
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13038-1
10.1016/j.heliyon.2024.e37007
e37007
Research Article
Pan-cancer analysis reveals copper transporters as promising potential targets
Li Yueqin lyq2017@csu.edu.cn
abcd⁎
Yu Zhen e
a Institute of Integrative Chinese Medicine, Department of Integrated Chinese Medicine, Xiangya Hospital, Central South University, Changsha, China
b NATCM Key Laboratory of TCM Gan, Xiangya Hospital, Central South University, Changsha, China
c Hunan Key Laboratory of TCM Gan, Xiangya Hospital, Central South University, Changsha, China
d National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
e Department of Pharmacy, Xiangya Hospital, Central South University, Changsha, China
⁎ Corresponding author. lyq2017@csu.edu.cn
27 8 2024
15 9 2024
27 8 2024
10 17 e370075 8 2024
26 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Background

Copper transport proteins (SLC31A1, ATP7A, ATP7B) regulate copper levels in the body and may be involved in tumor development. However, their comprehensive expression and function across various cancers remain unclear.

Methods

The expressions of copper transporters in 33 tumors and normal tissues were analyzed using TCGA, GTEx, CCLE, ULCAN, and HPA databases. Cox regression assessed their impact on patient survival. Gene alterations were explored using cBioPortal. Spearman correlation tests were performed to investigate the associations between copper transporters and tumor mutation burden (TMB), microsatellite instability (MSI), and infiltration of immune cells. Gene functions were analyzed using STRING and GeneMANIA databases. Drug sensitivity was assessed using GSCALite database. ATP7B expression in lung squamous cell carcinoma (LUSC) was validated by immunohistochemical staining.

Results

Copper transporters exhibited variable expression patterns across various cancer types, indicating their potential dual role as either oncogenes or tumor suppressor genes, depending on the cancer type. Significant associations were found between these transporters and tumor stage, as well as prognosis in most tumors studied. Pathway analysis identified links between copper transporters and tumor-related pathways like apoptosis and RAS/MAPK. Copy number variation (CNV) analysis revealed varying degrees of gene amplification and deletion of copper transporters in most tumors. Copper transporters exhibited strong correlations with immune features, including TMB, MSI, and immune-infiltrating cells, suggesting their potential role in guiding immunotherapy. They were also associated with sensitivity to various chemotherapeutic and immunotherapeutic drugs. Immunohistochemical tests validated the correlation between elevated ATP7B level and worse progression-free survival (PFS) in LUSC.

Conclusion

Copper transporters may serve as potential tumor markers and therapeutic targets.

Keywords

Copper homeostasis
Pan-cancer analysis
Biomarker
Individualized treatment
Cancer
==== Body
pmc1 Introduction

Globally, cancer is now the primary reason for mortality [1]. The main reason for the high death rate is the lack of effective treatment methods and unclear understanding of how the disease spreads [2]. Hence, it is crucial to discover novel therapeutic targets and create innovative approaches for treating cancer.

Copper, an essential trace element, plays a key role in multiple biological functions including protecting against oxidative stress, supporting cellular energy production, and enhancing the immune system [3]. Intracellular copper concentration is typically maintained within a homeostatic range. Deviations, either through overload or deficiency, can lead to cytotoxic effects and potential cell death [4]. Organisms have evolved intricate systems to maintain copper balance to reduce the harmful impacts [5]. Solute carrier family 31 member 1 (SLC31A1), a high-affinity copper transporter, helps bring copper into cells, while ATPase Copper Transporting Alpha (ATP7A) and ATPase Copper Transporting Beta (ATP7B) work to remove extra copper. Together, these three copper transporters maintain cellular copper balance [6].

Recent research has emphasized the importance of copper transporters (SLC31A1, ATP7A, ATP7B) in the field of cancer biology [7]. For instance, increased expression of SLC31A1 was linked to unfavorable outcomes in breast cancer [8], bladder cancer [9], and glioma [10], while leading to improved survival in non-small-cell lung cancer [11]. Compared with normal tissues, ATP7A expression was significantly elevated in hepatocellular carcinoma [12] and esophageal squamous cell carcinoma [13], while decreased in ovarian carcinoma [14]. Patients with overexpression of ATP7B had higher survival rates in gliomas [15], but unfavorable clinical outcomes in hepatocellular carcinoma [16]. These results underscore the dual role of copper transporters and highlight the need for further research to elucidate their specific functions in each cancer type.

This research involved a comprehensive analysis of the mRNA and protein expression patterns of copper transporters in 33 kinds of cancer and normal tissue samples. Information from multiple databases was integrated to investigate the associations between these transporters and different variables such as tumor stages, prognosis, cancer-related pathways, genetic mutations, immune cell infiltration, and drug response. Preliminary verification was conducted through immunohistochemical experiments. The research design overview is illustrated in Fig. 1.Fig. 1 Flowchart of the study design. By comprehensive use of datasets from TCGA, CCLE, GTEx, UALCAN, cBioPortal, GSCALite, HPA, STRING, GeneMANIA, we explored the association of copper transporters with tumor stages, prognosis, cancer-related signaling pathways, gene mutation, immune cell infiltration, and drug sensitivity in 33 tumors.

