整合多组学分析和机器学习,完善肺腺癌的分子亚型、预后和免疫疗法。

IF 3.9 4区 生物学 Q1 GENETICS & HEREDITY Functional & Integrative Genomics Pub Date : 2024-06-27 DOI:10.1007/s10142-024-01388-x
Tao Han, Ying Bai, Yafeng Liu, Yunjia Dong, Chao Liang, Lu Gao, Jiawei Zhou, Jianqiang Guo, Jing Wu, Dong Hu
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引用次数: 0

摘要

肺腺癌(LUAD)具有侵袭性强、易转移的恶性特征。目前仍缺乏合适的生物标志物来促进精准治疗方案的完善。我们结合 10 种已知的聚类算法和来自 4 个维度的 omics 数据,确定了 LUAD 的高分辨率分子亚型。随后,我们基于亚型相关基因和包含10种机器学习算法的集成程序框架,开发了机器学习相关预后特征共识(CMRS)。研究人员从肿瘤微环境、基因组图谱、免疫治疗、药物敏感性和单细胞分析等角度分析了CMRS的效率。结果显示,通过多组学聚类分析,我们发现了2种综合组学亚型(CSs),其中CS1患者的生存预后更差,侵袭性、mRNAsi和突变频率更高。随后,我们根据 CS1 中上调的 13 个关键基因开发了 CMRS。CMRS的预后预测效率优于大多数已建立的LUAD预后特征。CMRS与肿瘤微环境特征变异和基因组不稳定性的产生有很强的相关性。在临床表现方面,高CMRS组患者更有可能从免疫疗法中获益,而低CMRS组患者更有可能从化疗和靶向药物疗法中获益。此外,我们还评估了奈拉替尼、寡霉素 A 等药物可能成为高 CMRS 组患者的候选药物。单细胞分析显示,CMRS 相关基因主要在上皮细胞中表达。本研究基于多组学数据发现的新型分子亚型可为LUAD的分层治疗提供新的见解,而CMRS的发展可作为精准治疗和免疫治疗LUAD获益程度的候选指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

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来源期刊
CiteScore
3.50
自引率
3.40%
发文量
92
审稿时长
2 months
期刊介绍: Functional & Integrative Genomics is devoted to large-scale studies of genomes and their functions, including systems analyses of biological processes. The journal will provide the research community an integrated platform where researchers can share, review and discuss their findings on important biological questions that will ultimately enable us to answer the fundamental question: How do genomes work?
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