5 results on '"Canlı, Seçil Demirkol"'
Search Results
2. Breast Cancer Plasticity after Chemotherapy Highlights the Need for Re-Evaluation of Subtyping in Residual Cancer and Metastatic Tissues.
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Padzińska-Pruszyńska, Irena Barbara, Akbar, Muhammad Waqas, Isbilen, Murat, Górka, Emilia, Kucukkaraduman, Baris, Canlı, Seçil Demirkol, Dedeoğlu, Ege, Azizolli, Shila, Cela, Isli, Akcay, Abbas Guven, Hakanoglu, Hasim, Bodnar, Lubomir, Cierniak, Szczepan, Kozielec, Zygmunt, Pruszyński, Jacek Jerzy, Bittel, Martyna, Gure, Ali Osmay, Król, Magdalena, and Taciak, Bartłomiej
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BREAST cancer ,TRIPLE-negative breast cancer ,BREAST ,TREATMENT effectiveness ,METASTASIS ,GENE expression - Abstract
This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276 genes whose expression was related to survival in such patients. The gene expression data were then used to classify patients into two major groups based on the presence or absence of Wingless/Integrated-pathway (Wnt-pathway) and mesenchymal (Mes) markers (Wnt/Mes). Patients with a low expression of Wnt/Mes-related genes had a favorable outcome, with no deaths observed during follow-up, while patients with a high expression of Wnt/Mes genes had a higher mortality rate of 50% within 19 months. The identified gene list could be validated and potentially used to shape treatment options for TNBC patients eligible for neoadjuvant therapy providing valuable insights into the development of more effective treatments for TNBC. Our data also showed significant variation in gene expression profiles before and after chemotherapy, with most tumors switching to a more mesenchymal/stem cell-like profile. To verify this observation, we performed an in silico analysis to classify breast cancer tumors in Prediction Analysis of Microarray 50 (PAM50) molecular classes before treatment and after treatment using gene expression data. Our findings demonstrate that following drug intervention and metastasis, certain tumors undergo a transition to alternative subtypes, resulting in diminished therapeutic efficacy. This underscores the necessity for reevaluation of patients who have experienced relapse or metastasis post-chemotherapy, with a focus on molecular subtyping. Tailoring treatment strategies based on these refined subtypes is imperative to optimize therapeutic outcomes for affected individuals. [ABSTRACT FROM AUTHOR]
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- 2024
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3. Evaluation of an aldo-keto reductase gene signature with prognostic significance in colon cancer via activation of epithelial to mesenchymal transition and the p70S6K pathway.
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Canlı, Seçil Demirkol, Seza, Esin Gülce, Sheraj, Ilir, Gömçeli, Ismail, Turhan, Nesrin, Carberry, Steven, Prehn, Jochen H M, Güre, Ali Osmay, and Banerjee, Sreeparna
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EPITHELIAL-mesenchymal transition , *COLON cancer , *BIOTRANSFORMATION (Metabolism) , *WESTERN immunoblotting , *PROTEIN microarrays , *ESOPHAGEAL motility - Abstract
AKR1B1 and AKR1B10, members of the aldo-keto reductase family of enzymes that participate in the polyol pathway of aldehyde metabolism, are aberrantly expressed in colon cancer. We previously showed that high expression of AKR1B1 (AKR1B1HIGH) was associated with enhanced motility, inflammation and poor clinical outcome in colon cancer patients. Using publicly available datasets and ex vivo gene expression analysis (n = 51, Ankara cohort), we have validated our previous in silico finding that AKR1B1HIGH was associated with worse overall survival (OS) compared with patients with low expression of AKR1B1 (AKR1B1LOW) samples. A combined signature of AKR1B1HIGH and AKR1B10LOW was significantly associated with worse recurrence-free survival (RFS) in microsatellite stable (MSS) patients and in patients with distal colon tumors as well as a higher mesenchymal signature when compared with AKR1B1LOW/AKR1B10HIGH tumors. When the patients were stratified according to consensus molecular subtypes (CMS), AKR1B1HIGH/AKR1B10LOW samples were primarily classified as CMS4 with predominantly mesenchymal characteristics while AKR1B1LOW/AKR1B10HIGH samples were primarily classified as CMS3 which is associated with metabolic deregulation. Reverse Phase Protein Array carried out using protein samples from the Ankara cohort indicated that AKR1B1HIGH/AKR1B10LOW tumors showed aberrant activation of metabolic pathways. Western blot analysis of AKR1B1HIGH/AKR1B10LOW colon cancer cell lines also suggested aberrant activation of nutrient-sensing pathways. Collectively, our data suggest that the AKR1B1HIGH/AKR1B10LOW signature may be predictive of poor prognosis, aberrant activation of metabolic pathways, and can be considered as a novel biomarker for colon cancer prognostication. [ABSTRACT FROM AUTHOR]
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- 2020
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4. Glutamine withdrawal leads to the preferential activation of lipid metabolism in metastatic colorectal cancer
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Taşkıran, Aliye Ezgi Güleç, Karaoğlu, Diren Arda, Eylem, Cemil Can, Ermiş, Çağdaş, Güderer, İsmail, Nemutlu, Emirhan, Canlı, Seçil Demirkol, and Banerjee, Sreeparna
- Abstract
•Glutamine is differentially metabolized in primary versus metastatic tumors.•A three gene glutamine metabolism signature could predict prognosis.•Metastatic SW620 cells increased lipid uptake upon glutamine starvation.•Glutamine starvation led to increased motility in SW620 cells
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- 2024
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5. A Stemness and EMT Based Gene Expression Signature Identifies Phenotypic Plasticity and is A Predictive but Not Prognostic Biomarker for Breast Cancer
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Nevin Belder, Murat Isbilen, Ali O. Gure, Ozgur Sahin, Baris Kucukkaraduman, Muhammad Waqas Akbar, Secil Demirkol Canli, Can Turk, Akbar, Muhammad Waqas, Belder, Nevin, Demirkol-Canlı, Seçil Demirkol, Küçükkaraduman, Barış, Türk, Can, Şahin, Özgür, and Güre, Ali Osmay
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0301 basic medicine ,Cell type ,In silico ,Biology ,Lapatinib ,predictive biomarkers ,Transcriptome ,03 medical and health sciences ,Breast cancer ,0302 clinical medicine ,Predictive biomarkers ,Cancer stem cell ,medicine ,Tumor plasticity ,Epithelial–mesenchymal transition ,Transcriptomics ,transcriptomics ,tumor plasticity ,Gene signature ,medicine.disease ,030104 developmental biology ,Oncology ,030220 oncology & carcinogenesis ,Cancer research ,Research Paper ,medicine.drug - Abstract
Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality. This work was partially funded by a grant from the Turkish Scientific and Technological Research Council/TUBITAK (117S058) to AOG and one from The Higher Education Commission of Pakistan to MWA.
- Published
- 2020
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