چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | نرجس صدیقی |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | کمیته تحقیقات دانشجویی |
| کد مقاله | 87147 |
| عنوان فارسی مقاله | شناسایی تنظیم کننده های کلیدی مرتبط با پیش آگهی سرطان پستان |
| عنوان لاتین مقاله | Identification of key regulators associated with breast cancer prognosis |
| نوع ارائه | سخنرانی |
| عنوان کنگره / همایش | CANCER GENOMICS 2024 |
| 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 | |
| تاریخ شمسی شروع و خاتمه کنگره/همایش | 1403/08/02 الی 1403/08/04 |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://icgcs.com/abstract/ |
| آدرس علمی (Affiliation) نویسنده متقاضی | Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran |
| نویسنده | نفر چندم مقاله |
|---|---|
| نرجس صدیقی | دوم |
| مهدی طالبی | اول |
| عنوان | متن |
|---|---|
| کلمات کلیدی | Keywords: Breast cancer, BRCA, prognostic, ceRNA network, bioinformatics |
| خلاصه مقاله | Abstract Introduction: Breast cancer is a heterogeneous disease that is the leading cause of cancer-related death in women globally. Although many efforts have been made to determine the biomarkers and the exact mechanism of this cancer, it is still not completely clear. This study aims to examine the prognostic-associated genes of breast cancer based on bioinformatic analysis of PPI, enrichment analysis, immune interaction, and ceNetwork. Method: Initially, gepia2 was used to select the prognostic genes based on survival analysis with logFC and HR. Then, the PPI network for up/down prognostic genes was drawn separately with the string in Cytoscape software and the hub genes were selected based on their degree and interaction; enrichment analysis of up/ down prognostic genes was evaluated separately with Enrichr. Also, for hub down-regulated genes, the network (genes, their TFs, miRNA, and their circRNA) and immune interaction (TIMER database) were analyzed, and the Human Protein Atlas (HPA) was used for evaluating and confirming the expression of selected genes in breast tissue. Result: Out of 3556 genes acquired from TCGA-RNAseq for AML, 334 genes are considered significant, of which 127 genes are prognostic. The result of the PPI network showed that the down-prognostic genes didn't have any interactions, and 4 up-prognostic genes (PAICS, HN1, UBE2C, AAGAB) have degrees of more than 10 and were selected as hub genes for further analysis. Besides, we conducted enrichment analysis for up and down prognostic genes separately. The result showed that Mitotic Cell Cycle Phase Transition (biological process), External Side Of Apical Plasma Membrane (cellular component), Neutral L-amino Acid Transmembrane Transporter Activity (molecular function) and Cell cycle (kegg pathway) were associated significantly with up-regulated genes and Aspartate Metabolic Process (biological process), Lytic Vacuole (cellular component), Carboxylic Acid Binding (molecular function) and Glycosaminoglycan degradation (kegg pathway) were associated with down-prognostic genes. the result of TIMER analysis showed that the hub genes were almost associated with the immune systems. In the end, the ceRNA network was drawn for hub genes based data conducted from mirDB for miRNA associated with genes, which identified 22 miRNA for UBE2C, 76 for AAGAB, 75 for HN1 and 103 for PAICS; besides, we identified nine circRNA associated with HN1, seven circRNA associated with PAICS, five circRNA associated with UBE2C and ten circRNA associated with AAGAB; also, 36 TF associated with breast were identified for AAGAB, 31 for HN1, 37 for PAICS and 27 for UBE2C. finally, the expression level of these genes was checked in breast tissues obtained from HPA. Conclusion: These results indicated that PAICS, HN1, UBE2C, and AAGAB can be a prognostic indicator for BRCA. overexpression of these genes may serve as an indicator for poor breast cancer outcomes. Further clinical and para-clinical investigation in needed for confirmation and also, these genes may be a choice for future targeted therapy studies. |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| 1736500337575 (4).png | 1403/12/29 | 3257193 | دانلود |
| CGC2024-Abstract-Book3_55.pdf | 1403/12/29 | 405561 | دانلود |
