Limits...
Transcriptome-wide identification and study of cancer-specific splicing events across multiple tumors.

Tsai YS, Dominguez D, Gomez SM, Wang Z - Oncotarget (2015)

Bottom Line: To obtain a global picture of cancer-specific splicing, we analyzed transcriptome sequencing data from 1149 patients in The Cancer Genome Atlas project, producing a core set of AS events significantly altered across multiple cancer types.These cancer-specific AS events are highly conserved, are more likely to maintain protein reading frame, and mainly function in cell cycle, cell adhesion/migration, and insulin signaling pathways.We also found that most genes whose expression is closely associated with cancer-specific splicing are key regulators of the cell cycle.

View Article: PubMed Central - PubMed

Affiliation: Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA.

ABSTRACT
Dysregulation of alternative splicing (AS) is one of the molecular hallmarks of cancer, with splicing alteration of numerous genes in cancer patients. However, studying splicing mis-regulation in cancer is complicated by the large noise generated from tissue-specific splicing. To obtain a global picture of cancer-specific splicing, we analyzed transcriptome sequencing data from 1149 patients in The Cancer Genome Atlas project, producing a core set of AS events significantly altered across multiple cancer types. These cancer-specific AS events are highly conserved, are more likely to maintain protein reading frame, and mainly function in cell cycle, cell adhesion/migration, and insulin signaling pathways. Furthermore, these events can serve as new molecular biomarkers to distinguish cancer from normal tissues, to separate cancer subtypes, and to predict patient survival. We also found that most genes whose expression is closely associated with cancer-specific splicing are key regulators of the cell cycle. This study uncovers a common set of cancer-specific AS events altered across multiple cancers, providing mechanistic insight into how splicing is mis-regulated in cancers.

Show MeSH

Related in: MedlinePlus

Genes associated with cancer-specific AS events(A) Flow chart of identifying possible regulators of cancer-specific AS. (B) Gene ontology analysis of the 304 genes that are highly correlated with the 163 tumor AS events. (Spearman rank correlation > = 0.4 across 1319 samples, p-value < 0.005, and correlated with more than 30 out of the 163 tumor AS). (C) PPI networks of genes that are highly correlated with the 163 cancer-specific AS events. Color-coded proteins are clustered by MCODE. Light purple-colored nodes were proteins that were not clustered into any group by MCODE. The most enriched function/GO-term was labeled next to each cluster. The genes involved in RNA binding and splicing regulation are also indicated at the bottom.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4466652&req=5

Figure 6: Genes associated with cancer-specific AS events(A) Flow chart of identifying possible regulators of cancer-specific AS. (B) Gene ontology analysis of the 304 genes that are highly correlated with the 163 tumor AS events. (Spearman rank correlation > = 0.4 across 1319 samples, p-value < 0.005, and correlated with more than 30 out of the 163 tumor AS). (C) PPI networks of genes that are highly correlated with the 163 cancer-specific AS events. Color-coded proteins are clustered by MCODE. Light purple-colored nodes were proteins that were not clustered into any group by MCODE. The most enriched function/GO-term was labeled next to each cluster. The genes involved in RNA binding and splicing regulation are also indicated at the bottom.

Mentions: To explore possible regulatory mechanisms of cancer-specific AS, we systematically calculated the correlation between the PSI value of the 163 cancer-specific AS events and the expression of all detectable genes (Figure 6A). We found that the set of cancer-specific AS events are indeed significantly correlated with expression of many genes, among which are 304 genes highly correlated with more than 30 cancer-specific AS events. This set of genes are either positively or negatively correlated with the PSI values of many cancer-specific AS events, and thus may reflect potential regulatory pathways for the associated AS events.


Transcriptome-wide identification and study of cancer-specific splicing events across multiple tumors.

Tsai YS, Dominguez D, Gomez SM, Wang Z - Oncotarget (2015)

Genes associated with cancer-specific AS events(A) Flow chart of identifying possible regulators of cancer-specific AS. (B) Gene ontology analysis of the 304 genes that are highly correlated with the 163 tumor AS events. (Spearman rank correlation > = 0.4 across 1319 samples, p-value < 0.005, and correlated with more than 30 out of the 163 tumor AS). (C) PPI networks of genes that are highly correlated with the 163 cancer-specific AS events. Color-coded proteins are clustered by MCODE. Light purple-colored nodes were proteins that were not clustered into any group by MCODE. The most enriched function/GO-term was labeled next to each cluster. The genes involved in RNA binding and splicing regulation are also indicated at the bottom.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4466652&req=5

Figure 6: Genes associated with cancer-specific AS events(A) Flow chart of identifying possible regulators of cancer-specific AS. (B) Gene ontology analysis of the 304 genes that are highly correlated with the 163 tumor AS events. (Spearman rank correlation > = 0.4 across 1319 samples, p-value < 0.005, and correlated with more than 30 out of the 163 tumor AS). (C) PPI networks of genes that are highly correlated with the 163 cancer-specific AS events. Color-coded proteins are clustered by MCODE. Light purple-colored nodes were proteins that were not clustered into any group by MCODE. The most enriched function/GO-term was labeled next to each cluster. The genes involved in RNA binding and splicing regulation are also indicated at the bottom.
Mentions: To explore possible regulatory mechanisms of cancer-specific AS, we systematically calculated the correlation between the PSI value of the 163 cancer-specific AS events and the expression of all detectable genes (Figure 6A). We found that the set of cancer-specific AS events are indeed significantly correlated with expression of many genes, among which are 304 genes highly correlated with more than 30 cancer-specific AS events. This set of genes are either positively or negatively correlated with the PSI values of many cancer-specific AS events, and thus may reflect potential regulatory pathways for the associated AS events.

Bottom Line: To obtain a global picture of cancer-specific splicing, we analyzed transcriptome sequencing data from 1149 patients in The Cancer Genome Atlas project, producing a core set of AS events significantly altered across multiple cancer types.These cancer-specific AS events are highly conserved, are more likely to maintain protein reading frame, and mainly function in cell cycle, cell adhesion/migration, and insulin signaling pathways.We also found that most genes whose expression is closely associated with cancer-specific splicing are key regulators of the cell cycle.

View Article: PubMed Central - PubMed

Affiliation: Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA.

ABSTRACT
Dysregulation of alternative splicing (AS) is one of the molecular hallmarks of cancer, with splicing alteration of numerous genes in cancer patients. However, studying splicing mis-regulation in cancer is complicated by the large noise generated from tissue-specific splicing. To obtain a global picture of cancer-specific splicing, we analyzed transcriptome sequencing data from 1149 patients in The Cancer Genome Atlas project, producing a core set of AS events significantly altered across multiple cancer types. These cancer-specific AS events are highly conserved, are more likely to maintain protein reading frame, and mainly function in cell cycle, cell adhesion/migration, and insulin signaling pathways. Furthermore, these events can serve as new molecular biomarkers to distinguish cancer from normal tissues, to separate cancer subtypes, and to predict patient survival. We also found that most genes whose expression is closely associated with cancer-specific splicing are key regulators of the cell cycle. This study uncovers a common set of cancer-specific AS events altered across multiple cancers, providing mechanistic insight into how splicing is mis-regulated in cancers.

Show MeSH
Related in: MedlinePlus