenomeScan B.V. Plesmanlaan 1D, 2333 BZ Leiden, The Netherlands; (M.C.); (M.G.); (Z.G.); (B.J.)
| | - Bart Janssen
- GenomeScan B.V. Plesmanlaan 1D, 2333 BZ Leiden, The Netherlands; (M.C.); (M.G.); (Z.G.); (B.J.)
| | - Graham Hamilton
- Glasgow Polyomics, University of Glasgow, Glasgow G61 1QH, UK;
| | - Hing Y. Leung
- Institute of Cancer Sciences, University of Glasgow, Glasgow G61 1QH, UK;
- CRUK Beatson Institute, Glasgow G61 1BD, UK
- Correspondence: (H.Y.L.); (I.J.B.)
| | - Inès J. Beumer
- GenomeScan B.V. Plesmanlaan 1D, 2333 BZ Leiden, The Netherlands; (M.C.); (M.G.); (Z.G.); (B.J.)
- Correspondence: (H.Y.L.); (I.J.B.)
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Martínez R, Codina AE, Barata C, Tauler R, Piña B, Navarro-Martín L. Transcriptomic effects of tributyltin (TBT) in zebrafish eleutheroembryos. A functional benchmark dose analysis. JOURNAL OF HAZARDOUS MATERIALS 2020; 398:122881. [PMID: 32474318 DOI: 10.1016/j.jhazmat.2020.122881] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 04/03/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
Exposure to the antifouling tributyltin (TBT) has been related to imposex in mollusks and to obesogenicity, adipogenesis and masculinization in fish. To understand the underlying molecular mechanisms, we evaluated dose-response effects of TBT (1.7-56 nM) in zebrafish eleutheroembryos transcriptome exposed from 2 to 5 days post-fertilization. RNA-sequencing analysis identified 3238 differentially expressed transcripts in eleutheroembryos exposed to TBT. Benchmark dose analyses (BMD) showed that the point of departure (PoD) for transcriptomic effects (9.28 nM) was similar to the metabolomic PoD (11.5 nM) and about one order of magnitude lower than the morphometric PoD (67.9 nM) or the median lethal concentration (LC50: 93.6 nM). Functional analysis of BMD transcriptomic data identified steroid metabolism and cholesterol and vitamin D3 biosynthesis as the most sensitive pathways to TBT (<50% PoD). Conversely, transcripts related to general stress and DNA damage became affected only at doses above the PoD. Therefore, our results indicate that transcriptomes can act as early molecular indicators of pollutant exposure, and illustrates their usefulness for the mechanistic identification of the initial toxic events. As the estimated molecular PoDs are close to environmental levels, we concluded that TBT may represent a substantial risk in some natural environments.
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Affiliation(s)
- Rubén Martínez
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain; Universitat de Barcelona (UB), Barcelona, Catalunya 08007, Spain.
| | - Anna E Codina
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain; Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.
| | - Carlos Barata
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Romà Tauler
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Benjamin Piña
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
| | - Laia Navarro-Martín
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona, Catalunya, 08034, Spain.
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Rahem SM, Epsi NJ, Coffman FD, Mitrofanova A. Genome-wide analysis of therapeutic response uncovers molecular pathways governing tamoxifen resistance in ER+ breast cancer. EBioMedicine 2020; 61:103047. [PMID: 33099086 PMCID: PMC7585053 DOI: 10.1016/j.ebiom.2020.103047] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 09/02/2020] [Accepted: 09/18/2020] [Indexed: 01/10/2023] Open
Abstract
Background Prioritization of breast cancer patients based on the risk of resistance to tamoxifen plays a significant role in personalized therapeutic planning and improving disease course and outcomes. Methods In this work, we demonstrate that a genome-wide pathway-centric computational framework elucidates molecular pathways as markers of tamoxifen resistance in ER+ breast cancer patients. In particular, we associated activity levels of molecular pathways with a wide spectrum of response to tamoxifen, which defined markers of tamoxifen resistance in patients with ER+ breast cancer. Findings We identified five biological pathways as markers of tamoxifen failure and demonstrated their ability to predict the risk of tamoxifen resistance in two independent patient cohorts (Test cohort1: log-rank p-value = 0.02, adjusted HR = 3.11; Test cohort2: log-rank p-value = 0.01, adjusted HR = 4.24). We have shown that these pathways are not markers of aggressiveness and outperform known markers of tamoxifen response. Furthermore, for adoption into clinic, we derived a list of pathway read-out genes and their associated scoring system, which assigns a risk of tamoxifen resistance for new incoming patients. Interpretation We propose that the identified pathways and their read-out genes can be utilized to prioritize patients who would benefit from tamoxifen treatment and patients at risk of tamoxifen resistance that should be offered alternative regimens. Funding This work was supported by the Rutgers SHP Dean's research grant, Rutgers start-up funds, Libyan Ministry of Higher Education and Scientific Research, and Katrina Kehlet Graduate Award from The NJ Chapter of the Healthcare Information Management Systems Society.
