scholarly journals Evidence of a noncoding transcript of the RIPK2 gene overexpressed in head and neck tumor

2018 ◽  
Author(s):  
Ulises M. M. Villagra ◽  
Bianca R. da Cunha ◽  
Giovana M. Polachini ◽  
Tiago Henrique ◽  
Carlos H. T. P. da Silva ◽  
...  
Keyword(s):  
Cell Lines ◽  
Noncoding Rna ◽  
Kinase Domain ◽  
Transcriptional Level ◽  
Biological Processes ◽  
Nf Kappa B ◽  
Tissue Samples ◽  
Short Transcript ◽  
Stress Signals ◽  
Receptor Interacting Proteins

ABSTRACTReceptor-interacting proteins are a family of serine/threonine kinases, which integrate extra and intracellular stress signals caused by different factors, including infections, inflammation and DNA damage. Receptor-interacting serine/threonine-protein kinase 2 (RIP-2) is a member of this family and an important component of the nuclear factor NF-kappa-B signaling pathway. The corresponding human gene RIPK2 generates two transcripts by alternative splicing, the full-length and a short transcript. The short transcript has a truncated 5’ sequence, which results in a predicted isoform with a partial kinase domain but able to transduce signals through its caspase recruitment domain. In this study, the expression of RIPK2 was investigated in human tissue samples and, in order to determine if both transcripts are similarly regulated at the transcriptional level, cancer cell lines were submitted to temperature and acid stresses. We observed that both transcripts are expressed in all tissues analyzed, with higher expression of the short one in tumor samples, and they are differentially regulated following temperature stress. Despite transcription, no corresponding protein for the short transcript was detected in tissues and cell lines analyzed. We propose that the shorter transcript is a noncoding RNA and that its presence in the cell may play regulatory roles and affect inflammation and other biological processes related to the kinase activity of RIP-2.

scholarly journals Alterations of RNA splicing patterns in esophagus squamous cell carcinoma

2021 ◽  
Author(s):  
Jiyu Ding ◽  
Chunquan Li ◽  
Yinwei Cheng ◽  
Zepeng Du ◽  
Qiuyu Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cell Lines ◽  
Squamous Cell ◽  
Single Gene ◽  
Splicing Factor ◽  
Cell Junction ◽  
Biological Processes ◽  
Tissue Samples ◽  
And Migration

Abstract Alternative splicing (AS) is an important biological process for regulating the expression of various isoforms from a single gene and thus to promote proteome diversity. In this study, RNA-seq data from 15 pairs of matched esophageal squamous cell carcinoma (ESCC) and normal tissue samples as well as two cell lines were analyzed. AS events with significant differences were identified between ESCC and matched normal tissues, which were re-annotated to find protein coding genes or non-coding RNAs. A total of 45,439 AS events were found. Of these, 6,019 (13.25%) significant differentially AS events were identified. Exon skipping (SE) events occupied the largest proportion of abnormal splicing events. Fifteen differential splicing events with the same trends of ΔΨ values in ESCC tissues, as well in the two cell lines were found. Four pathways and 20 biological processes related to pro-metastasis cell junction and migration were significantly enriched for the differentially spliced genes. The upregulated splicing factor SF3B4, which regulates 92 gene splicing events, could be a potential prognostic factor of ESCC. Differentially spliced genes, including HNRNPC, VCL, ZNF207, KIAA1217, TPM1 and CALD1 are shown with a sashimi plot. These results suggest that cell junction- and migration-related biological processes are influenced by AS abnormalities, and aberrant splicing events can be affected by splicing factor expression changes. The involved splicing factor SF3B4 was found to be a survival-related gene in ESCC and is presumed to regulate AS in multiple cancers. In summary, we identified significant differentially expressed AS events which may be related to the development of ESCC.

