scholarly journals Characterization of a novel chicken muscle disorder through differential gene expression and pathway analysis using RNA-sequencing

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Marie F Mutryn ◽  
Erin M Brannick ◽  
Weixuan Fu ◽  
William R Lee ◽  
Behnam Abasht
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Differential Gene Expression ◽  
Pathway Analysis ◽  
Chicken Muscle ◽  
Muscle Disorder ◽  
Differential Gene

scholarly journals Gastrointestinal Goblet Cell Adenocarcinomas Harbor Distinctive Clinicopathological, Immune, and Genomic Landscape

2021 ◽  
Vol 11 ◽  
Author(s):  
Dong-Liang Lin ◽  
Li-Li Wang ◽  
Peng Zhao ◽  
Wen-Wen Ran ◽  
Wei Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
Colorectal Adenocarcinoma ◽  
Signet Ring Cell ◽  
Cell Component ◽  
Signet Ring ◽  
Differential Gene ◽  
Ring Cell

Goblet cell adenocarcinoma (GCA) is a rare amphicrine tumor and difficult to diagnose. GCA is traditionally found in the appendix, but extra-appendiceal GCA may be underestimated. Intestinal adenocarcinoma with signet ring cell component is also very rare, and some signet ring cell carcinomas are well cohesive, having some similar morphological features to GCAs. It is necessary to differentiate GCA from intestinal adenocarcinomas with cohesive signet ring cell component (IACSRCC). The goal of this study is to find occurrence of extra-appendiceal GCA and characterize the histological, immunohistochemical, transcriptional, and immune landscape of GCA. We collected 12 cases of GCAs and 10 IACSRCCs and reviewed the clinicopathologic characters of these cases. Immunohistochemical stains were performed with synaptophysin, chromogranin A, CD56, somatostatin receptor (SSTR) 2, and Ki-67. Whole transcriptome RNA-sequencing was performed, and data were used to analyze differential gene expression and predict immune cell infiltration levels in GCA and IACSRCC. RNA-sequencing data for colorectal adenocarcinoma were gathered from TCGA data portal. Of the 12 patients with GCA, there were 4 women and 8 men. There were three appendiceal cases and nine extra-appendiceal cases. GCAs were immunohistochemically different from IACSRCC. GCA also had different levels of B-cell and CD8+ T-cell infiltration compared to both colorectal adenocarcinoma and cohesive IACSRCCs. Differential gene expression analysis showed distinct gene expression patterns in GCA compared to colorectal adenocarcinoma, with a number of cancer-related differentially expressed genes, including upregulation of TMEM14A, GOLT1A, DSCC1, and HSD17B8, and downregulation of KCNQ1OT1 and MXRA5. GCA also had several differentially expressed genes compared to IACSRCCs, including upregulation of PRSS21, EPPIN, RPRM, TNFRSF12A, and BZRAP1, and downregulation of HIST1H2BE, TCN1, AC069363.1, RP11-538I12.2, and REG4. In summary, the number of extra-appendiceal GCA was underestimated in Chinese patients. GCA can be seen as a distinct morphological, immunohistochemical, transcriptomic, and immunological entity. The classic low-grade component of GCA and the immunoreactivity for neuroendocrine markers are the key points to diagnosing GCA.

scholarly journals Characterization of Distinct Classes of Differential Gene Expression in Osteoblast Cultures from Non-Syndromic Craniosynostosis Bone

2014 ◽  
Vol 2 ◽  
pp. 121-130 ◽  
Author(s):  
Monica L. Rojas-Peña ◽  
Rene Olivares-Navarrete ◽  
Sharon Hyzy ◽  
Dalia Arafat ◽  
Zvi Schwartz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Syndromic Craniosynostosis ◽  
Differential Gene

scholarly journals Microarray-based characterization of differential gene expression during vocal fold wound healing in rats

2015 ◽  
Vol 8 (3) ◽  
pp. 311-321 ◽  
Author(s):  
N. V. Welham ◽  
C. Ling ◽  
J. A. Dawson ◽  
C. Kendziorski ◽  
S. L. Thibeault ◽  
...  
Keyword(s):  
Gene Expression ◽  
Wound Healing ◽  
Differential Gene Expression ◽  
Vocal Fold ◽  
Differential Gene

scholarly journals Authentication of Differential Gene Expression in Oral Squamous Cell Carcinoma using Machine Learning Applications

