The CCANED-CIPHER Study: Early Cancer Detection and Treatment Response Monitoring Using AI-Based Platelet and Immune Cell Transcriptomic Profiling
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 6,000
- 试验地点
- 4
- 主要终点
- Identification of Platelet RNA Biomarkers Distinguishing Cancer Patients from Controls
研究概览
简要总结
The purpose of the CCANED-CIPHER study is to develop and validate an AI-based blood test for early cancer detection and to monitor treatment effectiveness in cancer patients. This two-phase, multi-center observational study aims to identify specific transcriptomic biomarkers in platelets and immune cells that distinguish cancer patients from healthy individuals and correlate with treatment outcomes. By analysing blood samples using artificial intelligence, the study seeks to create a safe, non-invasive method to enhance cancer diagnosis and monitor treatment responses over time.
详细描述
The CCANED-CIPHER study aims to revolutionise cancer diagnostics and treatment monitoring by developing and evaluating an AI-based early cancer detection tool that profiles RNA biomarkers from platelets and immune cells in blood samples. This non-invasive approach leverages liquid biopsy methods to enhance early cancer detection and provide insights into therapeutic responses.
Phase 1 (Common Cancer Early Detection [CCANED]): Early Cancer Detection
Objective:
To identify specific platelet-derived RNA biomarkers that can distinguish individuals with common cancers from healthy controls using AI-driven transcriptomic analysis.
Methodology:
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 40 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age: Adults aged 40 years or older.
- •Confirmed diagnosis of one of the following common cancers: Non-Small Cell Lung Cancer (NSCLC), Glioblastoma Multiforme (GBM), Colorectal Cancer, Hepatocellular Carcinoma (HCC), Breast Cancer, Prostate Cancer, Ovarian Cancer, Pancreatic Cancer.
排除标准
- •Currently pregnant.
- •Presence of any active infectious diseases.
- •Use of anticoagulant or antiplatelet drugs within the past 2 weeks.
- •Any medical or psychological conditions that may affect the participant's ability to comply with study procedures.
- •Phase 2 ( Cancer Immuno-Profiling of Hematologic and Extracellular RNA - CIPHER)
- •Inclusion Criteria:
- •Adults aged 40 years or older.
- •Confirmed diagnosis of: Hepatocellular Carcinoma (HCC), Non-Small Cell Lung Cancer (NSCLC)
- •Willingness to provide blood samples at the specified intervals (baseline, 6 weeks, and 6 months post-therapy initiation).
- •Exclusion Criteria:
- •Presence of another malignancy unless it has been in remission for at least 5 years.
- •Significant uncontrolled co-morbid conditions that may interfere with study participation or outcomes.
结局指标
主要结局
Identification of Platelet RNA Biomarkers Distinguishing Cancer Patients from Controls
时间窗: Baseline (single time point)
Utilise AI-based transcriptomic analysis of platelet RNA to identify biomarkers that differentiate between cancer patients and cancer-free controls.
Identification of RNA Biomarkers Correlating with Therapeutic Response (Phase 2)
时间窗: Baseline to 6 months post-therapy initiation
Identify RNA biomarkers from immune cells and platelets that correlate with clinical treatment response, as measured by standard criteria (e.g., RECIST)
Association Between Immune Cell Transcriptomes and AI-Based Platelet Signals
时间窗: Baseline to 6 months post-therapy initiation
Evaluate how changes in immune cell transcriptomes are associated with signals detected by the AI-based platelet profiling tool.
次要结局
- Sensitivity and Specificity of the AI-Based Diagnostic Tool (Phase 1)(Baseline)
- Feasibility of Platelet Transcriptomic Profiling Implementation(Phase 1 - 2 years)
- Development of Predictive Models for Treatment Outcomes (Phase 2)(Phase 2 - Two years)
- Identification of Biomarkers Predictive of Relapse and Drug Resistance (Phase 2)(Baseline to 6 months post-therapy initiation)
研究者
Javier Toledo
Chief Medical Officer
Dysplasia Diagnostics Limited