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Affiliation(s)
- Sarra M Rahem
- Department of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA
| | - Nusrat J Epsi
- Department of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA
| | - Frederick D Coffman
- Department of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA; Department of Physician Assistant Studies and Practice, USA; Department of Pathology & Laboratory Medicine, New Jersey Medical School, Newark, New Jersey 07107, USA
| | - Antonina Mitrofanova
- Department of Biomedical and Health Informatics, Rutgers School of Health Professions, Rutgers Biomedical and Health Sciences, USA; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, New Jersey 08901, USA.
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Mir DA, Balamurugan K. Modulation of the host cell mitochondrial proteome by PemKSa toxin protein exposure. Microb Pathog 2020; 140:103963. [DOI: 10.1016/j.micpath.2020.103963] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 12/28/2019] [Accepted: 01/01/2020] [Indexed: 12/16/2022]
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Barneh F, Mirzaie M, Nickchi P, Tan TZ, Thiery JP, Piran M, Salimi M, Goshadrou F, Aref AR, Jafari M. Integrated use of bioinformatic resources reveals that co-targeting of histone deacetylases, IKBK and SRC inhibits epithelial-mesenchymal transition in cancer. Brief Bioinform 2020; 20:717-731. [PMID: 29726962 DOI: 10.1093/bib/bby030] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Revised: 03/04/2018] [Indexed: 02/07/2023] Open
Abstract
With the advent of high-throughput technologies leading to big data generation, increasing number of gene signatures are being published to predict various features of diseases such as prognosis and patient survival. However, to use these signatures for identifying therapeutic targets, use of additional bioinformatic tools is indispensible part of research. Here, we have generated a pipeline comprised of nearly 15 bioinformatic tools and enrichment statistical methods to propose and validate a drug combination strategy from already approved drugs and present our approach using published pan-cancer epithelial-mesenchymal transition (EMT) signatures as a case study. We observed that histone deacetylases were critical targets to tune expression of multiple epithelial versus mesenchymal genes. Moreover, SRC and IKBK were the principal intracellular kinases regulating multiple signaling pathways. To confirm the anti-EMT efficacy of the proposed target combination in silico, we validated expression of targets in mesenchymal versus epithelial subtypes of ovarian cancer. Additionally, we inhibited the pinpointed proteins in vitro using an invasive lung cancer cell line. We found that whereas low-dose mono-therapy failed to limit cell dispersion from collagen spheroids in a microfluidic device as a metric of EMT, the combination fully inhibited dissociation and invasion of cancer cells toward cocultured endothelial cells. Given the approval status and safety profiles of the suggested drugs, the proposed combination set can be considered in clinical trials.
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Affiliation(s)
- Farnaz Barneh
- Department of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Drug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Mehdi Mirzaie
- Department of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Payman Nickchi
- Drug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.,Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, Canada
| | - Tuan Zea Tan
- Cancer Science Institute of Singapore, National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore, Translational Centre for Development and Research, National University Health System, MD11, #03-10, 10 Medical Drive, Singapore 117597, Singapore
| | - Jean Paul Thiery
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore.,Institut Gustave Roussy, Inserm Unit 1186 Comprehensive Cancer Center, Villejuif, France.,CNRS UMR 7057 Matter and Complex Systems, University Paris Denis Diderot, Paris, France
| | - Mehran Piran
- Drug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Mona Salimi
- Department of Physiology and Pharmacology, Pasteur Institute of Iran, Tehran, Iran
| | - Fatemeh Goshadrou
- Department of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amir R Aref
- Department of Medical Oncology, Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, Harvard Medical School, Boston 02215, USA
| | - Mohieddin Jafari
- Drug Design and Bioinformatics Unit, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
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13
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Li X, Cooper NGF, O'Toole TE, Rouchka EC. Choice of library size normalization and statistical methods for differential gene expression analysis in balanced two-group comparisons for RNA-seq studies. BMC Genomics 2020; 21:75. [PMID: 31992223 PMCID: PMC6986029 DOI: 10.1186/s12864-020-6502-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 01/16/2020] [Indexed: 12/20/2022] Open
Abstract
