Evidence map›Paper›PMID 42291443›Full record

ReviewPeerJ2026

The metabolic escape: how tumor metabolic reprogramming drives drug resistance.

Yan Chen, Zixu Wu, Wenzhe Si, Xujun Liu

Abstract readReview
In one paragraph

Review in PeerJ, 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

4 authors.

Yan ChenDepartment of Laboratory Medicine, Peking University First Hospital, Beijing, China.
Zixu WuDepartment of Laboratory Medicine, Peking University First Hospital, Beijing, China.
Wenzhe SiDepartment of Laboratory Medicine, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University Third Hospital, Beijing, China.
Xujun LiuDepartment of Laboratory Medicine, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last few years, metabolic reprogramming has been recognized as a fundamental characteristic of cancer, and is also acknowledged as a crucial cause to drug resistance, which consistently acts as a significant barrier in cancer treatment by allowing tumor cells to adapt and escape various therapies. This review gives a systematically investigation of how metabolic reprogramming contributes to drug resistance in cancer, including aerobic glycolysis (also known as the Warburg effect), lactate metabolism, glutamine addiction, lipid synthesis reprogramming, mitochondrial and ion metabolic changes. Furthermore, by clarifying the mechanisms behind these reprogrammed metabolic pathways, we explain how these changes lead to drug resistance and highlight potential molecular targets for therapeutic intervention. Additionally, we discuss emerging strategies aimed at exploiting these metabolic vulnerabilities, offering new insights for overcoming drug resistance in cancer. By integrating recent discoveries in this field, we present a unified perspective on targeting metabolic vulnerabilities to overcome drug resistance, which is an urgent need in precision oncology, and timely and concise insights for cancer biologists and researchers in the field of exploring the metabolic mechanisms of drug resistance. We hope this review will provide valuable insights for molecular tumor biologists seeking to elucidate the molecular roles of tumor metabolic reprogramming and drug resistance in cancer.

Indexed as

Drug Resistance, NeoplasmMetabolic ReprogrammingNeoplasmsAnimalsAntineoplastic AgentsGlycolysisHumansMitochondriaTumor MicroenvironmentWarburg Effect, OncologicAntineoplastic AgentsCancerCancer therapeuticsDrug resistanceMetabolic reprogrammingTumor microenvironment

Identifiers

PMID42291443
PMCPMC13256050

What OpenQuestion holds

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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.