Dayanç, Barış Emre
Loading...
Profile URL
Name Variants
Dayanc, B. E.
Dayanc, BE
Dayanc, Emre
Dayanc, Baris E.
Dayanc, Baris Emre
Dayanc, BE
Dayanc, Emre
Dayanc, Baris E.
Dayanc, Baris Emre
Job Title
Email Address
emre.dayanc@ieu.edu.tr
edayanc@mit.edu
edayanc@mit.edu
Main Affiliation
09.01. Basic Medical Sciences
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
0
Research Products
3GOOD HEALTH AND WELL-BEING
5
Research Products
4QUALITY EDUCATION
0
Research Products
5GENDER EQUALITY
0
Research Products
6CLEAN WATER AND SANITATION
0
Research Products
7AFFORDABLE AND CLEAN ENERGY
0
Research Products
8DECENT WORK AND ECONOMIC GROWTH
0
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
10REDUCED INEQUALITIES
0
Research Products
11SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
12RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
13CLIMATE ACTION
1
Research Products
14LIFE BELOW WATER
0
Research Products
15LIFE ON LAND
0
Research Products
16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
17PARTNERSHIPS FOR THE GOALS
0
Research Products

Documents
9
Citations
557
h-index
6

Documents
13
Citations
517

Scholarly Output
7
Articles
5
Views / Downloads
44/166
Supervised MSc Theses
1
Supervised PhD Theses
0
WoS Citation Count
28
Scopus Citation Count
27
Patents
0
Projects
1
WoS Citations per Publication
4.00
Scopus Citations per Publication
3.86
Open Access Source
5
Supervised Theses
1
| Journal | Count |
|---|---|
| Turkish Journal of Biology | 2 |
| European Journal of Immunology | 1 |
| Expert Reviews in Molecular Medicine | 1 |
| Internatıonal Journal of Pharmacology | 1 |
| Journal of Cancer | 1 |
Current Page: 1 / 1
Scopus Quartile Distribution
Competency Cloud

7 results
Scholarly Output Search Results
Now showing 1 - 7 of 7
Article Citation - WoS: 26Citation - Scopus: 25A Combined Ulbp2 and Sema5a Expression Signature as a Prognostic and Predictive Biomarker for Colon Cancer(Ivyspring Int Publ, 2017) Demirkol, Secil; Gomceli, Ismail; Isbilen, Murat; Dayanc, Baris Emre; Tez, Mesut; Bostanci, Erdal Birol; Turhan, NesrinBackground: Prognostic biomarkers for cancer have the power to change the course of disease if they add value beyond known prognostic factors, if they can help shape treatment protocols, and if they are reliable. The aim of this study was to identify such biomarkers for colon cancer and to understand the molecular mechanisms leading to prognostic stratifications based on these biomarkers. Methods and Findings: We used an in house R based script (SSAT) for the in silico discovery of stage-independent prognostic biomarkers using two cohorts, GSE17536 and GSE17537, that include 177 and 55 colon cancer patients, respectively. This identified 2 genes, ULBP2 and SEMA5A, which when used jointly, could distinguish patients with distinct prognosis. We validated our findings using a third cohort of 48 patients ex vivo. We find that in all cohorts, a combined ULBP2/SEMA5A classification (SU-GIB) can stratify distinct prognostic sub-groups with hazard ratios that range from 2.4 to 4.5 (p <= 0.01) when overall-or cancer-specific survival is used as an end-measure, independent of confounding prognostic parameters. In addition, our preliminary analyses suggest SU-GIB is comparable to Oncotype DX colon (R) in predicting recurrence in two different cohorts (HR: 1.5-2; p <= 0.02). SU-GIB has potential as a companion diagnostic for several drugs including the PI3K/mTOR inhibitor BEZ235, which are suitable for the treatment of patients within the bad prognosis group. We show that tumors from patients with worse prognosis have low EGFR autophosphorylation rates, but high caspase 7 activity, and show upregulation of pro-inflammatory cytokines that relate to a relatively mesenchymal phenotype. Conclusions: We describe two novel genes that can be used to prognosticate colon cancer and suggest approaches by which such tumors can be treated. We also describe molecular characteristics of tumors stratified by the SU-GIB signature.Article Citation - WoS: 1Citation - Scopus: 1Classification of Colon Cancer Patients Into Consensus Molecular Subtypes Using Support Vector Machines(TUBITAK, 2023-12-28) Kochan, Necla; Dayanç, Barış EmreBackground/aim: The molecular heterogeneity of