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Dysregulation of the vascular endothelial growth factor and semaphorin ligand-receptor families in prostate cancer metastasis.

Bender RJ, Mac Gabhann F - BMC Syst Biol (2015)

Bottom Line: We found pro-lymphangiogenic signatures, including the genes encoding VEGFC and VEGFD, associated with primary tumors that ultimately became aggressive.To leverage our mechanistic understanding, and to link multigene expression changes to outcomes, we performed individualized computational simulations of competitive VEGF and Sema receptor binding across many tumor samples.Therapeutic inhibition of angiogenesis in metastatic prostate cancer should account for both of these routes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA. bender.rj@gmail.com.

ABSTRACT

Background: The vascular endothelial growth factor (VEGF) family is central to cancer angiogenesis. However, targeting VEGF as an anti-cancer therapeutic approach has shown success for some tumor types but not others. Here we examine the expression of the expanded VEGF family in prostate cancer, including the Semaphorin (Sema) family members that compete with VEGFs for Neuropilin binding and can themselves have pro- or anti-angiogenic activity.

Results: First, we used multivariate statistical methods, including partial least squares and clustering, to examine VEGF/Sema gene expression variability in previously published prostate cancer microarray datasets. We show that unlike some cancers, such as kidney cancer, primary prostate cancer is characterized by both a down-regulation of the pro-angiogenic members of the VEGF family and a down-regulation of anti-angiogenic members of the Sema family. We found pro-lymphangiogenic signatures, including the genes encoding VEGFC and VEGFD, associated with primary tumors that ultimately became aggressive. In contrast to primary prostate tumors, prostate cancer metastases showed increased expression of key pro-angiogenic VEGF family members and further repression of anti-angiogenic class III Sema family members. Given the lack of success of VEGF-targeting molecules so far in prostate cancer, this suggests that the reduction in anti-angiogenic Sema signaling may potentiate VEGF signaling and even promote resistance to VEGF-targeting therapies. Inhibition of the VEGF 'accelerator' may need to be accompanied by promotion of the Sema 'brake' to block cancer angiogenesis. To leverage our mechanistic understanding, and to link multigene expression changes to outcomes, we performed individualized computational simulations of competitive VEGF and Sema receptor binding across many tumor samples. The simulations suggest that loss of Sema expression promotes angiogenesis by lowering plexin signaling, not by potentiating VEGF signaling via relaxation of competition.

Conclusions: The combined analysis of bioinformatic data with computational modeling of ligand-receptor interactions demonstrated that enhancement of angiogenesis in prostate cancer metastases may occur through two different routes: elevation of VEGFA and reduction of class 3 Semaphorins. Therapeutic inhibition of angiogenesis in metastatic prostate cancer should account for both of these routes.

No MeSH data available.


Related in: MedlinePlus

Intra-patient variability of metastases is low relative to inter-patient variability. a Many genes have consistent alterations in metastatic samples from the same patient while variable expression patterns between patients are more common. Blue box plots indicate the range of expression in the 21 normal samples, with the upper and lower ends of the boxes corresponding to the third and first quartiles of the data, respectively. The numbers along the x-axis indicate to which patient the dots above correspond. b Consensus K-means clustering of GSE38241 metastases according to VEGF/Sema expression shows a consistent co-clustering pattern for 5 clusters. Dark blue indicates a high frequency of co-clustering between consensus runs, while white indicates no co-clustering. Colors at the top and left indicate the patient from which each metastatic sample was taken. c Heatmap of gene expression across 18 GSE38241 metastases. The mean expression of each gene in the normal prostate tissue samples is subtracted from the expression of each gene in the metastases so that the heatmap shows up/downregulation relative to normal. Only the most variable of the VEGF/Sema genes are displayed. Dashed lines separate clusters, and colors at the top correspond to patients as in b. d-e: As for b and c, but with the set of 85 angiogenesis-related genes
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Fig4: Intra-patient variability of metastases is low relative to inter-patient variability. a Many genes have consistent alterations in metastatic samples from the same patient while variable expression patterns between patients are more common. Blue box plots indicate the range of expression in the 21 normal samples, with the upper and lower ends of the boxes corresponding to the third and first quartiles of the data, respectively. The numbers along the x-axis indicate to which patient the dots above correspond. b Consensus K-means clustering of GSE38241 metastases according to VEGF/Sema expression shows a consistent co-clustering pattern for 5 clusters. Dark blue indicates a high frequency of co-clustering between consensus runs, while white indicates no co-clustering. Colors at the top and left indicate the patient from which each metastatic sample was taken. c Heatmap of gene expression across 18 GSE38241 metastases. The mean expression of each gene in the normal prostate tissue samples is subtracted from the expression of each gene in the metastases so that the heatmap shows up/downregulation relative to normal. Only the most variable of the VEGF/Sema genes are displayed. Dashed lines separate clusters, and colors at the top correspond to patients as in b. d-e: As for b and c, but with the set of 85 angiogenesis-related genes

Mentions: The metastasis samples in the GSE38241 dataset included three to four metastases per patient from five different patients, providing the opportunity to analyze VEGF/Sema gene expression in both inter- and intra-patient contexts. We observed a high degree of consistency between metastases from the same patient, with VEGFA consistently up-regulated and several class 3 semaphorins, KDR, and NRP2 consistently down-regulated (Fig. 4a; the numbers 16, 17, 21, 22, and 30 on the x-axis correspond to different patients). Some genes that were not significantly altered when comparing all metastases to normal samples did show patient-specific alterations: VEGFC and SEMA6A were up-regulated in some metastases and down-regulated in others. SEMA6A was consistent within patients, while VEGFC was not.Fig. 4


Dysregulation of the vascular endothelial growth factor and semaphorin ligand-receptor families in prostate cancer metastasis.

