Integration of single-cell regulon atlas and multi-omics data for prognostic stratification and personalized treatment prediction in human lung adenocarcinoma

被引：2

作者：

Xiong, Yi ^{[1
,2
,3
]}

Zhang, Yihao ^{[1
,2
,3
]}

Liu, Na ^{[1
,2
,4
]}

Li, Yueshuo ^{[1
,2
,4
]}

Liu, Hongwei ^{[1
,2
]}

Yang, Qi ^{[1
,2
]}

Chen, Yu ^{[3
]}

Xia, Zhizhi ^{[5
]}

Chen, Xin ^{[6
]}

Wanggou, Siyi ^{[1
,2
]}

Li, Xuejun ^{[1
,2
]}

机构：

[1] Cent South Univ, Xiangya Hosp, Dept Neurosurg, Changsha 410008, Hunan, Peoples R China

[2] Cent South Univ, Xiangya Hosp, Hunan Int Sci & Technol Cooperat Base Brain Tumor, Changsha 410008, Hunan, Peoples R China

[3] Cent South Univ, Xiangya Sch Med, Changsha 410013, Peoples R China

[4] Cent South Univ, Xiangya Hosp, Postdoctoral Res Workstat, Changsha 410078, Hunan, Peoples R China

[5] Univ Toronto, Dept Pharmacol & Toxicol, Toronto, ON M5S 1A8, Canada

[6] Shanghai Jiao Tong Univ, Shanghai Songjiang Dist Cent Hosp, Songjiang Res Inst, Sch Med, Shanghai 201600, Peoples R China

来源：

JOURNAL OF TRANSLATIONAL MEDICINE | 2023年 / 21卷 / 01期

基金：

中国国家自然科学基金;

关键词：

LUAD; LPRI; Prognostic model; Transcriptional regulation; TCGA; Single cell RNA sequencing; TME; Chemotherapy and immunotherapy; DIFFERENTIATION; CANCER; LANDSCAPE; MODELS;

D O I：

10.1186/s12967-023-04331-z

中图分类号：

R-3 [医学研究方法]; R3 [基础医学];

学科分类号：

1001 ;

摘要：

Transcriptional programs are often dysregulated in cancers. A comprehensive investigation of potential regulons is critical to the understanding of tumorigeneses. We first constructed the regulatory networks from single-cell RNA sequencing data in human lung adenocarcinoma (LUAD). We next introduce LPRI (Lung Cancer Prognostic Regulon Index), a precision oncology framework to identify new biomarkers associated with prognosis by leveraging the single cell regulon atlas and bulk RNA sequencing or microarray datasets. We confirmed that LPRI could be a robust biomarker to guide prognosis stratification across lung adenocarcinoma cohorts. Finally, a multi-omics data analysis to characterize molecular alterations associated with LPRI was performed from The Cancer Genome Atlas (TCGA) dataset. Our study provides a comprehensive chart of regulons in LUAD. Additionally, LPRI will be used to help prognostic prediction and developing personalized treatment for future studies.

引用

页数：19

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