Introduction

Kidney cancer is the third commonest malignancy of the urinary system and has morbidity and mortality rates of 2.2% and 1.8%, respectively1. Kidney renal clear cell carcinoma (KIRC) is the most common kidney cancer, accounting for 80–90% of total renal cell carcinoma (RCC) cases2. Due to the lack of specific clinical symptoms in the early stage, about 30% of the patients with this disease have metastasis at the time of diagnosis, almost 40% of which are prone to postoperative recurrence3. Meanwhile, advanced metastatic or recurrent RCC has limited treatment, since it is not sensitive to radiation nor chemotherapy. Though targeted therapy has modest improvement over previous cytokine therapies, the outlook for high-risk patients remains poor. Therefore, it is urgent to identify biomarkers for early diagnosis and prognosis of RCC. Epigenetic alterations, such as abnormal DNA methylation, play an important role in the development and progression of kidney cancer, thus, they are considered as potential biomarkers for RCC early diagnosis and for monitoring prognosis.

Runt-related transcription factors (RUNX) are named after the discovery of the developmental regulatory gene runt. They have been reported to be vital in leukemia and solid tumors derived from different organs. To date, RUNX family members (RUNX1, RUNX2, RUNX3) have been revealed in diverse developmental process, including cell proliferation, differentiation and apoptosis4. Abnormal methylation status of RUNX genes has been found in several cancers including prostate cancer5, esophageal cancer6 and breast cancer7, which may affect their expression levels. Some studies considered RUNX1 as not only a tumor-suppressive factor but also an oncogenic factor8,9,10. For instance, in lung cancer, missing RUNX1 was found to result in enhanced proliferation, migration, and invasion of tumor cells11, while it was regarded as a tumor suppressor connected with stabilization of Axis inhibition protein1 (AXIN1) expression12. Meanwhile, high RUNX1 expression level was found correlating with poor prognosis in triple-negative breast cancer13. Furthermore, the evidence has proved that RUNX proteins displayed various post-translational modifications such as acetylation14, methylation15, phosphorylation16 and sumoylation17. All of these contribute to the functional complexity of RUNX genes.

So far, a few studies have investigated the expression profiles of RUNX genes in RCC18,19. However, the relationship between RUNX genes and the onset, progression and prognosis of RCC remains controversial. Therefore, our study aimed to analyze the connection between the expression levels of RUNX genes and clinicopathological parameters of RCC especially KIRC patients by multi-dimensional analysis methods, and conducted a preliminary analysis of their regulation and potential functions.

Materials and methods

Pan-cancer analysis of expression levels of RUNX genes by Oncomine and gene expression profiling interactive analysis (GEPIA)

Initially, pan-cancer analysis was performed to assess the transcriptional levels of RUNX genes in different types of cancer and corresponding normal tissues using Oncomine, including 460, 450 and 447 total unique analyses for RUNX1, RUNX2 and RUNX3 respectively. Oncomine (https://www.oncomine.org/) is a platform that provide solutions for individual researchers and multinational companies with robust peer-reviewed analysis methods as well as a powerful set of analysis functions that compute gene expression signatures, clusters and gene-set modules and that allow extracting biological insights from the data automatically. This database contains 715 datasets, 86,733 normal and tumor samples20. Then, we utilized GEPIA in this study to verify the relationship between the expression of RUNX genes and kidney cancer. GEPIA (http://gepia.cancer-pku.cn/) is an interactive web server for analyzing the RNA sequencing expression data of 9736 tumors and 8587 normal samples from the TCGA and the GTEx projects by using a standard processing pipeline21. In prognostic analysis, we grouped the patients by the median as a cut-off value.

UALCAN, cBio cancer genomics portal (cBioPortal) and CPTAC analyses

Then we obtained and downloaded the clinical and FPKM-standardized RNA-seq data and the clinical information of 531 KIRC patients from the TCGA database. The clinical data were preprocessed by removal of samples without survival status and patients with survival time less than 30 days were also excluded because they might die of non-cancer-related diseases. Furthermore, we performed univariate and multivariate Cox regression analysis to demonstrate the correlations between OS and clinical variables.

After the pan-cancer analysis, we explored the relationship between promoter methylation status and its mRNA expression of RUNX1 gene, using UALCAN and cBioPortal database. UALCAN (http://ualcan.path.uab.edu/index.html) is an interactive web resource for analyzing cancer data and providing gene expression analysis by using TCGA datasets (https://www.cancer.gov) 22. The Beta value indicates level of DNA methylation ranging from 0 (unmethylated) to 1 (fully methylated). Different beta value cut-off has been considered to indicate hyper-methylation (Beta value: 0.7–0.5) or hypo-methylation (Beta-value: 0.3–0.25)23,24. The cBioPortal (http://www.cbioportal.org/) is an open access for interactive exploration of multiple cancer genomics data sets, currently covering 282 cancer researches25. The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC, https://proteomics.cancer.gov/) is a public data portal of proteomic sequence and corresponding genomic sequence datasets. Using CPTAC, we mined the protein expression of RUNX genes.

