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Identification of lncRNA-associated competing triplets reveals global patterns and prognostic markers for cancer.

Wang P, Ning S, Zhang Y, Li R, Ye J, Zhao Z, Zhi H, Wang T, Guo Z, Li X - Nucleic Acids Res. (2015)

Bottom Line: In the lncACT cross-talk network, disease-associated lncRNAs, miRNAs and coding-genes showed specific topological patterns indicative of their competence and control of communication within the network.Based on the global cross-talk network and cluster analyses, nine cancer-specific sub-networks were constructed.H19- and BRCA1/2-associated lncACTs were able to discriminate between two groups of patients with different clinical outcomes.

View Article: PubMed Central - PubMed

Affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

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Related in: MedlinePlus

Sub-network analysis of competing lncACTs. (A) A BRCA-specific sub-network was derived from the global crosstalk network, which consisted of 95 lncRNAs, 68 miRNAs, 197 mRNAs and contained 132 functional modules. Two example modules are demarcated by circles. The lncRNAs, miRNAs and coding-genes are colored blue, red and yellow, respectively. The node degree is indicated by the node size. (B) One module had five nodes, all of which have been experimentally demonstrated to have key roles in the development of breast cancer. The expression heat map is shown on the right. In the heat map, highly expressed genes are shown in red, low expression genes are shown in green. (C) The lncRNA H19 was identified as a hub that connects five competing modules. (D) The lncRNA MIR22HG is functionally complementary to H19 and interacts with the same miRNAs. A genomic representation of miR-22 is shown in the red bar and MIR22HG is shown on the bottom. Predicted miR-22 target sites on MIR22HG are shown in the black bar, with detailed miRNA binding information of the site nearest to the miR-22 locus illustrated on the right. (E) Hierarchical clustering of 248 patients based on H19 and BRCA1/2 lncACT expression. (F) Kaplan-Meier survival analysis of two groups of patients with different clinical outcomes. Those that showed no progression or who were still alive at the time of the last follow-up were censored (+). Survival days are shown along the X axis. Overall survival rates are shown along the Y axis.
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Figure 5: Sub-network analysis of competing lncACTs. (A) A BRCA-specific sub-network was derived from the global crosstalk network, which consisted of 95 lncRNAs, 68 miRNAs, 197 mRNAs and contained 132 functional modules. Two example modules are demarcated by circles. The lncRNAs, miRNAs and coding-genes are colored blue, red and yellow, respectively. The node degree is indicated by the node size. (B) One module had five nodes, all of which have been experimentally demonstrated to have key roles in the development of breast cancer. The expression heat map is shown on the right. In the heat map, highly expressed genes are shown in red, low expression genes are shown in green. (C) The lncRNA H19 was identified as a hub that connects five competing modules. (D) The lncRNA MIR22HG is functionally complementary to H19 and interacts with the same miRNAs. A genomic representation of miR-22 is shown in the red bar and MIR22HG is shown on the bottom. Predicted miR-22 target sites on MIR22HG are shown in the black bar, with detailed miRNA binding information of the site nearest to the miR-22 locus illustrated on the right. (E) Hierarchical clustering of 248 patients based on H19 and BRCA1/2 lncACT expression. (F) Kaplan-Meier survival analysis of two groups of patients with different clinical outcomes. Those that showed no progression or who were still alive at the time of the last follow-up were censored (+). Survival days are shown along the X axis. Overall survival rates are shown along the Y axis.

