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Introduction

In previous years, despite advancements in preventative measures and lifestyle changes, the incidence of skin cutaneous melanoma (SKCM) has slowed its upward trend (1,2). However, studies demonstrate that in the United States, ~97,610 new melanoma cases were estimated to be diagnosed in 2023 (3), with cutaneous melanoma accounting for 72% of all skin cancer-related deaths (excluding basal cell carcinoma and squamous cell carcinoma) (4). These data underscore the impact of melanoma within the spectrum of skin cancer types. Consequently, there remains a pressing need for continued research efforts to explore effective treatment strategies and therapeutic targets for cutaneous melanoma.

In general, the incidence of melanoma is often associated with prolonged exposure to ultraviolet (UV) radiation, primarily from UVA and UVB spectra. Genomic analyses across various types of cancer have shown that cutaneous melanomas carry an exceptionally high mutational burden, often >10 mutations per megabase. These mutations frequently exhibit UV-specific signatures, with a notable prevalence of C-to-T transitions and G-to-T transversions (5,6). While the effects of radiation from different UV spectra can overlap owing to their ability to induce DNA mutation, UVA and UVB irradiation have distinct mechanisms in promoting melanoma. For example, UVB mainly causes damage by being absorbed by cellular components such as DNA, aromatic amino acids and unsaturated lipids, while also generating some reactive oxygen species (ROS). By contrast, UVA primarily causes damage through the production of ROS, with less direct absorption by cellular components such as DNA (7).

In contemporary melanoma management, therapeutic decision-making is fundamentally driven by comprehensive tumour genetic profiling, enabling precise alignment of targeted interventions with specific driver mutations (8,9). This approach is clearly demonstrated by BRAF inhibitors, with vemurafenib emerging as a prototypical agent demonstrating >50% objective response rates and clinically meaningful survival improvements in phase 1/2 trials involving patients with BRAF V600E mutations (10). The successful advancement of RAF-MEK inhibitors into multi-phase clinical trials (I–III) is fundamentally rooted in precision therapeutic paradigms that strategically align tumour genotype with selective pathway blockade, driving measurable survival benefits in genetically defined patient populations (11). However, this approach has its limitations. For example, some patients may exhibit a suboptimal response to these inhibitors or experience individual adverse reactions such as arthralgia, rash, nausea, photosensitivity, fatigue, cutaneous squamous-cell carcinoma, pruritus and palmar-plantar dysesthesia (12). When addressing the challenge of mitigating the aforementioned side effects, a promising approach lies in identifying an additional target for concurrent melanoma treatment, thereby enabling RAF-MEK inhibitor dose reduction while optimizing efficacy. Hence, a comprehensive exploration of the interplay between genes and melanoma development is key for devising personalized targeted treatments.

Elongator acetyltransferase complex subunit 6 (ELP6) (13) serves a pivotal role within the elongator complex, together with ELP1, ELP2, ELP3, ELP4 and ELP5 (14). Studies in this domain suggest that within eukaryotic cells, the ELP6 subunit facilitates protein translation by modifying tRNAs corresponding to specific codons, including those containing the amino acids AAA (15), CAA (16) and GAA (17). Previous research has demonstrated notable associations between the ELP subunits and tumorigenesis, progression and/or metastasis across a spectrum of malignancies, including gallbladder carcinoma (18,19), sonic hedgehog pathway-associated medulloblastoma (20), brain cancer (21), breast carcinoma (22) and lung carcinoma (23). Notably, a previous study by Close et al (24), which utilized melanoma-derived cells in vitro, preliminarily established a positive correlation between ELP6 expression and the ability of melanoma to form clones and migrate. These findings suggest a potential role for inhibiting ELP6 expression in melanoma therapy. However, there are currently no reports on whether the expression of ELP subunits, particularly ELP6, changes in patients with melanoma, whether ELP6 gene expression levels are associated with patient survival rates and the underlying reasons for any alterations in ELP6 expression.

Therefore, the present study aimed to systematically characterize the expression patterns and mutational profiles of ELP1-6 in melanoma by integrating GEPIA and TCGA databases, evaluate the clinical relevance of ELP1-6 expression levels with patient prognosis and investigate the biological function of ELP6 in melanoma progression as well as its regulatory effects on targeted therapy sensitivity.

Materials and methods

Public data collection

Analyses were performed using the standardized pipeline of the Gene Expression Profiling Interactive Analysis (GEPIA, http://gepia.cancer-pku.cn/index.html) platform (25), which provides pre-integrated transcriptomic datasets from The Cancer Genome Atlas (TCGA, http://portal.gdc.cancer.gov/) and Genotype-Tissue Expression (GTEx, http://gtexportal.org/home/). Users input target gene symbols (ELP1-6) to activate the platform's automated analytical pipeline, which directly generates comparative expression boxplots between SKCM and normal tissues. No local data download or computational processing was performed, as all outputs were produced through the platform's self-contained analytical modules. Survival analyses utilized TCGA-derived clinical follow-up data, with patient grouped by median ELP1-6 expression levels and Kaplan-Meier curve. Publicly available RNA-seq data of cutaneous melanoma (accession no, GSE15605) were retrieved from the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/).

To examine ELP1-6 alterations, including missense mutations, splice mutations, truncating mutations, structural variants, amplifications and deep deletions, the TCGA-SKCM dataset (PanCancer Atlas) using cBioPortal for Cancer Genomics (https://www.cbioportal.org/, version 3.7.29) was analysed.

Survival analysis

Essential clinical data for patients with SKCM, such as age, sex, survival time, survival status and stage, from the TCGA database were obtained. These data were then matched with whole-transcriptome profiling data for the ELP6high (n=234) and ELP6low (n=234) groups, categorized on the basis of the median expression of ELP6 [median log2(TPM + 1)=4.9055], using sample IDs. Patients without complete clinical follow-up information were excluded. Kaplan-Meier survival analysis was performed via R statistical software (version 4.1.2; https://www.r-project.org/; Posit Software, PBC) and the ‘survival’ (version 3.3.1) and ‘survminer’ (version 0.4.9) packages to assess the relationship between ELP6 mRNA expression levels and survival outcomes of patients with SKCM. To compare the survival distributions between the high and low expression groups, the log rank test was applied, a non-parametric method that evaluates the observed vs. expected events (such as deaths) at each time point. The test calculates a χ2 statistic, with the resulting P-value determining the statistical significance. P<0.05 was considered to indicate a statistically significant difference.

