Browsing by Author "Yazar, Metin"

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Citation Count: 2
Assessment of 13 in silico pathogenicity methods on cancer-related variants
(Pergamon-elsevier Science Ltd, 2022) Yazar, Metin; Ozbek, Pemra; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
Single nucleotide variants (SNVs) are single base substitutions that could influence many biological functions in the cell including gene expression, protein folding, and protein-protein interactions among many others. Thus, predictions of functional effects of cancer-related variants are crucial for drug responses and treatment options in clinical oncology. Experimental identification of these effects could be slow, inefficient, and inconvenient, hence in silico methods are gaining popularity in predicting the variants' effects. There are many studies on the cancer variants, however, up to date, none of these have been aimed to assess the performance metrics of in silico pathogenicity methods on functional relevance of cancer variants obtained from ClinVar. To this end, we examined the pathogenicity predictions of cancer-related variant datasets of 8 cancer types (bladder, breast, colon, colorectal, kidney, liver, lung, and pancreas cancer) retrieved from ClinVar using 13 different in silico methods including SIFT, CADD, FATHMM-weighted, FATHMM-unweighted, GERP(++), MetaSVM, Mutation Assessor, MutationTaster, MutPred, PolyPhen-2, Provean, Revel and VEST4. A combination of statistical performance metric analysis, prediction distribution frequency data and ROC curve analysis results have suggested that; among all in silico prediction tools, top three tools with the highest discriminatory power were found to be MutPred (AUC = 0.677), MetaSVM (AUC = 0.645) and Revel (AUC = 0.637).
Citation Count: 5
Cancer Drug Repositioning by Comparison of Gene Expression in Humans and Axolotl (Ambystoma mexicanum) During Wound Healing
(Mary Ann Liebert, inc, 2019) Oktem, Elif Kubat; Yazar, Metin; Gulfidan, Gizem; Arga, Kazim Yalcin; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
Urodele amphibians such as the axolotl (Ambystoma mexicanum) display a large capacity for tissue regeneration and remarkable resistance to cancer. As a model organism, axolotl thus offers a unique opportunity for cancer research and anticancer drug discovery, not to mention the discerning mechanisms that underpin controlled cellular growth and regeneration versus cancer. To the best of our knowledge, little is known on comparative gene expression changes during regeneration events such as wound healing in axolotl and humans. Using publicly available transcriptomics data and bioinformatics analyses, we examined the differential gene expression signatures in skin wound samples from axolotl and humans after skin biopsy punch injury, in comparison with intact (uninjured) control skin samples. We identified 95 genes exhibiting a reversal expression pattern between humans and axolotl during the wound healing/regeneration period. These genes were significantly associated with collagen biosynthesis, extracellular matrix organization, PI3K-Akt signaling pathway, immune system response, and apoptotic process. Furthermore, this new gene set exhibited high prognostic performance in discriminating the survival risk in skin-related cancers, including melanoma (hazard ratio [HR] = 8.14, p < 10(-30)), oral cancer (HR >100, p < 10(-12)), and head and neck carcinoma (HR = 5.29, p < 10(-30)). Moreover, considering these gene signatures, we repositioned 11 small molecules as potential anticancer drug candidates indicating reversal effects on upregulated human genes and downregulated axolotl genes or mimicking downregulated human genes and upregulated axolotl genes. We anticipate that this study offers new insights on gene signatures bridging regeneration mechanisms with tumorigenesis and cancer drug repositioning.
Citation Count: 0
Computational drug repurposing for primary hyperparathyroidism
(Elsevier Ireland Ltd, 2024) Oktem, Elif Kubat; Yazar, Metin; Aysan, Erhan; Acar, Ozge Karabiyik; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
In hyperparathyroidism (hyperPTH), excessive amounts of PTH are secreted, interfering with calcium regulation in the body. Several drugs can control the disease's side effects, but none of them is an alternative treatment to surgery. Therefore, new drug candidates are necessary. In this study, three computationally repositioned drugs, DG 041, IMD 0354, and cucurbitacin I, are evaluated in an in vitro model of hyperPTH. First, we integrated publicly available transcriptomics datasets to propose drug candidates. Using 3D spheroids derived from a single primary hyperPTH patient, we assessed their in vitro efficacy. None of the proposed drugs affected the viability of healthy cell control (HEK293) or overactive parathyroid cells at the level of toxicity. This behavior was attributed to the non-cancerous nature of the parathyroid cells, establishing the hyperPTH disease model. Cucurbitacin I and IMD 0354 exhibited a slight inverse relationship between increased drug concentrations and cell viability, whereas DG 041 increased viability. Based on these results, further studies are needed on the mechanism of action of the repurposed drugs, including determining the effects of these drugs on cellular PTH synthesis and secretion and on the metabolic pathways that regulate PTH secretion.
