Evidence map›Paper›PMID 41483442›Full record

ReviewDiscover oncology2026

Targeting shared mechanisms of cisplatin resistance and metastasis in lung cancer for novel therapeutic strategies.

Xiao Liang, Xiaoren Zhu, Yingying Zhang, Minbin Chen, Na Liu

Abstract readReview
In one paragraph

Review in Discover 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.

Xiao Liang *Department of Radiotherapy and Oncology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, 215300, China. 593180042@qq.com.
Xiaoren Zhu *Department of Radiotherapy and Oncology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, 215300, China.
Yingying Zhang *Department of Radiotherapy and Oncology, Gusu School, Nanjing Medical University, The First People's Hospital of Kunshan, Suzhou, 215300, Jiangsu, China.
Minbin ChenDepartment of Radiotherapy and Oncology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, 215300, China. cmb1981@163.com.
Na LiuDepartment of Radiotherapy and Oncology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, 215300, China.

Funding

Health Commission Medical Research Program of Jiangsu Province Z2023096National Natural Science Foundation 82072712
6 · The paper itself

Abstract

Cisplatin, a cornerstone therapeutic agent in lung cancer chemotherapy, is significantly limited by the development of drug resistance, which remains a principal driver of treatment failure. Investigations have demonstrated that cisplatin-resistant lung cancer cells frequently acquire an enhanced metastatic phenotype, which is correlated with severely adverse clinical outcomes. Growing evidence indicates that chemoresistance and metastasis share underlying molecular pathways and exhibit mutually reinforcing relationships. Key mechanisms include metabolic reprogramming, epithelial‒mesenchymal transition (EMT), immunosuppressive microenvironment remodeling, and adaptive activation of prosurvival signaling pathways, which collectively contribute to accelerated disease progression and diminished patient survival. This review provides recent insights into the pathogenic crosstalk between cisplatin resistance and metastasis, and discusses integrated targeting strategies designed to overcome the limitations of conventional monotherapy.

Indexed as

Cisplatin resistanceCombination therapyMetabolic reprogrammingTargeting therapyTumor metastasis

Identifiers

PMID41483442
PMCPMC12864612

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.