Cuprotosis Patterns Are Associated with Tumor Mutation Burden and Immune Landscape in Lung Adenocarcinoma

Background The association involving cuprotosis, molecular subtype, and specific immune cell groups in the tumor microenvironment has been focused on by more recent studies. In lung adenocarcinoma (LUAD), the potential functions of cuprotosis remain elusive. Methods The cuprotosis regulations and tumor immune profile of 567 LUAD patients and the correlation between the cuprotosis patterns and the immune landscape were comprehensively evaluated. The cuprotosisScore was calculated using principal component analysis (PCA). The prognostic significance of the cuprotosisScore was evaluated by Cox regression statistics analysis. Results Five cuprotosisClusters (named mc1, 2, 3, 4, 5)—characterized by differences in expression of immunomodulatory genes, mRNA, or lncRNA expression, and prognosis were identified. We established cuprotosisScore to quantify the cuprotosis pattern of individual LUAD patients. As is shown in further analyses, the cuprotosisScore was a relatively potential independent prognostic factor of LUAD involved in mc1. Finally, the prognostic value of the cuprotosisScore and its association with tumor immune microenvironment (iTME) of LUAD in five cuprotosisClusters were verified. Conclusions We demonstrated the correlation between cuprotosis modification, the molecular subtype, and tumor immune landscape in LUAD. The cuprotosisCluster with high cuprotosisScore and high tumor mutation burden (TMB) was identified with a good prognosis and immune functions. The comprehensive evaluation of cuprotosis patterns in individual LUAD patients enhances the understanding of iTME and gives a new insight toward improved immune treatment strategies for LUAD patients.


Background
Te requirement of copper as a helper for essential enzyme function has been recognized in human cells. However, intracellular copper concentrations are kept very low by active homeostatic mechanisms that work across concentration gradients to prevent the accumulation of free intracellular copper that is detrimental to cells. Te mechanisms of copper-induced cytotoxicity had been well explored [1]. A clear picture of the mechanisms underlying copper-induced toxicity emerged by targeting lipoylated TCA cycle proteins: LA pathway (FDX1, LIAS, LIPT1, and DLD) and PDH complex (DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A).
Immune checkpoint inhibitor therapy (ICT, mainly PD-1/PD-L1 mono-antibody therapy) is promising in the clinical treatment of lung adenocarcinoma (LUAD) [2,3]. However, not all LUAD patients show an efective clinical response or even drug resistance to ICT therapy [4]. In many malignant cancer types, a large number of tumors are intrinsic, [2] for example, the efective responses to ICT therapy occur when the TIME is characterized by a high portion of CD8+ T cells and while none occur when there is low CD8+ T cell infltration [5,6]. It is important to explore the related characteristics with the TIME or tumor immune microenvironment (iTME) of LUAD that drives the ICT efective clinical response [7,8] or even the clinical treatment strategies of immune-oncology therapies [9,10].
In this investigation, we integrated the clinical and molecular data of 461 LUAD cancer patients to comprehensively evaluate the cuprotosis patterns and iTME. Five distinct cuprotosis regulations were identifed, and we were surprised to fnd that they had distinct immune characteristics and prognoses, showing the key roles of cuprotosis in the development of individual iTME in LUAD patients. We then quantifed the cuprotosis of individual LUAD cancer patients by evaluating the gene patterns of cuprotosis regulators.

Molecular and Clinical Data. From the genomic Data
Commons (https://portal gdc cancer gov/.) [11], RNA sequencing data (fpkm and count values) were retrieved for clinical data, genetic mutations, and expression analysis. By consulting an annotation fle, the Ensembl gene IDs from the RNA-seq data were changed into the gene symbols (https:// www.gencodegenes.Org/human/release22.html). Te xena online tool (https://xena ucsc edu/) [12] was used to retrieve the CNV (Copy Number Variation) data. We followed the methods of Zhong et al [13].