Background High-throughput RNA sequencing (RNA-seq) has evolved as an important analytical tool in molecular biology. Although the utility and importance of this technique have grown, uncertainties regarding the proper analysis of RNA-seq data remain. Of primary concern, there is no consensus regarding which normalization and statistical methods are the most appropriate for analyzing this data. The lack of standardized analytical methods leads to uncertainties in data interpretation and study reproducibility, especially with studies reporting high false discovery rates. In this study, we compared a recently developed normalization method, UQ-pgQ2, with three of the most frequently used alternatives including RLE (relative log estimate), TMM (Trimmed-mean M values) and UQ (upper quartile normalization) in the analysis of RNA-seq data. We evaluated the performance of these methods for gene-level differential expression analysis by considering the factors, including: 1) normalization combined with the choice of a Wald test from DESeq2 and an exact test/QL (Quasi-likelihood) F-Test from edgeR; 2) sample sizes in two balanced two-group comparisons; and 3) sequencing read depths. Results Using the MAQC RNA-seq datasets with small sample replicates, we found that UQ-pgQ2 normalization combined with an exact test can achieve better performance in term of power and specificity in differential gene expression analysis. However, using an intra-group analysis of false positives from real and simulated data, we found that a Wald test performs better than an exact test when the number of sample replicates is large and that a QL F-test performs the best given sample sizes of 5, 10 and 15 for any normalization. The RLE, TMM and UQ methods performed similarly given a desired sample size. Conclusion We found the UQ-pgQ2 method combined with an exact test/QL F-test is the best choice in order to control false positives when the sample size is small. When the sample size is large, UQ-pgQ2 with a QL F-test is a better choice for the type I error control in an intra-group analysis. We observed read depths have a minimal impact for differential gene expression analysis based on the simulated data.
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Affiliation(s)
- Xiaohong Li
- Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, KY, USA.
| | - Nigel G F Cooper
- Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, KY, USA
| | | | - Eric C Rouchka
- Department of Computer Science and Engineering, University of Louisville, Louisville, KY, USA
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14
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Thiemeyer H, Taher L, Schille JT, Harder L, Hungerbuehler SO, Mischke R, Hewicker-Trautwein M, Kiełbowicz Z, Brenig B, Schütz E, Beck J, Murua Escobar H, Nolte I. Suitability of ultrasound-guided fine-needle aspiration biopsy for transcriptome sequencing of the canine prostate. Sci Rep 2019; 9:13216. [PMID: 31519932 PMCID: PMC6744464 DOI: 10.1038/s41598-019-49271-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 08/15/2019] [Indexed: 02/06/2023] Open
Abstract
Ultrasound-guided fine-needle aspiration (US-FNA) biopsy is a widely used minimally invasive sampling procedure for cytological diagnosis. This study investigates the feasibility of using US-FNA samples for both cytological diagnosis and whole transcriptome RNA-sequencing analysis (RNA-Seq), with the ultimate aim of improving canine prostate cancer management. The feasibility of the US-FNA procedure was evaluated intra vitam on 43 dogs. Additionally, aspirates from 31 euthanised dogs were collected for standardising the procedure. Each aspirate was separated into two subsamples: for cytology and RNA extraction. Additional prostate tissue samples served as control for RNA quantity and quality evaluation, and differential expression analysis. The US-FNA sampling procedure was feasible in 95% of dogs. RNA isolation of US-FNA samples was successfully performed using phenol-chloroform extraction. The extracted RNA of 56% of a subset of US-FNA samples met the quality requirements for RNA-Seq. Expression analysis revealed that only 153 genes were exclusively differentially expressed between non-malignant US-FNAs and tissues. Moreover, only 36 differentially expressed genes were associated with the US-FNA sampling technique and unrelated to the diagnosis. Furthermore, the gene expression profiles clearly distinguished between non-malignant and malignant samples. This proves US-FNA to be useful for molecular profiling.
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Affiliation(s)
- H Thiemeyer
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
- Department of Haematology/Oncology/Palliative Care, Rostock University Medical Centre, Rostock, Germany
| | - L Taher
- Division of Bioinformatics, Department of Biology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - J T Schille
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
- Department of Haematology/Oncology/Palliative Care, Rostock University Medical Centre, Rostock, Germany
| | - L Harder
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
| | - S O Hungerbuehler
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
| | - R Mischke
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
| | - M Hewicker-Trautwein
- Institute of Pathology, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
| | - Z Kiełbowicz
- Department and Clinic of Veterinary Surgery, Faculty of Veterinary Medicine, Wroclaw University of Environmental and Life Sciences, Wrocław, Poland
| | - B Brenig
- University of Göttingen, Institute of Veterinary Medicine, Göttingen, Germany
| | - E Schütz
- Chronix Biomedical, Göttingen, Germany
| | - J Beck
- Chronix Biomedical, Göttingen, Germany
| | - H Murua Escobar
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany
- Department of Haematology/Oncology/Palliative Care, Rostock University Medical Centre, Rostock, Germany
| | - I Nolte
- Small Animal Clinic, University of Veterinary Medicine Hannover, Foundation, Hannover, Germany.
