AC067930.4/miR-375 Axis Regulates the Malignant Progression of Colon Adenocarcinoma Through the Cuproptosis-Related Gene SLC6A6

Introduction

Colon adenocarcinoma (COAD), a subtype of colorectal cancer (CRC), is characterized by significant heterogeneity and strong invasiveness.¹ Despite the continuous advancements in surgery, chemotherapy, targeted therapy, and immunotherapy, the overall prognosis of COAD remains suboptimal, particularly the low five-year survival for patients in advanced stages.² Chemotherapy resistance, molecular heterogeneity, metastatic propensity, and tumor microenvironment collectively represent barriers to current therapeutic options.³ Identifying novel molecular mechanisms and discovering effective therapeutic targets are crucial for enhancing the prognosis of patients with COAD.

Non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have garnered growing attention for their pivotal roles in tumor initiation and progression.⁴ miRNAs typically interact with the 3’ untranslated region (3’UTR) of target mRNAs, resulting in mRNA degradation or suppression of translation, and thus, act as negative regulators of gene expression.⁵ miRNAs regulate cellular processes, including proliferation, apoptosis, migration, and invasion, in various malignancies, such as COAD.^6,7 For example, miR-375, a key tumor suppressor miRNA, can exert an inhibitory effect in different solid tumors by targeting multiple oncogenic pathways.^8,9 In COAD, the downregulation of miR-375 expression is strongly associated with tumor progression and a poor prognosis; however, its potential regulatory mechanism requires further investigation.¹⁰ lncRNAs are ncRNAs that exceed 200 nucleotides in length. They regulate gene expression through various mechanisms at transcriptional and post-transcriptional stages.¹¹ The competitive endogenous RNA (ceRNA) mechanism is a significant model that has been developed in recent years, suggesting that lncRNA may indirectly influence the downstream target genes of miRNA by competing for binding, thereby contributing to tumorigenesis and progression.¹² Specifically, lncRNA can act as a “sponge” that binds to a specific miRNA, reducing its inhibitory effects on the target mRNA and achieving a de-inhibitory effect on the mRNA.¹³ In COAD, various lncRNAs have been implicated in tumor progression, the formation of drug resistance, and immune regulation.¹⁴ Integrating the ceRNA theory to elucidate the lncRNA and miRNA interaction network that regulates target gene expression would enhance the understanding of the mechanisms underlying COAD and offer novel avenues for targeted therapeutic research.

Programmed cell death (PCD) is a crucial biological process that maintains the body’s homeostasis and is widely involved in key life activities, including tissue development, immune regulation, and tumor suppression.¹⁵ In recent years, the advancement of high-throughput technology has enabled scientists to identify several novel cell death mechanisms, among which cuproptosis, a newly found unique RCD process, has garnered increasing attention.¹⁶ Cuproptosis, a form of cell death characterized by the abnormal accumulation of copper ions, differs from ferroptosis and apoptosis.¹⁷ Research indicates that copper ions can influence acylated proteins in the mitochondrial tricarboxylic acid cycle under certain conditions, promote aberrant protein aggregation, and compromise the stability of iron–sulfur cluster proteins, leading to mitochondrial malfunction and cytotoxic responses.¹⁸ Compared to other cell death methods, cuproptosis exhibits greater specificity, particularly reliant on mitochondrial integrity and metabolic activity, therefore demonstrating strong selectivity for tumor cells with highly active metabolism.^17,19 Studies have shown that cuproptosis is involved in regulating the growth, metastasis, and treatment sensitivity of various tumor types, such as hepatocellular carcinoma, lung adenocarcinoma, and breast cancer.^20,21 It is also suggested that cuproptosis is not only a novel type of cell death but also a unique target for tumor treatment. However, current research on cuproptosis in COAD remains relatively limited. A thorough investigation of the molecular pathways underlying cuproptosis in COAD will enhance our understanding of its malignant progression and may yield novel intervention strategies for targeted tumor therapy.

SLC6A6 (solute carrier family 6 member 6) is an important gene encoding a taurine transporter, which is involved in cell osmotic pressure regulation, ion balance, and anti-oxidative stress response.²² In many cancers, high expression of SLC6A6 is closely associated with survival, drug resistance, and invasion of tumor cells.²³ Recent studies have pointed out that SLC6A6 may participate in the malignant progression of tumors by regulating cell stress and metabolic pathways.²³ In COAD, SLC genes are also considered to be an important factor affecting tumor proliferation and drug resistance.²⁴ However, there is currently no systematic study on the potential role of SLC6A6 in regulating cuproptosis, especially in COAD.

