论文标题
系统分析揭示了关键的microRNA作为肺癌进行性阶段的诊断和预后因素
Systematic analysis reveals key microRNAs as diagnostic and prognostic factors in progressive stages of lung cancer
论文作者
论文摘要
microRNA在从有机体发育到肿瘤进展的许多生物学过程中起着必不可少的作用。在肿瘤学中，这些microRNA在癌症病理学中构成了基本调节作用，该作用为通过转录组数据探究对临床特征的影响提供了基础。以前的工作着重于机器学习（ML）在不同的癌症数据库中搜索生物标志物，但是这些生物标志物的功能尚不清楚。将肺癌作为研究的原型案例。通过将临床信息整合到成绩单表达数据中，我们系统地分析了microRNA对恶化肺腺癌（LUAD）对诊断和预后因素的影响。降低尺寸后，使用无监督的分层聚类来找到代表各个患者阶段microRNA独特表达模式的诊断因素。此外，我们开发了一个分类框架，轻梯度增强机（LightGBM）和Shapley添加说明（SHAP）算法，以筛选出预后因素。富集分析表明，诊断和预后因素不仅富含与癌症相关的ATHWays，而且还参与了许多重要的细胞信号转导和免疫反应。 These key microRNAs also impact the survival risk of LUAD patients at all (or a specific) stage(s) and some of them target some important Transcription Factors (TF).The key finding is that five microRNAs (hsa-mir-196b, hsa-mir-31, hsa-mir-891a, hsa-mir-34c, and hsa-mir-653) can then serve as not only potential diagnostic factors but also监测肺癌的预后工具。
MicroRNAs play an indispensable role in numerous biological processes ranging from organismic development to tumor progression.In oncology,these microRNAs constitute a fundamental regulation role in the pathology of cancer that provides the basis for probing into the influences on clinical features through transcriptome data. Previous work focused on machine learning (ML) for searching biomarkers in different cancer databases, but the functions of these biomarkers are fully not clear. Taking lung cancer as a prototype case of study. Through integrating clinical information into the transcripts expression data, we systematically analyzed the effect of microRNA on diagnostic and prognostic factors at deteriorative lung adenocarcinoma (LUAD). After dimension reduction, unsupervised hierarchical clustering was used to find the diagnostic factors which represent the unique expression patterns of microRNA at various patient's stages. In addition, we developed a classification framework, Light Gradient Boosting Machine (LightGBM) and SHAPley Additive explanation (SHAP) algorithm, to screen out the prognostic factors. Enrichment analyses show that the diagnostic and prognostic factors are not only enriched in cancer-related athways, but also involved in many vital cellular signaling transduction and immune responses. These key microRNAs also impact the survival risk of LUAD patients at all (or a specific) stage(s) and some of them target some important Transcription Factors (TF).The key finding is that five microRNAs (hsa-mir-196b, hsa-mir-31, hsa-mir-891a, hsa-mir-34c, and hsa-mir-653) can then serve as not only potential diagnostic factors but also prognostic tools in the monitoring of lung cancer.
