| Title |
Metabolomic Machine Learning-based Model Predicts Efficacy of Chemoimmunotherapy for Advanced Lung Squamous Cell Carcinoma |
| Description |
Chemoimmunotherapy has now become the standard first-line treatment for individuals diagnosed with advanced lung squamous carcinoma. Serum metabolomics holds significant potential for application in predicting responses to chemoimmunotherapy and is capable of identifying and validating potential biomarkers. The aim of the study was to establish a model that can predict the prognosis of chemoimmunotherapy in patients with advanced lung squamous cell carcinoma, integrating metabolomics with machine learning techniques. |
| Organism |
Homo sapiens |
| Data Type |
Metabolome Data by Mass Spectrometry (MS) |
| Data Accessibility |
Controlled-access |
| BioProject |
PRJCA037927 |
| Release Date |
2025-03-31 |
| Submitter |
Xueyan Zhang (zxychest0109@163.com) |
| Organization |
Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University |
| Submission Date |
2025-03-29 |