Mentions: To exemplify how these competing modules can provide insight into the pathogenesis of cancer, the BRCA sub-network comprising 95 lncRNAs, 68 miRNAs and 197 mRNAs within 132 functional modules was examined (Figure 5A). A module was identified consisting of five nodes that have all been shown experimentally to play key roles in the development of BRCA (Figure 5B). The downregulation of the lncRNA H19 significantly decreased breast cancer cell growth (14), while its overexpression enhanced the tumorigenic properties (66). The miRNAs miR-17 and miR-20 have been found to inhibit BRCA cell migration and invasion via a heterotypic secreted signal (67,68). The downstream gene thrombospondin-1, an angiogenesis inhibitor regulated by p53 and retinoblastoma was previously shown to be a serological biomarker for BRCA (69). Mitogen-activated protein (MAP)3K12, an activator of MAP kinase pathway, had distinctive patterns of somatic mutations in BRCA (70), as reported in Genes-to-Systems Breast Cancer (71). A strong inverse correlation was observed between the intermediate miRNA layer and lncRNA and mRNA layers, indicating extensive competing interactions within this module (Figure 5B). LncRNA H19 was also a hub related to five competing modules, indicating that H19 could control communication between different functional sub-networks in BRCA (Figure 5C). In another example, the lncRNA MIR22HG, which shared miRNAs with H19, was also the host gene of the miRNA hsa-miR-22 (Figure 5D). These results indicate a functional complementation between MIR22HG and H19 and a potential feedback regulation of MIR22HG by miR-22. Based on these analyses, H19-associated lncACTs likely play important regulatory roles in BRCA progression. To assess the clinical relevance of these findings, a survival analysis (Materials and Methods) was performed on an H19-associated lncACT module (Figure 5B), in which all components have been experimentally confirmed as being involved in BRCA pathogenesis. There were no differences between expression clustered two groups of patients (Supplementary Figure S13). lncACTs of two breast cancer risk genes, BRCA1 and BRCA2 which formed nine lncACTs with two miRNAs and nine lncRNAs were also found no significant results (Supplementary Figure S13). However, when expression profiles in the H19 and BRCA1/2 lncACT module (HB_module) were integrated (Figure 5E) and patients were reclassified into two groups, survival analyses indicated that these lncACTs could distinguish the two groups of patients with different clinical outcomes (Figure 5F). A univariate Cox regression analysis was carried out to evaluate association between survival and expression level of each lncRNA/miRNA/mRNA node in HB_module. BRCA2 (P = 4.43E−02) and miR-20b (P = 8.00E−03) were significantly associated with BRCA survival (Supplementary Table S5). By testing all nodes of HB_module with the risk score model (Materials and Methods), HB_module was found to be the most significant factor associated with survival (P = 3.73E−5 in Supplementary Table S5). To test whether the whole HB_module could better distinguish patients than lncRNAs/miRNAs/mRNAs and combinations thereof, Kaplan-Meier survival curves were generated of the classification based on each node of the module, integration of BRCA2 and miR-20b, H19- and BRCA1/2-associated lncACTs, and all lncRNAs, miRNAs, and coding genes (Supplementary Figure S13). HB_module distinguished BRCA patients better than the others with the most significant P value (P = 3.8E−3), suggesting that it can be used as a potential prognostic biomarker for BRCA.


Identification of lncRNA-associated competing triplets reveals global patterns and prognostic markers for cancer.

Wang P, Ning S, Zhang Y, Li R, Ye J, Zhao Z, Zhi H, Wang T, Guo Z, Li X - Nucleic Acids Res. (2015)