colon cancer has made classification of tumors a requirement for effective treatment. One of the approaches for molecular subtyping of colon cancer patients is the consensus molecular subtypes (CMS), developed by the Colorectal Cancer Subtyping Consortium. CMS-specific RNA-Seq-dependent classification approaches are recent, with relatively low sensitivity and specificity. In this study, we aimed to classify patients into CMS groups using their RNA-seq profiles. Materials and methods: We first identified subtype-specific and survival-associated genes using the Fuzzy C-Means algorithm and log-rank test. We then classified patients using support vector machines with backward elimination methodology. Results: We optimized RNA-seq-based classification using 25 genes with a minimum classification error rate. In this study, we reported the classification performance using precision, sensitivity, specificity, false discovery rate, and balanced accuracy metrics. Conclusion: We present a gene list for colon cancer classification with minimum classification error rates and observed the lowest sensitivity but the highest specificity with CMS3-associated genes, which significantly differed due to the low number of patients in the clinic for this group. © TÜBİTAK.Conference Object Discovery of Subtype Specific Markers Through Fuzzy Logic and Non-Parametric Approaches Using Transcriptomic Data in Immune Related Colon Cancer(Wiley, 2021) Kochan, Necla; Dayanç, Barış Emre; Dayanc, Emre[Abstract Not Available]Article Cholinergic Receptor Binding Profile of Hypericum Perforatum L. and Its Active Constituents(Asian Network Scientific Information-Ansinet, 2022-09-15) Hamurtekin, Emre; Hamurtekin, Y.; Matucci, R.; Dei, S.; Dayanç, Barış Emre; Kazdağlı, Hasan; Baris, E.Background andObjective: Hypericum perforatum L (HP) is a popular herbal medicine with different pharmacological effects. This study investigated the possible cholinergic receptor affinities of HP extract and its three active constituents: hyperforin, hypericin and pseudohypericin. Materials and Methods: Radioactive compounds [3H]-N-methyl scopolamine used for muscarinic receptor binding studies in Chinese hamster ovary cells expressing human muscarinic receptor subtypes and [3H]-cytisine used for nicotinic receptor binding tests performed with mouse brains without a cerebellum. Muscarinic binding inhibition was observed with HP extract considerably for hM2 and hM5. Results: Hyperforin, hypericin and pseudohypericin showed a much lower affinity for muscarinic receptors at higher concentrations. The HP extract and its constituents did not produce any nicotinic receptor binding inhibition. Conclusion:These results suggested that post-junctional direct muscarinic receptor interaction may modulate some effects of HP extract and its constituents however different mechanisms apart from direct cholinergic receptor interaction might be considered for the pharmacological actions of hyperforin, hypericin and pseudohypericin.Master Thesis Kalp ve Damar Cerrahisi Yoğun Bakım Ünitesinde Santral Venöz Kateter Bakımı Uygulamalarının Hasta Bağışıklık Sistemi Hücre Sayıları Üzerine Etkisi(İzmir Ekonomi Üniversitesi, 2021) Eröz, Derya; Dayanç, Barış Emre; İntepeler, Şeyda SerenSantral venöz kateterizasyon, klinikte kritik hastaların sıvı tedavisinde, ilaç uygulamalarında, kan, total parenteral nütrisyon (TPN) verilmesinde ve hemodinamik durumun izleminde kullanılmaktadır. Bu çalışmada kalp-damar cerrahisi yoğun bakım ünitesinde yatan; açık kalp ameliyatı olmuş, santral venöz kateteri olan yetişkin hastalarda, santral kateter bakımı uygulamalarının hasta bağışıklık sistemi hücre sayıları üzerine etkisi incelenmiştir. Santral venöz kateter (SVK) Önlem Paketi (ÖP) uygulanan ve uygulanmayan olmak üzere hastaların, rutin alınan kan tahlillerinden preop, postop 1 ve postop 2. günlerindeki Beyaz kan hücreleri (WBC), Nötrofil, Lenfosit, Monosit, Eozinofil, Bazofil) değerleri karşılaştırılmıştır. SVK Ö.P. uygulanmayan 39, SVK Ö.P. uygulanan 101 hasta bulunmaktadır. Preoperatif immün sistem hastalığı (ör. İmmün yetmezlik veya otoimmün hastalık tanısı), enfeksiyöz hastalığı, onkolojik tanısı olan hastalar çalışmanın dışında bırakılmıştır. SVK Ö.P. uygulamasıyla, santral