scholarly journals Alterations of RNA Splicing Patterns in Esophagus Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Jiyu Ding ◽  
Chunquan Li ◽  
Yinwei Cheng ◽  
Zepeng Du ◽  
Qiuyu Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cell Lines ◽  
Squamous Cell ◽  
Rna Splicing ◽  
Single Gene ◽  
Cell Junction ◽  
Biological Processes ◽  
Tissue Samples ◽  
And Migration

Abstract Alternative splicing (AS) is an important biological process for regulating the expression of various isoforms from a single gene and thus to promote proteome diversity. In this study, RNA-seq data from 15 pairs of esophageal squamous cell carcinoma (ESCC) tissue samples and two cell lines were analyzed. AS events with significant differences between ESCC and matched normal tissues were re-annotated to find protein coding genes or non-coding RNAs. A total of 45,439 AS events was found. Of these, 6,019 (13.25%) significant differentially AS events were identified. Exon skipping (SE) events occupied the largest proportion of abnormal splicing events. Fifteen differential splicing events with the same trends of ΔΨ values in ESCC tissues and cell lines were found. Four pathways and 20 biological processes related to cell junction and migration were significantly enriched. The upregulated splicing factor SF3B4, which regulates 92 gene splicing events, could be a potential prognostic factor of ESCC. Sashimi plotting was applied to show the differentially-spliced genes, including HNRNPC, VCL, ZNF207, KIAA1217, TPM1 and CALD1. These results suggest that cell junction- and migration-related biological processes and KEGG pathways are affected by the AS abnormalities, and aberrant splicing events can be affected by changed expression of splicing factors. In summary, we identified significant differentially AS events which might be related to the development of ESCC.

scholarly journals Interplay of transcriptional signaling by progesterone, cyclic AMP, and inflammation in myometrial cells: implications for the control of human parturition

2019 ◽  
Vol 25 (7) ◽  
pp. 408-422 ◽  
Author(s):  
Zachary Stanfield ◽  
Peyvand Amini ◽  
Junye Wang ◽  
Lijuan Yi ◽  
Huiqing Tan ◽  
...  
Keyword(s):  
B Cell ◽  
Cell Line ◽  
Cell Lines ◽  
Interleukin 1 ◽  
Similarity Index ◽  
Cyclic Adenosine Monophosphate ◽  
Adenosine Monophosphate ◽  
Nf Kappa B ◽  
Tissue Samples ◽  
Network Analyses

Abstract Parturition involves cellular signaling changes driven by the complex interplay between progesterone (P4), inflammation, and the cyclic adenosine monophosphate (cAMP) pathway. To characterize this interplay, we performed comprehensive transcriptomic studies utilizing eight treatment combinations on myometrial cell lines and tissue samples from pregnant women. We performed genome-wide RNA-sequencing on the hTERT-HM${}^{A/B}$ cell line treated with all combinations of P4, forskolin (FSK) (induces cAMP), and interleukin-1$\beta$ (IL-1$\beta$). We then performed gene set enrichment and regulatory network analyses to identify pathways commonly, differentially, or synergistically regulated by these treatments. Finally, we used tissue similarity index (TSI) to characterize the correspondence between cell lines and tissue phenotypes. We observed that in addition to their individual anti-inflammatory effects, P4 and cAMP synergistically blocked specific inflammatory pathways/regulators including STAT3/6, CEBPA/B, and OCT1/7, but not NF$\kappa$B. TSI analysis indicated that FSK + P4- and IL-1$\beta$-treated cells exhibit transcriptional signatures highly similar to non-laboring and laboring term myometrium, respectively. Our results identify potential therapeutic targets to prevent preterm birth and show that the hTERT-HM${}^{A/B}$ cell line provides an accurate transcriptional model for term myometrial tissue.

scholarly journals Long Noncoding RNA NEAT1 Promotes Growth and Metastasis of Cholangiocarcinoma Cells

