Decoding LncRNA in COPD: Unveiling Prognostic and Diagnostic Power and Their Driving Role in Lung Cancer Progression

解码慢性阻塞性肺疾病中的长链非编码RNA:揭示其预后和诊断价值及其在肺癌进展中的驱动作用

阅读:1

Abstract

Chronic obstructive pulmonary disease (COPD) and lung cancer represent formidable challenges in global health, characterized by intricate pathophysiological mechanisms and multifaceted disease progression. This comprehensive review integrates insights from diverse perspectives to elucidate the intricate roles of long non-coding RNAs (lncRNAs) in the pathogenesis of COPD and lung cancer, focusing on their diagnostic, prognostic, and therapeutic implications. In the context of COPD, dysregulated lncRNAs, such as NEAT1, TUG1, MALAT1, HOTAIR, and GAS5, emerge as pivotal regulators of genes involved in the disease pathogenesis and progression. Their identification, profiling, and correlation with the disease severity present promising avenues for prognostic and diagnostic applications, thereby shaping personalized disease interventions. These lncRNAs are also implicated in lung cancer, underscoring their multifaceted roles and therapeutic potential across both diseases. In the domain of lung cancer, lncRNAs play intricate modulatory roles in disease progression, offering avenues for innovative therapeutic approaches and prognostic indicators. LncRNA-mediated immune responses have been shown to drive lung cancer progression by modulating the tumor microenvironment, influencing immune cell infiltration, and altering cytokine production. Their dysregulation significantly contributes to tumor growth, metastasis, and chemo-resistance, thereby emphasizing their significance as therapeutic targets and prognostic markers. This review summarizes the transformative potential of lncRNA-based diagnostics and therapeutics for COPD and lung cancer, offering valuable insights into future research directions for clinical translation and therapeutic development.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。