the prognosis of colorectal adenocarcinoma: a study based on TCGA

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https://doi.org/10.1007/s12094-021-02602-z RESEARCH ARTICLE

Tumor microenvironment‑associated gene C3 can predict

the prognosis of colorectal adenocarcinoma: a study based on TCGA

Y. Liu¹ · X. Wang¹

Received: 4 February 2021 / Accepted: 16 March 2021 / Published online: 25 March 2021

Abstract

Background Colorectal cancer is one of the most common malignancies. With continuous exploration of the interaction between tumor cells and the immune system, tumor immunotherapy has become a revolution. However, CRC remains one of the less effective tumors for immunotherapy. The tumor microenvironment plays an important role in tumorigenesis and progression. The aim of this study is to explore tumor microenvironment-related genes that can predict the prognosis of colorectal adenocarcinoma, and also to provide new ideas for the mechanism of tumor development as well as immunotherapy.

Methods After estimating Stromalscore and Immunescore of colorectal adenocarcinoma tumor samples according to RNA- Seq expression data downloaded from TCGA, we screened for TME-related differential genes. We filtered prognosis-related core genes by constructing protein–protein interaction networks and making one-factor cox analysis for prognosis. Finally, the relative content of 22 immune cells in tumor tissues was evaluated, and then immune cells associated with core genes were identified.

Results We screened 773 differential genes related to the TME. Then we identified C3 as a core gene associated with prognosis. Single gene analysis showed that C3 expression was significantly higher in tumor tissues than in normal tissues (p < 0.001). High C3 expression was associated with lower overall survival (p = 0.046). Tumor immune cell analysis showed that mast cells resting, mast cells activated, T cells CD4 memory activated, eosinophils, and macrophages M0 were C3-associated immune cells.

Conclusions C3 has potential as a biomarker for colorectal adenocarcinoma and could provide new research ideas for the diagnosis and treatment of colorectal adenocarcinoma, especially for immunotherapy.

Keywords Colorectal adenocarcinoma · Tumor microenvironment · TCGA · Immunotherapy · Immune cell · C3

Introduction

Colorectal cancer (CRC) is one of the most common malignant tumors and the leading cause of cancer-related deaths.

According to a statistical study, CRC is the third most common malignant tumor and ranks second in mortality worldwide [1]. In recent years, the proportion of CRC patients under 50 has been increasing [2, 3]. Apart from genetic factors, the occurrence of CRC is also related to environmental factors such as diet, lifestyle, and obesity [4–6].

The treatment and prognosis of CRC are closely related to gene expression, and common predictive biomarkers include

RAS genes, BRAF gene, and microsatellite instability. At a molecular level, chromosomal instability (CIN), microsatellite instability (MSI), epigenetic instability or CpG island methylation phenotype (CIMP) are three molecular pathways connected with CRC [7–10]. According to gene expression, the CRC Subtyping Consortium (CRCSC) divides colorectal cancer into four molecular subtypes: CMS1, CMS2, CMS3, CMS4, and this classification has already been used as a predictor in clinical trials [11].

Malignant solid tumor tissues include not only tumor cells, but also tumor-associated normal epithelial and stromal cells, immune cells, vascular cells, etc. These cells and their associated substances constitute the tumor microenvironment (TME). TME has an important and complex role in the development of tumor. It has been demonstrated that stromal cells have an important role in tumor growth, disease progression and drug resistance [12–14]. Infiltrating

* X. Wang

qiluwangxw@163.com

1 Department of Medical Oncology, Qilu Hospital of Shandong University, Jinan, Shandong, China

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immune cells play different roles in different tumors. For example, infiltrating T lymphocytes in TME have a tumor suppressive role in ovarian cancer [15]; whereas, infiltrating immune cells are associated with tumor growth, invasion and metastasis in CRC [16]. Therefore, assessing the infiltration of immune cells and stromal cells in TME is relevant for the diagnosis and prognostic evaluation of tumors.

So in this study, we aimed to explore crucial genes which play important roles in TME and prognosis of colorectal adenocarcinoma.

