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Differential gene expression analysis in k562 human leukemia cell line treated with benzene.

ABSTRACT: Even though exposure to benzene has been linked to a variety of cancers including leukemia, the detailed molecular mechanisms relevant to benzene-induced carcinogenesis remain to be clearly elucidated. In this study, we evaluated the effects of benzene on differential gene expression in a leukemia cell line. The K562 leukemia cell line used in this study was cultured for 3 h with 10 mM benzene and RNA was extracted. To analyze the gene expression profiles, a 41,000 human whole genome chip was employed for cDNA microarray analysis. We initially identified 6,562 genes whose expression was altered by benzene treatment. Among these, 3,395 genes were upregulated and 3,167 genes were downregulated by more than 2-fold, respectively. The results of functional classification showed that the identified genes were involved in biological pathways including transcription, cell proliferation, the cell cycle, and apoptosis. These gene expression profiles should provide us with further insights into the molecular mechanisms underlying benzene-induced carcinogenesis, including leukemia.

SUBMITTER: Choi S

PROVIDER: S-EPMC3834516 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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Differential gene expression analysis in k562 human leukemia cell line treated with benzene.

Choi Sulji S Kim Ji-Young JY Moon Jai-Dong JD Baek Hee Jo HJ Kook Hoon H Seo Sang-Beom SB

Toxicological research 20110301 1

Even though exposure to benzene has been linked to a variety of cancers including leukemia, the detailed molecular mechanisms relevant to benzene-induced carcinogenesis remain to be clearly elucidated. In this study, we evaluated the effects of benzene on differential gene expression in a leukemia cell line. The K562 leukemia cell line used in this study was cultured for 3 h with 10 mM benzene and RNA was extracted. To analyze the gene expression profiles, a 41,000 human whole genome chip was em ...[more]

PMID: 24278550

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Project description:This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose level of expression is altered by PTPRG modulation and Imatinib concentration. Statistical tests as differential expression analysis (DEA) supported by gene set enrichment analysis (GSEA) and modern methods of ontological term analysis are presented along with some results of current interest for forthcoming experimental research in the field of the transcriptomic landscape of CML. In particular, we present two methods that differ in the order of the analysis steps. After a gene selection based on fold-change value thresholding, we applied statistical tests to select differentially expressed genes. Therefore, we applied two different methods on the set of differentially expressed genes. With the first method (Method 1), we implemented GSEA, followed by the identification of transcription factors. With the second method (Method 2), we first selected the transcription factors from the set of differentially expressed genes and implemented GSEA on this set. Method 1 is a standard method commonly used in this type of analysis, while Method 2 is unconventional and is motivated by the intention to identify transcription factors more specifically involved in biological processes relevant to the CML condition. Both methods have been equipped in ontological knowledge mining and word cloud analysis, as elements of novelty in our analytical procedure. Data analysis identified RARG and CD36 as a potential PTPRG up-regulated genes, suggesting a possible induction of cell differentiation toward an erithromyeloid phenotype. The prediction was confirmed at the mRNA and protein level, further validating the approach and identifying a new molecular mechanism of tumor suppression governed by PTPRG in a CML context.

Project description:BACKGROUND:Therapies targeting the epidermal growth factor receptor (EGFR) result in a painful rash, the most common and debilitating toxicity among patients with non-small cell lung cancer (NSCLC) who take EGFR tyrosine kinase inhibitor (TKI) therapy; however, predicting the development and the severity of the rash is difficult. OBJECTIVE:The aim of this study was to examine how erlotinib-an EGFR TKI that NSCLC patients take to stop or slow tumor growth-altered the transcriptome of dermal fibroblasts. METHODS:Dermal fibroblasts (ATCC PCS-201-012) were seeded in cell culture flasks, grown under standard conditions, and transferred to cell culture dishes. Cells were treated once daily for 3 days with erlotinib 100 nM (n = 5), erlotinib 1 ?M (n = 5), vehicle 1 ?M (dimethyl sulfoxide) (n = 5), or no treatment (n = 5). Total RNA was extracted using a standard TRIzol method and hybridized using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Raw intensities generated from the arrays were normalized using a Robust Multiarray Average method and analyzed using analysis of variance in Limma R software. Differentially expressed genes were analyzed using Ingenuity Pathway Analysis to identify canonical or noncanonical signaling pathways enriched in this dataset. RESULTS:We selected genes for investigation based on their potential role in wound healing (AQP3), rash development (CCL2), fibroblast activation (PALLD), cancer and cancer progression (GDF-15, SLC7A11, MMP12, and DIRAS3), and cell cycle control (CDC6). We were able to validate four of these genes by both Western blot analysis and quantitative polymerase chain reaction (MMP12, CCL2, CDC6, and SLC7A11). DISCUSSION:If found predictive of rash in future studies using patient samples, our findings may help to identify those at risk for severe rash so that (a) the dose of EGFR TKI therapy may be adjusted; (b) additional treatments for the rash can be developed; and/or (c) precise, patient-centered interventions can be developed so that patients with cancer can better self-manage their rash and adhere to EGFR TKI treatment.

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Differential gene expression analysis in k562 human leukemia cell line treated with benzene.

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Differential gene expression analysis in k562 human leukemia cell line treated with benzene.

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