2020 ◽  
Author(s):  
Rian Pratama ◽  
Jae Joon Hwang ◽  
Ji Hye Lee ◽  
Giltae Song ◽  
Hae Ryoun Park
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Rna Sequencing ◽  
Differential Gene Expression ◽  
Sequencing Data ◽  
Machine Learning Applications ◽  
Differential Gene

Abstract Background: Recently, the possibility of tumour classification based on genetic data has been investigated. However, genetic datasets are difficult to handle because of their massive size and complexity of manipulation. In the present study, we examined the diagnostic performance of machine learning applications using imaging-based classifications of oral squamous cell carcinoma (OSCC) gene sets.Methods: RNA sequencing data from SCC tissues from various sites, including oral, non-oral head and neck, oesophageal, and cervical regions, were downloaded from The Cancer Genome Atlas (TCGA). The feature genes were extracted through a convolutional neural network (CNN) and machine learning, and the performance of each analysis was compared.Results: The ability of the machine learning analysis to classify OSCC tumours was excellent. However, the tool exhibited poorer performance in discriminating histopathologically dissimilar cancers derived from the same type of tissue than in differentiating cancers of the same histopathologic type with different tissue origins, revealing that the differential gene expression pattern is a more important factor than the histopathologic features for differentiating cancer types.Conclusion: The CNN-based diagnostic model and the visualisation methods using RNA sequencing data were useful for correctly categorising OSCC. The analysis showed differentially expressed genes in multiwise comparisons of various types of SCCs, such as KCNA10, FOSL2, and PRDM16, and extracted leader genes from pairwise comparisons were FGF20, DLC1, and ZNF705D.

scholarly journals Comparative RNA-sequencing profiled the differential gene expression of liver in response to acetyl-CoA carboxylase inhibitor GS-0976 in a mouse model of NASH

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8115
Author(s):  
Ying Lu ◽  
Xiaolan Su ◽  
Manyu Zhao ◽  
Qianru Zhang ◽  
Chuang Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mouse Model ◽  
Rna Sequencing ◽  
Hepatic Steatosis ◽  
Differential Gene Expression ◽  
Receptor Interaction ◽  
Therapeutic Effects ◽  
Acetyl Coa Carboxylase ◽  
Acetyl Coa ◽  
Differential Gene

Background Non-alcoholic steatohepatitis (NASH) is a progressive liver disease characterized by hepatic steatosis, lobular inflammation and fibrosis. Acetyl-CoA carboxylase (ACC) isoform 1 and 2 involved in de novo lipogenesis (DNL) and fatty acid oxidation have been identified as a therapeutic target in NASH. GS-0976, the inhibitor of ACC1 and ACC2, has achieved favorable therapeutic effects in clinical trials with NASH. The purpose of this study was to explore the transcriptional alterations regulated by GS-0976 in NASH. Methods C57BL/6 mice were fed on a choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) or normal diet for 12 weeks. Mice were treated with or without GS-0976 (3 mg/kg per day) in the last 8 weeks. Oil Red O, Haematoxylin-eosin (H & E), and Sirius Red were used to evaluate hepatic steatosis, inflammation and fibrosis. The comparative RNA-sequencing was conducted to analyse the hepatic gene expression profiles in mice. Reverse transcription–polymerase chain reaction analysis was performed to validate the differential expression of representative genes. Results GS-0976 attenuated the steatosis, inflammation, and fibrosis of NASH in CDAHFD mouse model. High-throughput sequencing and differential gene expression analysis showed that there were 516 up-regulated genes and 525 down-regulated genes after GS-0976 treatment. Genes involved in the metabolic process, extracellular matrix formation, immune response, and angiogenesis were significantly enriched. The “Metabolic pathways” and “ECM-receptor interaction” pathways were the most significantly enriched KEGG pathways in the up-regulated and down-regulated differentially expressed genes (DEGs), respectively. Conclusions Transcriptome analysis showed that GS-0976 could regulate the expression of genes related to metabolism, inflammation and fibrosis in NASH. The global transcriptomic changes in gene expression promote the further understanding for the inhibition mechanisms of GS-0976 in NASH.

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