The role of ADAM-like decysin 1 in non-eosinophilic chronic rhinosinusitis with nasal polyps

Sugimoto, Naoki; Kasai, Yoshiyuki; Asaka, Daiya; Mitsuyoshi, Ryoto; Tsurumoto, Tadao; Takaishi, Shinya; Omae, Sachiko; Kojima, Hiromi; Tanaka, Yasuhiro; Haruna, Shinichi

doi:10.1080/00016489.2018.1481296

Cited by 5 publications

(7 citation statements)

References 18 publications

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“…In both studies, increased level of ADAMDEC1 was demonstrated to play a crucial role in tumour division and progression. However, it must be noted that, increased levels of ADAMDEC1 have also been shown to be associated with the inflammation in Crohn’s disease [71] and has also been reported to be highly expressed in Chronic rhinosinusitis with nasal polyps [74].…”

Section: Discussionmentioning

confidence: 99%

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel

et al. 2019

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Background: One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current populationbased screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). Methods: A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. Results: Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. Conclusion: MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

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Section: Discussionmentioning

confidence: 99%

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel

et al. 2019

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“…Significant heterogeneity regarding laboratory techniques was also noted. For most researchers, the method of choice was immunohistochemistry alone or additional to other techniques (22,26,31,33,34,36,38,39,(41)(42)(43)49,51,52,57,62) . Different methods have been applied for quantifying MMP labelling index.…”

Section: Study Characteristicsmentioning

confidence: 99%

“…Chain Reaction (PCR) (26,41,46,49,54,(56)(57)(58) and Western Blot analysis (13,29,46,49,53,54,57,59,62) were also selected by several researchers, while immunofluorescence (27,34,37,57) , Northern blot analysis (23) and Luminex (60,61) were used in a minority of studies. It is however of note that in studies where multiple methods were applied (quantitative) m-RNA and protein levels were reported to be in consistency with each other and with semi-quantitative or qualitative immunohistochemical results (26,34,41,49,57,62) .…”

Section: Studymentioning

confidence: 99%

Matrix metalloproteinases and chronic rhinosinusitis with nasal polyposis. Unravelling a puzzle through a systematic review

Lygeros

Danielides

Grafanaki

et al. 2021

Rhin

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BACKGROUND: The expression of metalloproteinases (MMPs) in chronic rhinosinusitis with nasal polyposis (CRSwNP) was reviewed in order to investigate their possible use as therapeutical targets and/or biomarkers. METHODOLOGY: The differences between CRSwNP and normal controls or CRS without NP, as well as the effects of various treatments on MMPs, tissue inhibitors of MMPs (TIMPs) and MMP/TIMP ratios were considered as primary outcomes. Additional factors reported to affect MMP expression levels were noted as secondary outcomes. Data regarding inflammatory subtypes, patients’ clinical characteristics, controls, laboratory method(s) and origin of samples were also pooled. Studies on 10 or fewer patients or on specimens other than nasal and serum were excluded. RESULTS: Forty-three studies were included. Tissue sample origin, allergic rhinitis, smoking, infection, medication intake and primary or recurrent disease should be considered as confounding factors for MMP levels. MMP-1 and -7 were consistently found to be significantly higher in CRSwNP patients than controls. CRSwNP endotypes with distinctly different inflammation patterns seem to present similar MMP-related remodelling patterns. CONCLUSIONS: The existing literature has revealed several population and methodology related confounding factors and remains inconclusive regarding the roles of MMPs in CRSwNP pathophysiology and their possible clinical usefulness as biomarkers and therapeutical targets.

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“…MMP9 [217], S100A12 [218], CBS (cystathionine beta-synthase) [219], SOCS3 [220], IGFBP2 [221], MMP8 [222], OSM (oncostatin M) [223], TLR5 [224], S100A8 [225], PDE6H [226], CEBPB (CCAAT enhancer binding protein beta) [227], PLAU (plasminogen activator, urokinase) [228] [243], PFKFB3 [244], NQO2 [245], CTSD (cathepsin D) [246], SERPINB1 [247], ADAMTS1 [248], SOX5 [249], FASLG (Fas ligand) [250] [267], LCN2 [268], ADAMDEC1 [269], IL1RN [270], TLR4 [271] and TXNIP (thioredoxin interacting protein) [272] as biomarkers of sinusitis. MMP9 [262], IGF2 [273], SOCS3 [274], MMP8 [265], OSM (oncostatin M) [266], PLAU (plasminogen activator, urokinase) [275], ADAMDEC1 [269], IL1RN [270], TLR4 [271], CD80 [276] and TXNIP (thioredoxin interacting protein) [272] make great contributions to the progression of nasal polyps. MMP9 [277], S100A12 [278], IGF2 [279], GPR84 [280], SOCS3 [281], ANXA3 [282], IGFBP2 [283], NOS1AP [284], G0S2 [285], HP (haptoglobin) [286], MMP8 [287], SLC6A19 [288], OSM (oncostatin M)…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Genes and Underlying Mechanisms in Cystic Fibrosis and its Associated Complications Based on Bioinformatics Analysis of Next Generation Sequencing Data Analysis

Vastrad¹,

Vastrad²

2022

Preprint

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Cystic fibrosis (CF) is one of the inherited autosomal recessive disorders with very complicated pathogenesis. Identifying the molecular signatures and specific biomarkers of CF might provide novel clues for CF and and CF associated complications prognosis and targeted therapy. Based on the nexgeneration sequencing (NGS) dataset GSE136371 downloaded from the Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) between CF samples and normal controls were identified by using DESeq2 bioconductor package of R software. Gene ontology (GO) and REACTOME pathway enrichment analyses were applied for the DEGs. Then protein-protein interaction (PPI) network of these DEGs was visualized by Cytoscape with IMEx interactome database. The most significant module from the PPI network was selected for GO and pathway enrichment analysis. Subsequently, a miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed to identify hub genes, miRNAs and TFs. Finally, receiver operating characteristic curve (ROC) analysis was established to validate these hub genes. Total of 917 DEGs were identified between CF and normal control samples in GSE136371 dataset, including 479 up regulated and 438 down regulated genes. The most enriched DEGs in GO and pathway enrichment analysis were mainly associated with response to stimulus, regulation of cellular process, Neutrophil degranulation and rRNA processing. PPI network, module analysis, miRNA-hub gene regulatory network and TF-hub gene regulatory network predicted ten hub genes (FN1, UBE2D1, SRPK1, MAPK14, CEBPB, HSP90AB1, HSPA8, XRCC6, NCL and PARP1). In conclusion, the DEGs, relative pathways and hub genes identified in the present study might aid in understanding of the molecular mechanisms underlying CF and CF associated complications progression and provide potential molecular targets and biomarkers for CF and CF associated complications.

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The role of ADAM-like decysin 1 in non-eosinophilic chronic rhinosinusitis with nasal polyps

Abstract: This study demonstrates that ADAMDEC1 is involved in the pathogenesis of NECRSwNP, and also bacterial endotoxin signalling in macrophages; however, the underlying mechanism remains to be elucidated.

Cited by 5 publications

References 18 publications

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel

Matrix metalloproteinases and chronic rhinosinusitis with nasal polyposis. Unravelling a puzzle through a systematic review

Identification of Key Genes and Underlying Mechanisms in Cystic Fibrosis and its Associated Complications Based on Bioinformatics Analysis of Next Generation Sequencing Data Analysis

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