Browsing by Author "Tombaz, Melike"

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Open Access
Discovery of cancer-specific and independent prognostic gene subsets of the slit-robo family using TCGA-PANCAN datasets
(Mary Ann Liebert, 2021-12-08) Özhan, Ayşe; Tombaz, Melike; Konu, Özlen
The Slit-Robo family of axon guidance molecules works in concert, playing important roles in organ devel opment and cancer. Expressions of individual Slit-Robo genes have been used in calculating univariable hazard ratios (HRuni) for predicting cancer prognosis in the literature. However, Slit-Robo members do not act in dependently; hence, hazard ratios from multivariable Cox regression (HRmulti) on the whole gene set can further lead to identification of cancer-specific, novel, and independent prognostic gene pairs or modules. Herein, we obtained mRNA expressions of the Slit-Robo family consisting of four Robos (ROBO1/2/3/4) and three Slits (SLIT1/2/3), along with four types of survival outcome across cancers found in the Cancer Genome Atlas (TCGA). We used cluster heat maps to visualize closely associated pairs/modules of prognostic genes across 33 different cancers. We found a smaller number of significant genes in HRmulti than in HRuni, suggesting that the former analysis was less redundant. High ROBO4 expression emerged as relatively protective within the family, in both types of HR analyses. Multivariable Cox regression, on the other hand, revealed significantly more HR signatures containing Slit-Robo pairs acting in opposing directions than those containing Slit-Slit or Robo-Robo pairs for disease-specific survival. Furthermore, we discovered, through the online app SmulTCan’s lasso regression, Slit-Robo gene subsets that significantly differentiated between high- versus low-risk prog nosis patient groups, particularly for renal cancers and low-grade glioma. The statistical pipeline reported herein can help test independent and significant pairs/modules within a codependent gene family for cancer prog nostication, and thus should also prove useful in personalized/precision medicine research.
Open Access
Doxorubicin induces prolonged DNA damage signal in cells overexpressing DEK isoform-2
(Public Library of Science, 2022-10-03) Özçelik, Emrah; Kalaycı, Ahmet; Çelik, Büşra; Avcı, Açelya; Akyol, Hasan; Kılıç, İrfan Baki; Güzel, Türkan; Çetin, Metin; Öztürk, Merve Tuzlakoğlu; Çalışkaner, Zihni Onur; Tombaz, Melike; Yoleri, Dilan; Konu, Özlen; Kandilci, Ayten
DEK has a short isoform (DEK isoform-2; DEK2) that lacks amino acid residues between 49–82. The full-length DEK (DEK isoform-1; DEK1) is ubiquitously expressed and plays a role in different cellular processes but whether DEK2 is involved in these processes remains elusive. We stably overexpressed DEK2 in human bone marrow stromal cell line HS-27A, in which endogenous DEKs were intact or suppressed via short hairpin RNA (sh-RNA). We have found that contrary to ectopic DEK1, DEK2 locates in the nucleus and nucleolus, causes persistent үH2AX signal upon doxorubicin treatment, and couldn’t functionally compensate for the loss of DEK1. In addition, DEK2 overexpressing cells were more sensitive to doxorubicin than DEK1-cells. Expressions of DEK1 and DEK2 in cell lines and primary tumors exhibit tissue specificity. DEK1 is upregulated in cancers of the colon, liver, and lung compared to normal tissues while both DEK1 and DEK2 are downregulated in subsets of kidney, prostate, and thyroid carcinomas. Interestingly, only DEK2 was downregulated in a subset of breast tumors suggesting that DEK2 can be modulated differently than DEK1 in specific cancers. In summary, our findings show distinct expression patterns and subcellular location and suggest non-overlapping functions between the two DEK isoforms. © 2022 Ozçelik et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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, Özlen
Regulation 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.
