Interferon-Inducible Protein 16 (IFI16) is a Prognostic Biomarker and Related to Immune Infiltrates in Renal Cell Carcinoma (RCC)

Background: Renal cell carcinoma is one of the most common and lethal types of cancer within the urinary system. the current challenges include how to diagnose RCC in the earlier stage and the drug resistance to chemotherapy or radiotherapy. Therefore, to investigate the survival rate and immune infiltration in RCC base on gene expression of IFI16 in RCC. Methods: We explored the relationship between the transcription level of IFI16 and clinical data in RCC through various online databases, including ONCOMINE, GEPIA, Timer and COEXPEDIA. Results: In comparison with the corresponding normal tissues, the mRNA expression levels of IFI16 are higher in KIRC tissues (p 0.05), while lower in KICH tissues (p0.05). The mRNA expression of IFI16 has a positive correlation with TNM stage in KIRC(p=8.56e-07) and KIRP(p=0.00078). In KIRC, the higher expression of IFI16 suggests lower OSHR=1.4; P=0.037; Log-rank p=0.037). In KIRP, the higher expression of IFI16 suggests lower DFS and OS (respectively, HR=1.9, P=0.037, Log-rank p=0.034; HR=2.3, P=0.011, Log-rank p=0.0091). In contrast, the expression level of IFI16 has a negative correlation with the tumour purity in KICH, KIRC and KIRP via the Timer database (all, p < 0.05). In KIRC and KIRP, the expression level of IFI16 has a positive correlation with the tumor-infiltrating immune cells (TIICs) (all, p < 0.05), except the macrophages in KIRP. In KIRC, the main TIICs in the arm-level deletion state of the IFI16 gene were B cell, CD4+T cell, Neutrophil, and Dendritic cell, while the main TIICs in the high amplification state were Macrophage (all, p < 0.0001). genes TIICs. the of TIICs the IFI16 TIICs arm-level IFI16 B CD4+T dendritic TIICs


Background
Renal cell carcinoma accounts for 2-3% of all human malignancies 1 and ranks ninth in the most common malignancies in Western countries. It is estimated that more than 338,000 people are diagnosed with RCC each year, with a 22% increase projected by 2020. RCC includes a group of heterogeneous cancers with different genetic and molecular changes that underlie many histological subtypes 2 . Kidney renal clear cell carcinoma(KIRC), kidney renal papillary cell carcinoma(KIRP), and Kidney Chromophobe (KICH) are the most common pathological types in kidney cancer, accounting for 85-90% of all renal malignancies 3 . There are more than 140,000 RCC-related deaths per year 4 .
Due to the development of the surgical procedures and the use of new drugs, the RCC patients' survival rate has been significantly prolonged 5 . However, the current challenges include how to diagnose RCC in the earlier stage and the drug resistance to chemotherapy or radiotherapy.
Therefore, there is an urgent need for more effective biomarkers and therapeutic targets.
IFI16 is an AIM2-like receptor that can sense the dsDNA of some viruses to activate the STING-TBK1 pathway to produce IFN-β6 for antiviral defense 6 . Besides, it has been found to bind with the DNA and form an Inflammasome-cytoplasmic protein complex. It responds to various physiological and pathogenic stimuli, including PAMP and DAMP, and promotes caspase-1 activation and the synthesis of pro-IL-1β/IL-18 7 . It is essential to clean pathogens or damaged cells. Further evidence indicates that IFI16 had been shown to enhance the activation of known p53 target genes (including p21, Hdm2, and bax), thereby inducing p53-mediated cell cycle arrest and human cancer cell apoptosis 8, 9 . Mazibrada et al. 10 established that it significantly reduced the tumor volume of head and neck cancer when IFI16 was overexpressed in tumor cells, accompanied by a decrease in tumor neovascularization and an increase in tumor necrosis area. Wei Lin et al. 11 demonstrated that the expression levels of IFI16 are lower in the liver cancer tissues compared to the healthy tissues. When forced expression of IFI16 in hepatocellular carcinoma promoted apoptosis and decreased cell viability. Studies have shown that the overexpression of IFI16 can significantly inhibit the growth of liver cancer and reduce tumor volume. But, it was found that the expression of IFI16 in oral cancer is up-regulated by activating NF-κB signaling, thereby promoting cell growth and preventing apoptosis 12 13 .The current research suggests IFI16 not only functions as a tumour suppressor gene but also functions as an oncogene. So how does it function in kidney cancer? So far, the bioinformatics analysis has not been used to analyze the role of IFI16 in RCC. Therefore, in this study, we aimed to investigate the expression, prognosis, and immune infiltration of IFI16 in RCC patients via different databases. Our results have important implications to screen biomarkers and guide target therapy in RCC.

