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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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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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Abbreviations

SKCM:

Skin cutaneous melanoma

lncRNA:

Long non-coding RNA

ARLs:

Autophagy-related lncRNAs

ARLPs:

Autophagy-related lncRNA pairs

AMBRA1:

Beclin 1-regulated autophagy protein 1

AC:

Acid ceramidase

ARGs:

Autophagy-related genes

TCGA:

The cancer genome atlas

HADb:

Human autophagy database

KM:

Kaplan–Meier

PRARLs:

Prognosis-related ARLs

Coef:

Coefficient

ROC:

Receiver operator characteristic curve

DSS:

Disease specific survival

CCM:

Calibration curve method

C-index:

Concordance-index

DCA:

Decision curve analysis

TMB:

Tumor mutation burden

GSEA:

Gene set enrichment analysis

WGCNA:

Weighted gene co-expression network analysis

TOM:

Topology overlap measurement

GS:

Gene significance

MS:

Module significance

TIP:

Tracking tumor immunophenotype

IPS:

Immunophenoscore

HRs:

Hazard ratios

CIs:

Confidence intervals

VAF:

Variant allele frequency

CTLA-4:

Cytotoxic T-lymphocyte-associated protein 4

PD-1:

Programmed cell death-1

USP30-AS1:

USP30 antisense RNA 1

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Author notes

  1. Yuyao Liu and Haoxue Zhang contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Department of Burns, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China

    Yuyao Liu & Delin Hu

  2. Department of Dermatovenerology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China

    Haoxue Zhang & Shengxiu Liu

  3. Key Laboratory of Dermatology, Ministry of Education, Hefei , Anhui Province, China

    Haoxue Zhang & Shengxiu Liu

  4. Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Medical University, Hefei, Anhui Province, China

    Haoxue Zhang & Shengxiu Liu

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Contributions

YYL and HXZ: are responsible for writing and submitting the papers, collecting and analyzing data, managing all pictures and tables; DLH and SXL: are responsible for the ideas and guidance. The authors have read and approved the final manuscript.

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Correspondence to Delin Hu or Shengxiu Liu.

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Liu, Y., Zhang, H., Hu, D. et al. New algorithms based on autophagy-related lncRNAs pairs to predict the prognosis of skin cutaneous melanoma patients. Arch Dermatol Res 315, 1511–1526 (2023). https://doi.org/10.1007/s00403-022-02522-0

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