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15
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Mir DA, Balamurugan K. Global Proteomic Response of Caenorhabditis elegans Against PemK Sa Toxin. Front Cell Infect Microbiol 2019; 9:172. [PMID: 31214513 PMCID: PMC6555269 DOI: 10.3389/fcimb.2019.00172] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 05/08/2019] [Indexed: 12/13/2022] Open
Abstract
Bacterial exotoxins are major causative agents that infect by promoting cell and tissue damages through disabling the invading host immune system. However, the mode of action by which toxins modulate host immune system and lead cell death is still not completely understood. The nematode, Caenorhabditis elegans has been used as an attractive model host for toxicological studies. In this regard, the present study was undertaken to assess the impact of Staphylococcus aureus toxin (PemK) on the host C. elegans through global proteomics approach. Our proteomic data obtained through LC-MS/MS, subsequent bioinformatics and biochemical analyses revealed that in response to PemKSa a total of 601 proteins of C. elegans were differentially regulated in response to PemKSa. The identified proteins were found to mainly participate in ATP generation, protein synthesis, lipid synthesis, cytoskeleton, heat shock proteins, innate immune defense, stress response, neuron degeneration, and muscle assembly. Current findings suggested that involvement of several regulatory proteins that appear to play a role in various molecular functions in combating PemKSa toxin-mediated microbial pathogenicity and/or host C. elegans immunity modulation. The results provided a preliminary view of the physiological and molecular response of a host toward a toxin and provided insight into highly complex host-toxin interactions.
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16
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Mir DA, Balamurugan K. A proteomic analysis of Caenorhabditis elegans mitochondria during bacterial infection. Mitochondrion 2019; 48:37-50. [PMID: 30926536 DOI: 10.1016/j.mito.2019.03.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 01/13/2019] [Accepted: 03/12/2019] [Indexed: 12/11/2022]
Abstract
Mitochondria are involved in a variety of cellular metabolic processes and their functions are regulated by intrinsic and extrinsic stimuli. Recent studies have revealed functional diversity and importance of mitochondria in many cellular processes, including the innate immune response. This study evaluated the specific response and proteomic changes in host Caenorhabditis elegans mitochondria during Pseudomonas aeruginosa PAO1 infection. We performed an inclusive approach to determine the C. elegans mitochondria proteome. The protein fractions of mitochondria were analysed by tandem LC-MS/MS, 129 differentially regulated proteins were identified, indicating an involvement of various mitochondrial processes. The several known components of the oxidative phosphorylation (OXPHOS) machinery, the tricarboxylic acid (TCA) cycle, mitochondrial unfolded protein response (UPRmt) and stable mitochondria-encoded proteins were found to be differentially expressed. Our results in-depth provide new horizons for mitochondria-associated protein functions and the classification of mitochondrial diseases during host-pathogen interaction.
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Affiliation(s)
- Dilawar Ahmad Mir
- Department of Biotechnology, Alagappa University, Karaikudi, Tamil Nadu 630003, India
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17
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Saleembhasha A, Mishra S. Novel molecules lncRNAs, tRFs and circRNAs deciphered from next-generation sequencing/RNA sequencing: computational databases and tools. Brief Funct Genomics 2019. [PMID: 28637169 DOI: 10.1093/bfgp/elx013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Powerful next-generation sequencing (NGS) technologies, more specifically RNA sequencing (RNA-seq), have been pivotal toward the detection and analysis and hypotheses generation of novel biomolecules, long noncoding RNAs (lncRNAs), tRNA-derived fragments (tRFs) and circular RNAs (circRNAs). Experimental validation of the occurrence of these biomolecules inside the cell has been reported. Their differential expression and functionally important role in several cancers types as well as other diseases such as Alzheimer's and cardiovascular diseases have garnered interest toward further studies in this research arena. In this review, starting from a brief relevant introduction to NGS and RNA-seq and the expression and role of lncRNAs, tRFs and circRNAs in cancer, we have comprehensively analyzed the current landscape of databases developed and computational software used for analyses and visualization for this emerging and highly interesting field of these novel biomolecules. Our review will help the end users and research investigators gain information on the existing databases and tools as well as an understanding of the specific features which these offer. This will be useful for the researchers in their proper usage thereby guiding them toward novel hypotheses generation and saving time and costs involved in extensive experimental processes in these three different novel functional RNAs.