Fig. 1

2 Methods

2.1 Transcriptome analysis of copper transporters

Copper transporters mRNA levels in healthy tissues were sourced from the GTEx database (https://commonfund.nih.gov/GTEx), with tumor tissue levels obtained from the TCGA (https://www.cancer.gov/aboutnci/organization/ccg/research/structural-genomics/tcga). Furthermore, details on mRNA levels in cancer cells were acquired from the Cancer Cell Line Encyclopedia (CCLE) (https://sites.broadinstitute.org/ccle). Transcriptome information from 33 tumors was processed with the ‘RMA’ software to eliminate NA values and duplicates, then converted to log2(TPM + 1). Finally, the expressions of copper transporters between normal individuals and tumor patients were compared using the R package “limma”and “ggplot2”.

2.2 Analysis of copper transporters protein levels in pan-cancer tissues

Immunohistochemistry pictures from the Human Protein Atlas (HPA) (https://www.proteinatlas.org/) were utilized to evaluate the varying expressions of copper transporters. Protein expression data differences were acquired through the ‘CPTAC’ tool within the UALCAN databas(http://ualcan.path.uab.edu/index.html), based on the methodology outlined in a prior research paper [17]. Briefly, Log2 spectral count ratio values from CPTAC were first normalized within each sample profile, and then normalized across all samples. A comparison between normal and cancer tissues was conducted using two sets of t-tests.

2.3 Pathological stage analysis

The ‘Expression Analysis' module of UALCAN database was employed to investigate the mRNA levels of copper transporters across various cancer stages, using the approach described by Darshan et al. [17]. Gene expression levels were normalized to Transcripts Per Million (TPM). t-test was used to explore the correlation between protein expression and pathological stage.

2.4 Survival analysis

Data on survival and clinical characteristics were obtained from TCGA for each individual sample. The software packages ‘survival’ and ‘forestplot’ were employed to examine the impact of copper transporters on survival metrics including progression-free survival (PFS) and overall survival (OS) [18]. A Cox model was used to estimate the risk of survival (Hazard Ratio, HR) associated with each gene.

2.5 Analysis of cancer pathway

Using GSCALite (https://guolab.wchscu.cn/GSCA/#/), this research examined how copper transporters impact the activation of cancer pathways [19]. The pathway activity score (PAS) differences between these subsets were analyzed using the Student's T-test. P-values were corrected for false discovery rate (FDR), with a threshold of FDR ≤0.05 indicating statistical significance. A higher PAS for a gene's high expression indicates potential pathway activation, while a lower PAS suggests an inhibitory effect.

2.6 Constructing protein-protein interaction (PPI) and gene-gene interaction (GGI) networks

The STRING database (www.string-db.org), a prediction server utilized for analyzing protein-protein interaction (PPI) data, was used to acquire a list of proteins interacting with the copper transporters family [20]. We utilized GeneMANIA (http//genemania.org/) to explore genes that interact with our specified target genes [21]. The gene lists from both sources were combined and analyzed for enrichment using the R package ‘ClusterProfiler'.

2.7 Mutation analysis

The frequency of changes in copper transporters in different types of cancers was analyzed using the CBioPortal database (https://www.cbioportal.org/) [22]. The percentage of Copy Number Variation (CNV) and its correlation with mRNA expression in each cancer type were calculated. The single nucleotide variation (SNV) percentage was computed using dividing the Number of Mutated Samples by the Number of Cancer Samples.

2.8 Correlation of copper transporters expression with tumor mutation burden (TMB) and tumor microsatellite instability (MSI)

TMB and MSI scores were assessed using mutation data retrieved from TCGA following the method described by Cheng et al. [23]. Briefly, Spearman's method was utilized to examine the relationship between the expression of copper transporters and levels of TMB and MSI.

2.9 Tumor immunology analysis

TCGA was utilized to assess the immune infiltration, utilizing the analysis techniques outlined by Wang and colleagues [24]. Spearman correlation analysis heat map was created to show how immune scores and copper transporter gene expression are related in various types of cancer.

2.10 Drug sensitivity analysis

We examined the associations between gene expression and drug response by using the Genomics of Drug Sensitivity in Cancer (GDSC) database available at www.cancerrxgene.org, following a methodology outlined in a prior research [25].

2.11 Immunohistochemistry

Twenty-three LUSC samples were gathered from Xiangya Hospital, Central South University. All patients signed informed consent. Approval for the study was given by the Xiangya Hospital Medical Ethics Committee(No.CTXY-110008-2). Tissue sections were prepared and stained following established protocols [26]. Expression levels were classified as either high or low depending on the median value.

3 Results

3.1 Transcriptomic expression analysis of copper transporters

The expressions of copper transporters in normal tissues were depicted in Fig. 2A. The analysis revealed that SLC31A1 expression was predominant in liver tissue and minimal in muscle tissue. Skin tissue exhibited the highest levels of ATP7A, whereas liver tissue displayed the lowest. Notably, ATP7B expression was prominent in testicular tissue but reduced in most other normal tissues.Fig. 2 mRNA expression of copper transporters in tumor and normal samples.

