TMT proteomics reveals that miR-425-5p promotes proliferation and metastasis of malignant melanoma by inhibiting SCARA5

Abstract

Background

While the relationship between miRNAs and malignant melanoma is well-established, the role of miR-425-5p in melanoma remains underexplored. This study investigated the molecular mechanisms underlying miR-425-5p-mediated regulation of malignant melanoma proliferation and metastasis, with emphasis on its interaction with scavenger receptor class A member 5 (SCARA5).

Methods

The impact of SCARA5 and miR-425-5p on melanoma cell proliferation and metastatic potential was assessed using CCK-8, clonogenic, scratch, and Transwell assays. Western blotting was employed to quantify apoptosis markers, epithelial-mesenchymal transition (EMT)-related proteins, and components of the Akt signaling pathway. Bioinformatics and dual-luciferase reporter assays validated the direct interaction between miR-425-5p and SCARA5. In vivo, a subcutaneous tumor model in nude mice was used to evaluate tumor growth, and TUNEL staining was performed to assess apoptosis. Tandem Mass Tag (TMT) proteomics was applied to comprehensively identify downstream pathways modulated by miR-425-5p.

Results

Silencing SCARA5 in A375 and A2058 cells downregulated the expression of caspase-3 and E-cadherin levels while elevating Bcl-2, p-AKT, N-cadherin, β-catenin, and ZEB1 levels. Conversely, SCARA5 overexpression reversed these effects. Dual-luciferase assays confirmed that miR-425-5p could directly target SCARA5. Inhibition of miR-425-5p expression increased SCARA5 expression and suppressed proliferation/metastasis, whereas miR-425-5p mimics reduced SCARA5 expression and enhanced malignancy. In the in vivo model, SCARA5 overexpression significantly inhibited tumor growth, while the administration of miR-425-5p agonists promoted it. Proteomics further revealed that miR-425-5p could suppress the PPARγ pathway and activate the AKT signaling pathway.

Conclusion

Our findings demonstrate that miR-425-5p promotes melanoma progression by downregulating SCARA5, thereby inhibiting apoptosis, activating AKT phosphorylation, and inducing EMT. These findings identify the miR-425-5p/SCARA5 axis as a potential therapeutic target for melanoma.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-026-04239-w.

Introduction

Malignant melanoma represents one of the most aggressive and metastatic cancers in humans. Although it accounts for less than 5% of all skin cancer cases, it is responsible for 75% of skin cancer-related deaths. The global incidence of malignant melanoma is increasing globally, with an observed decrease in the age of onset, especially among Caucasians [1, 2]. While early diagnosis of malignant melanoma is associated with a high cure rate, its prognosis remains poor due to its highly aggressive nature. The overall 5-year survival rate for patients receiving traditional chemotherapy is reportedly less than 5% [3, 4]. In recent years, significant therapeutic progress has been made with the use of immunotherapy (such as PD-1/PD-L1 inhibitors) and targeted therapy (such as BRAF/MEK inhibitors). However, the 5-year survival rate for patients with malignant melanoma remains approximately 15% [2]. Therefore, identifying early diagnostic biomarkers, elucidating key drivers of metastasis, and developing targeted therapies are critical steps in effectively controlling tumor progression.

SCARA5, a protein localized to the cell membrane, has been shown to induce apoptosis in tumor cells while reducing tumor angiogenesis, thereby acting as a low-key tumor suppressor [5]. Research has investigated the role of SCARA5 in ferritin uptake, revealing its ability to bind serum ferritin, stimulate its endocytosis from the cell surface, and facilitate subsequent iron delivery, thereby interacting with ferritin on the cell surface. Besides, SCARA5 has been implicated in various types of tumors. For instance, experiments involving nude mice and lung cancer have demonstrated that the upregulation of SCARA5 expression inhibits cell migration and invasion, further promoting apoptosis [6]. In breast tumor tissues, SCARA5 expression is typically downregulated and correlated with promoter hypermethylation, which is significantly associated with the histological grade of these tumors [7]. SCARA5 has been shown to inhibit tumor growth and metastasis by regulating key signaling pathways, including STAT3 and FAK, which are crucial for cell survival, proliferation, invasion, angiogenesis, and immune evasion by tumors [8]. However, while several bioinformatics studies suggest a potential link between SCARA5 expression and prognosis in malignant melanoma [9], the clinical significance of SCARA5 in malignant melanoma and its precise relationship with patient prognosis remain insufficiently elucidated, and there is limited understanding of its potential role in the development of malignant melanoma and the underlying molecular mechanisms.

miRNAs represent a class of highly conserved non-coding RNAs consisting of 21–22 nucleotides (nt) that are found across diverse organisms. The human genome reportedly encodes over 2000 miRNAs, which play a crucial role in intracellular regulation and can modulate the expression of multiple genes [10]. miRNAs have been established as integral components of epigenetic regulation [11, 12]. They can regulate every cellular process, and abnormal expression profiles of miRNAs are hallmarks of several diseases, including cancer [13]. The degree of complementary binding between a miRNA and its target gene determines the effect on gene expression. There are two modes of complementary binding: the first is akin to siRNA, where complete complementarity leads to the degradation of the target gene’s mRNA; the second involves incomplete complementarity, which does not affect the stability of the target gene’s mRNA but inhibits its translation. Both types of complementary interactions can occur simultaneously [14]. miRNAs are characterized by their high degree of evolutionary conservation, which enables a single miRNA to potentially target multiple genes, and conversely, allows several miRNAs to collectively regulate the same gene [15]. For instance, miR-425-5p has been identified as a biomarker for metastatic prostate cancer [16]. Furthermore, it can promote tumor growth and metastasis in colorectal cancer by activating the β-catenin pathway and facilitating epithelial-mesenchymal transition [17]. Studies have also indicated that overexpression of miR-425-5p is associated with poor prognosis and tumor progression in non-small cell lung cancer [18]. It is important to acknowledge an earlier study reporting that miR-425 (without an isoform specified) acts as a tumor suppressor in melanoma, inhibiting metastasis by repressing the PI3K-Akt pathway via targeting IGF-1 [19] This observation appears to contrast with our findings, which suggest a tumor-promoting role for the miR-425-5p isoform in malignant melanoma. This apparent discrepancy may be attributed to two factors: isoform-specific function and differential target engagement. The primary miR-425 precursor produces two mature microRNAs: miR-425-5p and miR-425-3p, which often exert distinct biological functions by targeting different mRNA transcripts. Critically, our study specifically validates the interaction between miR-425-5p and SCARA5, leading to AKT pathway activation. the contrasting roles underscore the necessity of investigating the specific mechanisms driven by the distinct miR-425 isoforms in melanoma.Therefore, identifying new early-warning biomarkers, key metastatic drivers, and developing novel targeted therapies are crucial for effectively controlling tumor progression. As highlighted by a recent comprehensive review, overcoming therapeutic resistance and understanding non-mutation-driven metastatic mechanisms (such as epigenetic regulation by miRNAs) remain key challenges in melanoma research. Although SCARA5 is considered a tumor suppressor and miR-425-5p has shown important roles in other cancers, their specific interaction and functional mechanisms in melanoma remain to be elucidated.

In cancer research, integrated multi-omics studies that encompass high-throughput omics data hold great promise for elucidating disease mechanisms, identifying diagnostic and predictive biomarkers, and uncovering signals related to disease progression and stratification. These studies incorporate various omics disciplines, including genomics, transcriptomics, proteomics, methylomics, lipidomics, and metabolomics [20]. Proteomics plays a pivotal role as an intermediary technology in systems biology during the post-genomic era. Besides, proteomics enables analysis of the composition, activity patterns, and protein-protein interactions of intracellular proteins from a holistic perspective [21]. Tandem mass tag (TMT) technology, developed by Thermo Fisher Scientific, is a relative and absolute quantitative method for in vitro isobaric labeling of polypeptides. It employs 6, 10, and 16 isotope tags to specifically label the amino groups of polypeptides. High-resolution tandem mass spectrometry enables the simultaneous comparison of protein expression levels across up to 16 samples, making it a high-throughput screening technology in quantitative proteomics [22]. In the present study, TMT proteomics technology was used to assess whether the targeted inhibition of SCARA5 by miR-425-5p promotes the proliferation and metastatic potential of malignant melanoma.

Materials and methods

Bioinformatics analysis

RNA-sequencing data and corresponding clinical information for melanoma were downloaded from the Cancer Genome Atlas (TCGA and XENA) database (https://portal.gdc.cancer.gov/). The integrated dataset used was the TCGA Skin Cutaneous Melanoma (SKCM) combined with the GTEx normal tissue data, officially identified as the TCGA_GTEx-SKCM cohort. This dataset included 469 melanoma tissues and 813 normal tissue samples. The expression levels of SCARA5 and miR-425-5p were extracted and subsequently compared between tumor and normal tissues using the Wilcoxon rank-sum test. For clinicopathological correlation, the association between gene expression and clinicopathological features such as TNM stage and pathological tumor stage (pT) was analyzed using the Chi-square test or Fisher’s exact test. Survival analysis, including Overall Survival (OS) and Disease-Free Survival (DFS), was performed using the Kaplan-Meier method, with the significance of the differences assessed with the log-rank test. A P-value < 0.05 was considered statistically significant.

Cell culture

The human malignant melanoma cell lines A375 (derived from a 54-year-old female; amelanotic; BRAF V600E mutant), A2058 (from a 43-year-old male; amelanotic; BRAF V600E mutant), and SK-MEL-1 (from a 24-year-old male; amelanotic; NRAS Q61R mutant; established at Sloan-Kettering Institute) were obtained from Pronoase (Wuhan, China). The spontaneously immortalized normal human melanocyte line PIG1 (established by Dr. Caroline Le Poole from neonatal foreskin) was acquired from Zhongqiao Xinzhou Biotechnology (Shanghai, China). All cell lines underwent authentication and were routinely tested for mycoplasma contamination. A375, A2058, and PIG1 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS; Pronoase, Wuhan, China) and 1% penicillin/streptomycin (Sigma-Aldrich, St. Louis, USA) at 37 °C in a humidified incubator with 5% CO₂. SK-MEL-1 cells were maintained in MEM supplemented with 10% FBS (Pronoase, Wuhan, China) and 1% penicillin/streptomycin (Sigma-Aldrich, St. Louis, USA) under identical culture conditions. The A375 and A2058 cell lines were selected for subsequent functional experiments due to their relatively higher endogenous expression of SCARA5 compared to SK-MEL-1 in our preliminary screening, as well as their established malignant phenotypes.

