RPS3 predicts poor overall survival in HBV-related hepatocellular carcinoma patients: a data-mining with LASSO-regression algorithm

التفاصيل البيبلوغرافية
العنوان: RPS3 predicts poor overall survival in HBV-related hepatocellular carcinoma patients: a data-mining with LASSO-regression algorithm
المؤلفون: J, Shi, T, Zhang, Z-G, Yang, F-L, Chen, W-S, Zhang
المصدر: European review for medical and pharmacological sciences. 26(18)
سنة النشر: 2022
مصطلحات موضوعية: Ribosomal Proteins, Hepatitis B virus, Carcinoma, Hepatocellular, Liver Neoplasms, Biomarkers, Tumor, Data Mining, Humans, RNA, Messenger, alpha-Fetoproteins, Prognosis, Algorithms, Biomarkers
الوصف: This analysis aimed to investigate the candidate biomarkers associated with overall survival (OS) in hepatocellular carcinoma (HCC) patients.In the GSE14520 dataset, candidate parameters were selected and included in the Cox regression and Nomogram models through bioinformatic enrichment methods and LASSO analysis, survivor functions of candidate biomarkers were also assessed.Complement and coagulation cascades including 36 differential expressed genes (DEGs) and ribosome pathway including 27 DEGs were significantly enriched (both p0.05 and adjusted p0.05). LASSO model, Cox regression and nomogram analysis indicated that RPS3, together with BCLC and TNM staging, were significantly associated with OS in HCC patients. Validated in the GEO series, TCGA and Human Protein Atlas (HPA) datasets, RPS3 mRNA and RPS3 protein were significantly upregulated in tumor tissues compared to that in nontumor tissues (all p0.05). Upregulation of RPS3 has been linked to high alpha fetoprotein (AFP), advanced tumor stages and multinodular (all p0.05). After adjusting AFP, tumor stage and multinodular, log rank analysis revealed that HCC patients with high RPS3 had unfavorable OS compared to those with low RPS3 (all p0.05).RPS3 upregulation in tumors might contribute to unfavorable OS in HCC patients.
تدمد: 2284-0729
URL الوصول: https://explore.openaire.eu/search/publication?articleId=pmid________::167dee854e1454d61e30568299379ff0
https://pubmed.ncbi.nlm.nih.gov/36196722
حقوق: OPEN
رقم الأكسشن: edsair.pmid..........167dee854e1454d61e30568299379ff0
قاعدة البيانات: OpenAIRE