Abstract

   Ferroptosis, a newly discovered irondependent form of regulated cell
   death caused by excessive accumulation of lipid peroxides, is linked to
   the development and treatment response of various types of cancer,
   including gastric cancer (GC). Noncoding RNAs (ncRNAs), as key
   regulators in cancer, have both oncogenic and tumor suppressive roles.
   However, studies on ferroptosis-related ncRNA networks in GC are still
   lacking. Here, we first identified 61 differentially expressed genes
   associated with ferroptosis in GC by computing and analyzing gene
   expression profile of tumor and normal tissues for GC. Then, upstream
   lncRNAs and miRNAs interacting with them were found through miRNet and
   miRBase databases, and hub lncRNAs and miRNAs were obtained through
   topological analysis. Finally, the ceRNA regulatory network linked to
   ferroptosis in GC was established, which includes two ferroptosis
   marker genes (TXNIP and TSC22D3), one driver gene (GABARAPL1), and one
   suppressor gene (CAV1). Kaplan-Meier survival analysis showed that
   changes in the expression of these genes were associated with the
   survival of GC patients. Furthermore, our study revealed that this
   ceRNA network may influence the progression of GC by regulating
   ferroptosis process. These results will help experimental researchers
   to design an experiment study to further explore the roles of this
   regulatory network in GC ferroptosis.

   Subject terms: Data mining, Data processing, Gene regulatory networks,
   Genome informatics, Predictive medicine

Introduction

   Ferroptosis, a newly discovered mechanism and unique modality of
   programmed cell death, is driven by the accumulation of a large number
   of iron, free radical production, fatty acid supply, lipid
   peroxidation, and the destruction of intracellular redox
   balance^[38]1,[39]2. It is an irondependent manner of nonapoptotic cell
   death. Many cellular biological processes can alter cellular
   susceptibility to ferroptosis by altering cellular iron contents^[40]3.
   For example, enhancing intracellular iron export makes some cells more
   resistant to ferroptosis^[41]4,[42]5. A study suggests that when
   transferrin expression is silenced, hepatocytes compensatorily
   upregulate SLC39A14 expression, resulting in excessive import of iron
   that then leads to ferroptosis^[43]6. Additionally, numerous signaling
   pathways and cellular metabolic pathways relevant to human disease,
   notably cancer, are driven by ferroptosis^[44]7,[45]8. A growing number
   of studies have confirmed that ferroptosis has been involved in the
   development of a variety of cancer, and plays a critical role in
   inhibiting tumorigenesis^[46]2,[47]9. However, research into
   ferroptosis have just begun in many ways, and the underlying mechanism
   of ferroptosis in cancers, particularly gastric cancer, is poorly
   understood.

   Gastric cancer (CG) is a common and deadly human malignancy that
   seriously threatens the lives and health of millions of people
   worldwide^[48]10,[49]11. With the rapid development of medical
   technology, the diagnosis and treatment of GC have made great progress,
   but patient survival is still poor^[50]12,[51]13. Precision therapy
   remains a challenge. More recently, accumulating evidence indicates
   that ferroptosis is critical for eliminating cancer cells, which could
   open up a new way for cancer therapy^[52]9,[53]14.

   Interestingly, long noncoding RNA (lncRNA) and microRNA (miRNA) are
   increasingly recognized as crucial regulators in the regulation of
   ferroptosis of cancer cells^[54]9,[55]15. The regulatory loop between
   lncRNA and miRNA plays a dynamic role in transcription and translation
   of protein-coding genes, influencing multiple biological processes in
   cancers, such as cell death, cell cycle and
   proliferation^[56]16–[57]18. lncRNAs function as competitive endogenous
   RNAs (ceRNAs) to regulate mRNAs through competitively binding miRNAs,
   therefore forming largescale regulatory networks across the
   transcriptome^[58]17. CeRNA regulatory networks play important roles in
   cancer initiation and development^[59]19–[60]21, as well as have
   significant regulatory effects on the ferroptosis of cancer^[61]22.
   lncRNA NEAT1, as a ceRNA, facilitates ferroptosis in hepatocellular
   carcinoma by controlling miR-362-3p and MIOX^[62]23. MiR-375 can
   trigger ferroptosis to suppress the stemness of GC cells through
   interacting SLC7A11, which could be used as a potential target to
   induce ferroptosis^[63]24. However, the function and molecular
   mechanism of ncRNAs in regulating ferroptosis of cancers remain
   unclear.

