Evidence map›Paper›PMID 39170367›Full record

ArticleHeliyon2024

Construction of a prognostic model for ovarian cancer based on a comprehensive bioinformatics analysis of cuproptosis-associated long non-coding RNA signatures.

Rujun Chen, Yating Huang, Ke Sun, Fuyun Dong, Xiaoqin Wang, Junhua Guan, Lina Yang, He Fei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Rujun ChenDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
Yating HuangDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
Ke SunDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
Fuyun DongDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
Xiaoqin WangDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
Junhua GuanDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
Lina YangDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.
He FeiDepartment of Gynecology and Obstetrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OCa) is a common malignancy in women, and the role of cuproptosis and its related genes in OCa is unclear. Using the GSE14407 dataset, we analyzed the expression and correlation of cuproptosis-related genes (CRGs) between tumor and normal groups. From the TCGA-OV dataset, we identified 20 cuproptosis-related long non-coding RNAs (CuLncs) associated with patient survival through univariate Cox analysis. OCa patients were divided into early-stage and late-stage groups to analyze CuLncs expression. Cluster analysis classified patients into two clusters, with Cluster1 having a poorer prognosis. Significant differences in "Lymphatic Invasion" and "Cancer status" were observed between clusters. Seven CRGs showed significant expression differences, validated using the human protein atlas (HPA) databases. Immune analysis revealed a higher ImmuneScore in Cluster1. GSEA identified associated signaling pathways. LASSO regression included 11 CuLncs to construct and validate a survival prediction model, classifying patients into high-risk and low-risk groups. Correlations between riskScore, Cluster phenotype, ImmuneScore, and immune cell infiltration were explored. Cell experiments showed that knocking down AC023644.1 decreases OCa cell viability. In conclusion, we constructed an accurate prognostic model for OCa based on 11 CuLncs, providing a basis for prognosis assessment and potential immunotherapy targets.

Indexed as

CuproptosisImmune infiltrationLong non-coding RNAs signaturePatient survivalPrognostic model

Identifiers

PMID39170367
PMCPMC11336372

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.