venöz kateter bakımına bağlı immün değişikliklerin gözlenmesine yönelik kanıta dayalı veri oluşturulmuştur. Önlem paketi uygulanan hastaların preop, postop 1 ve postop 2. gün verileri önlem paketi uygulanmayan hastaların sonuçları ile karşılaştırıldığında, grupların kendi içindeki total lökosit, nötrofil, lenfosit, bazofil, monosit ve eozinofil sayıları açısından değişimler anlamlı iken; gruplar arasında anlamlı bir fark saptanmamıştır (p>0.05). Sonuç olarak SVK önlem paketi uygulamasının, immun hücre sayılarını etkilemediği gözlenmiştir.Article Classification of Colon Cancer Patients Into Consensus Molecular Subtypes Using Support Vector Machines(2023-12-28) Koçhan, Necla; Dayanç, Barış EmreBackground/aim: The molecular heterogeneity of colon cancer has made classification of tumors a requirement for effective treatment. One of the approaches for molecular subtyping of colon cancer patients is the consensus molecular subtypes (CMS), developed by the Colorectal Cancer Subtyping Consortium. CMS-specific RNA-Seq-dependent classification approaches are recent, with relatively low sensitivity and specificity. In this study, we aimed to classify patients into CMS groups using their RNA-seq profiles. Materials and methods: We first identified subtype-specific and survival-associated genes using the Fuzzy C-Means algorithm and log- rank test. We then classified patients using support vector machines with backward elimination methodology. Results: We optimized RNA-seq-based classification using 25 genes with a minimum classification error rate. In this study, we reported the classification performance using precision, sensitivity, specificity, false discovery rate, and balanced accuracy metrics. Conclusion: We present a gene list for colon cancer classification with minimum classification error rates and observed the lowest sensitivity but the highest specificity with CMS3-associated genes, which significantly differed due to the low number of patients in the clinic for this group.Article Citation - WoS: 1Citation - Scopus: 1Novel Approach Methodologies in Modeling Complex Bioaerosol Exposure in Asthma and Allergic Rhinitis Under Climate Change(Cambridge Univ Press, 2025) Atalay-Sahar, Esra; Yildiz-Ozturk, Ece; Ozgur, Su; Aral, Arzu; Dayanc, Emre; Goksel, Tuncay; Goksel, OzlemThe undeniable impact of climate change and air pollution on respiratory health has led to increasing cases of asthma, allergic rhinitis and other chronic non-communicable immune-mediated upper and lower airway diseases. Natural bioaerosols, such as pollen and fungi, are essential atmospheric components undergoing significant structural and functional changes due to industrial pollution and atmospheric warming. Pollutants like particulate matter(PMx), polycyclic aromatic hydrocarbons(PAHs), nitrogen dioxide(NO2), sulfur dioxide(SO2) and carbon monoxide(CO) modify the surface and biological properties of atmospheric bioaerosols such as pollen and fungi, enhancing their allergenic potentials. As a result, sensitized individuals face heightened risks of asthma exacerbation, and these alterations likely contribute to the rise in frequency and severity of allergic diseases. NAMs, such as precision-cut lung slices(PCLS), air-liquid interface(ALI) cultures and lung-on-a-chip models, along with the integration of data from these innovative models with computational models, provide better insights into how environmental factors influence asthma and allergic diseases compared to traditional models. These systems simulate the interaction between pollutants and the respiratory system with higher precision, helping to better understand the health implications of bioaerosol exposure. Additionally, NAMs improve preclinical study outcomes by offering higher throughput, reduced costs and greater reproducibility, enhancing the translation of data into clinical applications. This review critically evaluates the potential of NAMs in researching airway diseases, with a focus on allergy and asthma. It highlights their advantages in studying the increasingly complex structures of bioaerosols under conditions of environmental pollution and climate change, while also addressing the existing gaps, challenges and limitations of these models.