LinkedOmics analysis and gene set enrichment analysis (GSEA)

After confirming that RUNX1 was associated with prognosis of KIRC, we preliminarily analyzed its specific cytological function and molecular mechanism. LinkedOmics (http://linkedomics.org/login.php) is a publicly available portal that includes multi-omics data from all 32 TCGA cancer types26. LinkedOmics was used to investigate the transcription networks of RUNX1 in KIRC. Data from the LinkFinder results were signed and ranked, meanwhile GSEA was used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways27, transcription factor-target enrichment and kinase-target enrichment. The statistical analyses were based on the Molecular Signatures Database (MSigDB)28; 1000 simulations were performed and False discovery rate (FDR < 0.05) was used to select significantly enriched gene sets.

Ethical approval

No ethical approval was obtained because this study did not involve a clinical evaluation, did not involve laboratory animals and invasive procedures.

Results

Analysis of expression level of RUNX genes in pan-cancer

As shown in Fig. 1, pan-cancer analysis results showed that RUNX1 increased significantly in 58 datasets, especially those of leukemia, head and neck cancer, colorectal cancer, kidney cancer, and breast cancer. As for RUNX2, 24 datasets displayed increased expression, whereas 14 datasets showed the opposite results. Similarly, higher expression of RUNX3 was found in 19 datasets, while lower expression was found in 10 datasets. Overall, the obtained results indicated significantly elevated expression of RUNX1 (with fold changes of 6.58 to 6.51) and RUNX3 (with fold changes of 2.7 to 8.32) in kidney cancer (Table 1).

Figure 1
figure 1

Oncomine analysis of the mRNA expression levels of RUNX genes in different cancers. The differences in expression levels of genes between cancer and normal tissues are concluded. The thresholds (p-value < 0.01, fold change > 2; gene rank < 10%; data type: mRNA) are indicated in the colored cells. Red cells represent overexpression of the target gene in tumor tissues compared to normal tissues, while blue cells indicate downregulation of the gene. Gene rank is depicted by the color depth in the cells.

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Table 1 Differential expression level analysis of RUNX genes in different types of kidney cancer.
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Verification of expression of RUNX genes in kidney cancer

To further verify differential expression of RUNX genes in kidney cancer, we compared expression profiles of each gene between different kinds of kidney cancer samples and paired normal tissues by GEPIA. The results indicated that RUNX1 and RUNX3 were significantly overexpressed in KIRC (Fig. 2A, C). For RUNX2, no significant expression difference was found (Fig. 2B). Furthermore, the relationship between expressions of RUNX1, RUNX2and RUNX3 and prognosis of KIRC were performed by GEPIA and the results revealed that higher expression of RUNX1 had poorer overall survive (OS) in kidney cancer patients (p < 0.001, Fig. 2D). Especially, higher expression of RUNX1 was also found correlated to poor prognosis in KIRC (p < 0.001, Fig. 2E) and KIRP patients (p = 0.024, Fig. 2G), whereas there was no significant relation between RUNX1 and OS in KICH patients (p = 0.27, Fig. 2F). Besides, RUNX2 expression showed significant correlation to the prognosis of KIRC patients (p = 0.046, Fig. 2H), while RUNX3 did not (p = 0.77, Fig. 2I).

Figure 2
figure 2

(A–C) GEPIA analysis results of the mRNA expression level of RUNX genes in different types of kidney cancer. Box plots of individual RUNX expression in KIRC tissues and paired normal tissues, *: p-value < 0.05. (D–I) Correlation analysis between RUNX1, RUNX2 and RUNX3 expressions and overall survival in different types of kidney cancer patients by Kaplan–Meier plotter. KICH: kidney chromophobe renal cell carcinoma KIRC: kidney renal clear cell carcinoma, KIRP: kidney renal papillary cell carcinoma.

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Correlation analysis between RUNX1 and clinicopathological characteristics in KIRC

Table 2 showed the basic clinical characteristics. In total, we identified 531 KIRC patients with RUNX1 expression data and clinical information. The results showed that RUNX1 was highly expressed in female patients and white race. Higher RUNX1 expression was associated with advanced TNM stage and poor histological grade stage. The results were consistent with that RUNX1 might be an unfavorable factor for KIRC patients. Furthermore, we performed Cox regression analysis, and results showed stage and age were significantly associated with OS in KIRC patients (Fig. 3A). Then Multivariate Cox regression analysis showed that stage was an independent factor influencing KIRC prognosis (Fig. 3B).