2018 ◽  
Vol 26 (6) ◽  
pp. 879-888 ◽  
Author(s):  
Cheng Zhang ◽  
Jing-Yi Li ◽  
Fu-Zhou Tian ◽  
Gang Zhao ◽  
Hai Hu ◽  
...  
Keyword(s):  
Cell Lines ◽  
Colony Formation ◽  
Noncoding Rna ◽  
Pcr Analysis ◽  
Tissue Samples ◽  
Nontumor Tissue ◽  
E Cadherin

Long noncoding RNAs (lncRNAs) are known to play important roles in cancers. However, little is known about lncRNAs in cholangiocarcinoma (CCA), a cholangiocyte malignancy with poor prognosis. We investigated the role of nuclear paraspeckle assembly transcript 1 (NEAT1) lncRNA in promoting CCA. qRT-PCR analysis of patient samples showed that NEAT1 expression was higher in CCA tumors than in matched adjacent nontumor tissue. NEAT1 levels were also higher in CCA cell lines than in a normal biliary epithelium cell line (HIBEpic). NEAT1 knockdown in CCA cell lines using shNEAT1 reduced cell proliferation and colony formation in CCK-8 and colony formation assays, respectively. CCA cells transfected with shNEAT1 also exhibited reduced metastasis and invasiveness in Transwell assays. NEAT1 knockdown cells produced smaller tumors, demonstrating that NEAT1 promotes tumor growth in vivo. Silencing of NEAT1 increased E-cadherin expression in vitro, and E-cadherin expression was inversely correlated with NEAT1 expression in CCA tissue samples. RIP and ChIP assays suggest that NEAT1 is recruited to the E-cadherin promoter by EZH2 (enhancer of zeste homolog 2), where it represses E-cadherin expression. These findings indicate that NEAT1 exerts oncogenic effects in CCA. We postulate that NEAT1 is a potentially useful diagnostic and therapeutic target for CCA.

scholarly journals Alterations of RNA splicing patterns in esophagus squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiyu Ding ◽  
Chunquan Li ◽  
Yinwei Cheng ◽  
Zepeng Du ◽  
Qiuyu Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cell Lines ◽  
Squamous Cell ◽  
Single Gene ◽  
Splicing Factor ◽  
Cell Junction ◽  
Biological Processes ◽  
Tissue Samples ◽  
And Migration

AbstractAlternative splicing (AS) is an important biological process for regulating the expression of various isoforms from a single gene and thus to promote proteome diversity. In this study, RNA-seq data from 15 pairs of matched esophageal squamous cell carcinoma (ESCC) and normal tissue samples as well as two cell lines were analyzed. AS events with significant differences were identified between ESCC and matched normal tissues, which were re-annotated to find protein coding genes or non-coding RNAs. A total of 45,439 AS events were found. Of these, 6019 (13.25%) significant differentially AS events were identified. Exon skipping (SE) events occupied the largest proportion of abnormal splicing events. Fifteen differential splicing events with the same trends of ΔΨ values in ESCC tissues, as well in the two cell lines were found. Four pathways and 20 biological processes related to pro-metastasis cell junction and migration were significantly enriched for the differentially spliced genes. The upregulated splicing factor SF3B4, which regulates 92 gene splicing events, could be a potential prognostic factor of ESCC. Differentially spliced genes, including HNRNPC, VCL, ZNF207, KIAA1217, TPM1 and CALD1 are shown with a sashimi plot. These results suggest that cell junction- and migration-related biological processes are influenced by AS abnormalities, and aberrant splicing events can be affected by splicing factor expression changes. The involved splicing factor SF3B4 was found to be a survival-related gene in ESCC and is presumed to regulate AS in multiple cancers. In summary, we identified significant differentially expressed AS events which may be related to the development of ESCC.

scholarly journals HERV-K Gag RNA and Protein Levels Are Elevated in Malignant Regions of the Prostate in Males with Prostate Cancer

