Introduction
Renal cell carcinoma (RCC) is the most common malignancy in the kidneys. There are about 210,000 new patients with this disease worldwide each year, accounting for 2–3% of all cancer cases. Kidney renal clear cell carcinoma (KIRC) or clear cell renal cell carcinoma (ccRCC) is a main histological subtype of RCC, accounting for 80–90% of the total number of RCC patients. There is a poor prognosis for patients with KIRC, which seriously affects their life and health [
1]. Although surgical treatment is effective in the treatment of patients with kidney cancer at an early stage, the recurrence and metastasis may occur in as many as 30% of patients after radical surgery, who have unfavorable survival and prognosis [
2]. Generally, the patient with metastatic renal cell carcinoma (Mrcc) cannot be cured, with the median survival being only 18 months and a low 5-year survival rate. In recent years, some patients with kidney cancer have benefited from the immune checkpoint inhibitors, especially the programmed death receptor-1 (PD-1) and its ligand (PD-L1) inhibitors [
3]. However, the overall effective rate of immunotherapies is less than 40%, and a considerable number of patients cannot benefit from immunotherapies [
4]. As per some analysis results, in addition to the low sensitivity of patients with kidney cancers to immunosuppressants, drug resistance in tumors is also a common reason for the decreased treatment efficiency. Therefore, the survival and prognosis of patients with kidney cancer can be effectively improved by exploring the important biological processes in the occurrence and development of kidney cancer and identifying drugs sensitive to tumor treatment.
The long non-coding RNA (lncRNA) is an RNA with a length of more than 200 bp that cannot encode proteins, and it is extensively distributed in the nucleus and cytoplasm [
5]. In previous, lncRNAs were thought to be the “noise” in the process of gene expression [
6]. However, DERRIEN et al. [
7] found that lncRNAs are produced through a transcriptional pathway similar to that of the coding gene and have similar histone modifications, splicing patterns and exons/ introns. LncRNAs are transcribed from either strand of the coding gene, and they can or not be polyadenylated [
8]. Currently, it has been confirmed in related studies that lncRNAs have a decisive role in RCC. WANG et al. [
9] found that the lncRNA RP11-436H11.5 can be overexpressed in kidney cancer cells OSRC-2, the expression level of the oncogene BCL-W protein is elevated and cell invasion is also enhanced. After these cells are treated with the BCL-W inhibitor ATB-737, cell invasion is reduced; the inhibition is more pronounced at a higher concentration of ATB-737. Meanwhile, HE et al. [
10] analyzed the tissue and plasma samples from 46 patients with RCC, and they found that lncRNA GIHCG increases significantly in the tissue and plasma samples of these patients (
P < 0.01). The lncRNA GIHCG in stage II-IV is significantly higher than that in stage I (
P = 0.028). Besides, the lncRNA GIHCG in Fuhrman G3-G4 is significantly higher than that in Fuhrman G1-G2 (
P = 0.032).
All life activities can be traced back to cell metabolism, which provides an energy source and material basis for cell growth and proliferation. Multiple complex metabolic enzymes may generate abundant small molecules of metabolites during cell metabolism. These small molecules not only exert influence in the classical metabolic pathway, but also fulfill a non-metabolic function as signal molecules. These molecules could connect the extracellular microenvironment factors with the intracellular gene expression information, which would exercise an impact on various features and processes of cells, thus affecting the occurrence and development of tumors.
Copper is an indispensable molecule in cell metabolism. According to recent studies, cuproptosis is induced by its direct combination with components related to lipidation in the tricarboxylic acid cycle (TCA cycle). It may cause the aggregation of 3apidated proteins and the loss of iron-sulfur cluster proteins, which would induce protein toxic stress and cell death in the end [
11]. As is known to all, the mitochondrion is the energy metabolism center of cells, and the TCA cycle in mitochondria is a common metabolic pathway in aerobic organisms [
12,
13]. According to the findings of this study, it can be speculated that cuproptosis, which is different from pyroptosis and ferroptosis, may operate a larger function in predicting the survival of tumor cells and the occurrence and development of tumors. It has been revealed from previous studies that copper ions can be enriched significantly in tumor cells compared with normal cells, but the content of other metal ions (such as iron and zinc ions) is usually lower than the normal value [
14]. In addition, copper can also promote the occurrence and development of tumors by enhancing the metastasis of cancer cells and activating cell proliferation and metabolism [
15]. Supported by the above evidences, we took the lead in using bioinformatics technology to explore the expression differences of cuproptosis-related genes in KIRC tissues, and constructed a clinical prediction model for cuproptosis gene-related long non-coding RNA. In addition, we conducted further exploratory analyses of tumor immune response and mutation load based on this model.