Western blot analysis

Proteins were first extracted from cells or malignant melanoma xenograft tissues obtained from nude mice, and their concentrations were measured. The samples were then subjected to electrophoresis at a constant voltage of 100 V until the dye front reached 2–3 mm from the bottom of the gel (approximately 120 min). Proteins were transferred to a membrane at 300 mA for 90 min, with adjustments made based on the molecular weight of the target proteins. After transfer, the membrane was blocked with 5% non-fat milk at room temperature for 2 h. Following blocking, primary antibodies were added and incubated with gentle shaking at room temperature for 1 h. All Western blot experiments were performed using proteins extracted from three independent biological replicates (n = 3). The primary antibodies and their details are as follows: E-Cadherin (Wuhan Sanying, 1:5000, 120 kDa, polyclonal), N-Cadherin (Wuhan Sanying, 1:2000, 130 kDa, polyclonal), ZEB1 (Wuhan Sanying, 1:500, 190 kDa, polyclonal) Beta-catenin (Wuhan Sanying, 1:5000, 92 kDa, polyclonal), Caspase-3 (Wuhan Sanying, 1:500, 32 kDa, polyclonal), Bcl-2 (Wuhan Sanying, 1:2000, 26 kDa, polyclonal), GAPDH (Abcam, 1:1000, 36 kDa, monoclonal), AKT (Wuhan Sanying, 1:5000, 56 kDa, monoclonal), P-AKT (Ser473) (Wuhan Sanying, 1:5000, 60 kDa, monoclonal), SCARA5 (Abcam, 1:1000, 50 kDa, polyclonal). After primary antibody incubation, the membrane was washed three times with PBST for 10 min each. Secondary antibodies, diluted at 1:2000, were added and incubated at room temperature for 1 h. Subsequently, the membrane was washed twice with PBST and once with PBS, each for 10 min. Finally, protein bands were visualized using ECL chemiluminescent detection reagents.

Real-time quantitative PCR (RT-qPCR)

To extract RNA, 1 mL of Trizol lysis reagent was added to frozen cells, clinical malignant melanoma tissue samples, or xenograft tissues obtained from nude mice, followed by incubation on ice for 5 min. Next, 200 µL of chloroform was added, and the mixture was vigorously shaken and left at room temperature for 3 min. After centrifugation at 10,000 g for 10 min at 4 °C, the upper aqueous phase was carefully transferred to a new RNase-free EP tube. An equal volume of isopropanol was added, mixed thoroughly, and incubated at −20 °C overnight. The next day, the sample was centrifuged at 10,000 g for 10 min at 4 °C, and the supernatant was discarded. The pellet was washed with 1 mL of 75% ethanol, mixed, and centrifuged at 3,000 g for 3 min at 4 °C. The supernatant was discarded, and the pellet was air-dried at room temperature for 10–15 min to allow the ethanol to evaporate. The pellet was then dissolved in 20 µL of nuclease-free ddH₂O, incubated at room temperature for 2 min, and stored at −80 °C.To eliminate potential genomic DNA contamination, the purified RNA was subsequently treated with DNase I (RNase-free) prior to quality assessment. RNA quality was assessed by measuring the absorbance at 260 nm and 280 nm, with an A260/A280 ratio between 1.8 and 2.0 considered acceptable. RNA concentration was determined using a Drop spectrophotometer. Primers for the target gene were designed based on the CDS region obtained from the NCBI database and synthesized by a commercial provider. The primer sequences used were: SCARA5: Forward: GCAAGGGCACAGAGGAAACCATC, Reverse: GGCATCTTCGGCATGTCCACAG, β-actin (internal control): Forward: CATGTACGTTGCTATCCAGGC, Reverse: CTCCTTAATGTCACGCACGAT, miR-425-5p: Forward: ACGGCACAATGACACGATCACT, Reverse: ATCCAGTGCAGGGTCCGAGG, U6 (internal control): Forward: CTCGCTTCGGCAGCACA, Reverse: AACGCTTCAACGAATTTGCGT. For reverse transcription of RNA into cDNA, a commercial kit was used. A reaction mixture containing RNA template, Oligo (dT)18 primers, and nuclease-free water was prepared to a final volume of 12 µL. Subsequently, 5X Reaction Buffer, RiboLock RNase inhibitor, dNTP mix, and reverse transcriptase were added to a total volume of 20 µL. The mixture was incubated at 42 °C for 1 h, followed by heat inactivation at 70 °C for 5 min. The resulting cDNA was used for subsequent PCR or stored at −80 °C. Real-time quantitative PCR was performed using the NovoStart^® SYBR qPCR SuperMix Plus kit according to the manufacturer’s instructions. The reaction mixture consisted of 25 µL of 2X Taq Master Mix, the appropriate amounts of forward and reverse primers, 2 µL of cDNA template, and ddH₂O to a total volume of 50 µL. The PCR cycling conditions were: Pre-denaturation at 94 °C for 1 min 30 s. Denaturation at 94 °C for 20 s, annealing at 57 °C for 20 s, and extension at 72 °C for 1 min, repeated for 45 cycles. Final extension at 72 °C for 5 min, followed by hold at 4 °C. Amplification Cycle threshold (Ct) values were obtained using the PCR analysis software. Relative expression levels of SCARA5 and miR-425-5p were calculated using the formula RQ = 2^−ΔΔCTRQ, with β-actin and U6 as internal controls. The results were then subjected to statistical analysis.

Transfection

For shRNA transfection to silence the SCARA5 gene, an appropriate target region within the coding DNA sequence (CDS) was selected to maximize the silencing effect, given its critical role in gene function. The shRNA sequence utilized in the pGPU6/GFP/Neo vector was: SCARA5-Homo(5’-CACCGTTCCCGAACGTGTCACGTTTCAAGAGAACGTGACACGTTCGGGAATTTTTTG-3’) and a non-coding control, SCARA5-Homo-NC (5’-GTTCTCCGAACGTGTCACGT-3’). Subsequent shRNA transfection experiments were conducted to ensure the accuracy and reliability of the experimental results, providing precise data for subsequent gene silencing analyses. Strict aseptic techniques were followed throughout the procedure to avoid cell contamination. First, target cells were cultured under appropriate conditions to the logarithmic growth phase, ensuring healthy cell status. The cells were then dissociated using trypsin and evenly seeded into a 6-well plate. When the cell confluence reached approximately 60%, transfection was carried out. After washing the cells twice with PBS, two sterile 1.5 mL EP tubes were prepared: one containing 200 µL of serum-free opi-MEM medium and 4 µL of shRNA plasmid, and the other containing 200 µL of serum-free opi-MEM medium and 5 µL of Lipofectamine transfection reagent. The total volume in each well was adjusted to 2 mL.

After gently mixing the solutions in each tube, they were left to stand for 5 min. The two solutions were then combined and incubated for an additional 20 min to form Lipofectamine-shRNA complexes. These complexes were added to the 6-well plate, and the plate was incubated in the culture chamber for 4–6 h. After this, the medium was replaced with complete medium containing serum, and cells were incubated for an additional 48 h. To evaluate the silencing efficiency of SCARA5 expression, PCR, Western blot, and other methods were used. Based on the results, the transfection conditions were optimized to achieve stable and effective shRNA-mediated gene silencing.

Screening of stable gene-edited cell lines

Cellular selection for stable transfectants was performed using appropriate selective antibiotics, chosen based on the antibiotic resistance gene present in the expression plasmid used. Common selective antibiotics include G418 and adenosine deaminase inhibitors (e.g., puromycin). In our experiment, the plasmid used was pGPU6/GFP/Neo, and after transfection, cells were subjected to positive selection using G418 at a final concentration of 500 µg/mL. The medium containing G418 was replaced every 2 days until no dead cells were visible in the supernatant. After 1–2 weeks, the cells were collected, and protein expression was assessed. The stable expression of SCARA5 was verified using methods such as Western blot and fluorescence microscopy.

CCK-8 proliferation assay

Cell proliferation was assessed using the Cell Counting Kit-8 (CCK-8) assay. Cells were divided into three experimental groups: treatment group (transfected with overexpression or silencing plasmids), control group (transfected with NC plasmid), and blank group (no treatment). After culturing the cells to the logarithmic growth phase and ensuring optimal cell condition, the cell density was adjusted to 3000 cells/100 µL and seeded into a 96-well plate. Each group included at least three replicate wells and a blank well (containing only medium). At 24-, 48-, and 72-hours post-seeding, 10 µL of CCK-8 reagent was added to each well, ensuring no air bubbles were formed. After incubation at 37 °C with 5% CO₂ for 4 h, the absorbance was measured at 450 nm using a microplate reader. Finally, GraphPad software was used to analyze the data and generate cell proliferation curves. The experiment was repeated three times to ensure the reliability of the results.

Scratch assay

Cells were divided into three groups: a treatment group, a control group, and a blank group. They were seeded into 6-well plates and cultured until a confluent monolayer was formed. A 10 µL pipette tip was used to create a scratch along a ruler, and PBS was gently used to wash away cell debris. The initial time point was recorded immediately after the scratch. At specific time points (e.g., 6 h), images were taken under a microscope to monitor the cell migration process. The width of the scratch was measured using ImageJ software, and the migration distance or percentage change was calculated. The experiment was repeated three times to ensure the reliability of the data.

Colony formation assay

Cells were divided into treatment, control, and blank groups, ensuring consistent cell numbers and experimental conditions across all groups. For cell seeding, logarithmic phase cells were digested with trypsin, resuspended, and counted to ensure equal cell numbers for each group. A total of 300 cells were seeded into a 60 mm culture dish and incubated at 37 °C with 5% CO₂ for 7 days until visible colonies formed. Following incubation, cells were washed with PBS, fixed with 4% paraformaldehyde for 30 min, and stained with crystal violet for 5 min. Excessive stain was then washed off. The number of colonies was counted under a microscope, and only colonies containing at least 50 cells were considered as countable colonies. The monolayer colony formation rate was calculated using the formula: colony number ÷ seeded cell number × 100%. The experiment was repeated three times to ensure the accuracy of the results.

Transwell invasion assay

Before the cell invasion assay, Matrigel was thawed overnight at 4 °C and diluted with a serum-free medium at a 1:8 ratio. A 60 µL aliquot of the diluted Matrigel was carefully applied to the upper chamber of the Transwell insert, ensuring an even layer without bubbles. The Matrigel was incubated for 3 h to polymerize into a thin film. After removing any excess liquid, 100 µL of serum-free medium was added, and the chamber was rehydrated for 30 min. Cells were divided into treatment, control, and blank groups. Cells were digested with trypsin, resuspended, and adjusted to a concentration of 50,000 cells per 200 µL. The cells were then seeded into the upper chamber, while the lower chamber was filled with complete medium containing serum. The 24-well plate was gently shaken to ensure even cell distribution and then incubated at 37 °C with 5% CO₂. After 24 h, non-invading cells were removed, and the remaining cells were fixed with 4% paraformaldehyde for 30 min. The cells were then stained with crystal violet for 5 min and washed three times with PBS. After air drying, five random fields were selected under a microscope for observation and cell counting. The experiment was repeated three times to ensure the consistency and reliability of the results.

Migration assay

During the experimental preparation, cells were divided into three groups: treatment, control, and blank groups. For processing and seeding, cells were digested with trypsin, resuspended, and adjusted to a concentration of 50,000 cells per 200 µL. The cells were then seeded into the upper chamber, and 800 µL of complete medium containing serum was added to the lower chamber. The 24-well plate was gently shaken using a cross-hatch method to ensure uniform distribution of the cells at the bottom of the upper chamber and then incubated at 37 °C with 5% CO₂ for continued culture. After 24 h, the plate was removed, and the medium and non-migrated cells in the upper chamber were discarded. Non-migrated cells were carefully removed from the upper chamber using sterile cotton swabs or cell scrapers. The samples were fixed with 4% paraformaldehyde at room temperature for 30 min, followed by staining with crystal violet for 5 min. The samples were washed three times with PBS. After air drying, five random fields were selected under a 10⋅ microscope for observation and cell counting. The experiment was repeated three times to ensure the consistency and reliability of the results.

Dual-luciferase reporter assay

Dual-luciferase reporter vectors containing predicted target binding sequences, including h-SCARA5-miR-425-5p MUT, h-SCARA5-miR-425-5p WT, and negative control vectors, were designed and constructed by GeneDesign. Log-phase cells were evenly seeded into a 24-well cell culture plate. After 24 h, when the cells reached 70% confluence, the dual-luciferase reporter plasmids were transfected. The experimental design included six groups: 3’UTR-NC+MicroRNA-NC, 3’UTR-NC+micro-mimics, 3’UTR-WT+MicroRNA-NC, 3’UTR-WT+micro-mimics, 3’UTR-Mu+MicroRNA-NC, and 3’UTR-Mu+MicroRNA-mimics. Before transfection, two EP tubes were prepared. One tube contained 50 µL of serum-free medium and 500 ng of plasmid, while the other contained 50 µL of serum-free medium and 1 µL of Lipofectamine 2000 transfection reagent. After mixing and incubating for 5 min, the contents of the two tubes were combined and left at room temperature for 20 min. Then, 100 µL of the mixture was added to the corresponding wells. Six hours after transfection, the medium was replaced with complete culture medium. After 24–48 h, the medium was discarded, and the cells were washed twice with PBS. Next, 80–100 µL of RIPA lysis buffer was added to each well, and the plate was shaken at 4 °C for 30 min. For luciferase activity measurement, 60 µL of Luciferase Assay Reagent II was added to a 96-well plate, and 10 µL of cell supernatant was added to each well in the dark. The luciferase reaction intensity was then measured. Subsequently, 90 µL of Stop & Glo Reagent was added to each well, and the activity of the internal control, Renilla luciferase, was measured.

Each sample was analyzed in triplicate, with the firefly luciferase to Renilla luciferase ratio (RLU1/RLU2) calculated.

TUNEL apoptosis detection

First, tumor tissues were harvested from nude mice and fixed in formalin for preservation. The fixed tissue samples were subjected to dehydration, clearing, and infiltration before being embedded in frozen sectioning medium for subsequent slicing. Using a Leica tissue slicer, the samples were cut into 7 μm-thick sections and placed onto glass slides. Next, the TUNEL reaction mixture, containing terminal deoxynucleotidyl transferase (TdT) and biotinylated dUTP (a biotin-labeled nucleotide), was applied to the tissue sections. The samples were incubated in the dark for a specified period, allowing TdT to bind to the DNA breaks and incorporate the label. After incubation, streptavidin conjugated with a fluorescent dye or an anti-biotin antibody was used to detect the dUTP-biotin labeling. Subsequently, the cell nuclei were counterstained with a fluorescent dye (such as DAPI) to observe nuclear morphology. The samples were washed to remove unbound fluorescent labels and then sealed with a mounting medium. Finally, the slides were observed under a fluorescence microscope to quantify and assess the distribution of TUNEL-positive cells, indicative of apoptosis.

Nude mouse tumorigenesis experiment

For in vivo experiments, each nude mouse was subcutaneously injected with 1 × 10⁶ tumor cells suspended in 0.2 mL of physiological saline to promote cell survival and growth, into the dorsal thoracic region. Tumor formation was typically observed within 5–7 days post-injection, often reaching the size of a mung bean or a soybean. A375 cells exhibited relatively rapid growth, and tumors were visible as early as 7 days post-injection. Tumor size was measured every 4 days using calipers to record both the longest and shortest diameters, and tumor volume was calculated using the formula: V=(a × b²)/2, where a represents the longest diameter and b is the shortest diameter. The body weight and overall health of the nude mice were also monitored. When the tumor volume reached 2000 mm³, the mice were euthanized following ethical guidelines. For euthanasia, the mice were first anesthetized with sodium pentobarbital, then euthanized by cervical dislocation. The back skin was incised, and the tumor was carefully excised using blunt dissection. After cleaning, photographing, and weighing the tumor, it was divided into two parts: one part was frozen for RNA extraction, and the other was fixed in formalin for immunohistochemical analysis. All surgical instruments were autoclaved before use to ensure the reliability and sterility of the experiment. All mouse experiments were conducted following institutional guidelines and were approved by the Committee on the Ethics of Animal Experiments of Jiangsu Medicine College (Permit Number: XMLL-2023-708). BALB/c nude mice, aged 6 weeks, were used for this study. This study utilized a total of 25 six-week-old BALB/c nude mice, which were randomly allocated into five groups: OE-SCARA5 group (injection of SCARA5-overexpressing cells), OE-SCARA5 + agmir-425-5p group (injection of agmir-425-5p after tumor formation), Control group (A375 melanoma cell injection, no treatment), Control+agmir-425-5p group (tumor formation followed by agmir-425-5p injection), and sh-SCARA5 group (injection of SCARA5-silenced cells). The entire in vivo experiment was repeated 3 times to ensure the reliability of the results.

Mass spectrometry experimental method

Tumor tissues obtained from the nude mouse experiment were subjected to TMT-based proteomics analysis. Three experimental groups, each with three biological replicates per group (n = 3), were selected: (1) the Control group, (2) the Control+agmir-425-5p group, and (3) the OE-SCARA5 + agmir-425-5p group. The tissues were lysed using SDT lysis buffer (4% SDS, 100 mM Tris/HCl pH 7.6, 0.1 M DTT), and protein quantification was performed using the BCA method. After quantification, an appropriate amount of protein was digested using the Filter Aided Proteome Preparation (FASP) method, and the resulting peptides were desalted using C18 cartridges. After lyophilization, the peptides were dissolved in 40 µL of 0.1% formic acid for quantification (OD280). Next, 100 µg of peptides per sample were labeled according to the Thermo TMT labeling kit protocol, for each of the three experimental groups (OE-a425-5p, con-a425-5p, and con). After labeling, the peptides were fractionated using the High pH Reversed-Phase Peptide Fractionation Kit. The C18 columns were equilibrated with acetonitrile and 0.1% trifluoroacetic acid (TFA), and the peptides were desalted by low-speed centrifugation. A gradient elution was performed using increasing concentrations of high-pH acetonitrile solution. After elution, the peptides were dissolved in 0.1% formic acid (FA) and lyophilized, followed by peptide concentration measurement (OD280). Besides, peptides were fractionated using SCX chromatography and AKTA Purifier 100, with specific buffers used for chromatographic separation. The LC-MS/MS analysis was conducted using an HPLC system (Easy nLC) with a nano flow rate. The peptides were separated using 0.1% formic acid in water and acetonitrile as mobile phases, with a flow rate of 300 nL/min. The samples were then analyzed using a Q-Exactive mass spectrometer.

Protein clustering analysis

Quantitative information of target protein sets was normalized, and hierarchical clustering heatmaps of protein expression levels in the samples were generated using the ComplexHeatmap R package.

Subcellular localization analysis

The CELLO method was used to predict the subcellular localization. Protein sequence data with known subcellular localization information from public databases were used for modeling, and the subcellular localization of the target proteins was predicted.

Protein domain analysis

The Pfam database and the InterProScan software package were used to perform domain analysis of the target protein sequences and to obtain domain annotation information.

GO annotation

Blast2GO was used for GO annotation, including sequence alignment, GO term extraction, GO annotation, and supplementary annotation from InterProScan.

KEGG pathway annotation

KEGG pathway annotations of the target protein set were performed using the KEGG Automatic Annotation Server (KAAS).

Enrichment analysis

Enrichment analysis was conducted using Fisher’s exact test to compare the distribution of various GO categories, KEGG pathways, or domains in the target protein set and the overall protein set.

Statistical analysis

In this study, data processing and analysis were performed using SPSS version 25.0 and GraphPad Prism 8 statistical software. Each experiment was independently repeated at least three times, and the results are expressed as the mean ± standard deviation (SD). Prior to all parametric tests, the normality of data distribution was assessed using the Shapiro-Wilk test, and the homogeneity of variances (homoscedasticity) was assessed using Levene’s test. For continuous variables, the T-test or Mann-Whitney U test was used for analysis, while for categorical variables, we applied the Chi-square test or Fisher’s exact test. For comparisons among multiple groups (e.g., Western blot grayscale quantification), one-way ANOVA was used, followed by Tukey’s post-hoc test for multiple comparison correction.For data involving two independent variables (e.g., cell proliferation curves over time in the CCK-8 assay), two-way ANOVA was utilized, followed by Tukey’s post-hoc test for pairwise comparisons. Besides, Pearson correlation coefficient analysis was used to evaluate the correlation between the two variables. The significance level was set at α = 0.05 (two-tailed), and P-values less than 0.05 were considered statistically significant, marked as * (P < 0.05), ** (P < 0.01), *** (P < 0.001).

Results

Expression of SCARA5 in normal and malignant melanoma cell lines

Analysis of TCGA data revealed that SCARA5 expression was significantly lower in malignant melanoma tissues compared to adjacent normal tissues (Fig. 1A). Besides, low SCARA5 expression was associated with poor prognosis, while high SCARA5 expression correlated with better prognosis (Fig. 1B). Western blot and RT-PCR assays were performed to detect SCARA5 protein and mRNA expression in several melanoma cell lines, including A375, A2058, SK-MEL-1, and PIG1. SCARA5 expression was found to be highest in the normal melanocyte cell line PIG1. Among the malignant melanoma cell lines, SCARA5 expression decreased in the following order: A375 > A2058 > SK-MEL-1, suggesting a potential role for SCARA5 as a tumor suppressor gene in malignant melanoma progression (Fig. 1C-D). Fluorescence microscopy experiments demonstrated that SCARA5 was widely distributed in A375 and A2058 cells. Consistent with reports suggesting dual functionality, while its presence was detected in multiple subcellular regions, the protein accumulated predominantly in the cytoplasm in these malignant melanoma lines (Fig. 1E).

Fig. 1.

SCARA5 Expression is Downregulated in Melanoma and Correlated with Prognosis. (A) SCARA5 mRNA in melanoma tissues (n=146) compared to normal tissues (n=27]) from TCGA. Data were analyzed using the Wilcoxon rank-sum test. (B) Higher SCARA5 expression correlated with improved overall survival (OS) in patients with malignant melanoma. (C,D) Western blot and RT-PCR assays conducted to measure SCARA5 protein and mRNA expression in various melanoma cell lines. (E) Immunofluorescence analysis showed the subcellular localization of SCARA5 in A375 and A2058 cells.

SCARA5 acts as a tumor suppressor, inhibiting malignant melanoma proliferation, migration, invasion, and promoting apoptosis

This section of the study explored the functional role of SCARA5 in malignant melanoma cells (A375 and A2058) through gene silencing and overexpression experiments. The results confirmed that SCARA5 exerts a tumor-suppressive effect. Western blot experiments confirmed that the expression of SCARA5 in the sh-SCARA5 group was significantly reduced compared to the control groups (sh-NC and Control). In the SCARA5 silenced group, the expression of the anti-apoptotic protein Bcl-2 was significantly increased, while the expression of the pro-apoptotic protein caspase-3 was significantly decreased, suggesting that silencing SCARA5 inhibited cell apoptosis (Fig. 2A). CCK-8 proliferation and colony formation assays both showed that silencing SCARA5 significantly increased the proliferation rate and colony formation ability of A375 and A2058 cells (P < 0.05) (Fig. 2B). Scratch wound healing and Transwell invasion assays, along with colony formation results, indicated that silencing SCARA5 significantly enhanced the migration and invasion abilities of A375 and A2058 cells (P < 0.05) (Fig. 2C-E). Western blot experiments confirmed that the expression of SCARA5 in the OE-SCARA5 group was significantly higher than in the control groups (OE-NC and Control). In the SCARA5 overexpression group, the expression of the anti-apoptotic protein Bcl-2 was significantly decreased, while the expression of the pro-apoptotic protein caspase-3 was significantly increased, suggesting that overexpressing SCARA5 promotes cell apoptosis (Fig. 3A). CCK-8 proliferation and colony formation assays both showed that overexpressing SCARA5 significantly reduced the proliferation rate and colony formation ability of A375 and A2058 cells (P < 0.05) (Fig. 3B). Scratch wound healing and Transwell invasion assays, along with colony formation results, indicated that overexpressing SCARA5 significantly reduced the migration and invasion abilities of A375 and A2058 cells (P < 0.05) (Fig. 3C-E). In conclusion, the expression level of SCARA5 is negatively correlated with the malignant phenotype of melanoma cells, suggesting that SCARA5 plays a crucial tumor-suppressive role in malignant melanoma.

Fig. 2.

Silencing SCARA5 in MM Cell Lines. (A) Western blot analysis indicated that silencing SCARA5 inhibited apoptosis in A375 and A2058 cells. (B) CCK8 assays revealed significantly enhanced cell proliferation in the sh-SCARA5 group compared to controls. (C) Clonogenic assays showed that silencing SCARA5 significantly promoted clonogenic growth in both cell lines. (D) Scratch wound assays demonstrated that silencing SCARA5 significantly increased the migration ability of A375 and A2058 cells. (E) Transwell invasion assays revealed that silencing SCARA5 markedly enhanced the invasion capacity of both A375 and A2058 cells. Data are presented as mean ± SD from three independent experiments. Statistical significance was determined by one-way ANOVA with Tukey's post-hoc test. *P < 0.05, **P < 0.01, ***P < 0.001.

Fig. 3.

Overexpression of SCARA5 in MM Cell Lines. (A) Western blot analysis showed that SCARA5 overexpression enhanced apoptosis in A375 and A2058 cells. (B) CCK8 assays indicated that SCARA5 overexpression significantly reduced cell proliferation in both cell lines. (C) Clonogenic assays suggested that SCARA5 overexpression significantly inhibited clonogenic growth in both A375 and A2058 cells. (D) Scratch wound assays revealed that SCARA5 overexpression significantly decreased the migration ability of A375 and A2058 cells. (E) Transwell invasion assays showed that SCARA5 overexpression significantly reduced the invasion capacity of both A375 and A2058 cells. **Data are presented as mean ± SD from three independent experiments. Statistical significance was determined by one-way ANOVA with Tukey's post-hoc test. *P < 0.05, **P < 0.01, *P < 0.001.

Changes in protein expression related to EMT and AKT pathways after SCARA5 silencing and overexpression

After silencing SCARA5, cells were divided into three groups: sh-SCARA5, sh-NC, and Control. Western blot analysis was used to measure the expression levels of EMT-related proteins (E-cadherin, N-cadherin, β-catenin, ZEB1), p-AKT, and AKT. As shown in Fig. 4A, compared to the sh-NC and Control groups, the sh-SCARA5 group exhibited a significant increase in the phosphorylation of AKT, along with elevated expression of mesenchymal markers N-cadherin, β-catenin, and ZEB1, while the epithelial marker E-cadherin was notably downregulated. These results indicated that silencing SCARA5 could promote AKT phosphorylation and the epithelial-to-mesenchymal transition (EMT) process in malignant melanoma cells. To assess the impact of SCARA5 overexpression, cells were divided into three groups: OE-SCARA5, OE-NC, and Control. Western blot analysis was used to assess the expression levels of EMT markers (E-cadherin, N-cadherin, β-catenin, ZEB1), p-AKT, and AKT. As shown in Fig. 4B, compared to the OE-NC and Control groups, the OE-SCARA5 group displayed significantly reduced AKT phosphorylation, with a decrease in mesenchymal markers N-cadherin, β-catenin, and ZEB1, and a marked increase in the epithelial marker E-cadherin. These results collectively suggest that overexpression of SCARA5 inhibits AKT phosphorylation and the EMT process in malignant melanoma cells.

Fig. 4.

Effects of SCARA5 Silencing or Overexpression on EMT and AKT Pathways in MM Cell Lines. (A) Compared to the sh-NC and Control groups, silencing SCARA5 (sh-SCARA5) led to a significant increase in AKT phosphorylation, accompanied by elevated expression of mesenchymal markers N-cadherin, β-catenin, and ZEB1, while the epithelial marker E-cadherin was notably downregulated. (B) SCARA5 overexpression (OE-SCARA5) significantly reduced AKT phosphorylation, decreased mesenchymal markers N-cadherin, β-catenin, and ZEB1, and increased the expression of the epithelial marker E-cadherin. Representative blots from three independent experiments are shown.

SCARA5 is negatively regulated by miR-425-5p, and miR-425-5p expression is upregulated in MM tissues and cell lines

Bioinformatics prediction using the miRWALK tool (http://mirwalk.umm.uni-heidelberg.de/) identified a complementary binding site for miR-425-5p in the 3’ UTR region of the SCARA5 gene. To further investigate this interaction, we commissioned Shanghai Jima Biotechnology to construct wild-type and mutant dual-luciferase reporter vectors containing the predicted target binding sequences (Fig. 5A), namely h-SCARA5-miR-425-5p MUT and h-SCARA5-miR-425-5p WT. In A375 and A2058 cell lines, the 3’UTR-WT, 3’UTR-Mu, and 3’UTR-NC plasmids were co-transfected with miR-425-5p mimics or mimic-NC. After 24 h, luciferase activity was measured. The results showed that miR-425-5p significantly inhibited the fluorescence activity of the wild-type reporter (P < 0.05) but yielded no effect on the mutant reporter. These findings collectively provide direct evidence that miR-425-5p can bind to the 3’UTR region of SCARA5 and regulate its expression (Fig. 5B). TCGA data analysis of miR-425-5p expression across 33 cancer types (ACC, BLCA, BRCA, CESC, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KICH, KIRC, KIRP, LAML, LGG, LIHC, LUAD, LUSC, MESO, OV, PAAD, PCPG, PRAD, READ, SARC, MM, STAD, TGCT, THCA, THYM, UCEC, UCS, UVM) revealed miR-425-5p overexpression in most cancer types (Fig. 5C). RT-PCR analysis confirmed that miR-425-5p expression was significantly higher in malignant melanoma tissues compared to normal tissues. Moreover, the expression of miR-425-5p in A375 and A2058 cell lines was notably higher than in melanocytes (PIG1) (Fig. 5D-E).

Fig. 5.

Expression of miR-425-5P in Tumors and Its Complementary Binding Site with SCARA5. (A) miRWALK predicted the target binding and binding map at the Gemma site. (B) miR-425-5p significantly inhibited the fluorescence activity of the wild-type vector. (C) Expression of miR-425-5p across various pan-cancer tumor tissues in the TCGA database. (D) Expression of miR-425-5p in cutaneous malignant melanoma tissues. (E) Expression of miR-425-5p in malignant melanoma cell lines.

Next, the correlation between the expression level of miR-425-5p and clinical data from 60 malignant melanoma patients was analyzed using SPSS to further explore its clinical significance in melanoma. The results (Table 1) showed that the expression level of miR-425-5p was not associated with patient age (P = 0.919), gender (P = 0.438), presence of ulcers (P = 0.451), or tumor location (P = 0.611). However, analysis of the correlation between TNM staging and miR-425-5p revealed that higher TNM stages were associated with higher miR-425-5p expression levels, indicating that high miR-425-5p expression was related to advanced TNM staging in malignant melanoma (P = 0.044).

Table 1.

Association of miR-425-5p Expression and Clinicopathological Features in Melanoma

Clinical pathological feature	n	miR-425-5P		X2	P
		Low expression(n = 29)	High expression(n = 31)
Gender  Male  Female	30 30	16 13	14 17	0.601	0.438
Age (years)  ≤ 60  >60	19 41	9 20	10 21	0.010	0.919
Ulcer  No  Yes	46 14	21 8	25 6	0.568	0.451
Tumor Location  Head and Neck  Trunk  Limbs	6 14 40	4 6 19	2 8 21	0.987	0.611
TNM Stage  I, II  III, IV	40 20	23 6	17 14	4.038	0.044*

#:Chi-square test; *P < 0.05

miR-425-5p modulates SCARA5 expression to drive proliferation, metastasis, and inhibit apoptosis via the AKT and EMT pathways

This study systematically evaluated the impact of miR-425-5p mimics and inhibitors on the malignant phenotype of malignant melanoma (MM) cells and its molecular mechanism, including SCARA5-mediated rescue experiments. miR-425-5p negatively regulates SCARA5 expression and promotes the malignant phenotype of cells. Western blot analysis showed a negative regulatory relationship between miR-425-5p and SCARA5. Compared to the control group, the SCARA5 protein level was significantly elevated in the miR-425-5p inhibitor group, while it was significantly reduced in the miR-425-5p mimic group (P < 0.05) (Fig. 6A). CCK-8 proliferation and colony formation assays revealed that the miR-425-5p inhibitor significantly reduced the proliferation and colony formation abilities of A375 and A2058 cells (P < 0.05) (Fig. 6B and C). In contrast, the miR-425-5p mimic group showed significantly enhanced cell proliferation and colony formation abilities (P < 0.05). Scratch wound healing and Transwell invasion assays consistently showed that the cell migration and invasion abilities were significantly weakened in the miR-425-5p inhibitor group, while they were significantly enhanced in the miR-425-5p mimic group (P < 0.05) (Fig. 6D and E-F). These results collectively suggest that miR-425-5p promotes the proliferation, invasion, and migration of A375 and A2058 melanoma cells by inhibiting SCARA5 expression. We further explored the molecular mechanisms behind miR-425-5p regulation of the malignant phenotype. In the miR-425-5p mimic group, the expression of the anti-apoptotic protein Bcl-2 was significantly increased, while the expression of the pro-apoptotic protein caspase-3 was significantly decreased (P < 0.05). In contrast, the miR-425-5p inhibitor group showed a decrease in Bcl-2 expression and an increase in caspase-3 expression (Fig. 7A). These results indicate that upregulation of miR-425-5p inhibits melanoma cell apoptosis. In the miR-425-5p mimic group, mesenchymal markers N-cadherin, beta-catenin, and ZEB1 were significantly increased, while the epithelial marker E-cadherin was significantly decreased (P < 0.05). In contrast, the miR-425-5p inhibitor group showed reduced expression of N-cadherin, beta-catenin, and ZEB1, while E-cadherin expression was significantly increased (Fig. 7B). This suggests that upregulation of miR-425-5p promotes the epithelial-mesenchymal transition (EMT) process. After transfection with miR-425-5p inhibitor, there was no significant change in the total AKT protein expression, but the phosphorylation level of AKT decreased. Similarly, after transfection with miR-425-5p mimics, there was no significant change in total AKT protein expression, but the phosphorylation level of AKT increased. To verify that miR-425-5p regulates apoptosis, EMT, and AKT phosphorylation through SCARA5, we conducted rescue experiments. Transfection of miR-425-5p mimics into a cell line stably overexpressing SCARA5 partially inhibited p-AKT expression. In contrast, transfection of miR-425-5p inhibitors into cells stably transfected with sh-SCARA5 reversed the changes in p-AKT expression levels (Fig. 7C).

Fig. 6.

Changes of MM Cells After Transfection with miR-425-5p Inhibitor and miR-425-5p Mimic. (A) Silencing miR-425-5p promoted SCARA5 expression, while overexpression of miR-425-5p inhibited SCARA5 expression in A375 and A2058 cells. (B) CCK8 assays showed that miR-425-5p promoted cell proliferation in A375 and A2058 cells. (C) Clonogenic assays confirmed that miR-425-5p enhanced cell proliferation in A375 and A2058 cells. (D) Scratch assays demonstrated that miR-425-5p promoted cell migration in A375 and A2058 cells. (E-F) Transwell assays showed that miR-425-5p significantly affected both the invasion and migration abilities of A375 and A2058 cells. **Data are presented as mean ± SD from three independent experiments. Statistical significance was determined by one-way ANOVA with Tukey's post-hoc test. *P < 0.05, **P < 0.01, *P < 0.001.

Fig. 7.

Effects of miR-425-5p Inhibition and Overexpression on EMT and AKT Pathways in MM Cell Lines. (A) Western blot analysis confirmed that miR-425-5p regulated apoptosis in A375 and A2058 cells. (B) Western blot analysis revealed that miR-425-5p regulated the EMT process in both cell lines. (C) miR-425-5p regulated AKT phosphorylation levels in both A375 and A2058 cells. Representative blots from three independent experiments are shown.

In vivo validation of miR-425-5p-mediated SCARA5 targeting: impact on tumor growth and apoptosis

The results indicated that all nude mice injected with A375 melanoma cells successfully developed tumors without localized signs of inflammation or rupture, with tumor growth typically observed approximately 7 days after injection. The OE-SCARA5 + agmir-425-5p and Control+agmir-425-5p groups started receiving agmir-425-5p injections two weeks after tumor formation. The injections were administered at a dose of 1 nmol every three days for a total of two weeks. After the injections were stopped, the tumor growth rate in the sh-SCARA5 group was significantly faster than in the Control group, and the growth rate in the OE-SCARA5 group was slower (all P < 0.05). The tumor growth rate in the OE-SCARA5 + agmir-425-5p group increased significantly, while the Control+agmir-425-5p group also showed a marked increase in tumor growth after agmir-425-5p intervention (all P < 0.05) (Fig. 8A). After 42 days of subcutaneous inoculation (or when tumor volume reached 2000 mm³), the nude mice were euthanized, and the tumors were excised for measurement and weighing. The average tumor weights in each group were as follows: OE-SCARA5 group: 490.4 mg, Control group: 1044.6 mg, sh-SCARA5 group: 1865 mg, OE-SCARA5 + agmir-425-5p group: 1104.2 mg, and Control+agmir-425-5p group: 1920 mg. Compared with the Control group, the tumor weight in the OE-SCARA5 group was significantly reduced, while the tumor weight in the sh-SCARA5 group was significantly increased (all P < 0.05). In comparison with the OE-SCARA5 group, the tumor weight in the OE-SCARA5 + agmir-425-5p group increased significantly (P < 0.05), and similarly, the tumor weight in the Control+agmir-425-5p group was significantly increased (P < 0.05). However, there were no significant differences in tumor weight between the OE-SCARA5 + agmir-425-5p group and the Control group, nor between the sh-SCARA5 group and the Control+agmir-425-5p group (all P > 0.05). These results suggest that SCARA5 may inhibit the early formation and rapid proliferation of melanoma tumors, while agmir-425-5p may promote tumor growth. The TUNEL assay was next used to detect cell apoptosis. The results showed that the OE-SCARA5 group exhibited the highest level of apoptosis, followed by the OE-SCARA5 + agmir-425-5p group, and then the Control group. The Control+agmir-425-5p group and the sh-SCARA5 group exhibited the lowest levels of apoptosis. Importantly, there was no significant difference in apoptosis between the OE-SCARA5 + agmir-425-5p group and the Control group, nor between the Control+agmir-425-5p group and the sh-SCARA5 group (Fig. 8B). These findings indicate that SCARA5 promotes apoptosis in melanoma in vivo, while agmir-425-5p suppresses melanoma cell apoptosis.

Fig. 8.

Tumor Formation Experiment in Nude Mice and TUNEL Apoptosis Analysis. (A) Comparison of tumor volume and weight between the different groups in nude mice. (B) TUNEL staining was used to assess tumor apoptosis in nude mice. **Data are presented as mean ± SD (n=5 per group). Statistical significance for tumor volume and weight was determined by one-way ANOVA with Tukey's post-hoc test. *P < 0.05, **P < 0.01, *P < 0.001.

