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.