   To understand the relationship between ncRNAs and ferroptosis in
   gastric cancer, we constructed a ceRNA network related to ferroptosis,
   which revealed the underlying mechanism of lncRNAs and miRNAs in
   regulating ferroptosis of GC. First, aberrantly expressed genes
   associated with ferroptosis were obtained in GC by transcriptome
   analysis. Further, functional and pathway enrichment analyses were
   conducted to explore the roles of these genes in GC. Then, upstream
   lncRNAs and miRNAs that affected the abnormal expression of
   ferroptosis-related genes were identified, and the four key lncRNAs and
   six miRNAs were found by topological analysis. Finally, these four key
   lncRNAs were revealed to act as ceRNAs to modulate ferroptosis in
   gastric cancer by regulating cancer-related miRNAs and protein-coding
   genes. Collectively, our findings provide new insights into the
   regulation of ferroptosis as a mean of eliminating gastric cancer
   cells.

Results

Identification of ferroptosis-related genes in gastric cancer

   Based on transcriptome data of gastric cancer from the TCGA Cohort, we
   analyzed significantly differentially expressed genes between the 343
   tumor and 30 normal tissues using the negative binomial distribution.
   The 10,658 unique genes were identified. Among them, the 61
   ferroptosis-related genes are dysregulated in GC (Fig. [64]1A and
   Table.[65]SI in Supplementary Information 2). 22 of these 61 genes are
   upregulated (padj < 0.05 and log2FoldChang > 1) and 39 genes are
   downregulated in gastric cancer (padj < 0.05 and log2FoldChang < (−1);
   Fig. [66]1B). Their expression in 343 tumor and 30 normal tissue
   samples is shown in Fig. [67]1C,D.

Figure 1.

   [68]Figure 1
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   (A) The differentially expressed genes (DEGs) associated with
   ferroptosis in gastric cancer. (B) The upregulated genes with
   padj < 0.05 and log2FoldChang > 1 and the downregulated genes with
   padj < 0.05 and log2FoldChang < (−1). (C and D) Heatmaps of 22
   upregulated genes and 39 downregulated genes in 343 tumor and 30 normal
   tissues from GC. The row represents the gene expression value of each
   gene, and the column represents each sample. The redder the color, the
   higher the gene expression value. The bluer the color, the lower the
   gene expression value.

   In order to further understand the biological behavior of these 61
   differentially expressed ferroptosis-related genes in GC, we performed
   the pathway and biological process enrichment analysis, such as KEGG
   Pathway, WikiPathways, GO Biological Processes, Reactome Gene Sets, and
   Canonical Pathways, by Metascape^[70]25 (Fig. [71]2 and Table.[72]S1).
   The result showed that ferroptosis pathway is the most representative
   enriched term, with Log10 (p) equals (−16.00) and Log10 (q) equals
   (−11.65) (Fig. [73]2A), which including CAV1, TXNIP, DPP4, SLC1A5,
   TFRC, NOX1, and NOX4 (Table.[74]S1). It has been indicated that NOX4
   elevation can promote ferroptosis of astrocyte by activating oxidative
   stressinduced lipid peroxidation and impairing mitochondrial metabolism
   in Alzheimer's disease^[75]26 In addition, ferroptosis pathway was
   revealed to be closely related to multiple biological processes, such
   as positive regulation of cell death, fatty acid metabolic process, and
   reactive oxygen species metabolic process (Fig. [76]2B). Moreover,
   Chemical carcinogenesisreactive oxygen species and VEGFA-VEGFR2
   signaling pathway were enriched. These data suggested that the abnormal
   expression of these 61 genes is associated with ferroptosis in gastric
   cancer, and is involved in other biological processes and signaling
   pathways related to tumor.

Figure 2.

   [77]Figure 2
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   The functional and pathway enrichment analysis of 61 differentially
   expressed ferroptosis-related genes. (A) The top 20 enriched ontology
   clusters. The abscissa represents the significant P value of
   enrichment. The color represents the P value, and darker colors
   indicate smaller P values. (B) Network of functional and pathway
   enrichment terms. Each node represents an enriched term and is colored
   by its cluster ID. Those nodes that share the same cluster ID are
   generally close to each other.

