چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | سید حسین خوش رفتار |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | کمیته تحقیقات دانشجویی |
| کد مقاله | 87073 |
| عنوان فارسی مقاله | شناسایی CDK1 و EZH2 به عنوان اهداف درمانی بالقوه برای سرطان پستان از طریق WGCNA |
| عنوان لاتین مقاله | Identifying CDK1 and EZH2 as potential therapeutic targets for breast cancer through WGCNA |
| نوع ارائه | پوستر |
| عنوان کنگره / همایش | Second International Congress of Cancer Genomics (CGC2024) |
| نوع کنگره / همایش | بین المللی |
| کشور محل برگزاری کنگره/ همایش | Iran (Islamic Republic) |
| شهر محل برگزاری کنگره/ همایش | تهران |
| سال انتشار/ ارائه شمسی | 1403 |
| سال انتشار/ارائه میلادی | 2024 |
| تاریخ شمسی شروع و خاتمه کنگره/همایش | 1403/08/02 الی 1403/08/04 |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://civilica.com/doc/2149315/ |
| آدرس علمی (Affiliation) نویسنده متقاضی | Student Research Comminttee, Tabriz University of Medical Sciences, Tabriz, Iran |
| نویسنده | نفر چندم مقاله |
|---|---|
| سید حسین خوش رفتار | اول |
| پریسا علیرضایی نجف آبادی | دوم |
| صبا هادی | سوم |
| آناهیتا سلیمانی | چهارم |
| سیما منصوری درخشان | پنجم |
| محمد مصطفی پورسیف | ششم |
| عنوان | متن |
|---|---|
| خلاصه مقاله | Introduction: Breast cancer (BC) is a significant contributor to cancer-related deaths in women globally, impacting approximately one out of every eight women in developed nations. Over the past few years, RNA Sequencing (RNA-seq) has emerged as a remarkable and functional technology for analyzing gene expression patterns. Methods: In this particular study, the RNA-seq dataset labeled as BioProject: PRJNA855324 was obtained from the SRA database and subsequently subjected to analysis within the Linux Ubuntu v22.04.4 and RStudio v4.3 environments. The “EdgeR” package was utilized to process the file and detect differentially expressed genes (DEGs) between BC samples. Next, 802 genes were chosen based on criteria of absolute logFC greater than one and an adjusted p-value less than 0.05 to build the co-expression network. Weighted gene co‐expression network analysis (WGCNA) was utilized to build a gene co‐expression network. The soft-thresholding parameter was set to β = 14. After that, the adjacency matrix was converted to a topological overlap matrix (TOM). Afterward, the TOM-based dissimilarity measure was used to classify highly correlated genes into gene modules using average linkage hierarchical clustering, with a minimum threshold of 15. Subsequently, the correlations between the module eigengenes and clinical features were calculated. Finally, Gene Ontology and pathway analysis of the modules that hold clinical relevance were conducted through R packages such as “clusterProfiler”, “AnnotationDbi” and “enrichplot”. Results: two modules were screened out using the average linkage hierarchical clustering, which showed a strong correlation with the Luminal B subtype (cor=0.41, p=5.6e−13), and was selected for further analysis. Among them, two genes (i.e., CDK1 and EZH2) were considered hub genes in the brown module, which had a high “Degree Distribution” and “Bottleneck”, respectively. Based on the information provided by the Gene Ontology and pathway analysis, these genes exert regulatory control over various crucial pathways, including cell cycle and DNA repair. Conclusion: The Luminal B subtype of breast cancer could potentially be treated more effectively by targeting the DEGs that have been identified. |
| کلمات کلیدی | breast cancer; therapeutic target; WGCNA |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| New Microsoft Word Document.pdf | 1404/02/22 | 135470 | دانلود |
| Certificate_CG.png | 1403/12/18 | 3408629 | دانلود |