In this article, we first discovered that lncRNA AC067930.4 “sponges” miR-375 through the ceRNA mechanism, thereby influencing the expression of its downstream target gene SLC6A6, which is associated with cuproptosis. In functional experiments, we found that inhibition of SLC6A6 can effectively promote cuproptosis in COAD cells, as determined by copper ion concentration detection and analysis of reactive oxygen species (ROS) levels. Gene set enrichment analysis (GSEA) and cell function experiments confirmed that the AC067930.4/miR-375/SLC6A6 axis is critically involved in regulating the proliferation of COAD cells. Mechanistically, dual luciferase reporter assays confirmed that AC067930.4 functions as a ceRNA for miR-375, thereby mitigating its repressive influence on SLC6A6. Our study revealed the biological function of the AC067930.4/miR-375/SLC6A6 regulatory axis in COAD and its potential role in the cuproptosis mechanism, providing a new theoretical foundation and intervention strategies for the targeted treatment of COAD.

Materials and Methods

Data Collection

Forty-one pairs of cancerous and adjacent non-cancerous tissue samples, together with clinical data from 488 patients with COAD, were acquired from The Cancer Genome Atlas (TCGA) database. To investigate the associations between gene expression and clinical outcomes, univariate Cox regression and GSEA were conducted on the entire dataset.

Differential Expression Analysis

Differential expression analysis played a crucial role in identifying miRNAs, mRNAs, and lncRNAs that exhibited substantial expression fluctuations. The analysis of these molecules was performed using the “limma” R package (version 3.52.4), with filtering based on log fold change and corresponding p-values. For enhanced data interpretation, volcano plots were constructed using the “ggplot2” R package (version 3.4.0). Meanwhile, heat maps were created via the “pheatmap” R package (version 1.0.12), providing a visual overview of differential expression profiles.

Univariate Cox Analysis

Univariate Cox regression, a standard tool in survival analysis, was used to assess the impact of individual variables (therapeutic approaches, disease stages, demographic factors, and molecular indicators) on survival and recurrence. The Cox proportional hazards model yielded hazard ratios, p-values, and confidence intervals (CIs), facilitating the identification of variables strongly correlated with survival outcomes.

Consensus Clustering

The expression data of the selected genes underwent consensus clustering using the “Consensus Cluster Plus” R package, investigating cluster formations from k = 2 to 9 with 1000 iterations to ensure stable categorization. The consensus matrix and cumulative distribution function (CDF) curves were meticulously evaluated to pinpoint the optimal cluster number. Subsequent survival analysis across clusters was performed using the Kaplan–Meier method, complemented by Chi-square tests to examine the distribution of categorical attributes among groups, thereby shedding light on the distinctions between cuproptosis-associated clusters.

Construction of ceRNA Network

To construct the ceRNA network of lncRNAs, miRNAs, and mRNAs, we utilized miRWalk to identify potential lncRNA–miRNA binding sites and RNAhybrid, along with TarBase, to predict miRNA–targeted mRNAs. We selected suitable lncRNAs and integrated significant co-expression relationships among lncRNAs, miRNAs, and mRNAs to build the network, visualized using Cytoscape 3.7.3.

GSEA

GSEA was implemented to investigate the biological processes of COAD-associated DEGs from differential analysis. The ClusterProfiler R package was employed to analyze hallmark gene sets. DEGs were ordered based on log2FC values for normalized enrichment score (NES) calculation. Significantly enriched pathways were identified when |NES| exceeded 1 and the p-value was below 0.05.

DAVID Enrichment Analysis

Differentially expressed genes (DEGs) related to COAD were analyzed using the DAVID platform, with a focus on Gene Ontology (GO) terms associated with COAD. Significant enrichment was determined using p < 0.05. Bubble plots were generated to highlight key biological processes in COAD.

Lipid Peroxidation Measurement

COAD cells (ATCC) in 6-well plates were treated with reagents and subsequently harvested and rinsed. Cells were resuspended in phosphate-buffered solution (PBS) with 4 µM DCFH-DA (D399, Thermo Fisher Scientific, USA) at 37°C for 25 min. After washing twice with PBS, the fluorescent signals were measured using flow cytometry (excitation wavelength: 485 nm; emission wavelength: 530 nm). At least 10,000 cells per sample were analyzed. Relative Mean Fluorescence Intensity (MFI) assessed ROS levels, with results analyzed via FlowJo.

Cell Culture

COAD cells HCT-116 and SW480 were respectively cultured in McCoy’s 5A and Leibovitz’s L-15 media, each supplemented with 10% fetal bovine serum (FBS) and 1% penicillin–streptomycin. The cultivation was carried out at 37°C in an atmosphere containing 5% CO₂. Our cell lines were obtained from ATCC.

Transfection

Lipofectamine 3000 (L3000001, Invitrogen, USA) was used for transfecting siRNAs, ASOs, mimics, and inhibitors from Biomics and RiboBio. Transfection was performed per the manufacturer’s guidelines. siRNA sequences are presented in Supplementary Table 1.

CCK-8

COAD cells were seeded in 96-well plates at around 2000 cells per well. At designated time intervals (24, 48, and 72 h), 10 µL of CCK-8 reagent (HY-K0301, MCE, USA) was introduced to each well. Following a 2-h incubation at 37°C, absorbance was measured at 450 nm utilizing a microplate reader.

Cell Migration Assay

Cells were placed in upper chambers with 200 µL serum-free medium, using uncoated Transwell chambers (3470, Corning, USA). Lower chambers contained 10% FBS. After 24 hours, cells were fixed and stained with crystal violet for 15 minutes. Cells were then imaged and counted across five fields, with the experiment repeated three times.

Apoptosis Analysis

COAD cells were harvested and rinsed with ice-cold PBS. They were resuspended in the binding buffer from the Annexin V–FITC/PI Apoptosis Detection Kit (HY-K1073, MCE, USA). This kit utilizes Annexin V–FITC to identify apoptotic cells and PI to detect cells with membrane compromise. Upon staining, apoptosis was quantified using a Cytoflex flow cytometer (Beckman Coulter), with CytExpert Software analyzing apoptotic cells based on fluorescence.

Quantitative Real-Time PCR (qPCR)

Total RNA was extracted from COAD cells and normal counterparts using TRIzol reagent (Invitrogen, 15596026CN, USA). Genomic DNA was isolated using the FastPure DNA Isolation Kit (Vazyme, DC102-01). RNA concentration and quality were assessed using Nanodrop 2000 (Thermo Fisher). Circular DNA (cDNA) for circRNA/mRNA analysis was synthesized using the PrimeScript RT Master Mix (RR036A, Takara, Japan) with random primers. For miRNA reverse transcription, PrimeScript RT Reagent Kit (RR047A, Takara, Japan) with stem-loop primers was used. qPCR was performed with TB Green Premix Ex Taq II (RR820A, Takara, Japan) on an ABI Prism 7500 system. GAPDH was used as an internal control for relative expression calculation via the 2^–(ΔΔCT) method. Each sample was analyzed in triplicate. Primer sequences are provided in Supplementary Table 2.

RNA Immunoprecipitation Quantitative PCR (RIP-qPCR)

Gene expression profiles were quantified using the Dynabeads™mRNA Purification Kit (cat. no. 61006; Invitrogen). Total RNA was extracted and subjected to immunoprecipitation by incubation with anti-SLC6A6 (ab236898; Abcam) or non-specific control IgG (ab172730; Abcam) under rotation at 4°Cfor 2 hours. RNA-antibody complexes were captured using Pierce™ Protein A/G Magnetic Beads (cat. no. 88803; Thermo Scientific), collected with a magnetic separator, washed three times in 1×immunoprecipitation buffer supplemented with RNase inhibitor, and then treated with proteinase K for RNA elution. After digestion, 5 μg of glycogen and 2.5 volumes of 100% ethanol in 3 M sodium acetate were added, and the RNA was precipitated overnight at −80 °C. The precipitated RNA was recovered and quantified by qPCR.

Subcutaneous Tumor Formation in Nude Mice

HCT116 human colorectal cancer cells (ATCC) were resuspended in PBS. Female BALB/c nude mice aged 4–6 weeks were selected, and 0.1 mL of the cell suspension (containing 2×10⁶ cells) was subcutaneously inoculated into the right dorsal axillary region. After inoculation, the general condition of the mice and tumor formation were observed daily. The NC inhibitor and miR-375 inhibitor were injected into each animal via intra-tumor injection at 5 days after tumor implantation. When the tumor volume reached the experimental endpoint (typically approximately 1000 mm³) or at the predetermined observation time point, the mice were euthanized by cervical dislocation. Tumor tissues were then excised, weighed, and partially preserved in 4% paraformaldehyde or liquid nitrogen for subsequent analyses. All animal experiments were conducted in accordance with the guidelines for the care and use of laboratory animals and approved by the Institutional Animal Care and Use Committee (IACUC) of Zhejiang Provincial Laboratory Animal Center (Approval No. ZJCLA-IACUC-20011263).

Intracellular Copper Ion Concentration Measurement

COAD cells were seeded into six-well plates and incubated overnight for attachment. Then, the cells were treated with CuCl₂ and Elesclomol for 24 h to induce cuproptosis. After treatment, the medium was discarded, and cells were rinsed with ice-cold PBS to remove any extracellular copper ions. Cells were collected, centrifuged, and resuspended in ultrapure water. After sonication and centrifugation, the supernatant was collected. By following the instructions for the Cell Copper (Cu2+) Colorimetric Assay Kit (E-BC-K300-M, Elabscience, USA), the supernatant was mixed with the assay reagent in a 96-well plate. The reaction proceeded as recommended, and the optical density was measured to quantify intracellular copper.

Luciferase Reporter Gene Assay

Plasmids containing the wild-type and mutant 3’UTR sequences of AC067930.4 and mRNA were constructed and inserted into the GP-miRGLO luciferase reporter vector (Genepharma, China). After transfection, luciferase activity was quantified using the Dual-Luciferase Reporter Assay System (E1910, Promega, USA), following the manufacturer’s instructions.

Statistical Analysis

Statistical evaluation was conducted using GraphPad Prism 10.1.0, with data presented as mean ± standard deviation (SD) to encapsulate the central tendency and variability. The independent Student’s t-test was utilized for pairwise comparisons based on the assumptions of normality and homogeneity of variances. For multi-group comparisons, one-way analysis of variance (ANOVA) was applied to evaluate the significance of mean differences across groups. A threshold of p < 0.05 was considered statistically significant, with all tests being two-tailed to accommodate effect directionality.

Results

Identifying lncRNAs, microRNAs, and mRNAs Associated with the Development of COAD

The expression of biomarkers shifts during tumor development, with many serving as oncogenes or tumor suppressors to drive or restrain tumor malignancy. Yet, the function of the ceRNA axis formed by these genes in colon cancer remains ambiguous. To explore the underlying mechanism, we analyzed the mRNAs, lncRNAs, and miRNAs of 41 pairs of COAD tumor and paracancerous samples, respectively. The results showed that 2311 upregulated and 2643 downregulated genes were identified in mRNAs, 746 upregulated and 2204 downregulated genes were extracted after differential analysis of lncRNAs, and 178 upregulated genes and 255 downregulated genes were found after analysis of miRNAs (Figure 1A–C). Next, we performed univariate Cox analysis on 524 COAD samples. There were 775 oncogenes and 349 tumor suppressor genes in mRNAs, 444 oncogenes and 47 tumor suppressor genes in lncRNAs, and 24 oncogenes and 13 tumor suppressor genes in miRNAs (Figure 1B).

Figure 1 The results of univariate cox and differential expression analysis of mRNAs, lncRNAs and miRNAs from the TCGA database. (A) Volcano plots of differential expression analysis of mRNAs, lncRNAs and miRNAs. (B) The top ten results of univariate cox analysis in mRNAs, lncRNAs and miRNAs. (C) Heatmaps of differential expression analysis of mRNAs, lncRNAs and miRNAs.

Consensus Clustering Analysis of Cuproptosis-Related Genes

Copper ions are intricately associated with the therapeutic efficacy of COAD, and cuproptosis may significantly contribute to the development of COAD. To classify COAD patients according to cuproptosis levels, consensus clustering was performed on the expression data from 13 previously identified cuproptosis related genes. The analysis categorized 524 COAD patients from the TCGA database into various clusters (k = 2–9). The optimal clustering effect was observed when k = 4 (Figure 2A, Supplementary Figure S1A and B). Kaplan–Meier analysis was used to investigate the differences in overall survival between the two clusters, revealing that group 3 had significantly better survival than group 4 (Figure 2B). The limma package was used to perform differential expression analysis on Groups 3 and 4, and the results demonstrated the presence of 241 upregulated and 259 downregulated DEGs (Figure 2C and D, Supplementary Figure S1C). Furthermore, we conducted GSEA on the obtained DEGs and found that they were mainly enriched in proliferation- and migration-related pathways (Figure 2E).

Figure 2 Consensus cluster analysis of cuproptosis related genes. (A) Consensus clustering heatmap of cuproptosis related genes with k=4. (B) Kaplan-Meier survival curve between cluster 3 and cluster 4. (C) The volcanic map showed the differential genes of the two clusters. (D) The heat map of differentially expressed genes. (E) GO enrichment analysis of cuproptosis related genes.

Construction of Cuproptosis-Related ceRNA Axis

Based on the above results, we constructed a ceRNA network regulating the malignant progression of COAD, using mRNAs obtained from cuproptosis differential expression analysis, as well as lncRNAs and microRNAs obtained from univariate Cox analysis of 524 COAD samples. This network contains 15 lncRNAs, 1 miRNA, 2 mRNAs, and 30 sets of interaction axes (Figure 3A and Supplementary Figure S2). In many cancers, high expression of SLC6A6 is closely associated with survival, drug resistance, and tumor cell invasion, and it is of great significance in COAD research. Currently, SLC6A6 has not been investigated for cuproptosis and miR-375. Therefore, we will focus our research on the ceRNA axis that regulates SLC6A6. To verify the role of SLC6A6 in cuproptosis, we treated COAD cell lines HCT-116 and SW480 with Elesclomol, a kind of cuproptosis inducer. The IC₅₀ values of these two cell lines are 56.14 nM and 48.63 nM, respectively (Figure 3B). Next, we exposed these cells to Elesclomol at concentrations of 0, 25, and 50 nM and assessed changes in cellular ROS levels via flow cytometry. The results showed that compared to the control group, the ROS levels were significantly reduced in the si-SLC6A6 group (Figure 3C), indicating that inhibition of SLC6A6 reduced oxidative stress in cells. Surprisingly, SLC6A6 suppression significantly increased Cu²⁺ levels (Figure 3D), which indicated that inhibition of SLC6A6 may enhance the sensitivity of COAD cells to cuproptosis inducers. In addition, electron microscopy clearly revealed that, compared with the control group, the si-SLC6A6 group exhibited obvious mitochondrial shrinkage and a marked reduction in inner membrane cristae after using cuproptosis inducers. These findings further indicated the occurrence of cuproptosis (Figure 3E). By sorting the count values of 15 lncRNAs in the ceRNA axis, we selected the top 5 lncRNAs, namely AC012531.1, AC067930.4, AC131934.1, AL391152.1, and AP001528.1, which may regulate SLC6A6 (Figure 3F).

Figure 3 Construction of COAD cancer related ceRNA network by integrated analysis. (A) LncRNA-miRNA-mRNA regulatory axes extracted from the ceRNA network. (B) CCK8 assay was used to measure cell viability 24 hours after exposure to increasing doses of Elesclomol. (C) SLC6A6 knockdown cells and control groups cells were treated with increasing doses of Elesclomol for 24 hours, and the levels of reactive oxygen species (ROS) were measured using flow cytometry. (D) SLC6A6 knockdown cells and control groups cells were treated with increasing doses of Elesclomol for 24 hours, and the concentration of copper (Cu2+) was measured. (E) Transmission electron microscopy (TEM) images related to cuproptosis. (F) The LncRNA-miRNA-mRNA pattern diagram. Data were expressed as the mean ± standard deviation of three independent experiments (n = 3). (****, p < 0.0001). Abbreviation: NS, Not Significant.

AC067930.4 May Regulate the ceRNA Axis Associated with Cuproptosis in COAD

To investigate which lncRNA plays a key role in regulating SLC6A6, differential expression and survival analyses were carried out on AC012531.1, AC067930.4, AC131934.1, AL391152.1, and AP001528.1. The results of differential expression analysis demonstrated that AC012531.1, AC067930.4, and AC131934.1 were significantly overexpressed in COAD (Figure 4A). Survival and correlation analyses revealed that lncRNA AC067930.4 is closely linked to poorer survival outcomes and higher SLC6A6 expression levels (Figure 4B and C). The area under the curve showed that AC067930.4 was also more sensitive to survival (Figure 4D). To further screen the results and validate our hypothesis, ASO was used to knock down AC012531.1, AC067930.4, and AP001528.1, respectively. The nucleic acid level variation of SLC6A6 was assayed, demonstrating that its expression is most significantly regulated by AC067930.4. In contrast, knocking down other lncRNAs did not result in significant differences (Figure 4E). Overall, AC067930.4 appears to be the key lncRNA regulate SLC6A6 expression.