(A) Heatmap of the mRNA expressions of copper transporters in normal tissues. Information was acquired from the GTEx.

(B) Heatmap of the mRNA expression profiles of copper transporters in 33 cancers. Data were sourced from the TCGA.

(C) mRNA expression of copper transporters in tumor cells. Data were downloaded from the CCLE.

(D) Comparison of mRNA expressions of copper transporters between normal individuals and tumor patients. Normal samples were depicted by blue box plots, whereas tumor samples were depicted by red box plots. *p < 0.05; **p < 0.01; ***p < 0.001.

(E) Venn diagram identifying cancers with differential expression in all three copper transporters. The Venn diagram illustrated the overlap of cancer types where the expressions of all three copper transporters consistently changed.

(F) mRNA differences of copper transporters in tumor and adjacent normal tissues. The fold change (FC) was determined by dividing the average expression in tumor samples by the average expression in normal samples. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2

Subsequently, the expressions of copper transporters across various cancers were investigated through the TCGA database. SLC31A1 was expressed in all cancers, with PCPG showing the highest levels and THYM the lowest, as illustrated in Fig. 2B. ATP7A showed minimal expression in LIHC and was most expressed in LAML, whereas ATP7B expression was minimal in DLBC and maximal in READ. Fig. 2C displayed the varying expression levels of these transporters in diverse cancer cell lines, showcasing the fluctuating expression in tumor cells.

Furthermore, a comparison of copper transporter expression between normal individuals and tumor patients was conducted using TCGA data, as illustrated in Fig. 2D. Significant disparities in SLC31A1 expression were observed in 13 cancer types, except in cancers lacking normal tissue data. ATP7A and ATP7B exhibited significant differential expression in 12 and 15 cancer types, respectively. The Venn diagram showed that the three copper transporters had similar differential expression in BLCA, BRCA, KIRC, KIRP, LIHC, LUSC, STAD, THCA, and UCEC (Fig. 2E).

Additionally, paired samples of tumors and adjacent normal tissues in the TCGA database were used for paired comparison analyses (Fig. 2F). Only 14 kinds of cancers have over 10 pairs of such tissues. The findings showed varying expression of SLC31A1 in BLCA, BRCA, KIRC, KICH, KIRP, LIHC, LUSC, LUAD, PRAD, THCA. At the same time, ATP7A was differently expressed in KICH, KIRP, LIHC, LUSC, HNSC, STAD. Whereas ATP7B was differently expressed in BRCA, COAD, KIRC, KIRP, PRAD, THCA.

In summary, the expression patterns of copper transporter genes varied across different cancer types, suggesting their potential roles as oncogenes or tumor suppressor genes, contingent on the type of cancer.

3.2 Comparison of copper transporters protein expressions in normal and tumor tissues

The protein levels of copper transporters were evaluated by analyzing immunohistochemistry (IHC) from the HPA database and comparing them with protein expression data from the ULCAN database. As demonstrated in Fig. 3, findings from both databases aligned. In comparison with normal tissues, SLC31A1 expression was markedly decreased in LIHC and increased in GBM. ATP7A was significantly upregulated in LIHC but downregulated in BRCA. Furthermore, ATP7B showed enhanced expression in BRCA and UCEC.Fig. 3 Comparison of copper transporter protein levels in normal tissue and tumor tissue.

(A) Comparing the levels of SLC31A1 levels between normal and tumor tissues with representative immunohistochemistry images.

(B) Comparison of ATP7A levels between normal and tumor tissues with representative immunohistochemistry images.

(C) Comparison of ATP7B levels between normal and tumor tissues with representative immunohistochemistry images.

*p < 0.05; **p < 0.01; ***p < 0.001.

Fig. 3

3.3 Correlations between copper transporters expressions and clinicopathology

A thorough examination was performed to assess the levels of copper transporters SLC31A1, ATP7A, and ATP7B in different cancer stages. In comparison with normal tissues, SLC31A1 expression was notably elevated in tumor tissues at pathological stages in BLCA, BRCA, ESCA, and UCEC. However, its expression was reduced in the clinical stages of CHOL, KIRC, KIRP, LIHC, LUAD, LUSC, and THCA (Fig. 4A). ATP7A expression was elevated in the clinical stages of CHOL, KICH, LIHC, and UCEC, while it was reduced in the pathological stages of BRCA, KIRC, KIRP, LUSC, and THCA (Fig. 4B). ATP7B expression was reduced in the clinical stages of LUSC and THCA, while it was raised in the disease stages of BRCA, COAD, KIRC, READ, STAD and UCEC (Fig. 4C). These findings suggested that copper transporters may hold substantial clinical relevance for the early diagnosis of these malignancies.Fig. 4 Expression level of copper transporters in different pathological stages.

(A) SLC31A1 expression levels across various pathological stages.

