Radiogenomic Profiling of Dendritic Cells and Macrophages to Predict Recurrence in Colorectal Liver Metastasis (RaP-DMac-LiMe)

August 4, 2026 updated by: Famularo Simone, Fondazione Policlinico Universitario Agostino Gemelli IRCCS

The RaP-DMac-LiMe study (Radiogenomic Profiling of Dendritic Cells and Macrophages to Predict Recurrence in Colorectal Liver Metastasis) is a monocentric, non-profit observational study promoted by Fondazione Policlinico Universitario A. Gemelli IRCCS. Its primary aim is to identify immunological, genomic, and radiomic biomarkers associated with recurrence risk in patients with colorectal liver metastases (CRLM) undergoing curative-intent liver resection.

The study is based on the need to improve prognostic stratification in CRLM by integrating information from the tumor immune microenvironment, tumor genomics, radiomics, and clinical data. Particular attention is given to myeloid immune cells, especially dendritic cells and tumor-associated macrophages, whose role in metastatic progression and recurrence remains insufficiently understood.

The primary objective is to assess the association between myeloid immune profiles and recurrence risk through integrated molecular, spatial, genomic, and radiological analyses. Secondary objectives include characterizing the transcriptomic and genomic features of dendritic cells and macrophages, identifying radiomic and circulating tumor DNA (ctDNA) biomarkers, and evaluating their potential as non-invasive tools for recurrence prediction and patient stratification.

The study includes a retrospective cohort of approximately 160 patients treated between 2009 and 2023 and a prospective cohort of approximately 50 patients who will be followed for 24 months. Tumor tissue samples, peripheral blood, imaging data (CT/MRI), and clinical information collected during routine care will be analyzed without introducing any experimental interventions or deviations from standard clinical practice.

Analyses will include transcriptomic profiling, multiplex spatial characterization of immune cells, circulating tumor DNA sequencing using next-generation sequencing technologies, radiomic feature extraction, and integration of all data using statistical and machine learning approaches. Predictive models will be trained on retrospective data and independently validated in the prospective cohort.

The primary endpoint is the prediction of colorectal liver metastasis recurrence within two years after liver resection. Ultimately, the study aims to develop and validate a multimodal predictive model integrating immune, genomic, radiomic, and clinical variables to improve recurrence risk assessment and support personalized patient management.

The overall study duration is 36 months. All procedures will be conducted in accordance with ethical standards and data protection regulations, with samples and clinical data pseudonymized and handled in compliance with the GDPR.

Study Overview

Study Type

Observational

Enrollment (Estimated)

210

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Adult patients with metastatic colorectal cancer and histologically confirmed colorectal liver metastases undergoing standard clinical management and curative-intent liver resection at Fondazione Policlinico Universitario A. Gemelli IRCCS. The study includes both a retrospective cohort with available tumour tissue and clinical data and a prospective cohort undergoing collection of tumour tissue and peripheral blood samples during routine clinical care

Description

Inclusion Criteria:

  • Age ≥18 years.
  • Histologically confirmed colorectal liver metastases.
  • Administration of neoadjuvant chemotherapy prior to liver resection, with objective tumour response classified as partial response (PR) or stable disease (SD) according to RECIST criteria.
  • Availability of a hepatobiliary contrast-enhanced MRI performed within 2 months before surgery.
  • Provision of informed consent for prospectively enrolled participants, or eligibility under Article 110-bis of the Italian Privacy Code for retrospectively enrolled participants.

Exclusion Criteria:

  • Recurrent metastatic disease.
  • Liver resection performed with non-curative intent.
  • Current or previous hepatitis B virus (HBV) or hepatitis C virus (HCV) infection.
  • Concomitant malignancies or history of another malignancy treated within the previous 5 years.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Retrospective CRLM Cohort
Patients with histologically confirmed colorectal liver metastases who underwent curative-intent liver resection between January 2009 and December 2023 and for whom tumour tissue and clinical data are available. Retrospective collection and analysis of tumour tissue, radiological, genomic, immune and clinical data.
Analysis of tumour tissue, radiological images, and clinical data collected during routine clinical care. Molecular, genomic, spatial, transcriptomic, and radiomic profiling will be performed to investigate associations with recurrence risk and clinical outcomes in patients with colorectal liver metastases. No investigational drugs, devices, or experimental procedures are administered as part of the study.
Prospective CRLM Cohort
Patients with histologically confirmed colorectal liver metastases undergoing standard clinical management and curative-intent liver resection, enrolled prospectively with collection of tumour tissue and peripheral blood samples. Prospective collection and analysis of tumour tissue, peripheral blood-derived ctDNA, radiological, genomic, immune and clinical data.
Patients with histologically confirmed colorectal liver metastases undergoing standard clinical management and curative-intent liver resection, enrolled prospectively with collection of tumour tissue and peripheral blood samples. Prospective collection and analysis of tumour tissue, peripheral blood-derived ctDNA, radiological, genomic, immune and clinical data.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Prediction of Colorectal Liver Metastasis Recurrence
Time Frame: 24 Months after liver resection
Prediction of colorectal liver metastasis recurrence following curative-intent liver resection using an integrated model based on radiogenomic, immune, and clinical profiling. Recurrence will be assessed through routine clinical follow-up and radiological evaluation.
24 Months after liver resection

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Genomic Alterations Associated With Immune Landscape Patterns
Time Frame: Baseline (analysis of collected tumour tissue and ctDNA samples)
Identification of tumour-associated genetic alterations correlated with specific immune microenvironment profiles in colorectal liver metastases.
Baseline (analysis of collected tumour tissue and ctDNA samples)
Radiomic Features Associated With Immune Cell Distribution
Time Frame: Baseline (pre-operative MRI/CT imaging)
Identification of radiomic features associated with the distribution and characteristics of dendritic cells and tumour-associated macrophages within tumour tissues.
Baseline (pre-operative MRI/CT imaging)
Performance of the Machine Learning-Based Recurrence Prediction Model
Time Frame: Up to 24 Months after liver resection
Development and validation of a machine learning-based model for recurrence risk prediction. Model performance will be assessed using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value.
Up to 24 Months after liver resection
Correlation Between Myeloid Immune Cell Frequencies and Clinical Outcome Measures
Time Frame: Up to 24 Months after liver resection
Correlation between dendritic cell and tumor-associated macrophage frequencies (% of CD45⁺ immune cells), measured by multiparametric flow cytometry, and overall survival (months), relapse-free survival (months), and recurrence status (yes/no).
Up to 24 Months after liver resection

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Simone Famularo, Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

September 1, 2026

Primary Completion (Estimated)

September 1, 2029

Study Completion (Estimated)

December 31, 2029

Study Registration Dates

First Submitted

July 29, 2026

First Submitted That Met QC Criteria

July 29, 2026

First Posted (Actual)

August 4, 2026

Study Record Updates

Last Update Posted (Actual)

August 6, 2026

Last Update Submitted That Met QC Criteria

August 4, 2026

Last Verified

August 1, 2026

More Information

Terms related to this study

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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