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18
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Wang T, Li B, Nelson CE, Nabavi S. Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data. BMC Bioinformatics 2019; 20:40. [PMID: 30658573 PMCID: PMC6339299 DOI: 10.1186/s12859-019-2599-6] [Citation(s) in RCA: 147] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 01/03/2019] [Indexed: 12/16/2022] Open
Abstract
Background The analysis of single-cell RNA sequencing (scRNAseq) data plays an important role in understanding the intrinsic and extrinsic cellular processes in biological and biomedical research. One significant effort in this area is the detection of differentially expressed (DE) genes. scRNAseq data, however, are highly heterogeneous and have a large number of zero counts, which introduces challenges in detecting DE genes. Addressing these challenges requires employing new approaches beyond the conventional ones, which are based on a nonzero difference in average expression. Several methods have been developed for differential gene expression analysis of scRNAseq data. To provide guidance on choosing an appropriate tool or developing a new one, it is necessary to evaluate and compare the performance of differential gene expression analysis methods for scRNAseq data. Results In this study, we conducted a comprehensive evaluation of the performance of eleven differential gene expression analysis software tools, which are designed for scRNAseq data or can be applied to them. We used simulated and real data to evaluate the accuracy and precision of detection. Using simulated data, we investigated the effect of sample size on the detection accuracy of the tools. Using real data, we examined the agreement among the tools in identifying DE genes, the run time of the tools, and the biological relevance of the detected DE genes. Conclusions In general, agreement among the tools in calling DE genes is not high. There is a trade-off between true-positive rates and the precision of calling DE genes. Methods with higher true positive rates tend to show low precision due to their introducing false positives, whereas methods with high precision show low true positive rates due to identifying few DE genes. We observed that current methods designed for scRNAseq data do not tend to show better performance compared to methods designed for bulk RNAseq data. Data multimodality and abundance of zero read counts are the main characteristics of scRNAseq data, which play important roles in the performance of differential gene expression analysis methods and need to be considered in terms of the development of new methods. Electronic supplementary material The online version of this article (10.1186/s12859-019-2599-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tianyu Wang
- Computer Science and Engineering Department, University of Connecticut, Storrs, CT, USA
| | - Boyang Li
- Department of Molecular & Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Craig E Nelson
- Department of Molecular & Cell Biology, The Institute for Systems Genomics, CLAS, University of Connecticut, Storrs, CT, USA
| | - Sheida Nabavi
- Computer Science and Engineering Department, The Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA.
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19
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Hassan H, Shanak S. GOTrapper: a tool to navigate through branches of gene ontology hierarchy. BMC Bioinformatics 2019; 20:20. [PMID: 30634902 PMCID: PMC6330489 DOI: 10.1186/s12859-018-2581-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2018] [Accepted: 12/11/2018] [Indexed: 11/14/2022] Open
Abstract
Background Gene Ontology (GO) is a useful resource of controlled vocabulary that provides information about annotated genes. Based on such resource, finding the biological function is useful for biologists to come up with different hypotheses and help further investigations of an experiment. The biological function for desired genes and gene associations is picked up from a randomly chosen list or through the analysis of differential gene expression. Many tools have been developed to utilize GO knowledge and cluster genes according to relevant biological functions. The retrieved GO terms include both specific and non-specific terms, which is not user-friendly in terms of data analysis. Thus one approach is still missing, which allows navigating through different levels of GO hierarchy manually. Result We developed a tool, GOTrapper, which allows moving up or down to the very bottom of the GO hierarchy. This is performed manually by the user, based on an assigned threshold. This tool grabs the shared terms by the desired set of input genes of Homo sapiens. Here, two inputs are possible. “Within” is to find associated terms within one gene list, and “Between” is to find associated terms between two lists. The tool also provides the option to return the terms with the pre-selected evidence codes. Conclusion GOTrapper is a user-friendly Java tool that helps the user move up and down the ontology tree, which leads to new hypotheses and devising new association of the input genes. It also allows returning terms of associated genes based on selected evidence codes. This tool can be accessed and is freely available at https://github.com/BioGeneTools/GOTrapper. Electronic supplementary material The online version of this article (10.1186/s12859-018-2581-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hezha Hassan
- Public Health Laboratory, Sulaimaniyah, Kurdistan Region, 46001, Iraq. .,Genome Informatics, Faculty of Technology and Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.