Chemotherapeutic sensitivity prediction

To predict drug sensitivity, the Cancer Cell Line Encyclopaedia (version no. CCLE2012, http://sites.broadinstitute.org/ccle/) (26) and the R package ‘pRRopheticPredict’ (version 0.5) that employ the ridge regression model were utilized, as previously published (27). Statistical analysis was conducted using the Wilcoxon test. P<0.05 was considered to indicate a statistically significant difference.

Cell culture

The 293T, SK-MEL-2 and A375 cell lines were obtained from Procell Life Science & Technology Co., Ltd., and were authenticated using STR analysis. A375 cells, a melanoma cell line, harbour the BRAF V600E mutation (28), and SK-MEL-2 cells, also melanoma-derived, harbour an N-RAS mutation (29), both of which are relevant to the study of melanoma. The cell lines were cultured according to standard protocols in medium supplemented with 10% foetal bovine serum (FBS) and 100 µg/ml penicillin. The cells were maintained at 37°C in a humidified atmosphere with 5% CO2.

Cell counting kit-8 (CCK-8) cytotoxicity assay

The target cells were seeded at a density of 5,000 cells per well in 96-well plates and allowed to adhere overnight under standard culture conditions (37°C, 5% CO2). Cells were then treated with U0126 (0, 0.1, 0.2, 0.5 or 1 µM in 0.1% DMSO) for 24 or 48 h at 37°C. Following treatment, the medium was replaced with fresh serum-free medium supplemented with 10 µl of CCK-8 solution (cat. no. HY-K0301; MedChemExpress) for 1 h at 37°C. The optical density of each well was then measured at 450 nm using a microplate reader (ELx800; BioTek; Agilent Technologies, Inc.). Background absorbance, determined from wells containing only culture medium and CCK-8 solution, was subtracted from the obtained values. Relative cell viability was calculated by comparing the absorbance of treated cells to that of untreated control cells.

RNA extraction and real-time quantitative PCR (RT-qPCR)

Total RNA extraction was carried out using TRIzol reagent (Invitrogen; Thermo Fisher Scientific, Inc.) following the manufacturer's protocol. Following extraction, RNA quality and quantity were assessed using a NanoDrop spectrophotometer (NanodropTM lite; Thermo Fisher Scientific, Inc.) or agarose gel electrophoresis. cDNA synthesis was subsequently performed using reverse transcriptase M-MLV (RNase H-), and RT-qPCR was subsequently conducted using TB Green® Premix Ex Taq™ II (Tli RNaseH Plus; Takara Bio, Inc.) on a real-time PCR System (Bio-Rad Laboratories, Inc.) under the following thermocycling conditions: 95°C for 30 sec; 39 cycles of 95°C for 10 sec, 56°C for 15 sec and 72°C for 15 sec. Melt curve analysis was performed at the following thermocycling conditions: 95°C for 15 sec, 55°C for 15 sec and continuous heating from 55–95°C at 0.5°C increments every 5 sec to verify amplification specificity. Gene expression levels were normalized to those of GAPDH, and relative expression was calculated using the 2−ΔΔCq method (30,31). To ensure accuracy and reproducibility, triplicate experiments were performed for each sample. Target genes were amplified using the following primers: ELP6 forward (F), 5′-TGGCTGTGCTAGACTTCAT-3′ and reverse (R), 5′-GTCATTCTCCTCATCCTCC-3′; GAPDHF, 5′-ACAACTTTGGTATCGTGGAAGG-3′ and R, 5′-GCCATCACGCCACAGTTTC-3′; proliferating cell nuclear antigen (PCNA) F, 5′-CCTGCTGGGATATTAGCTCCA-3′ and R, 5′-CAGCGGTAGGTGTCGAAGC-3′; Ki67 F, 5′-ACGCCTGGTTACTATCAAAAGG-3′ and R, 5′-CAGACCCATTTACTTGTGTTGGA-3′; KARS1 F, 5′-ACAGATAATGAGCCCTTTG-3′ and R, 5′-GTTGTTGGAGTCCGTGAG-3′; p44 MAPK F, 5′-CTACACGCAGTTGCAGTACAT-3′ and R, 5′-CAGCAGGATCTGGATCTCCC-3′; and p42 MAPK F, 5′-CATGTCTGAAGCGCAGTAAGATT-3′ and R, 5′-TACACCAACCTCTCGTACATCG-3′.

Western blotting

ShCtrl and shELP6-3 293T cell lines were treated with cycloheximide (CHX, cat. no. HY-12320; MedChemExpress) 0 or 10 µg/ml in serum free medium at 37°C with 5% CO2 for 0 or 24 h, while shCtrl and shELP6 A375 cells were exposed to CHX (0 or 10 µg/ml) under the aforementioned conditions for 0, 12 or 24 h. Cellular proteins were extracted using RIPA lysis buffer (cat. no. r0010-100; Beijing Solarbio Science & Technology Co., Ltd.) supplemented with PMSF (cat. no. P0100; Beijing Solarbio Science & Technology Co., Ltd.) and protease/phosphatase inhibitor cocktail (cat. no. P6730; Beijing Solarbio Science & Technology Co., Ltd.). After lysis on ice, the lysates were centrifuged at 16,000 × g for 30 min at 4°C to collect the protein-containing supernatant, which was then quantified using the Bradford assay. Equal amounts (50 µg) of protein samples were separated using 10 or 12% SDS-PAGE gels and transferred onto polyvinylidene fluoride membranes (cat. no. SEQ00010; Merck KGaA). The membranes were blocked with 5% milk at room temperature for 1 h and incubated overnight at 4°C with primary antibodies targeting ERK1/2 (cat. no. 51068-1-AP; 1:1,000; Proteintech Group, Inc.), phospho-ERK1/2 (cat. no. Thr202/Tyr204) (cat. no. 28733-1-AP; 1:500; Proteintech Group, Inc.) or GFP (cat. no. 66002; 1:3,000; Proteintech Group, Inc.), together with GAPDH (cat. no. 60004; 1:3,000; Proteintech Group, Inc.) or tubulin (cat. no. 66031; 1:3,000; Proteintech Group, Inc.) as the housekeeping proteins for normalization. After incubation with goat anti-mouse (cat. no. SA00001-1; 1:5,000; Proteintech Group, Inc.) or goat anti-rabbit (cat. no. SA00001-2; 1:5,000; Proteintech Group, Inc.) secondary antibodies at room temperature for 1 h, protein bands were subsequently visualized using the Immobilon Western Chemiluminescent HRP substrate (cat. no. WBKLS0100; Merck KGaA).