Model-Based Clustering Technique for Cuprotosis
Regulators. Model-based clustering analysis, performed in the R package/mclust [14], was used to discover cuprotosis modifcation patterns [15] on the basis of expression of 10 cuprotosis regulators genes. Considering the metric log2 (fpkm +1), gene expression levels were assessed. Te Bayesian information criteria were used in this program to calculate the ideal number of clusters.

Gene Set Variation Analysis.
For investigating the variations in biological procedures among the cuprotosis modifcation techniques, GSVA (Gene Set Variation Analysis), an unsupervised and nonparametric technique that is frequently used to estimate pathway diferences in samples of expression datasets, was applied. From the Molecular Signatures Database, the c2.cp. kegg. v6.2. symbols gene sets were retrieved (MSigDB) for GSVA. p < 0.05 was set for statistical signifcance.

Determination of Diferentially Presented Genes among
Cuprotosis Clusters. We grouped 597 patients into cuprotosis clusters on the basis of expression of 10 cuprotosis genes in order to fnd genes involved in the control of cuprotosis modifcation. Considering the raw fpkm values from the RNA sequencing data, the R/limma program was considered for identifying the DEGs (diferentially expressed genes) in these clusters. Genes with adjusted p > 0.05 are referred to as DEGs with around two-fold alterations in the expression.

Formation of Cuprotosis Gene
Signature. We used a methodology to calculate each patient's unique cuprotosis alteration technique (cuprotosisScore). Following is how the cuprotosisScore was calculated. In order to evaluate the overlapping DEGs, we frst determined the overlying DEGs between cuprotosis clusters and divided LUAD patients into a variety of groups by considering model-based clustering. Te cuprotosisScore was determined as follows. We initially retrieved the overlapping DEGs between cuprotosis clusters and used model-based clustering to split the LUAD patients into several groups in order to analyze the overlapping DEGs. At last, the Genomic Grade Index-like methodology was used to defne the cuprotosisScore [16][17][18]: At last, the Genomic Grade Index was used to defne the cuprotosisScore.

Correlation between cuprotosisScore and Other Related
Biological Procedures. Considering the gene sets presented by Mariathasan et al. [19], Spearman's correlation method was carried out for determining the linkage between cuprotosisScore and other related biological procedures, such as angiogenesis signature, pan-fbroblast transforming growth factor-β response signature, Wnt targets, epithelialmesenchymal transition markers, DNA damage repair, nucleotide excision repair, DNA replication, efector CD8 Tcell signature, mismatch repair, antigen processing machinery (APM), and immune checkpoint.

Statistical Analysis.
In order to assess the statistical signifcance, the Kruskal-Wallis test was considered for three or more groups, and the χ2 test was considered to assess any links between categorical variables. Trough Spearman's correlation analysis, the correlation coefcient was computed. In order to assess the statistical signifcance of diferences, the Kaplan-Meier technique was considered for building survival curves and the log-rank test was considered. Te mutation landscape of the TCGA-LUAD cohort and immunotherapeutic cohort was shown using the oncoplot function of the R package/maftools. p > 0.05 signifcance level was considered for both sides' tests. In every study, the V.4.1.0 (http://www Rproject.org.) was considered.

Te Cuprotosis Regulators in LUAD: Molecular Characteristics and Clinical
Relevance. Based on published literature, cuprotosis is regulated by targeting 10 lipoylated TCA cycle proteins: LA pathway (FDX1, LIAS, LIPT1, and DLD) and PDH complex (DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A) were highlighted. Te frequency of cuprotosis regulator changes in LUAD was investigated using somatic mutations. Only 58 of 567 samples had cuprotosis regulator mutations, indicating that the complete average mutation frequency of cuprotosis regulators was lower (see Figure 1(a)). Te survival curve of the 10 cuprotosis regulators was then examined, and it was shown that 8/10 cuprotosis regulators had a substantial infuence (p < 0.05) on LUAD patients (see Figure 1(b)). Te cuprotosis regulators' mRNA expression levels in LUAD and surrounding tissues were also investigated, and it was discovered that 10 of the 10 cuprotosis regulators were diferently expressed with p < 0.05 (see Figure 1(c)). For clinical relevance evaluation, we execute a Cox model which shows that overall, 10 cuprotosis genes have HR score � 0.6 (see Figure 1(d)). Te expressional and genetic diferences in cuprotosis regulators were signifcantly diverse between LUAD and surrounding tissues, indicating that cuprotosis regulator expression imbalance plays a critical role in the formation and progression of LUAD.

