Background: Exosomes are cell-derived vesicles and bear a specific set of nucleic acids including DNA (exoDNA). Thus, this study is to explore whether exoDNA in malignant pleural effusions (MPEs) could be a novel DNA source for mutation detection of epidermal growth factor receptor (EGFR).Methods: In this study, 52 lung adenocarcinoma patients were enrolled, and EGFR mutation status was detected with tumor tissues as well as cell blocks and exosomes in MPEs. The sensitivity, specificity and consistency of EGFR detection using exosomes were evaluated, compared with gene detection using tumor tissues and cell blocks. And the clinical response of patients who were detected as EGFR mutation in exosomes and treated with EGFR tyrosine kinase inhibitor (EGFR-TKI) was explored.Results: Gene detection using exosomes showed sensitivity of 100%, specificity of 96.55% and coincidence rate of 98.08% (Kappa = 0.961, P < 0.001), compared with detection using tumor tissues and cell blocks. After EGFR-TKI treatment, patients detected as EGFR mutation by exosomes showed efficacy rate of 83% and disease control rate of 100%. And patients who were detected as wild type in tumor tissues or cell blocks but EGFR mutation in exosomes turned up as PR or SD.Conclusions: These results demonstrated that exoDNA in MPEs could be used as a DNA source for EGFR detection in lung adenocarcinoma.
The progression of colorectal cancer (CRC) is a multistep process and metastatic CRC is always incurable; consequently, CRC is the leading cause of cancer-related deaths. There is therefore an urgent need for identifying useful biomarkers with enough sensitivity and specificity to detect this disease at early stages, which will significantly reduce the mortality for this malignancy. In this study, we performed an integrating analysis of different RNA-Seq data sets to find new candidate biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of CRC carcinogenesis. We identified 883 differentially expressed genes (DEGs) across the studies between CRC and normal control (NC) tissues by combining five RNA-Seq data sets. Gene function analysis revealed high correlation with carcinogenesis. The top 10 most significantly DEGs were further evaluated by quantitative real-time polymerase chain reaction (qRT-PCR) in both rectal cancer (RC) and colon cancer (CC), and the results matched well with integrating data, suggesting that the method of integrating analysis of different RNA-seq data sets is acceptable. Therefore, integrating analysis of different RNA-seq data sets may be a useful way to overcome the limitation of small sample size in a single RNA-seq study. In addition, our study showed that some genes, such as SIM2, ADAMTS6, FOXD4L4 and DNAH5, may have an important role in the development of CRC, which could be applied for diagnosis, prognosis and as therapy for this malignancy. Our findings would also help to understand the pathology of CRC.
BackgroundDespite new treatment options for hepatocellular carcinomas (HCC) recently, 5-year survival remains poor, ranging from 50 to 70%, which may attribute to the lack of early diagnostic biomarkers. Thus, developing new biomarkers for early diagnosis of HCC, is extremely urgent, aiming to decrease HCC-related deaths.MethodsIn the study, we conducted a comprehensive characterization of gene expression data of HCC based on a bioinformatics method. The results were confirmed by real time polymerase chain reaction (RT-PCR) and TCGA database to prove the credibility of this integrated analysis.ResultsAfter integrating analysis of seven HCC gene expression datasets, 1167 differential expressed genes (DEGs) were identified. These genes mainly participated in the process of cell cycle, oocyte meiosis, and oocyte maturation mediated by progesterone. The results of experiments and TCGA database validation in 10 genes was in full accordance with findings in integrated analysis, indicating the high credibility of our integrated analysis of different gene expression datasets. ASPM, CCT3, and NEK2 was showed to be significantly associated with overall survival of HCC patients in TCGA database.ConclusionThis method of integrated analysis may be a useful tool to minish the heterogeneity of individual microarray, hopefully outputs more accurate HCC transcriptome profiles based on large sample size, and explores some potential biomarkers and therapy targets for HCC.Electronic supplementary materialThe online version of this article (doi:10.1186/s13000-016-0596-x) contains supplementary material, which is available to authorized users.
Abstract. Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix-receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT-qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.
Peroxisome proliferator-activated receptors (PPARs) have been extensively studied for over 3 decades and consist of three isotypes, including PPARα, γ, and β/δ, that were originally considered key metabolic regulators controlling energy homeostasis in the body. Cancer has become a leading cause of human mortality worldwide, and the role of peroxisome proliferator-activated receptors in cancer is increasingly being investigated, especially the deep molecular mechanisms and effective cancer therapies. Peroxisome proliferator-activated receptors are an important class of lipid sensors and are involved in the regulation of multiple metabolic pathways and cell fate. They can regulate cancer progression in different tissues by activating endogenous or synthetic compounds. This review emphasizes the significance and knowledge of peroxisome proliferator-activated receptors in the tumor microenvironment, tumor cell metabolism, and anti-cancer treatment by summarizing recent research on peroxisome proliferator-activated receptors. In general, peroxisome proliferator-activated receptors either promote or suppress cancer in different types of tumor microenvironments. The emergence of this difference depends on various factors, including peroxisome proliferator-activated receptor type, cancer type, and tumor stage. Simultaneously, the effect of anti-cancer therapy based on drug-targeted PPARs differs or even opposes among the three peroxisome proliferator-activated receptor homotypes and different cancer types. Therefore, the current status and challenges of the use of peroxisome proliferator-activated receptors agonists and antagonists in cancer treatment are further explored in this review.
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