Citation Count: 2
Drug Repositioning Identifies Six Drug Candidates for Systemic Autoimmune Diseases by Integrative Analyses of Transcriptomes from Scleroderma, Systemic Lupus Erythematosus, and Sjogren's Syndrome
(Mary Ann Liebert, inc, 2022) Oktem, Elif Kubat; Yazar, Metin; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
The mechanisms of systemic autoimmune diseases (ADs) are still not clearly understood. Understanding the etiology of systemic ADs and identifying new therapeutic targets require a systems science approach. Using publicly available transcriptome data and bioinformatic analysis, we investigated the differential gene expression profiles of patients with scleroderma, systemic lupus erythematosus, and Sjogren's syndrome. Of these common differentially expressed gene signatures, 208 were regulated in the same direction (either upregulated or downregulated in all datasets) and used for drug repositioning. Six small molecule drug candidates (KU-0063794, YM-155 [sepantronium bromide], MST-312 [telomerase inhibitor IX], PLX-4720, ZM 336372, and 528116.cdx [PIK-75]) were discovered by drug repositioning as potential therapeutics for systemic ADs. The Search Tool for Chemical Interactions was used to find the anticipated target genes of the repositioned molecules. The PI3K/AKT pathway topped the list of common enriched pathways with the most anticipated target genes of the six repositioned small molecules. We also report here the molecular docking findings on the binding affinity between the repositioned drug candidates and genes from the protein-protein interaction network modules of anticipated target genes. Taken together, this study provides new insights and opens up new possibilities on both pathogenesis and treatment of systemic ADs through drug repositioning.
Citation Count: 17
In SilicoTools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review
(Mary Ann Liebert, inc, 2021) Yazar, Metin; Ozbek, Pemra; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines thein silicotools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination ofin silicoapproaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions madein silico.
Citation Count: 3
Identification of a novel HLA-A*26 allele, HLA-A*26:01:36, in a Turkish family by sequence-based typing
(Wiley-blackwell, 2014) Sari, G.; Yazar, M.; Tozkir, H.; Duymaz, J.; Gurkan, H.; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
HLA-A*26:01:36 differs from the closest allele HLA-A*26:01:01 by a nucleotide change at the position 114.
Citation Count: 7
Increased frequency of class I and II anti-human leukocyte antigen antibodies in systemic lupus erythematosus and scleroderma and associated factors: a comparative study
(Wiley, 2016) Tozkir, Hilmi; Pamuk, Omer Nuri; Duymaz, Julide; Gurkan, Hakan; Yazar, Metin; Sari, Gulce; Pamuk, Gulsum Emel; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
Aim: There is significant autoantibody production in systemic lupus erythematosus (SLE) and scleroderma (SSc); microchimerism is also thought to play a role in pathogenesis. We determined the frequency of anti-HLA antibodies in SLE and SSc patients and evaluated associated clinical factors. Methods: We included 77 SLE patients, 46 SSc patients and 53 healthy controls into the study. Clinical data about the patients were obtained from hospital records. Anti-human leukocyte (anti-HLA) antigen antibody analysis of sera was performed by applying Lifecodes anti-HLA Class I and Class II Screening kits based on xMAP technology. Results: The frequencies of class I and II anti-HLA antibodies were significantly higher in SLE (27.3% and 41.6%) and SSc (26.1% and 41.3%) groups than in healthy controls (1.9% and 5.7%) (all P < 0.001). Frequencies of thrombocytopenia (P = 0.021), anti-ribonucleoprotein (P = 0.037) and anti-Ro (P = 0.027) were significantly higher in the class I antibody-positive SLE group; however, pericarditis was less frequent (P = 0.05). On the other hand, the class II antibody-positive SLE group had more frequent anti-ribosomal P antibody (P = 0.038), but less frequent active disease (P = 0.038). In the SSc group, class I antibody-positive patients had more frequent digital ulcers (P = 0.048) and anti-centromere antibodies (P = 0.01). There was no association of anti-HLA antibodies with pulmonary hypertension and interstitial fibrosis in SSc patients. Conclusions: Both class I and class II antibodies were found to be significantly increased in SLE and SSc. Rather than major organ involvement, anti-HLA antibodies were associated with the presence of other antibodies in both diseases.
