Although glioblastomas are common, there remains a need to elucidate the underlying mechanisms behind their initiation and progression and identify molecular pathways for improving treatment. In this study, sixteen fresh-frozen glioblastoma samples and seven samples of healthy brain tissues were analyzed with miRNA and whole transcriptome microarray chips. Candidate miRNAs and mRNAs were selected to validate expression in fifty patient samples in total with the criteria of abundance, relevance and prediction scores. miRNA and target mRNA relationships were assessed by inhibiting selected miRNAs in glioblastoma cells. Functional tests have been conducted in order to see the effects of miRNAs on invasion, migration and apoptosis of GBM cells. Analyses were carried out to determine correlations between selected molecules and clinicopathological features. 1332 genes and 319 miRNAs were found to be dysregulated by the microarrays. The results were combined and analyzed with Transcriptome Analysis Console 3 software and the DAVID online database. Primary differential pathways included Ras, HIF-1, MAPK signaling and cell adhesion. OncomiR candidates 21-5p, 92b-3p, 182-5p and 339-5p for glioblastoma negatively correlated with notable mRNA targets both in tissues and in in vitro experiments. miR-21-5p and miR-339-5p significantly affected migration, invasion and apoptosis of GBM cells in vitro. Significant correlations with overall survival, tumor volume, recurrence and age at diagnosis were discovered. In this article we present valuable integrated microarray analysis of glioblastoma samples regarding miRNA and gene-expression levels. Notable biomarkers and miRNA-mRNA interactions have been identified, some of which correlated with clinicopathological features in our cohort.

Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.

Despite the availability of various treatment protocols, response to therapy in patients with Acute Myeloid Leukemia (AML) remains largely unpredictable. Transcriptomic profiling studies have thus far revealed the presence of molecular subtypes of AML that are not accounted for by standard clinical parameters or by routinely used biomarkers. Such molecular subtypes of AML are predicted to vary in response to chemotherapy or targeted therapy. The Renin-Angiotensin System (RAS) is an important group of proteins that play a critical role in regulating blood pressure, vascular resistance and fluid/electrolyte balance. RAS pathway genes are also known to be present locally in tissues such as the bone marrow, where they play an important role in leukemic hematopoiesis. In this study, we asked if the RAS genes could be utilized to predict drug responses in patients with AML. We show that the combined in silico analysis of up to five RAS genes can reliably predict sensitivity to Doxorubicin as well as Etoposide in AML. The same genes could also predict sensitivity to Doxorubicin when tested in vitro. Additionally, gene set enrichment analysis revealed enrichment of TNF-alpha and type-I IFN response genes among sensitive, and TGF-beta and fibronectin related genes in resistant cancer cells. However, this does not seem to reflect an epithelial to mesenchymal transition per se. We also identified that RAS genes can stratify patients with AML into subtypes with distinct prognosis. Together, our results demonstrate that genes present in RAS are biomarkers for drug sensitivity and the prognostication of AML.

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancers. Known risk factors for this disease are currently insufficient in predicting mortality. In order to better prognosticate patients with PDAC, we identified 20 genes by utilizing publically available high-throughput transcriptomic data from GEO, TCGA and ICGC which are associated with overall survival and event-free survival. A score generated based on the expression matrix of these genes was validated in two independent cohorts. We find that this "Pancreatic cancer prognostic score 20-PPS20" is independent of the confounding factors in multivariate analyses, is dramatically elevated in metastatic tissue compared to primary tumor, and is higher in primary tumors compared to normal pancreatic tissue. Transcriptomic analyses show that tumors with low PPS20 have overall more immune cell infiltration and a higher CD8 T cell/Treg ratio when compared to those with high PPS20. Analyses of proteomic data from TCGA PAAD indicated higher levels of Cyclin B1, RAD51, EGFR and a lower E-cadherin/Fibronectin ratio in tumors with high PPS20. The PPS20 score defines not only prognostic and biological subgroups but can predict response to targeted therapy as well. Overall, PPS20 is a stronger and more robust transcriptomic signature when compared to similar, previously published gene lists.

Cancer-testis (CT) genes are expressed in various cancers but not in normal tissues other than in cells of the germline. Although DNA demethylation of promoter-proximal CpGs of CT genes is linked to their expression in cancer, the mechanisms leading to demethylation are unknown. To elucidate such mechanisms we chose to study the Caco-2 colorectal cancer cell line during the course of its spontaneous differentiation in vitro, as we found CT genes, in particular PAGE2, -2B and SPANX-B, to be up-regulated during this process. Differentiation of these cells resulted in a mesenchymal-to-epithelial transition (MET) as evidenced by the gain of epithelial markers CDX2, Claudin-4 and E-cadherin, and a concomitant loss of mesenchymal markers Vimentin, Fibronectin-1 and Transgelin. PAGE2 and SPAN-X up-regulation was accompanied by an increase in Ten-eleven translocation-2 (TET2) expression and cytosine 5-hydroxymethylation as well as the disassociation of heterochromatin protein 1 and the polycomb repressive complex 2 protein EZH2 from promoter-proximal regions of these genes. Reversal of differentiation resulted in down-regulation of PAGE2, -2B and SPANX-B, and induction of epithelial-to-mesenchymal transition (EMT) markers, demonstrating the dynamic nature of CT gene regulation in this model.