Plasmid constructs

The overexpression vector was constructed by amplifying ELP6 cDNA from 293T cells using PCR. PCR amplification was performed with PrimeSTAR HS DNA polymerase (cat. no. R010A; Takara Bio, Inc.) using the following primers: F, 5′-GGAATTCATGTTCGTGGAACTTAATAACC-3′ and R, 5′-AAGGTACCTCACAGAACAGCAGGAGACAT-3′. The following thermocycling conditiona were used: 98°C for 2 min; 35 cycles of 98°C for 10 sec, 55°C for 15 sec, 72°C for 1 min and 72°C for 5 min. The PCR product was separated on a 1% agarose gel (cat. no. 9012-36-6, Sangon Biotech Co., Ltd.) stained with GeneRed (cat. no. RT211, Tiangen Biotech Co., Ltd.), and the target band (~0.8 kb) was excised and purified using a Gel Extraction Kit (cat. no. DP209-02; Tiangen Biotech Co., Ltd.). Both the PCR product and the PEGFP-C2 plasmid (Runyan Laboratory Reagents Co., Ltd.) were subsequently digested with EcoRI (cat. no. 1040S; Takara Bio, Inc.) and KpnI (cat. no. 1068S; Takara Bio, Inc.) enzymes. The digested fragments were ligated together via T4 DNA ligase (cat. no. 2011A; Takara Bio, Inc.) and transformed into competent Eschericia coli DH5α cells (cat. no. 9027; Takara Bio, Inc.). Positive transformants were selected on LB agar plates containing 50 µg/ml kanamycin (cat. no. K8020; Beijing Solarbio Science & Technology Co., Ltd.), and the resulting plasmid was purified using the Rapid Plasmid Extraction Kit (cat. no. DP105-02; Tiangen Biotech Co., Ltd.) according to the manufacturer's protocol. Verification of the construct was achieved through restriction enzyme digestion and Sanger sequencing (data not shown), which confirmed the successful integration of ELP6 into the pEGFP-C2 plasmid. The p42-MAPK-pcDNA3.10V5-HisB plasmid was obtained from Genewiz, Inc.

Cell transfection

The 293T or A375 cells were transfected with Lipofectamine™ 2000 transfection reagent (cat. no. 11668019; Thermo Fisher Scientific, Inc.) in accordance with the manufacturer's instructions. Briefly, 293T or A375 cells were seeded to achieve 60–70% confluency prior to transfection. Plasmid DNA (2 µg/well in 6-well plates) or siRNA (50 nM final concentration) and the transfection reagent, were separately diluted in Opti-MEM reduced serum medium (cat. no. 31985070; Gibco; Thermo Fisher Scientific, Inc.), mixed at a 1:3 ratio (DNA/siRNA : reagent), and incubated at 20°C for 20 min to form complexes. These complexes were then gently added dropwise to the cells and swirled to ensure an even distribution. After incubation at 37°C (5% CO2) for 4 h (plasmid) or 24 h (siRNA), the medium was replaced with fresh complete growth medium. The siRNA sequences used were as follows: siNC sense, 5′-UUCUCCGAACGUGUCACGUTT-3′ and antisense, 5′-ACGUGACACGUUCGGAGAATT-3′; and lysyl tRNA synthetase (LysRS; T4) sense, 5′-GGAGAAUGUAGCAACCACUUU-3′ and antisense, 5′-AGUGGUUGCUACAUUCUCCUU-3′. Cells were harvested for downstream analyses at 24, 48 72 h post-transfection.

Virus preparation

Specific short hairpin RNA (shRNA) sequences designed to target ELP6 were integrated into psi-LVRU6GP vector backbones (GeneCopoeia, Inc.) using BamHI (cat. no. 1010S; Takara Bio, Inc.) and EcoRI (cat. no. 1040S; Takara Bio, Inc.) restriction enzyme digestion, followed by ligation with T4 DNA ligase (cat. no. 2011A; Takara Bio, Inc.). The integrity of the construct was confirmed by Sanger sequencing (data not shown). Subsequently, viruses were generated using 293T cells. Initially, 293T cells were cultured and expanded in 10-cm dishes to an appropriate density. The constructed shRNA vector was transfected, along with the helper virus packaging vectors pMD2.G and psPAX2 (Runyan Laboratory Reagents Co., Ltd.), into 293T cells using Lipofectamine™ 2000 transfection reagent (cat. no. 11668019; Thermo Fisher Scientific, Inc.). The transfected cells were incubated at 37°C for 48 h to facilitate virus production, after which the culture supernatant was collected. Finally, the virus was stored at −80°C for subsequent experiments. The shRNA sequences used are listed in Table I.

Table I. shRNA sequences.

Table I.

shRNA sequences.

shRNA	Sequence (5′-3′)
H-ELP6-psi-shRNA-1	S: GATCCGCTTTCTCTCCTTCTATCTCAATCAAGAGTTGAGATAGAAGGAGAGAAAGTTTTTTGG
	AS: AATTCCAAAAAACTTTCTCTCCTTCTATCTCAACTCTTGATTGAGATAGAAGGAGAGAAAGCG
H-ELP6-psi-shRNA-2	S: GATCCGGAAACTGACTCTACTCTGTGATCAAGAGTCACAGAGTAGAGTCAGTTTCTTTTTTGG
	AS: AATTCCAAAAAAGAAACTGACTCTACTCTGTGACTCTTGATCACAGAGTAGAGTCAGTTTCCG
H-ELP6-psi-shRNA-3	S: GATCCGCAGTCATCAGAGCCATCTGATTCAAGAGATCAGATGGCTCTGATGACTGTTTTTTGG
	AS: AATTCCAAAAAACAGTCATCAGAGCCATCTGATCTCTTGAATCAGATGGCTCTGATGACTGCG
Non-targeting sequence	S: GATCCGGCTTCGCGCCGTAGTCTTATCAAGAGTAAGACTACGGCGCGAAGCTTTTTTGG
	AS: AATTCCAAAAAAGCTTCGCGCCGTAGTCTTACTCTTGATAAGACTACGGCGCGAAGCCG

[i] S, sense; AS, anti-sense; sh, short hairpin.