Bender RJ, Mac Gabhann F - BMC Syst Biol (2015)

Intra-patient variability of metastases is low relative to inter-patient variability. a Many genes have consistent alterations in metastatic samples from the same patient while variable expression patterns between patients are more common. Blue box plots indicate the range of expression in the 21 normal samples, with the upper and lower ends of the boxes corresponding to the third and first quartiles of the data, respectively. The numbers along the x-axis indicate to which patient the dots above correspond. b Consensus K-means clustering of GSE38241 metastases according to VEGF/Sema expression shows a consistent co-clustering pattern for 5 clusters. Dark blue indicates a high frequency of co-clustering between consensus runs, while white indicates no co-clustering. Colors at the top and left indicate the patient from which each metastatic sample was taken. c Heatmap of gene expression across 18 GSE38241 metastases. The mean expression of each gene in the normal prostate tissue samples is subtracted from the expression of each gene in the metastases so that the heatmap shows up/downregulation relative to normal. Only the most variable of the VEGF/Sema genes are displayed. Dashed lines separate clusters, and colors at the top correspond to patients as in b. d-e: As for b and c, but with the set of 85 angiogenesis-related genes
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4559909&req=5

Fig4: Intra-patient variability of metastases is low relative to inter-patient variability. a Many genes have consistent alterations in metastatic samples from the same patient while variable expression patterns between patients are more common. Blue box plots indicate the range of expression in the 21 normal samples, with the upper and lower ends of the boxes corresponding to the third and first quartiles of the data, respectively. The numbers along the x-axis indicate to which patient the dots above correspond. b Consensus K-means clustering of GSE38241 metastases according to VEGF/Sema expression shows a consistent co-clustering pattern for 5 clusters. Dark blue indicates a high frequency of co-clustering between consensus runs, while white indicates no co-clustering. Colors at the top and left indicate the patient from which each metastatic sample was taken. c Heatmap of gene expression across 18 GSE38241 metastases. The mean expression of each gene in the normal prostate tissue samples is subtracted from the expression of each gene in the metastases so that the heatmap shows up/downregulation relative to normal. Only the most variable of the VEGF/Sema genes are displayed. Dashed lines separate clusters, and colors at the top correspond to patients as in b. d-e: As for b and c, but with the set of 85 angiogenesis-related genes
Mentions: The metastasis samples in the GSE38241 dataset included three to four metastases per patient from five different patients, providing the opportunity to analyze VEGF/Sema gene expression in both inter- and intra-patient contexts. We observed a high degree of consistency between metastases from the same patient, with VEGFA consistently up-regulated and several class 3 semaphorins, KDR, and NRP2 consistently down-regulated (Fig. 4a; the numbers 16, 17, 21, 22, and 30 on the x-axis correspond to different patients). Some genes that were not significantly altered when comparing all metastases to normal samples did show patient-specific alterations: VEGFC and SEMA6A were up-regulated in some metastases and down-regulated in others. SEMA6A was consistent within patients, while VEGFC was not.Fig. 4

Bottom Line: We found pro-lymphangiogenic signatures, including the genes encoding VEGFC and VEGFD, associated with primary tumors that ultimately became aggressive.To leverage our mechanistic understanding, and to link multigene expression changes to outcomes, we performed individualized computational simulations of competitive VEGF and Sema receptor binding across many tumor samples.Therapeutic inhibition of angiogenesis in metastatic prostate cancer should account for both of these routes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA. bender.rj@gmail.com.

ABSTRACT

Background: The vascular endothelial growth factor (VEGF) family is central to cancer angiogenesis. However, targeting VEGF as an anti-cancer therapeutic approach has shown success for some tumor types but not others. Here we examine the expression of the expanded VEGF family in prostate cancer, including the Semaphorin (Sema) family members that compete with VEGFs for Neuropilin binding and can themselves have pro- or anti-angiogenic activity.

Results: First, we used multivariate statistical methods, including partial least squares and clustering, to examine VEGF/Sema gene expression variability in previously published prostate cancer microarray datasets. We show that unlike some cancers, such as kidney cancer, primary prostate cancer is characterized by both a down-regulation of the pro-angiogenic members of the VEGF family and a down-regulation of anti-angiogenic members of the Sema family. We found pro-lymphangiogenic signatures, including the genes encoding VEGFC and VEGFD, associated with primary tumors that ultimately became aggressive. In contrast to primary prostate tumors, prostate cancer metastases showed increased expression of key pro-angiogenic VEGF family members and further repression of anti-angiogenic class III Sema family members. Given the lack of success of VEGF-targeting molecules so far in prostate cancer, this suggests that the reduction in anti-angiogenic Sema signaling may potentiate VEGF signaling and even promote resistance to VEGF-targeting therapies. Inhibition of the VEGF 'accelerator' may need to be accompanied by promotion of the Sema 'brake' to block cancer angiogenesis. To leverage our mechanistic understanding, and to link multigene expression changes to outcomes, we performed individualized computational simulations of competitive VEGF and Sema receptor binding across many tumor samples. The simulations suggest that loss of Sema expression promotes angiogenesis by lowering plexin signaling, not by potentiating VEGF signaling via relaxation of competition.

Conclusions: The combined analysis of bioinformatic data with computational modeling of ligand-receptor interactions demonstrated that enhancement of angiogenesis in prostate cancer metastases may occur through two different routes: elevation of VEGFA and reduction of class 3 Semaphorins. Therapeutic inhibition of angiogenesis in metastatic prostate cancer should account for both of these routes.

No MeSH data available.


Related in: MedlinePlus