Sub-network analysis of competing lncACTs. (A) A BRCA-specific sub-network was derived from the global crosstalk network, which consisted of 95 lncRNAs, 68 miRNAs, 197 mRNAs and contained 132 functional modules. Two example modules are demarcated by circles. The lncRNAs, miRNAs and coding-genes are colored blue, red and yellow, respectively. The node degree is indicated by the node size. (B) One module had five nodes, all of which have been experimentally demonstrated to have key roles in the development of breast cancer. The expression heat map is shown on the right. In the heat map, highly expressed genes are shown in red, low expression genes are shown in green. (C) The lncRNA H19 was identified as a hub that connects five competing modules. (D) The lncRNA MIR22HG is functionally complementary to H19 and interacts with the same miRNAs. A genomic representation of miR-22 is shown in the red bar and MIR22HG is shown on the bottom. Predicted miR-22 target sites on MIR22HG are shown in the black bar, with detailed miRNA binding information of the site nearest to the miR-22 locus illustrated on the right. (E) Hierarchical clustering of 248 patients based on H19 and BRCA1/2 lncACT expression. (F) Kaplan-Meier survival analysis of two groups of patients with different clinical outcomes. Those that showed no progression or who were still alive at the time of the last follow-up were censored (+). Survival days are shown along the X axis. Overall survival rates are shown along the Y axis.
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Figure 5: Sub-network analysis of competing lncACTs. (A) A BRCA-specific sub-network was derived from the global crosstalk network, which consisted of 95 lncRNAs, 68 miRNAs, 197 mRNAs and contained 132 functional modules. Two example modules are demarcated by circles. The lncRNAs, miRNAs and coding-genes are colored blue, red and yellow, respectively. The node degree is indicated by the node size. (B) One module had five nodes, all of which have been experimentally demonstrated to have key roles in the development of breast cancer. The expression heat map is shown on the right. In the heat map, highly expressed genes are shown in red, low expression genes are shown in green. (C) The lncRNA H19 was identified as a hub that connects five competing modules. (D) The lncRNA MIR22HG is functionally complementary to H19 and interacts with the same miRNAs. A genomic representation of miR-22 is shown in the red bar and MIR22HG is shown on the bottom. Predicted miR-22 target sites on MIR22HG are shown in the black bar, with detailed miRNA binding information of the site nearest to the miR-22 locus illustrated on the right. (E) Hierarchical clustering of 248 patients based on H19 and BRCA1/2 lncACT expression. (F) Kaplan-Meier survival analysis of two groups of patients with different clinical outcomes. Those that showed no progression or who were still alive at the time of the last follow-up were censored (+). Survival days are shown along the X axis. Overall survival rates are shown along the Y axis.
Mentions: To exemplify how these competing modules can provide insight into the pathogenesis of cancer, the BRCA sub-network comprising 95 lncRNAs, 68 miRNAs and 197 mRNAs within 132 functional modules was examined (Figure 5A). A module was identified consisting of five nodes that have all been shown experimentally to play key roles in the development of BRCA (Figure 5B). The downregulation of the lncRNA H19 significantly decreased breast cancer cell growth (14), while its overexpression enhanced the tumorigenic properties (66). The miRNAs miR-17 and miR-20 have been found to inhibit BRCA cell migration and invasion via a heterotypic secreted signal (67,68). The downstream gene thrombospondin-1, an angiogenesis inhibitor regulated by p53 and retinoblastoma was previously shown to be a serological biomarker for BRCA (69). Mitogen-activated protein (MAP)3K12, an activator of MAP kinase pathway, had distinctive patterns of somatic mutations in BRCA (70), as reported in Genes-to-Systems Breast Cancer (71). A strong inverse correlation was observed between the intermediate miRNA layer and lncRNA and mRNA layers, indicating extensive competing interactions within this module (Figure 5B). LncRNA H19 was also a hub related to five competing modules, indicating that H19 could control communication between different functional sub-networks in BRCA (Figure 5C). In another example, the lncRNA MIR22HG, which shared miRNAs with H19, was also the host gene of the miRNA hsa-miR-22 (Figure 5D). These results indicate a functional complementation between MIR22HG and H19 and a potential feedback regulation of MIR22HG by miR-22. Based on these analyses, H19-associated lncACTs likely play important regulatory roles in BRCA progression. To assess the clinical relevance of these findings, a survival analysis (Materials and Methods) was performed on an H19-associated lncACT module (Figure 5B), in which all components have been experimentally confirmed as being involved in BRCA pathogenesis. There were no differences between expression clustered two groups of patients (Supplementary Figure S13). lncACTs of two breast cancer risk genes, BRCA1 and BRCA2 which formed nine lncACTs with two miRNAs and nine lncRNAs were also found no significant results (Supplementary Figure S13). However, when expression profiles in the H19 and BRCA1/2 lncACT module (HB_module) were integrated (Figure 5E) and patients were reclassified into two groups, survival analyses indicated that these lncACTs could distinguish the two groups of patients with different clinical outcomes (Figure 5F). A univariate Cox regression analysis was carried out to evaluate association between survival and expression level of each lncRNA/miRNA/mRNA node in HB_module. BRCA2 (P = 4.43E−02) and miR-20b (P = 8.00E−03) were significantly associated with BRCA survival (Supplementary Table S5). By testing all nodes of HB_module with the risk score model (Materials and Methods), HB_module was found to be the most significant factor associated with survival (P = 3.73E−5 in Supplementary Table S5). To test whether the whole HB_module could better distinguish patients than lncRNAs/miRNAs/mRNAs and combinations thereof, Kaplan-Meier survival curves were generated of the classification based on each node of the module, integration of BRCA2 and miR-20b, H19- and BRCA1/2-associated lncACTs, and all lncRNAs, miRNAs, and coding genes (Supplementary Figure S13). HB_module distinguished BRCA patients better than the others with the most significant P value (P = 3.8E−3), suggesting that it can be used as a potential prognostic biomarker for BRCA.

Bottom Line: In the lncACT cross-talk network, disease-associated lncRNAs, miRNAs and coding-genes showed specific topological patterns indicative of their competence and control of communication within the network.Based on the global cross-talk network and cluster analyses, nine cancer-specific sub-networks were constructed.H19- and BRCA1/2-associated lncACTs were able to discriminate between two groups of patients with different clinical outcomes.

View Article: PubMed Central - PubMed

Affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Show MeSH
Related in: MedlinePlus