Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.
Lung cancer is the leading cause of cancer-related death in China. In order to improve prognosis of lung cancer as well as provide new therapeutic targets, the identification of effective biomarkers for the prognosis of lung cancer is of great significance. It has been reported that some small molecules such as lncRNA, circRNA and polypeptides in human plasm have good prospects in diagnosing or evaluating the stage of diseases. In this study, we planned to use multi-omics combined with clinical data to discovery some small molecules that are potential to predict the prognosis of lung cancer patients. In addition, we want to construct a new risk score model that provide a candidate model for prognostic evaluation of lung cancer. And we hope our study can provide insights for precision immunotherapy of lung cancer by exploring the differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration between different risk score groups.
Study Type
OBSERVATIONAL
Enrollment
500
Renji Hospital, Shanghai Jiaotong University school of medicine
Shanghai, China
RECRUITINGIdentify some prognostic biomarkers in lung cancer.
1. Our study will identify some biomarkers that can predict the prognosis of lung cancer patients. 2. Our study will construct a new risk score model that provide a candidate model for prognostic evaluation of lung cancer. 3. Our research will provide insights for precision immunotherapy of lung cancer by exploring the differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration between different risk score groups.
Time frame: 1 week
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