Evidence map›Paper›PMID 40469185›Full record

ReviewFrontiers in oncology2025

Metabolic reprogramming and therapeutic targeting in non-small cell lung cancer: emerging insights beyond the Warburg effect.

Hong Cai, Feng Zhang, Fang Xu, Chunhui Yang

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  10. Divergent CD45Frontiers in immunology · 2026
    Article
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  15. [Applications and Advances of Metabolomics in Lung Cancer Research].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025
    Review
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  17. Article
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

4 authors.

Hong Cai *Department of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Feng Zhang *Department of Clinical Laboratory, Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China.
Fang XuDepartment of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Chunhui YangDepartment of Clinical Laboratory, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Recent advancements have illuminated the intricate metabolic reprogramming that underpins NSCLC progression and resistance to therapy. Beyond the classical Warburg effect, emerging evidence highlights the pivotal roles of altered lipid metabolism, amino acid utilization, and the metabolic crosstalk within the tumor microenvironment (TME). This review delves into the latest discoveries in NSCLC metabolism, emphasizing novel pathways and mechanisms that contribute to tumor growth and survival. We critically assess the interplay between cancer cell metabolism and the TME, explore the impact of metabolic heterogeneity, and discuss how metabolic adaptations confer therapeutic resistance. By integrating insights from cutting-edge technologies such as single-cell metabolomics and spatial metabolomics, we identify potential metabolic vulnerabilities in NSCLC. Finally, we propose innovative therapeutic strategies that target these metabolic dependencies, including combination approaches that enhance the efficacy of existing treatments and pave the way for personalized metabolic therapies.

Indexed as

metabolic reprogrammingmetabolic vulnerabilitiesnon-small cell lung cancertherapeutic targetingtumor microenvironment

Identifiers

PMID40469185
PMCPMC12133740

What OpenQuestion holds

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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.