Open Access
Functional analysis of co-expression networks of zebrafish ace2 reveals enrichment of pathways associated with development and disease
(Canadian Science Publishing, 2022-02-02) Keşkuş, Ayşe Gökçe; Tombaz, Melike; Arıcı, Burçin İrem; Dinçaslan, Fatma Betül; Nabi, Afshan; Shehwana, Huma; Konu, Özlen
Human Angiotensin I Converting Enzyme 2 (ACE2) plays an essential role in blood pressure regulation and SARS-CoV-2 entry. ACE2 has a highly conserved, one-to-one ortholog (ace2) in zebrafish, which is an important model for human diseases. However, the zebrafish ace2 expression profile has not yet been studied during early development, between genders, across different genotypes, or in disease. Moreover, a network-based meta-analysis for the extraction of functionally enriched pathways associated with differential ace2 expression is lacking in the literature. Herein, we first identified significant development-, tissue-, genotype-, and gender-specific modulations in ace2 expression via meta-analysis of zebrafish Affymetrix transcriptomics datasets (ndatasets = 107); and the correlation analysis of ace2 meta-differential expression profile revealed distinct positively and negatively correlated local functionally enriched gene networks. Moreover, we demonstrated that ace2 expression was significantly modulated under different physiological and pathological conditions related to development, tissue, gender, diet, infection, and inflammation using additional RNA-seq datasets. Our findings implicate a novel translational role for zebrafish ace2 in organ differentiation and pathologies observed in the intestines and liver.
Open Access
Global miRNA expression of bone marrow mesenchymal stem/stromal cells derived from Fanconi anemia patients
(Springer, 2021-11-18) Cagnan, I.; Keles, M.; Keskus, Ayse Gokce; Tombaz, Melike; Sahan, O. B.; Aerts-Kaya, F.; Uckan-Cetinkaya, D.; Konu, Ozlen; Gunel-Ozcan, A.
Fanconi anemia (FA) is a rare genetic disorder characterized by genomic instability, developmental defects, and bone marrow (BM) failure. Hematopoietic stem cells (HSCs) in BM interact with the mesenchymal stem/stromal cells (MSCs); and this partly sustains the tissue homeostasis. MicroRNAs (miRNAs) can play a critical role during these interactions possibly via paracrine mechanisms. This is the first study addressing the miRNA profile of FA BM–MSCs obtained before and after BM transplantation (preBMT and postBMT, respectively). Non-coding RNA expression profiling and quality control analyses were performed in Donors (n = 13), FA preBMT (n = 11), and FA postBMT (n = 6) BM–MSCs using GeneChip miRNA 2.0 Array. Six Donor-FA preBMT pairs were used to identify a differentially expressed miRNA expression signature containing 50 miRNAs, which exhibited a strong correlation with the signature obtained from unpaired samples. Five miRNAs (hsa-miR-146a-5p, hsa-miR-148b-3p, hsa-miR-187-3p, hsa-miR-196b-5p, and hsa-miR-25-3p) significantly downregulated in both the paired and unpaired analyses were used to generate the BM–MSCs’ miRNA—BM mononuclear mRNA networks upon integration of a public dataset (GSE16334; studying Donor versus FA samples). Functionally enriched KEGG pathways included cellular senescence, miRNAs, and pathways in cancer. Here, we showed that hsa-miR-146a-5p and hsa-miR-874-3p were rescued upon BMT (n = 3 triplets). The decrease in miR-146a-5p was also validated using RT-qPCR and emerged as a strong candidate as a modulator of BM mRNAs in FA patients.
Open Access
A shiny application for pancan survival analysis with paralog/miRNA pairs and in vitro validation of miRNA synergism in liver cancer
(2022-09) Tombaz, Melike
Emerging 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.
Open Access
SmulTCan: A Shiny application for multivariable survival analysis of TCGA data with gene sets
(Elsevier Ltd, 2021-10) Özhan, Ayşe; Tombaz, Melike; Konu, Özlem
Background Survival analysis is widely used in cancer research, and although several methods exist in R, there is the need for a more interactive, flexible, yet comprehensive online tool to analyze gene sets using Cox proportional hazards (CPH) models. The web-based Shiny application (app) SmulTCan extends existing tools to multivariable CPH models of gene sets—as exemplified using the netrins and their receptors (netrins-receptors). It can be used to identify survival gene signatures (GSs) and select the best subsets of input gene, microRNA, methylation level, and copy number variation sets from the Cancer Genome Atlas (TCGA). Objectives To create a tool for CPH model building and best subset selection, using survival data from TCGA with input gene expression files from UCSC Xena. Furthermore, we aim to analyze the input TSV file of netrins-receptors in SmulTCan and discuss our findings. Methods SmulTCan uses Shiny's reactivity with built-in R functions from packages for CPH model analysis and best subset selection including “survminer”, “riskRegression”, “rms”, “glmnet”, and “BeSS”. Results Results from the SmulTCan app with the netrins-receptors gene set indicated unique hazard ratio GSs in certain renal and neural cancers, while the best subsets for this gene set, obtained via the app, could differentiate between prognostic outcomes in these cancers.