(B) ATP7A expression levels across various pathological stages.

(C) ATP7B expression levels across various pathological stages.

∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001.

Fig. 4

3.4 The prognostic value of copper transporters

Survival association analyses were performed for each type of cancer to evaluate the prognostic importance of copper transporters, including OS (Fig. 5A) and PFS (Fig. 5B). Increased levels of SLC31A1 were linked to worse OS in patients with ACC, BLCA, BRCA, LGG, MESO, and SKCM. The hazard ratios (HR) for these types of cancer were found to be significantly higher than 1, suggesting an increased risk of death from the disease (p < 0.05). In contrast, higher SLC31A1 expression was associated with improved OS in KIRC, suggesting a protective effect (HR < 1, p < 0.05). Furthermore, patients exhibiting high ATP7A expression demonstrated reduced survival rates in LGG, whereas those with elevated ATP7A expression showed enhanced survival in ACC, KIRC, MESO. Elevated ATP7B expression correlated with diminished survival in UCEC, while correlating with improved survival in KIRC and LGG.Fig. 5 The prognostic value of copper transporters.

(A) Overall survival (OS) .

(B) Progression-free survival (PFS).

Fig. 5

Elevated levels of SLC31A1 were linked to worse survival rates in ACC, BLCA, BRCA, CESC, LGG, MESO, and UVM for PFS, while showing a positive correlation with better survival in KIRC and READ. Furthermore, increased ATP7A expression was linked to worse survival in BLCA, LGG, and LIHC, while exhibiting improved survival in MESO and KIRC. Conversely, elevated ATP7B expression was associated with reduced survival rates in COAD and LUSC, yet enhanced survival rates in KIRC, LGG, and THCA. These findings highlighted the complex role of copper transporters in cancer prognosis, demonstrating variable effects across different cancer types.

3.5 Cancer-related pathways analysis

In the majority cancers, the expressions of copper transporters exhibited significant correlations with both tumor stage and prognosis. This discovery prompted us to speculate that these transporters could be involved in the advancement of tumors by affecting signaling pathways within the tumor. The analysis of pathways indicated a notable participation of copper transporters in different signaling pathways related to cancer (Fig. 6). SLC31A1 primarily participated in the stimulation of RTK (25 % activation compared to 0 % inhibition), apoptosis (22 % activation compared to 3 % inhibition), and RAS/MAPK (16 % activation compared to 0 % inhibition). For ATP7A, the main pathways were inactivation of cell cycle (0 % activation vs. 19 % suppression) and apoptosis (3 % activation vs. 22 % suppression). ATP7B primarily activated the RTK pathways, with a 28 % activation rate compared to a 3 % inhibition rate. The findings suggested that copper transporters may have a significant impact on regulating pathways associated with cancer.Fig. 6 Effects of copper transporters on pathway activity.

Fig. 6

The red boxes showed the percentage of 33 types of tumors in which the pathway was activated, while the blue boxes showed the percentage of tumor types in which the pathway was suppressed.

3.6 Molecular interaction network and enrichment analysis

We performed molecular interaction network analysis and enrichment analysis to further understand the potential functions of copper transporters. A total of 8 proteins that interact with them, were obtained from the STRING database (Fig. 7A). Additionally, utilizing the GeneMANIA website, we identified 20 genes that interact with the copper transporter family (Fig. 7B). We conducted Gene Ontology (GO) enrichment analysis by merging these two gene lists. In the biological process category, these molecules were predominantly involved in copper transport and copper homeostasis. Analysis of cellular component enrichment revealed that the majority of compounds were concentrated in late endosomes, basolateral and apical plasma membranes, recycling endosomes, trans-Golgi network, and integral components of the plasma membrane. Analysis of molecular function enrichment revealed that the majority of molecules were involved in the activity of transporting copper ions across membranes and binding copper ions (Fig. 7C). Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis highlighted their involvement in mineral absorption and platinum drug resistance.Fig. 7 Potential functions of copper transporters.

(A) The PPI network of copper transporters and their interacting proteins

(B) The GGI network between genes associated with copper transporters.

(C) Functional enrichment analysis on molecules that interact with copper transporters.

Fig. 7

3.7 Analysis of genetic alteration

To explore the gene alteration status of copper transporters across pan-cancer, we utilized data from the CBioPortal database. Fig. 8A displays the primary gene modifications identified, including mutation, amplification, and deep deletion. The mutation rate of SLC31A1 was highest among patients with pancreatic, esophageal, and bone cancer. Likewise, patients with melanoma, bladder, and non-small cell lung cancer exhibited the highest mutation rate of ATP7A. Furthermore, the mutation rate of ATP7B was highest in colorectal, esophageal, and lung cancer.Fig. 8 The alteration of copper transporters in pan-cancers.

(A) The frequency of alterations categorized by different mutation types. (B)Distribution of copy number variations (CNV) across 33 cancers. (C)Relationship between copy number variations and messenger RNA levels. The statistical significance was depicted by the size of the data points, with bigger dots indicating greater significance. FDR denoted false discovery rate.

