4.1 Low expression of DOCK2 in lung adenocarcinoma.
In six lung adenocarcinoma studies based on GEO and TCGA databases, DOCK2 expression in lung adenocarcinoma was lower in contrast with that in non-malignant tissues (Fig. 1A-E). DOCK2 also showed low expression in 192 pairs of lung adenocarcinoma and the paired para-carcinoma tissue in GEO, as well as TCGA data resources (Fig. 1F-H). In TCGA data resource, ROC curve was employed to explore the differentiation effect of DOCK2 in lung adenocarcinoma and para-cancerous tissues. The area under the curve of DOCK2 is (AUC) 0.792 (Fig. 1I), indicating that DOCK2 may be a potential molecular marker of lung adenocarcinoma.
4.2 Relationship of DOCK2 expression with clinic-pathological parameters in patients with lung adenocarcinoma.
As the mechanism of DOCK2 in lung adenocarcinoma is not clear, the study of the relationship of DOCK2 expression with clinic-pathological features is helpful to elucidate the role of DOCK2 in lung adenocarcinoma. The data demonstrated that the expression level of DOCK2 was remarkably related with the staging changes of T, M and TNM in the data of TCGA lung adenocarcinoma, as indicated in Fig. 2A, C, D. The patients with high expression of DOCK2 had lower T, M and TNM stages, indicating that DOCK2 may be involved in delaying the progression of lung adenocarcinoma.
Besides, to understand the prognostic impact of DOCK2 expression on lung adenocarcinoma, Cox proportional hazard regression model was employed to explore the prognostic predictors. On the basis of the median value of DOCK2 expression (the median value is 2.448), individuals with lung adenocarcinoma were stratified into two groups: DOCK2 high expression group and DOCK2 low expression group. Univariate analysis illustrated that low DOCK2 expression was related with short OS. Other clinical features, consisting of T, N, M and TNM, were also related to OS. In order to verify the prognostic value of DOCK2 in lung adenocarcinoma, multivariate analysis was performed. The data illustrated that only the expression of DOCK2, as well as TNM stage were independently correlated with OS (Fig. 2E, F), indicating that the expression of DOCK2 is not only helpful in the diagnosis of lung adenocarcinoma, but also plays a better role in assessing the clinical prognosis of patients than T stage, N stage and M stage.
4.3 DOCK2 co-expression network in lung adenocarcinoma.
To understand the biological function of DOCK2 in lung adenocarcinoma, the LindFinder module of LinkedOmics website was employed to detect the co-expression model of DOCK2 in TCGA-LUAD. As illustrated in Fig. 3A, 11013 genes (dark red dots) were positively linked to DOCK2 and 8975 genes (dark green dots) were negatively linked to DOCK2. Figures 3B and 3C represent the the heat maps of the first 50 genes positively and negatively linked to DOCK2, respectively. GO annotations illustrated that the genes co-expressed by DOCK2 were primarily involved in interleukin production, neuroinflammatory response, acquired immune response, leukocyte migration, activation of lymph node cells and so on. As illustrated in Fig. 3E, the KEGG pathway analysis showed autoimmune thyroid disease, Staphylococcus aureus infection, intestinal immune network producing IgA, allograft rejection and so on (Fig. 3F).
These results suggest that DOCK2 expression network has a broad range of influences on immune activation in lung adenocarcinoma.
It is worth to note that the first 50 genes positively related to DOCK2 have a high likelihood of becoming low-risk markers of lung adenocarcinoma, and the HR values of most genes are less than 1. On the contrary, in the first 50 genes negatively associated with DOCK2, most of the genes had HR values greater than 1, suggesting that these genes are risk genes, as shown in Fig. 4A, 4B.
4.4. The relationship of DOCK2 with the level of immune invasion
We searched the TIMER database for whether the expression of DOCK2 affected the level of immune cell invasion in lung adenocarcinoma. Pearson correlation analysis illustrated that DOCK2 expression was positively linked to B cells, CD4 T cells, CD8 T cells, dendritic cells, macrophages and neutrophils (Fig. 5A). In the GSE72094 dataset, the positive relationship of DOCK2 expression with these immune cells in the TCGA-LUAD cohort has also been well verified (Fig. 5B).
