Evidence map›Paper›PMID 36437242›Full record

ArticleScientific reports2022

A novel prognostic model for cutaneous melanoma based on an immune-related gene signature and clinical variables.

Yifan Tang, Huicong Feng, Lupeng Zhang, Chiwen Qu, Jinlong Li, Xiangyu Deng, Suye Zhong, Jun Yang, Xiyun Deng, Xiaomin Zeng and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2022. 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

12 authors.

Yifan Tang *Department of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, 410013, Hunan, China.
Huicong Feng *Department of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, 410013, Hunan, China.
Lupeng ZhangDepartment of Biochemistry and Molecular Biology, Jishou University School of Medicine, Jishou, 416000, Hunan, China.
Chiwen QuDepartment of Statistics, College of Mathematics and Computer Science, Hunan Normal University, Changsha, 410081, Hunan, China.
Jinlong LiDepartment of Biochemistry and Molecular Biology, Jishou University School of Medicine, Jishou, 416000, Hunan, China.
Xiangyu DengDepartment of Epidemiology and Health Statistics, Xiangya Public Health School, Central South University, Changsha, 410078, Hunan, China.
Suye ZhongDepartment of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, 410013, Hunan, China.
Jun YangDepartment of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, 410013, Hunan, China.
Xiyun DengDepartment of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, 410013, Hunan, China.
Xiaomin ZengDepartment of Epidemiology and Health Statistics, Xiangya Public Health School, Central South University, Changsha, 410078, Hunan, China. zxiaomin@csu.edu.cn.
Yiren WangDepartment of Epidemiology and Health Statistics, Xiangya Public Health School, Central South University, Changsha, 410078, Hunan, China. brightwyr@hotmail.com.
Xiaoning PengDepartment of Pathology and Pathophysiology, Hunan Normal University School of Medicine, Changsha, 410013, Hunan, China. pxiaoning@hunnu.edu.cn.

Funding

National Natural Science Foundation of China 61761001Start-up fund for Prof. Peng Xiaoning from Jishou University 91602-111900
6 · The paper itself

Abstract

Abundant evidence has indicated that the prognosis of cutaneous melanoma (CM) patients is highly complicated by the tumour immune microenvironment. We retrieved the clinical data and gene expression data of CM patients in The Cancer Genome Atlas (TCGA) database for modelling and validation analysis. Based on single-sample gene set enrichment analysis (ssGSEA) and consensus clustering analysis, CM patients were classified into three immune level groups, and the differences in the tumour immune microenvironment and clinical characteristics were evaluated. Seven immune-related CM prognostic molecules, including three mRNAs (SUCO, BTN3A1 and TBC1D2), three lncRNAs (HLA-DQB1-AS1, C9orf139 and C22orf34) and one miRNA (hsa-miR-17-5p), were screened by differential expression analysis, ceRNA network analysis, LASSO Cox regression analysis and univariate Cox regression analysis. Their biological functions were mainly concentrated in the phospholipid metabolic process, transcription regulator complex, protein serine/threonine kinase activity and MAPK signalling pathway. We established a novel prognostic model for CM integrating clinical variables and immune molecules that showed promising predictive performance demonstrated by receiver operating characteristic curves (AUC ≥ 0.74), providing a scientific basis for predicting the prognosis and improving the clinical outcomes of CM patients.

Indexed as

MelanomaSkin NeoplasmsAntigens, CDBiomarkers, TumorButyrophilinsCutaneous Malignant MelanomaHumansPrognosisTumor MicroenvironmentAntigens, CDBiomarkers, TumorBTN3A1 protein, humanButyrophilins

Identifiers

PMID36437242
PMCPMC9701680

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.