Cross experimental analysis of microarray gene expression data from volatile organic compounds treated targets

Gene sequencing and expression of Raf-1 in lymphatic metastasis of hypopharyngeal carcinoma

OBJECTIVE

We performed differential gene screening for lymphatic metastasis of hypopharyngeal carcinoma by gene sequencing. We also aimed to investigate the expression and clinicopathological significance of the screened gene in hypopharyngeal carcinoma lymphatic metastasis.

METHODS

The clinicopathological characteristics of 98 patients with hypopharyngeal carcinoma were collected to make survival analysis by Kaplan-Meier & log-rank test. Six cases of tumor tissues from patients with or without lymphatic metastasis were used for gene sequencing of differentially expressed genes. The most frequently differently expressed genes were validated by RT-PCR and Western blot in another 20 patients diagnosed for hypopharyngeal carcinoma. A total of 70 cases of hypopharyngeal carcinoma tumor tissues and normal tissues were investigated to examine the immunohistochemical expression and to explore the prognostic value by Kaplan-Meier & log-rank test and Cox's test.

RESULTS

Lymphatic metastasis has been proved to cause a reduction in postoperative survival of patients with hypopharyngeal carcinoma. The results of gene sequencing analysis showed that Raf-1 was a differentially expressed gene in lymphatic metastasis of hypopharyngeal carcinoma. Moreover, the expression of Raf-1 was significantly up-regulated in tumor tissues of lymphatic metastasis patients compared to non-lymphatic metastasis tumor tissues and normal tissues. Meanwhile, Raf-1 had been verified to be an independent risk factor affecting the prognosis of hypopharyngeal carcinoma.

CONCLUSIONS

For the first time, we investigated Raf-1 as an independent prognostic risk factor of lymphatic metastasis in hypopharyngeal carcinoma. It suggests that Raf-1 may serve as an important potential biomarker in preventing and diagnosing lymphatic metastasis in patients with hypopharyngeal carcinoma and improving the prognosis of patients.

The identification of induction chemo-sensitivity genes of laryngeal squamous cell carcinoma and their clinical utilization

PURPOSE

To identify potential molecular markers for induction chemotherapy of Laryngeal squamous cell carcinoma (LSCC).

METHODS

Differently expressed genes between chemo-sensitive group (seven cases) and chemo-insensitive (five cases) group after induction chemotherapy by TPF were identified by microarrays. Bayes network and Random forest analyses were employed to identify core genes for induction chemotherapy. The diagnostic value of these core genes was also evaluated by ROC analysis.

RESULTS

Six genes (SPP1, FOLR3, KYNU, LOC653219, ADH7 and XAGE1A) are highly expressed, while seven gene (CADM1, NDUFA4L2, CCND2, RARRES3, ERAP2, LYD6 and CNTNAP2) present significantly low expression. Among these genes, genes CADM1, FOLR3, KYNU, and CNTNAP2 are core candidates for LSCC chemo-sensitivity. And that the low expression of CADM1 may result in chemo-sensitivity, which leads to high expression of gene FOLR3 and KYNU, and low expression of gene CNTNAP2. Besides, ROC analysis shows that these four genes exhibit effective diagnostic value for induction chemo-sensitivity.

CONCLUSIONS

CADM1 may be a potential molecular marker for LSCC induction chemotherapy, while CADM1, FOLR3, KYNU, and CNTNAP2 may provide essential guidance for LSCC diagnosis and follow-up treatment strategies.

Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data

The toxicogenomics field aims to understand and predict toxicity by using 'omics' data in order to study systems-level responses to compound treatments. In recent years there has been a rapid increase in publicly available toxicological and 'omics' data, particularly gene expression data, and a corresponding development of methods for its analysis. In this review, we summarize recent progress relating to the analysis of RNA-Seq and microarray data, review relevant databases, and highlight recent applications of toxicogenomics data for understanding and predicting compound toxicity. These include the analysis of differentially expressed genes and their enrichment, signature matching, methods based on interaction networks, and the analysis of co-expression networks. In the future, these state-of-the-art methods will likely be combined with new technologies, such as whole human body models, to produce a comprehensive systems-level understanding of toxicity that reduces the necessity of in vivo toxicity assessment in animal models.

Evaluation of whole wastewater effluent impacts on HepG2 using DNA microarray-based transcriptome analysis

DNA microarray-based transcriptome analysis with human hepatoma HepG2 cells was applied to evaluate the impacts of whole wastewater effluents from the membrane bioreactors (MBRs) and the activated sludge process (AS). In addition, the conventional bioassays (i.e., cytotoxicity tests and bioluminescence inhibition test), which were well-established for the evaluation of the overall effluent toxicity, were also performed for the same samples. Transcriptome analysis revealed that 2 to 926 genes, which were categorized to 0 to 225 biological processes, were differentially expressed after exposure to the effluents and the raw wastewater. Among the tested effluents, the effluent from a MBR operated at a relatively long solid retention time (i.e., 40 days) and small membrane pore size (i.e., 0.03 μm) showed the least impacts on the HepG2 even at the level comparable to tap water. The observed gene expression responses were in good agreement with the results of cytotoxicity tests, and provided additional molecular mechanistic information on adverse effects occurred in the sublethal region. Furthermore, the genes related to "lipid metabolism", "response to endogenous stimulus", and "response to inorganic substance" were selected as potential genetic markers, and their expression levels were quantified to evaluate the cellular impacts and treatability of wastewater effluents. Although the harmful impacts and innocuous impacts could not be distinguished at present, the results demonstrated that the DNA microarray-based transcriptome analysis with human HepG2 cells was a powerful tool to rapidly and comprehensively evaluate impacts of whole wastewater effluents.

Monitoring of deiodinase deficiency based on transcriptomic responses in SH-SY5Y cells

Iodothyronine deiodinase types I, II, and III (D1, D2, and D3, respectively), which constitute a family of selenoenzymes, activate and inactivate thyroid hormones through the removal of specific iodine moieties from thyroxine and its derivatives. These enzymes are important in the biological effects mediated by thyroid hormones. The expression of activating and inactivating deiodinases plays a critical role in a number of cell systems, including the neuronal system, during development as well as in adult vertebrates. To investigate deiodinase-disrupting chemicals based on transcriptomic responses, we examined differences in gene expression profiles between T3-treated and deiodinase-knockdown SH-SY5Y cells using microarray analysis and quantitative real-time RT-PCR. A total of 1,558 genes, consisting of 755 upregulated and 803 downregulated genes, were differentially expressed between the T3-treated and deiodinase-knockdown cells. The expression levels of 10 of these genes (ID2, ID3, CCL2, TBX3, TGOLN2, C1orf71, ZNF676, GULP1, KLF9, and ITGB5) were altered by deiodinase-disrupting chemicals (2,3,7,8-tetrachlorodibenzo-p-dioxin, polychlorinated biphenyls, propylthiouracil, iodoacetic acid, methylmercury, β-estradiol, methimazole, 3-methylcholanthrene, aminotriazole, amiodarone, cadmium chloride, dimethoate, fenvalerate, octylmethoxycinnamate, iopanoic acid, methoxychlor, and 4-methylbenzylidene-camphor). These genes are potential biomarkers for detecting deiodinase deficiency and predicting their effects on thyroid hormone production.