Evidence map›Paper›PMID 40517166›Full record

ReviewSignal transduction and targeted therapy2025

Advances in molecular pathology and therapy of non-small cell lung cancer.

Qing Huang, Yuanxiang Li, Yingdan Huang, Jingyi Wu, Wendai Bao, Chang Xue, Xiaoyu Li, Shuang Dong, Zhiqiang Dong, Sheng Hu

Abstract readReview
In one paragraph

Review in Signal transduction and targeted therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
116citing papers in PubMed, 6 pooled it
–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

116 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  13. Unravelling the human disposition of [British journal of clinical pharmacology · 2026
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  17. PCK2 Inhibition Reverses Cisplatin Resistance of Non-Small Cell Lung Cancer by Triggering Ferroptosis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  18. Review
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  20. Article

56 more citing papers are in PubMed but not listed here.

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.

Qing Huang *Department of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Yuanxiang Li *Department of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Yingdan Huang *Department of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Jingyi Wu *Department of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Wendai Bao *Center for Neurological Disease Research, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, China.
Chang XueDepartment of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Xiaoyu LiDepartment of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Shuang DongDepartment of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China.
Zhiqiang DongDepartment of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China. dongz@mail.hzau.edu.cn.ORCID 0000-0001-6259-915X
Sheng HuDepartment of Medical Oncology, Huazhong University of Science and Technology, Tongji Medical College, Hubei Cancer Hospital, Wuhan, 430079, Hubei, China. ehusmn@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past two decades, non-small cell lung cancer (NSCLC) has witnessed encouraging advancements in basic and clinical research. However, substantial unmet needs remain for patients worldwide, as drug resistance persists as an inevitable reality. Meanwhile, the journey towards amplifying the breadth and depth of the therapeutic effect requires comprehending and integrating diverse and profound progress. In this review, therefore, we aim to comprehensively present such progress that spans the various aspects of molecular pathology, encompassing elucidations of metastatic mechanisms, identification of therapeutic targets, and dissection of spatial omics. Additionally, we also highlight the numerous small molecule and antibody drugs, encompassing their application alone or in combination, across later-line, frontline, neoadjuvant or adjuvant settings. Then, we elaborate on drug resistance mechanisms, mainly involving targeted therapies and immunotherapies, revealed by our proposed theoretical models to clarify interactions between cancer cells and a variety of non-malignant cells, as well as almost all the biological regulatory pathways. Finally, we outline mechanistic perspectives to pursue innovative treatments of NSCLC, through leveraging artificial intelligence to incorporate the latest insights into the design of finely-tuned, biomarker-driven combination strategies. This review not only provides an overview of the various strategies of how to reshape available armamentarium, but also illustrates an example of clinical translation of how to develop novel targeted drugs, to revolutionize therapeutic landscape for NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsDrug Resistance, NeoplasmHumansImmunotherapyMolecular Targeted Therapy

Identifiers

PMID40517166
PMCPMC12167388

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.