Multi-omics Combined With Clinical Data Analysis to Identify Prognostic Biomarkers of Lung Cancer
试验速览
- 阶段
- 不适用
- 入组人数
- 500
- 试验地点
- 1
- 主要终点
- Identify some prognostic biomarkers in lung cancer.
研究概览
简要总结
Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Patients diagnosed with lung cancer;
- •Untreated lung cancer patients;
- •No history of chronic or serious diseases, such as cardiovascular disease, liver disease, kidney disease, respiratory disease, blood disease, lymphatic disease, endocrine disease, immune disease, mental disease, neuromuscular disease, gastrointestinal system disease, etc.
排除标准
- •Patients with other tumors;
- •Lung cancer patients who had been treated;
- •Abnormal liver and kidney function;
- •Acute and chronic infectious diseases
结局指标
主要结局
Identify some prognostic biomarkers in lung cancer.
时间窗: 1 week
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.
次要结局
未报告次要终点