Fig. 8

An examination was carried out on genetic variations in copper transporters. Surprisingly, the distribution of the CNV displayed that the main types of CNV were amplification and deletion in the heterozygous state(Fig. 8B). Moreover, CNV profiles varied across different cancer types.

Positive correlation between mRNA expression and CNV was identified through correlation analysis, with SLC31A1 in OV, ATP7A in LUSC, and ATP7B in COAD showing notable associations(Fig. 8C). Conversely, a negative correlation was observed for ATP7A in KIRP and PCPG. These findings suggested that CNV alterations of copper transporters may contribute to their dysregulated expressions, potentially exerting a significant role in tumor progression.

3.8 The relationship between copper transporters and tumor mutation burden (TMB), tumor microsatellite instability (MSI)

TMB is a measurable indicator that shows the amount of mutations in cancer cells and can provide insight into the immune system's reaction. SLC31A1 expression exhibited a strong positive correlation with TMB in various cancer types including LUAD, LGG, PAAD, BLCA, UCEC, BRCA, COAD, STAD, SARC, ACC and THYM, but had a notable negative correlation with UVM and THCA (Fig. 9A). Regarding ATP7A, positive correlations were observed in LGG and THYM, indicating higher mutation burdens associated with increased ATP7A expression in these tumors, while negative correlations were found in UVM, THCA, LUAD, KIRP, KIRC, COAD, and BRCA. ATP7B expression showed notably positive correlations with TMB in several tumors, including ESCA and THYM, while exhibiting significant negative correlations with DLBC, CESC, BRCA, LGG, COAD, THCA, and SKCM.Fig. 9 Correlation between the gene expression and TMB and MSI in pan-cancer.

(A) The relationship between the expression of copper transporters and TMB across various tumors.

(B) The association between the expression of copper transporters and MSI across diverse tumors.

Fig. 9

Following this, an examination was implemented to determine the relationship between expression and MSI (Fig. 9B). The expression of SLC31A1 showed strong positive correlations with COAD, UCEC, READ and STAD, but had significant negative correlations with DLBC, PRAD, LUSC, and LUAD. ATP7A showed significant positive associations with COAD, LUSC, UCEC, READ and ACC. Conversely, ATP7A was negatively associated with DLBC and PRAD. Furthermore, ATP7B exhibited significant positive correlations with LUAD, LUSC and CHOL, while showing negative associations with DLBC, PCPG, and COAD.

Overall, these results highlighted the diverse roles of copper transporters in influencing TMB and MSI across different cancers, suggesting their potential as biomarkers for cancer prognosis and therapy.

3.9 Tumor immune cell infiltration

We collected infiltration data for six types of immune cells by utilizing the TIMER database. Fig. 10 showed that the three copper transporters were associated with immune cell infiltration in most tumors. Specifically, SLC31A1 level showed a positive correlation with immune cell infiltration in various cancers, including BRCA, BLCA, COAD, KIRC, LGG, LUAD, MESO, OV, PRAD, READ, SARC, THCA, UCEC, and UCS. ATP7A expression exhibited strong positive correlations with the infiltration of all six types of immune cells in KIRC, LGG, LIHC, and READ. Conversely, ATP7B expression showed negative associations with the infiltration of these immune cells in SKCM and STAD. These results highlighted the intricate relationship between copper transporter levels and the infiltration of immune cells in tumor microenvironment.Fig. 10 Correlation between copper transporters' expression and immune infiltration. (A) SLC31A1. (B) ATP7A. (C) ATP7B. ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001.

Fig. 10

3.10 Drug sensitivity analysis

Genomic aberrations and immune infiltration can significantly influence drug responses. Our analysis revealed several significant correlations between copper transporter expression and drug sensitivity(Fig. 11). Higher level of ATP7B was associated with decreased sensitivity to Nilotinib, suggesting that ATP7B expression may lead to resistance to this medication. Likewise, the expression of ATP7A showed an inverse relationship with the susceptibility to SB52334, indicating a possible involvement in conferring resistance to this treatment. SLC31A1 expression was notably linked to the responsiveness of various chemotherapy medications and targeted treatments, such as methotrexate, vorinostat, temozolomide, docetaxel, trametinib, and more. These findings highlighted the potential impact of dysregulated copper transporters’ expression on chemotherapy and targeted drug therapy resistance. Comprehending these connections may guide the creation of improved treatment plans and individualized treatments for individuals with cancer.Fig. 11 Drug sensitivity analysis of copper transporters. FDR, false discovery rate.

Fig. 11

3.11 The verification of the expression of ATP7B by IHC in LUSC

Due to the differential expression of ATP7B in LUSC and its relationship with survival observed in the bioinformatics analysis, we further validated these findings by using IHC. Representative IHC pictures were shown in Fig. 12A. The results suggested that ATP7B expression did not exhibit significant differences across various tumor stages (Fig. 12B). Following this, we examined the relationship between ATP7B expression and patient prognosis, finding that while ATP7B expression was not correlated with OS, it was significantly correlated with PFS (Fig. 12C and D).Fig. 12 Verification of ATP7B expression in LUSC.

