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.

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.

The study population will consist of patients with a confirmed pathological diagnosis of colorectal cancer or lung cancer. Eligible participants include adults who have undergone diagnostic biopsy or surgical resection yielding tumor tissue available for analysis. Clinical data and corresponding tumor specimens (including H&E slides, paraffin blocks, and discarded ex vivo tissue) will be collected. All cases were prospectively collected from Nanfang Hospital, Southern Medical University.

Requests for the data collected and analyzed in this study will be considered if the application is in line with public benefits and the applicant is willing to sign a data access agreement. Contact can be through the corresponding author.