The CCANED-CIPHER Study: Early Cancer Detection and Treatment Response Monitoring Using AI-Based Platelet and Immune Cell Transcriptomic Profiling

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.