Abstract：
Lung cancer is the deadliest and most aggressive malignancy in the world. Preventing cancer is crucial. Therefore, the new molecular targets have laid the foundation for molecular diagnosis and targeted therapy of lung cancer. PLA2G1B plays a key role in lipid metabolism and inflammation. PLA2G1B has selective substrate specificity. In this paper, the recombinant protein molecular structure of PLA2G1B was studied and novel therapeutic interventions were designed to disrupt PLA2G1B activity and impede tumor growth by targeting specific regions or residues in its structure. Construct protein-protein interaction networks and core genes using R\'s \"STRING\" program. LASSO, SVM-RFE and RF algorithms identified important genes associated with lung cancer. 282 deg were identified. Enrichment analysis showed that these genes were mainly related to adhesion and neuroactive ligand-receptor interaction pathways. PLA2G1B was subsequently identified as developing a preventative feature. GSEA showed that PLA2G1B is closely related to α-linolenic acid metabolism. Through the analysis of LASSO, SVM-RFE and RF algorithms, we found that PLA2G1B gene may be a preventive gene for lung cancer.
摘要：
肺癌是世界上最致命和最具侵袭性的恶性肿瘤。预防癌症至关重要。因此,新的分子靶点为肺癌的分子诊断和靶向治疗奠定了基础。PLA2G1B在脂质代谢和炎症中起关键作用。PLA2G1B具有选择性底物特异性。在本文中,研究了PLA2G1B的重组蛋白分子结构,并设计了新的治疗干预措施,通过靶向PLA2G1B结构中的特定区域或残基来破坏PLA2G1B活性并阻止肿瘤生长.使用R的“STRING”程序构建蛋白质-蛋白质相互作用网络和核心基因。拉索,SVM-RFE和RF算法确定了与肺癌相关的重要基因。鉴定了282度。富集分析表明，这些基因主要与粘附和神经活性配体-受体相互作用途径有关。PLA2G1B随后被确定为具有预防性特征。GSEA显示PLA2G1B与α-亚麻酸代谢密切相关。通过对LASSO的分析,SVM-RFE和RF算法，我们发现PLA2G1B基因可能是肺癌的预防基因。