Identification of upstream lncRNAs and miRNAs associated with ferroptosis

   According to the information provided by the FerrDb database, 22 of the
   61 ferroptosis-related genes were identified as driver genes that can
   promote ferroptosis, such as MAPK3 and GABARAPL1; 14 genes were
   considered as suppressors, which can prevent ferroptosis, such as
   CDKN1A and CAV1; 33 genes were known as markers that can indicate the
   occurrence of ferroptosis, such as NFE2L2 and TXNIP (Fig. [79]3A).
   Among them, some genes play multiple roles in ferroptosis, with 6 genes
   in both drivers and markers, and 2 genes in both suppressors and
   markers (Fig. [80]3B).

Figure 3.

   [81]Figure 3
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   (A) Classification of differentially expressed genes associated with
   ferroptosis in gastric cancer. (B) Intersection of driver genes,
   suppressor genes, and marker genes. (C) The hub subnetwork between the
   242 DEmiRNAs and 57 ferroptosis-related genes. (D) The hub subnetwork
   between the 20 DEmiRNAs and 83 DElncRNAs. The color of the point
   represents the connectivity of the node in the network. The darker the
   color of the nodes, the more important the genes in the network. (E)
   The top 15 key DEmiRNAs/ferroptosis-related genes in the interaction
   network between the 242 DEmiRNAs and 57 ferroptosis-related genes. (F)
   The top 15 key DEmiRNAs/DElncRNAs in the interaction network between
   the 20 DEmiRNAs and 83 DElncRNAs.

   In order to understand the role of ncRNAs in the ferroptosis of gastric
   cancer, we predicted upstream lncRNAs and miRNAs that interact with 61
   ferroptosis-related genes. Based on the miRNet and miRBase databases,
   thousands of upstream miRNAs were found. Among them, 242 miRNA are
   significantly differentially expressed between tumor and normal tissues
   from GC (p < 0.01 and |log2FoldChang|> 1; Table.[83]SII in
   Supplementary Information 3).These 242 miRNAs can bind to 57
   ferroptosis-related genes, forming 992 interaction pairs. A hub
   subnetwork consisting of 22 differentially expressed miRNAs (DEmiRNAs)
   and 28 ferroptosis-related genes was constrcuted using the topological
   methods in CytoHubba (Fig. [84]3C). These DEmiRNAs and
   ferroptosis-related genes have a relatively high degree and play a key
   role in the network. The top 15 key DEmiRNAs and genes with higher
   degrees were listed, such as CDKN1A, TXNIP, and miR13p (Fig. [85]3E).

   Additionally, the upstream lncRNAs associated with ferroptosis were
   predicted through the miRNet database. 433 lncRNAs were found to
   interact with 20 of the 22 DEmiRNAs. Among these lncRNAs, 83 lncRNAs
   are significantly differentially expressed between tumor and normal
   tissue from GC patients (padj < 0.05 and |log2FoldChang|> 1;
   Table.[86]SIII in Supplementary Information 4). Based on the
   interaction between the 20 DEmiRNAs and 83 differentially expressed
   lncRNAs (DElncRNAs), a hub lncRNAmiRNA subnetwork was constructed by
   topological method. The network consists of 30 DElncRNAs and 20
   DEmiRNAs (Fig. [87]3D). The top 15 key DElncRNAs and DEmiRNAs were
   displayed as in Fig. [88]3F. These key DElncRNAs and DEmiRNAs may play
   important roles in ferroptosis of gastric cancer.

Association between ferroptosis-related genes and survival of gastric cancer

   To explore whether these ferroptosis-related genes affect the survival
   of GC patients, we performed Kaplan-Meier survival analysis. For the 28
   key ferroptosis-related genes in hub network, seven genes were found to
   be associated with patient survival (p < 0.05; Fig. [89]4). The results
   showed that the five-year survival rate of SLC1A5 high expression group
   is higher than that of the low expression group, whereas the five-year
   survival rate of high expression group of other six genes is lower than
   that of the low expression group (Fig. [90]4). For example, patients
   with high expression of RGS4 and TXNIP exhibited a poorer prognosis in
   gastric cancer, while those with high expression of SLC1A5 have a
   better prognosis within five years.

Figure 4.