Methods
We used a multidimensional analysis strategy to study the expression, mutation, regulation,

GEPIA (Gene Expression Profiling Interactive Analysis) dataset
GEPIA uses standard processing pipelines to analyze the RNA sequencing expression data from 9,736 tumors and 8,587 normal samples from the TCGA and GTEx projects. GEPIA provides customizable features such as dimension reduction analysis, correlation analysis, tumor / normal differential expression analysis, analysis based on cancer types or pathological stages, similar gene detection, and patient survival analysis 15 . We analyzed the correlation between the mRNA expression of IFI16 and the prognosis and tumor stage in RCC through the GEPIA database.

TIMER (Tumor Immune Estimation Resource) analysis
TIMER (https://cistrome.shinyapps.io/timer/) 16 is a comprehensive database to examine the immune invasion of various malignancies systematically. This data set evaluates the abundance of six immune infiltrates cells (CD8 + T cells, B cells, CD4 + T cells, macrophages, neutrophils, and dendritic cells) by using the statistical methods and the pathological estimation methods. We used the database to explore the relationship between the expression of IFI 16 and the abundance of immune infiltrates in RCC. We also explored the relationship between the somatic cell copy number change and the immune infiltration by considering P <0.05 as the cut-off criterion statistically significant.

COEXPEDIA analysis
Co-expression genes of IFI16 were analyzed using the COEXPEDIA database 17 (http://www.coexpedia.org/), which is a database of context-associated co-expression networks inferred from individual series of microarray samples for human and mouse samples based on Gene Expression Omnibus data (https://www.ncbi.nlm.nih.gov/geo/). The generated network was a filtered network for the medical subject heading term 'RCC'. The score for each gene is a summation of edgeweights (Log-likelihood score) to all connected genes in the network.

Function enrichment analysis
Function enrichment analysis has become a common method for high-throughput omics data analysis. It is expected to discover biological pathways that play a crucial role in biological processes, thereby revealing and understanding the basic molecular mechanisms of biological processes. IFI16 and the obtained co-expression genes of IFI16 in RCC were analyzed by Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathway and Gene Ontology (GO) enrichment analysis through the R language "GGplot2" package and the "cluster Profiler" package 18,19 , the p-value < 0.05 was set as the cut-off criteria.

Transcriptional levels of IFI16 in patients with RCC.
In order to determine the difference in IFI16 expression in RCC and normal renal tissues, we analyzed the transcriptional level of IFI16 via the ONCOMIINE database. Figure 1 shows the mRNA expression of IFI16 was observed in 20 different cancer tissues. Compare to the corresponding normal tissues, the mRNA expression levels of IFI16 appear high in 54 study data sets, while appear low in 6 study data sets. In the study of RCC, the mRNA expression level of IFI16 appear high in 7 study data set and only appear low in 1 study data set. As Figure 2 and Table 1 show, the expression of IFI16 in RCC tissues exist significantly higher apart from the healthy renal tissues, and the fold change is greater than 2.
3.2 Relationship between the transcriptional level of IFI16 and clinical pathology and tumor stage in RCC.
Through the GEPIA database, we investigated the expression of IFI16 in different pathological types of RCC. Compared to the corresponding normal tissue, the mRNA expression level of IFI16 in KIRC tissues seem to be higher (p 0.05), while in KICH tissues seem to be lower (p 0.05) ( Figure 3A-B). We  3.5 Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.
To further analyze the specific molecular network of IFI16 in RCC, the co-expression of genes connected with IFI16 functionally was predicted by using the Coexpedia database. As a result, there are 108 genes co-expressed with the IFI16 gene ( Figure 6A and Table 2). The co-expression network of IFI16 has performed the functional enrichment analysis. The results were mainly enriched in certain functions, including neutrophil degranulation, phagocytosis, vesicle-mediated transport regulation, secretory granule membrane, cytoplasmic vesicle lumen, vesicle lumen, actin binding, peptide binding and amide binding ( Figure 6B). The co-expression network of IFI16 has also performed the functional KEGG enrichment analysis. The results were mainly enriched in certain signal pathways, including tuberculosis, toxoplasmosis, phagosome, leishmaniasis, and Fc gamma R-med8ted ( Figure 6C). Studies have shown that IFI16 is poorly expressed in normal kidney tissue.