Citation Count: 5
Integrative Analysis of Motor Neuron and Microglial Transcriptomes from SOD1^G93A Mice Models Uncover Potential Drug Treatments for ALS
(Springernature, 2022) Oktem, Elif Kubat; Aydin, Busra; Yazar, Metin; Arga, Kazim Yalcin; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
Amyotrophic lateral sclerosis (ALS) is a fatal disease of motor neurons that mainly affects the motor cortex, brainstem, and spinal cord. Under disease conditions, microglia could possess two distinct profiles, M1 (toxic) and M2 (protective), with the M2 profile observed at disease onset. SOD1 (superoxide dismutase 1) gene mutations account for up to 20% of familial ALS cases. Comparative gene expression differences in M2-protective (early) stage SOD1(G93A) microglia and age-matched SOD1(G93A) motor neurons are poorly understood. We evaluated the differential gene expression profiles in SOD1(G93A) microglia and SOD1(G93A) motor neurons utilizing publicly available transcriptomics data and bioinformatics analyses, constructed biomolecular networks around them, and identified gene clusters as potential drug targets. Following a drug repositioning strategy, 5 small compounds (belinostat, auranofin, BRD-K78930611, AZD-8055, and COT-10b) were repositioned as potential ALS therapeutic candidates that mimic the protective state of microglia and reverse the toxic state of motor neurons. We anticipate that this study will provide new insights into the ALS pathophysiology linking the M2 state of microglia and drug repositioning.
Citation Count: 1
Revisiting allostery in CREB-binding protein (CBP) using residue-based interaction energy
(Springer, 2020) Yazar, Metin; Ozbek, Pemra; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
CREB-binding protein (CBP) is a multi-subunit scaffold protein complex in transcription regulation process, binding and interacting with ligands such as mixed-lineage leukemia (MLL) and c-Myb allosterically. Here in this study, we have revisited the concept of allostery in CBP via residue-based interaction energy calculation based on molecular dynamics (MD) simulations. To this end, we conducted MD simulations of KIX:MLL:c-Myb ternary complex, its binary components and kinase-inducible domain (KID) interacting domain (KIX) backbone. Interaction energy profiles and cross correlation analysis were performed and the results indicated that KIX:MLL and KIX:c-Myb:MLL complexes demonstrate significant similarities according to both analysis methods. Two regions in the KIX backbone were apparent from the interaction energy and cross correlation maps that hold a key to allostery phenomena observed in CBP. While one of these regions are related to the ligand binding residues, the other comprises of L-12-G(2) loop and alpha(3) helix regions that have been found to have a significant role in allosteric signal propagation. All in all, residue-based interaction energy calculation method is demonstrated to be a valuable calculation technique for the detection of allosteric signal propagation and ligand interaction regions.
Citation Count: 0
Three candidate anticancer drugs were repositioned by integrative analysis of the transcriptomes of species with different regenerative abilities after injury
(Elsevier Sci Ltd, 2023) Oktem, Elif Kubat; Demir, Ummuhan; Yazar, Metin; Arga, Kazim Yalcin; Genetik ve Biyomühendislik / Genetic and Bio-Engineering
Regeneration is a homeostatic process that involves the restoration of cells and body parts. Most of the molecular mechanisms and signalling pathways involved in wound healing, such as proliferation, have also been associated with cancer cell growth, suggesting that cancer is an over/unhealed wound. In this study, we examined differentially expressed genes in spinal cord samples from regenerative organisms (axolotl and zebrafish) and nonregenerative organisms (mouse and rat) compared to intact control spinal cord samples using publicly available transcriptomics data and bioinformatics analyses. Based on these gene signatures, we investigated 3 small compounds, namely cucurbitacin I, BMS-754807, and PHA-793887 as potential candidates for the treatment of cancer. The predicted target genes of the repositioned compounds were mainly enriched with the greatest number of genes in cancer pathways. The molecular docking results on the binding affinity between the repositioned compounds and their target genes are also reported. The repositioned 3 small compounds showed anticancer effect both in 2D and 3D cell cultures using the prostate cancer cell line as a model. We propose cucurbitacin I, BMS-754807, and PHA-793887 as potential anticancer drug candidates. Future studies on the mechanisms associated with the revealed gene signatures and anticancer effects of these three small compunds would allow scientists to develop therapeutic approaches to combat cancer. This research contributes to the evaluation of mechanisms and gene signatures that either limit or cause cancer, and to the development of new cancer therapies by establishing a link between regeneration and carcinogenesis.