肺腺癌多组学整合分析表4
肺腺癌多组学数据整合分析，用于识别分子亚型并指导精准治疗。
基本信息
资源简介
肺腺癌多组学整合分析表4
【一句话概览】
本数据集是 figshare 公开的多模态数据集，收录 1 个文件、合计 2.73 MB，主题涵盖 lung adenocarcinoma、molecular classification、multi-omics data、immunotherapy、precision medicine，可用于跨模态对齐与融合建模研究，CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Table_4_Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.XLSX》。配套论文《RETRACTED ARTICLE: Multi-omics analysis of genomics, epigenomics and transcriptomics for molecular subtypes and core genes for lung adenocarcinoma》发表于 BMC Cancer（2021），DOI：10.1186/s12885-021-07888-4。源站首次发布：2022-06-03。
【数据内容】
源站原始描述：Lung adenocarcinoma (LUAD) is one of the most common histological subtypes of lung cancer. The aim of this study was to construct consensus clusters based on multi-omics data and multiple algorithms. In order to identify specific molecular characteristics and facilitate the use of precision medicine on patients we used gene expression, DNA methylation, gene mutations, copy number variation data, and clinical data of LUAD patients for clustering. Consensus clusters were obtained using a consensus…
中文译文（机器翻译，仅供快速理解，请以原文为准）：肺腺癌（LUAD）是肺癌最常见的组织学亚型之一。本研究旨在基于多组学数据和多种算法构建共识聚类。为了识别特定分子特征并促进精准医学在患者中的应用，我们使用LUAD患者的基因表达、DNA甲基化、基因突变、拷贝数变异数据及临床数据进行聚类。通过五种多组学整合算法的共识集成获得共识聚类，并确定了四种分子亚型。CS1和CS2亚型预后较好。基于免疫和药物敏感性预测，我们推断CS1可能对免疫治疗反应较差，且对化疗药物敏感性较低。CS2细胞的高免疫浸润可能对免疫治疗反应良好。此外，CS2亚型也可能对EGFR分子靶向治疗有反应。CS3和CS4亚型与不良预后相关。这两种亚型突变更多，尤其是TP53突变，并且对肺癌化疗药物敏感性更高。然而，CS3富集于免疫相关通路，可能对anti-PD1免疫治疗有反应。此外，CS1和CS4对铁死亡
【数据结构与技术规格】
文件数 1 个，合计 2.73 MB。Table_4_Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.XLSX：application/vnd.openxmlformats-officedocument.spreadsheetml.sheet，2.73 MB。数据集 DOI：10.3389/fmed.2022.894338.s004。
【主题与分类】
源站学科分类：Radiology and Organ Imaging、Foetal Development and Medicine、Obstetrics and Gynaecology、Primary Health Care、Medical and Health Sciences not elsewhere classified、Dermatology。主题标签：lung adenocarcinoma、molecular classification、multi-omics data、immunotherapy、precision medicine。
【适用方向】
多模态数据适合跨模态对齐、融合建模与联合表征学习方向的研究。
【获取与许可】
源站页面：https://frontiersin.figshare.com/articles/dataset/Table_4_Multi-Omics_Integrative_Analysis_of_Lung_Adenocarcinoma_An_in_silico_Profiling_for_Precise_Medicine_XLSX/19974641
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Ruan, Xinjia; Ye, Yuqing; Cheng, Wenxuan; Xu, Li; Huang, Mengjia; Chen, Yi; et al. (2022). Table_4_Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.XLSX. Frontiers. Dataset
【使用注意】
· 源站最后修改于 2023-06-05，引用时请注意版本时效。
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使用方式
数据集获取（Figshare）
- 源站标题：Table_4_Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.XLSX
- DOI：10.3389/fmed.2022.894338.s004
- 发布日期：2022-06-03
- 文件数：1 个
- 文件总体积：2.73 MB
- 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_4_Multi-Omics_Integrative_Analysis_of_Lung_Adenocarcinoma_An_in_silico_Profiling_for_Precise_Medicine_XLSX/19974641
命令行下载
curl -L -o "Table_4_Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.XLSX" "https://ndownloader.figshare.com/files/35570795"
文件清单
Table_4_Multi-Omics Integrative Analysis of Lung Adenocarcinoma: An in silico Profiling for Precise Medicine.XLSX（2.73 MB）
文件总体积 2.73 MB（源站 API 实测）。
数据说明
Lung adenocarcinoma (LUAD) is one of the most common histological subtypes of lung cancer. The aim of this study was to construct consensus clusters based on multi-omics data and multiple algorithms. In order to identify specific molecular characteristics and facilitate the use of precision medicine on patients we used gene expression, DNA methylation, gene mutations, copy number variation data, and clinical data of LUAD patients for clustering. Consensus clusters were obtained using a consensus ensemble of five multi-omics integrative algorithms. Four molecular subtypes were identified. The CS1 and CS2 subtypes had better prognosis. Based on the immune and drug sensitivity predictions, we inferred that CS1 may be less responsive to immunotherapy and less sensitive to chemotherapeutic drugs. The high immune infiltration of CS2 cells may respond well to immunotherapy. Additionally, the CS2 subtype may also respond to EGFR molecular targeted therapy. The CS3 and CS4 subtypes were associated with poor prognosis. These two subtypes had more mutations, especially TP53 ones, as well as higher sensitivity to chemotherapeutics for lung cancer. However, CS3 was enriched in immune-related pathways and may respond to anti-PD1 immunotherapy. In addition, CS1 and CS4 were less sensitive to ferroptosis inhibitors. We performed a comprehensive analysis of the five types of omics data using five clustering algorithms to reveal the molecular characteristics of LUAD patients. These findings provide new insights into LUAD subtypes and potential clinical treatment strategies to guide personalized management and treatment.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fmed.2022.894338.s004（source: https://frontiersin.figshare.com/articles/dataset/Table_4_Multi-Omics_Integrative_Analysis_of_Lung_Adenocarcinoma_An_in_silico_Profiling_for_Precise_Medicine_XLSX/19974641）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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