Figure 4 AC067930.4 may regulate the ceRNA axis associated with cuproptosis in colon adenocarcinoma. (A) The expression of potential lncRNAs between tumor and normal tissues in COAD patients. The green box indicates the normal tissue and the red box indicates the tumor tissue. (B) Survival analysis in the high and low expression lncRNA groups. (C) Pearson correlation coefficient analysis between SLC6A6 and potential lncRNAs. (D) The ROC curves of the potential lncRNAs. (E) RT-qPCR assays were used to detect the expressions of SLC6A6 mRNA levels in HCT116 and SW480 cells with potential lncRNAs knockdown by ASO (T-test). Values were expressed as the mean±SD from three experiments, and the asterisk indicates the statistical significance compared to the controls (*, p < 0.05, ****, p < 0.0001). Abbreviation: NS, Not Significant.

miR-375, AC067930.4, and SLC6A6 Can Regulate the Malignant Progression of COAD

Based on the forecasting outcomes, AC067930.4/miR-375/SLC6A6 might be the ceRNA axis influencing COAD progression. However, their role in COAD’s malignant process remains to be determined. Therefore, we categorized COAD samples into high- and low-expression groups based on AC067930.4 for differential expression analysis and GSEA (miR-375 and SLC6A6 underwent similar analyses). The findings indicated that the DEGs regulated by these three genes were chiefly enriched in pathways related to proliferation, apoptosis, and migration. (Figure 5A and Supplementary Figure S3). To confirm how the three genes affect COAD’s proliferation, apoptosis, and migration, CCK-8 assays, apoptosis detection, and Transwell migration experiments were done after inhibiting AC067930.4/SLC6A6 and overexpressing miR-375. Proliferation and migration were reduced while apoptosis increased. This matched GSEA (Figure 5B–D), showing the three genes can drive COAD’s malignant progression.

Figure 5 AC067930.4, miR-375 and SLC6A6 regulate the COAD malignant progression. (A) The bubble diagrams of GO enrichment analysis in low expression group and high expression group among SLC6A6, AC067930.4 and miR-375 by DAVID database. (B) The CCK8 assays of COAD cells were performed when SLC6A6, AC067930.4 and miR-375 inhibited or overexpressed for 48h. (C) The cell migration assays were used to detect the migratory ability of COAD cells when SLC6A6, AC067930.4 and miR-375 inhibited or overexpressed for 48h. (D) The apoptosis assays were used to detect the apoptosis ability of COAD cells when SLC6A6, AC067930.4 and miR-375 inhibited or overexpressed for 48h. Values were expressed as the mean ± SD from three experiments, and the asterisk indicates the statistical significance compared to the controls (***, p < 0.001, ****, p < 0.0001).

AC067930.4 and miR-375 Can Regulate the Expression of SLC6A6 in COAD

To further investigate the relationship between AC067930.4, miR-375, and SLC6A6, we carried out a Pearson correlation analysis on these three genes. The findings revealed a correlation among them (Figure 6A). Next, ASO was applied to knock down AC067930.4, after which changes in miR-375 and SLC6A6 expression were assessed. Results indicated that SLC6A6 expression decreased while miR-375 expression increased (Figure 6B). Then, we assessed the levels of AC067930.4 and SLC6A6 when miR-375 was overexpressed via mimic or inhibited by an inhibitor. Results indicated that miR-375 negatively modulated AC067930.4 and SLC6A6 (Figure 6C and D). These results suggest that AC067930.4 and miR-375 can modulate SLC6A6 in COAD, and this interaction aligns with the ceRNA axis model.

Figure 6 AC067930.4 and miR-375 can regulate SLC6A6 in COAD. (A) Pearson correlation coefficient analysis among SLC6A6, AC067930.4 and miR-375. (B) RT-qPCR assays were used to detect the expression of SLC6A6, AC067930.4 and miR-375 in COAD cells treated with AC067930.4 ASO. (C) RT-qPCR assays were used to detect the expression of SLC6A6, AC067930.4 and miR-375 in COAD cells treated with miR-375 mimic for 48h. (D) RT-qPCR assays were used to detect the expression of SLC6A6, AC067930.4 and miR-375 in COAD cells treated with miR-375 inhibitor for 48h. Values were expressed as the mean±SD from three experiments, and the asterisk indicates the statistical significance compared to the controls. (***, p < 0.001, ****, p < 0.0001).