We then used ETSIMATE algorithm to analyze if DOCK2 expression was related with the total immune infiltration level of lung adenocarcinoma. The results demonstrated that there was a remarkable relationship of DOCK2 with immune score (Immunescore) in both TCGA and GEO lung adenocarcinoma data sets (Fig. 5C-D). In addition, patients who had high immune scores had poorer OS in contrast with those with low immune scores, which was in agreement with the data of univariate prognostic analysis of DOCK2 expression (Fig. 5E-H).
4.5 the relationship between DOCK2 and immune molecules.
To deepen the understanding of the relationship of DOCK2 with immune infiltration, we studied the relationship of the expression of DOCK2 with diverse immune signals, consisting of immune-related signals, three immunomodulators, chemokines and receptors of 28 types of T lymphocyte studied by Charoentong et al(14).
The correlation between DOCK2 expression and various immune characteristics was abstracted from TISIDB data resource. Figure 6A indicates the correlation of DOCK2 with (TILs) in tumor-invading lymph node cells, including Treg_abundence, Tem_CD8_abundance, NK_abundance, and NKT_abundance. Immunomodulators can be further divided into three groups, which contain immunosuppressants, immunostimulators and (MHC) molecules. Figure 6B shows that the immunosuppressant associated with DOCK2 is CSF1R_exp, TIGIT_exp, BTLA_exp, and IL10_exp. Figure 6C shows that the immunostimulant associated with DOCK2 is TNFSF13B_exp, IL2RA_exp, CD27_exp and CD40_exp. Figure 6D shows that the MHC molecule associated with DOCK2 is HLA- DOA _ exp, HLA-E_exp, HLA- DRB1_exp and HLA-B_exp. Figure 6E demonstrates that the chemokine associated with DOCK2 is CCL19_exp, CCL4_exp, CXCL12_exp as well as CCL18_exp. Figure 6F illustrates that the receptor associated with DOCK2 is CCR4_exp, CCR8_exp, CXCR5_exp and CXCR4_exp.
Hence, this study verified that DOCK2 is widely involved in the regulation of various immune molecules in lung adenocarcinoma and affects the immune infiltration of tumor microenvironment.
4.6 Expression of DOCK2 in lung adenocarcinoma in clinical tissue specimens
We collected tissue samples from 60 cases of lung adenocarcinoma treated by surgical resection at The First Affiliated Hospital of Chengdu Medical College, and DOCK2 expression in lung adenocarcinoma and corresponding non-malignant tissues was assayed by RT-qPCR. The data illustrated that the mRNA with DOCK2 was 0.531 (0.217,1.211), which was lower in contrast with that of 3.284 (2.271, 4.325), Z =-4.999, P༜0.05. (Fig. 7A). DOCK2 expression was remarkably linked to clinical stage and tumor size (P < 0.05) (Table1). Prognostic analysis demonstrated that the patients were stratified into high DOCK2 expression group and low DOCK2 expression group on the basis of the median expression of DOCK2 evaluated by RT-qPCR. The prognosis of low DOCK2 expression group was worse relative to that of high DOCK2 expression group (Fig. 7B). It is consistent with the results predicted by bioinformatics analysis.
Table 1
Correlation between DOCK2 expression and patient characteristics
Characteristics | n = 60 | DOCK2(mRNA) | Chi-square | P-value |
High (n = 30) | Low (n = 30) |
Gender | | | | 0.271 | 0.602 |
Male | 26 | 12 | 14 | | |
Female | 34 | 18 | 16 | | |
Age (year) | | | | 0.069 | 0.793 |
≤ 60 | 35 | 18 | 17 | | |
> 60 | 25 | 12 | 13 | | |
Stage | | | | 5.079 | 0.024 |
I/II | 42 | 25 | 17 | | |
Ⅲ/IV | 18 | 5 | 13 | | |
Tumor diameter (cm) | | | | 4.356 | 0.037 |
≤ 5 | 45 | 26 | 19 | | |
> 5 | 15 | 4 | 11 | | |
Differentiation | | | | 0.606 | 0.436 |
High/moderate | 33 | 15 | 18 | | |
Poor | 17 | 15 | 12 | | |