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Identification of regulatory SNPs associated with genetic modifications in lung adenocarcinoma.

Lu TP, Hsiao CK, Lai LC, Tsai MH, Hsu CP, Lee JM, Chuang EY - BMC Res Notes (2015)

Bottom Line: A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis.Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations.In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma.

View Article: PubMed Central - PubMed

Affiliation: Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan. tplu@ntu.edu.tw.

ABSTRACT

Background: Although much research effort has been devoted to elucidating lung cancer, the molecular mechanism of tumorigenesis still remains unclear. A major challenge to improve the understanding of lung cancer is the difficulty of identifying reproducible differentially expressed genes across independent studies, due to their low consistency. To enhance the reproducibility of the findings, an integrated analysis was performed to identify regulatory SNPs. Thirty-two pairs of tumor and adjacent normal lung tissue specimens were analyzed using Affymetrix U133plus2.0, Affymetrix SNP 6.0, and Illumina Infinium Methylation microarrays. Copy number variations (CNVs) and methylation alterations were analyzed and paired t-tests were used to identify differentially expressed genes.

Results: A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis. Subsequently, three statistical approaches were performed to explore regulatory SNPs, which revealed that the genotypes of 551 and 66 SNPs were associated with CNV and changes in methylation, respectively. Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations.

Conclusions: In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma.

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Related in: MedlinePlus

Heatmaps of gene expression, copy number variation (CNV), and methylation level of the 505 differentially expressed genes in tumor tissue. In the gene expression heatmap (middle column), red represents up-regulation and green represents down-regulation. The gene order was the same in all three panels. For CNV and methylation alteration (left, right columns), one-way hierarchical clustering was first performed on the β-value difference and subsequently the copy number difference. For CNV (left column), gold indicates amplification and cyan indicates deletion. For methylation level (right column), blue denotes hypermethylation and yellow denotes hypomethylation.
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Fig1: Heatmaps of gene expression, copy number variation (CNV), and methylation level of the 505 differentially expressed genes in tumor tissue. In the gene expression heatmap (middle column), red represents up-regulation and green represents down-regulation. The gene order was the same in all three panels. For CNV and methylation alteration (left, right columns), one-way hierarchical clustering was first performed on the β-value difference and subsequently the copy number difference. For CNV (left column), gold indicates amplification and cyan indicates deletion. For methylation level (right column), blue denotes hypermethylation and yellow denotes hypomethylation.

Mentions: To explore the associations among CNVs, methylation, and gene expression levels, hierarchical clustering was performed using the Genesis program [22]. The input data were the gene expression ratios between tumor and normal tissue of the differentially expressed genes (Figure 1, middle column). Using the same order of genes, corresponding CNVs and methylation changes in those genes were illustrated as heatmaps (Figure 1, left and right panels, respectively).Figure 1


Identification of regulatory SNPs associated with genetic modifications in lung adenocarcinoma.

Lu TP, Hsiao CK, Lai LC, Tsai MH, Hsu CP, Lee JM, Chuang EY - BMC Res Notes (2015)

Heatmaps of gene expression, copy number variation (CNV), and methylation level of the 505 differentially expressed genes in tumor tissue. In the gene expression heatmap (middle column), red represents up-regulation and green represents down-regulation. The gene order was the same in all three panels. For CNV and methylation alteration (left, right columns), one-way hierarchical clustering was first performed on the β-value difference and subsequently the copy number difference. For CNV (left column), gold indicates amplification and cyan indicates deletion. For methylation level (right column), blue denotes hypermethylation and yellow denotes hypomethylation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4384239&req=5

Fig1: Heatmaps of gene expression, copy number variation (CNV), and methylation level of the 505 differentially expressed genes in tumor tissue. In the gene expression heatmap (middle column), red represents up-regulation and green represents down-regulation. The gene order was the same in all three panels. For CNV and methylation alteration (left, right columns), one-way hierarchical clustering was first performed on the β-value difference and subsequently the copy number difference. For CNV (left column), gold indicates amplification and cyan indicates deletion. For methylation level (right column), blue denotes hypermethylation and yellow denotes hypomethylation.
Mentions: To explore the associations among CNVs, methylation, and gene expression levels, hierarchical clustering was performed using the Genesis program [22]. The input data were the gene expression ratios between tumor and normal tissue of the differentially expressed genes (Figure 1, middle column). Using the same order of genes, corresponding CNVs and methylation changes in those genes were illustrated as heatmaps (Figure 1, left and right panels, respectively).Figure 1

Bottom Line: A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis.Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations.In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma.

View Article: PubMed Central - PubMed

Affiliation: Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan. tplu@ntu.edu.tw.

ABSTRACT

Background: Although much research effort has been devoted to elucidating lung cancer, the molecular mechanism of tumorigenesis still remains unclear. A major challenge to improve the understanding of lung cancer is the difficulty of identifying reproducible differentially expressed genes across independent studies, due to their low consistency. To enhance the reproducibility of the findings, an integrated analysis was performed to identify regulatory SNPs. Thirty-two pairs of tumor and adjacent normal lung tissue specimens were analyzed using Affymetrix U133plus2.0, Affymetrix SNP 6.0, and Illumina Infinium Methylation microarrays. Copy number variations (CNVs) and methylation alterations were analyzed and paired t-tests were used to identify differentially expressed genes.

Results: A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis. Subsequently, three statistical approaches were performed to explore regulatory SNPs, which revealed that the genotypes of 551 and 66 SNPs were associated with CNV and changes in methylation, respectively. Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations.

Conclusions: In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma.

Show MeSH
Related in: MedlinePlus