Proteomics identifies potential mechanistic pathways

In this study, TMT-based proteomics was employed to analyze the differential expression of proteins (Fig. 9A). A total of 692,119 spectra were generated, with 105,751 matched spectra, 44,551 peptides, and 39,927 unique peptides identified. From these, 6,400 proteins were identified, with 6,399 proteins successfully quantified. Differential expression analysis revealed 896 differential proteins (277 upregulated and 619 downregulated) between the Control + agmir-425-5p and Control groups and 368 differential proteins (213 upregulated and 155 downregulated) between the OE-SCARA5 + agmir-425-5p and Control + agmir-425-5p groups (Fig. 9B). A pie chart was generated to illustrate the distribution and quantity of proteins in subcellular organelles across the three groups (Fig. 9C). Hierarchical clustering of differentially expressed proteins in the OE-a425-5p vs. Control, Control-a425-5p vs. Control, and OE-a425-5p vs. Control-a425-5p groups was performed, and the results are displayed in a heatmap. The data within each group showed high similarity, while between-group patterns were distinct, effectively distinguishing the groups. Notably, the significantly differentially expressed proteins (FC > 1.2 and P < 0.05) exhibited a clear separation in the heatmap, confirming the effectiveness of the algorithm. Blue represents significantly downregulated proteins, while red represents upregulated proteins (Fig. 9D). A volcano plot was also generated to visualize the significance of protein differences between groups. Blue indicates significantly downregulated proteins (FC < 0.83 and P < 0.05), red represents upregulated proteins (FC > 1.2 and P < 0.05), and gray represents non-significant proteins (Fig. 9E). InterProScan was used to predict the domains of the differentially expressed proteins, and the top 20 protein domains in the OE-a425-5p vs. Control, Control-a425-5p vs. Control, and OE-a425-5p vs. Control-a425-5p groups were listed (Fig. 9F). Blast2Go was used for GO annotation and statistical analysis of the differentially expressed proteins in the three groups (Fig. 9G). KEGG pathway analysis was utilized to annotate and analyze the differential proteins. The pathways most significantly enriched in the three groups were the Ribosome, PI3K-Akt signaling pathway, Protein digestion and absorption, Focal adhesion, and ECM-receptor interaction, which aligned with our prior molecular validation of AKT signaling. We also examined upregulated and downregulated pathways and observed significant suppression of PPAR pathway activity in Control-a425-5p vs. Control (Fig. 9H). To validate these proteomics findings and confirm the pathway regulation in vivo, Western Blot analysis was conducted using protein extracts from the xenograft tumor tissues to examine the expression of SCARA5 and PPAR-γ pathway proteins. The results indicated that the OE-SCARA5 group showed the highest expression of SCARA5 and PPAR-γ (P < 0.05), followed by the OE-SCARA5 + agmir-98-5P group and the Control group. The expression of SCARA5 was the lowest in the sh-SCARA5 group (P < 0.05). However, there was no significant difference in SCARA5 expression between the OE-SCARA5 + agmir-98-5P group and the Control group, nor between the Control+agmir-98-5P group and the sh-SCARA5 group (P > 0.05) (Fig. 9I).

Fig. 9.

Proteomics Analysis of Potential Mechanisms. (A) Statistical overview of the spectra, peptides, and proteins identified through TMT proteomics. (B) Statistical map of differentially expressed proteins. (C) Subcellular localization of differentially expressed proteins was analyzed using CELLO software. (D) Differentially expressed proteins were grouped and classified. (E) Volcano plot illustrating significant differences in protein expression between groups. (F) Fisher's exact test was applied for domain enrichment analysis of differentially expressed proteins in each group. (G) Differentially expressed proteins were annotated and counted using Blast2Go software. (H) KEGG pathway analysis revealed that treatment with an agomir for miR-425-5p significantly suppressed the PPAR pathway compared to the control group. (I) Western blot validation of PPAR-γ expression changes in tumor tissues from the five experimental groups. **Data for the bar graph are presented as mean ± SD (n=3 per group). Statistical significance was determined by one-way ANOVA with Tukey's post-hoc test. *P < 0.05, **P < 0.01, *P < 0.001.

Discussion

Despite significant progress in targeted therapy and immunotherapy, addressing therapeutic resistance remains a core challenge in the current treatment of malignant melanoma. As emphasized by a recent comprehensive review in the field, elucidating the molecular pathways that drive tumor progression and resistance is crucial [23]. The results of our study provide new insights into this area by demonstrating that miR-425-5p activates the AKT signaling pathway and promotes the EMT process by targeting SCARA5. This new regulatory axis offers a deeper understanding of melanoma invasion and metastasis, suggesting its potential as a key factor contributing to malignant progression and a promising new therapeutic target. Malignant melanoma typically appears on the skin surface but can also affect mucosal areas [24]. Compared to other skin cancers, malignant melanoma poses a significantly higher threat due to its ability to rapidly spread and metastasize to other organs [25]. Staging is critical in the diagnosis of malignant melanoma as it helps determine the severity of the disease. While early-stage melanomas typically exhibit a high cure rate, the survival rate of patients with late-stage disease is significantly poorer [3]. Therefore, early detection and timely treatment are essential for improving patient survival. Current treatment strategies for malignant melanoma include surgical resection, radiotherapy, chemotherapy, immunotherapy, and targeted therapy, with targeted therapy emerging as a promising research focus in melanoma treatment [26, 27].

Over the past few years, targeted therapy has made significant progress in the treatment of malignant melanoma. Approximately 50% of melanoma patients harbor BRAF gene mutations, which play a key role in the development of melanoma [28]. Drugs such as Vemurafenib and Dabrafenib can reportedly inhibit the abnormal signaling caused by BRAF mutations, effectively suppressing the proliferation of melanoma cells. To enhance treatment efficacy, BRAF inhibitors are often combined with MEK inhibitors (such as Trametinib) to slow cell growth and reduce resistance to BRAF inhibitors [29]. In addition to directly targeting tumor cell growth signals, immune checkpoint inhibitors (such as PD-1 and CTLA-4 inhibitors) are also used to treat malignant melanoma [30]. These drugs activate the immune system, enhancing the body’s immune response to tumors. Despite the success of targeted therapies in a subset of patients, acquired resistance remains a significant challenge. Therefore, there is an ongoing search for new targets and treatment strategies to provide effective treatment options for this patient population.

SCARA5, a member of the scavenger receptor class A family, plays a crucial role in cellular immunity, regulating inflammation, and clearing cellular and extracellular environments, suggesting a specialized role in fundamental cellular biological processes [31]. Our investigation validated SCARA5 expression in three malignant melanoma cell lines (A375, A2058, SK-MEL-1) and one normal human melanocyte cell line (PIG1), revealing that SCARA5 expression was significantly higher in PIG1 than in the melanoma cells. By knocking down and overexpressing SCARA5 in A375 and A2058 cells, we found SCARA5 involvement in various biological processes in melanoma cells, including proliferation, migration, and invasion. Knocking down SCARA5 significantly enhanced melanoma cell proliferation, migration, and invasion, whereas overexpressing SCARA5 led to a marked reduction in these abilities. These findings collectively suggest that SCARA5 may play an important role in regulating cell proliferation, migration, and invasion in malignant melanoma. Further studies could provide deeper insights into the molecular mechanisms of SCARA5 and its specific role in melanoma progression, offering new clues for the development of related therapeutic strategies.

Apoptosis represents a precisely controlled cell death mechanism that plays a crucial role in tissue homeostasis, immune regulation, and developmental morphogenesis [32]. However, in certain malignancies, particularly in malignant melanoma, the regulation of apoptosis may become disrupted, allowing cancer cells to evade normal cell death mechanisms. A hallmark of malignant melanoma is its resistance to apoptosis. Cancer cells can alter apoptotic pathways through various mechanisms, including genetic mutations and epigenetic changes, thereby enabling them to evade normal cell death [33]. The Bcl-2 family of proteins plays a pivotal role in regulating apoptosis. In malignant melanoma, abnormal expression of Bcl-2 family proteins can lead to resistance to apoptosis. This abnormal expression may be caused by genetic mutations or other regulatory mechanisms [34]. Caspase-3, a member of the cysteine-aspartic protease family, is also crucial in the apoptosis process. Caspase-3 is considered one of the most important executioners of apoptosis, and its activation is essential for the execution phase of cell death. Malignant melanoma cells are widely believed to enhance their survival by activating anti-apoptotic signaling pathways, such as the PI3K/Akt and MAPK pathways, thereby slowing or blocking apoptosis. The overactivation of these pathways in melanoma is closely associated with the cancer cells’ resistance to apoptosis [35]. Understanding the mechanisms behind melanoma’s resistance to apoptosis is critical for developing more effective treatment strategies. A deeper understanding of these mechanisms will help identify targeted drugs and therapeutic approaches to reinstate apoptosis in cancer cells, thereby effectively suppressing tumor growth. In the present study, Western Blot was conducted to evaluate the expression of Caspase-3 and Bcl-2 in A375 and A2058 cells after SCARA5 knockdown and overexpression. We observed a significant decrease in Caspase-3 expression after SCARA5 knockdown, suggesting that SCARA5 knockdown may lead to a negative regulation of Caspase-3, which is a key apoptosis executor. Caspase-3 downregulation could reflect an increased resistance to apoptosis, thereby promoting cell survival. Besides, Bcl-2 expression was significantly elevated after SCARA5 knockdown. Bcl-2 is an anti-apoptotic protein, and its upregulation likely indicates the activation of anti-apoptotic signaling pathways due to SCARA5 downregulation, thereby maintaining cell survival. Conversely, after SCARA5 overexpression, Caspase-3 expression was significantly upregulated, and Bcl-2 expression decreased markedly. These results suggest that SCARA5 plays a significant role in regulating apoptosis, and its expression levels may directly influence cell survival and apoptosis. Overall, these findings provide important clues for understanding SCARA5’s role in melanoma and its involvement in regulating apoptotic pathways.

EMT represents a crucial process in cancer cell invasion and migration, characterized by a morphological shift from epithelial cells with a cobblestone-like appearance to elongated, spindle-shaped fibroblast-like cells [36]. EMT enhances cell motility and invasiveness, enabling cells to cross the basement membrane and invade surrounding tissues. Typical markers of EMT include E-cadherin, N-cadherin, β-catenin, and ZEB1. E-cadherin, a hallmark epithelial marker, is typically downregulated during EMT, leading to diminished cell-cell adhesion and promoting the transition from epithelial to mesenchymal states. Loss of E-cadherin is a key factor in EMT, occurring in several cancer types, including lung, breast, colon, and ovarian cancers [37]. Conversely, N-cadherin, which replaces E-cadherin during EMT, is now understood to upregulate cell adhesion and facilitate mesenchymal transition [38]. β-catenin is a crucial cell adhesion molecule involved in EMT, and its redistribution is associated with the downregulation of E-cadherin. ZEB1, a transcription factor, is considered a major regulator of EMT and promotes mesenchymal transformation by repressing epithelial markers [39]. In malignant melanoma, EMT is closely associated with tumor invasion and metastasis, enabling melanoma cells to acquire enhanced migratory and invasive abilities, enabling them to penetrate the basement membrane, penetrate blood vessel walls, and ultimately colonize distant sites [40]. The Wnt and PI3K/Akt signaling pathways have also been implicated in the regulation of EMT in melanoma [41, 42]. The activation of these pathways may induce morphological and functional changes in melanoma cells, further enhancing their invasiveness and metastatic potential. Our Western Blot experiments revealed that E-cadherin expression significantly decreased following SCARA5 knockdown, while N-cadherin, β-catenin, and ZEB1 levels significantly increased. Conversely, after SCARA5 overexpression, E-cadherin expression significantly increased, while N-cadherin, β-catenin, and ZEB1 expression markedly decreased. These results suggest that SCARA5 yields a positive regulatory effect in inhibiting EMT, thereby potentially limiting the invasive and metastatic abilities of melanoma cells.

Our study findings demonstrated that SCARA5 could inhibit the proliferation, invasion, and migration of malignant melanoma cells. To further investigate the underlying mechanisms, bioinformatics approaches were employed to search for upstream miRNAs that may target SCARA5 in the TargetScan and miWALK databases. The results predicted that miR-425-5p could potentially bind to SCARA5. miR-425-5p has been reported to participate in the tumorigenesis of various cancers. In gastric cancer, miR-425-5p is reportedly overexpressed in tumor tissues, and its high expression is associated with tumor invasion depth and TNM stage, making it a marker for poor prognosis [43, 44]. In breast cancer, miR-425-5p is also upregulated and linked to poor prognosis. Overexpression of miR-425-5p significantly promotes breast cancer cell growth and affects the cell cycle progression of these cells [45]. In colorectal cancer, miR-425-5p overexpression correlates with the chemotherapeutic sensitivity of CRC cells to 5-fluorouracil and oxaliplatin, an effect mediated by miR-425-5p’s regulation of PDCD10 protein [46]. In lung cancer, miR-425-5p enhances cell proliferation and inhibits apoptosis via the PTEN/PI3K/AKT signaling pathway [47]. These studies overlap in their assertion that miR-425-5p represents a potential therapeutic target in various cancers. Notably, despite significant research supporting its role in other cancers, the specific mechanism of miR-425-5p in malignant melanoma remains unclear, even with its documented high expression [48]. In the present study, the binding site between miR-425-5p and SCARA5 was validated using dual-luciferase reporter assays. Furthermore, through a series of experiments, including cell invasion, migration, cloning, CCK8, and wound healing assays, the miR-425-5p mimic not only inhibited SCARA5 protein expression but also promoted the proliferation, invasion, and migration of melanoma cells. Conversely, transfection with miR-425-5p inhibitor led to an increase in SCARA5 expression and inhibited melanoma cell proliferation, invasion, and migration. These results confirmed that miR-425-5p directly targets SCARA5, suggesting a negative regulatory relationship between miR-425-5p and SCARA5, which promotes melanoma progression. We also examined the expression of apoptosis and EMT-related proteins in A375 and A2058 cells transfected with miR-425-5p mimic and inhibitor via Western blot. The results indicated that upregulation of miR-425-5p suppressed melanoma cell apoptosis, while downregulation of miR-425-5p promoted apoptosis. Moreover, upregulation of miR-425-5p led to a significant decrease in E-cadherin expression, along with an increase in N-cadherin, β-catenin, and ZEB1 expression. In contrast, downregulation of miR-425-5p resulted in increased E-cadherin expression and decreased N-cadherin, β-catenin, and ZEB1 expression. These findings suggest that the upregulation of miR-425-5p may inhibit apoptosis in melanoma cells, thereby promoting the EMT process. Conversely, the downregulation of miR-425-5p may help promote apoptosis and inhibit EMT, thereby maintaining an epithelial state.

AKT (Protein Kinase B) plays a critical role in the PI3K/AKT pathway, regulating several key cellular processes essential for cell survival, proliferation, metabolism, and growth. Abnormal AKT activity is closely linked to the onset and progression of various diseases, especially cancers, making it a critical therapeutic target. AKT activation promotes cell survival and proliferation by inhibiting apoptosis and increasing the expression of anti-apoptotic proteins (such as Bcl-2 family members), thereby enhancing cell viability. Furthermore, AKT regulates cell cycle proteins to promote cell division and proliferation. In terms of metabolism, AKT regulates glucose metabolism and lipid synthesis, facilitating glucose uptake and utilization while inhibiting lipid breakdown, thus providing sufficient energy and material support for rapid cell proliferation [49–51].

We next investigated the expression of AKT and P-AKT in A375 and A2058 cells transfected with miR-425-5p mimic and inhibitor using Western blot. We observed that the upregulation of miR-425-5p enhanced AKT phosphorylation, leading to AKT activation and involvement in multiple biological processes, including cell survival, apoptosis, proliferation, and EMT. In contrast, downregulation of miR-425-5p inhibited AKT phosphorylation, reducing AKT activation, which may impact relevant cellular processes. These findings further underscore the significance of miR-425-5p in regulating the AKT pathway, offering valuable insights into its role in melanoma. To further validate the interaction between miR-425-5p and SCARA5 and enhance the reliability and reproducibility of our study, we designed rescue experiments. The rescue experiments showed that after upregulation of miR-425-5p, the phosphorylation level of AKT increased but was reversed by SCARA5 overexpression. Conversely, downregulation of miR-425-5p reduced AKT phosphorylation, and this reduction was reversed by SCARA5 silencing. Besides, in vivo tumor formation experiments in nude mice were conducted to further validate the negative regulatory relationship between miR-425-5p and SCARA5. After euthanizing the mice, tumor samples from three groups (Control, Control+agmir 425-5p, and OE-SCARA5 + agmir 425-5p) underwent proteomics analysis, which showed that the inhibitory effect of miR-425-5p on SCARA5 in vivo also involved the suppression of the PPAR pathway.

The PPAR pathway is a signaling pathway involving nuclear receptors, including three homologous subtypes: PPARα, PPARβ/δ, and PPARγ. These receptors play a crucial role in various physiological processes, primarily regulating lipid metabolism, energy balance, and inflammation [52]. Upon activation, these PPAR subtypes form complexes with coactivators, which then bind to PPRE (PPAR response elements) to regulate the transcription of multiple genes. The PPAR pathway has a complex relationship with tumors, influencing various biological processes, including cell proliferation, apoptosis, inflammation, and angiogenesis [52–54]. Notably, different PPAR subtypes may play distinct roles in different types of cancer. For instance, activation of PPARγ is considered to suppress tumor growth, while the role of PPARβ/δ may be more complex and vary depending on the tumor type [55]. The activation of the PPAR pathway has potential anti-inflammatory and anti-tumor effects. By inhibiting inflammatory responses and regulating biological processes such as cell proliferation and apoptosis, PPAR activation could influence the development of melanoma. Eastham et al. reported that all PPAR genes are expressed in both melanocytes and melanoma cells [56]. PPARs are involved in various processes in melanoma, including melanogenesis [57, 58]. PPAR also regulates the cell cycle and proliferation of melanoma cells; the anti-proliferative activity of PPAR agonists in melanoma cell lines is caused by cell cycle arrest rather than inducing apoptosis [59]. Dana et al. reported that the PPARγ agonist, pioglitazone, significantly reduced the proliferation of melanoma cells and tumor size in mice [60]. Moreover, treatment with ciglitazone significantly inhibited the development of human melanoma xenografts in nude mice [61]. Studies have shown that activation of PPARγ inhibits melanoma cell proliferation and induces apoptosis by inhibiting Toll-like receptor-4 (TLR-4)-dependent NF-κB pathways [58]. PPARβ/δ suppression of MMP-9 gene and protein expression increases adhesion of mouse melanoma B16F10 cells to endothelial cells, thereby enhancing motility and invasiveness, which is crucial for melanoma metastasis [62]. Overall, these studies demonstrate the complexity of the PPAR pathway in melanoma research.

In addition to the direct regulation of the AKT and EMT pathways described in our study, the intrinsic functions of SCARA5 as a phagocytic receptor warrant further consideration. SCARA5 is reportedly involved in processes such as iron metabolism, partly through its interaction with ferritin, and can influence cellular redox homeostasis. Both iron availability and reactive oxygen species (ROS) levels are critical regulators of tumor cell behavior, including proliferation and metastasis. Therefore, the pro-malignant phenotypes observed upon SCARA5 downregulation are not solely a result of disinhibited AKT/EMT signaling but could also be indirectly mediated or amplified by alterations in intracellular iron levels or ROS production. These parameters were not directly measured in the current study. Future investigations exploring whether the miR-425-5p/SCARA5 axis also modulates melanoma progression through these iron and ROS-dependent mechanisms would provide a more comprehensive understanding of its multifaceted role as a tumor suppressor. Localization Discrepancy of SCARA5 in Melanoma While SCARA5 is classically described as a cell membrane-localized scavenger receptor [31, 63], our immunohistochemistry and immunofluorescence results. reveal a predominant cytoplasmic localization of SCARA5 in malignant melanoma cells (A375 and A2058). This observation, which contrasts with its canonical membrane residency, suggests a crucial tumor-specific alteration or a dual regulatory role of SCARA5 in the tumor microenvironment. This shift in location has been noted in other malignancies and might be linked to two potential mechanisms: (1) failed protein trafficking to the cell surface, or (2) enhanced internalization and subsequent cytoplasmic accumulation or degradation. Functionally, this cytoplasmic sequestration may compromise SCARA5’s primary cell-surface functions, such as its role in binding ligands or iron-ferritin complexes, thereby contributing to the malignant phenotype observed in our study. Future research should clarify the precise mechanism driving this mislocalization and its impact on the downstream signaling pathways regulated by SCARA5.