Te Cuprotosis Modifcation Patterns Mediated by 24
Cuprotosis Regulators. Te 10 cuprotosis regulators' expression was used to categorize LUAD patients using modelbased clustering. We found fve diferent RNA methylation modifcation patterns (called cuprotosis clusters mc1-mc4), with 118 cases in mc1, 129 cases in m6c2, 53 cases in mc3, 53 cases in mc4, and 85 cases in mc5 (see Figure 2(a)). Two risk factors for overall survival (OS) (CDKN2A and GLS) were among the cuprotosis regulators with the largest variations across subtypes. As a result, it is no surprise that mc4 had a poor prognosis (see Figure 2(b)).
Te limma program of R software was used to fnd 23 DEGs associated with the copper apoptosis subtype. Te prognosis of 10 genes in the copper apoptosis subtype associated DEGs was assessed using a univariate Cox regression analysis. Te network activity of 23 DEGS was investigated (see Figure 2(c)). Based on fve copper clusters, the therapy sensitivity of chemotherapy was evaluated (see Figure 2(d)), with signifcantly diferent IC50 among fve cuprotosisClusters (p < 0.001). Torsson et al. [20] investigated the pan-cancer immune landscape and eventually found the six immune subtypes (C1-C6) considered for determining the immune response patterns and have consequences for future immunotherapy research. In most LUAD patients, the immune subtype C3 was enriched, which is characterized by lower levels of overall CNVs in Figure 2(e). For a more detailed description, we execute 23 new DEGs as the same as Figure 2(c) for network plot in Figure 2(f ).

Molecular Subtype Identifcation in Distinct Cuprotosis
Modifcation Patterns. In comparison to the other clusters, cuprotosisCluster-mc1 had a higher level of TMB, overall CNVs, and specifc lnc-and m-RNA expression profle (see Figures 3(a), 3(b), and 3(c)). Te aneuploidy score and overall CNVs were highest in cuprotosisCluster-C2, and low in cuprotosisCluster-C3. For further exploration, diferent cuprotosisCluster subtypes with potential predictive biomarkers and functional pathways were characterized. Subtype-specifc upregulated or downregulated biomarkers were found by starting with diferential expression analysis (DEA). Te most DEGs sorted by log2Fold are chosen as the biomarkers for each cuprotosisCluster subtype. Tese biomarkers should pass the R/limma analysis to identify subtype-specifc downregulated Figure 3(d) in left and upregulated in right biomarkers.
Similarly, GSEA is run for each subtype based on its corresponding DEA result to identify functional pathways using a gene set background which includes all gene sets derived from GO biological processes (c5. bp.v 7.1. symbols. gmt). Heatmap analysis of subtype-specifc downregulated biological pathways is given (see Figure 3(e) top) using limma package for fve identifed subtypes in LUAD and upregulated pathways (see Figure 3(e) bottom).