Material and methods

Data acquisition

We downloaded the colorectal adenocarcinoma RNA-Seq expression data from The Cancer Genome Atlas (TCGA, https:// portal. gdc. cancer. gov/) as well as clinical data. The RNA-Seq expression data included 39 normal samples and 398 tumor samples, and the clinical data of 385 patients involved follow-up time, sex, age, and TNM stage.

Tumor microenvironment analysis

All statistical analyses were finished by R (v.4.0.2). Exclud- ing the low-expression RNA-Seq expression data, the esti- mate package was applied to the tumor samples for Stro- malscore and Immunescore. The samples were divided into low-dozen and high-dozen groups. Kaplan–Meier (KM) survival analysis was performed to evaluate the effect of Stromalscore and Immunescore on survival. Because colorectal adenocarcinoma has a relatively good prognosis and follow-up time of some data is too short, we selected the survival data with follow-up time greater than 180 days. Our study also analyzed the relationship between the above-two scores and clinical characteristics.

Differentially expressed genes (DEGs) filter

We divided the tumor samples into high-scoring and low- scoring groups according to Stromalscore and Immunescore, respectively, and the Wilcoxon test was applied for differential gene analysis to screen out the DEGs. |LogFC|> 1 and FDR < 0.05 were considered to be differential. GO enrichment analysis and KEGG enrichment analysis were also performed on the DEGs by applying the clusterProfiler package. The String database (http:// string- db. org/ cgi/ input.

pl) was used to PPI network analysis of DEGs to screen for correlated genes with combined scores > 0.95. We counted the neighboring nodes of each gene. The DEGs with neighboring nodes > or = 10 were selected as the PPI network’s core genes. The top three genes with the most nodes are:

CXCL8, ITGAM and IL10. Then we selected clinical samples with follow-up time greater than 180 days and filtered prognosis-related genes by applying one-factor cox analysis.

The PPI network core genes associated with the prognosis of colorectal adenocarcinoma were obtained through the above analysis, and the genes screened in this paper were gene C3.

And then we applied Cytoscape software to visualize the network of these four genes: CXCL8, ITGAM, IL10 and C3, aiming to show C3 plays a core role.

Single gene analysis

Wilcoxon test was applied to analyze the differences in C3 gene expression between normal and tumor tissues.

We divided tumor samples into low- and high-expression groups according to C3 expression level, and Kaplan–Meier (KM) survival analysis was used to analyze the relationship between C3 gene and overall survival (OS). Also, we applied limma package to investigate the correlation between C3 expression level and clinical characteristics.

C3 gene‑related immune cell analysis

According to the RNA-Seq expression data of colorectal adenocarcinoma, CIBERSORT software was applied to obtain the relative content of 22 kinds of immune cells in each sample. Screen the value of p < 0.05 to improve the accuracy of data. We grouped tumor samples according to the C3 gene expression, and made difference analysis and correlation analysis between C3 and immune cells. The above analysis selected the immune cells associated with C3 gene. In all calculations, p < 0.05 was considered significant.

Results

Data acquisition

Colorectal adenocarcinoma RNA-Seq expression data and clinical data were downloaded from the TCGA website in September 2020. The RNA-Seq expression data consisted of 39 normal and 398 tumor samples. The 385 clinical data age range was 31–90 years, with 180 female patients and 205 male patients. After excluding unknown clinical data, the data were organized, as shown in Table 1.

Tumor microenvironment assessment

Stromalscore and Immunescore were performed on tumor samples. Stromalscore ranged from − 2204.16 to 1685.93 and Immunescore ranged from − 967.41 to 2405.66. Com- bining clinical data, we analyzed the relationship between scores and survival, which showed that Stromalscore and

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Immunescore were not significantly correlated with prognosis (p = 0.226, p = 0.748, respectively). Figure 1a shows that Immunescore was lower in metastatic colorectal adenocarcinoma (p = 0.0035). What’s more, Immunescore was higher in stage I and II colorectal adenocarcinoma tumor tissues than stage III/IV tumor tissues (p = 0.0033) (Fig. 1b). No significant difference was seen between Immunescore and

other clinical data. In addition, Stromalscore was not significantly correlated with clinical features.

