Browsing by Subject "Survival"
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Item Open Access Estimation of a change point in a hazard function based on censored data(Springer New York LLC, 2003) Gijbels, I.; Gürler, Ü.The hazard function plays an important role in reliability or survival studies since it describes the instantaneous risk of failure of items at a time point, given that they have not failed before. In some real life applications, abrupt changes in the hazard function are observed due to overhauls, major operations or specific maintenance activities. In such situations it is of interest to detect the location where such a change occurs and estimate the size of the change. In this paper we consider the problem of estimating a single change point in a piecewise constant hazard function when the observed variables are subject to random censoring. We suggest an estimation procedure that is based on certain structural properties and on least squares ideas. A simulation study is carried out to compare the performance of this estimator with two estimators available in the literature: an estimator based on a functional of the Nelson-Aalen estimator and a maximum likelihood estimator. The proposed least squares estimator turns out to be less biased than the other two estimators, but has a larger variance. We illustrate the estimation method on some real data sets.Item Open Access Expression of IFITM1 in chronic myeloid leukemia patients(Elsevier, 2005) Akyerli, C. B.; Beksac, M.; Holko, M.; Frevel, M.; Dalva, K.; Özbek, U.; Soydan, E.; Özcan, M.; Özet, G.; İlhan, O.; Gürman, G.; Akan, H.; Williams, B. R. G.; Özçelik, T.We investigated the peripheral blood gene expression profile of interferon induced transmembrane protein 1 (IFITM1) in sixty chronic myeloid leukemia (CML) patients classified according to new prognostic score (NPS). IFITM1 is a component of a multimeric complex involved in the trunsduction of antiproliferative and cell adhesion signals. Expression level of IFITM1 was found significantly different between the high- and low-risk groups (P = 9.7976 × 10-11) by real-time reverse transcription polymerase chain reaction (RT-PCR). Higher IFITM1 expression correlated with improved survival (P = 0.01). These results indicate that IFITM1 expression profiling could be used for molecular classification of CML, which may also predict survival.Item Open Access Immunomodulatory function and in vivo properties of pediococcus pentosaceus OZF, a promising probiotic strain(Springer, 2013) Osmanagaoglu, O.; Kiran, F.; Yagci, F. C.; Gursel, I.Some of the important properties of probiotics are the ability to survive during gastrointestinal transit and to modulate the immune functions. The objectives of the reported study were to assess in vivo gastrointestinal survival of orally administered Pediococcus pentosaceus OZF using an animal model BALB/c mice, and to examine its effects on the immune response. Following oral administration to mice, the ability of Pediococcus pentosaceus OZF to pass and survive through the mouse gastrointestinal system was investigated by analyzing the recovery of the strain in fecal samples. Microbiological and polymerase chain reaction (PCR) methods proved that the strain OZF could overcome specific conditions in the gastrointestinal tract of mice and reach the intestine alive after ingestion. To observe the effect of oral administration on immune response, IL-6, IL-12 and IFN-γ were measured by ELISA, and the strain OZF was found to cause increases in IL-6 synthesis in regularly fed mice. However, stimulation was carried out with various concentrations of bacterial ssDNA and heat killed cells of Pediococcus pentosaceus OZF. The heat killed cells of the strain OZF were shown to produce IFN- γ independently from IL-12. On the other hand, a significant difference between control and experimental group was noticed when lipopolysaccharide, a TLR4 (toll like receptor) ligand, was used. Overall, Pediococcus pentosaceus OZF may be a valuable probiotic strain for therapeutic uses. Nevertheless, further studies on the mechanisms of immunomodulatory effect will allow for better clarification of the immune functions of this strain. © Springer-Verlag Berlin Heidelberg and the University of Milan 2012.Item Open Access Prognostic biomarker identification and classification of colorectal cancer patients: a dual gene-based and sample-based approach(Bilkent University, 2023-08) Naeemaee, RonakColorectal cancer (CRC) is one of the most heterogeneous cancer types, with high mortality rates making it the one of the deadliest cancer among men and women. The heterogeneity of CRC comes from the numerous clinicopathological characteristics of these tumors, including; KRAS/BRAF mutation, Microsatellite Instability (MSI), and stage. Another essential factor recently emphasized is the tumor location (proximal or distal). Consequently, many studies have focused on finding prognostic biomarkers for CRC patients to increase the efficiency of their treatment plans. However, despite the attempts, these biomarkers fail in clinical transition as they lack robustness and consistent results in their validation studies. Moreover, understanding the mechanism behind