| | - Siba Shanak
- Faculty of Sciences, Arab American University-Palestine, P.O Box 240, Jenin, Palestine
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20
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Systematic analysis reveals molecular characteristics of ERG-negative prostate cancer. Sci Rep 2018; 8:12868. [PMID: 30150711 PMCID: PMC6110738 DOI: 10.1038/s41598-018-30325-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Accepted: 07/27/2018] [Indexed: 01/18/2023] Open
Abstract
The TMPRSS2:ERG gene fusion is the most prevalent early driver gene activation in prostate cancers of European ancestry, while the fusion frequency is much lower in Africans and Asians. The genomic characteristics and mechanisms for patients lacking ERG fusion are still unclear. In this study, we systematically compared the characteristics of gene fusions, somatic mutations, copy number alterations and gene expression signatures between 201 ERG fusion positive and 296 ERG fusion negative prostate cancer samples. Both common and group-specific genomic alterations were observed, suggesting shared and different mechanisms of carcinogenesis in prostate cancer samples with or without ERG fusion. The genomic alteration patterns detected in ERG-negative group showed similarities with 77.5% of tumor samples of African American patients. These results emphasize that genomic and gene expression features of the ERG-negative group may provide a reference for populations with lower ERG fusion frequency. While the overall expression patterns were comparable between ERG-negative and ERG-positive tumors, we found that genomic alterations could affect the same pathway through distinct genes in the same pathway in both groups of tumor types. Altogether, the genomic and molecular characteristics revealed in our study may provide new opportunities for molecular stratification of ERG-negative prostate cancers.
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21
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Zhang Q, Li J, Wang D, Wang Y. Finding disagreement pathway signatures and constructing an ensemble model for cancer classification. Sci Rep 2017; 7:10044. [PMID: 28855608 PMCID: PMC5577098 DOI: 10.1038/s41598-017-10258-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Accepted: 08/07/2017] [Indexed: 12/02/2022] Open
Abstract
Cancer classification based on molecular level is a relatively routine research procedure with advances in high-throughput molecular profiling techniques. However, the number of genes typically far exceeds the number of the sample size in gene expression studies. The existing gene selection methods are almost based on statistics and machine learning, overlooking relevant biological principles or knowledge while working with biological data. Here, we propose a robust ensemble learning paradigm, which incorporates multiple pathways information, to predict cancer classification. We compare the proposed method with other methods, such as Elastic SCAD and PPDMF, and estimate the classification performance. The results show that the proposed method has the higher performances on most metrics and robust performance. We further investigate the biological mechanism of the ensemble feature genes. The results demonstrate that the ensemble feature genes are associated with drug targets/clinically-relevant cancer. In addition, some core biological pathways and biological process underlying clinically-relevant phenotypes are identified by function annotation. Overall, our research can provide a new perspective for the further study of molecular activities and manifestations of cancer.
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Affiliation(s)
- Qiaosheng Zhang
- Harbin Institute of Technology, School of Computer Science and Technology, Harbin, 150001, P.R. China.,Heilongjiang Bayi Agricultural University, College of Science, Daqing, 163319, P.R. China
| | - Jie Li
- Harbin Institute of Technology, School of Computer Science and Technology, Harbin, 150001, P.R. China.
| | - Dong Wang
- Harbin Institute of Technology, School of Computer Science and Technology, Harbin, 150001, P.R. China
| | - Yadong Wang
- Harbin Institute of Technology, School of Computer Science and Technology, Harbin, 150001, P.R. China
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22
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Chen Z, Gerke T, Bird V, Prosperi M. Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review. Biomed Hub 2017; 2:1-15. [PMID: 31988908 PMCID: PMC6945900 DOI: 10.1159/000472146] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 03/07/2017] [Indexed: 12/12/2022] Open
Abstract
Objectives The aim of the study is to review biotechnology advances in gene expression profiling on prostate cancer (PCa), focusing on experimental platform development and gene discovery, in relation to different study designs and outcomes in order to understand how they can be exploited to improve PCa diagnosis and clinical management. Methods We conducted a systematic literature review on gene expression profiling studies through PubMed/MEDLINE and Web of Science between 2000 and 2016. Tissue biopsy and clinical gene profiling studies with different outcomes (e.g., recurrence, survival) were included. Results Over 3,000 papers were screened and 137 full-text articles were selected. In terms of technology used, microarray is still the most popular technique, increasing from 50 to 70% between 2010 and 2015, but there has been a rise in the number of studies using RNA sequencing (13% in 2015). Sample sizes have increased, as well as the number of genes that can be screened all at once, but we have also observed more focused targeting in more recent studies. Qualitative analysis on the specific genes found associated with PCa risk or clinical outcomes revealed a large variety of gene candidates, with a few consistent cross-studies. Conclusions The last 15 years of research in gene expression in PCa have brought a large volume of data and information that has been decoded only in part, but advancements in high-throughput sequencing technology are increasing the amount of data that can be generated. The variety of findings warrants the execution of both validation studies and meta-analyses. Genetic biomarkers have tremendous potential for early diagnosis of PCa and, if coupled with other diagnostics (e.g., imaging), can effectively be used to concretize less-invasive, personalized prediction of PCa risk and progression.