DEGs related to tumor microenvironment

According to Stromalscore and Immunescore, we applied the Wilcoxon test to screen TME-related DEGs (|LogFC|> 1, FDR < 0.05). We obtained 1434 Stromalscore-related DEGs and 1011 Immunescore-related DEGs, and visualized the 100 most significantly up-regulated and down-regulated genes (Fig. 2a, b). Then we selected 773 TME-related DEGs, of which 769 were positively related genes and four were negatively related genes (Fig. 2c). GO enrichment analysis of DEGs was performed. It showed DEGs were mainly distributed in collagen-containing extracellular matrix components and were involved in biochemical processes such as T-cell activation, positive regulation of cytokines, and specifically performed molecular functions such as receptor ligand activity and signaling receptor activator activity (Fig. 3a, b). KEGG enrichment analysis showed that DEGs were mainly involved in cytokine–cytokine receptor interaction (Fig. 3c, d).

Prognosis‑associated gene C3 is a core gene of PPI network

String database was applied to PPI network analysis of DEGs, and the genes with the most neighboring nodes were CXCL8, ITGAM and IL10. The 23 genes with neighboring nodes > or = 10 were selected as the core genes (Fig. 4a). On the other hand, one-factor cox analysis filtered 61 genes related to prognosis. Finally, we selected prognosis-associated gene C3 as a core gene of the PPI

Table 1 Patient characteristics

Clinical characteristics Count Percentage (%)

Age 385 (31–90) 100.00

Gender

Male 205 53.25

Female 180 46.75

Stage

I 66 17.65

II 151 40.37

III 103 27.54

IV 54 14.44

T

T1 9 2.34

T2 68 17.71

T3 263 68.49

T4 44 11.46

M

M0 286 84.12

M1 54 15.88

N

N0 231 60.00

N1 88 22.86

N2 66 17.14

Fig. 1 The relationship between Immunescore and clinical characteristics. a Immunescore in non-metastatic and metastatic colorectal adenocarcinoma. b Immunescore in different stages of colorectal adenocarcinoma

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network (Fig. 4b). The Cytoscape software mapping revealed that C3 has a close relationship with the most nodes genes, further demonstrating the role of C3 as a core gene (Fig. 4c).

Single‑gene analysis of C3

By single-gene analysis of C3, we found that C3 expression in tumor tissues was significantly higher than that in normal tissues (p < 0.001) (Fig. 5a). At the same time, KM survival analysis showed patients with high C3 expression in tumor tissue had a shorter OS, meaning high C3 expression predicted a poorer prognosis (p = 0.046) (Fig. 5b). In association with clinical features, C3 expression differed between stage I and IV colorectal adenocarcinoma patients (p = 0.049) (Fig. 5c). At the same time, no significant differences were seen in age, gender, local invasion, lymph node metastasis, and distant metastasis.

C3‑associated immune cells

We applied CIBERSORT software to obtain the relative content of 22 immune cells in each tumor sample and visualized them (Fig. 6a). Through the differential analysis of immune cells, we found that T cells CD4 memory activated, T cells follicular helper, macrophages M0, mast cells resting, mast cells activated, and eosinophils were different in the C3 high and low expression groups (p = 0.012, p = 0.047, p = 0.010, p = 0.009, p = 0.010, p = 0.026, respec- tively) (Fig. 6b). Immune cell and C3 correlation analysis showed that macrophages M1, macrophages M0, mast cells resting, T cells regulatory (Tregs) were positively correlated with C3 expression (p = 0.011, p = 0.0042, p = 0.032, p = 0.0016, respectively), eosinophils, T cells CD4 memory activated, NK cells activated, mast cells activated, dendritic cells activated were negatively correlated with C3 expression (p = 0.034, p = 0.006, p = 0.014, p = 0.026, p = 0.044, respectively) (Fig. 6c, d). In summary, we found that mast

Fig. 2 a Heat map of the top 100 DEGs in low Stromalscore and high Stromalscore. b Heat map of the top 100 DEGs in low Immunescore and high Immunescore. c The Venn diagram shows the DEGs of the

tumor microenvironment. There are four downregulate genes and 769 upregulate genes

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cells resting, mast cells activated, T cells CD4 memory activated, eosinophils, and macrophages M0 were C3-associated immune cells.

Discussion

Studies have shown that mortality from colorectal cancer has slowed in recent years in developed countries, possibly due to its early detection [17]. However, colorectal cancer is still one of the primary cancers worldwide and will continue to put economic pressure on human society. In this study, we explored the DEGs associated with the TME in colorectal adenocarcinoma. We searched for the core genes associated with prognosis among the DEGs, hoping to promote studies in colorectal adenocarcinoma diagnosis, prognosis, and immunotherapy. In this paper, the C3 gene was identified as a PPI network core gene associated with colorectal

adenocarcinoma prognosis, which may be related to the development of colorectal adenocarcinoma.

Correlation of Immunescore with colorectal adenocarcinoma

Immunescore is a scoring system based on the quantita- tive analysis of cytotoxic T cells and memory T cells in the core of the tumor (CT) and the invasive margin (IM) of the tumor [18]. Many studies have shown that tumor immune infiltration is associated with tumor prognosis and sensitivity to treatment [19–23]. Prospective cohort studies have demonstrated that immune cells infiltrating the tumor and higher overall lymphocyte response scores are independent prognostic factors that increase CRC specificity and overall survival [24]. Related studies have shown that immune infiltration and Immunescore are an independent indicator of MSI that can better determine the prognosis of CRC patients and determine whether patients are at high risk of recurrence

Fig. 3 a GO enrichment analysis of DEGs in colorectal adenocarci- noma. b Distribution of DEGs in colorectal adenocarcinoma for different GO-enriched functions. c KEGG pathway analysis of DEGs

associated with colorectal adenocarcinoma. d Distribution of DEGs in colorectal adenocarcinoma for different KEGG-enriched functions

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[25]. In this paper, our study showed that lower Immune- score in advanced metastatic colorectal adenocarcinoma tumor tissues, suggesting that lower tumor Immunescore may predict later clinical stage.

Analysis of core genes

We constructed a PPI network of DEGs and identified 23 closely related genes: CXCL8, ITGAM, IL10, CXCL10, CCR2, CCR5, CCR1, CXCL9, CCL5, CD4, CXCL11, C3,

CCL19, CCL21, CCL4, CXCL13, ITGB2, TYROBP, HLA- DRA, CCL13, CD3E, FCER1G and IL6. Chemokines and their receptors play an important role in the immune system, mediating the activation and transport of immune cells in innate and acquired immunity [26]. To date, 50 chemokines and 20 chemokine receptors have been identified. In malignant tumors, multiple chemokines and their receptors can contribute to tumor development and metastasis through different mechanisms [27–29]. However, chemokines also induce the mobilization and colonization of antitumor

Fig. 4 a PPI network of DEGs. The genes of which connected nodes are over or equal to 10 are chosen. b The Venn diagram shows C3 is a sig- nificant interaction gene and related to prognosis. c The network of these four genes: CXCL8, ITGAM, IL10 and C3

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cells in tumor tissues, thus exerting antitumor effects [30].

The core genes in our screen included a total of 10 genes encoding chemokines, CXCL8, CXCL10, CXCL9, CCL5, CXCL11, CCL19, CCL21, CCL4, CXCL13, CCL13, and three chemokine receptors, CCR2, CCR5, and CCR1.

According to this, we hypothesized that chemokines are the important components of TME and are involved in multiple signaling pathways. CXCL8 is one of the earliest and most well-studied chemokines that is regulated by multiple signaling pathways [31]. It has been demonstrated that CXCL8 is an independent prognostic indicator of colon cancer, and CXCL8 expression is upregulated in colon cancer and its level increases with disease progression or metastasis [32].

