Lung Adenocarcinoma, Lung Cancer, Lung Squamous Cell Carcinoma, Non Small Cell Lung Cancer
Conditions
Brief summary
Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.
Detailed description
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.
Interventions
None listed
Sponsors
RenJi Hospital
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
Yes
Inclusion criteria
* 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.
Exclusion criteria
* Patients with other tumors; * Lung cancer patients who had been treated; * Abnormal liver and kidney function; * Acute and chronic infectious diseases
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Identify some prognostic biomarkers in lung cancer. | 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. |
Countries
China
Contacts
Primary ContactKaimin Mao, Doctor
Backup ContactHuang, Doctor
Outcome results
None listed