Clinical Trial Finder

Phase 1 (CCANED)

Inclusion Criteria:

• - 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.

Exclusion Criteria:

• - 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 (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.

Detailed 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 (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: Participant Recruitment: Enroll 3,500 patients with confirmed diagnoses of various common cancers and 1,500 cancer-free controls matched by age and sex. Sample Collection: Obtain a single blood sample from each participant at baseline. Laboratory Analysis: Platelet Isolation: Extract platelets from blood samples. RNA Sequencing: Perform transcriptomic profiling to identify RNA expression patterns. Data Analysis: AI Integration: Use machine learning algorithms to analyze RNA data and identify biomarkers indicative of cancer presence. Statistical Evaluation: 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 (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: Participant Recruitment: Enroll 1,000 cancer patients diagnosed with HCC or NSCLC across stages I to

• IV. Sample Collection: 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: Extract these components from blood samples. Transcriptomic Profiling: Analyse RNA expression changes over time. Data Analysis: Correlation Studies: Evaluate associations between RNA biomarkers and clinical treatment responses. Predictive Modelling: 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: Non-Invasive Diagnostics: A blood test that reduces the need for invasive tissue biopsies. Early Detection: Potential for identifying cancers at an earlier, more treatable stage. Personalised Medicine: Tailored treatment strategies based on individual biomarker profiles. Improved Monitoring: Enhanced ability to monitor treatment effectiveness and adjust therapies accordingly. Predictive Insights: Early detection of relapse or drug resistance, enabling prompt clinical interventions. Expected Impact and Future Applications By integrating advanced AI technologies with innovative liquid biopsy methods, the CCANED-CIPHER study aims to significantly improve cancer detection and patient outcomes. 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.

Arms

: Cancer Patients (Phase 1)

This arm will include 3,500 individuals with confirmed diagnoses of common cancers such as Non-Small Cell Lung Cancer (NSCLC), Glioblastoma Multiforme (GBM), Colorectal Cancer, Hepatocellular Carcinoma (HCC), Breast Cancer, Prostate Cancer, Ovarian Cancer, and Pancreatic Cancer.

: Healthy Individuals

This arm will consist of 1,500 age- and sex-matched cancer-free individuals serving as controls.

: Cancer Patients Undergoing Treatment

This cohort will include 1,000 patients diagnosed with Hepatocellular Carcinoma (HCC) or Non-Small Cell Lung Cancer (NSCLC) across stages I to IV who are about to commence standard cancer therapy.

Interventions

Diagnostic Test: - DiNanoQ: A multi-cancer early detection (MCED) blood test

Procedure: Participants will undergo a single blood draw at baseline. Sample Analysis: Platelet Isolation: Platelets will be extracted from the collected blood samples. RNA Analysis: RNA from the isolated platelets will be extracted and analyzed using AI-based transcriptomic profiling to identify biomarkers associated with cancer.

Other: - DiNanoTrack: Therapeutic Response Monitoring Blood Test

Procedures: Blood Sample Collection: Participants will have blood samples drawn at three time points: Baseline: Before therapy initiation. 6 Weeks Post-Therapy Initiation: To monitor early treatment response. 6 Months Post-Therapy Initiation: To assess longer-term therapeutic outcomes. Sample Analysis: Platelet and Immune Cell Isolation: Platelets: Extracted from each blood sample to continue monitoring RNA profiles. Immune Cells: Separated from the blood samples to analyse immune response to therapy. RNA Analysis: Platelet RNA: Analysed to observe changes in transcriptomic profiles over time using AI-based tools. Immune Cell RNA: Examined to assess transcriptomic changes associated with therapeutic responses. Data Correlation: Therapeutic Response Assessment: RNA profiles from platelets and immune cells will be correlated with clinical outcomes to identify biomarkers predictive of treatment efficacy, progression-free survival, relapse, and drug resistance.