Evidence map›Paper›PMID 36905554›Full record

ArticleBulletin of experimental biology and medicine2023

Differential Expression of Autophagy-Related Long Non-Coding RNA in Melanoma.

C Dai, W H Kai, X Pan

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Article in Bulletin of experimental biology and medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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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

3 authors.

C DaiDepartment of Medicine, Tongling Polytechnic, Tongling, Anhui, China.
W H KaiDepartment of Medicine, Tongling Polytechnic, Tongling, Anhui, China. 793041992@qq.com.
X PanDepartment of Medicine, Tongling Polytechnic, Tongling, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the role of autophagy-related differential long non-coding RNA (lncRNA) in the pathogenesis of melanoma, we established a prognostic prediction model for patients with melanoma based on the expression profiles of autophagy-related gene. Based on The Cancer Genome Atlas and GeneCard database, we used single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network analysis (WGCNA), uniCOX in R software for COX proportional hazard regression analysis, and enrichment analysis to get an idea of biological processes with autophagy-related genes, which evaluates the relationship between autophagy-related genes and immune cell infiltration in patients with melanoma. The roles of identified lncRNA were evaluated by the risk score based on the results of single factor regression analysis for each lncRNA and on the prognosis for patients obtained from the database. Then, the whole sample was divided into high- and low-risk groups. Survival curve analysis showed that low-risk group had a better prognosis. Enrichment analysis revealed multiple key pathways enriched with lncRNA-associated genes. Analysis of immune cell infiltration revealed differences between high- and low-risk groups. Finally, 3 datasets verified the effect of our model on prognosis. There are important autophagy-related lncRNA in patients with melanoma. Top 6 lncRNA are significantly related to the overall survival rate of patients with melanoma and provide the basis for predicting the prognostic survival of patients.

Indexed as

MelanomaRNA, Long NoncodingAutophagyDatabases, FactualGene Expression ProfilingHumansRNA, Long Noncodingautophagy-related genesdata base analysislong non-coding RNAmelanoma

Identifiers

PMID36905554

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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.