Limits...
Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia.

Ecker S, Pancaldi V, Rico D, Valencia A - Genome Med (2015)

Bottom Line: Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.We found that U-CLL, the more aggressive type of the disease, shows significantly increased variability of gene expression across patients and that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication.There are strong relations between gene expression variability and disease subtype linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

View Article: PubMed Central - PubMed

Affiliation: Structural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.

ABSTRACT

Background: Chronic lymphocytic leukemia (CLL) presents two subtypes which have drastically different clinical outcomes, IgVH mutated (M-CLL) and IgVH unmutated (U-CLL). So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.

Methods: We analyzed gene expression data of two large cohorts of CLL patients and quantified expression variability across individuals to investigate differences between the two subtypes using different measures and statistical tests. Functional significance was explored by pathway enrichment and network analyses. Furthermore, we implemented a random forest approach based on expression variability to classify patients into disease subtypes.

Results: We found that U-CLL, the more aggressive type of the disease, shows significantly increased variability of gene expression across patients and that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication. These functions indicate a potential relation between gene expression variability and the faster progression of this CLL subtype. Finally, a classifier based on gene expression variability was able to correctly predict the disease subtype of CLL patients.

Conclusions: There are strong relations between gene expression variability and disease subtype linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

No MeSH data available.


Related in: MedlinePlus

Network representation of genes with increased variability in U-CLL in the context of a B cell specific network [36]. Node sizes are determined by the degrees of the nodes, that is, big nodes represent highly connected genes. Different network modules are highlighted in different colors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4308895&req=5

Fig2: Network representation of genes with increased variability in U-CLL in the context of a B cell specific network [36]. Node sizes are determined by the degrees of the nodes, that is, big nodes represent highly connected genes. Different network modules are highlighted in different colors.

Mentions: To further understand the functional context of these differentially variable genes, we used a B cell specific functional interaction network [36] and extracted a subnetwork of the top differentially variable genes with increased variability in U-CLL in both datasets analyzed (Additional file 1) and their direct neighbors (considering only genes connected with at least two other genes). As a result, we identified a network of 892 genes connected by 3,390 edges (see Methods). Figure 2 shows the network with five highlighted subnetwork modules we identified (Louvain method [38]). A functional analysis of these network modules shows that every module is highly enriched in biological processes and pathways, further confirming our previous results of biological functions affected by increased expression variability in U-CLL and giving a deeper insight into these processes and pathways as well as the genes involved (Table 1 and Additional file 5).Figure 2


Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia.

Ecker S, Pancaldi V, Rico D, Valencia A - Genome Med (2015)

Network representation of genes with increased variability in U-CLL in the context of a B cell specific network [36]. Node sizes are determined by the degrees of the nodes, that is, big nodes represent highly connected genes. Different network modules are highlighted in different colors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4308895&req=5

Fig2: Network representation of genes with increased variability in U-CLL in the context of a B cell specific network [36]. Node sizes are determined by the degrees of the nodes, that is, big nodes represent highly connected genes. Different network modules are highlighted in different colors.
Mentions: To further understand the functional context of these differentially variable genes, we used a B cell specific functional interaction network [36] and extracted a subnetwork of the top differentially variable genes with increased variability in U-CLL in both datasets analyzed (Additional file 1) and their direct neighbors (considering only genes connected with at least two other genes). As a result, we identified a network of 892 genes connected by 3,390 edges (see Methods). Figure 2 shows the network with five highlighted subnetwork modules we identified (Louvain method [38]). A functional analysis of these network modules shows that every module is highly enriched in biological processes and pathways, further confirming our previous results of biological functions affected by increased expression variability in U-CLL and giving a deeper insight into these processes and pathways as well as the genes involved (Table 1 and Additional file 5).Figure 2

Bottom Line: Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.We found that U-CLL, the more aggressive type of the disease, shows significantly increased variability of gene expression across patients and that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication.There are strong relations between gene expression variability and disease subtype linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

View Article: PubMed Central - PubMed

Affiliation: Structural Biology and Biocomputing Programme, Spanish National Cancer Research Center (CNIO), 28029 Madrid, Spain.

ABSTRACT

Background: Chronic lymphocytic leukemia (CLL) presents two subtypes which have drastically different clinical outcomes, IgVH mutated (M-CLL) and IgVH unmutated (U-CLL). So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.

Methods: We analyzed gene expression data of two large cohorts of CLL patients and quantified expression variability across individuals to investigate differences between the two subtypes using different measures and statistical tests. Functional significance was explored by pathway enrichment and network analyses. Furthermore, we implemented a random forest approach based on expression variability to classify patients into disease subtypes.

Results: We found that U-CLL, the more aggressive type of the disease, shows significantly increased variability of gene expression across patients and that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication. These functions indicate a potential relation between gene expression variability and the faster progression of this CLL subtype. Finally, a classifier based on gene expression variability was able to correctly predict the disease subtype of CLL patients.

Conclusions: There are strong relations between gene expression variability and disease subtype linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

No MeSH data available.


Related in: MedlinePlus