Expression levels of ELFN1 in COAD
The mRNA expression profiles of ELFN1 in both tumor tissues and normal colon tissues from the TCGA and GEO websites were explored. It was found the ELFN1 mRNA expression level was significantly upregulated in COAD tissues from the TCGA database (P<0.01) (Fig. 1a). A similar result could be seen in 41 matched tumor and normal colon tissues from a TCGA cohort (P<0.01) (Fig. 1b). The high ELFN1 mRNA expression level in tumor samples was also verified in GSE39582 and GSE146009 cohorts (P<0.01) (Fig. 1c, d). Simultaneously, ELFN1 was also highly expressed in several types of cancers, such as esophageal cancer, stomach cancer, and breast cancer by bioinformatic analysis for the resting 32 cancer types (Additional File. 1a).
Association between ELFN1 mRNA expression and clinicopathological characteristics
The ELFN1 mRNA expression levels of 446 COAD samples from the TCGA database in different clinicopathological parameters were presented (Table. 1).The association between ELFN1 mRNA expression level and clinicopathological parameters was analyzed. The outcomes manifested that high ELFN1 mRNA in COAD had a positive association with the advanced Tumor stage (IV vs. I; IV vs. II), T stage (T4 vs. T2), N stage (N2 vs. N0; N2 vs. N1), M stage (M1 vs. M0), Lymphatic metastasis (YES vs. NO), Vascular invasion (YES vs. NO) and Perineural invasion (YES vs. NO) (P<0.05) (Fig. 2a-g). However, no association was seen between ELFN1 mRNA expression and the patient's Age, Gender (P>0.05) (Fig. 2h-i).
Table1. Clinicopathological characteristics of 446 samples from the TCGA cohort.
|
|
ELFN1 expression
|
|
Characteristic
|
Type
|
High
|
Low
|
Total
|
Age(years)
|
<=65
|
94(42.15%)
|
88(39.46%)
|
182(40.81%)
|
|
>65
|
129(57.85%)
|
135(60.54%)
|
264(59.19%)
|
Gender
|
Female
|
113(50.67%)
|
99(44.39%)
|
212(47.53%)
|
|
Male
|
110(49.33%)
|
124(55.61%)
|
234(52.47%)
|
Vital status
|
Alive
|
171(76.68%)
|
187(83.86%)
|
358(80.27%)
|
|
Dead
|
52(23.32%)
|
36(16.14%)
|
88(19.73%)
|
pTumor Stage
|
Stage I
|
33(14.8%)
|
41(18.39%)
|
74(16.59%)
|
|
Stage II
|
83(37.22%)
|
93(41.7%)
|
176(39.46%)
|
|
Stage III
|
64(28.7%)
|
60(26.91%)
|
124(27.8%)
|
|
Stage IV
|
36(16.14%)
|
25(11.21%)
|
61(13.68%)
|
|
Unknow
|
7(3.14%)
|
4(1.79%)
|
11(2.47%)
|
pT Stage
|
T1
|
5(2.24%)
|
5(2.24%)
|
10(2.24%)
|
|
T2
|
34(15.25%)
|
42(18.83%)
|
76(17.04%)
|
|
T3
|
152(68.16%)
|
152(68.16%)
|
304(68.16%)
|
|
T4
|
32(14.35%)
|
24(10.76%)
|
56(12.56%)
|
pN Stage
|
N0
|
124(55.61%)
|
141(63.23%)
|
265(59.42%)
|
|
N1
|
47(21.08%)
|
55(24.66%)
|
102(22.87%)
|
|
N2
|
52(23.32%)
|
27(12.11%)
|
79(17.71%)
|
pM Stage
|
M0
|
159(71.3%)
|
171(76.68%)
|
330(73.99%)
|
|
M1
|
36(16.14%)
|
25(11.21%)
|
61(13.68%)
|
|
Unknow
|
28(12.56%)
|
27(12.11%)
|
55(12.33%)
|
Lymphatic invasion
|
YES
|
96(43.05%)
|
63(28.25%)
|
159(35.65%)
|
|
NO
|
107(47.98%)
|
139(62.33%)
|
246(55.16%)
|
|
Unknow
|
20(8.97%)
|
21(9.42%)
|
41(9.19%)
|
Vascular invasion
|
YES
|
58(26.01%)
|
37(16.59%)
|
95(21.3%)
|
|
NO
|
134(60.09%)
|
159(71.3%)
|
293(65.7%)
|
|
Unknow
|
31(13.9%)
|
27(12.11%)
|
58(13%)
|
Perineural invasion
|
YES
|
26(11.66%)
|
19(8.52%)
|
45(10.09%)
|
|
NO
|
58(26.01%)
|
73(32.74%)
|
131(29.37%)
|
|
Unknow
|
139(62.33%)
|
131(58.74%)
|
270(60.54%)
|
CEA level(ng/L)
|
<=5
|
92(41.26%)
|
94(42.15%)
|
186(41.7%)
|
|
>5
|
53(23.77%)
|
43(19.28%)
|
96(21.52%)
|
|
Unknow
|