AC067930.4 Acts as the ceRNA of miR-375 to Regulate SLC6A6, Thereby Affecting the Malignant Progression of COAD

To verify if AC067930.4 acts as a ceRNA for miR-375, we introduced matching mutations into the forecast interaction sites between AC067930.4 and miR-375 (Figure 7A). A luciferase reporter assay was then conducted to assess the impact of these mutations on luciferase activity. The results demonstrated that miR-375 regulated the luciferase activity of wild-type AC067930.4, whereas the mutant showed no significant regulation (Figure 7B). To validate the endogenous interaction between miR-375, AC067930.4, and SLC6A6, an RIP-qPCR assay was performed. Compared with the control IgG group, significantly higher levels of miR-375 and AC067930.4 were detected in the RNA complexes specifically enriched by the SLC6A6 antibody, thereby confirming the endogenous binding between miR-375, AC067930.4, and SLC6A6 protein under physiological conditions (Figure 7C). We then analyzed the pathways linked to COAD progression, focusing on genes co-regulated by SLC6A6 and miR-375. Our analysis revealed significant enrichment of differentially expressed genes (DEGs) in pathways related to cell growth and migration (Figure 7D and E). To verify this finding, we inhibited miR-375 in both control and SLC6A6-knockdown experimental groups and assessed cell proliferation and migration. While it boosted tumor cell proliferation and migration in the control group, this effect was absent in the SLC6A6-knockdown group (Figure 7F and G). In addition, we further validated our conclusions through in vivo experiments. After inhibiting miR-375 expression in siNC group and the SLC6A6 knockdown group, respectively, the results of subcutaneous tumor-bearing experiments in nude mice showed that miR-375 inhibition promoted tumor cell growth in siNC group, whereas this effect was not observed in the SLC6A6 knockdown group (Figure 8A and B). These results suggest that miR-375 may regulate the malignant progression of COAD through SLC6A6.

Figure 7 As the ceRNA of miR-375, AC067930.4 regulates SLC6A6 and affects the malignant progression of COAD. (A) Predicted binding site between miR-375 and AC067930.4. (B) Luciferase assays were performed to test the effect of miR-375 on wild-type or mutant AC067930.4 after treating with miR-375 mimic for 48h. (C) The Rip assays were used to validate the sponge mechanism of the ceRNA. (D) Venn diagrams represent the overlapped genes between miR-375 and SLC6A6. (E) The bubble diagram of GO enrichment analysis of miR-375 and SLC6A6 overlapped genes by DAVID database. (F) The CCK8 results of siNC or siSLC6A6 COAD cell lines treated with miR-375 inhibitor. (G) The migration results of siNC or siSLC6A6 COAD cell lines treated with miR-375 inhibitor. Values were expressed as the mean ± SD from three experiments, and the asterisk indicates the statistical significance compared to the controls (****, p < 0.0001). Abbreviation: NS, Not Significant.

Figure 8 MiR-375 may regulate the malignant progression of COAD through SLC6A6. (A) Representative images of subcutaneous tumors derived from HCT116 cells in nude mice. The mice were treated with siNC (control) or siSLC6A6 in combination with either NC inhibitor or miR‑375 inhibitor, as indicated. (B) Quantitative analysis of tumor weight at the end of the experiment. Values were expressed as the mean ± SD (n = 5 per group), and the asterisk indicates the statistical significance compared to the controls (****, p < 0.0001). Abbreviation: NS, Not Significant.

Discussion

COAD is a prevalent malignancy of the digestive tract, with high heterogeneity, invasiveness, and poor prognosis. Although some progress has been made in surgery, chemoradiotherapy, and targeted therapy, some patients do not respond well to conventional treatment and are prone to recurrence and metastasis. The regulatory mechanism of ncRNA has garnered significant attention, particularly the role of ceRNA interactions between miRNA and lncRNA in tumorigenesis, which has become more elucidated. The ceRNA network indirectly regulates gene expression by sequestering miRNAs through competitive binding and has demonstrated notable biological relevance across various types of tumors. Research on COAD has indicated that lncRNA H19, SNHG1, and others can modulate classical oncogenic pathways, including Wnt and PI3K/Akt, via the ceRNA mechanism, hence influencing cell proliferation and death.^25,26 This study established a novel ceRNA regulatory axis in COAD, demonstrating that lncRNA AC067930.4 sequesters miR-375, alleviating its suppression of the cuproptosis-related gene SLC6A6, which in turn enhances the proliferation of COAD cells. This result improves our understanding of the ceRNA mechanism, expands the ncRNA regulatory map in COAD, and provides a foundation for exploring new therapeutic targets.

As a novel form of RCD, cuproptosis differs mechanistically from conventional apoptosis, autophagy, and ferroptosis. Copper ions interact with acylated proteins in mitochondria, triggering protein aggregation and the breakdown of iron–sulfur cluster proteins, ultimately leading to cell death.²⁷ This procedure is strongly associated with mitochondrial metabolic activity and so may selectively kill tumor cells with high metabolic rates.¹⁷ Research has indicated that cuproptosis contributes to the progression of several cancers, including liver, lung, and breast cancers, and influences tumor responsiveness to therapy.^28–30 In this study, patients with COAD were classified into two subtypes with varying levels of cuproptosis through consensus clustering. The findings revealed marked differences in various biological processes and signaling pathways between the two subtypes, and further differential analysis identified a subset of genes associated with cuproptosis. This suggests that cuproptosis may have important biological functions in COAD and can act as a potential target for therapeutic intervention. Our research elucidates the relationship between the cuproptosis mechanism and the progression of COAD while also providing a theoretical foundation for the development of interventions related to copper ion metabolism.