(A) Representative IHC images of ATP7B expression.

(B) The relationship between ATP7B expression and tumor stages.

(C) The relationship between ATP7B expression and OS.

(D)The relationship between ATP7B expression and PFS.

Fig. 12

4 Discussion

In this current study, we performed an extensive analysis across various types of cancer to examine how copper transporters (SLC31A1, ATP7A, and ATP7B) were expressed and their relationships with tumor stages, prognosis, cancer-related pathways, gene mutations, immune cell presence, and drug response. Moreover, we validated the role of ATP7B in LUSC using IHC. Our research offers new perspectives on the possible functions of these transporters in cancer biology and treatment.

The role of copper metabolism-related genes in tumors has garnered widespread attention [27]. Liu H. and colleagues examined the cuproptosis gene group, which consists of 7 genes that promote cuproptosis, 3 genes that inhibit cuproptosis, and 2 copper transporters, in relation to SNV, CNV, methylation, mRNA levels, interactions between pathways, and miRNA controls in 33 different tumor types [28]. This study provides new insights into the genetics of cuproptosis genes, yet the protein expression profiles of these genes across various cancer types remain to be elucidated. Later, Wu et al. conducted a comprehensive study on cuproptosis regulators across various types of cancer using TCGA, serving as a valuable resource for upcoming research on cuproptosis [29]. However, they did not investigate copper transporters. There are several differences between our study and previous studies. Firstly, our study focuses on copper transporters (SLC31A1, ATP7A, ATP7B) by integrating multi-omics data, including mRNA expression (from TCGA, GTEx and CCLE), protein expression (from HPA and UALCAN). These comprehensive datasets provide a thorough understanding of copper transporters. Secondly, clinical tissue samples were collected for immunohistochemical test to validate the results of ccbioinformatics analysis, thereby ensuring their reliability. Thirdly, we studied the relationship between copper transporters and immune infiltration, as well as drug sensitivity. Understanding these connections may guide the development of improved treatment plans and personalized therapies for cancer patients. In summary, our study enhanced the understanding of copper transporters in cancer biology and distinguish our work from existing literature.

Our current research revealed variations in copper transporters’ expression among different cancer types, indicating their possible functions as either oncogenes or tumor suppressor genes, determined by the specific cancer type. Likewise, earlier research has indicated that elevated level of SLC31A1 was linked to unfavorable outcomes in breast cancer [8], bladder cancer [9], glioma [10], while leading to improved survival in non-small-cell lung cancer [11]. Additionally, previous pan-cancer analysis indicated that SLC31A1 was highly expressed in most tumors and lowly expressed in a few compared to healthy tissues [30,31]. These findings are consistent with our results. Compared with normal tissues, ATP7A expression was significantly elevated in hepatocellular carcinoma [12] and esophageal squamous cell carcinoma [13], while decreased in ovarian carcinoma [14]. As for ATP7B, patients with overexpression of ATP7B had higher survival rates in gliomas [15], but unfavorable clinical outcomes in hepatocellular carcinoma [16]. Previous pan-cancer results have also confirmed the dual role of ATP7B in various tumors [32]. Collectively, these results underscore the dual role of copper transporters in cancer biology and highlight the necessity for further research to elucidate their specific mechanisms in each cancer type.

In our immune infiltration analysis, we have observed that SLC31A1 and ATP7A facilitate immune cell infiltration, whereas ATP7B impedes immune cell infiltration in most tumors. These distinct effects of the three copper transporters on immune infiltration may contribute to the dual role of copper ions in immune responses. For instance, Voli et al. proposed that copper may upregulate PD-L1 expression, thereby promoting immune evasion [33]. Conversely, copper can promote M1 macrophage polarization and trigger immunogenic cell death [6,34]. However, the intricate mechanisms underlying the interplay between copper and immunity remain elusive and warrant further investigation in future studies.

Considering the differential expression of ATP7B in LUSC and its relationship with survival in the bioinformatics analysis, we collected 23 cases of LUSC to validated these findings. Consistent with the bioinformatics analysis, patients with high ATP7B expression had worse PFS. However, ATP7B expression was not show significant differences across various tumor stages. The small sample size could be the reason for this.

Although our research offers valuable perspectives, it is crucial to recognize specific constraints. The main constraint is the dependence on bioinformatics and clinical confirmation of limited sample sizes, lacking direct experimental validation. Future research should include clinical studies with large samples, as well as animal and in vitro molecular experiments.

5 Conclusion

Overall, our research has revealed important connections between the levels of copper transporters and different aspects of cancer biology, such as tumor stage, clinical outcome, immune cell presence, and cancer-related signaling pathways in various types of tumors. These observations present copper transporters as potential targets for personalized therapy in the future.

Funding

Funding for this project was provided by the National Natural Science Foundation of China, China (NO. 82204531 ) and the Youth Foundation of Hunan Provincial Natural Science Foundation of China , China (NO. 2020JJ5910 ).Abbreviation

	Detail	
ACC	Adrenocortical carcinoma	
BLCA	Bladder Urothelial Carcinoma	
BRCA	Breast invasive carcinoma	
CESC	Cervical squamous cell carcinoma and endocervical adenocarcinoma	
CHOL	Cholangio carcinoma	
COAD	Colon adenocarcinoma	
DLBC	Lymphoid Neoplasm Diffuse Large B-cell Lymphoma	
ESCA	Esophageal carcinoma	
GBM	Glioblastoma multiforme	
HNSC	Head and Neck squamous cell carcinoma	
KICH	Kidney Chromophobe	
KIRC	Kidney renal clear cell carcinoma	
KIRP	Kidney renal papillary cell carcinoma	
LAML	Acute Myeloid Leukemia	
LGG	Brain Lower Grade Glioma	
LIHC	Liver hepatocellular carcinoma	
LUAD	Lung adenocarcinoma	
LUSC	Lung squamous cell carcinoma	
MESO	Mesothelioma	
OV	Ovarian serous cystadenocarcinoma	
PAAD	Pancreatic adenocarcinoma	
PCPG	Pheochromocytoma and Paraganglioma	
PRAD	Prostate adenocarcinoma	
READ	Rectum adenocarcinoma	
SARC	Sarcoma	
SKCM	Skin Cutaneous Melanoma	
STAD	Stomach adenocarcinoma	
TGCT	Testicular Germ Cell Tumors	
THCA	Thyroid carcinoma	
THYM	Thymoma	
UCEC	Uterine Corpus Endometrial Carcinoma	
UCS	Uterine Carcinosarcoma	
UVM	Uveal Melanoma	
TCGA	The Cancer Genome Atlas	
CCLE	Cancer Cell Line Encyclopedia	
GTEx	Genotype-Tissue Expression	
HPA	Human Protein Atlas	
FC	fold change	
PPI	protein–protein interaction	
GGI	gene-gene interaction	
PFS	progression free survival	
DSS	disease-specific survival	
CNV	copy number variation	
TMB	tumor mutation burden	
MSI	tumor microsatellite instability	
TPM	Transcripts Per Million	
KEGG	Kyoto Encyclopedia of Genes and Genomes	
GO	Gene Ontology	

CRediT authorship contribution statement

Yueqin Li: Conceptualization, Data curation, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing. Zhen Yu: Methodology, Resources.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
==== Refs
References

1 Siegel R.L. Giaquinto A.N. Jemal A. Cancer statistics, 2024 CA A Cancer J. Clin. 74 1 2024 12 49
2 Guo Y. Wu H. Wiesmüller L. Chen M. Canonical and non-canonical functions of p53 isoforms: potentiating the complexity of tumor development and therapy resistance Cell Death Dis. 15 6 2024 412 38866752
3 Chen L. Min J. Wang F. Copper homeostasis and cuproptosis in health and disease Signal Transduct. Targeted Ther. 7 1 2022 378
4 Xie J. Yang Y. Gao Y. He J. Cuproptosis: mechanisms and links with cancers Mol. Cancer 22 1 2023 46 36882769
5 Ge E.J. Bush A.I. Casini A. Cobine P.A. Cross J.R. DeNicola G.M. Connecting copper and cancer: from transition metal signalling to metalloplasia Nat. Rev. Cancer 22 2 2022 102 113 34764459
6 Liu W.Q. Lin W.R. Yan L. Xu W.H. Yang J. Copper homeostasis and cuproptosis in cancer immunity and therapy Immunol. Rev. 321 1 2024 211 227 37715546
7 Li Y.Q. Copper homeostasis: emerging target for cancer treatment IUBMB Life 72 9 2020 1900 1908 32599675
8 Li L. Li L. Sun Q. High expression of cuproptosis-related SLC31A1 gene in relation to unfavorable outcome and deregulated immune cell infiltration in breast cancer: an analysis based on public databases BMC Bioinf. 23 1 2022 350
9 Lin Y.Z. Liu W.H. Wu Y.P. Cai H. Zheng Q.S. Wei Y. Revealing the potential of solute carrier family 31 (copper transporters), member 1: insights into its role in bladder cancer progression and therapeutic implications Int. J. Immunopathol. Pharmacol. 38 2024 3946320241240706
10 Wang J. Li S. Guo Y. Zhao C. Chen Y. Ning W. Cuproptosis-related gene SLC31A1 expression correlates with the prognosis and tumor immune microenvironment in glioma Funct. Integr. Genomics 23 3 2023 279 37610668
11 Sun C. Zhang Z. Qie J. Wang Y. Qian J. Wang J. Genetic polymorphism of SLC31A1 is associated with clinical outcomes of platinum-based chemotherapy in non-small-cell lung cancer patients through modulating microRNA-mediated regulation Oncotarget 9 35 2018 23860 23877 29844858
12 Zhao X. Chen J. Yin S. Shi J. Zheng M. He C. The expression of cuproptosis-related genes in hepatocellular carcinoma and their relationships with prognosis Front. Oncol. 12 2022 992468
13 Li Z.H. Lu X. Li S.W. Chen J.T. Jia J. Expression of ATP7A in esophageal squamous cell carcinoma (ESCC) and its clinical significance Int. J. Clin. Exp. Pathol. 12 9 2019 3521 3525 31934199
14 Elsnerova K. Mohelnikova-Duchonova B. Cerovska E. Ehrlichova M. Gut I. Rob L. Gene expression of membrane transporters: importance for prognosis and progression of ovarian carcinoma Oncol. Rep. 35 4 2016 2159 2170 26820484
15 Zhang Z. Zhang A. Shi Y. Zhao Z. Zhao Z. An association between ATP7B expression and human cancer prognosis and immunotherapy: a pan-cancer perspective BMC Med. Genom. 16 1 2023 307
16 Sugeno H. Takebayashi Y. Higashimoto M. Ogura Y. Shibukawa G. Kanzaki A. Expression of copper-transporting P-type adenosine triphosphatase (ATP7B) in human hepatocellular carcinoma Anticancer Res. 24 2c 2004 1045 1048 15154620
17 Chandrashekar D.S. Bashel B. Balasubramanya S.A.H. Creighton C.J. Ponce-Rodriguez I. Chakravarthi B. UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses Neoplasia 19 8 2017 649 658 28732212
18 Liu T. Yang K. Chen J. Qi L. Zhou X. Wang P. Comprehensive pan-cancer analysis of KIF18A as a marker for prognosis and immunity Biomolecules 13 2 2023
19 Liu C.J. Hu F.F. Xie G.Y. Miao Y.R. Li X.W. Zeng Y. GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels Briefings Bioinf. 24 1 2023
20 Szklarczyk D. Kirsch R. Koutrouli M. Nastou K. Mehryary F. Hachilif R. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest Nucleic Acids Res. 51 D1 2023 D638-d46
21 Franz M. Rodriguez H. Lopes C. Zuberi K. Montojo J. Bader G.D. GeneMANIA update 2018 Nucleic Acids Res. 46 W1 2018 W60-w4
22 Gao J. Aksoy B.A. Dogrusoz U. Dresdner G. Gross B. Sumer S.O. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal Sci. Signal. 6 269 2013 pl1
23 Cheng X. Wang X. Nie K. Cheng L. Zhang Z. Hu Y. Systematic pan-cancer analysis identifies TREM2 as an immunological and prognostic biomarker Front. Immunol. 12 2021 646523
24 Wang T. Zhu T. Zhang Y. Bai J. Xue Y. Xu G. Pan-cancer analysis of the prognostic and immunological role of BRCA1-associated protein 1 gene (BAP1): friend or foe? Gene 840 2022 146765
25 Rees M.G. Seashore-Ludlow B. Cheah J.H. Adams D.J. Price E.V. Gill S. Correlating chemical sensitivity and basal gene expression reveals mechanism of action Nat. Chem. Biol. 12 2 2016 109 116 26656090
26 Li Y.Q. Chen J. Yin J.Y. Liu Z.Q. Li X.P. Gene expression and single nucleotide polymorphism of ATP7B are associated with platinum-based chemotherapy response in non-small cell lung cancer patients J. Cancer 9 19 2018 3532 3539 30310510
27 Tsvetkov P. Coy S. Petrova B. Dreishpoon M. Verma A. Abdusamad M. Copper induces cell death by targeting lipoylated TCA cycle proteins Science (New York, N.Y.) 375 6586 2022 1254 1261 35298263
28 Liu H. Pan-cancer profiles of the cuproptosis gene set Am. J. Cancer Res. 12 8 2022 4074 4081 36119826
29 Wu C. Tan J. Wang X. Qin C. Long W. Pan Y. Pan-cancer analyses reveal molecular and clinical characteristics of cuproptosis regulators iMeta 2 1 2023 e68 38868340
30 Zhang P. Yang H. Zhu K. Chang C. Lv W. Li R. SLC31A1 identifying a novel biomarker with potential prognostic and immunotherapeutic potential in pan-cancer Biomedicines 11 11 2023
31 Zhang G. Wang N. Ma S. Tao P. Cai H. Comprehensive analysis of the effects of the cuprotosis-associated gene SLC31A1 on patient prognosis and tumor microenvironment in human cancer Transl. Cancer Res. 13 2 2024 714 737 38482443
32 Liu H. Tang T. Pan-cancer genetic analysis of cuproptosis and copper metabolism-related gene set Front. Oncol. 12 2022 952290
33 Voli F. Valli E. Lerra L. Kimpton K. Saletta F. Giorgi F.M. Intratumoral copper modulates PD-L1 expression and influences tumor immune evasion Cancer Res. 80 19 2020 4129 4144 32816860
34 Gao X. Huang H. Pan C. Mei Z. Yin S. Zhou L. Disulfiram/copper induces immunogenic cell death and enhances CD47 blockade in hepatocellular carcinoma Cancers 14 19 2022
