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Article Open Access

m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma

  • Authors:
    • Yi Geng
    • Sijia Zhao
    • Tianxiang Geng
    • Xiu-Lian Xu
    • Xiaodie Zhang
  • View Affiliations / Copyright

    Affiliations: Department of Dermatological Surgery, Shanghai Skin Disease Hospital, School of Medicine, Tongji University, Shanghai 200443, P.R. China, Department of Orthopedics, Yantai Yuhuangding Hospital Affiliated to Medical College of Qingdao University, Yantai, Shandong 264000, P.R. China, Institute of Dermatology, Peking Union Medical College and Chinese Academy of Medical Sciences, Nanjing, Jiangsu 210042, P.R. China
    Copyright: © Geng et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 604
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    Published online on: October 21, 2025
       https://doi.org/10.3892/ol.2025.15350
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Abstract

Skin cutaneous melanoma (SKCM) is a highly aggressive malignancy, and understanding the mechanisms underlying its metastasis is essential for improving patient prognosis. N6‑methyladenosine (m6A) RNA modification is involved in tumor progression; however, its specific role in SKCM metastasis remains poorly defined. The present study aimed to identify m6A‑related regulatory genes associated with SKCM metastasis and to assess their impact on the tumor immune microenvironment. Expression data from primary and metastatic SKCM samples were obtained from the Gene Expression Omnibus (GSE8401, GSE15605, GSE46517 and GSE65904) and The Cancer Genome Atlas‑SKCM databases. A metastasis‑risk prediction model was constructed using least absolute shrinkage and selection operator‑Cox regression analysis. Differential expression analysis, functional enrichment, Pearson correlation, single‑sample gene set enrichment analysis and competing endogenous (ce)RNA network analysis were performed. Key gene expression levels were evaluated using reverse transcription‑quantitative PCR and immunohistochemistry. A total of 94 metastasis‑related mRNAs were identified as differentially expressed, of which 45 demonstrated significant associations with m6A regulators. Among them, 12 genes were associated with patient prognosis, with cadherin 3 (CDH3), keratin 17 (KRT17), plakophilin 1 (PKP1) and cellular retinoic acid binding protein 2 (CRABP2) identified as key candidates. A ceRNA network comprising these four mRNAs, 13 long noncoding RNAs, and 20 microRNAs was constructed. These core genes demonstrated significantly higher expression levels in tumor tissues compared with in adjacent normal tissues, were associated with a worse overall survival, and revealed strong correlations with immune cell infiltration, particularly mast cells and Th17 cells. In conclusion, m6A RNA modification may contribute to SKCM metastasis by regulating the expression of CDH3, KRT17, PKP1 and CRABP2, as well as modulating the tumor immune microenvironment. These findings offer novel insights into the metastatic mechanisms of SKCM and identify potential biomarkers for its diagnosis, prognosis and targeted immunotherapy.
View Figures

Figure 1

Critical SKCM metastasis-related
genes and signaling pathways in the GEO SKCM cohort. (A)
Identification of DEGs in 4 GEO datasets using the RobustRankAggreg
package. A heatmap of the top 20 upregulated and 10 downregulated
DEGs in the integrated GEO datasets analysis is presented: The rows
represent the genes, and the columns represent the GEO dataset.
Each cell contains the log2FoldChange value. Red
represents upregulated genes and blue represents downregulated
genes. GO analysis based on DEGs between metastatic and primary
SKCM. (B) GO enrichment analysis was performed using the
clusterProfiler package to evaluate the related biological
processes. (C) The line color of the ring graph represents the GO
terms, the points represent the genes and the size of the points
represents the count number. (D) Heatmap illustrating Pearson
correlation coefficients between metastasis-associated genes and
N6-methyladenosine regulators in SKCM, with color intensity
indicating the correlation coefficient (blue, negative; yellow,
neutral; and orange/red, positive). **P<0.01. SKCM, skin
cutaneous melanoma; GEO, Gene Expression Omnibus; DEGs,
differentially expressed genes; GO, Gene Ontology.

Figure 2

Prognostic gene signature
construction using the LASSO Cox regression analyses. (A)
Distribution of LASSO coefficients of the upregulated potential
prognostic genes in SKCM metastasis-related genes. (B) Generated
coefficient distribution plots for the logarithmic λ sequence for
the selection of the best parameter λ. (C) Overall performance of
the 12-gene signature in the TCGA-SKCM cohorts. The lower panel
presents a heatmap of the expression profiles of the 12 genes. (D)
Kaplan-Meier curves of the 12-gene signature in the TCGA-SKCM
cohort. The differences between the high- and low-risk groups were
measured using the log-rank test, using |Pearson R|>0.5 and
P<0.05 as thresholds. LASSO, least absolute shrinkage and
selection operator; TCGA, The Cancer Genome Atlas; SKCM, skin
cutaneous melanoma; HR; hazard ratio.