Establishing stable cell lines via lentiviral infection

Following the transfection of 293T and A375 cells with a lentivirus targeting ELP6, the cells were allowed to incubate for 24 h to facilitate viral infection. The infected cells were subsequently selected using puromycin antibiotic resistance (1.5 µg/ml; cat. no. p8230; Beijing Solarbio Science & Technology Co., Ltd.). This selection process was maintained for 2 weeks to establish stable cell lines, including shCtrl, shELP6-2 and shELP6-3 in 293T cells, as well as shCtrl and shELP6 in A375 cells. Characterization of these cell lines, aimed at confirming the expression of the ELP6 gene, was conducted through qPCR analysis as aforementioned.

Cell cycle analysis

shCtrl and shELP6 A375 cells (generated by lentiviral-mediated stable ELP6 knockdown as aforementioned) were seeded into T25 flasks at a density of 1×106 cells per flask. After overnight culture, cells were serum-starved in serum-free medium for 24 h, followed by stimulation with complete medium containing 10% FBS for another 24 h. Cells were harvested with 0.25% trypsin (cat. no. 12604013; Gibco; Thermo Fisher Scientific, Inc.), washed twice with phosphate-buffered saline (PBS; cat. no. C10010500BT; Gibco; Thermo Fisher Scientific, Inc.), and fixed in 75% ice-cold ethanol at 4°C for 12 h. Fixed cells were washed with PBS, treated with 100 µg/ml RNase A (cat. no. 9001-99-4; Beijing Solarbio Science & Technology Co., Ltd.) at 37°C for 30 min to digest RNA and then stained with 50 µg/ml propidium iodide (PI) (cat. no. 25535-16-4; Beijing Solarbio Science & Technology Co., Ltd.) in the dark at 4°C for 30 min for DNA quantification. For flow cytometric analysis, a FACSVerse flow cytometer (BD Biosciences) equipped with PI fluorescence captured was used, and cell cycle distribution (G0/G1, S, G2/M phases) was quantified using ModFit LT software (version 4.0.5; Verity Software House, Inc.).

Statistical analysis

All experiments were independently conducted at least three times. Data were expressed as mean ± SEM. Statistical comparisons were performed using the two-tailed unpaired student's t-test for two-group analyses. For multi-group comparisons, one-way ANOVA was applied followed by Tukey's test or Dunnett's test. Non-normally distributed data were analysed with Wilcoxon paired signed-rank test. P<0.05 was considered to indicate a statistically significant difference.

Results

ELP6 is highly expressed in SKCM

Previous investigations have demonstrated the growth-promoting effects of ELP subunits in sonic hedgehog-related medulloblastoma (15), brain cancer (16), breast cancer (17) and lung cancer (18). The present study investigated the potential anticancer activities of ELP subunits in SKCM. Using the GEPIA database, systematic examination of whether the mRNA expression levels of ELP subunits (including ELP1-6) were altered in various types of cancer was conducted. Compared with that in normal tissues, the mRNA expression levels of ELP1, ELP2, ELP3 and ELP4 in SKCM remained unchanged (Fig. 1A-D). By contrast, when the same criteria were used, the expression levels of ELP5 and ELP6 SKCM were significantly increased compared with that in normal tissues (Fig. 1E and F).

Figure 1. Prognostic impact of ELP1, ELP2, ELP3, ELP4, ELP5 and ELP6 expression levels in patients with SKCM. The transcriptional levels of (A) ELP1 (ns), (B) ELP2 (ns), (C) ELP3 (ns), (D) ELP4 (ns), (E) ELP5 (*P<0.05) and (F) ELP6 (*P<0.05) in the normal (grey) and SKCM (red) groups according to the GEPIA database. (G) The predictive performance of ELP6 to distinguish between normal and SKCM samples was high, demonstrated using the GSE15605 dataset. (H-M) Kaplan-Meier plotter analysis of OS rates between patients with SCKM stratified into the following groups: (H) ELP1high and ELP1low, (I) ELP2high and ELP2low, (J) ELP3high and ELP3low, (K) ELP4high and ELP4low, (L) ELP5high and ELP5low and (M) ELP6high and ELP6low, according to GEPIA data. (N) The Kaplan-Meier survival curves by ELP6 transcript levels in patients with TCGA-SKCM (n=458). ELP6, elongator acetyltransferase complex subunit 6; SKCM, skin cutaneous melanoma; GEPIA, Gene Expression Profiling Interactive Analysis; GSE, gene set enrichment; OS, overall survival; ns, not significant.

Next, the potential impact of increased expression levels of ELP subunits on clinical outcomes was examined. Using transcriptomic data from the GEO database (dataset accession no. GSE15605), receiver operating characteristic curve analysis demonstrated that ELP6 expression levels significantly distinguished SKCM samples from normal tissues, with an area under the curve of 0.794 (95% CI, 0.666–0.901) (Fig. 1G). Using the GEPIA database to generate Kaplan-Meier curves, it was determined that increased mRNA expression levels of ELP1, 2, 3, 4 and 5 did not have a significant effect on the prolonged time to recurrence or death (Fig. 1H-L). However, increased expression levels of the specific subunit ELP6 were significantly associated with shorter overall survival (OS) in patients with SKCM (Fig. 1M), whereas increased ELP6 expression levels had no significant impact on disease-free survival (Fig. S1A). The survival analysis from the GEPIA database (Fig. 1M) showed lower survival rates between 100 to 200 months, followed by a reversal of survival trends between 250 to 300 months. To account for this, transcriptome profiling data was utilized with complete clinical information from the TCGA-SKCM cohort, which includes patients with SKCM categorized into two groups based on the median expression level of ELP6: OS-ELP6high (n=229) and OS-ELP6low (n=229). To further refine the analysis, the follow-up period was restricted to the first 18 years (216 months). The truncated analysis still demonstrated significant survival differences (Fig. 1N; P<0.05), with higher ELP6 expression levels being associated with poorer prognosis and a shorter median OS in patients with SKCM. When comparing OS across different stages, ELP6 expression levels were closely associated with poorer OS in both stage 0/I/II (Fig. S1B) and stage III/IV groups (Fig. S1C). Moreover, subgroup analysis based on sex demonstrated that elevated ELP6 expression levels were significantly associated with worse OS specifically in male patients with SKCM (Fig. S1D and E).