The chemokine receptor CXCR3 is expressed on the surface of effector CD8 + T cells, Th1 cells and NK cells and is the

primary receptor driving the recruitment of immune cells to tumor tissue [33]. CXCR3 binds to three known ligands:

CXCL9, CXCL10 and CXCL11. Both CXCL9 and CXCL10 enhances the function of effector Th1 cells, but CXCL11 mediates the suppression of effector T cell function because of its different binding site of CXCR3 [34]. CXCL10 is the most studied ligand for CXCR3 and has potential as a tar- get gene for cancer therapy. One study found that combin- ing CXCL10 gene therapy with radiotherapy improved the therapeutic efficacy in a HeLa cell xenograft tumor model of cervical cancer [35]. In addition, a clinical study of colorectal cancer patients found that elevated serum CXCL10 levels were significantly associated with poor survival in cured patients at all stages, respectively, and was an independent marker for predicting liver metastasis [36].

Fig. 5 a Expression of C3 in normal and tumor tissues. b Kaplan–Meier survival analysis: impact of C3 expression on overall survival (OS) in colorectal adenocarcinoma. c Expression of C3 in different stages of colorectal adenocarcinoma

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ITGAM is an essential oncogenic gene among integrin family members and has been shown to have a pro-tumor- igenic role in renal cell carcinoma and ovarian cancer [37, 38]. The molecular mechanism of ITGAM in colorectal cancer is still unclear. IL-10 is a significant member of the IL-10 superfamily, initially known as cytokine synthesis inhibitory factor (CSIF), but its role in tumor pathogenesis is controversial. On the one hand, IL-10 has a pro-tumori- genic role in melanoma, lung cancer, lymphoma, and higher levels of IL-10 often suggest poor prognosis [39–41]. How- ever, basic experiments have demonstrated that IL-10 has a tumor-suppressive effect in breast cancer and melanoma mouse models [42, 43]. The complex role of IL-10 in tumor development may be related to its involvement in multiple signaling pathways [44]. A clinical study showed that serum levels of IL-10 were elevated in patients with colorectal cancer, and the higher the IL-10 level, the higher the rate of tumor recurrence [45].

High C3 expression suggests poor prognosis

The complement cascade is triggered by different mechanisms that converge at complement 3 (C3) to produce effector molecules that “replenish” antibodies and phagocytes to clear foreign microbes (via C3b), promote inflammation (via C3a and C5a), and lyse pathogens (via the formation of the C5b–9 membrane attack complex) [46]. The complement system is an essential component in maintaining immune homeostasis in the body, and its disruption or dysregulation may lead to autoimmune and inflammatory diseases [47].

C3, as a critical component of the complement system, plays a vital role in the immune process. It has been demonstrated that C3 can promote tumor development through different molecular mechanisms in various mouse models of lung cancer, ovarian cancer, and melanoma [48–50]. An experi- ment evaluated the effects of complement inhibitors on the host immune system using flow cytometry, PCR, and Elisa techniques after injecting the inhibitors to a transplantable murine colon cancer model. The results showed that complement inhibitors eliminated C3 and slowed tumor growth in loaded mice, suggesting that complement depletion therapy may increase immunotherapy efficacy [51]. In this study, C3 was shown to be a tumor microenvironment-associated gene, as well as having a high number of neighboring nodes in the PPI network. We speculate that C3 inhibitors may increase immunotherapy sensitivity in colon adenocarcinoma

patients, but extensive studies are needed before this can be done.

An informatics analysis covering 30 human tumor types showed that the gene encoding C3 was strongly expressed in all cancer types along with the component genes of the classical complement pathway; however, the relationship between C3 and tumor prognosis was unclear. High C3 expression predicted longer survival in mesothelioma, sar- coma and so on, while lower survival in colon adenocarcinoma, non-small-cell lung cancer, and renal clear cell carcinoma [52]. In addition, a study found that the level of C3a was significantly higher in patients with colorectal adenocarcinoma than in healthy individuals [53]. And the level of C3a was significantly lower in CRC patients after treatment [54]. Consistent with our study, high C3 expression in colorectal cancer was associated with a lower OS. What’s more, there was higher expression of C3 in stage IV compared to stage I. All these indicated that C3 may serve as a marker to predict the prognosis of colorectal adenocarcinoma. The mechanism of action of C3 and other components of the complement system in colorectal adenocarcinoma development has not been clarified, and further studies are needed.

