Identify Prognostic Biomarkers of Lung Cancer

Lung Cancer Clinical Trial

Official title:

Multi-omics Combined With Clinical Data Analysis to Identify Prognostic Biomarkers of Lung Cancer

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05010330
• Other study ID #: MKM2021-720
• Status: Recruiting
• Start date: July 1, 2020
• Est. completion date: September 30, 2021

Study information

• Verified date: August 2021
• Source: RenJi Hospital
• Contact: Kaimin Mao, Doctor
• Phone: 86-15071027291
• Email: mkm444931158[@]126.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 500
• Est. completion date: September 30, 2021
• Est. primary completion date: September 20, 2021
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

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

Related Conditions & MeSH terms

• Adenocarcinoma of Lung
• Lung Adenocarcinoma
• Lung Cancer
• Lung Neoplasms
• Lung Squamous Cell Carcinoma
• Non Small Cell Lung Cancer

Locations

Country	Name	City	State
China	Renji Hospital, Shanghai Jiaotong University school of medicine	Shanghai

Sponsors (1)

Lead Sponsor	Collaborator
RenJi Hospital

Country where clinical trial is conducted

China, 

References & Publications (1)

Zhang Y, Yang M, Ng DM, Haleem M, Yi T, Hu S, Zhu H, Zhao G, Liao Q. Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD. Mol Ther Nucleic Acids. 2020 Sep 4;21:860-873. doi: 10.1016/j.omtn.2020.07.024 — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Identify some prognostic biomarkers in lung cancer.	Our study will identify some biomarkers that can predict the prognosis of lung cancer patients.; Our study will construct a new risk score model that provide a candidate model for prognostic evaluation of lung cancer.; 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.	1 week