Skip to main content
OpenTrials
Recruiting

NCT Number: NCT06778512

LcProt: Proteomics Longitudinal Cohort Study on Lung Cancer

This study will utilize tissue and peripheral blood samples for proteomics analysis and establish a longitudinal proteomics cohort at multiple critical treatment time points to explore the research value of proteomics in the diagnosis and treatment of lung cancer. The study includes key time points such as screening, postoperative efficacy prediction, and efficacy prediction after medication.

Recruiting

Interested in participating?

Request Info

Key information

Conditions

Lung Cancer Lung Cancer Lung Diseases Lung Neoplasms NSCLC Neoplasms Neoplasms by Site Respiratory Tract Diseases Respiratory Tract Neoplasms Thoracic Neoplasms

Age range

18 year–75 year

Sex eligibility

All sexes

Study type

Observational

Primary location

the First Affiliated of Guangzhou Medical University

Guangzhou, Guangdong, 510120, China

Location status: Recruiting

Location contact

Jianxing He, Professor

CONTACT

[email protected]

86-20-83337792

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Signing of the informed consent form;
  • Male or female, aged 18-75 years;
  • Patients with lung nodules confirmed by CT examination;
  • Good preoperative pulmonary function cooperation and complete reporting;
  • Preoperative chest single/dual phase CT scans without significant artefacts and with complete imaging;
  • The interval between preoperative pulmonary function and single/dual phase CT scans does not exceed one month.

Exclusion criteria

  • Poor preoperative pulmonary function cooperation or missing reports;
  • Preoperative chest single/dual phase CT scans exhibit significant artefacts or image omission;
  • The interval between preoperative pulmonary function and single/dual phase CT scans exceeds one month;
  • Complication with severe respiratory disorders (such as lung transplantation, pneumothorax, giant bullae, etc.);
  • Coexisting with other severe functional impairments;
  • Patients with obstructive lesions such as airway or esophageal stenosis;

(8) Medication use before pulmonary function testing that does not meet the cessation guidelines; (9) Pulmonary function report quality graded D-F.

Treatment and study plan

Using tissue and peripheral blood proteomics to distinguish the benign and malignant nature of lung cancer in patients, as well as to evaluate therapeutic efficacy and long-term prognosis during the t

Other

Peripheral blood samples from enrolled participants will be drawn, or lesion tissues will be obtained through procedures such as biopsy or surgery, followed by quantitative proteomics analysis using mass spectrometry.

Other names: Draw peripheral blood, Obtain lesion tissue

Primary outcomes

  1. Area Under the Curve

    Time frame: 3 years

    AUC, or Area Under the Curve, is a commonly used metric in statistical and machine learning models, particularly for evaluating the performance of classification models. It refers to the area under the Receiver Operating Characteristic (ROC) curve, which plots the true positive rate (sensitivity) against the false positive rate (1-specificity) at various threshold settings. An AUC value ranges from 0 to 1, where:

    • 1 indicates a perfect model,
    • 0.5 suggests a model no better than random guessing,
    • < 0.5 reflects a model performing worse than random.

    In clinical studies, AUC is often used to assess diagnostic tests, where a higher AUC indicates better test accuracy in distinguishing between conditions (e.g., disease vs. no disease).

Secondary outcomes

  1. Differentially Expressed Proteins

    Time frame: 3 years

    Differential proteins, or differentially expressed proteins (DEPs), refer to proteins that show significant changes in expression levels between different biological or experimental conditions, such as disease vs. healthy states, treated vs. untreated groups, or across time points in longitudinal studies. These proteins are identified through quantitative proteomics techniques, including mass spectrometry or label-free methods, and analyzed using statistical or bioinformatics tools to determine significance.

Study contacts

Contact information is provided by the study sponsor or research team.

Jianxing He, Professor

CONTACT

[email protected]

86-20-83337792

Sponsors and collaborators

Lead sponsor

The First Affiliated Hospital of Guangzhou Medical University

Other

Registry information

Official study title

LcProt: Proteomics Longitudinal Cohort Study on Lung CancerProspective Longitudinal Cohort Study of Lung Cancer Based on Peripheral Blood and Tissue Proteomics

Important dates

Study start
2019
Primary completion
2026
Study completion
2026
First posted
Jan 16, 2025
Registry last updated
Jan 16, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.