Discussion
Renal cell carcinoma (RCC) is a malignancy from renal tubular epithelium, and its incidence ranks third among all tumors in the urinary system, with an upward trend with each passing year [
23]. Although surgical resection is the most effective method in the treatment of RCC, the majority of patients have progressed to the middle and advanced stages at the moment of diagnosis. Besides, such tumors are not sensitive to radiotherapies, chemotherapies and immunotherapies, and short-term drug resistance may occur during the application of targeted therapies. Thus, RCC patients usually have a poor prognosis [
24,
25].
Therefore, the prediction and treatment of RCC can be promoted by exploring the critical genes and molecules that affect the occurrence and development of KIRC and constructing a stable prognosis model. Recently, the identification of a new cell death mechanism, namely cuproptosis [
11], provides an important approach to inducing cell death, which is different from such traditional cell death methods as apoptosis, ferroptosis, pyroptosis and necroptosis. There are double roles for copper. Specifically, copper fulfills an essential function as a cofactor of enzymes for all animals; however, even a moderate intracellular concentration of copper may be toxic and even induce cell death [
26]. As is revealed from existing studies, cuproptosis is mediated by an ancient mech–nism—protein lipidation. Lipidated proteins are mainly distributed in the tricarboxylic acid(TCA) cycle, in which lipidation may be required for the function of enzymes [
27,
28]. Besides, the relationship between mitochondrial metabolism and cuproptosis sensitivity is further explained in some studies. Specifically, the cells with active respiration and TCA cycles increase the lev17apidatedidated TCA enzymes (especially PDH complex); sulfonyl directly binds copper, which results in the aggregati17apidatedidated proteins and the loss of proteins containing Fe-S clusters, thus inducing heatshockprotein70(HSP70) reflecting acute proteotoxic stress [
11]. However, the growth and proliferation of tumor cells are closely related to the TCA cycle and other basal metabolic processes [
29,
30]. Based on that, it can be boldly speculated that cuproptosis may play a certain role in RCC.
After the KIRC expression profile data, clinical data and mutation spectrum data are downloaded from the TCGA database to conduct integrated analysis, the differential expression of 19 cuproptosis-related genes from normal kidney tissues and tumor tissues is explored at first. Surprisingly, it can be found that there are 16 differentially expressed genes (DEGs) among these 19 cuproptosis-related genes (Fig.
2A), including 14 genes that are highly expressed in normal samples, accounting for more than 90% of DEGs. It suggests that cuproptosis is a low-level activity in RCC cells. If cuproptosis is activated, will the growth of KIRC cells be inhibited? This shall be a question worthy of further exploration!
As per the systematic analysis of lncRNA expression profile, there are many abnormally expressed lncRNAs in RCC [
31,
32], which could cause changes in protein expression and function and corresponding cell signaling pathways. Additionally, these abnormally expressed lncRNAs closely correlate with the occurrence, development, diagnosis, prognosis and drug resistance of RCC [
33,
34],
NLRP3 is a member of the cuproptosis gene family. Related studies found that LincRNA-CoX2, previously known as a mediator of activation and suppression of immune gene expression in innate immune cells, binds TO NF-κB P65 and promotes its nuclear translocation and transcription, regulating the expression of inflammasome sensor NLRP3 and adaptor ASC [
35]. Kumar A et al. found that the expression of NLRP3 and its downstream components (caspase-1 and IL-1β) were enhanced in ccRCC, and LSD2 may be involved in the regulation of NLRP3 immunosomes in cancer cells, which could be a potential target for the treatment of ccRCC [
36].