78(34.98%)
|
86(38.57%)
|
164(36.77%)
|
The potential of ELFN1 to be a diagnostic and prognostic indicator in COAD
Due to the high expression of ELFN1 in COAD, its diagnostic and prognostic value for patients with COAD was analyzed. Generally, the high ELFN1 expression of COAD patients in the TCGA-COAD cohort exhibited worse OS (Fig. 3a) and Progression-free survival (PFI) (Fig. 3b) than that in the low ELFN1 expression patients (P<0.05). Simultaneously, the low expression of ELFN1 in the GSE29621 cohort exhibited favorable OS (P<0.01) (Fig. 3c), while ELFN1 expression had no effect on disease-free survival (DFS) of patients with COAD (P>0.05) (Fig. 3d). Then, low ELFN1 expression in the GSE17536 cohort correlated with a favorable OS (Fig. 3e) and DFS (P<0.05) (Fig. 3f). It was also revealed that high ELFN1 expression in stomach cancer, ocular melanomas and cervical cancer patients were correlated with a poor OS (P<0.05) (Additional File. 1b-d).
The clinicopathological parameters, including ELFN1 expression level, age, T, N, M stage, and tumor stage, were thought to influence patients' OS in COAD by univariate Cox regression analysis (P<0.05) (Fig. 4a). Also, multivariate Cox regression analysis revealed that ELFN1 expression, age and T stage were independent prognostic predictors for COAD patients (P<0.05) (Fig. 4b). Furthermore, ROC curve analysis showed that ELFN1 (AUC=0.900)had a more satisfactory diagnostic value than that of carcinoembryonic antigen (CEA) for COAD (AUC=0.547) (Fig. 4c). The ROC curves of ELFN1 for OS at 3, 5, and 10 years were also plotted (Fig. 4d).
Relationship between TIICs and ELFN1 expression in COAD
The relative abundances of 22 TIICs in each COAD tumor sample were calculated using the CIBERSORT algorithm. The high infiltration levels of M0 Macrophages and Tregs were found in COAD tissues with the high expression of ELFN1, while the infiltration levels of activated CD4 memory T cells, resting or activated Dendritic cells were low in the high ELFN1 expression COAD tissues (P<0.05) (Fig.5a). The correlation between the relative abundance of TIICs and ELFN1 expression level was also investigated. The outcomes revealed that ELFN1 expression had a positive correlation with the infiltrating levels of Tregs and M0 Macrophages, but inversely correlated with that of activated Dendritic cells and both resting and activated CD4 memory T cells in COAD (P<0.05) (Fig. 5b-f).
The relationship between infiltrating Tregs, M0 Macrophages, and clinicopathological parameters was analyzed. The higher relative abundance of Tregs in COAD had a positive association with the advanced Tumor stage (III vs. II) (P<0.05) (Fig. 6a), whereas its abundance changes had no influence on the T stage, N stage, and M stage (Fig. 6b-d) (P>0.05). The relative abundance of M0 Macrophages was positively correlated with the early N stage (P<0.05), surprisingly, it revealed the opposite trend in the advanced N stage (Fig.6g) (P>0.05). Besides, the altered abundance of M0 Macrophages had no effect on Tumor stage, T stage and M stage (Fig. 6 e, f, h) (P>0.05). The changes of Tregs infiltration levels in COAD had no influence on OS (Fig. 6i) (P>0.05). However, lower Tregs' relative abundance was associated with better PFI (Fig. 6j) (P<0.05). The changes of relative abundances of M0 Macrophages had no effect on OS and PFI (Fig. 6 k, l) (P>0.05).