   [91]Figure 4
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   The Kaplan-Meier survival analysis of ferroptosis-related genes. The p
   value was calculated by the log-rank test.

Construction of ferroptosis-related ceRNA network in gastric cancer

   Based on the ceRNA hypothesis, lncRNAs/mRNAs, as ceRNA molecules,
   function through miRNA response element (MRE) to competitively bind
   with same miRNAs, thereby regulating gene expression to affect cell
   function^[93]17,[94]27. We analyzed the correlation between the
   expression of seven survival-related genes and DEmiRNAs from the hub
   subnetwork (Fig. [95]3C), through the Pearson correlation coefficient.
   The miRNA-mRNA interaction pairs with Corr < 0.5 and p < 0.05 were
   selected, which include the 8 miRNAs and 4 ferroptosis-related genes
   (Fig. [96]5A and Table [97]S2).

Figure 5.

   [98]Figure 5
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   Correlation between the expression of ncRNAs and ferroptosis-related
   genes in gastric cancer. (A) Pearson correlation between the expression
   level (log2-transformed RPM/FPKM value) of upstream DEmiRNAs and
   survival-related genes. (B) Pearson correlation between the expression
   level (log2-transformed FPKM value) of upstream DElncRNAs and
   ferroptosis-related genes. (C) Pearson correlation between the
   expression level (log2-transformed FPKM/RPM value) of upstream
   DElncRNAs and DEmiRNAs associated with ferroptosis. Corr: Pearson
   correlation coefficient.

   Furthermore, Pearson correlation coefficient between the expression of
   these 8 miRNAs and DElncRNAs from the hub subnetwork (Fig. [100]3D) was
   calculated. lncRNA LINC00641, SNHG14, PWAR6, and PART1 showed negative
   correlation with the 8 miRNAs, six of which were statistically
   significant correlated to these lncRNAs (p < 0.05; Fig. [101]5C and
   Table [102]S3). Moreover, these four lncRNAs interacted with the six
   miRNAs. In addition, these four lncRNAs were significantly positively
   correlated with the four ferroptosis-related genes (p < 0.05;
   Fig. [103]5B).

   According to the above analysis, a ferroptosis-related ceRNA regulatory
   network was constructed by Cytoscape (Fig. [104]6), which contributes
   to understand the regulatory role of ncRNAs in ferroptosis of gastric
   cancer. In this network, the six key DEmiRNAs are shared by four key
   DElncRNAs (LINC00641, SNHG14, PWAR6, and PART1) and ferroptosis-related
   genes (CAV1, TXNIP, GABARAPL1, and TSC22D3). Moreover, the expression
   of these four DElncRNAs and four ferroptosis-related genes is
   significantly lower in GC than in normal tissues (Fig.[105]S1).
   Conversely, the expression of six DEmiRNAs is markedly downregulated in
   GC tissues (Fig.[106]S2). These data suggested that the four key
   ferroptosis-related genes are regulated by four key lncRNAs and six key
   miRNAs, thereby affecting ferroptosis in gastric cancer.

Figure 6.

   [107]Figure 6
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   A ferroptosis-related ceRNA regulatory network in gastric cancer.

Validation of a potential ceRNA regulatory network associated with
ferroptosis in gastric cancer

   In the ferroptosis-related ceRNA regulatory network (Fig. [109]6), we
   found that TXNIP, a marker of the occurrence of ferroptosis, can be
   regulated through the interaction of lncRNA PWAR6 and miR-106b-5p. To
   further assess the reliability of the results, we analyzed the
   expression of TXNIP and lncRNA PWAR6 using [110]GSE79973 GC dataset
   from the GEO database, as well as the expression of shared miR-106b-5p
   using [111]GSE78091 GC dataset. These data indicated that the
   expression of TXNIP and PWAR6 is significantly reduced in GC tissues
   compared to normal tissues, and the expression of miR-106b-5p is
   markedly elevated in GC (p < 0.05; Fig. [112]7A). The target sites in
   TXNIP and PWAR6 were predicted to pair with miR-106b-5p by TargetScan
   analysis (p < 0.05; Fig. [113]7B). These results further demonstrate
   that lncRNA PWAR6, as a competitive endogenous RNA, affects the
   expression of TXNIP by competitively binding miR-106b-5p, which plays a
   critical role in the ferroptosis of GC.

