Jiana Fang, Jingru Huang, Jiazhong Zhang, Lin Chen, Jin Deng
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引用次数: 0
Abstract
Purpose: The molecular properties of TLSs in pancreatic cancer are still not well comprehended. This research delved into the molecular properties of intratumoral TLSs in pancreatic cancer through the exploration of multi-omics data. Methods: Seven key genes were identified through Cox regression analysis and random survival forest analysis from a total of 5908 genes related to TLSs. These genes were utilized to construct a prognosis model, which was subsequently validated in two independent cohorts. Additionally, the study investigated the molecular features of different populations of TLSs from multiple perspectives. The model’ s forecasting accuracy was verified by analyzing column-line graphs and decision curves, taking into account the patients’ clinical traits. Results: The analysis of immune cell infiltration showed a notably greater presence of Macrophage M0 cells in the group at high risk than in the low-risk group. The pathway enrichment analysis demonstrated the activation among common cancer-related pathways, including ECM receptor interaction, pathways in cancer, and focal adhesion, in the high-risk group. Additionally, the methylation study revealed notable disparities in DNA methylation between two TLS groups across four regions: TSS200, 5’ UTR, 1stExon, and Body. A variety of notably distinct sites were linked with PVT1. Furthermore, by constructing a competing endogenous RNA network, several mRNAs and lncRNAs were identified that compete for the binding of hsa-mir-221. Conclusion: Overall, this research sheds light on the molecular properties of TLSs across various pancreatic cancer stages and suggests possible focal points for the treatment of pancreatic cancer. result: The analysis of immune cell infiltration showed a notably greater presence of Macrophage M0 cells in the group at high-risk than in the low-risk group. Pathway enrichment analysis demonstrated the activation among common cancer-related pathways, including ECM receptor interaction, pathways in cancer, and focal adhesion, in the high-risk group. Additionally, the methylation study revealed notable disparities in DNA methylation between two TLSs groups across four regions: TSS200, 5’ UTR, 1stExon, and Body. A variety of notably distinct sites were linked with PVT1. By constructing a competing endogenous RNA network, multiple mRNAs and lncRNAs competing for the binding of hsa-mir-221 were identified.
Current ProteomicsBIOCHEMICAL RESEARCH METHODS-BIOCHEMISTRY & MOLECULAR BIOLOGY
CiteScore
1.60
自引率
0.00%
发文量
25
审稿时长
>0 weeks
期刊介绍:
Research in the emerging field of proteomics is growing at an extremely rapid rate. The principal aim of Current Proteomics is to publish well-timed in-depth/mini review articles in this fast-expanding area on topics relevant and significant to the development of proteomics. Current Proteomics is an essential journal for everyone involved in proteomics and related fields in both academia and industry.
Current Proteomics publishes in-depth/mini review articles in all aspects of the fast-expanding field of proteomics. All areas of proteomics are covered together with the methodology, software, databases, technological advances and applications of proteomics, including functional proteomics. Diverse technologies covered include but are not limited to:
Protein separation and characterization techniques
2-D gel electrophoresis and image analysis
Techniques for protein expression profiling including mass spectrometry-based methods and algorithms for correlative database searching
Determination of co-translational and post- translational modification of proteins
Protein/peptide microarrays
Biomolecular interaction analysis
Analysis of protein complexes
Yeast two-hybrid projects
Protein-protein interaction (protein interactome) pathways and cell signaling networks
Systems biology
Proteome informatics (bioinformatics)
Knowledge integration and management tools
High-throughput protein structural studies (using mass spectrometry, nuclear magnetic resonance and X-ray crystallography)
High-throughput computational methods for protein 3-D structure as well as function determination
Robotics, nanotechnology, and microfluidics.