Next, proteins were extracted from five tumor groups and underwent Western blotting to examine the expression of PPARγ. We found that the expression levels of PPARγ varied among the five groups: Control+agmir 425-5p exhibited the lowest expression, followed by sh-SCARA5, then Control, OE-SCARA5 + agmir 425-5p, and OE-SCARA5, which demonstrated the highest expression. The PPARγ expression level in the OE-SCARA5 + agmir 425-5p group was not significantly different from the Control group, confirming that OE-SCARA5 + agmir 425-5p could restore PPARγ expression. This result further supports the proteomics prediction. Previously, the relationship between five cell groups and the PI3K/AKT pathway was verified at the cellular level. Similar to the PI3K/AKT pathway, the PPAR pathway plays a key role in cell signaling, influencing cell biology, metabolic regulation, and the development of various diseases [64]. Studies have shown that these two pathways interact, with PPAR pathway activation potentially inhibiting PI3K/AKT pathway activity, which in turn affects cell growth, survival, and metabolism [65]. Activation of the PPAR pathway may have a suppressive effect on malignant melanoma by regulating key biological processes, including cell differentiation, apoptosis, and inflammation. Indeed, understanding the interaction between the PI3K/AKT and PPAR pathways is important in melanoma research and treatment. To summarize our findings, miR-425-5p targets and suppresses the expression of SCARA5, promoting the proliferation, invasion, and metastasis of malignant melanoma. This effect is mediated by inhibition of the PPAR pathway and activation of P-AKT phosphorylation, thereby promoting EMT and inhibiting apoptosis in melanoma cells.

In addition to its role at the cellular level via the AKT and PPAR pathways, the miR-425-5p/SCARA5 regulatory axis investigated in this study may also be integrated to broader systemic regulatory networks. As a recent review emphasized, melanoma can “hijack” the body’s homeostasis by influencing the neuroendocrine system, thereby creating a favorable systemic environment for its own growth and metastasis [66]. For example, a tumor may affect the hypothalamic-pituitary-adrenal (HPA) axis or alter sympathetic nervous system activity by secreting certain factors. Although this study did not directly investigate this aspect, the pathway changes observed (such as alterations in the AKT and PPAR pathways, which are closely related to cellular metabolism and inflammation) suggest that miR-425-5p/SCARA5 might function not only as a local regulatory factor but also as a link connecting the tumor to the body’s systemic responses. Future research could investigate whether this regulatory axis influences the levels of specific hormones or neurotransmitters in the serum of melanoma patients. Finally, the proteomics dataset generated in this study constitutes a valuable resource for future exploration. A highly promising direction would be to re-mine this data to search for specific neuroendocrine signatures. Indeed, analyzing the expression changes of neuropeptides, hormone receptors, or related signaling molecules among the different experimental groups could reveal deeper connections between our regulatory axis and systemic responses in the body.

Finally, while this study established a linear regulatory axis, it is important to acknowledge that cellular signaling is rarely unidirectional. The interplay between the pathways identified in the present study likely involves complex crosstalk and feedback loops that were beyond the scope of this initial investigation. For instance, established crosstalk exists between the PI3K/AKT and PPAR pathways. It is highly conceivable that activated AKT could, in turn, modulate the transcriptional activity of PPARγ through phosphorylation, creating a more complex regulatory network. Furthermore, a negative feedback loop might exist, where downstream effectors of EMT could potentially suppress the expression of the upstream miR-425-5p to maintain cellular homeostasis. Future studies employing techniques such as co-immunoprecipitation to detect protein-protein interactions or phosphoproteomics to map signaling dynamics will be necessary to dissect these intricate interactions and fully elucidate the network governing melanoma progression.

Several limitations of this study should be acknowledged. First, the sample size for our in vivo experiments (n = 5 per group) was relatively small. Although this sample size is common for exploratory studies in this field and was sufficient to detect statistically significant differences due to the strong biological effects observed, a larger sample size would provide greater statistical power and enhance the generalizability of our findings. Furthermore, our in vivo analysis primarily focused on primary subcutaneous tumor growth, and we did not perform detailed histopathological examinations of the tumors or conduct systematic autopsies to assess for distant metastases. Therefore, while our data suggest a role for the miR-425-5p/SCARA5 axis in tumor proliferation, its direct impact on tumor morphology and in vivo metastatic potential requires further investigation, ideally through orthotopic or tail-vein injection models. The present study examined the expression level of PPAR-γ to explore its potential involvement in the observed regulatory pathway. However, PPAR-γ activity is not solely determined by its expression level. Rather, its transcriptional activity is influenced by ligand binding, post-translational modifications such as phosphorylation, and intracellular localization, which collectively modulate its functional state. Although our current results focus on expression changes detected by Western blot and qPCR, we acknowledge the value of directly assessing PPAR-γ activity. Future studies involving transcriptional activity assays or coactivator recruitment analysis may help provide further mechanistic insights. A significant limitation of this study pertains to the cellular models used. The melanoma cell lines primarily used for functional assays, A375 and A2058, are known to be amelanotic or poorly melanotic. Given that melanin pigmentation is an active participant in melanoma biology, influencing processes such as drug resistance, redox homeostasis, and immunogenicity [67], it is highly conceivable that the regulatory effects of the miR-425-5p/SCARA5 axis could be modulated by the melanin content within the cell. Our study did not compare the functional impact of this pathway in melanotic versus amelanotic contexts. Future studies should address this gap by including a diverse panel of cell lines exhibiting varying degrees of pigmentation to ascertain whether the melanin synthesis pathway interacts with or modifies the described signaling.

Limitations

This study has made significant progress in elucidating the role of the miR-425-5p/SCARA5/AKT-PPARγ axis in the progression of malignant melanoma, but we also recognize several limitations in the research, which point to directions for future in-depth studies:

Although this study confirmed the regulation of AKT phosphorylation, EMT, and PPARγ expression by the miR-425-5p/SCARA5 axis through Western blot and rescue experiments, the complex cross-talk and feedback mechanisms between the signaling pathways remain incompletely understood. We only assessed the expression of PPARγ, but its functional activity (such as modifications from ligand binding or phosphorylation) was not directly measured. Future research will need to employ techniques like phosphoproteomics, co-immunoprecipitation, or activity assays to provide deeper, more comprehensive, and novel insights into the mechanisms. There is also a lack of analysis regarding the expression correlation of SCARA5, miR-425-5p, and their pathways in larger clinical cohorts. Future work should involve more extensive validation using IHC or tissue microarray techniques on clinical samples to enhance the clinical significance and translational potential of this axis. The in vivo experiments in this study mainly focused on the growth rate of subcutaneous tumors. The direct effect of the miR-425-5p/SCARA5 axis on distant metastatic potential has not been systematically evaluated. Future research should use more clinically relevant models, such as orthotopic or tail vein injection models, combined with detailed histopathological analysis, to validate the role of this axis in melanoma metastasis. The melanoma cell lines used in this study, A375 and A2058, are non-pigmented or poorly pigmented. Since melanin plays an active role in cell signaling and drug resistance, the functional effects of this regulatory axis may be influenced by the intracellular melanin content. Subsequent studies should include cell lines with different levels of pigmentation to more comprehensively assess the function of SCARA5 in various biological contexts.

Conclusion

In summary, our experimental results indicate that SCARA5 expression in malignant melanoma is reduced and negatively regulated by miR-425-5p. Downregulation of SCARA5 promotes AKT phosphorylation, increases the expression of the anti-apoptotic protein Bcl-2, and decreases the expression of caspase-3, thereby inhibiting apoptosis. Besides, SCARA5 downregulation suppresses E-cadherin expression while upregulating N-cadherin, ZEB1, and β-catenin expression, promoting EMT and enhancing the migration and invasion capabilities of melanoma cells. Moreover, the regulation of miR-425-5p on SCARA5 affects the expression of PPAR-γ protein (Fig. 10). These findings suggest that miR-425-5p and SCARA5 play important roles in malignant melanoma, providing new therapeutic targets and research directions for the treatment and prognosis of melanoma.

Fig. 10.

Proposed Hypothetical Model for the Regulation of Melanoma Progression by the miR-425-5p/SCARA5 Axis. This schematic represents a proposed hypothetical model illustrating how miR-425-5p may promote melanoma progression. The direct targeting of SCARA5 by miR-425-5p and the subsequent effects on AKT phosphorylation, EMT, and apoptosis are supported by the findings of this study (indicated by solid lines). Other potential downstream interactions, such as the regulation of the PPAR pathway, are integrated based on our proteomics data and existing literature and represent areas for future investigation (indicated by dashed lines).

Author contributions

Haizhou Yu and Xia Li contributed to the conception and design of the review. Qinggan Ni and Danqing Ying wrote the manuscript, collected clinical patient data, and performed the experiments. Jingjian Chang conducted the data analyses. All authors participated in the manuscript revision, read and approved the submitted version. Qinggan Ni and Danqing Ying are co-first authors.

Funding

This work was supported by funding from the 2024 Yancheng Science and Technology Projects (YCBK2024017).

Data availability

The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This was conducted in full compliance with international ethical standards and approved by the Ethics Committee of the First People’s Hospital of Yancheng City (2023-K-014). All mouse experiments followed institutional guidelines and were approved by the Jiangsu Medicine College Animal Research Ethics Committee (Approval Number: XMLL-2023-708).

Consent for publication

Written informed consent was obtained from all participants prior to their inclusion in this study.

Competing interests

The authors declare no competing interests.