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 | 86022 |
| عنوان فارسی مقاله | درک ژن های بالقوه خاص برای لوسمی میلوئید حاد با تجزیه و تحلیل پان کنسر |
| عنوان لاتین مقاله | Understanding Specific Potential Genes for Acute Myeloid Leukemia by pan-cancer Analysis |
| نوع ارائه | پوستر |
| عنوان کنگره / همایش | the 20th International Congress of Stem Cell Biology & Technology and the 25th International Congress of Reproductive Biomedicine |
| 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 | 1403/06/07 الی 1403/06/09 |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://royancongress.com/preCongress |
| آدرس علمی (Affiliation) نویسنده متقاضی | Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran |
| نویسنده | نفر چندم مقاله |
|---|---|
| نرجس صدیقی | اول |
| عنوان | متن |
|---|---|
| کلمات کلیدی | Acute myeloid leukemia, TCGA, RNAseq, bioinformatics, pan-cancer analysis |
| خلاصه مقاله | Background: Acute myeloid leukemia (AML) is caused by functionally complementary genetic mutations that cause uncontrolled proliferation and maturational arrest of myeloid precursor cells. Nowadays, gene expression profile analysis is a potent research technique that reveals patients' dysregulated genes by integrating data from functional genomics, molecular transcription, and genetics. In this study, we are going to evaluate TCGA datasets in acute myeloid leukemia and investigate genes that are exclusively related to this cancer with pan-cancer analysis. Method: First, GEPIA2 was used to examine the AML dataset to identify all DEGs linked. Genes with a P-value < 0.05 were considered significant; after that, significant genes were divided into 4 groups including up/down prognostic or protective genes according to the logFC and HR. A Protein-protein interaction network of associated with AML was constructed with STRING at the Cytoscape software, and hub-genes were identified based on their scores and interaction. In the end, we used Pan-cancer analysis with GEPIA2 and UALCAN for hub genes and got to the 4 genes that were exclusive. Result: Of 7965 genes acquired from TCGA-RNAseq for AML, 843 genes are considered significant (adjusted P-value < 0.05), of which 666 genes are prognostic and 174 genes are protective. According to the result, 8 genes are significantly related to survival including PSMG1, SLC37A1, FAM207A, GPS2, CSTB, CHAF1B, AKAP9, and ABCG1 (p-value and q-value < 0.05). PPI networks were drawn for significant genes and also hub genes. All of the genes except HSPA5 were prognostic. After pan-cancer analysis, we found NDUFS8,MRPL12,MRPL2, and SOD1 which are expressed significantly less than usual (Compared with other cancers as well as with normal samples). Conclusion: This study identifies 4 genes that are involved specifically in the occurrence and progression of Acute Myeloid Leukemia. This information may hold promise as potential biomarkers and therapeutic targets. |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| AML.pdf | 1403/09/03 | 301504 | دانلود |
| 1732377096075.jpg | 1403/09/03 | 18712294 | دانلود |