Figure 3

Construction, prognosis analysis and
enrichment analysis of the ceRNA network. (A) Venn diagram of the
co-expressed differential mRNAs and lncRNAs of CDH3, KRT17, PKP1
and CRABP2 in SKCM. (B) Global view of the ceRNA network, which
consists of 13 lncRNAs, 20 miRNAs and 4 mRNAs. Triangles,
rectangles and diamonds represent mRNAs, miRNAs and lncRNAs,
respectively. (C) Prognostic analysis of the ceRNA network
expression level in SKCM assessed using the Kaplan-Meier plotter.
KRT17, PKP1, CDH3, CRABP2, SOX21-AS1, hsa-miR-1276 and
hsa-miR-151a-3p were demonstrated to be risk factors for SKCM,
whilst hsa-miR-3200-3p, hsa-miR-1976 were protective factors for
SKCM. (D) Functional enrichment analyses of co-expressed
differential mRNAs of CDH3, KRT17, PKP1 and CRABP2 in SKCM. The
Sankey diagram shows the pathways in which the co-expressed
differential mRNAs were mainly enriched. The bubble pattern
demonstrates the top 10 enrichment pathways with Entities ratio and
Entities count. The y-axis represents the pathway and the x-axis
represents the rich factor. The size and color of each bubble
represent the number of differentially expressed genes enriched in
the pathway and the -log10(P-value), respectively.
ceRNA, competing endogenous RNA; lncRNA, long noncoding RNA; KRT17,
keratin 17; PKP1, plakophilin 1; CDH3, cadherin 3; CRABP2, cellular
retinoic acid binding protein 2; SKCM, skin cutaneous melanoma;
miRNA/miR, microRNA.

Figure 4

Association of m6A regulators with
the development and progression of SKCM. (A) Compared with normal
samples, four downregulated (METTL3, WTAP, YTHDC1 and YTHDC2) and
13 upregulated regulators (ALKBH5, VIRMA, RBM15, ZC3H13, IGF2BP1,
IGF2BP2, IGF2BP3, YTHDF1, YTHDF2, YTHDF3, HNRNPC, HNRNPA2B1 and
RBMX) were identified in tumor samples. (B) ALKBH5, METTL3, WTAP,
RBM15, YTHDF2, HNRNPC, HNRNPA2B1, RBMX, YTHDC1 and IGF2BP3
exhibited consistently higher or lower mRNA levels as SKCM clinical
staging progressed. *P<0.05; **P<0.01; ***P<0.001. m6A,
N6-methyladenosine; SKCM, skin cutaneous melanoma; METTL,
methyltransferase, m6A complex catalytic subunit; WTAP, Wilms'
tumor associated protein; YTHD, YTH m6A RNA binding protein;
ALKBH5, AlkB homolog 5, RNA demethylase; VIRMA, Vir Like m6A
methyltransferase associated; RBM, RNA binding motif protein;
ZC3H13, zinc finger CCCH-type containing 13; IGF2BP, insulin like
growth factor 2 mRNA binding protein; HNRNP heterogeneous nuclear
ribonucleoprotein; ns, not significant; TPM, transcripts per
million.

Figure 5

Association between m6A regulators
with the expression levels of KRT17, PKP1, CDH3 and CRABP2 in SKCM.
The expression level of KRT17 was associated with METTL3, RBM15,
ALKBH5, IGF2BP3 and HNRNPC; the expression level of PKP1 was
associated with METTL16, ALKBH5, IGF2BP3, YTHDF1 and YTHDF2; the
expression level of CDH3 was associated with VIRMA, RBM15B, YTHDC2,
IGF2BP1 and RBMX; the expression level of CRABP2 was associated
with METTL3, RBM15B, FTO, ALKBH5, IGF2BP1 and YTHDF1. *P<0.05;
**P<0.01; ***P<0.001. m6A, N6-methyladenosine; KRT17, keratin
17; PKP1, plakophilin 1; CDH3, cadherin 3; CRABP2, cellular
retinoic acid binding protein 2; SKCM, skin cutaneous melanoma;
METTL, methyltransferase, m6A complex catalytic subunit; WTAP,
Wilms' tumor associated protein; VIRMA, Vir Like m6A
methyltransferase associated; RBM, RNA binding motif protein;
ZC3H13, zinc finger CCCH-type containing 13; FTO, fat mass and
obesity-associated protein; ALKBH5, AlkB homolog 5, RNA
demethylase; YTHD, YTH m6A RNA binding protein; IGF2BP, insulin
like growth factor 2 mRNA binding protein; HNRNP heterogeneous
nuclear ribonucleoprotein.

Figure 6

Immune landscape of KRT17, PKP1, CDH3
and CRABP2 expression levels in SKCM. (A) Correlations of 24 immune
cells with KRT17, PKP1, CDH3 and CRABP2 expression levels,
respectively. The size of the dots represents the absolute
Pearson's correlation coefficient values. (B). Enrichment
differences of 24 immune cell types between high- and
low-expression groups of KRT17, PKP1, CDH3 and CRABP2. *P<0.05;
**P<0.01; ***P<0.001. KRT17, keratin 17; PKP1, plakophilin 1;
CDH3, cadherin 3; CRABP2, cellular retinoic acid binding protein 2;
SKCM, skin cutaneous melanoma; NK, natural killer; DC, dendritic
cell; aDC, activated DC; TFH, follicular helper T cells; Tcm,
central memory T cells; Tgd, γδ T cells; Tem, effector memory T
cells; pDC, plasmacytoid DC; iDC, immature DC.

Figure 7

Clinical significance of KRT17, PKP1,
CDH3 and CRABP2 expression in patients with SKCM. (A) Receiver
operating characteristic curves of KRT17, PKP1, CDH3 and CRABP2
expression of patients with SKCM in The Cancer Genome Atlas cohort.
(B) Expression levels of KRT17, PKP1, CDH3 and CRABP2 were
positively associated with the pathological stage. (C) In TNM
staging, the expression of KRT17, PKP1, CDH3 and CRABP2 were only
significantly associated with T stage, but not with N and M stage.
(D) No association was demonstrated between KRT17, PKP1, CDH3 and
CRABP2 expression and age. *P<0.05; **P<0.01; ***P<0.001.
KRT17, keratin 17; PKP1, plakophilin 1; CDH3, cadherin 3; CRABP2,
cellular retinoic acid binding protein 2; SKCM, skin cutaneous
melanoma; TPR, true positive rate; FPR, false positive rate; AUC,
area under the curve; TPM, transcripts per million; T, tumor; N,
node; M, metastasis.

Figure 8

Expression of KRT17, PKP1, CDH3 and
CRABP2 in SKCM tissues. The expression levels of KRT17, PKP1, CDH3
and CRABP2 were markedly increased in SKCM tumor tissues (right
panels) compared with in adjacent normal tissues (left panels).
KRT17, keratin 17; PKP1, plakophilin 1; CDH3, cadherin 3; CRABP2,
cellular retinoic acid binding protein 2; SKCM, skin cutaneous
melanoma.
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Copy and paste a formatted citation
Spandidos Publications style
Geng Y, Zhao S, Geng T, Xu X and Zhang X: m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma. Oncol Lett 30: 604, 2025.
APA
Geng, Y., Zhao, S., Geng, T., Xu, X., & Zhang, X. (2025). m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma. Oncology Letters, 30, 604. https://doi.org/10.3892/ol.2025.15350
MLA
Geng, Y., Zhao, S., Geng, T., Xu, X., Zhang, X."m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma". Oncology Letters 30.6 (2025): 604.
Chicago
Geng, Y., Zhao, S., Geng, T., Xu, X., Zhang, X."m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma". Oncology Letters 30, no. 6 (2025): 604. https://doi.org/10.3892/ol.2025.15350
Copy and paste a formatted citation
x
Spandidos Publications style
Geng Y, Zhao S, Geng T, Xu X and Zhang X: m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma. Oncol Lett 30: 604, 2025.
APA
Geng, Y., Zhao, S., Geng, T., Xu, X., & Zhang, X. (2025). m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma. Oncology Letters, 30, 604. https://doi.org/10.3892/ol.2025.15350
MLA
Geng, Y., Zhao, S., Geng, T., Xu, X., Zhang, X."m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma". Oncology Letters 30.6 (2025): 604.
Chicago
Geng, Y., Zhao, S., Geng, T., Xu, X., Zhang, X."m6A RNA methylation regulator‑associated genes drive metastasis and immune cell infiltration in skin cutaneous melanoma". Oncology Letters 30, no. 6 (2025): 604. https://doi.org/10.3892/ol.2025.15350
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