Browsing by Subject "Gene network"
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Item Open Access Extraction and prioritization of a gene-cancer-by-survival network involved in homeostasis of intracellular calcium concentrations using TCGA PANCAN data(Mary Ann Liebert, Inc. Publishers, 2022-05-26) Tombaz, Melike; Yanyatan, Çağdaş; Keşküş, Ayşe Gökçe; Konu, ÖzlenRegulation of intracellular calcium concentrations, [Ca++]i is important in maintaining the viability of normal as well as cancer cells and can be mediated by tumor microenvironment. Calcium release-activated calcium channel protein (ORAI) calcium channels on the plasma membrane (PM) become physically connected by stromal interaction molecules (STIMs) to the endoplasmic reticulum (ER), on which paralogous receptors of inositol phosphate and of ryanodine are also present along with ATP2A/SERCA (sarco/endoplasmic reticulum calcium ATPases) subunits (also known as PM-ER geneset). Proper expression of this functionally and physically interconnected geneset is essential for the maintenance of [Ca++]i, yet has not been interrogated as a whole for its role in cancer prognosis using multivariable Cox regression. In the present study, we examined whether the expression profile of the PM-ER geneset exhibited prognostic significance across different cancers found in The Cancer Genome Atlas (TCGA) by generating gene-cancer-by-survival networks, in which the nodes represented either genes or cancers and the edges, the logarithmically transformed hazard ratios for overall survival (OS). We then applied network clustering to identify the gene-cancer subnetworks with high connectivity, among which uveal melanoma (UVM) emerged exhibiting the highest degree of genes (k = 10). BAP1, a well-known [Ca++]i regulator and a tumor suppressor, was not found to be significant in predicting OS by PM-ER geneset for UVM, yet it was for several others, including mesothelioma (MESO). Moreover, the best subset of the PM-ER geneset obtained by lasso predicted OS in the TCGA UVM cohort with an area under the receiver operating characteristics (AUC) of 91.4%, comparable to or better than previous prognostic signatures in the literature. Our findings indicate that homeostasis of [Ca++]i is an essential determinant of prognosis in multiple cancers and particularly in UVM. The proposed gene-cancer-by-survival network approach can be extended with other gene sets as well as different survival types.Item Open Access A shiny application for pancan survival analysis with paralog/miRNA pairs and in vitro validation of miRNA synergism in liver cancer(Bilkent University, 2022-09) Tombaz, MelikeEmerging cancer survival tools can predict risk of disease and identify prognostic biomarkers. Multivariable Cox proportional hazards models with mRNA and microRNAs (miRNAs) expression can differentiate survival outcomes. Previous studies showed that genes that belong to the same pathways/families may act independently, and in a cancer-specific manner. In this thesis, cancer-dependent hazard ratios of paralog genes and sense-antisense strands of miRNAs were tested for TCGA PANCAN. The results were presented in a R/Shiny web application that provides gene-by-survival networks. The gene-by-survival network approach also was applied to the plasma membrane-endoplasmic reticulum (PM-ER) calcium channel geneset. Among paralogs, cancer-specific prognostic signatures and functional compartmentalization were observed. Some cancers like UVM, MESO emerged as hub cancers for PM-ER signalling. Further the proposed gene-by-survival network approach has been extended for miRNA-mRNA triplets that may act in synergy in hepatocellular carcinoma (HCC). Next, the effects of synergistic miRNA pairs provided by miRCoop algorithm were tested on cell viability and target gene expression for selected triplets. The results have revealed that the combinatorial miRNA treatments show promising results as RNAi therapeutics yet future studies with different doses and triplets are needed.