Dataset Information

IgG is involved in the migration and invasion of clear cell renal cell carcinoma.

ABSTRACT:

Objective

To investigate if IgG can be expressed in clear cell renal cell carcinoma (cRCC) , and the expression of IgG is involved in the cancer progression. If IgG expression can serve as a potential target in cancer therapies and be used for judging the prognosis.

Materials and methods

By immunohistochemistry, we detected IgG in cRCC tissues(75 cRCC tissues and75 adjacent normal kidney tissues). Immunofluorescence and Western blot was used to detect the IgG in cRCC cell lines (786-0, ACHN and CAKI-I). By RT-PCR, the functional transcript of IgG heavy chain was detected. Knockdown of IgG was to analyze the proliferation, migration and invasion ability by CCK8, Transwell and Matrigel and apoptosis in cRCC cell lines.

Results

By immunohistochemistry, we found strong staining of IgG in 66 cases of 75 cRCC tissues and 63 cases of 75 adjacent normal kidney tissues. Immunofluorescence and Western blot was found IgG in cRCC cell lines. Knock-down IgG in cRCC cell lines resulted in significant inhibition of cell proliferation, migration and invasion, and the induction of apoptosis of the 786-0 cells. The immunohistochemistry analysis showed that high IgG expression significantly correlated with the poor differentiation and advanced stage of cRCC.

Conclusion

IgG was over expressed in cRCC and was involved in the proliferation, migration and invasion of cancer cells. IgG expression may serve as a potential target in cancer therapies and could be used for judging the prognosis.

SUBMITTER: Sheng Z

PROVIDER: S-EPMC4893138 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

IgG is involved in the migration and invasion of clear cell renal cell carcinoma.

Sheng Zhengzuo Z Liu Yang Y Qin Caipeng C Liu Zhenhua Z Yuan Yeqing Y Hu FengZhan F Du Yiqing Y Yin Huaqi H Qiu Xiaoyan X Xu Tao T

Journal of clinical pathology 20151030 6

<h4>Objective</h4>To investigate if IgG can be expressed in clear cell renal cell carcinoma (cRCC) , and the expression of IgG is involved in the cancer progression. If IgG expression can serve as a potential target in cancer therapies and be used for judging the prognosis.<h4>Materials and methods</h4>By immunohistochemistry, we detected IgG in cRCC tissues(75 cRCC tissues and75 adjacent normal kidney tissues). Immunofluorescence and Western blot was used to detect the IgG in cRCC cell lines (7 ...[more]

PMID: 26519488

Similar Datasets

Project description:BackgroundMicroRNAs (miRNAs) serve as important regulators of the tumorigenesis and progression of many human cancers. Therefore, we evaluated the biological function and underlying mechanism of miR-363 in clear cell renal cell carcinoma (ccRCC).MethodsThe expression of miR-363 in ccRCC tissues compared with adjacent normal renal tissues was detected by quantitative real-time polymerase chain reaction, and the association between miR-363 levels and prognosis of ccRCC patients was analyzed. The candidate target gene of miR-363 was determined by in silico analysis and luciferase reporter assays. The effects of miR-363 on the proliferation, migration and invasion of ccRCC cells in vitro were determined by MTS assay, colony formation assay, Transwell assay and wound healing assay. We also investigated the roles of miR-363 in vivo by a xenograft tumour model. The mechanism of miR-363 on the proliferation, migration and invasion of ccRCC was determined by gain- and loss-of-function analyses.Resultswe demonstrated that miR-363 expression was obviously downregulated in ccRCC tissues and that reduced miR-363 expression was correlated with poor disease-free survival (DFS) in ccRCC patients after surgery. S1PR1 expression was inversely correlated with the level of miR-363 in human ccRCC samples. Luciferase reporter assays suggested that S1PR1 was a direct functional target of miR-363. miR-363 downregulated S1PR1 expression and suppressed the proliferation, migration and invasion abilities of ccRCC cells in vitro and suppressed xenograft tumour growth in vivo. Importantly, miR-363 exerted its biological function by inhibiting S1PR1 expression in ccRCC cells, leading to the repression of ERK activation. Moreover, we found that the levels of downstream effectors of ERK, including PDGF-A, PDGF-B, and epithelial-mesenchymal transition (EMT)-related genes, were decreased after miR-363 overexpression.ConclusionsOur results suggest that miR-363 acts as a tumour suppressor by directly targeting S1PR1 in ccRCC and may be a potential new therapeutic target for ccRCC.

Project description:Kidney Renal Clear Cell Carcinoma (KIRC) is one of fatal genitourinary diseases and accounts for most malignant kidney tumours. KIRC has been shown resistance to radiotherapy and chemotherapy. Like many types of cancers, there is no curative treatment for metastatic KIRC. Using advanced sequencing technologies, The Cancer Genome Atlas (TCGA) project of NIH/NCI-NHGRI has produced large-scale sequencing data, which provide unprecedented opportunities to reveal new molecular mechanisms of cancer. We combined differentially expressed genes, pathways and network analyses to gain new insights into the underlying molecular mechanisms of the disease development.Followed by the experimental design for obtaining significant genes and pathways, comprehensive analysis of 537 KIRC patients' sequencing data provided by TCGA was performed. Differentially expressed genes were obtained from the RNA-Seq data. Pathway and network analyses were performed. We identified 186 differentially expressed genes with significant p-value and large fold changes (P < 0.01, |log(FC)| > 5). The study not only confirmed a number of identified differentially expressed genes in literature reports, but also provided new findings. We performed hierarchical clustering analysis utilizing the whole genome-wide gene expressions and differentially expressed genes that were identified in this study. We revealed distinct groups of differentially expressed genes that can aid to the identification of subtypes of the cancer. The hierarchical clustering analysis based on gene expression profile and differentially expressed genes suggested four subtypes of the cancer. We found enriched distinct Gene Ontology (GO) terms associated with these groups of genes. Based on these findings, we built a support vector machine based supervised-learning classifier to predict unknown samples, and the classifier achieved high accuracy and robust classification results. In addition, we identified a number of pathways (P < 0.04) that were significantly influenced by the disease. We found that some of the identified pathways have been implicated in cancers from literatures, while others have not been reported in the cancer before. The network analysis leads to the identification of significantly disrupted pathways and associated genes involved in the disease development. Furthermore, this study can provide a viable alternative in identifying effective drug targets.Our study identified a set of differentially expressed genes and pathways in kidney renal clear cell carcinoma, and represents a comprehensive computational approach to analysis large-scale next-generation sequencing data. The pathway and network analyses suggested that information from distinctly expressed genes can be utilized in the identification of aberrant upstream regulators. Identification of distinctly expressed genes and altered pathways are important in effective biomarker identification for early cancer diagnosis and treatment planning. Combining differentially expressed genes with pathway and network analyses using intelligent computational approaches provide an unprecedented opportunity to identify upstream disease causal genes and effective drug targets.

Dataset Information

IgG is involved in the migration and invasion of clear cell renal cell carcinoma.

Objective

Materials and methods

Results

Conclusion

Publications

IgG is involved in the migration and invasion of clear cell renal cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets