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Predicting response of immunotherapy and targeted therapy and prognosis characteristics for renal clear cell carcinoma based on m1A methylation regulators

التفاصيل البيبلوغرافية
العنوان: Predicting response of immunotherapy and targeted therapy and prognosis characteristics for renal clear cell carcinoma based on m1A methylation regulators
المؤلفون: Lei Li, Hongwei Tan, Jiexue Zhou, Fengming Hu
المصدر: Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)
بيانات النشر: Nature Portfolio, 2023.
سنة النشر: 2023
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Abstract In recent years, RNA methylation modification has been found to be related to a variety of tumor mechanisms, such as rectal cancer. Clear cell renal cell carcinoma (ccRCC) is most common in renal cell carcinoma. In this study, we get the RNA profiles of ccRCC patients from ArrayExpress and TCGA databases. The prognosis model of ccRCC was developed by the least absolute shrinkage and selection operator (LASSO) regression analysis, and the samples were stratified into low–high risk groups. In addition, our prognostic model was validated through the receiver operating characteristic curve (ROC). “pRRophetic” package screened five potential small molecule drugs. Protein interaction networks explore tumor driving factors and drug targeting factors. Finally, polymerase chain reaction (PCR) was used to verify the expression of the model in the ccRCC cell line. The mRNA matrix in ArrayExpress and TCGA databases was used to establish a prognostic model for ccRCC through LASSO regression analysis. Kaplan Meier analysis showed that the overall survival rate (OS) of the high-risk group was poor. ROC verifies the reliability of our model. Functional enrichment analysis showed that there was a obviously difference in immune status between the high-low risk groups. “pRRophetic” package screened five potential small molecule drugs (A.443654, A.770041, ABT.888, AG.014699, AMG.706). Protein interaction network shows that epidermal growth factor receptor [EGRF] and estrogen receptor 1 [ESR1] are tumor drivers and drug targeting factors. To further analyze the differential expression and pathway correlation of the prognosis risk model species. Finally, polymerase chain reaction (PCR) showed the expression of YTHN6-Methyladenosine RNA Binding Protein 1[YTHDF1], TRNA Methyltransferase 61B [TRMT61B], TRNA Methyltransferase 10C [TRMT10C] and AlkB Homolog 1[ALKBH1] in ccRCC cell lines. To sum up, the prognosis risk model we created not only has good predictive value, but also can provide guidance for accurately predicting the prognosis of ccRCC.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-023-39935-4
URL الوصول: https://doaj.org/article/71038458b31040d2a8e1f5bbc38930bf
رقم الأكسشن: edsdoj.71038458b31040d2a8e1f5bbc38930bf
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-023-39935-4