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Transcriptomic Heterogeneity in Cancer as a Consequence of Dysregulation of the Gene-Gene Interaction Network.

van Wieringen WN, van der Vaart AW - Bull. Math. Biol. (2015)

Bottom Line: Dysregulation of the regulatory network results in less control of transcript levels in the cell.Hence, dysregulation is reflected in the heterogeneity of the transcriptome: the more dysregulated the pathway, the more the transcriptomic heterogeneity.These mechanisms are statistically motivated, explored in silico, and their plausibility to occur in vivo illustrated by means of oncogenomics data of breast cancer studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, P. O. Box 7057, 1007 MB, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl.

ABSTRACT
Many pathways are dysregulated in cancer. Dysregulation of the regulatory network results in less control of transcript levels in the cell. Hence, dysregulation is reflected in the heterogeneity of the transcriptome: the more dysregulated the pathway, the more the transcriptomic heterogeneity. We identify four scenarios for a transcriptomic heterogeneity increase (i.e., pathway dysregulation) in cancer: (1) activation of a molecular switch, (2) a structural change in a regulator, (3) a temporal change in a regulator, and (4) weakening of gene-gene interactions. These mechanisms are statistically motivated, explored in silico, and their plausibility to occur in vivo illustrated by means of oncogenomics data of breast cancer studies.

No MeSH data available.


Related in: MedlinePlus

Illustration of the effect of a disturbance. Artificial time series data of the expression levels of a three-gene pathway are generated in accordance with Model (4) (full parametric details given in SM F). The (unperturbed) data, representing gene expression levels of the first gene of the pathway, are shown in the top panel. The lower panel contains the perturbed data of this gene, generated in accordance with Model (5) with the same innovations as the unperturbed data except for the disturbance. The disturbance occurs at time point . The dashed line connects the observation. The solid line is a moving average smoothing of the data (Color figure online)
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Fig5: Illustration of the effect of a disturbance. Artificial time series data of the expression levels of a three-gene pathway are generated in accordance with Model (4) (full parametric details given in SM F). The (unperturbed) data, representing gene expression levels of the first gene of the pathway, are shown in the top panel. The lower panel contains the perturbed data of this gene, generated in accordance with Model (5) with the same innovations as the unperturbed data except for the disturbance. The disturbance occurs at time point . The dashed line connects the observation. The solid line is a moving average smoothing of the data (Color figure online)

Mentions: The previous section attributes the surge in transcriptomic heterogeneity to switching to a regulatory module with changes in its DNA copy number. If such changes may cause this heterogeneity surge, one expects temporary changes to have a similar effect. Indeed, disturbances of the cellular regulatory network may also cause the transcriptomic entropy increase. This can be witnessed in perturbation experiments, in which the consequences (e.g., at the transcriptomic level) of an internal or external alteration to the cellular regulatory network are studied. An artificial illustration of this is given in Fig. 5. The figure portrays the expression levels of a gene over time, in the situation without and with a disturbance. It is obvious that the disturbed sequence exhibits more variation. A well-known example of such a disturbance is radiation. Exposure to radiation, even at low dose, may cause thyroid cancer (e.g., Ron et al. 1995). Below we provide a statistical underpinning of the effect of a disturbance on the increase in transcriptomic heterogeneity.Fig. 5


Transcriptomic Heterogeneity in Cancer as a Consequence of Dysregulation of the Gene-Gene Interaction Network.

van Wieringen WN, van der Vaart AW - Bull. Math. Biol. (2015)

Illustration of the effect of a disturbance. Artificial time series data of the expression levels of a three-gene pathway are generated in accordance with Model (4) (full parametric details given in SM F). The (unperturbed) data, representing gene expression levels of the first gene of the pathway, are shown in the top panel. The lower panel contains the perturbed data of this gene, generated in accordance with Model (5) with the same innovations as the unperturbed data except for the disturbance. The disturbance occurs at time point . The dashed line connects the observation. The solid line is a moving average smoothing of the data (Color figure online)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644214&req=5

Fig5: Illustration of the effect of a disturbance. Artificial time series data of the expression levels of a three-gene pathway are generated in accordance with Model (4) (full parametric details given in SM F). The (unperturbed) data, representing gene expression levels of the first gene of the pathway, are shown in the top panel. The lower panel contains the perturbed data of this gene, generated in accordance with Model (5) with the same innovations as the unperturbed data except for the disturbance. The disturbance occurs at time point . The dashed line connects the observation. The solid line is a moving average smoothing of the data (Color figure online)
Mentions: The previous section attributes the surge in transcriptomic heterogeneity to switching to a regulatory module with changes in its DNA copy number. If such changes may cause this heterogeneity surge, one expects temporary changes to have a similar effect. Indeed, disturbances of the cellular regulatory network may also cause the transcriptomic entropy increase. This can be witnessed in perturbation experiments, in which the consequences (e.g., at the transcriptomic level) of an internal or external alteration to the cellular regulatory network are studied. An artificial illustration of this is given in Fig. 5. The figure portrays the expression levels of a gene over time, in the situation without and with a disturbance. It is obvious that the disturbed sequence exhibits more variation. A well-known example of such a disturbance is radiation. Exposure to radiation, even at low dose, may cause thyroid cancer (e.g., Ron et al. 1995). Below we provide a statistical underpinning of the effect of a disturbance on the increase in transcriptomic heterogeneity.Fig. 5

Bottom Line: Dysregulation of the regulatory network results in less control of transcript levels in the cell.Hence, dysregulation is reflected in the heterogeneity of the transcriptome: the more dysregulated the pathway, the more the transcriptomic heterogeneity.These mechanisms are statistically motivated, explored in silico, and their plausibility to occur in vivo illustrated by means of oncogenomics data of breast cancer studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, P. O. Box 7057, 1007 MB, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl.

ABSTRACT
Many pathways are dysregulated in cancer. Dysregulation of the regulatory network results in less control of transcript levels in the cell. Hence, dysregulation is reflected in the heterogeneity of the transcriptome: the more dysregulated the pathway, the more the transcriptomic heterogeneity. We identify four scenarios for a transcriptomic heterogeneity increase (i.e., pathway dysregulation) in cancer: (1) activation of a molecular switch, (2) a structural change in a regulator, (3) a temporal change in a regulator, and (4) weakening of gene-gene interactions. These mechanisms are statistically motivated, explored in silico, and their plausibility to occur in vivo illustrated by means of oncogenomics data of breast cancer studies.

No MeSH data available.


Related in: MedlinePlus