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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

Boxplots of two SNPs, rs3088324 and rs11966226, showing significant association with copy number variation. (A-B) Boxplots were used to demonstrate the difference in copy number between the specific SNPs (AG versus GG for rs3088324 and CC versus CT for rs11966226). Significance level was determined by a Wilcoxon rank sum test. The Y-axis represents copy number. (A)KDM5B, rs3088324, was correlated with copy number amplifications. (B)RNF217, rs11966226, was correlated with copy number deletions. (C-D) To evaluate whether CNVs were able to drive downstream gene expression changes, a Wilcoxon rank sum test was performed on the expression difference between tumor and normal tissue for each SNP. The two genes, (C)KDM5B and (D)RNF217, both showed significantly differential expression (p-values < 0.05) and concordance in terms of the direction of change of CNVs and gene expression. The Y-axis denotes relative expression ratios on a log scale. Dotted lines indicate the unchanging baseline.
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Fig2: Boxplots of two SNPs, rs3088324 and rs11966226, showing significant association with copy number variation. (A-B) Boxplots were used to demonstrate the difference in copy number between the specific SNPs (AG versus GG for rs3088324 and CC versus CT for rs11966226). Significance level was determined by a Wilcoxon rank sum test. The Y-axis represents copy number. (A)KDM5B, rs3088324, was correlated with copy number amplifications. (B)RNF217, rs11966226, was correlated with copy number deletions. (C-D) To evaluate whether CNVs were able to drive downstream gene expression changes, a Wilcoxon rank sum test was performed on the expression difference between tumor and normal tissue for each SNP. The two genes, (C)KDM5B and (D)RNF217, both showed significantly differential expression (p-values < 0.05) and concordance in terms of the direction of change of CNVs and gene expression. The Y-axis denotes relative expression ratios on a log scale. Dotted lines indicate the unchanging baseline.

Mentions: First, Fisher’s exact test was used to explore the relationships between CNVs and SNP groupings; i.e., for each SNP in the two models, a 2×2 or 3×2 contingency table was created and evaluated. As shown in Table 1, there were 1,048 and 843 SNPs showing significant associations with copy number amplifications or deletions, respectively (p-values < 0.01). Among these SNPs, a linear regression test was applied to examine whether the copy number differences were predicted by the coding variables in each model. The results showed that 551 SNPs successfully predicted the magnitude of CNVs with p-values of < 0.01, indicating that the correlations between these SNPs and CNVs were both qualitative and quantitative. Subsequently, a Kruskal-Wallis test was used to evaluate the classification performances of the groupings from those SNPs, which revealed 142 and 95 SNPs with significant copy number differences (p-values < 0.01). For example, rs3088324 in KDM5B was associated with amplifications, and rs11966226 in RNF217 was associated with deletions (Figure 2A-B). These results indicate that investigation of SNPs and CNVs concurrently may help to identify dysregulated hotspots of genetic amplifications/deletions. To explore whether those CNVs were able to trigger downstream gene expression changes, a Kruskal-Wallis test was performed on their expression differences according to SNP groupings. A few SNPs were significantly (p-values < 0.05, Table 2) associated with corresponding changes in transcription level, such as KDM5B and RNF217 (Figure 2C-D), which further demonstrated that explorations of CNVs based on SNPs may reveal important hereditary markers during lung tumorigenesis.Table 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)

Boxplots of two SNPs, rs3088324 and rs11966226, showing significant association with copy number variation. (A-B) Boxplots were used to demonstrate the difference in copy number between the specific SNPs (AG versus GG for rs3088324 and CC versus CT for rs11966226). Significance level was determined by a Wilcoxon rank sum test. The Y-axis represents copy number. (A)KDM5B, rs3088324, was correlated with copy number amplifications. (B)RNF217, rs11966226, was correlated with copy number deletions. (C-D) To evaluate whether CNVs were able to drive downstream gene expression changes, a Wilcoxon rank sum test was performed on the expression difference between tumor and normal tissue for each SNP. The two genes, (C)KDM5B and (D)RNF217, both showed significantly differential expression (p-values < 0.05) and concordance in terms of the direction of change of CNVs and gene expression. The Y-axis denotes relative expression ratios on a log scale. Dotted lines indicate the unchanging baseline.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig2: Boxplots of two SNPs, rs3088324 and rs11966226, showing significant association with copy number variation. (A-B) Boxplots were used to demonstrate the difference in copy number between the specific SNPs (AG versus GG for rs3088324 and CC versus CT for rs11966226). Significance level was determined by a Wilcoxon rank sum test. The Y-axis represents copy number. (A)KDM5B, rs3088324, was correlated with copy number amplifications. (B)RNF217, rs11966226, was correlated with copy number deletions. (C-D) To evaluate whether CNVs were able to drive downstream gene expression changes, a Wilcoxon rank sum test was performed on the expression difference between tumor and normal tissue for each SNP. The two genes, (C)KDM5B and (D)RNF217, both showed significantly differential expression (p-values < 0.05) and concordance in terms of the direction of change of CNVs and gene expression. The Y-axis denotes relative expression ratios on a log scale. Dotted lines indicate the unchanging baseline.
Mentions: First, Fisher’s exact test was used to explore the relationships between CNVs and SNP groupings; i.e., for each SNP in the two models, a 2×2 or 3×2 contingency table was created and evaluated. As shown in Table 1, there were 1,048 and 843 SNPs showing significant associations with copy number amplifications or deletions, respectively (p-values < 0.01). Among these SNPs, a linear regression test was applied to examine whether the copy number differences were predicted by the coding variables in each model. The results showed that 551 SNPs successfully predicted the magnitude of CNVs with p-values of < 0.01, indicating that the correlations between these SNPs and CNVs were both qualitative and quantitative. Subsequently, a Kruskal-Wallis test was used to evaluate the classification performances of the groupings from those SNPs, which revealed 142 and 95 SNPs with significant copy number differences (p-values < 0.01). For example, rs3088324 in KDM5B was associated with amplifications, and rs11966226 in RNF217 was associated with deletions (Figure 2A-B). These results indicate that investigation of SNPs and CNVs concurrently may help to identify dysregulated hotspots of genetic amplifications/deletions. To explore whether those CNVs were able to trigger downstream gene expression changes, a Kruskal-Wallis test was performed on their expression differences according to SNP groupings. A few SNPs were significantly (p-values < 0.05, Table 2) associated with corresponding changes in transcription level, such as KDM5B and RNF217 (Figure 2C-D), which further demonstrated that explorations of CNVs based on SNPs may reveal important hereditary markers during lung tumorigenesis.Table 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