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Recruiting NCT07239063

NCT07239063 Validation of High-Throughput Large-Format Tissue Preprocessing for Lung and Colorectal Cancer

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Clinical Trial Summary
NCT ID NCT07239063
Status Recruiting
Phase
Sponsor Nanfang Hospital, Southern Medical University
Condition CRC (Colorectal Cancer)
Study Type OBSERVATIONAL
Enrollment 1,000 participants
Start Date 2024-10-01
Primary Completion 2026-12

Eligibility & Interventions

Sex All sexes
Min Age N/A
Max Age N/A
Study Type OBSERVATIONAL

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 1,000 participants in total. It began in 2024-10-01 with a primary completion date of 2026-12.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief Summary

This project aims to employ a sample preprocessing system in conjunction with three-dimensional imaging techniques to generate morphologically more complete, high-resolution datasets for lung and colorectal cancers. Building on systematic experimental optimization of the preprocessing system, the investigators will establish tissue-clearing workflows and transparency assessment criteria specifically for lung and colorectal cancer specimens, and develop and validate an efficient 3D immunofluorescent iterative staining protocol adapted for these tumor types to achieve robust three-dimensional imaging. Successful implementation of this project will enable an in-depth characterization of the spatial morphological features of lung and colorectal cancer pathology, facilitate identification of more effective and precise interventional strategies, and ultimately contribute to improved overall survival for cancer patients. Additionally, the resulting datasets will support prospective validation of two-dimensional pathological models.

Eligibility Criteria

Inclusion Criteria: 1. Patients who have been pathologically diagnosed as having lung cancer or colorectal cancer. 2. Patients with complete clinical data and tumor tissue materials, including H\&E slides, paraffin blocks, and discarded ex vivo specimens. Exclusion Criteria: 1.Patients with missing data or specimens not meeting quality control requirements for analysis.

Contact & Investigator

Central Contact

Zhengyu Zhang

✉ zzyusmu@163.com

📞 +8613837365993

Principal Investigator

Liang Li

STUDY DIRECTOR

Nanfang Hospital, Southern Medical University

Frequently Asked Questions

Who can join the NCT07239063 clinical trial?

This trial is open to participants of all sexes, studying CRC (Colorectal Cancer). Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT07239063 currently recruiting?

Yes, NCT07239063 is actively recruiting participants. Contact the research team at zzyusmu@163.com for enrollment information.

Where is the NCT07239063 trial being conducted?

This trial is being conducted at Guangzhou, China.

Who is sponsoring the NCT07239063 clinical trial?

NCT07239063 is sponsored by Nanfang Hospital, Southern Medical University. The principal investigator is Liang Li at Nanfang Hospital, Southern Medical University. The trial plans to enroll 1,000 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: April 2026  ·  Data Methodology