Evidence map›Paper›PMID 32355756›Full record

ArticleAnnals of translational medicine2020

A twelve-gene signature for survival prediction in malignant melanoma patients.

Le-Bin Song, Qi-Jie Zhang, Xiao-Yuan Hou, Yan-Yan Xiu, Lin Chen, Ning-Hong Song, Yan Lu

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 31 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Le-Bin SongDepartment of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Qi-Jie ZhangDepartment of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Xiao-Yuan HouDepartment of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Yan-Yan XiuDepartment of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Lin ChenDepartment of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Ning-Hong SongDepartment of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Yan LuDepartment of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Nanjing Medical University · CNJiangsu Province Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMelanoma is defined as a highly mutational heterogeneous disease containing numerous alternations of the molecule. However, due to the phenotypically and genetically heterogeneity of malignant melanoma, conventional clinical characteristics remain restricted or limited in the ability to accurately predict individual outcomes and survival. This study aimed to establish an accurate gene expression signature to predict melanoma prognosis.

methodsIn this study, we established an RNA sequencing-based 12-gene signature data of melanoma patients obtained from 2 independent databases: the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We evaluated the quality of each gene to predict survival conditions in each database by employing univariate and multivariate regression models. A prognostic risk score based on a prognostic signature was determined. This prognostic gene signature further classified patients into low-risk and high-risk groups.

resultsBased on a prognostic signature, a prognostic risk score was determined. This prognostic gene signature further divided the patients into low-risk and high-risk groups. In the chemotherapy and radiotherapy groups of the TCGA cohort and V-raf murine sarcoma viral oncogene homolog B1 (BRAF) expression group in the GEO cohort, patients in the low-risk group had a longer survival duration compared to patients in the high-risk group. Nevertheless, the immunotherapy group in the TCGA database and neuroblastoma RAS viral oncogene homolog (NRAS) expression group in the GEO database had no significant differences in statistics. Moreover, this gene signature was associated with patient prognosis regardless of whether the Breslow depth was greater than or less than 3.75 mm. Stratified gene set enrichment analysis (GSEA) revealed that certain immune-related pathways, such as the T-cell signaling pathway, chemokine signaling pathway, and primary immunodeficiency, were significantly enriched in the low-risk group of both TCGA and GEO cohorts. This information implied the immune-related properties of the 12-gene signature.

conclusionsOur study emphasizes the significance of the gene expression signature in that it may be an indispensable prognostic predictor in melanoma and has great potential for application in personalized treatment.

Indexed as

gene expression signatureMelanomaprognostic predictiontreatment

Identifiers

PMID32355756
PMCPMC7186619
OpenAlexW3013111838

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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.