Evidence map›Paper›PMID 38577616›Full record

ReviewJournal of Cancer2024

Glucose metabolism reprogramming in gynecologic malignant tumors.

Jianhong Ma, Zhiqiang Yao, Liangjian Ma, Qinyin Zhu, Jiajia Zhang, Ling Li, Chang Liu

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 7 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Jianhong MaThe First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Zhiqiang YaoDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, China.
Liangjian MaThe First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Qinyin ZhuThe First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Jiajia ZhangDepartment of Child Health, the First Hospital of Lanzhou University, Lanzhou, 730000, China.
Ling LiThe First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Chang LiuDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, China.
Lanzhou University · CNFirst Hospital of Lanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incidence and mortality of gynecological tumors are progressively increasing due to factors such as obesity, viral infection, unhealthy habits, as well as social and economic pressures. Consequently, it has emerged as a significant threat to women's health. Numerous studies have revealed the remarkable metabolic activity of tumor cells in glycolysis and its ability to influence malignant biological behavior through specific mechanisms. Therefore, it is crucial for patients and gynecologists to comprehend the role of glycolytic proteins, regulatory molecules, and signaling pathways in tumorigenesis, progression, and treatment. This article aims to review the correlation between abnormal glucose metabolism and gynecologic tumors including cervical cancer (CC), endometrial carcinoma (EC), and ovarian cancer (OC). The findings from this research will provide valuable scientific insights for early screening, timely diagnosis and treatment interventions while also aiding in the prevention of recurrence among individuals with gynecological tumors.

Indexed as

aerobic glycolysiscervical cancerendometrial carcinomaovarian cancerpathological mechanismWarburg effect

Identifiers

PMID38577616
PMCPMC10988310
OpenAlexW4393905349

What Socratic 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 Socratic graph.