To investigate the underlying causes of the abnormal expression of ELP6, the cBioPortal database was utilized to analyse the mutation rates of ELP1, ELP2, ELP3, ELP4, ELP5 and ELP6 in TCGA-SKCM (PanCancer Atlas) in 363 SKCM samples. As shown in Fig. S2A, the incidence of mutations in ELP1-6 was markedly low in SKCM. Notably, while the mutation rates in ELP1, ELP2, ELP3, ELP4 and ELP5 were 6.0, 2.8, 4.0, 2.2 and 2.2%, respectively, ELP6 presented the lowest mutation rate at 1.4%, which included four missense mutations and one amplification, suggesting that there were no significant alterations in the sequence of ELP6 that could account for its upregulation. Moreover, associations between ELP6 expression levels and the sex or age of patients with SKCM were explored using TCGA clinical characteristics; however, no significant differences were detected either between the ≥50 and <50 years of age groups, or between males and females (Fig. S2B-E).

Positive association between ELP6 expression levels and cell proliferation capability

To ascertain whether increased ELP6 expression contributed to SKCM progression, Gene Set Enrichment Analysis (GSEA) was performed to predict potential mediators of its effects. This analysis showed that cell cycle progression pathways-driven by CDK1, E2F1-4, and PCNA-were positively enriched (data not shown), suggesting that ELP6 may promote tumorigenesis by enhancing proliferative signalling. To further validate this association, ELP6-knockdown clones were generated in 293T cells using four different shRNAs: shCtrl, shELP6-1, shELP6-2 and shELP6-3. The RNA knockdown efficiency reached ~20 and 70% inhibition of ELP6 expression levels in shELP6-2 and shELP6-3 cells, respectively (Fig. 2A), whereas no significant changes were observed in shELP6-1 (data not shown). Therefore, shELP6-2 and shELP6-3 were selected for the CCK-8 assay. ELP6 knockdown led to a significant reduction in cell viability (Fig. 2B and C). Given the significant inhibitory effects observed with shELP6-3, shELP6-3 was used to establish stable ELP6 knockdown clones in A375 cells and in SK-MEL-2 cells, denoted as shELP6-A375 (Fig. 2D) and shELP6-SK-MEL-2 (Fig. S3A). Consistent with these results, ELP6 suppression led to a significant reduction in the proliferation rate, as demonstrated by the CCK-8 assay (Figs. 2E and S3B).

Figure 2. ELP6 is essential for driving SKCM progression. (A) ELP6 knockdown efficiencies were assessed in 293T cells using two independent shRNAs, shELP6-2 and shELP6-3. The viability of shCtrl, (B) shELP6-2 and (C) shELP6-3 cells was assessed at 0 and 24 h. (D) ELP6 knockdown efficiency using shELP6 was assessed in A375 cells. (E) The viability of shCtrl and shELP6 A375 cells was assessed at 0, 24 and 48 h. The relative mRNA expression levels of Ki67 (F and G) and PCNA (H and I) were evaluated in shCtrl, shELP6-2 and shELP6-3 293T cells, as well as in shELP6 A375 cells. The levels of PCNA mRNA expression levels were evaluated in (J) shELP6-2 and (K) shELP6-3 cells after transfection with either the pEGFP-C2 or pEGFP-ELP6 plasmid. (L) Cell cycle distribution was analysed using flow cytometry, and the percentage of cells in each phase of the cell cycle was calculated. (M) shCtrl and (N) shELP6 A375 cells were exposed to 10% serum for 24 h, followed by staining with propidium iodide. *P<0.05; **P <0.01; ***P<0.001. ELP6, elongator acetyltransferase complex subunit 6; SKCM, skin cutaneous melanoma; sh, short hairpin; m, messenger; Ctrl, control; PCNA, proliferating cell nuclear antigen.

In response to uncontrolled proliferation conditions, cells can experience excessive activation of both Ki67 (32) and PCNA (33,34). Therefore, the mRNA expression levels of Ki67 (Fig. 2F and G) and PCNA (Fig. 2H and I) were analysed in stable cell lines with varying levels of ELP6 expression. Downregulation of Ki67 and PCNA mRNA expression levels in the shELP6-2, shELP6-3 and shELP6 cell lines were observed, compared with their respective controls. To further confirm the role of ELP6 expression in tumour progression, a GFP-tagged ELP6 plasmid was constructed and transiently transfected into both the shELP6-2 and shELP6-3 cell lines, in which ELP6 was silenced as aforementioned. The reintroduction of ELP6 resulted in a significant increase in PCNA mRNA expression levels (Fig. 2J and K; Fig. S3C), providing evidence that ELP6-mediated tumour promotion is linked to cell proliferation.

Next, the impact of ELP6 on the re-entry of quiescent A375 cells into the cell cycle when stimulated with serum was assessed. After a 24 h incubation of both shELP6 and shCtrl cells with FBS, flow cytometry was used to assess the cells ability to progress through the G1 phase (Fig. 2L-N). shELP6 cells predominantly experienced a G1 arrest, with only a limited number of cells advancing to the first S phase and reaching G2/M phases. By contrast, the control cells exhibited a greater propensity to enter the G1 phase. Therefore, the absence of ELP6 prevented FBS-stimulated cell cycle re-entry, leading to the arrest of A375 cells in the G1 phase.

