Evidence map›Paper›PMID 38755712›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2024

Multi

Meng Wu, Ke Li, Yangying Liao, Lan Li, Xiao Xiao, Yongjian Chen, Junweichen Guo, Feng Hu, Jing Qu, Zheng Wang and 1 more

Abstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

11 authors.

Meng WuDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002. wmyouxiang163@163.com.
Ke LiDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Yangying LiaoDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Lan LiDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Xiao XiaoDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Yongjian ChenDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Junweichen GuoDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Feng HuDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002.
Jing QuDepartment of Dermatology, Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine (Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine), Changsha 410006.
Zheng WangSchool of Computer Science, Hunan First Normal University, Changsha 410205, China. w8614@hotmail.com.
Hao FengDepartment of Dermatology, Hunan Provincial People's Hospital, Changsha 410002. doctorfenghao@hunnu.edu.cn.

Funding

the Key Project of Health Commission of Hunan Province 202104122479the Natural Science Foundation of Hunan Province 2021JJ30399
6 · The paper itself

Abstract

objectivesMelanoma is highly malignant and heterogeneous. It is essential to develop a specific prognostic model for improving the patients' survival and treatment strategies. Recent studies have shown that ferroptosis results from the overproduction of lipid peroxidation and is an iron-dependent form of programmed cell death. Despite this, ferroptosis-related genes (FRGs) and their clinical significances remain unknown in malignant melanoma. This study aims to assess the role of FRGs in melanoma, with the goal of developing a novel prognostic model that provides new insights into personalized treatment and improvement of therapeutic outcomes for melanoma.

methodsWe systematically characterized the genetic alterations and mRNA expression of 73 FRGs in The Cancer Genome Atlas (TCGA)-skin cutaneous melanoma (SKCM) dataset in this study. The results were validated with real-time RT-PCR and Western blotting. Subsequently, a multi-gene feature model was constructed using the TCGA-SKCM cohort. Melanoma patients were classified into a high-risk group and a low-risk group based on the feature model. As a final step, correlations between ferroptosis-related signatures and immune features, immunotherapy efficacy, or drug response were analyzed.

resultsBy analyzing melanoma samples from TCGA-SKCM dataset, FRGs exhibited a high frequency of genetic mutations and copy number variations (CNVs), significantly impacting gene expression. Additionally, compared with normal skin tissue, 30 genes with significantly differential expression were identified in melanoma tissues. A prognostic model related to FRGs, constructed using the LASSO Cox regression method, identified 13 FRGs associated with overall survival prognosis in patients and was validated with external datasets. Finally, functional enrichment and immune response analysis further indicated significant differences in immune cell infiltration, mutation burden, and hypoxia status between the high-risk group and the low-risk group, and the model was effective in predicting responses to immunotherapy and drug sensitivity.

conclusionsThis study develops a strong ferroptosis-related prognostic signature model which could put forward new insights into target therapy and immunotherapy for patients with melanoma.

Indexed as

FerroptosisMelanomaSkin NeoplasmsCutaneous Malignant MelanomaDNA Copy Number VariationsGene Expression Regulation, NeoplasticHumansMultiomicsMutationPrognosiscutaneous melanomaferroptosisimmunotherapyrisk scoretargeted therapytumor microenvironment

Identifiers

PMID38755712
PMCPMC11103070

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.