Evidence map›Paper›PMID 34523782›Full record

ArticleJournal of cellular and molecular medicine2021

Identification of metabolism-associated molecular subtype in ovarian cancer.

Xiaona Liu, Aoshen Wu, Xing Wang, Yunhe Liu, Yiang Xu, Gang Liu, Lei Liu

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  3. Review
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  5. Review
  6. Metabolic heterogeneity in early-stage lung adenocarcinoma revealed by RNA-seq and scRNA-seq.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Article
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  8. 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

7 authors at 2 institutions in 1 country.

Xiaona LiuInstitutes of Biomedical Sciences, Fudan University, Shanghai, China.
Aoshen WuInstitutes of Biomedical Sciences, Fudan University, Shanghai, China.
Xing WangInstitutes of Biomedical Sciences, Fudan University, Shanghai, China.
Yunhe LiuInstitutes of Biomedical Sciences, Fudan University, Shanghai, China.
Yiang XuSchool of Basic Medical Sciences, Fudan University, Shanghai, China.
Gang LiuInstitutes of Biomedical Sciences, Fudan University, Shanghai, China.
Lei LiuInstitutes of Biomedical Sciences, Fudan University, Shanghai, China.ORCID 0000-0002-9995-9080
Fudan University · CNShanghai Medical College of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OC) is the most lethal gynaecological cancer with genomic complexity and extensive heterogeneity. This study aimed to characterize the molecular features of OC based on the gene expression profile of 2752 previously characterized metabolism-relevant genes and provide new strategies to improve the clinical status of patients with OC. Finally, three molecular subtypes (C1, C2 and C3) were identified. The C2 subtype displayed the worst prognosis, upregulated immune-cell infiltration status and expression level of immune checkpoint genes, lower burden of copy number gains and losses and suboptimal response to targeted drug bevacizumab. The C1 subtype showed downregulated immune-cell infiltration status and expression level of immune checkpoint genes, the lowest incidence of BRCA mutation and optimal response to targeted drug bevacizumab. The C3 subtype had an intermediate immune status, the highest incidence of BRCA mutation and a secondary optimal response to bevacizumab. Gene signatures of C1 and C2 subtypes with an opposite expression level were mainly enriched in proteolysis and immune-related biological process. The C3 subtype was mainly enriched in the T cell-related biological process. The prognostic and immune status of subtypes were validated in the Gene Expression Omnibus (GEO) dataset, which was predicted with a 45-gene classifier. These findings might improve the understanding of the diversity and therapeutic strategies for OC.

Indexed as

Biomarkers, TumorEnergy MetabolismComputational BiologyDNA Copy Number VariationsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMetabolic Networks and PathwaysMolecular Diagnostic TechniquesMutationOvarian NeoplasmsPrognosisTranscriptomeTumor MicroenvironmentWorkflowBiomarkers, Tumorimmunemetabolic genesovarian cancerprognosissubtype

Identifiers

PMID34523782
PMCPMC8505839
OpenAlexW3200839399

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.