Publications by authors named "Betul Comertpay"

Article Synopsis
  • - Ovarian cancer significantly contributes to cancer-related deaths in women, making early diagnosis and personalized medicine crucial to improving outcomes through new drug discovery methods.
  • - The study utilized an integrated systems biology and machine learning approach to analyze multiple transcriptome datasets, identifying a significant gene module called "SOV-module" that consists of 19 genes associated with serous ovarian cancer.
  • - The SOV-module showed impressive diagnostic accuracy of 96.7% sensitivity and 100% specificity, and 63% accuracy in prognostic predictions, underscoring its potential as a genomic biomarker for personalized treatment strategies in ovarian cancer.
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Rheumatoid arthritis (RA) is an autoimmune disorder and common symptom of RA is chronic synovial inflammation. The pathogenesis of RA is not fully understood. Therefore, we aimed to identify underlying common and distinct molecular signatures and pathways among ten types of tissue and cells obtained from patients with RA.

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Differential expressions of certain genes during tumorigenesis may serve to identify novel manageable targets in the clinic. In this work with an integrated bioinformatics approach, we analyzed public microarray datasets from Gene Expression Omnibus (GEO) to explore the key differentially expressed genes (DEGs) in non-small cell lung cancer (NSCLC). We identified a total of 984 common DEGs in 252 healthy and 254 NSCLC gene expression samples.

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Article Synopsis
  • - Rheumatoid arthritis (RA) is an autoimmune disease where the immune system mistakenly attacks body tissues, leading to insufficient treatment options currently available.
  • - This study analyzed various patient-derived data (like synovial fluids and blood samples) using bioinformatics to identify potential drug candidates that could be repurposed for RA treatment.
  • - A total of 19 drug candidates, including FDA-approved options like momelotinib and ibrutinib, were identified for further study, which could lead to new treatments for RA.
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Cancer stem-like cells (CSCs) possess the ability to self-renew and differentiate, and they are among the major factors driving tumorigenesis, metastasis, and resistance to chemotherapy. Therefore, it is critical to understand the molecular substrates of CSC biology so as to discover novel molecular biosignatures that distinguish CSCs and tumor cells. Here, we report new findings and insights by employing four transcriptome datasets associated with CSCs, with CSC and tumor samples from breast, lung, oral, and ovarian tissues.

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Rheumatoid arthritis (RA) frequently seen chronic synovial inflammation causing joint destruction, chronic disability and reduced life expectancy. The pathogenesis of RA is not completely known. In this study, several gene expression data including synovial tissue and macrophages from synovial tissues were integrated with a holistic perspective and the molecular targets and signatures in RA were determined.

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