| Accession |
PRJCA007120 |
| Title |
Systematic analyses of early-stage lung cancer by scRNA-seq and lipidomic reveals aberrant lipid metabolism as detection biomarkers |
| Relevance |
Medical |
| Data types |
lipidomics
|
| Organisms |
Homo sapiens
|
| 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, 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. |
| Sample scope |
Multiisolate |
| Release date |
2021-11-09 |
| Publication |
| PubMed ID |
Article title |
Journal name |
DOI |
Year |
| 35108060
|
Lung cancer scRNA-seq and lipidomics reveal aberrant lipid metabolism for early-stage diagnosis
|
Science Translational Medicine
|
10.1126/scitranslmed.abk2756
|
2023
|
|
|
| Data provider |
|
| Biomaterial provider |
Mantang Qiu |
| Grants |
| Agency |
program |
Grant ID |
Grant title |
| National Natural Science Foundation of China (NSFC)
|
Young Scientists Fund
|
82102692
|
|
|
|
| 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 |
2021-11-07 |