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Affiliation(s)
- Zhaoyi Chen
- Department of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA
| | | | - Victoria Bird
- Department of Urology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Mattia Prosperi
- Department of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA
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23
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Zeng JH, Liang L, He RQ, Tang RX, Cai XY, Chen JQ, Luo DZ, Chen G. Comprehensive investigation of a novel differentially expressed lncRNA expression profile signature to assess the survival of patients with colorectal adenocarcinoma. Oncotarget 2017; 8:16811-16828. [PMID: 28187432 PMCID: PMC5370003 DOI: 10.18632/oncotarget.15161] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 01/24/2017] [Indexed: 02/06/2023] Open
Abstract
Growing evidence has shown that long non-coding RNAs (lncRNAs) can serve as prospective markers for survival in patients with colorectal adenocarcinoma. However, most studies have explored a limited number of lncRNAs in a small number of cases. The objective of this study is to identify a panel of lncRNA signature that could evaluate the prognosis in colorectal adenocarcinoma based on the data from The Cancer Genome Atlas (TCGA). Altogether, 371 colon adenocarcinoma (COAD) patients with complete clinical data were included in our study as the test cohort. A total of 578 differentially expressed lncRNAs (DELs) were observed, among which 20 lncRNAs closely related to overall survival (OS) in COAD patients were identified using a Cox proportional regression model. A risk score formula was developed to assess the prognostic value of the lncRNA signature in COAD with four lncRNAs (LINC01555, RP11-610P16.1, RP11-108K3.1 and LINC01207), which were identified to possess the most remarkable correlation with OS in COAD patients. COAD patients with a high-risk score had poorer OS than those with a low-risk score. The multivariate Cox regression analyses confirmed that the four-lncRNA signature could function as an independent prognostic indicator for COAD patients, which was largely mirrored in the validating cohort with rectal adenocarcinoma (READ) containing 158 cases. In addition, the correlative genes of LINC01555 and LINC01207 were enriched in the cAMP signaling and mucin type O-Glycan biosynthesis pathways. With further validation in the future, our study indicates that the four-lncRNA signature could serve as an independent biomarker for survival of colorectal adenocarcinoma.
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Affiliation(s)
- Jiang-Hui Zeng
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Liang Liang
- Department of General Surgery, First Affiliated Hospital of Guangxi Medical University (West Branch), Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Rong-Quan He
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Rui-Xue Tang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Xiao-Yong Cai
- Department of General Surgery, First Affiliated Hospital of Guangxi Medical University (West Branch), Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Jun-Qiang Chen
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Dian-Zhong Luo
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, P. R. China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, P. R. China
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Sharma S, Zapatero-Rodríguez J, O'Kennedy R. Prostate cancer diagnostics: Clinical challenges and the ongoing need for disruptive and effective diagnostic tools. Biotechnol Adv 2017; 35:135-149. [DOI: 10.1016/j.biotechadv.2016.11.009] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Revised: 11/20/2016] [Accepted: 11/28/2016] [Indexed: 02/06/2023]
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Wang K, Vijay V, Fuscoe JC. Stably Expressed Genes Involved in Basic Cellular Functions. PLoS One 2017; 12:e0170813. [PMID: 28125669 PMCID: PMC5268456 DOI: 10.1371/journal.pone.0170813] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 01/11/2017] [Indexed: 11/19/2022] Open
Abstract
Stably Expressed Genes (SEGs) whose expression varies within a narrow range may be involved in core cellular processes necessary for basic functions. To identify such genes, we re-analyzed existing RNA-Seq gene expression profiles across 11 organs at 4 developmental stages (from immature to old age) in both sexes of F344 rats (n = 4/group; 320 samples). Expression changes (calculated as the maximum expression / minimum expression for each gene) of >19000 genes across organs, ages, and sexes ranged from 2.35 to >109-fold, with a median of 165-fold. The expression of 278 SEGs was found to vary ≤4-fold and these genes were significantly involved in protein catabolism (proteasome and ubiquitination), RNA transport, protein processing, and the spliceosome. Such stability of expression was further validated in human samples where the expression variability of the homologous human SEGs was significantly lower than that of other genes in the human genome. It was also found that the homologous human SEGs were generally less subject to non-synonymous mutation than other genes, as would be expected of stably expressed genes. We also found that knockout of SEG homologs in mouse models was more likely to cause complete preweaning lethality than non-SEG homologs, corroborating the fundamental roles played by SEGs in biological development. Such stably expressed genes and pathways across life-stages suggest that tight control of these processes is important in basic cellular functions and that perturbation by endogenous (e.g., genetics) or exogenous agents (e.g., drugs, environmental factors) may cause serious adverse effects.