Table 2 The clinical characteristics about RUNX1 expression in KIRC patients.
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Figure 3
figure 3

Stage and age were significantly associated with OS in KIRC patients. (A) Univariate Cox regression analysis of correlations between OS and clinical variables. (B) Multivariate Cox regression analysis of correlations between OS and clinical variables.

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Analysis of promoter methylation status and protein expression of RUNX1 gene in KIRC

To explore the hinge of RUNX1 expression, we investigated the promoter methylation level of RUNX1 in KIRC by UALCAN. Twelve probes in RUNX1 promoter were used for detecting DNA methylation level of RUNX1 (Fig. 4A). Notably, primary tumor tissues had obviously lower promoter methylation levels than normal tissues (p < 0.001, Fig. 4B). Meanwhile, it was a significant inverse correlation between DNA methylation level of RUNX1 gene and its mRNA expression in KIRC samples (Spearman =  − 0.69, p = 1.33e−46; Pearson =  − 0.60, p = 1.19e−32, Fig. 4C) based on cBioPortal analysis. The results indicated that upregulated expression of RUNX1 was associated with DNA hypomethylation, and it could be considered as a risk factor for KIRC. Surprisingly, the prognosis analysis showed that patients with promoter hypomethylation of RUNX1 had a worse OS (p < 0.001, Fig. 4D). Furthermore, we compared the protein expression of RUNX1 in normal and KIRC tissues, verifying that the expression level of RUNX1 protein was indeed significantly elevated in KIRC (p < 0.001, Fig. 4E).

Figure 4
figure 4

DNA methylation aberration of RUNX1 in KIRC. (A) Probes for detecting DNA methylation of RUNX1 promoter. (B) UALCAN analysis about the promoter methylation levels of RUNX1 in KIRC and normal samples. (C) The correlation analysis between the promoter methylation level of RUNX1 and its expression level based on cBioPortal database. (D) Correlation analysis between the promoter methylation level of RUNX1 and overall survival in KIRC patients by LinkedOmics. The blue line indicated low methylation level of RUNX1, while the red line indicated high level. (E) CPTAC analysis about the comparison of RUNX1 protein expression between normal and KIRC tissues. KIRC: kidney renal clear cell carcinoma.

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Enrichment analysis of RUNX1 gene functional networks in KIRC

As shown in the volcano plot using LinkedOmics analysis (Fig. 5A), red spots represented genes positively correlated with RUNX1 in KIRC, while green spots represented genes with a negative correlation. Furthermore, the top 50 significant gene correlated positively or negatively with RUNX1 were shown in the heat maps (Fig. 5B, C), which suggested a widespread impact of RUNX1 in the transcription. In addition, GSEA showed varying expression of RUNX1 gene mainly in the receptor complex, cell-substrate junction and apical part of cell, which primarily participated in adaptive immune response, leukocyte migration and protein targeting. They played a key role in receptor-ligand activity, protein tyrosine kinase activity, transferase activity, and transferring acyl groups (Fig. 6A–C). KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in proteoglycans in cancer, microRNAs in cancer, focal adhesion and peroxisome (Fig. 6D–F). To further explore the targets of RUNX1 gene in KIRC, we analyzed the transcription factors and kinase targets of positively correlated gene sets generated by GSEA (Table 3). The top 3 most significant kinase target networks related to LYN proto-oncogene, p21 activated kinase 1(PAK1) and HCK proto-oncogene3. The transcription factor target network was mainly related with ETS1, NFKAPPAB, MZF1, IRF, SRF.

Figure 5
figure 5

Genes differentially expressed in correlation with RUNX1 in KIRC by LinkedOmics. (A) Volcano plots in analyzing differential expression genes correlated with RUNX1 in KIRC. (B, C) Heat maps showing genes positively and negatively correlated with RUNX1 in KIRC (TOP 50). Red indicates positively correlated genes and blue indicates negatively correlated genes.

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Figure 6
figure 6

Significantly enriched GO annotations and KEGG pathways of RUNX1 in KIRC were analyzed using GSEA. (A) Cellular components. (B) Biological processes. (C) Molecular functions. (D) KEGG pathway analysis (www.kegg.jp/kegg/kegg1.html). KEGG pathway annotations of the cell cycle pathway. (E) Peroxisome biogenesis, (F) MicroRNAs in cancer. Red marked nodes are associated with the Leading Edge Gene.

