Browsing by Author "Sönmez, Dilara"
Now showing items 1-4 of 4
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The importance of sPD-1, sOX40L and sGITR in terms of clinicopathology and histopathology in gastric cancer
Horozoğlu, Cem; Sönmez, Dilara; Küçükhüseyin, Özlem; Demirkol, Şeyda; Hakan, Mehmet Tolgahan; Arıkan, Soykan; Yaylım, İlhan (De Gruyter, 2021)Abstract: Objectives: Immunoregulatory GITR, OX40L and PD-1 molecules play an active role in the regulation of tumor microenvironment and have been shown in many cancer types. However, there are limited studies of these ... -
Is there any relationship between LGALS3 gene variations and histopathological criteria in laryngeal squamous cell carcinoma (LSCC)?
Horozoğlu, Cem; Demirkol, Şeyda; Verim, Ayşegül; Sönmez, Dilara; Sürmen, Saime; Küçükhüseyin, Özlem; Zeybek, Ümit; Yaylım, İlhan (De Gruyter, 30.12.2021)Objectives: Genetic variations of LGALS3 (Galectin-3) were found to be associated with treatment resistance, mortality, recurrence, high tumor volume and multiple tumor involvement in solid organ cancers. The modulators ... -
Potential role of immune cell genetic variants associated with tumor microenvironment response in laryngeal squamous cell carcinoma (LSCC) in terms of clinicopathological features
Horozoğlu, Cem; Sönmez, Dilara; Demirkol, Şeyda; Hakan, Mehmet Tolgahan; Kaleler, İslim; Hepokur, Ceylan; Verim, Ayşegül; Yaylım, İlhan (Elsevier GmbH, 12.2021)Immunomodulatory signals regulate the self-tolerance, activation, priming and survival processes of T cells. Programmed cell death protein 1 (PD1), Programmed death-ligand 1 (PD-L1) inhibitory signals and CD27, CD28 ... -
Predicting the predisposition to colorectal cancer based on SNP profiles of immune phenotypes using supervised learning models
Çakmak, Ali; Ayaz, Huzeyfe; Arıkan, Soykan; İbrahimzada, Ali R.; Demirkol, Şeyda; Sönmez, Dilara; Hakan, Mehmet T.; Sürmen, Saime T.; Horozoğlu, Cem; Doğan, Mehmet B.; Küçükhüseyin, Özlem; Cacına, Canan; Kıran, Bayram; Zeybek, Ümit; Baysan, Mehmet; Yaylım, İlhan (Springer Nature, 2022)AbstractThis study explores the machine learning-based assessment of predisposition to colorectal cancer based on single nucleotide polymorphisms (SNP). Such a computational approach may be used as a risk indicator and an ...
