Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Using 4D Urinary Proteomics to Predict and Evaluate Treatment Response in Colorectal Cancer

Cancer Institute and Hospital, Chinese Academy of Medical Sciences · 2025
ClinicalTrials.gov · Datasets · License: Public Domain · 2025
Open Source ↗
colorectal-cancer-crcneoadjuvant-therapyproteomics
The goal of this observational study is to learn how well urinary proteins can predict treatment response in patients with locally advanced colorectal cancer (LACC) undergoing neoadjuvant therapy. The main question it aims to answer is: Can urinary protein markers help predict and evaluate how patients with LACC respond to neoadjuvant therapy? Participants diagnosed with LACC will provide urine samples before and after neoadjuvant therapy. These samples will be analyzed using 4D deep urinary proteomics and machine learning to identify proteins linked to treatment response. Some participants' tumor tissues will also be used to create organoid models for further testing.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1340216
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive