Evidence map›Paper›PMID 37205195›Full record

ReviewFrontiers in oncology2023

Abnormal lipid metabolism in cancer-associated cachexia and potential therapy strategy.

Ruoxin Fang, Ling Yan, Zhengkai Liao

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
4.7field-weighted citation impact, top 4% of its field
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

19 citing papers in PubMed, 27 citations in OpenAlex.

  1. Dyslipidaemias in cancer patients.European heart journal · 2026
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  12. Hallmarks of Cancer Cachexia: Sexual Dimorphism in Related Pathways.International journal of molecular sciences · 2025
    Review
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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

3 authors at 1 institution in 1 country.

Ruoxin FangDepartment of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Wuhan, Hubei, China.
Ling YanDepartment of Cardiology, Renmin Hospital of Wuhan University, Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, Hubei, China.
Zhengkai LiaoDepartment of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Wuhan, Hubei, China.
Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer-associated cachexia (CAC) is a major characteristic of advanced cancer, associates with almost all types of cancer. Recent studies have found that lipopenia is an important feature of CAC, and it even occurs earlier than sarcopenia. Different types of adipose tissue are all important in the process of CAC. In CAC patients, the catabolism of white adipose tissue (WAT) is increased, leading to an increase in circulating free fatty acids (FFAs), resulting in " lipotoxic". At the same time, WAT also is induced by a variety of mechanisms, browning into brown adipose tissue (BAT). BAT is activated in CAC and greatly increases energy expenditure in patients. In addition, the production of lipid is reduced in CAC, and the cross-talk between adipose tissue and other systems, such as muscle tissue and immune system, also aggravates the progression of CAC. The treatment of CAC is still a vital clinical problem, and the abnormal lipid metabolism in CAC provides a new way for the treatment of CAC. In this article, we will review the mechanism of metabolic abnormalities of adipose tissue in CAC and its role in treatment.

Indexed as

adipose tissuecachexiacancerlipid metabolismtherapy strategy

Identifiers

PMID37205195
PMCPMC10185845
OpenAlexW4367853270

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.