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Archives of Dermatological Research

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09.01.2023 | ORIGINAL PAPER

New algorithms based on autophagy-related lncRNAs pairs to predict the prognosis of skin cutaneous melanoma patients

verfasst von: Yuyao Liu, Haoxue Zhang, Delin Hu, Shengxiu Liu

Erschienen in: Archives of Dermatological Research | Ausgabe 6/2023

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Abstract

Skin cutaneous melanoma (SKCM) is the most malignant skin tumor for it is enormously easy to develop invasion and metastasis. Autophagy is a process by which cellular material is degraded by lysosomes or vacuoles and recycled. Autophagy-related long non-coding RNAs (lncRNAs) have been thought to correlate with SKCM. This study aims to explore the prognostic significance of autophagy-related lncRNAs and establish a prognostic model of autophagy-related lncRNA pairs in SKCM. Firstly, the RNA-seq data and related clinical information were downloaded from the TCGA database. 446 qualified samples were enrolled. 222 autophagy-related genes were obtained from the HADb database. Pearson correlation analysis was conducted to identify autophagy-related lncRNAs (ARLs). After that, we obtained prognosis-related ARLs and autophagy-related lncRNA pairs (ARLPs). Using Lasso-Cox regression analysis, an autophagy-related lncRNA-pair prognostic signature was established. The accuracy of the signature were confirmed through a series of validations in terms of mutation profiles, immunity infiltration, and cellular pathways. And we used the random forest method to find USP30-AS1 as a key mediating factor in SKCM.

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Titel: New algorithms based on autophagy-related lncRNAs pairs to predict the prognosis of skin cutaneous melanoma patients
verfasst von: Yuyao Liu
Haoxue Zhang
Delin Hu
Shengxiu Liu
Publikationsdatum: 09.01.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Archives of Dermatological Research / Ausgabe 6/2023
Print ISSN: 0340-3696
Elektronische ISSN: 1432-069X
DOI: https://doi.org/10.1007/s00403-022-02522-0

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New algorithms based on autophagy-related lncRNAs pairs to predict the prognosis of skin cutaneous melanoma patients

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