Discussion
In bioinformatics analysis, we explored the mRNA expression of IFI16 are significantly higher in RCC tissues than the normal renal tissues, and the fold change is greater than 2, which strongly suggests that IFI16 is overexpressed in RCC. By comparing with the corresponding normal kidney tissues, the mRNA expression level of IFI16 expresses higher in KKIRC and KIRP tissues, while lower in KICH tissues. These findings are similar to some previous studies. For example, Overexpression IFI16 was observed in cervical squamous cell carcinoma 12 and oral squamous cell carcinoma 13 . Therefore, we also investigated the relationship between the transcriptional level of IFI16 and the tumor stage in RCC. Due to the increasing TNM stage the level of IFI16 expression are increases in KIRC and KIRP. To sum up, it's reasonable to assume that IFI16 acts as an oncogene in the progression of kidney cancer.
In this case, IFI16 can be used as a biomarker for early screening in RCC.
In this article, we also explored the relationship between IFI16 expression and survival in RCC. The results indicate the positive correlation between the IFI16 expression with DFS and OS in RCC 13,22 .
Furthermore, our study manifested the levels of expression IFI16 positively correlated with TIICs in KIRC and KIRP, while negatively correlated with the tumor purity in RCC. It is well known that higher the purity of the tumor, better the response to treatment and survival will be. Mast cell density has been reported to be highly correlated with the extent of both normal and pathologic angiogenesis, such as the angiogenesis observed in chronic inflammatory diseases and tumors, including gastric cancer and endometrial cancer 23 . An experimental study has demonstrated that interaction between lung cancer cells and macrophages promotes the invasiveness and matrix-degrading activity of cancer cells 24 .To sum up the two results above, IFI16 can act as prognostic biomarker for RCC.
Moreover, due to the association between the TIICs and the tumour prognosis, we investigated the relationship between the transcriptional level of IFI16 and immune infiltration in RCC. The results revealed that the levels of IFI16 expression have a positively correlation with TIICs in RCC, while the negative correlation with macrophages in KICH. Existing studies indicated more TIICs reflects on less response to the treatment and survival. Recently, tumor-associated macrophage infiltration is correlated with angiogenesis and unfavorable prognosis in several kinds of cancer, including gastric cancer, endometrial cancer, and breast cancer [25][26][27] .Combined with the above research results and existing research data, we assume that IFI16 can be used as a biomarker for the diagnosis and prognosis of renal cancer, apart from that it can be used as a potential therapeutic target.
Tumor development and progression are associated with multiple genomic aberrations, which in turn may influence TIICs. In this study, we compared the abundance of TIICs under different mutation states of the IFI16 gene. The result of analysis in KIRC prompt the central TIICs in the arm-level deletion state of IFI16 were B cell, CD4+T cell, neutrophil, and dendritic cell, while the primary TIICs in the high amplification state of IFI16 was macrophages. The high expression of FI16 is positively correlated with the infiltration of macrophages, and the role of macrophages in KIRC require further studies.
Elucidating the underlying mechanism of RCC development is of great significance for the effective treatment of patients with RCC 28 . The co-expression network of IFI16 is used to perform GO and KEGG function enrichment analysis. The results enriched in certain functions including neutrophil degranulation, phagocytosis, the regulation of vesicle-mediated transport, and enriched in certain signal pathways including tuberculosis, toxoplasmosis, phagosome, leishmaniasis and Fc gamma R-med8ted. These results also suggest that IFI16 involves in the immune response and mediates the development of the inflammatory diseases. Therefore, it is essential for us to better understand the interaction between the tumor microenvironment and the TIICs. The characterization of adaptive immune responses seems to become an indispensable prognostic tool in a wide range of cancers and might be more important than the current cancer staging systems 29,30 . It requires further research and exploration.
This study provides evidence for the significance of IFI16 in renal cell carcinoma and the potential role of novel biomarkers. Our results indicate the association between the IFI16 expression with the clinicopathological features, prognosis, and immune cell infiltration in RCC. At the same time, we also identified the co-expressed genes of IFI16 in RCC. These genes play an important role in immunerelated functions and signaling pathways through the functional enrichment analysis, which suggests the gene of IFI16 is not only a prognosis biomarker for RCC patients but also has the possibility to associate with the immune response to RCC. At the same time, our research has some limitations. On the one hand, our results have not been confirmed by the clinical samples. On the other hand, we did not delve into the mechanism of IFI16 in RCC progression. Our results indicate the association between the IFI16 expression with the clinicopathological features, prognosis, and immune cell infiltration in RCC.

Conclusion
As of now, we demonstrated that IFI16 expression can act as a marker of diagnosis and prognosis for patients with RCC, providing important guidelines for the management of RCC patients, which might be associated with the immune infiltration.

Declarations
Ethics approval and consent to participate: Not applicable.
Consent of publicationAll authors have reviewed the manuscript and agree to publish it in its current form.
Availability of data and materialsAll data generated or analyzed during this study are included in this published article.
Competing interestsThe authors declare that they have no competing interests.
Funding: Additional Supporting Information may be found in the online version of this article.

Figure 2
The mRNA expression of IFI16 in RCC tissues and adjacent normal kidney tissues (ONCOMINE).