Analysis of C3‑associated immune cell

The tumor immune microenvironment is a crucial factor influencing tumor initiation and progression. The tumor’s local immune status depends on the density, composition, functional status, and organization of the infiltrating leukocytes [55]. Binding between complement and receptor can recruit leukocytes and thus change the local immune status of the tumor. Therefore, in this paper, we applied CIBER- SORT to analyze the relative expression of immune cells in colorectal adenocarcinoma tumor tissues and the relationship between infiltrated immune cells and C3 expression.

Our study showed that macrophages M0 and mast cells resting in the tumor tissue microenvironment were positively correlated with C3 expression. In contrast, T cells CD4 + memory activated, eosinophils, and mast cells activated were negatively correlated with C3 expression. An ani- mal study showed that increased C3 immunoreactivity leads to increased macrophages in tumor tissues, which usually preferentially differentiate into a tumor-promoting phenotype [56]. The predominant activation pathway of mast cells is by IgE-dependent activation, but mast cells can also be activated by other pathways such as C3a [57]. In contrast, we have shown that colorectal adenocarcinoma tissues with high C3 expression have a higher proportion of resting mast cells and a lower proportion of activated mast cells, and that there may be a different molecular mechanism leading to reduced mast cell activation than in normal tissues. Eosinophils have been shown to have an antitumor effect in colon cancer [58].

Also, C3a and C5a receptors are present on the surface of

Fig. 6 a Relative proportions of 22 tumor infiltration immune cells (TIICs) subpopulation in tumor samples. b The Violin plot exhibits the expression of TIICs between low C3 expression tumor tissue and high C3 expression tumor tissue. c TIICs which are negatively correlated with C3 expression. d TIICs which are positively correlated with C3 expression

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eosinophils [59]. Although the mechanism between C3 and eosinophils is not clear, we speculate that C3 may inhibit the recruitment of eosinophils through some pathway, thus promoting the development of colorectal adenocarcinoma.

GO enrichment analysis revealed that DEGs are mainly involved in the T-cell activation process. Therefore, among C3-associated immune cells, we are particularly interested in activated CD4 + memory T cells. The pool of memory T cells is a reservoir of T lymphocytes exposed to antigen stimulation, and memory T cells can proliferate and be maintained for a long time after initial exposure to antigen [60]. Thus, memory T cells may lead to long-term immunity to human cancers. In colorectal cancer, the ratio of CD4 + memory T cells decreases with local tumor invasion. Also, in patients with tumor recurrence, the density of CD4 + memory T cells is lower in the primary focus [61].

We found that in colorectal adenocarcinoma tumor tissues, activated CD4 + memory T cells were differential among high and low C3 expression groups, and the relative content of activated CD4 + memory T cells was lower in tumor tissues with high C3 expression. And as the C3 expression content increased, the relative content of activated CD4 + memory T cells decreased. Therefore, we hypothesized that C3 may inhibit the activation of CD4 + memory T cells through certain signaling pathways, which in turn promotes the development of colorectal adenocarcinoma.

Conclusion

In conclusion, we used the TCGA database to identify the TME-related gene C3 as predictive of colorectal adenocarcinoma prognosis and associated with the infiltration of immune cells in the tumor microenvironment. We believe that C3 has potential as a biomarker for colorectal adenocarcinoma and could provide new research ideas for the diagnosis and treatment of colorectal adenocarcinoma, especially for immunotherapy.

Funding Not applicable.

Data availability All relevant data are within the paper.

Code availability All relevant codes are within the paper.

Declarations

Conflict of interest All the authors declared that they have no conflict of interest.

Ethics approval Not applicable.

Consent to participate Not applicable.

Consent for publication Not applicable.

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