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An integrated analysis of molecular aberrations in NCI-60 cell lines.

Yeang CH - BMC Bioinformatics (2010)

Bottom Line: To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions.For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3) Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4) Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. chyeang@webmail.stat.sinica.edu.tw

ABSTRACT

Background: Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.

Results: We propose an integrated modeling framework to identify the statistical and putative causal relations of various molecular aberrations and gene expressions in cancer. To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. Layer 1 models associate gene expressions with the molecular aberrations on the same loci. Layer 2 models associate expressions with the aberrations on different loci but have known mechanistic links. Layer 3 models associate expressions with nonlocal aberrations which have unknown mechanistic links. We applied the layered models to the integrated datasets of NCI-60 cancer cell lines and validated the results with large-scale statistical analysis. Furthermore, we discovered/reaffirmed the following prominent links: (1) Protein expressions are generally consistent with mRNA expressions. (2) Several gene expressions are modulated by composite local aberrations. For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3) Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4) Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.

Conclusions: The analysis results on NCI-60 data justify the utility of the layered models for the incoming flow of cancer genomic data. Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.

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Related in: MedlinePlus

Three-layered models connecting molecular aberrations and gene expressions. Left: layer 1 models connecting mutations, CNVs, DNA methylations with mRNA and protein expressions of the same genes (g1 in the diagram). Solid black lines indicate transcription and translation. Solid green lines indicate layer 1 associations. Associations with mutations or DNA methylations are inhibitory. Middle: layer 2 models connecting internal segment CNVs and transcription factor expressions with expressions of another gene. Here g1 is a known target of transcription factor TF1. Dashed red lines indicate layer 2 associations. Right: layer 3 models connecting external segment CNVs, mutations and DNA methylations with mRNA expressions of a gene on another chromosomal segement. Dotted blue lines indicate layer 3 associations. Associations with external DNA methylations are inhibitory, whereas associations with external gene mutations can be positive or negative.
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Figure 1: Three-layered models connecting molecular aberrations and gene expressions. Left: layer 1 models connecting mutations, CNVs, DNA methylations with mRNA and protein expressions of the same genes (g1 in the diagram). Solid black lines indicate transcription and translation. Solid green lines indicate layer 1 associations. Associations with mutations or DNA methylations are inhibitory. Middle: layer 2 models connecting internal segment CNVs and transcription factor expressions with expressions of another gene. Here g1 is a known target of transcription factor TF1. Dashed red lines indicate layer 2 associations. Right: layer 3 models connecting external segment CNVs, mutations and DNA methylations with mRNA expressions of a gene on another chromosomal segement. Dotted blue lines indicate layer 3 associations. Associations with external DNA methylations are inhibitory, whereas associations with external gene mutations can be positive or negative.

Mentions: The novelty of our approach dwells on the priority of incorporating molecular aberrations in the model. We propose a layered modeling framework to identify the molecular aberrations explicating the expression data. The central idea is to sequentially apply a hierarchy of models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. A more complex model is not incorporated unless either the aberration data required for simpler models are not available or the explanatory power of the former significantly surpasses the power of any simpler models. We classify the mechanistic models into three layers according to the directness and uncertainty connecting the causes (observed molecular aberrations) and effects (observed gene expressions). Figure 1 illustrates the relations of molecular aberrations in each class.


An integrated analysis of molecular aberrations in NCI-60 cell lines.

Yeang CH - BMC Bioinformatics (2010)

Three-layered models connecting molecular aberrations and gene expressions. Left: layer 1 models connecting mutations, CNVs, DNA methylations with mRNA and protein expressions of the same genes (g1 in the diagram). Solid black lines indicate transcription and translation. Solid green lines indicate layer 1 associations. Associations with mutations or DNA methylations are inhibitory. Middle: layer 2 models connecting internal segment CNVs and transcription factor expressions with expressions of another gene. Here g1 is a known target of transcription factor TF1. Dashed red lines indicate layer 2 associations. Right: layer 3 models connecting external segment CNVs, mutations and DNA methylations with mRNA expressions of a gene on another chromosomal segement. Dotted blue lines indicate layer 3 associations. Associations with external DNA methylations are inhibitory, whereas associations with external gene mutations can be positive or negative.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2984587&req=5

Figure 1: Three-layered models connecting molecular aberrations and gene expressions. Left: layer 1 models connecting mutations, CNVs, DNA methylations with mRNA and protein expressions of the same genes (g1 in the diagram). Solid black lines indicate transcription and translation. Solid green lines indicate layer 1 associations. Associations with mutations or DNA methylations are inhibitory. Middle: layer 2 models connecting internal segment CNVs and transcription factor expressions with expressions of another gene. Here g1 is a known target of transcription factor TF1. Dashed red lines indicate layer 2 associations. Right: layer 3 models connecting external segment CNVs, mutations and DNA methylations with mRNA expressions of a gene on another chromosomal segement. Dotted blue lines indicate layer 3 associations. Associations with external DNA methylations are inhibitory, whereas associations with external gene mutations can be positive or negative.
Mentions: The novelty of our approach dwells on the priority of incorporating molecular aberrations in the model. We propose a layered modeling framework to identify the molecular aberrations explicating the expression data. The central idea is to sequentially apply a hierarchy of models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. A more complex model is not incorporated unless either the aberration data required for simpler models are not available or the explanatory power of the former significantly surpasses the power of any simpler models. We classify the mechanistic models into three layers according to the directness and uncertainty connecting the causes (observed molecular aberrations) and effects (observed gene expressions). Figure 1 illustrates the relations of molecular aberrations in each class.

Bottom Line: To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions.For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3) Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4) Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. chyeang@webmail.stat.sinica.edu.tw

ABSTRACT

Background: Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.

Results: We propose an integrated modeling framework to identify the statistical and putative causal relations of various molecular aberrations and gene expressions in cancer. To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. Layer 1 models associate gene expressions with the molecular aberrations on the same loci. Layer 2 models associate expressions with the aberrations on different loci but have known mechanistic links. Layer 3 models associate expressions with nonlocal aberrations which have unknown mechanistic links. We applied the layered models to the integrated datasets of NCI-60 cancer cell lines and validated the results with large-scale statistical analysis. Furthermore, we discovered/reaffirmed the following prominent links: (1) Protein expressions are generally consistent with mRNA expressions. (2) Several gene expressions are modulated by composite local aberrations. For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3) Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4) Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.

Conclusions: The analysis results on NCI-60 data justify the utility of the layered models for the incoming flow of cancer genomic data. Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.

Show MeSH
Related in: MedlinePlus