Evidence map›Paper›PMID 42719091›Full record

ReviewFrontiers in oncology2026

Resistance mechanisms and countermeasures in CLDN18.2-positive tumors: from molecular networks to clinical practice.

Yutao Xia, Mingfang Wang, Taosheng Huang, Kai Sun, Peng Wang

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 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

5 authors.

Yutao XiaDepartment of Oncology, Weifang Yidu Central Hospital, Weifang, Shandong, China.
Mingfang WangDepartment of Oncology, Weifang Yidu Central Hospital, Weifang, Shandong, China.
Taosheng HuangDepartment of Oncology, Weifang Yidu Central Hospital, Weifang, Shandong, China.
Kai SunDepartment of Oncology, Weifang Yidu Central Hospital, Weifang, Shandong, China.
Peng WangDepartment of Oncology, Weifang Yidu Central Hospital, Weifang, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Claudin 18.2 (CLDN18.2) has rapidly become a major target in solid-tumor oncology. Zolbetuximab, the first anti-CLDN18.2 antibody, was approved in 2024 for HER2-negative, CLDN18.2-high advanced gastric and gastro-esophageal junction adenocarcinoma, and more than one hundred CLDN18.2-directed trials are now under way across monoclonal antibodies, antibody-drug conjugates, bispecific antibodies and CAR-T cells. As these agents enter the clinic, resistance has become the central challenge. This review synthesizes the resistance mechanisms emerging from this experience and organizes them into six biological dimensions, separating those distinctive to CLDN18.2 from those shared across therapeutic platforms, and pairs each with mechanism-matched countermeasures weighted by level of evidence. From this synthesis we advance a central argument about treatment sequencing: because CLDN18.2 expression declines progressively under therapeutic pressure, continuous target-plus-chemotherapy acts on an eroding antigen substrate. For patients with high, homogeneous baseline expression, an early intensive induction followed by CLDN18.2-directed maintenance may therefore be preferable to indefinite target-plus-chemotherapy. We further consider the tissue-context-dependent biology of CLDN18.2 relevant to patient selection, and outline the prospective, biomarker-embedded trials needed to test these proposals.

Indexed as

CAR-T cell therapyclaudin 18.2CLDN18.2resistance mechanismstargeted therapytumor microenvironmentzolbetuximab

Identifiers

PMID42719091
PMCPMC13555379

What OpenQuestion holds

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Registered trials

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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.