ELP6 drives proliferation via the ERK1/2 pathway

Given the frequent activation of the RAS-BRAF-ERK1/2 pathway in melanoma and the analogous impact on the cell cycle observed with alterations in pathway activity (35), as observed with ELP6-mediated changes, it was investigated whether the RAS-BRAF-ERK1/2 pathway mediated ELP6-induced cell proliferation. In ELP6-deficient cells, a marked reduction in both total and phosphorylated p42 MAPK levels in 293T (Fig. 3A) and A375 (Fig. 3B) cells was observed, while total p42 MAPK levels were also significantly lower in SK-MEL-2 cells compared with that in the control cells (Fig. S3D). ERK phosphorylation efficiency (p-p42/total p42) remained unchanged in knockdown cells. However, both total and phosphorylated ERK levels (normalized to either GAPDH or tubulin) decreased correspondingly (P<0.01; Fig. 3C and D), demonstrating that reduced ERK protein abundance drives the decline in active signaling molecules. qPCR analysis was used to assess the mRNA expression levels of p42 MAPK and p44 MAPK in both the ELP6-normal and the ELP6-silenced cell lines (Fig. 3E and F). A significant decrease in the expression levels of both p42 MAPK and p44 MAPK in A375 cells following ELP6 silencing was demonstrated (Fig. 3F). By contrast, while p44 MAPK expression levels remained stable, there was a notable increase in p42 MAPK expression levels in ELP6-silenced 293T cells compared with their respective parental lines (Fig. 3E).

Figure 3. p42 MAPK serves a key role in mediating the proliferative effects induced by ELP6 in SKCM. Western blot analysis in shCtrl, (A) shELP6-3 293T and (B) shELP6 A375 cells of p42 MAPK or pi-p42 MAPK (Thr202/Tyr204) expression levels. (C and D) Quantification of p42 MAPK or pi-p42 MAPK (Thr202/Tyr204) protein expression levels. mRNA expression levels of p44 MAPK and p42 MAPK, normalized to the GAPDH, in the shCtrl, (E) shELP6-2, shELP6-3 293T and (F) sh-ELP6 A375 cells. Western blot analysis of ELP6-GFP, tubulin and p42 MAPK in (G) shELP6-3 293T and (H) shELP6 A375 cells transfected with either the pEGFP-C2 or pEGFP-ELP6 plasmids, with quantification of p42 MAPK protein expression levels. pcDNA3.10V5-HisB or p42 MAPK-pcDNA3.10V5-HisB transfected into shCtrl, (I) shELP6-3 293T and (J) shELP6 A375 cells were subject to western blot analysis of p42 MAPK expression levels and (K and L) cell viability assays under the same treatment conditions. *P<0.05; **P<0.01; ***P<0.001. ELP6, elongator acetyltransferase complex subunit 6; ns, not significant; pi, phosphorylated; SKCM, skin cutaneous melanoma; sh, short hairpin; Ctrl, control.

Next, to gain insight into the influence of ELP6 on p42 MAPK protein regulation, a GFP-tagged ELP6 plasmid was introduced into the 293T and A375 cell lines. Transfection of the shELP6-3 293T and shELP6 A375 cells with the GFP-tagged ELP6 plasmid resulted in a marked increase in total p42 MAPK levels, suggesting a positive relationship between ELP6 and p42 MAPK (Fig. 3G and H). Additionally, conditions without viral infection (Fig. S4) and conditions with viral infection but without ELP6 knockdown were examined. Transfection with pEGFP-ELP6 increased p42 MAPK protein expression regardless of viral infection or ELP6 knockdown status (data not shown). To further investigate whether ELP6 expedited cell proliferation by increasing p42 MAPK activity, a HisB-tagged p42 MAPK plasmid was constructed and both western blot analysis and a CCK-8 assay on treated cells were conducted. A substantial increase in the intracellular p42 MAPK protein level in 293T and A375 cells upon transfection with the p42 MAPK plasmid (Fig. 3I and J). Moreover, reinstating p42 MAPK expression levels promoted proliferation in both the ELP6-disrupted cells and the control cells (Fig. 3K and L). These findings collectively underscored the pivotal contribution of p42 MAPK to ELP6-induced cell proliferation.

Given the consistent modulation of p42 MAPK protein levels and the distinct patterns of altered mRNA expression caused by changes in ELP6 levels across both cell lines, it was hypothesized that ELP6 may influence p42 MAPK through posttranscriptional regulation, such as by affecting the RNA translation efficiency or protein degradation rates. To investigate this, 293T and A375 cells were treated with CHX, a eukaryotic protein synthesis inhibitor that selectively binds to ribosomes and inhibits eEF2 mediated translocation. CHX treatment resulted in a notable decrease in p42 MAPK protein levels at 16 and 24 h in shCtrl 293T and A375 cells, respectively (Fig. 4A-D). However, no significant effect was observed in cells with silenced ELP6 at 16 and 24 h, suggesting that the absence of ELP6 in cells slowed the degradation rate of the p42 MAPK protein. This finding suggested that protein degradation speed might not be the primary factor contributing to the decrease in p42 MAPK protein levels caused by ELP6 deficiency.

Figure 4. ELP6 stimulates p42 MAPK at the post-transcriptional level. (A) shCtrl and shELP6-3 293T cell lines were treated with CHX followed by western blotting for p42 MAPK and tubulin, quantified in (B). (C) shCtrl and shELP6 A375 cells lines were similarly treated, followed by western blotting for p42 MAPK and GAPDH, quantified in (D). The (E) 293T and (F) A375 cell lines were treated with siT4 or siNC and mRNA expression levels of LysRS, normalized to the GAPDH, were determined to detect knockdown efficiencies. p42 MAPK protein expression levels, normalized to tubulin, were determined in the (G) 293T and (H) A375 cell lines treated with siT4 or siNC. *P<0.05. ns, not significant; NC, negative control; t, transfer; sh, short hairpin; si, silencing; LysRS, lysyl tRNA synthetase; ELP6, elongator acetyltransferase complex subunit 6; SKCM, skin cutaneous melanoma; Ctrl, control; CHX, cycloheximide; siT4, LysRS siRNA.

By modifying the wobble base, U34, of tRNA and disrupting codon-anticodon interactions, ELP6 has the potential to induce ribosomal pausing specifically at CAA and AAA codons (36), thereby impacting translation efficiency. Consequently, it was hypothesized that ELP6 could inhibit p42 MAPK protein expression by modulating codon translation rates. To investigate this possibility, qPCR was initially conducted (Fig. 4E and F), which demonstrated successful inhibition of newly synthesized LysRS, an enzyme responsible for accurately pairing lysine with the AAA codon during translation, upon silencing with siRNA, which was consistent with prior findings (37). Notably, within the subgroup exhibiting decreased production of newly synthesized cellular LysRS, there was a concurrent decline in p42 MAPK protein expression (Fig. 4G and H), resembling the phenotype observed in ELP6 deficiency. These data suggested that ELP6 regulated p42 MAPK through ribosomal pausing.