Viruses ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 449
Author(s):  
Simin D. Rezaei ◽  
Joshua A. Hayward ◽  
Sam Norden ◽  
John Pedersen ◽  
John Mills ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cell Lines ◽  
Endogenous Retrovirus ◽  
Human Endogenous Retrovirus ◽  
Normal Prostate ◽  
Tissue Samples ◽  
Gag Protein ◽  
Protein Levels ◽  
Prostate Epithelial Cells ◽  
Prostate Cancers

Heightened expression of human endogenous retrovirus (HERV) sequences has been associated with a range of malignancies, including prostate cancer, suggesting that they may serve as useful diagnostic or prognostic cancer biomarkers. We analysed the expression of HERV-K (Gag and Env/Np9 regions), HERV-E 4.1 (Pol and Env regions), HERV-H (Pol) and HERV-W (Gag) sequences in prostate cancer cells lines and normal prostate epithelial cells using qRT-PCR. HERV expression was also analysed in matched malignant and benign prostate tissue samples from men with prostate cancer (n = 27, median age 65.2 years (range 47–70)) and compared to prostate cancer-free male controls (n = 11). Prostate cancer epithelial cell lines exhibited a signature of HERV RNA overexpression, with all HERVs analysed, except HERV-E Pol, showing heightened expression in at least two, but more commonly all, cell lines analysed. Analysis of primary prostate material indicated increased expression of HERV-E Pol but decreased expression of HERV-E Env in both malignant and benign regions of the prostate in men with prostate cancer as compared to those without. Expression of HERV-K Gag was significantly higher in malignant regions of the prostate in men with prostate cancer as compared to matched benign regions and prostate cancer-free men (p < 0.001 for both), with 85.2% of prostate cancers donors showing malignancy-associated upregulation of HERV-K Gag RNA. HERV-K Gag protein was detected in 12/18 (66.7%) malignant tissues using immunohistochemistry, but only 1/18 (5.6%) benign tissue sections. Heightened expression of HERV-K Gag RNA and protein appears to be a sensitive and specific biomarker of prostate malignancy in this cohort of men with prostate carcinoma, supporting its potential utility as a non-invasive, adjunct clinical biomarker.

scholarly journals An E3 Ubiquitin Ligase RNF139 Serves as a Tumor-Suppressor in Glioma

2021 ◽  
Author(s):  
Xiaofeng Chen ◽  
Weiping Kuang ◽  
Yong Zhu ◽  
Bin Zhou ◽  
Xiaosong Li ◽  
...  
Keyword(s):  
Tumor Suppressor ◽  
Cell Lines ◽  
Ubiquitin Ligase ◽  
Glioma Cell ◽  
Protein Modification ◽  
E3 Ubiquitin Ligase ◽  
Ring Finger ◽  
Glioma Cells ◽  
Migration And Invasion ◽  
Tissue Samples

AbstractGlioma is highly lethal because of its high malignancy. Ubiquitination, a type of ubiquitin-dependent protein modification, has been reported to play an oncogenic or tumor-suppressive role in glioma development, depending on the targets. Ring finger protein 139 (RNF139) is a membrane-bound E3 ubiquitin ligase serving as a tumor suppressor by ubiquitylation-dependently suppressing cell growth. Herein, we firstly confirmed the abnormal downregulation of RNF139 in glioma tissues and cell lines. In glioma cells, ectopic RNF139 overexpression could inhibit, whereas RNF139 knockdown could aggravate the aggressive behaviors of glioma cells, including hyperproliferation, migration, and invasion. Moreover, in two glioma cell lines, RNF139 overexpression inhibited, whereas RNF139 knockdown enhanced the phosphorylation of phosphatidylinositol 3-kinase (PI3K) and AKT serine/threonine kinase 1 (AKT). In a word, we demonstrate the aberration in RNF139 expression in glioma tissue samples and cell lines. RNF139 serves as a tumor-suppressor in glioma by inhibiting glioma cell proliferation, migration, and invasion and promoting glioma cell apoptosis through regulating PI3K/AKT signaling.

scholarly journals Long noncoding RNA LINC00941 promotes pancreatic cancer progression by competitively binding miR-335-5p to regulate ROCK1-mediated LIMK1/Cofilin-1 signaling

