Clinical trial · Observational
Identify Prognostic Biomarkers of Lung Cancer
Multi-omics Combined With Clinical Data Analysis to Identify Prognostic Biomarkers of Lung Cancer
NCT05010330CI-TRIAL-00053354unknownClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.
Conditions
Conditions (4)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Adenocarcinoma | Lung Adenocarcinoma | ONTOLOGY_EXACT | 0.98 |
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
| Lung Squamous Cell Carcinoma | Lung Squamous Cell Carcinoma | ONTOLOGY_EXACT | 0.98 |
| Non Small Cell Lung Cancer | Lung Non-Small Cell Carcinoma | ALIAS | 0.90 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (2)
- label
- healthy control
- description
- healthy people
- label
- lung cancer
- description
- patients diagnosed with lung cancer
Primary outcomes (1)
- measure
- Identify some prognostic biomarkers in lung cancer.
- timeFrame
- 1 week
- description
- 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.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 80 Years
Show eligibility criteria text
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
References
Publications (1)
- RESULTZhang 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. Epub 2020 Jul 23. PMID 32805489