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

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.

Study Overview

• Status: Recruiting
• Conditions: Colorectal Cancer; Ovarian Cancer; Liver Carcinoma; Glioblastoma (GBM); Pancreatic Cancer, Adult; Lung Cancer (NSCLC); Prostate Cancers; Brest Cancer
• Intervention / Treatment: Diagnostic test: DiNanoQ: A multi-cancer early detection (MCED) blood test; Other: DiNanoTrack: Therapeutic Response Monitoring Blood Test

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 (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.

• Study Type: Observational
• Enrollment (Estimated): 6000

Contacts and Locations

• Study Contact: Name: Javier Toledo, Medical Degree; Phone Number: +44 (0)1223 496000; Email: research@dysplasiadx.com
• Study Contact Backup: Name: Osagie Izuogu, PhD; Phone Number: +44 (0)1223 496000; Email: info@dysplasiadx.com

Study Locations

• Argentina
  • Rosario, Argentina
    • Active, not recruiting
    • Various Cancer Centres
• Nigeria
  • Lagos, Nigeria
    • Recruiting
    • NSIA- Lagos University Teaching Hospital Cancer Centre
    • Contact: Adewumi Alabi, Oncology; Phone Number: +2348052843206; Email: aalabi@nlcc.ng
    • Contact: Solomon Rotimi, Ph.D; Email: solomon@dysplasiadx.com
• United Kingdom
  • Cambridge, United Kingdom, CB22 3AT
    • Enrolling by invitation
    • Babraham Research Institute
  • London, United Kingdom, W1W 7LT
    • Recruiting
    • Dysplasia Diagnostics Limited
    • Contact: Chief Medical Officer, Medical; Phone Number: +447494946013; Email: research@dysplasiadx.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

The CCANED-CIPHER study will enroll a diverse, geographically dispersed population to ensure the generalizability and robustness of its findings. The study is divided into two phases, utilizing up to 10 medical centers globally across the United Kingdom (UK), Europe, America, and Asia.

Phase 1 (CCANED):

Participants: 5,000 adults aged 40 years or older.

• Cancer Patients: 3,500 individuals with confirmed diagnoses of common cancers.
• Healthy Controls: 1,500 age-matched cancer-free individuals.

Recruitment Strategy: Participants will be identified and enrolled through the participating medical centers, ensuring a representative sample across different geographical locations.

Phase 2 (CIPHER):

Participants: 1,000 adults aged 40 years or older diagnosed with HCC or NSCLC across stages I to IV.

Recruitment Strategy: Cancer patients will be recruited from the participating cancer centers, ensuring a wide representation of disease stages and treatment backgrounds.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
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.	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.
Healthy Individuals; This arm will consist of 1,500 age- and sex-matched cancer-free individuals serving as controls.	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.
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.	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identification of Platelet RNA Biomarkers Distinguishing Cancer Patients from Controls	Utilise AI-based transcriptomic analysis of platelet RNA to identify biomarkers that differentiate between cancer patients and cancer-free controls.	Baseline (single time point)
Identification of RNA Biomarkers Correlating with Therapeutic Response (Phase 2)	Identify RNA biomarkers from immune cells and platelets that correlate with clinical treatment response, as measured by standard criteria (e.g., RECIST)	Baseline to 6 months post-therapy initiation
Association Between Immune Cell Transcriptomes and AI-Based Platelet Signals	Evaluate how changes in immune cell transcriptomes are associated with signals detected by the AI-based platelet profiling tool.	Baseline to 6 months post-therapy initiation

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity and Specificity of the AI-Based Diagnostic Tool (Phase 1)	Calculate the diagnostic accuracy of the AI-based tool in detecting cancer among participants.	Baseline
Feasibility of Platelet Transcriptomic Profiling Implementation	Assess the practicality of sample collection, processing, and analysis in a clinical setting.	Phase 1 - 2 years
Development of Predictive Models for Treatment Outcomes (Phase 2)	Create and validate predictive models that integrate platelet and immune cell RNA profiles to predict treatment response and progression-free survival.	Phase 2 - Two years
Identification of Biomarkers Predictive of Relapse and Drug Resistance (Phase 2)	Identify RNA biomarkers predictive of relapse and drug resistance at the 6-month follow-up.	Baseline to 6 months post-therapy initiation

Collaborators and Investigators

• Sponsor: Javier Toledo
• Investigators: Study Director: Solomon Rotimi, PhD, Dysplasia Diagnostics Limited; Principal Investigator: Javier Toledo, Medical Degree, Dysplasia Diagnostics Limited

Publications and helpful links

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Helpful Links

• WHO report

Study record dates

Study Major Dates

• Study Start (Actual): December 20, 2025
• Primary Completion (Estimated): August 1, 2027
• Study Completion (Estimated): August 1, 2028

Study Registration Dates

• First Submitted: November 28, 2024
• First Submitted That Met QC Criteria: December 3, 2024
• First Posted (Actual): December 5, 2024

Study Record Updates

• Last Update Posted (Estimated): January 2, 2026
• Last Update Submitted That Met QC Criteria: December 29, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Biomarker; Cancer; Oncology; Platelets; Liquid Biopsy; Precision Medicine; RNA; cancer screening; treatment response; Circulating Tumor DNA (ctDNA); Early Cancer Detection; Splicing; Health Data Analysis; AI-based Diagnostics; RNA Profiling; CircRNA
• Additional Relevant MeSH Terms: Urogenital Diseases; Genital Diseases; Endocrine System Diseases; Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Genital Diseases, Male; Prostatic Diseases; Male Urogenital Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Intestinal Diseases; Respiratory Tract Diseases; Neoplasms by Histologic Type; Gastrointestinal Neoplasms; Digestive System Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Intestinal Neoplasms; Rectal Diseases; Genital Diseases, Female; Lung Diseases; Endocrine Gland Neoplasms; Liver Diseases; Neoplasms, Glandular and Epithelial; Adenocarcinoma; Liver Neoplasms; Respiratory Tract Neoplasms; Thoracic Neoplasms; Colonic Diseases; Ovarian Diseases; Adnexal Diseases; Genital Neoplasms, Female; Gonadal Disorders; Carcinoma; Astrocytoma; Glioma; Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms, Nerve Tissue; Carcinoma, Bronchogenic; Bronchial Neoplasms; Neoplasms; Prostatic Neoplasms; Carcinoma, Hepatocellular; Lung Neoplasms; Colorectal Neoplasms; Ovarian Neoplasms; Glioblastoma; Carcinoma, Non-Small-Cell Lung; Pancreatic cancer, adult; Investigative Techniques; Clinical Laboratory Techniques; Diagnostic Techniques and Procedures; Diagnosis; Hematologic Tests
• Other Study ID Numbers: CCANED-CIPHER

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No