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jie Wang ◽  
Zhiwei He ◽  
Jian Xu ◽  
Peng Chen ◽  
Jianxin Jiang
Keyword(s):  
Pancreatic Cancer ◽  
Cell Growth ◽  
Cell Lines ◽  
Cancer Progression ◽  
Noncoding Rna ◽  
Epithelial Mesenchymal Transition ◽  
Loss Of Function ◽  
Mesenchymal Transition

AbstractAn accumulation of evidence indicates that long noncoding RNAs are involved in the tumorigenesis and progression of pancreatic cancer (PC). In this study, we investigated the functions and molecular mechanism of action of LINC00941 in PC. Quantitative PCR was used to examine the expression of LINC00941 and miR-335-5p in PC tissues and cell lines, and to investigate the correlation between LINC00941 expression and clinicopathological features. Plasmid vectors or lentiviruses were used to manipulate the expression of LINC00941, miR-335-5p, and ROCK1 in PC cell lines. Gain or loss-of-function assays and mechanistic assays were employed to verify the roles of LINC00941, miR-335-5p, and ROCK1 in PC cell growth and metastasis, both in vivo and in vitro. LINC00941 and ROCK1 were found to be highly expressed in PC, while miR-335-5p exhibited low expression. High LINC00941 expression was strongly associated with larger tumor size, lymph node metastasis, and poor prognosis. Functional experiments revealed that LINC00941 silencing significantly suppressed PC cell growth, metastasis and epithelial–mesenchymal transition. LINC00941 functioned as a molecular sponge for miR-335-5p, and a competitive endogenous RNA (ceRNA) for ROCK1, promoting ROCK1 upregulation, and LIMK1/Cofilin-1 pathway activation. Our observations lead us to conclude that LINC00941 functions as an oncogene in PC progression, behaving as a ceRNA for miR-335-5p binding. LINC00941 may therefore have potential utility as a diagnostic and treatment target in this disease.

57 Precision neoantigen discovery using novel algorithms and expanded HLA-ligandome datasets

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A62-A62
Author(s):  
Dattatreya Mellacheruvu ◽  
Rachel Pyke ◽  
Charles Abbott ◽  
Nick Phillips ◽  
Sejal Desai ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cell Lines ◽  
Antigen Processing ◽  
Large Scale ◽  
Prediction Models ◽  
K562 Cells ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
High Quality ◽  
Tissue Samples

BackgroundAccurately identified neoantigens can be effective therapeutic agents in both adjuvant and neoadjuvant settings. A key challenge for neoantigen discovery has been the availability of accurate prediction models for MHC peptide presentation. We have shown previously that our proprietary model based on (i) large-scale, in-house mono-allelic data, (ii) custom features that model antigen processing, and (iii) advanced machine learning algorithms has strong performance. We have extended upon our work by systematically integrating large quantities of high-quality, publicly available data, implementing new modelling algorithms, and rigorously testing our models. These extensions lead to substantial improvements in performance and generalizability. Our algorithm, named Systematic HLA Epitope Ranking Pan Algorithm (SHERPA™), is integrated into the ImmunoID NeXT Platform®, our immuno-genomics and transcriptomics platform specifically designed to enable the development of immunotherapies.MethodsIn-house immunopeptidomic data was generated using stably transfected HLA-null K562 cells lines that express a single HLA allele of interest, followed by immunoprecipitation using W6/32 antibody and LC-MS/MS. Public immunopeptidomics data was downloaded from repositories such as MassIVE and processed uniformly using in-house pipelines to generate peptide lists filtered at 1% false discovery rate. Other metrics (features) were either extracted from source data or generated internally by re-processing samples utilizing the ImmunoID NeXT Platform.ResultsWe have generated large-scale and high-quality immunopeptidomics data by using approximately 60 mono-allelic cell lines that unambiguously assign peptides to their presenting alleles to create our primary models. Briefly, our primary ‘binding’ algorithm models MHC-peptide binding using peptide and binding pockets while our primary ‘presentation’ model uses additional features to model antigen processing and presentation. Both primary models have significantly higher precision across all recall values in multiple test data sets, including mono-allelic cell lines and multi-allelic tissue samples. To further improve the performance of our model, we expanded the diversity of our training set using high-quality, publicly available mono-allelic immunopeptidomics data. Furthermore, multi-allelic data was integrated by resolving peptide-to-allele mappings using our primary models. We then trained a new model using the expanded training data and a new composite machine learning architecture. The resulting secondary model further improves performance and generalizability across several tissue samples.ConclusionsImproving technologies for neoantigen discovery is critical for many therapeutic applications, including personalized neoantigen vaccines, and neoantigen-based biomarkers for immunotherapies. Our new and improved algorithm (SHERPA) has significantly higher performance compared to a state-of-the-art public algorithm and furthers this objective.