Besides, there was a weak to moderate association among the relative abundance of different TIICs (Fig. 7). For example, the infiltration level of M0 macrophages in COAD negatively correlated with that of M1 Macrophages (r = -0.45) and resting Dendritic cells (r = -0.35).
Association of ELFN1 methylation with clinicopathological features in COAD
11 CpG sites of ELFN1 were found by analyzing the methylation database of TCGA-COAD (Fig. 8a). Further analyses showed that the ELFN1 hypermethylation was associated with earlier tumor stage, N stage, and M stage (Fig.8b-d) (P<0.05). Next, the associations of ELFN1 methylation with OS were evaluated. However, the methylation of ELFN1 did not affect the patient's survival (Additional File. 2a-k) (P>0.05).
Analysis of ELFN1 mutation in COAD
The mutation frequency of ELFN1 was too low in TCGA-COAD and ICGC-COAD cohorts (Fig. 9a, b).
Gene set functional enrichment analysis
Differentially activated signaling pathways related to the high ELFN1 expression in COAD datasets were identified by GSEA software (Table. 2). Many signaling pathways were enriched in the ELFN1 high expression phenotype, such as focal adhesion, pathways in cancer, the intestinal immune network for IGA production, Cell adhesion molecules (CAMs), MAPK, Hedgehog, VEGF, ECM receptor interactions, and Notch signaling pathway (Fig. 10).
Table2. Differentially activated signaling pathways related to the high ELFN1 expression in COAD by GSEA.
Name
|
ES
|
NES
|
Nominal p-value
|
FDR q-value
|
KEGG_CELL_ADHESION_MOLECULES_CAMS
|
0.699
|
2.212
|
<0.001
|
0.004
|
KEGG_HEDGEHOG_SIGNALING_PATHWAY
|
0.583
|
2.081
|
<0.001
|
0.013
|
KEGG_ECM_RECEPTOR_INTERACTION
|
0.712
|
2.052
|
0.001
|
0.014
|
KEGG_NOTCH_SIGNALING_PATHWAY
|
0.630
|
2.044
|
0.001
|
0.014
|
KEGG_FOCAL_ADHESION
|
0.569
|
2.013
|
0.007
|
0.013
|
KEGG_INTESTINAL_IMMUNE_NETWORK
_FOR_IGA_PRODUCTION
|
0.722
|
1.938
|
0.010
|
0.020
|
KEGG_MAPK_SIGNALING_PATHWAY
|
0.433
|
1.849
|
0.003
|
0.029
|
KEGG_PATHWAYS_IN_CANCER
|
0.435
|
1.823
|
0.010
|
0.032
|
KEGG_VEGF_SIGNALING_PATHWAY
|
0.453
|
1.805
|
0.008
|
0.038
|
FDR: false discovery rate; ES: enrichment Score; NES: normalized enrichment Score.
Co-expression analysis of ELFN1
The Pearson correlation coefficients between expression profiles of ELFN1 and PCGs were calculated to determine the co-expression relationships of the ELFN1 and PCGs. Then the Gene Ontology (GO) enrichment analysis was conducted. These genes encoded proteins playing roles mainly in transcription coregulator activity, GTPase regulator activity, growth factor binding, collagen binding crosstalk, extracellular matrix structural constituent, modification-dependent protein binding and transcription corepressor activity (Fig. 11a). The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis reflected the enrichment of ELFN1-related signatures associated with many immunological and cancer-related signaling pathways, like Human papillomavirus infection, PI3K-AKT, CRC, breast cancer, Hippo, ECM receptor interaction, and focal adhesion, Notch, MAPK, mTOR signaling pathways, and so on (Fig. 11b). The STRING and Cytoscape 3.8.2 software were applied to construct the Protein-protein Interaction (PPI) networks among ELFN1-related co-expressed genes. Proteins interaction data in COAD revealed 189 kinds of proteins could interact with ELFN1 protein, among which 21 kinds of proteins had a negative correlation with the expression of ELFN1, whereas the expression of ELFN1 positively correlated with the other 168 kinds of proteins (Fig. 12a). Based on |r|≥0.6, 20 co-expression genes were identified to be correlated with ELFN1 expression (Fig. 12b, c).