Evidence map›Paper›PMID 36950684›Full record

ArticleFrontiers in endocrinology2023

Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer.

Songyun Zhao, Xin Zhang, Feng Gao, Hao Chi, Jinhao Zhang, Zhijia Xia, Chao Cheng, Jinhui Liu

Open access · goldFull text read
In one paragraph

Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
19.4field-weighted citation impact, top 1% 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

60 citing papers in PubMed, 76 citations in OpenAlex.

  1. [The Role of Cuproptosis Related Key Genes in Ovarian Cancer and the Construction of a Prognostic Model].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
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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

8 authors at 5 institutions in 2 countries.

Songyun ZhaoWuxi Medical Center of Nanjing Medical University, Wuxi, China.
Xin ZhangDepartment of Pathology, The Second People's Hospital of Foshan, Affiliated Foshan Hospital of Southern Medical University, Foshan, China.
Feng GaoDepartment of Orthopaedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Hao ChiSouthwest Medical University, Luzhou, China.
Jinhao ZhangSouthwest Medical University, Luzhou, China.
Zhijia XiaDepartment of General, Visceral, and Transplant Surgery, Ludwig-Maximilians University, Munich, Germany.
Chao ChengDepartment of Neurosurgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.
Jinhui LiuDepartment of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jiangsu Province Hospital · CNNanjing Medical University · CNSouthwest Medical University · CNFoshan Second People's Hospital · CNLudwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ovarian cancer (OC) is one of the most common and most malignant gynecological malignancies in gynecology. On the other hand, dysregulation of copper metabolism (CM) is closely associated with tumourigenesis and progression. Here, we investigated the impact of genes associated with copper metabolism (CMRGs) on the prognosis of OC, discovered various CM clusters, and built a risk model to evaluate patient prognosis, immunological features, and therapy response. Methods: 15 CMRGs affecting the prognosis of OC patients were identified in The Cancer Genome Atlas (TCGA). Consensus Clustering was used to identify two CM clusters. lasso-cox methods were used to establish the copper metabolism-related gene prognostic signature (CMRGPS) based on differentially expressed genes in the two clusters. The GSE63885 cohort was used as an external validation cohort. Expression of CM risk score-associated genes was verified by single-cell sequencing and quantitative real-time PCR (qRT-PCR). Nomograms were used to visually depict the clinical value of CMRGPS. Differences in clinical traits, immune cell infiltration, and tumor mutational load (TMB) between risk groups were also extensively examined. Tumour Immune Dysfunction and Rejection (TIDE) and Immune Phenotype Score (IPS) were used to validate whether CMRGPS could predict response to immunotherapy in OC patients. Results: In the TCGA and GSE63885 cohorts, we identified two CM clusters that differed significantly in terms of overall survival (OS) and tumor microenvironment. We then created a CMRGPS containing 11 genes to predict overall survival and confirmed its reliable predictive power for OC patients. The expression of CM risk score-related genes was validated by qRT-PCR. Patients with OC were divided into low-risk (LR) and high-risk (HR) groups based on the median CM risk score, with better survival in the LR group. The 5-year AUC value reached 0.74. Enrichment analysis showed that the LR group was associated with tumor immune-related pathways. The results of TIDE and IPS showed a better response to immunotherapy in the LR group. Conclusion: Our study, therefore, provides a valuable tool to further guide clinical management and tailor the treatment of patients with OC, offering new insights into individualized treatment.

Indexed as

CopperOvarian NeoplasmsFemaleHumansNomogramsPrognosisRisk FactorsTumor MicroenvironmentCoppercopper metabolismimmunotherapymachine learningOCrisk score signatureTumor microenvironment

Identifiers

PMID36950684
PMCPMC10025496
OpenAlexW4323316778

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read21
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.