August 21, 2018

status: publishe

The VEGF pathway and the AKT/mTOR/p70S6K1 signalling pathway in human epithelial ovarian cancer

Vascular endothelial growth factor (VEGF)-A inhibitors exhibit unseen high responses and toxicity in recurrent epithelial ovarian cancer suggesting an important role for the VEGF/VEGFR pathway. We studied the correlation of VEGF signalling and AKT/mTOR signalling. Using a tissue microarray of clinical samples (N=86), tumour cell immunohistochemical staining of AKT/mTOR downstream targets, pS6 and p4E-BP1, together with tumour cell staining of VEGF-A and pVEGFR2 were semi-quantified. A correlation was found between the marker for VEGFR2 activation (pVEGFR2) and a downstream target of AKT/mTOR signalling (pS6) (R=0.29; P=0.002). Additional gene expression analysis in an independent cDNA microarray dataset (N=24) showed a negative correlation (R=−0.73, P<0.0001) between the RPS6 and the VEGFR2 gene, which is consistent as the gene expression and phosphorylation of S6 is inversely regulated. An activated tumour cell VEGFR2/AKT/mTOR pathway was associated with increased incidence of ascites (χ2, P=0.002) and reduced overall survival of cisplatin–taxane-based patients with serous histology (N=32, log-rank test, P=0.04). These data propose that VEGF-A signalling acts on tumour cells as a stimulator of the AKT/mTOR pathway. Although VEGF-A inhibitors are classified as anti-angiogenic drugs, these data suggest that the working mechanism has an important additional modality of targeting the tumour cells directly

Array-Based DNA Methylation Profiling for Breast Cancer Subtype Discrimination

BACKGROUND: Abnormal DNA methylation is well established for breast cancer and contributes to its progression by silencing tumor suppressor genes. DNA methylation profiling platforms might provide an alternative approach to expression microarrays for accurate breast tumor subtyping. We sought to determine whether the distinction of the inflammatory breast cancer (IBC) phenotype from the non-IBC phenotype by transcriptomics could be sustained by methylomics. METHODOLOGY/PRINCIPAL FINDINGS: We performed methylation profiling on a cohort of IBC (N = 19) and non-IBC (N = 43) samples using the Illumina Infinium Methylation Assay. These results were correlated with gene expression profiles. Methylation values allowed separation of breast tumor samples into high and low methylation groups. This separation was significantly related to DNMT3B mRNA levels. The high methylation group was enriched for breast tumor samples from patients with distant metastasis and poor prognosis, as predicted by the 70-gene prognostic signature. Furthermore, this tumor group tended to be enriched for IBC samples (54% vs. 24%) and samples with a high genomic grade index (67% vs. 38%). A set of 16 CpG loci (14 genes) correctly classified 97% of samples into the low or high methylation group. Differentially methylated genes appeared to be mainly related to focal adhesion, cytokine-cytokine receptor interactions, Wnt signaling pathway, chemokine signaling pathways and metabolic processes. Comparison of IBC with non-IBC led to the identification of only four differentially methylated genes (TJP3, MOGAT2, NTSR2 and AGT). A significant correlation between methylation values and gene expression was shown for 4,981 of 6,605 (75%) genes. CONCLUSIONS/SIGNIFICANCE: A subset of clinical samples of breast cancer was characterized by high methylation levels, which coincided with increased DNMT3B expression. Furthermore, an association was observed with molecular signatures indicative of poor patient prognosis. The results of the current study also suggest that aberrant DNA methylation is not the main force driving the molecular biology of IBC