Figure7.

   [114]Figure7
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   The validation of a ferroptosis-related ceRNA network. (A) The
   expression of TXNIP and lncRNA PWAR6 is downregulated in GC tissues
   compared to normal tissues, and miR-106b-5p is upregulated in GC. The p
   value was calculated using t-test. (B) The binding sites of shared
   miR-106b-5p with TXNIP and PWAR6.

Discussion

   Ferroptosis is a recently emerged irondependent nonapoptotic cell death
   cascade that can eliminate cancer cells in a nonapoptotic manner, and
   is considered a key target for the development of anticancer
   therapies^[116]7,[117]28. However, the mechanism that regulates
   ferroptosis remains unclear. Therefore, the discovery of key factors
   regulating ferroptosis in cancer has great clinical implications.

   With recent advances in research into cancer biology, accumulating
   studies have shown that ncRNAs, especially lncRNAs and miRNAs, are
   important mediators in the regulation of ferroptosis and iron
   metabolism^[118]29,[119]30. In this study, we obtained 22 upregulated
   and 39 downregulated genes associated with ferroptosis in gastric
   cancer, and identified the upstream DElncRNAs and DEmiRNAs that
   interact with these genes. For example, SLC1A5 was found to be an
   upregulated gene associated with ferroptosis in GC and related to
   patient prognosis (Fig. [120]1 and [121]4), which is consistent with
   the study of Xiang et al.^[122]31. Moreover, both our work and the
   study by Xiang et al. showed that hsa-miR-125b-5p can target SLC1A5
   (Fig. [123]3), which may play an important role in the targeted therapy
   of GC. Besides SLC1A5, our study also found that 6 of the 61 abnormally
   expressed ferroptosis-related genes were associated with the prognosis
   of GC, which include CAV1, GABARAPL1, TSC22D3, PRKAA2, RGS4, and TXNIP
   (Fig. [124]4). The study further revealed that TXNIP, CAV1, GABARAPL1,
   and TSC22D3 may play key roles in the regulation of ferroptosis in GC.
   TXNIP, a metabolic protein, has been considered to be a tumor
   suppressor gene in various malignant tumors, and its overexpression can
   suppress the growth and metastasis of cancer cells in tumor transplant
   models^[125]32. TXNIP is downregulated in GC than in normal tissues and
   has been shown to be a key marker for the prognosis of patients with
   gastric cancer^[126]33. We confirmed similar results by multiple
   statistical methods and KM analysis. However, to our knowledge, few
   studies have explored ceRNA regulatory network related to ferroptosis.

   The ceRNA regulatory networks play important roles in the initiation
   and progression of cancer^[127]34. Here we identified a key
   ferroptosis-related ceRNA regulatory network comprising 4 lncRNAs, 6
   miRNAs, and 4 ferroptosis-related genes in gastric cancer. This study
   found that PWAR6, LINC00641, SNHG14, and PART1 are markedly
   downregulated and involved in ferroptosis of gastric cancer. Similarly,
   Yang et al. indicated that LINC00641 is underexpressed in glioma cells,
   its overexpression inhibits cell proliferation but promoted apoptosis,
   and functions as a ceRNA in glioma cells by absorbing miR-4262 to
   regulate NRGN^[128]35. Moreover, we found that these four lncRNAs are
   regulated by six key miRNAs, such as miR-106b-5p, miR175-p, and
   miR-200b-3p, which are involved in the regulation of ferroptosis and
   possibly serve as candidate biomarkers for the prognosis and treatment
   of gastric cancer. Although all of these results provided evidence for
   the roles of these four key lncRNAs and six miRNAs in ferroptosis, more
   experimental studies are needed to confirm their mechanisms in gastric
   cancer.

Conclusions

   In conclusion, we analyzed the relationship between ncRNAs (lncRNAs and
   miRNAs) and ferroptosis in gastric cancer from the perspective of
   bioinformatics, and found an important ferroptosis-related ceRNA
   regulatory network, key lncRNAs and miRNAs that play critical roles in
   CG progression and affect the prognosis of GC patients. Hence, it will
   be important to validate the molecular mechanisms of these key lncRNA
   and miRNA regulators in ferroptosis of GC by experimental methods in
   the future. Our findings will provide references for proposing new