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NCT Number: NCT06717295

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

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.

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Key information

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Phase 1 (Common Cancer Early Detection - 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 ( 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.

Treatment and study plan

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

Diagnostic 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.

DiNanoTrack: Therapeutic Response Monitoring Blood Test

Other

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.

Primary outcomes

  1. Identification of Platelet RNA Biomarkers Distinguishing Cancer Patients from Controls

    Time frame: Baseline (single time point)

    Utilise AI-based transcriptomic analysis of platelet RNA to identify biomarkers that differentiate between cancer patients and cancer-free controls.

  2. Identification of RNA Biomarkers Correlating with Therapeutic Response (Phase 2)

    Time frame: 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)

  3. Association Between Immune Cell Transcriptomes and AI-Based Platelet Signals

    Time frame: 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.

Secondary outcomes

  1. Sensitivity and Specificity of the AI-Based Diagnostic Tool (Phase 1)

    Time frame: Baseline

    Calculate the diagnostic accuracy of the AI-based tool in detecting cancer among participants.

  2. Feasibility of Platelet Transcriptomic Profiling Implementation

    Time frame: Phase 1 - 2 years

    Assess the practicality of sample collection, processing, and analysis in a clinical setting.

  3. Development of Predictive Models for Treatment Outcomes (Phase 2)

    Time frame: Phase 2 - Two years

    Create and validate predictive models that integrate platelet and immune cell RNA profiles to predict treatment response and progression-free survival.

  4. Identification of Biomarkers Predictive of Relapse and Drug Resistance (Phase 2)

    Time frame: Baseline to 6 months post-therapy initiation

    Identify RNA biomarkers predictive of relapse and drug resistance at the 6-month follow-up.

Study contacts

Contact information is provided by the study sponsor or research team.

Javier Toledo, Medical Degree

CONTACT

[email protected]

+44 (0)1223 496000

Osagie Izuogu, PhD

CONTACT

[email protected]

+44 (0)1223 496000

Sponsors and collaborators

Lead sponsor

Javier Toledo

Industry

Registry information

Acronym: CCANED-CIPHER

Important dates

Study start
2025
Primary completion
2027
Study completion
2028
First posted
Dec 5, 2024
Registry last updated
Jan 2, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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