Evidence map›Paper›PMID 41444844›Full record

ArticleEJNMMI research2025

Data-driven identification and semi-automated quantification of molecular targets for tumour-imaging of colorectal liver metastases and primary colorectal tumours.

Mats I Warmerdam, Nidal Amenchar, Feline Hutten, A Stijn L P Crobach, Okker D Bijlstra, Nada Badr, J Sven D Mieog, Ronald van Vlierberghe, Alexander L Vahrmeijer, Peter J K Kuppen

Abstract read
In one paragraph

Article in EJNMMI research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Cadherin 17 and digestive cancers: from diagnostic to therapeutic opportunities.Journal of experimental & clinical cancer research : CR · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Mats I Warmerdam *Department of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands. m.i.warmerdam@lumc.nl.ORCID http://orcid.org/0000-0002-4546-5966
Nidal Amenchar *Department of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Feline HuttenDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
A Stijn L P CrobachDepartment of Pathology, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Okker D BijlstraDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Nada BadrDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
J Sven D MieogDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Ronald van VlierbergheDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Alexander L VahrmeijerDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.
Peter J K KuppenDepartment of Surgery, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate pre- and intraoperative assessment of disease extent is crucial for curative treatment of colorectal liver metastases (CRLM) and primary colorectal cancer (pCRC). Tumour-targeted nuclear imaging can enhance pre- and postoperative tumour staging, while tumour-specific fluorescence-guided surgery can improve intraoperative visualization. However, validated targets remain limited, particularly for CRLM. This study aimed to identify and validate novel molecular targets for CRLM using a data-driven approach. Additional objectives included pCRC target expression and evaluating target expression in neoadjuvant-treated patients.

resultsUsing a data-driven RNA-based discovery approach (Euretos), candidate targets for colorectal liver metastases were identified. Of these, the six highest-ranking targets-CEACAM5, EPCAM, CEACAM6, MUC13, FXYD3, and CDH17-were selected for validation through immunohistochemistry (IHC). Semi-automated image analysis quantified IHC staining intensity (0-100) for tumour epithelium and background on a per-pixel basis. A patient's staining pattern was regarded as positive if mean tumour epithelium scored positive (>25), background negative (<25) and tumour epithelium >25 points higher than background, referred to as relative positive expression. The proportion of CRLM samples showing relative positive expression was 79% for CEACAM5, 45% for EPCAM, 80% for CEACAM6, 24% for MUC13, 58% for FXYD3, and 22% for CDH17. CEACAM5/CEACAM6 combined positivity reached 90% (either one positive), showing that targeting both markers enables molecular imaging in nearly the entire population. Staining intensities were similar in pCRC epithelium (P >0.05). Neoadjuvant-treated CRLM exhibited higher expression for all targets.

conclusionUsing a novel data-driven approach, six potential imaging targets were successfully identified and validated. CEACAM5 and CEACAM6 emerged as strong targets that, regardless of neoadjuvant therapy, covered nearly the entire CRLM population-supporting their further probe development and clinical translation.

Indexed as

Colorectal cancerColorectal liver metastasesFluorescence-guided surgeryMolecular imagingNeoadjuvant treatmentNuclear imaging

Identifiers

PMID41444844
PMCPMC12847594

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.