Xiong Jiali, Xiao Kailan, He Huiyang, Tian Yuqiu
Department of Respiratory and Critical Medicine, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Department of Ultrasound Diagnosis, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Discov Oncol. 2024 Oct 29;15(1):600. doi: 10.1007/s12672-024-01469-0.
Using various bioinformatics tools, we constructed a prognostic model integrating the expression profiles of lipid metabolization-related lncRNAs and clinical features. Our study discovered that various lipid metabolism-related lncRNAs were linked to the prognosis of lung adenocarcinoma. The link between immune cell infiltration in the tumour microenvironment and the expression level of lncRNAs involved with lipid metabolism was also investigated. Our findings suggest that there is a complex interplay between lipid metabolism, microenvironmental heterogeneity, and immunotherapy in lung adenocarcinoma. Furthermore, the study has significant clinical implications for the development of effective therapies for patients with lung adenocarcinoma by investigating the potential of these lncRNAs as biomarkers for anticipating the response to immunotherapy. Finally, our study emphasises the significance of continued analysis of lncRNAs associated with lipid metabolism in tumours to better understand the mechanisms behind the incidence and progression of lung adenocarcinoma. Several of the strengths of our work are the extensive analysis of the relationship between lipid metabolism and lncRNAs in lung adenocarcinoma and the utilization of a sizable sample size from the TCGA-LUAD cohort. However, there are also some limitations. Firstly, the mechanisms of how these lncRNAs interact with lipid metabolism pathways and immune response require further investigation. Secondly, our study was based on bioinformatics analysis and lacked experimental verification. Finally, our study was limited to the TCGA-LUAD cohort and further validation using other independent cohorts is required. In conclusion, our study provides a comprehensive and systematic analysis of lncRNAs associated with lipid metabolism in lung adenocarcinoma. Lung cancer patients may benefit from using identified lncRNAs as therapeutic targets and prognostic biomarkers. Validating these findings and confirming the potential therapeutic applications of these lncRNAs will require more mechanistic research.
利用各种生物信息学工具，我们构建了一个整合脂质代谢相关长链非编码RNA（lncRNA）表达谱和临床特征的预后模型。我们的研究发现，多种脂质代谢相关lncRNA与肺腺癌的预后相关。我们还研究了肿瘤微环境中免疫细胞浸润与参与脂质代谢的lncRNA表达水平之间的联系。我们的研究结果表明，在肺腺癌中，脂质代谢、微环境异质性和免疫治疗之间存在复杂的相互作用。此外，通过研究这些lncRNA作为预测免疫治疗反应的生物标志物的潜力，该研究对开发针对肺腺癌患者的有效治疗方法具有重要的临床意义。最后，我们的研究强调了持续分析肿瘤中与脂质代谢相关的lncRNA的重要性，以便更好地理解肺腺癌发生和进展背后的机制。我们工作的几个优点是对肺腺癌中脂质代谢与lncRNA之间的关系进行了广泛分析，并利用了来自TCGA-LUAD队列的大量样本。然而，也存在一些局限性。首先，这些lncRNA如何与脂质代谢途径和免疫反应相互作用的机制需要进一步研究。其次，我们的研究基于生物信息学分析，缺乏实验验证。最后，我们的研究仅限于TCGA-LUAD队列，需要使用其他独立队列进行进一步验证。总之，我们的研究对肺腺癌中与脂质代谢相关的lncRNA进行了全面系统的分析。肺癌患者可能会受益于将已鉴定的lncRNA用作治疗靶点和预后生物标志物。验证这些发现并确认这些lncRNA的潜在治疗应用将需要更多的机制研究。