ELP6 sensitizes melanoma to ERK1/2 pathway inhibitors

To investigate whether ELP6 affected the antitumour effects of inhibitors targeting the RAF-MEK-ERK pathway, the BRAF mutation status between patients with SKCM with high and low ELP6 expression was compared. No significant difference in the BRAF mutation rate between the two groups was observed (Fig. S5). The R software package, pRRophetic (27), was used to predict and calculate the sensitivity values of several drugs, including the RAF inhibitors, AZ628 and sorafenib. A significant trend was demonstrated in that patients with SKCM exhibiting higher ELP6 levels displayed greater sensitivity to AZ628 and sorafenib inhibitors compared with those with lower ELP6 levels (Fig. 5A and B). By contrast, when the commercially available PI3K inhibitor BEZ235 and the P38 MAPK inhibitor VX702 were examined, the opposite pattern was observed (Fig. 5C and D).

Figure 5. ELP6 modulates drug sensitivity in melanoma cell lines. Box plots of the predicted clinical sensitivity of (A) AZ628, (B) Sorafenib, (C) NVP.BEZ235 and (D) VX702 in patients with SKCM categorized into ELP6high (red) or ELP6low (blue) groups from the The Cancer Atlas Genome database (n=468). (E) shCtrl, shELP6-2 and shELP6-3 293T cells were treated with U0126 for 0 and 48 h, and CCK-8 assays were performed to measure cell viability. shCtrl and shELP6 A375 cells were treated with U0126 for (F) 0, 24 and (G) 48 h, followed by a CCK-8 assay to assess cell viability. (H and I) shELP6-3 293T and shELP6 A375 cell lines were transfected with either the pEGFP-C2 or pEGFP-ELP6 plasmid, and treated U0126 for 48 h, followed by a CCK8 assay to evaluate cell viability. shCtrl (J) −293T and (K) -A375 cells were treated with U0126 for 24 h, ELP6 mRNA levels expression levels, normalized to GAPDH, were assessed. (L) Schematic illustrating the modulation of ERK1/2 by ELP6. Data are presented as mean ± SEM. Error bars represent the SEM and each point in the graph corresponds to an individual sample. *P<0.05; **P<0.01; ***P<0.001. ns, not significant; ELP6, elongator acetyltransferase complex subunit 6; SKCM, skin cutaneous melanoma; Ctrl, control; CCK-8, cell counting kit-8; Sh, short hairpin; SEM, standard error of the mean.

Based on the aforementioned present findings which demonstrated a positive association between ELP6 and p42 MAPK expression levels, coupled with the observation that patients lacking ELP6 exhibit poor responses to drugs targeting the RAF-MEK-ERK pathway, a possible explanation for this sensitivity could be that patients lacking sufficient ELP6 have less active p42 MAPK protein compared with those with higher ELP6 expression levels. To investigate this hypothesis, shCtrl, shELP6-2 and shELP6-3 293T cells were treated with the MEK1/2 inhibitor U0126. Growth inhibition assays demonstrated that the lack of ELP6 resulted in reduced sensitivity to U0126 (Fig. 5E). Notably, this diminished responsiveness was consistent across different cell types, as evidenced by similar trends observed in A375 cells lacking ELP6 (Fig. 5F and G) and SK-MEL-2 cells (Fig. S6). Furthermore, reintroduction of a GFP-tagged ELP6 plasmid restored the sensitivity of shELP6-3 and shELP6 cells to U0126 (Fig. 5H and I). Short-term exposure to U0126 did not significantly affect ELP6 mRNA levels (Fig. 5J and K), suggesting that ELP6 functioned as an upstream regulator of ERK1/2 and was not promptly modulated by ERK1/2 activity. Taken together, these findings suggested that ELP6 expression may have contributed, at least in part, to the diminished response of patients to RAF-MEK-ERK pathway inhibitors and highlighted its potential as a biomarker for guiding therapy.

Discussion

Melanoma presents a significant global public health challenge, contributing to 80% of skin cancer-related deaths due to its aggressive metastatic behaviour (38). Reducing melanoma mortality and improving patient responses to traditional chemotherapy remains crucial priorities in global healthcare. Previous studies have demonstrated the function of ELP6, a member of the elongator complex, in promoting cancer proliferation (18,19,21). For example, ELP6 has been shown to stabilize the elongator complex, thereby enhancing the metastatic potential of melanoma (24). In the present study, bioinformatics analysis of the TCGA SKCM dataset (via the GEPIA database) demonstrated that, among the elongator complex subunits, ELP6 was the only subunit that was both significantly upregulated in SKCM and closely associated with patient survival. However, survival analysis from the GEPIA database revealed lower survival rates between 100–200 months, followed by a reversal of survival trends between 250–300 months. The GEPIA database uses the log-rank test by default to assess survival curve differences, which assumes proportional hazard rates. When survival curves cross over, as observed between 250–300 months, this assumption is violated, which can affect the stability of the statistical results. Additionally, during the 250–300-month follow-up period, the number of patients alive in each group was relatively small (~10 individuals), which increases susceptibility to statistical fluctuations. The survival or death of a small number of individuals can disproportionately impact the survival curve. To address this issue, data were downloaded from the TCGA database for further analysis. The truncated analysis still showed significant survival differences. Based on these findings, we suggested that elevated ELP6 expression levels may serve as a marker of SKCM progression and has potential as a predictive biomarker for this cancer.

To further explore the underlying mechanisms, a preliminary GSEA was conducted, which demonstrated enrichment in the cell cycle signalling pathway. To investigate the potential role of ELP6 in cell proliferation via cell cycle regulation, 293T cells, known for their high transfection efficiency (39), were used to establish effective ELP6 knockdown during early experimental stages. In vitro cellular experiments demonstrated that ELP6 downregulation significantly impaired cell proliferation, as indicated by a reduced expression of the proliferation markers Ki67 and PCNA. To establish melanoma-specific relevance despite the non-melanoma origin of 293T cells (40), these findings were validated in two melanoma cell lines: A375 (BRAF V600E mutation) (28) and SK-MEL-2 (N-RAS mutation) (29). It was demonstrated that ELP6 knockdown consistently suppressed proliferation in both lines. Furthermore, cell cycle analysis of A375 cells further demonstrated that the loss of ELP6 led to an increased proportion of cells in the G1/G0 phase. These findings suggest that ELP6 deficiency causes cell cycle arrest in melanoma cells, hindering the transition from the G1 to the S phase, which may contribute to tumour development and progression.