Another related study showed that pyruvate dehydrogenase E1β subunit (PDHB) may be involved in the occurrence and development of colorectal cancer (CRC) under the regulation of LncRNA maternally expressed gene 3 (MEG3) [
37]. Although there are not many reports on cuproptosis gene-related long non-coding RNA at present, long non-coding RNA, as an important epigenetic regulator, is likely to play an important role in the expression of cuproptosis-related genes [
38].
In this study, an independent prognostic model based on cuproptosis-related lncRNAs is constructed according to the role of cuproptosis and lncRNAs in KIRC. Further, the potential effective drugs for treating KIRC are also investigated based on this model. A total of 197 cuproptosis-related lncRNAs are identified from the TCGA database, which can be employed to explore the prognostic function of cuproptosis-related lncRNAs. As per the results from the TCGA database, the prognostic value of 13 cuproptosis-related lncRNAs is validated, among which 8 cuproptosis-related lncRNAs can be employed to construct the cuproptosis-related lncRNA model to predict the OS of KIRC patients. Moreover, KIRC patients are divided into the high-risk group and the low-risk group based on the median of prognostic risk scores. The results indicate that the high-risk group has a worse prognosis. As per the multivariate Cox regression analysis results, the cuproptosis-related lncRNA model is an autologous risk factor for OS. The ROC analysis results suggest that this model is more effective than most conventional clinical features in predicting the OS of KIRC patients. Furthermore, a nomogram is also plotted to present the perfect concordance between the observation and the prediction 1-, 3-, and 5-year OS rates of the operating system. Finally, there is excellent concordance in the prediction 1-, 3-, and 5-year OS rates of the operating system. There is a higher accuracy for the risk model based on 8 cuproptosis-related lncRNAs independently related to OS of KIRC patients has a higher accuracy. Hence, this prediction model can be employed to identify new biomarkers for subsequent studies.
Additionally, the TIDE algorithm is adopted to predict the likelihood of the immunotherapeutic response. The results indicate that the high-risk group has a larger immune response rate than the low-risk group, which also suggests that immune-related drugs may have better efficacy in the high-risk group in the prediction model. This finding also provides guidance values for the application of immune-related drugs.
Furthermore, the immune and molecular characteristics of different subgroups are also analyzed under the model. The results suggest that there are certain differences in the enrichment and infiltration of immune cells between the high-risk and low-risk groups. Meanwhile, the expression and correlation of common immune-related genes such as PD1 and PD-L1 are also analyzed. The results indicate that there are significant differences in the expression of these important immune-related genes between the high-risk and low-risk groups. In addition, the expression of these genes positively correlates with risk scores.
This model has been verified through the datasets of the TCGA database. However, the ICGC RCC dataset are combined as an external cohort to verify the accuracy and practicability of this model. The survival analysis results demonstrate that there is a significant difference between the high-risk and low-risk groups. Therefore, this model can effectively predict the survival prognosis of KIRC patients.
As is known to all, pathological stage and grade are the decisive factors for the prognosis of KIRC patients. However, the same clinical stage and grade of tumors are not equal to the same prognosis. Therefore, it is of great significance to explore more comprehensive and specific predictive indicators or biomarkers. This cuproptosis-related lncRNA model has been constructed to provide a novel method for predicting the prognosis of KIRC patients. These findings also provide a new insight for exploring the modification process and mechanism of cuproptosis in lncRNAs. In this study, multiple methods are adopted to verify this new model, and hence the optimal model can be properly selected and applied.
However, there are still some limitations in this study. For instance, the biological mechanism of cuproptosis-related lncRNAs is not fully clarified in this model. Therefore, it is necessary to explore the role of lncRNAs and their interaction with cuproptosis-related genes. In summary, the findings in this study provide novel insights for predicting the survival and prognosis of KIRC patients, which may contribute to revealing the process and mechanism of cuproptosis-related lncRNAs. Furthermore, some potentially effective drugs are also preliminarily identified after the construction of this immunotherapy-sensitive model, which brings some implications for the treatment of KIRC patients.
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