Colorectal cancer is the third most common cancer in the world (Stoffel and Yurgelun, 2016). It is also one of the main causes of cancer deaths in both men and women globally (Drewes et al., 2016). The possible link between inflammation and tumors was first revealed in the 19th century by Rudolf Virchow (Hooper et al., 2012). Epidemiological and clinical studies have also shown that patients who have Crohn’s disease and ulcerative colitis, the two major types of inflammatory bowel disease, are at increased risk of colorectal cancer (CRC) (Rizzo et al., 2011). The gut is particularly rich in human microbes, and bacteria disrupt the homeostasis by activating immune signaling pathways, leading to an inflammatory environment (Brennan and Garrett, 2016). Tumor microenvironment plays an important role in the growth and development of tumors (Esteva et al., 2019; Strasser and Birnleitner, 2019). Inflammation can cause the aggregation and activation of immune cells, and the activated immune cells promote the proliferation of tumor cells by secreting pro-inflammatory cytokines and chemokines (Ferrari et al., 2019). Therefore, the relationship between inflammatory response and the immune microenvironment of colorectal cancer has attracted much attention. In this study, we screened out the inflammatory response genes related to the prognosis of intestinal tumors and constructed an inflammatory response risk score model. Enrichment of the model-related pathways was examined. Furthermore, we screened out the genes which may influence immune cell infiltration using the inflammatory response risk score model. The purpose of this study was to examine the relationship between inflammatory response and intestinal tumor immune microenvironment at the genetic level.

During tumor development, changes observed in the tumor sites resemble chronic inflammation, a process described as “a tumor is an unhealed wound” that promotes tumor survival (Grivennikov et al., 2010). Studies have shown that chronic inflammation is the leading cause of many cancers in humans (Bernstein et al., 2001). Although inflammation can be used as a strategy against microbes, it is also thought to be a marker of cancer and plays a key role in tumorigenesis. Inflammatory response plays a decisive role in different stages of tumor progression, including initiation, promotion, malignant transformation, invasion, and metastasis (Grivennikov et al., 2010), and can promote carcinogenesis by inducing gene mutations, stimulating angiogenesis and cell proliferation, or inhibiting cell apoptosis (Rutter et al., 2004). Inflammation-related genes are involved in these processes and act on corresponding pathways or regulate immune cells. Our study screened the inflammatory response genes associated with CRC and identified the core genes, among which CX3CL1, CCL22, SERPINE1, LTB4R, XCL1, GAL, TIMP1, ADIPOQ, and CRH were closely related to the prognosis of patients. CX3CL1 can induce the ERK pathway and cell proliferation, and also plays a specific tumor promoter role in breast cancer expressing ERBB2 (Tardáguila et al., 2013). CCL22 is a chemokine that is highly expressed in tumors, and promotes tumor growth, in addition to playing a role in tumor-related immunosuppression (Wiedemann et al., 2016). SERPINE1 and TIMP1 promote the migration and invasion of tumor cells (Song et al., 2016a; Klimczak-Bitner et al., 2016). SERPINE1 may also promote the invasion and metastasis of colorectal cancer (Simone et al., 2015). LTB4R is a potent chemoattractant involved in inflammatory and immune responses to the paeoniflora-like signaling pathway (Wilson et al., 2014), which is involved in all inflammatory diseases (Peters-Golden and Henderson, 2007). XCL1 promotes antitumor activity (Chou et al., 2020), and XCL1 expression is also significantly related to the number of tumor infiltrating CD8+T cells as well as the expression of PD-L1 in tumor cells (Tamura and Yoshihara, 2020). GAL methylation status may be an important marker for predicting clinical prognosis in patients who are with head and neck squamous cell carcinoma (Misawa et al., 2017). ADIPOQ gene play a role in chronic inflammation and cancer (Divella et al., 2017). CRH expression is associated with the advanced stage of ovarian cancer (Minas et al., 2007). It can be seen that these inflammatory response-related genes are closely related to tumors. Accordingly, we chose these nine genes to build an inflammatory model.

Inflammatory responses are associated with poor prognosis in a variety of tumors (Minas et al., 2007; Sano et al., 2018; Zhang et al., 2019). In order to further examine the relationship between the model and prognosis of patients, we evaluated the prognosis of patients by taking the product of the expression level and expression coefficient of the nine genes in the model in the two databases as the risk score. Significant differences in prognosis were found in the high-risk and low-risk groups, and patients in the low-risk group lived significantly longer than those in the high-risk group. However, in the process of using ROC curve to evaluate the accuracy of survival analysis, we found that the AUC value did not change much with the extension of time in the TCGA and GEO databases. This indicates that the accuracy of the ROC curve to evaluate survival was not ideal, which may be related to the following factors: First, the survival rate of CRC is 73.8% (70.0% for rectal cancer, 75.9% for colon cancer) (Fatemi et al., 2015), five- year survival rate is 68.4% (Kong et al., 2019), and average survival time is 142.17 ± 21.60 months (Fatemi et al., 2015). However, we evaluated 1-, 3-, and 5-years survival. Therefore, the survival situation could not be accurately reflected. Second, the sample was relatively small. Third, TCGA and GEO databases were selected for this study, and the predictive and prognostic accuracy of this model needs to be verified using multiple databases. Lastly, adjuvant therapies such as surgery and chemoradiotherapy also have an impact on the prognosis of patients (Fatemi et al., 2015). This study analyzed the impact of age, sex, T, M, N stage, and risk score on the prognosis of patients, and found that the risk score had a corresponding impact on the prognosis of patients in both databases. However, in the multivariate analysis, the p value of the risk score in the GEO database was >0.05, indicating that the risk score could not be used as an independent prognostic factor. On further examination, we found that all colorectal cancer types in the GEO database were adenocarcinomas, and the samples were all from France. Because of the limitations of tumor types and sample sources, the results may not accurately reflect the effect of inflammatory response on prognosis of colorectal cancer patients. Some patients had received chemotherapy, and the prognosis of CRC patients is related to the depth of tumor invasion, presence of lymph node metastasis (Haq et al., 2009), presence of other diseases, presence of venous or lymphatic invasion, tumor grade (Zlobec and Lugli, 2008), and genetic factors. These factors were not taken into account in this study, which is a limitation.

