Evidence map›Paper›PMID 41593682›Full record

ReviewCell division2026

Research progress on vasculogenic mimicry in colorectal cancer: mechanisms and therapeutic.

Jian Zewei, Zhao Haiyan

Abstract readReview
In one paragraph

Review in Cell division, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Jian ZeweiAffiliated Hospital of Inner Mongolia Medical University, Hohhot, 101059, Inner Mongolia Autonomous Region, China.
Zhao HaiyanDepartment of Medical Oncology, Inner Mongolia Medical University Affiliated Hospital, Hohhot, 101059, Inner Mongolia Autonomous Region, China. 15049139896@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is the third most common malignant tumor worldwide and is characterized by high incidence and mortality rates. In the chemotherapeutic treatment of CRC, antiangiogenic therapy is utilized throughout the entire disease course, particularly for highly metastatic tumors. However, studies have reported that resistance to current antiangiogenic therapies often develops, leading to suboptimal clinical outcomes. Vasculogenic mimicry (VM) represents a novel tumor blood supply mechanism that is distinct from traditional endothelial cell-dependent vasculature. VM channels are composed solely of tumor cells and extracellular basement membranes, emerge within malignant tumors requiring blood perfusion, and have been identified in numerous solid tumors. Research indicates that tumors exhibiting VM demonstrate greater proliferative, invasive, and metastatic potential, along with poorer prognosis, than those without VM. Additionally, studies suggest that VM contributes to the limited efficacy and resistance observed with antiangiogenic drugs in clinical practice. Thus, targeting VM is crucial in oncology, especially in CRC. Recent advances have been made in anti-VM drug therapy for CRC. Moving forward, combining VM-targeted strategies with conventional antiangiogenic therapies targeting endothelial cells may represent a promising new direction in CRC treatment. This review summarizes current insights into the mechanisms of VM in CRC and its therapeutic advancements, aiming to provide novel perspectives for clinical management.

Indexed as

Cancer stem cellsColorectal cancerEpithelial mesenchymal transitionExtracellular matrix remodelingHypoxic microenvironmentTargeted therapyVasculogenic mimicry

Identifiers

PMID41593682
PMCPMC12853891

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.