CRC progression can significantly help the personalization of treatments. Recently, the cancer neuroscience field has been focusing on elucidating neuropeptides' role in cancer and CRC as they have been proven to be involved in cancer progression. Accordingly, the thesis was divided into two approaches. The first approach was to further examine the role of neuropeptides by finding a subset of neuropeptides for the classification of the CRC samples and following functional analysis to understand the mechanism of their involvement. Moreover, the second approach attempted the determination of robust prognostic biomarkers in a specific sample group (Proximal, Stages 2 and 3) while controlling for the inconsistencies. In the first approach, a subset of 9 neuropeptide genes was found through Principle Component Analysis (PCA) with the ability to stratify the CRC samples into high and low expression groups. Functional analyses of these groups identified an association between the up-regulation of these neuropeptides and Hedgehog's (HHG) signaling pathway, and these activities are hypothesized to be primarily specific to the stroma of the tumor. Up-regulation of these neuropeptides was also linked with other pathways involved in cancer progression, such as; EMT, angiogenesis, and TGFβ activities. The second approach utilized a new methodology pipeline that aimed to ensure the selection of genes with no discrepancies among their probesets and across different technologies. Following the pipeline, 3 genes were identified, associated with favorable and non-favorable prognoses for Proximal, Stage 2, and 3 samples. However, although a very stringent methodology was used and various clinicopathological parameters such as the stage and location were considered, the prognostic associations observed were not as consistent, indicating the importance of the sample's molecular characteristics. This study also pointed out potential implications of neuropeptides in CRC progression and development. More elaborative studies are required for the clarification of the interactions of neuropeptides with the HHG signaling pathway. Furthermore, the identified prognostic biomarkers need to be validated through comprehensive validation studies in their associating subgroups of samples, as they are robust biomarkers with the potential to be used in clinics.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.Item Open Access Simultaneous miRNA and mRNA transcriptome profiling of glioblastoma samples reveals a novel set of OncomiR candidates and their target genes(Elsevier, 2018) Güllüoğlu, Ş.; Tüysüz, E. C.; Şahin, M.; Kuşkucu, A.; Yaltırık, C. K.; Türe, U.; Küçükkaraduman, Barış; Akbar, Muhammad Waqas; Güre, Ali Osmay; Bayrak, Ö. F.; Dalan, A. B.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.Item 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, ÖzlemBackground 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.Item Open Access Survival analysis and its applications in identifying genes, signatures, and pathways in human cancers(Bilkent University, 2021-09) Özhan, AyşeCancer literature makes use of survival analyses focused on gene expression based on univariable or multivariable regression. However, there is still a need to understand whether a) incorporating exon or isoform information on expression would improve estimation of survival in cancer patients; and b) applying multivariable regression to gene sets would allow to obtain cancer-specific independent gene signatures in cancer. Differential usage of individual exons, as well as transcripts, are phenomena common to cancerous tissue when compared to normal tissue. The glioblastoma, GBM; liver cancer LIHC; stomach adenocarcinoma, STAD; and breast carcinoma, BRCA datasets from The Cancer Genome Atlas (TCGA) were investigated to identify individual exons and transcripts with transcriptome-wide impact and significance on survival. Aggregation analyses of exons revealed the important genes for survival in each dataset, including GNA12 in STAD, AKAP13 in LIHC and RBMXL1 and CARS1 in BRCA. GSEA was applied on gene sets formed from the exon-based analysis, revealing distinct enrichment profiles for each dataset as well as overlaps for certain GO terms and KEGG pathways. In the second focus of this thesis, multivariable analyses on gene sets whose expressions were obtained from UCSC Xena were used to create two Shiny applications: one for dataset-specific analyses and one for analyses across TCGA-PANCAN. The dataset specific SmulTCan application incorporates Cox regression analyses with expressions of input genes of the user’s choice. The SmulTCan application contains additional model validation, best subset selection and prognostic analyses. The ClusterHR application performs clustering analyses with Cox regression results, while it can also be used for bicluster identification and comparison. The axon-guidance ligand-receptor gene sets Slit-Robo, netrins-receptors and Semas-receptors were used for demonstrating the apps. Several hazard ratio signatures and best subsets that can differentiate between prognostic outcomes have been identified from the input gene sets, as well as ligand-receptor pairs with prognostic significance.