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Table 3 Targets transcription factor and kinase of RUNX1 gene in KIRC from Linkedomics.
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Discussions

The RUNX family has been noticed to play an important role in leukemia and solid tumors. Known as one of the most frequently mutated genes in human leukemia, RUNX1 is originally identified to have a role in hematopoiesis29. Increasingly, it has been implicated in cancers of ovary30, prostate31 and stomach32, which was associated with either gain or loss of RUNX1 function. Recently, Yang et al. revealed that higher RUNX1 expression may be associated with poorer survival in RCC33; this was later confirmed by Rooney et al. who utilized a genetically engineered mouse (GEM) model18. According to a recent research from Kamikudo et al., as the RUNX family has a mechanism to compensate for loss among the family members, it is difficult to individually inhibit RUNX family proteins, RUNX family cluster regulation might be a cancer treatment strategy34. However, As Lie-a-ling mentioned, although it has become evident that expression level of RUNX1 can be used as a marker of tumor progression35, it is not yet fully uncovered how the alteration contributes to tumorigenesis, since both the amount and activation status of proteins can have effects. Therefore, we performed comprehensive analyses of the expression levels of RUNX genes in kidney cancer.

Our study showed that compared to normal kidney tissues, the expression levels of RUNX1 and RUNX3 were increased in KIRC cases. Prognostic studies further suggested that higher expression of RUNX1 gene was significantly associated with poorer OS in KIRC. Interestingly, the lower promoter methylation level of the RUNX1 gene was found to be significantly related to its higher mRNA and protein expression and, consequently, to the poorer OS of KIRC. In a research reported by Matsumura T et al., defection of RUNX1 methylation in hematopoietic stem cells (HSCs) was found to inhibit apoptosis and provide cells with a growth advantage, which is one of the important mechanisms to prevent the proliferation of damaged cells and maintain the genomic integrity after DNA damage36. Also, hypomethylation in some sites of RUNX1 can influence the transcription activity, though it remained unclear how promoter methylation of RUNX1 affects the expression status. For RUNX3, the methylation-mediated expression regulation has been observed to play a role in leukemia and solid tumors. Marcos et al. found that RUNX3 hypermethylation was a worse prognosis in leukemia37 and Avci et al. emphasized the methylated allele of RUNX3 as a significant inducer in human brain tumors38. More importantly, Cen et al. found a connection between higher level of RUNX3 methylation and poorer OS in KIRC39. Our results showed significantly elevated expression of RUNX3 in KIRC tissues. However, no significant relationship between the methylation level of RUNX3 and OS was noticed, which deserved further research.

Recent studies have found overexpression of RUNX1 in mouse models of kidney fibrosis, which is related to KIRC, indicating RUNX1 has a regulation of TGFβ-driven epithelial-to-mesenchymal transition (EMT)40. Recently, Young et al. indicated that RUNX1, which had a relationship with multiple signaling pathways including JAK/STAT, MAPK, p53 and VEGF, could be recognized as a novel therapeutic target and prognostic factor41. Kamikudo et al. found that moderate inhibition of RUNX1 most significantly increased the total level of RUNX family through “genetic compensation of RUNX family transcription factors”, emphasized the role of RUNX1 in tumorigenesis42. Furthermore, Zhao et al. manifested that PRMT1-dependent methylation of RUNX1 likely contributed to its inhibitory activity15. Considering our findings, patients with higher transcription levels of RUNX1 had worse prognosis, which corresponded to lower levels of promoter methylation. The results suggested that the promoter methylation of RUNX1 occurred in KIRC cases and deserved to be seen as a potential diagnostic and prognostic marker.

Previous studies suggested that RUNX1 was critical in a variety of genes transcription and played a role in cellular regulation. It has been recognized that genomic instability and mutagenesis are essential features of cancer cells, and kinases and their associated signaling pathways help stabilize and repair genomic DNA43,44. Ballissimo et al. noticed that cells with inefficient RUNX1 showed defects in DNA repair, including base excision, homologous recombination and DNA interstrand crosslink repair45. Sanoji et al. also proved that RUNX1 was involved in cell cycle arrest and apoptosis, as a potential factor in cancer formation46. In order to clarify the role of RUNX1 in KIRC, we tried to locate its target kinases and transcription factors by LinkedOmics, and found an extensive connection with them, indicating that RUNX1 was rather involved in cellular regulation. Furthermore, GSEA was performed to identify significantly enriched or depleted groups of genes. The results showed that RUNX1 was mainly responsible for adaptive immune response, leukocyte migration and protein targeting. In addition, RUNX1 mainly participated in peroxisome, microRNA and proteoglycans in cancers. We assume that these participations are likely to make RUNX1 an initiator of KIRC.

In conclusion, we performed an integrated analysis about the expression and prognostic value of RUNX genes in kidney cancer. Our results showed that RUNX1 and RUNX3 were upregulated in the tissues of KIRC compared to the normal ones. Furthermore, the results revealed that RUNX1 was a potential therapeutic target for KIRC, and that lower promoter methylation level of RUNX1 indicated poorer survival. Generally, we assumed RUNX1 may be a potential diagnostic and prognostic marker for KIRC, and its abnormal promoter methylation may participate in tumorigenesis, which lay a foundation for further study.