scholarly journals POS0458 IDENTIFICATION OF HUB GENES AND MOLECULAR PATHWAYS IN PATIENTS WITH RHEUMATOID ARTHRITIS BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 460.1-460
Author(s):  
L. Cheng ◽  
S. X. Zhang ◽  
S. Song ◽  
C. Zheng ◽  
X. Sun ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathway ◽  
Synovial Tissue ◽  
Bioinformatics Analysis ◽  
Metabolic Process ◽  
Shanxi Province ◽  
Molecular Pathways ◽  
Biological Processes ◽  
Hub Genes ◽  
Tissue Samples

Background:Rheumatoid arthritis (RA) is a chronic, inflammatory synovitis based systemic disease of unknown etiology1. The genes and pathways in the inflamed synovium of RA patients are poorly understood.Objectives:This study aims to identify differentially expressed genes (DEGs) associated with the progression of synovitis in RA using bioinformatics analysis and explore its pathogenesis2.Methods:RA expression profile microarray data GSE89408 were acquired from the public gene chip database (GEO), including 152 synovial tissue samples from RA and 28 healthy synovial tissue samples. The DEGs of RA synovial tissues were screened by adopting the R software. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Protein-protein interaction (PPI) networks were assembled with Cytoscape software.Results:A total of 654 DEGs (268 up-regulated genes and 386 down-regulated genes) were obtained by the differential analysis. The GO enrichment results showed that the up-regulated genes were significantly enriched in the biological processes of myeloid leukocyte activation, cellular response to interferon-gamma and immune response-regulating signaling pathway, and the down-regulated genes were significantly enriched in the biological processes of extracellular matrix, retinoid metabolic process and regulation of lipid metabolic process. The KEGG annotation showed the up-regulated genes mainly participated in the staphylococcus aureus infection, chemokine signaling pathway, lysosome signaling pathway and the down-regulated genes mainly participated in the PPAR signaling pathway, AMPK signaling pathway, ECM-receptor interaction and so on. The 9 hub genes (PTPRC, TLR2, tyrobp, CTSS, CCL2, CCR5, B2M, fcgr1a and PPBP) were obtained based on the String database model by using the Cytoscape software and cytoHubba plugin3.Conclusion:The findings identified the molecular mechanisms and the key hub genes of pathogenesis and progression of RA.References:[1]Xiong Y, Mi BB, Liu MF, et al. Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis. Med Sci Monit 2019;25:2246-56. doi: 10.12659/MSM.915451 [published Online First: 2019/03/28][2]Mun S, Lee J, Park A, et al. Proteomics Approach for the Discovery of Rheumatoid Arthritis Biomarkers Using Mass Spectrometry. Int J Mol Sci 2019;20(18) doi: 10.3390/ijms20184368 [published Online First: 2019/09/08][3]Zhu N, Hou J, Wu Y, et al. Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis. Medicine (Baltimore) 2018;97(22):e10997. doi: 10.1097/MD.0000000000010997 [published Online First: 2018/06/01]Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

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