Description

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

• Enrol 3,500 patients with confirmed diagnoses of various common cancers and 1,500 cancer-free controls matched by age and sex.
• Obtain a single blood sample from each participant at baseline.

Laboratory Analysis:

• Platelet Isolation from blood samples.
• RNA Sequencing and transcriptomic profiling to identify RNA expression patterns.

Data Analysis:

• Use machine learning algorithms to analyse RNA data and identify biomarkers indicative of cancer presence.
• Assess sensitivity and specificity of the diagnostic tool, and evaluate its ability to differentiate between cancer types.

Expected Outcomes:

• Identification of reliable RNA biomarkers for early cancer detection.
• Validation of the AI-based diagnostic tool's accuracy and feasibility in a clinical setting.

Phase 2 ( Cancer Immuno-Profiling of Hematologic and Extracellular RNA \[CIPHER\]): Therapeutic Response Monitoring

Objective

To evaluate how RNA biomarkers from immune cells and platelets correlate with therapeutic responses, providing insights into treatment efficacy and potential relapse.

Methodology

• Enrol 1,000 cancer patients diagnosed with HCC or NSCLC across stages I to IV.
• Baseline: Collect blood samples before therapy initiation.
• Follow-Up: Additional samples at 6 weeks and 6 months post-therapy initiation.

Laboratory Analysis:

• Isolation of Immune Cells and Platelets from blood samples.
• Analysis of RNA expression changes over time.

Data Analysis:

• Evaluate associations between RNA biomarkers and clinical treatment responses.
• Develop models integrating platelet and immune cell RNA profiles to predict outcomes.

Expected Outcomes:

• Identification of biomarkers that correlate with treatment responses and progression-free survival.
• Development of predictive models for relapse and drug resistance.

Significance of the Study

The CCANED-CIPHER study addresses critical needs in oncology by providing:

• A blood test that reduces the need for invasive tissue biopsies.
• Potential for identifying cancers at an earlier, more treatable stage.
• Tailored treatment strategies based on individual biomarker profiles.
• Enhanced ability to monitor treatment effectiveness and adjust therapies accordingly.
• Early detection of relapse or drug resistance, enabling prompt clinical interventions.

Expected Impact and Future Applications: The identification of specific RNA biomarkers from platelets and immune cells has the potential to transform current practices in oncology, offering a more efficient, accurate and patient-friendly approach to cancer care.