Lingshan Zhou, Yuan Yang, Jian Ma, Min Liu, Rong Liu, Xiaopeng Ma, Chengdong Qiao
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引用次数: 0
摘要
剪接失调与癌症之间的相关性已被越来越多地认识和证实。鉴别胰腺癌(PHC)中有价值的选择性剪接(AS)具有重要意义。利用the Cancer Genome Atlas和TCGASpliceSeq的数据生成PHC中的AS谱。然后,采用NMF聚类方法鉴定PHC患者的总体生存相关AS (OS-AS)亚型。随后,我们使用最小绝对收缩和选择算子Cox回归分析来构建as相关风险模型。剪接调控网络被Cytoscape 3.7发现。共获得1694个OS-AS事件。PHC患者分为第1组和第2组。第1组预后较差,免疫细胞浸润较低。随后,建立了一个预后特征,显示了预测OS和无进展生存期的良好性能。该特征的风险评分与独特的肿瘤免疫相关。此外,建立了一个包含风险评分和临床病理参数的nomogram。最后,构建了剪接因子- as调控网络。综合分析原发性肝癌AS事件与预后和肿瘤免疫的关系可能有助于提供可靠的信息来指导个体治疗策略。
Comprehensive analysis of alternative splicing signatures in pancreatic head cancer
The correlation between dysregulation of splicing and cancers has been increasingly recognised and confirmed. The identification of valuable alternative splicing (AS) in pancreatic head cancer (PHC) has a great significance. AS profiles in PHC were generated using the data from The Cancer Genome Atlas and TCGASpliceSeq. Then, the NMF clustering method was performed to identify overall survival-associated AS (OS-AS) subtypes in PHC patients. Subsequently, we used least absolute shrinkage and selection operator Cox regression analysis to construct an AS-related risk model. The splicing regulatory network was uncovered by Cytoscape 3.7. A total of 1694 OS-AS events were obtained. The PHC patients were divided into clusters 1 and 2. Cluster 1 had poorer prognosis and lower infiltration of immune cells. Subsequently, a prognostic signature was established that showed good performance in predicting OS and progression-free survival. The risk score of this signature was associated with the unique tumour immunity. Moreover, a nomogram incorporating the risk score and clinicopathological parameters was established. Finally, a splicing factor-AS regulatory network was developed. A comprehensive analysis of the AS events in PHC associated with prognosis and tumour immunity may help provide reliable information to guide individual treatment strategies.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.