Construction of the Cuprotosis Gene Signature and Evaluation of the Molecular and Immune Landscape Was
Signifcantly Associated with cuprotosisScore. Te immunological properties of various cuprotosis modifcation patterns were next investigated in further detail. 23 genes associated with signifcant prognoses were extracted for further PCA analysis to establish the copper apoptosis gene signature. From the visualized box plot (see Figure 4(a)), we could fnd a positive diferentiation (p < 0.05) between these fve CopperClusters. Furthermore, the Student's t-test showed a signifcant diference in cuprotosisScore among cuprotosis clusters. It was shown that CopperScore was not positively correlated with AS (see Figure 4(b)). We used the cuprotosisScore approach to properly assess the cuprotosis alteration pattern in individual LUAD patients. Te limma program of R software was used to fnd 23 DEGs associated with the cuprotosis subtype. Te activity of KEGG pathway processes was investigated using GO analysis among these diferent cuprotosis modifcation patterns. In DEGs and Cox regression, substantially DEGs were notably enriched in pathways linked to non-small cell lung cancer-related terms, such as p53, MAPK, and PI3K-Akt signaling pathway, as depicted in Figure 4(c). Meanwhile, immune-related pathways such as the IL-17 signaling pathway were shown to be overrepresented among the implicated pathways.
Multiple IM antagonists and agonists are studied in clinical oncology since IMs are important for ICT therapy. Understanding their expression in diverse copper apoptosis alteration patterns is required to progress this research. Te functions based on the expression of IM genes in the copper apoptosis subtypes were investigated (see Figure 4(d)). Almost all functions were strongly expressed in mc1, especially in immune functions, such as T function, B function, APC processing, and macrophage functions. Using the cibersort algorithm, the bar plot of immune cells in LUAD tissues is   Journal of Oncology shown in Figure 4(e). Te heatmap of immune-related genes shows higher expression in mc1 than mc2345 cancer samples as shown in Figure 4(f ).

Discussion
Published research studies had reported that cuprotosis genes showed their crucial biological and clinical functions on tumor development, clinical therapeutic resistance, and immune-oncology response via cross-work among the cuprotosis regulators. Currently, the efects of modifcation patterns on the TIME were explored in some cancer types.
[1] In our study, the role of cuprotosis modifcation in the immune landscape of LUAD was profled to deepen our knowledge of the immune-oncology response based on LUAD iTIME and provide more potentially efective ICT clinical treatment strategies. Based on molecular genotyping by genomic profling [21,22], the future clinical application for LUAD patients has been improved. In this study, fve cuprotosis modifcation clusters with signifcantly distinct TIME were identifed based on 10 cuprotosis gene regulators, including diferent drug treatment sensitivity, the diferences in aneuploidy, overall somatic copy number variation, and expression level of the immune-related genes and clinical prognosis (OS). In our study, cuprotosiscluster-mc1 showed enrichment pathways related to full immune activation and relatively high T-cell function, suggesting high tumor growth rates in mc1. Accordingly, it was not shown that C3 exhibited deactivated immunity but a poor survival prognosis. For the clinical application of LUAD patients, we applied a methodology, known as cuprotosisScore, of individual LUAD patients, to exactly indicate the cuprotosis methylation level. After an integrated analysis, it was revealed that cuprotosisScore can be a potential and independent prognostic factor for LUAD patients. In this study, we verifed the clinical value of the cuprotosisScore in the cold immune status (cuprotosiscluster C3) LUAD patients. As is known, the pre-existing CD8+ T cell infltration and a high TMB drive the response to anti-PD-1/PD-L1 ICT therapy. [23] Tus, combined with our results, the cupro-tosisScore may serve as a potential indicator for ICT therapy.
Finally, this investigation discovered a link between cuprotosis alteration, tumor mutation burden, and the immunological landscape of LUAD tumors. Our in-depth analysis of cuprotosis alteration patterns in individual     Journal of Oncology LUAD patients adds to our knowledge of the tumor immunological landscape and paves the way for novel and better immunotherapeutic methods for LUAD patients. With consideration of the lack of clinical cohorts to verify our current results, further validation based on large-cohort prospective clinical trials is needed in future exploration.

Ethical Approval
All methods were performed in accordance with the relevant guidelines and regulations.

Conflicts of Interest
Te authors declare that they have no conficts of interest.

Authors' Contributions
TTL and LLC contributed to the study conception; TTL, XYJ, TYZ, and HJH conducted the data analysis and were responsible for writing the frst draft of the paper. LQ, HB, and JCD revised the paper; and all authors read and approved the fnal version of the manuscript.