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Affiliation(s)
- Kejian Wang
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, United States of America
| | - Vikrant Vijay
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, United States of America
| | - James C. Fuscoe
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, United States of America
- * E-mail:
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Danaee P, Ghaeini R, Hendrix DA. A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2017; 22:219-229. [PMID: 27896977 PMCID: PMC5177447 DOI: 10.1142/9789813207813_0022] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Cancer detection from gene expression data continues to pose a challenge due to the high dimensionality and complexity of these data. After decades of research there is still uncertainty in the clinical diagnosis of cancer and the identification of tumor-specific markers. Here we present a deep learning approach to cancer detection, and to the identification of genes critical for the diagnosis of breast cancer. First, we used Stacked Denoising Autoencoder (SDAE) to deeply extract functional features from high dimensional gene expression profiles. Next, we evaluated the performance of the extracted representation through supervised classification models to verify the usefulness of the new features in cancer detection. Lastly, we identified a set of highly interactive genes by analyzing the SDAE connectivity matrices. Our results and analysis illustrate that these highly interactive genes could be useful cancer biomarkers for the detection of breast cancer that deserve further studies.
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Affiliation(s)
- Padideh Danaee
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97330, USA,
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Myers JS, von Lersner AK, Sang QXA. Proteomic Upregulation of Fatty Acid Synthase and Fatty Acid Binding Protein 5 and Identification of Cancer- and Race-Specific Pathway Associations in Human Prostate Cancer Tissues. J Cancer 2016; 7:1452-64. [PMID: 27471561 PMCID: PMC4964129 DOI: 10.7150/jca.15860] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 05/23/2016] [Indexed: 12/25/2022] Open
Abstract
Protein profiling studies of prostate cancer have been widely used to characterize molecular differences between diseased and non-diseased tissues. When combined with pathway analysis, profiling approaches are able to identify molecular mechanisms of prostate cancer, group patients by cancer subtype, and predict prognosis. This strategy can also be implemented to study prostate cancer in very specific populations, such as African Americans who have higher rates of prostate cancer incidence and mortality than other racial groups in the United States. In this study, age-, stage-, and Gleason score-matched prostate tumor specimen from African American and Caucasian American men, along with non-malignant adjacent prostate tissue from these same patients, were compared. Protein expression changes and altered pathway associations were identified in prostate cancer generally and in African American prostate cancer specifically. In comparing tumor to non-malignant samples, 45 proteins were significantly cancer-associated and 3 proteins were significantly downregulated in tumor samples. Notably, fatty acid synthase (FASN) and epidermal fatty acid-binding protein (FABP5) were upregulated in human prostate cancer tissues, consistent with their known functions in prostate cancer progression. Aldehyde dehydrogenase family 1 member A3 (ALDH1A3) was also upregulated in tumor samples. The Metastasis Associated Protein 3 (MTA3) pathway was significantly enriched in tumor samples compared to non-malignant samples. While the current experiment was unable to detect statistically significant differences in protein expression between African American and Caucasian American samples, differences in overrepresentation and pathway enrichment were found. Structural components (Cytoskeletal Proteins and Extracellular Matrix Protein protein classes, and Biological Adhesion Gene Ontology (GO) annotation) were overrepresented in African American but not Caucasian American tumors. Additionally, 5 pathways were enriched in African American prostate tumors: the Small Cell Lung Cancer, Platelet-Amyloid Precursor Protein, Agrin, Neuroactive Ligand-Receptor Interaction, and Intrinsic pathways. The protein components of these pathways were either basement membrane proteins or coagulation proteins.
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Affiliation(s)
- Jennifer S Myers
- 1. Department of Chemistry & Biochemistry, Florida State University, Tallahassee, FL, USA
| | - Ariana K von Lersner
- 1. Department of Chemistry & Biochemistry, Florida State University, Tallahassee, FL, USA
| | - Qing-Xiang Amy Sang
- 1. Department of Chemistry & Biochemistry, Florida State University, Tallahassee, FL, USA.; 2. Institute of Molecular Biophysics, Florida State University, Tallahassee, FL, USA
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