Lu Cao, Lili Duan, Rui Zhang, Wanli Yang, Ning Yang, Wenzhe Huang, Xuemin Chen, Nan Wang, Liaoran Niu, Wei Zhou, Junfeng Chen, Yiding Li, Yujie Zhang, Jinqiang Liu, Daiming Fan, Hong Liu
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LASSO algorithm was conducted to establish a prognostic risk model, and the validity of the proposed model was confirmed by an independent GEO dataset. Functional enrichment analysis was performed to reveal the potential biological functions and pathways of the signature and to estimate tumor immune infiltration. Potential therapeutic compounds were inferred utilizing CMap database. Expressions of hub genes were further verified through the Human Protein Atlas (HPA) database and RT-qPCR.</p><p><strong>Results: </strong>One thousand seven hundred thirty four RBPs were differently expressed in CRC samples and 4 gene modules remarkably linked to the prognosis were identified, based on which a 12-gene signature was established for prognosis prediction. Multivariate Cox analysis suggested this signature was an independent predicting factor of overall survival (P < 0.001; HR:3.682; CI:2.377-5.705) and ROC curves indicated it has an effective predictive performance (1-year AUC: 0.653; 3-year AUC:0.673; 5-year AUC: 0.777). GSEA indicated that high risk score was correlated with several cancer-related pathways, including cytokine-cytokine receptor cross talk, ECM receptor cross talk, HEDGEHOG signaling cascade and JAK/STAT signaling cascade. ssGSEA analysis exhibited a significant correlation between immune status and the risk signature. Noscapine and clofazimine were screened as potential drugs for CRC patients with high-risk scores. TDRD5 and GPC1 were identified as hub genes and their expression were validated in 15 pairs of surgically resected CRC tissues.</p><p><strong>Conclusion: </strong>Our research provides a depth insight of RBPs' role in CRC and the proposed signature are helpful to the personalized treatment and prognostic judgement.</p>","PeriodicalId":12862,"journal":{"name":"Hereditas","volume":"160 1","pages":"10"},"PeriodicalIF":2.7000,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9999506/pdf/","citationCount":"1","resultStr":"{\"title\":\"Development and validation of an RBP gene signature for prognosis prediction in colorectal cancer based on WGCNA.\",\"authors\":\"Lu Cao, Lili Duan, Rui Zhang, Wanli Yang, Ning Yang, Wenzhe Huang, Xuemin Chen, Nan Wang, Liaoran Niu, Wei Zhou, Junfeng Chen, Yiding Li, Yujie Zhang, Jinqiang Liu, Daiming Fan, Hong Liu\",\"doi\":\"10.1186/s41065-023-00274-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>RNA binding proteins (RBPs) have been implicated in oncogenesis and progression in various cancers. 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引用次数: 1
摘要
背景:RNA结合蛋白(rbp)参与多种癌症的发生和发展。然而,rbp作为结直肠癌(CRC)预后指标和治疗靶点的潜在价值需要进一步研究。方法:从文献中收集rbp 482例。采用加权基因共表达网络分析(WGCNA),根据TCGA队列获得的数据识别与预后相关的RBP基因模块。利用LASSO算法建立了预测风险模型,并通过独立GEO数据集验证了模型的有效性。功能富集分析揭示了该标记的潜在生物学功能和途径,并估计了肿瘤免疫浸润。利用CMap数据库推断潜在的治疗化合物。通过Human Protein Atlas (HPA)数据库和RT-qPCR进一步验证hub基因的表达。结果:在CRC样本中有1734个rbp存在差异表达,鉴定出4个与预后显著相关的基因模块,并以此为基础建立了预后预测的12个基因标记。多因素Cox分析提示rbp是总生存期的独立预测因素(P)。结论:我们的研究为rbp在结直肠癌中的作用提供了深入的认识,提出的rbp特征有助于个体化治疗和预后判断。
Development and validation of an RBP gene signature for prognosis prediction in colorectal cancer based on WGCNA.
Background: RNA binding proteins (RBPs) have been implicated in oncogenesis and progression in various cancers. However, the potential value of RBPs as prognostic indicators and therapeutic targets in colorectal cancer (CRC) requires further investigation.
Methods: Four thousand eighty two RBPs were collected from literature. The weighted gene co-expression network analysis (WGCNA) was performed to identify prognosis-related RBP gene modules based on the data attained from the TCGA cohorts. LASSO algorithm was conducted to establish a prognostic risk model, and the validity of the proposed model was confirmed by an independent GEO dataset. Functional enrichment analysis was performed to reveal the potential biological functions and pathways of the signature and to estimate tumor immune infiltration. Potential therapeutic compounds were inferred utilizing CMap database. Expressions of hub genes were further verified through the Human Protein Atlas (HPA) database and RT-qPCR.
Results: One thousand seven hundred thirty four RBPs were differently expressed in CRC samples and 4 gene modules remarkably linked to the prognosis were identified, based on which a 12-gene signature was established for prognosis prediction. Multivariate Cox analysis suggested this signature was an independent predicting factor of overall survival (P < 0.001; HR:3.682; CI:2.377-5.705) and ROC curves indicated it has an effective predictive performance (1-year AUC: 0.653; 3-year AUC:0.673; 5-year AUC: 0.777). GSEA indicated that high risk score was correlated with several cancer-related pathways, including cytokine-cytokine receptor cross talk, ECM receptor cross talk, HEDGEHOG signaling cascade and JAK/STAT signaling cascade. ssGSEA analysis exhibited a significant correlation between immune status and the risk signature. Noscapine and clofazimine were screened as potential drugs for CRC patients with high-risk scores. TDRD5 and GPC1 were identified as hub genes and their expression were validated in 15 pairs of surgically resected CRC tissues.
Conclusion: Our research provides a depth insight of RBPs' role in CRC and the proposed signature are helpful to the personalized treatment and prognostic judgement.
HereditasBiochemistry, Genetics and Molecular Biology-Genetics
CiteScore
3.80
自引率
3.70%
发文量
0
期刊介绍:
For almost a century, Hereditas has published original cutting-edge research and reviews. As the Official journal of the Mendelian Society of Lund, the journal welcomes research from across all areas of genetics and genomics. Topics of interest include human and medical genetics, animal and plant genetics, microbial genetics, agriculture and bioinformatics.