Furthermore, by using GSEA enrichment analysis to study the pathway enrichment in the high-risk groups and low-risk groups in the two databases. The study showed that the enriched pathways were mostly associated with hypoxia, inflammatory factors, and apoptosis.

Hypoxia and inflammation are closely related (Biddlestone et al., 2015). The inflammatory environment itself tends to be hypoxic (Watts and Walmsley, 2019), possibly because the metabolically active cells such as neutrophils migrating from the peripheral blood to the inflammatory tissue consume a large amount of energy (Borregaard and Herlin, 1982; Pollard and Borisy, 2003), and increase the oxygen demand (Rao and Suvas, 2019). Moreover, inflammation often leads to activation of the cellular hypoxia response pathways (Liu et al., 2014). Infection activates keratinocytes, macrophages, dendritic cells, and other cells, leading to the production of inflammatory cytokines (Wong and Goeddel, 1986; Mooney et al., 1990). Hypoxia also increases circulating proinflammatory cytokine levels (Song et al., 2016b). Tumor development has been shown to be associated with the inactivation of apoptosis (Xu et al., 2009). The downregulation of the tumor suppressor gene p53 can lead to reduced cell apoptosis and promote tumor growth (Bauer and Helfand, 2006), which are associated with many cancers (Rodrigues et al., 1990; Gasco et al., 2002). Some scientists also believe that apoptosis drives the proliferation and metastasis of tumor cells (Wang et al., 2013). Thus, there is a close relationship between inflammatory response, inflammatory factors, and apoptosis.

The immune system plays a decisive role in the initial inflammatory response to infection and injury and is the main driver of the inflammatory protective response (Carrillo-Salinas et al., 2019). Therefore, the inflammatory response often leads to the infiltration of immune cells. In our study, the infiltration of 11 types of immune cells including activated dendritic cells, macrophages M0, macrophages M1, neutrophils, activated natural killer (NK) cells, NK cells, plasma cells, CD4 memory T cells, helper T cells, CD8 T cells, and regulatory T cells was significantly differently between the high-risk and low-risk groups in the TCGA database. However, only the infiltrates of activated dendritic cells in the GEO database were significantly different in the high and low risk groups. Subsequently, the genes regulating activated dendritic cells were screened, and it was found that the expression of CCL2 gene was different in the groups with high and low risk in the TCGA and GEO databases. Other studies have also shown that the CCL2 gene is associated with inflammatory responses. CCL2 is a chemokine that attracts and activates monocytes (Conti and Rollins, 2004). CCL2 plays a crucial role in tumor cell growth, metastasis, and host immune response (Zhuang et al., 2018). Additionally, CCL2 has been shown to have both tumor stimulating and antitumor effects. Recent studies have suggested that CCL2 plays a major role in tumor progression and metastasis (Li et al., 2013). CCL2 can enhance the migration and invasion ability of prostate cancer cells (Natsagdorj and Izumi, 2019), as well as induce the invasion of liver cancer cells (Zhuang et al., 2018). High levels of CCL2 expression in various types of tumors are also associated with poor prognosis (Yang et al., 2016); for example, the increased level of CCL2 expression is related to poor prognosis in breast cancer patients (Lebrecht et al., 2004; Fang et al., 2015). Although many studies have elaborated the relationship between inflammatory response and colorectal cancer from the perspective of genetics and pharmacology, few articles have explored the relationship between inflammatory response-related genes and CRC at the genetic level. This study analyzed the relationship between inflammatory response-related genes and colorectal cancer at the genetic level, which can facilitate further research on colorectal cancer.

However, this study only carried out bioinformatics correlation analysis and did not explore the specific mechanism of inflammation response genes affecting prognosis. This study only proved that the risk scoring model established by us was related to prognosis of patients with colorectal cancer patients. Therefore, prospective studies, such as some basic and clinical studies, are needed to explore the specific mechanisms by which the genes we have identified interact with colorectal cancer.

In conclusion, inflammatory response plays a significant role in the prognosis of CRC patients and in the tumor immune microenvironment. Understanding the relationship between inflammatory response and immune cells is conducive to the faster application of effective immunotherapy for CRC treatment in the clinic, leading to an improvement in the prognosis of colorectal cancer patients.