As a taurine transporter, SLC6A6 plays an important role in regulating cellular osmotic pressure, maintaining ion homeostasis, and resisting oxidative stress.³¹ Multiple studies have shown that SLC6A6 is highly expressed in various tumors, which can promote tumor cell proliferation, migration, and drug resistance, and has significant carcinogenic potential in neuroblastoma, breast cancer, and so on.^32,33 SLC6A6 has been demonstrated to promote tumor survival via modulating metabolic balance and the oxidative stress response. It is worth noting that some studies have suggested that SLC6A6 may be closely related to copper ion homeostasis and the cuproptosis process, particularly in regulating mitochondrial function and redox state. However, its specific function in COAD and whether it is involved in regulating cuproptosis have not been systematically studied. This study confirmed for the first time that SLC6A6 was negatively correlated with cuproptosis in COAD. It was further confirmed through in vitro experiments that inhibition of SLC6A6 could significantly enhance the sensitivity of cells to copper ions and promote the accumulation of ROS, suggesting that it may be a negative regulator of cuproptosis. In addition, combined with the ceRNA mechanism, we found that SLC6A6 can be directly targeted and regulated by miR-375, and miR-375 itself is regulated by upstream lncRNA. In summary, we propose that SLC6A6 is regulated by ncRNA in COAD and participates in the regulatory network of the cuproptosis mechanism, providing theoretical support for it as a new diagnostic and therapeutic target.

This study constructed and verified a new molecular regulatory axis, namely the AC067930.4/miR-375/SLC6A6 axis, revealing its important role in synergistically regulating cuproptosis and tumor cell proliferation in COAD. Through experiments, such as copper ion concentration detection and ROS level determination, we found that the inhibition of SLC6A6 can effectively activate the cuproptosis pathway, suggesting it is a negative regulatory factor. GSEA and phenotypic experiments confirmed that this regulatory axis impacts key biological functions, including the cell cycle and mitochondrial metabolism. At the molecular mechanism level, dual-luciferase reporter experiments verified that miR-375 can directly bind to the 3’ UTR of SLC6A6, and this binding is interfered with by the competitive adsorption of lncRNA, further clarifying the regulatory pathway of ceRNA. The previous findings indicate that this ceRNA axis is crucial not only for regulating cuproptosis sensitivity but also for the proliferation and metastatic capacity of COAD. In addition to its mechanistic significance, the AC067930.4/miR-375/SLC6A6 regulatory axis also demonstrates promising clinical translational potential in Colon adenocarcinoma (COAD). Previous studies have mainly focused on classical cuproptosis-related regulators such as FDX1 and DLAT in tumor metabolism and therapeutic response; however, the involvement of ncRNA-mediated regulation in cuproptosis remains insufficiently explored. Compared with these earlier findings, our study extends the regulatory framework of cuproptosis by identifying an upstream ceRNA-based mechanism that modulates cellular sensitivity to copper-induced cell death. Importantly, the identification of SLC6A6 as a negative regulator of cuproptosis suggests that targeting this axis may enhance the efficacy of copper-dependent therapeutic strategies and improve tumor sensitivity to metabolic stress. Furthermore, given the stability and detectability of ncRNAs in clinical samples, the AC067930.4/miR-375/SLC6A6 axis may serve as a potential biomarker panel for prognosis evaluation and treatment stratification, thereby providing a feasible direction for future precision medicine approaches in COAD. This discovery presents a new model for studying ceRNA networks associated with cuproptosis and also provides a feasible direction for the development of multidimensional regulatory anti-cancer strategies.

In summary, we discovered and verified the regulatory relationship between miR-375 and its target gene, SLC6A6, in COAD for the first time, confirming that the ceRNA mechanism of upstream lncRNA regulates this process. Further experiments demonstrated that this regulatory axis has a significant impact on cuproptosis and cell proliferation, with important biological implications. Our study not only reveals the ncRNA regulatory mechanism related to cuproptosis but also expands the molecular network cognition of COAD, providing new research directions and potential intervention targets for future targeted therapy.