BRAF V600E mutation (41), a hallmark driver in melanoma, promotes tumorigenesis through hyperactivation of the intracellular MAPK signalling cascade, wherein p42 MAPK critically regulates the G0/G1 phase arrest. In the present study, it was demonstrated that ELP6 controlled cell cycle progression at the G1/G0 phase and tumour proliferation, yet its potential interplay with p42 MAPK remained unexplored. Therefore, whether ELP6 modulated both phosphorylated and total p42 MAPK protein levels was explored by using ELP6 knockdown models in melanoma A375 cells and non-melanoma 293T cells. Notably, ELP6 depletion led to a significant reduction in both phosphorylated and total p42 MAPK protein expression levels in both cell lines. However, the regulatory effects on p42 MAPK mRNA diverged between A375 cells (significant downregulation) and 293T cells (no significant change). This discrepancy prompted the present study to investigate whether ELP6 modulated p42 MAPK at the post-transcriptional level. Using the protein synthesis inhibitor CHX, a time dependent decline of total p42 MAPK levels was observed in parental A375 cells, reaching statistical significance at 24 h. However, in A375 cells with low ELP6 expression, no statistically significant difference in p42 MAPK levels was observed at 24 h. Thus, it could be considered that the downregulation of ELP6 in melanoma cell lines led to a decrease in the p42 MAPK protein, resulting in cell cycle arrest and reduced cell proliferation, a process not driven by accelerated protein degradation. Nevertheless, it is currently unclear if ELP6 specifically governs the translation termination fidelity of p42 MAPK, which is sensitive to translation termination control by ELP6 during ribosomal pausing, while the translation termination of other genes such as GAPDH or tubulin are not significantly changed, which requires further investigation.

Given the high prevalence of RAF mutations in melanoma (41), significant efforts have been made to develop RAF-MEK-ERK pathway inhibitors for effective melanoma treatment (42). However, the therapeutic responses observed in certain patients may be partially attributed to individual genetic heterogeneity. Consequently, understanding these resistance mechanisms holds promise for improving the clinical management of SKCM, especially in cases with limited therapeutic options. The results demonstrated in the present study that ELP6 governs p42 MAPK protein may suggest that interpatient variability in ELP6 levels could lead to differential clinical responses to MAPK cascade inhibitors, such as BRAF/MEK/ERK inhibitors. To explore this possibility, response of two sample groups (high ELP6 levels vs. low ELP6 levels) to inhibitors targeting the RAF-MEK-ERK signalling pathway was evaluated. This investigation indicated that patients with melanoma with lower ELP6 levels exhibited reduced sensitivity to these inhibitors, whereas alternative pathway inhibitors, such as p38 MAPK or PI3K inhibitors, demonstrated greater efficacy. On the basis of these findings, it could be suggested that in the absence of ELP6, the significant reduction in the downstream key protein p42 MAPK limits the effectiveness of re-inhibiting the same pathway, such as adding RAF and MEK inhibitors, thereby failing to further restrict melanoma growth. Conversely, when ELP6 is overexpressed or present in excess, it selectively could enhance the translation of p42 MAPK, leading to overactivation of ERK under conditions of upstream RAS and RAF mutations, supporting melanoma cell growth and survival. Therefore, in melanoma treatment, selecting appropriate therapeutic strategies based on the basis of ELP6 expression may potentially improve patient outcomes in the future.

Melanin deposition has been recognized as having a significant effect on the efficacy of melanoma treatment. Studies have shown that, among patients undergoing radiotherapy, survival times are notably longer for amelanotic metastatic patients with melanoma than for melanotic patients. In terms of immunotherapy (43), melanin promotes melanoma progression by inhibiting immune responses through the induction of glycolysis and the activation of hypoxia-inducible factor 1α (44,45). Additionally, melanin is associated with the production of specific neurotransmitters, such as L-DOPA (a precursor to melanin and regarded as a neurohormone) (46), which regulates the tumour microenvironment and protects cancer cells from the host immune response. In the present study, amelanotic melanoma cell lines A375 and SK-MEL-2 were used (47–50) to investigate the effects of ELP6 on melanoma development. However, these results may not fully reflect whether the function of ELP6 changes in the context of melanin deposition. Therefore, further evaluation using melanotic melanoma cell lines to assess the role of ELP6 in MAPK cascade inhibitor treatment may provide a more comprehensive understanding of the role of melanin in tumour progression and treatment resistance.

In the present study, a significant increase in ELP6 expression levels in tissue samples of patient with SKCM was demonstrated, which was significantly associated with reduced survival rates. The present findings demonstrate that ELP6 upregulation may accelerate melanoma progression through the ERK1/2 signalling pathway. Consequently, targeting the ERK1/2 pathway potentially represents a promising therapeutic strategy for patients with elevated ELP6 expression levels. Furthermore, the RAF-RAS-MEK pathway inhibitors, such as ERK1/2 inhibitors, have diminished efficacy in patients with low ELP6 expression levels, potentially due to reduced ERK1/2 activity. These insights underscore the key role of ELP6 in both melanoma progression and treatment response, suggesting valuable implications for therapeutic intervention in the future.

Supplementary Material

Supporting Data

Acknowledgements

Not applicable.

Funding

The present work was supported by the National Natural Science Foundation of China Grants (grant no. 81960655), Guizhou Provincial Basic Research Program [grant. no. qiankehejichu ZK(2022)372] and the Guizhou Provincial Basic Research Program [Natural Science; grant. no. ZK(2022)041].

Availability of data and materials

The data generated in the present study may be requested from the corresponding author.

Authors' contributions

YL and QW analysed data and performed experiments. QL assisted with experiments, data analysis, data verification and revision of the manuscript. PR designed the study and wrote the manuscript. YL and QL confirm the authenticity of all the raw data. All authors participated in writing the manuscript. All authors read and approved the final version of the manuscript.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References