Radiogenomic Profiling of Dendritic Cells and Macrophages to Predict Recurrence in Colorectal Liver Metastasis

Overview

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.

Interventions

• Other Radiogenomic and Immune Profiling
  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.
• Other Prospective Radiogenomic and ctDNA Profiling
  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.

Primary outcome measures

• Prediction of Colorectal Liver Metastasis Recurrence [Time frame: 24 Months after liver resection]

Secondary outcome measures (4)

• Correlation Between Myeloid Immune Cell Frequencies and Clinical Outcome Measures [Time frame: Up to 24 Months after liver resection]
• Genomic Alterations Associated With Immune Landscape Patterns [Time frame: Baseline (analysis of collected tumour tissue and ctDNA samples)]
• Radiomic Features Associated With Immune Cell Distribution [Time frame: Baseline (pre-operative MRI/CT imaging)]
• Performance of the Machine Learning-Based Recurrence Prediction Model [Time frame: Up to 24 Months after liver resection]

Eligibility criteria

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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model

Cohort

Study locations

Center list to be confirmed — check the primary protocol.

Identifiers

NCT: NCT07744139 · 27482

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