| Title |
Systematic analyses of early-stage lung cancer by scRNA-seq and lipidomic reveals aberrant lipid metabolism as detection biomarkers |
| Description |
Lung cancer is the leading cause of cancer mortality and early detection is the key to improve survival. However, there are no reliable blood-based tests currently available for early-stage lung cancer diagnosis. Here, we performed single-cell RNA sequencing of early-stage lung cancer and found lipid metabolism was broadly dysregulated in different cell types and glycerophospholipid metabolism is the most significantly altered lipid metabolism-related pathway. Untargeted lipidomics were detected in an exploratory cohort of 311 participants. Through support vector machine algorithm-based and mass spectrum-based feature selection, we have identified nine lipids as the most important detection features and developed a LC-MS-based targeted assay utilizing multiple reaction monitoring. |
| Organism |
Homo sapiens |
| Data Type |
Mixed |
| Data Accessibility |
Controlled-access |
| BioProject |
PRJCA007120 |
| Release Date |
2021-11-09 |
| Submitter |
Guangxi Wang (guangxiwang@bjmu.edu.cn) |
| Organization |
Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center |
| Submission Date |
2021-11-09 |