Evidence map›Paper›PMID 36620594›Full record

ArticleFrontiers in oncology2022

Role of cuproptosis-related gene in lung adenocarcinoma.

Yuan Liu, Wei Lin, Ying Yang, JingJing Shao, Hongyu Zhao, Gaoren Wang, Aiguo Shen

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
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  5. Cuproptosis in lung cancer: therapeutic options and prognostic models.Apoptosis : an international journal on programmed cell death · 2024
    Review
  6. Recent advances in copper homeostasis-involved tumor theranostics.Asian journal of pharmaceutical sciences · 2024
    Review
  7. Article
  8. Article
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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.

Yuan LiuCancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, China.
Wei LinDepartment of Pediatrics, the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Ying YangCancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, China.
JingJing ShaoCancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, China.
Hongyu ZhaoDepartment of Radiotherapy, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.
Gaoren WangCancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, China.
Aiguo ShenCancer Research Center Nantong, Affiliated Tumor Hospital of Nantong University, Nantong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Backgrounds: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, which is the leading cause of cancer death. Dysregulation of cell proliferation and death plays a crucial role in the development of LUAD. As of recently, the role of a new form of cell death, cuproptosis, and it has attracted more and more attention. As of yet, it is not clear whether cuproptosis is involved in the progression of LUAD. Methods: An integrated set of bioinformatics tools was utilized to analyze the expression and prognostic significance of cuproptosis-related genes. Meanwhile, a robust risk signature was developed using machine learning based on prognostic cuproptosis-related genes and explored the value of prognostic cuproptosis-related signature for clinical applications, functional enrichment and immune landscape. Lastly, the dysregulation of the cuproptosis-related genes in LUAD was validated by Results: In this study, first, cuproptosis-related genes were found to be differentially expressed in LUAD patients of public databases, and nine of them had prognostic value. Next, a cuproptosis-related model with five features (DLTA, MTF1, GLS, PDHB and PDHA1) was constructed to separate the patients into high- and low-risk groups based on median risk score. Internal validation set and external validation set were used for model validation and evaluation. What's more, Enrichment analysis of differential genes and the WGCNA identified that cuproptosis-related signatures affected tumor prognosis by influencing tumor immunity. Small molecule compounds were predicted based on differential expressed genes to improve poor prognosis in the high-risk group and a nomogram was constructed to further advance clinical applications. In closing, our data showed that FDX1 affected the prognosis of lung cancer by altering the expression of cuproptosis-related signature. Conclusion: A new cuproptosis-related signature for survival prediction was constructed and validated by machine learning algorithm and

Indexed as

cuproptosisimmune infiltrationimmune microenvironmentlung adenocarcinomaprognostic signature

Identifiers

PMID36620594
PMCPMC9811388

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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.