Analysis of the expression of cancer-associated fibroblast- and EMT-related proteins in submucosal invasive colorectal cancer

Abstract

Objective: Recent studies have shown that cancer-associated fibroblasts (CAFs) and the epithelial-mesenchymal transition (EMT) play important roles in the progression and metastasis of CRC. Although prediction of lymph node metastasis in submucosal invasive colorectal cancer (SiCRC) is important, the relationships of CAF and EMT with lymph node metastasis of SiCRC have not yet been examined. Here, we aimed to analyze the expression patterns of CAF- and EMT-related proteins in SiCRC.

Materials and Methods: The expression of CAF-related markers, including α-smooth muscle actin, CD10, podoplanin, fibroblast specific protein 1, and adipocyte enhancer-binding protein 1, and EMT-related proteins [zinc finger protein SNAI2 (ZEB1) and twist-related protein 1 (TWIST1) in SiCRC with (n = 29) or without (n = 80) lymph node metastasis was examined by immunohistochemistry. We examined the expression patterns of biomarkers using hierarchical cluster analysis. Consequently, four subgroups were established based on the expression patterns of CAF- and EMT-related markers, and the associations of these subgroups with clinicopathological variables.

Results: In multivariate analysis, subgroup 2, which was characterized by high expression of all markers, was correlated with lymph node metastasis (p < 0.01). Next, we examined the associations of individual biomarkers with lymph node metastasis. Multivariate analysis showed that moderately differentiated adenocarcinoma was significantly associated with lymph node metastasis (p < 0.05).

Conclusions: Our findings showed that expression patterns of CAF markers and EMT-related proteins may allow for stratification of patients into risk categories for lymph node metastasis in SiCRC.

Introduction

Endoscopic resection has been used as a standard curative therapy for Tis colorectal cancer (CRC; carcinoma in situ; intraepithelial or invasion of the lamina propria), given that this method is not associated with the risk of lymph node metastasis ^1-3. However, once CRC has invaded into the submucosal layer, it can acquire metastatic ability (incidence of approximately 10-15%) ^{3, 4}. In order to achieve curative resection of submucosal invasive CRC (SiCRC), various predictive factors for lymph node metastasis have been evaluated ^5-8, including depth of submucosal invasion, lymphatic/vascular invasion, and presence of poorly differentiated cancer components. Although a previous study showed that molecular alterations may develop into more progressive alterations following invasion of CRC cells into the submucosal layer ⁹, few studies have examined the association of lymph node metastasis with molecular changes occurring in the submucosal invasive area.

Although cancers are composed of cancer cells and surrounding stromal cells ¹⁰, the stromal cells are thought to be reactive in nature, not neoplastic in nature ¹¹. In previous studies, analysis of molecular alterations related to the progression or metastatic potential of CRC has primarily focused on cancer cells only ^11-12. However, progression of CRC has recently been shown to be closely associated with not only cancer cells but also the surrounding interstitial cells, include fibroblasts, histiocytes, endothelial cells, pericytes, and smooth muscle cells ¹¹. Among these cell types, fibroblasts are prominent modifiers of cancer progression; in particular, so-called cancer-associated fibroblasts (CAFs) are important promoters of tumor progression and metastasis ^11-14.

One of the most important biological features of CRC is the epithelial-mesenchymal transition (EMT), which is associated with tumor progression and metastasis ^{15, 16}. The EMT is characterized by low or negative expression of E-cadherin and high expression of the EMT-related proteins zinc finger protein SNAI1 (Snail), zinc finger protein SNAI2 (Slug), Twist-related protein 1 (TWIST1), and zinc finger E-box binding homeobox 1 (ZEB1), which act on the promoter region of E-cadherin ^15-18. The EMT promotes the morphological change from malignant epithelial cells to mesenchymal cells ¹⁸, suggesting that mesenchymal cells transformed through the EMT may be classified as CAFs. Thus, both CAF and the EMT are thought to be closely associated with tumor progression and metastasis because fibroblasts are found surrounding the cancer nest at the invasive front.

Many researchers have investigated the clinicopathological alteration of submucosal CRC ^{19, 20}; however, no studies have examined the molecular alterations, in particular, expression of CAF- and EMT-related proteins occurring in cancer cells that invade into the submucosal layer. Accordingly, in this study, we evaluated the usefulness of the expression patterns of CAF- and EMT-related proteins as well as clinicopathological variables to predict lymph node metastasis in submucosal invasive CRC.

Materials and Methods

Patients

In patients who underwent curative surgery for submucosal CRC (SiCRC) at Iwate Medical University, the present study was conducted on a nonconsecutive series of 109 patients whose medical records were complete and for whom the results of lymph node metastasis had been clarified. SiCRC was divided into two categories according to the absence or presence of lymph node metastasis. Depth of submucosal invasion was also subclassified into pSM1 and pSM2 based on the criteria used in Classification of the Japanese Society for Cancer of the Colon and Rectum ²¹. Briefly, nonpedunculated lesions with a vertical invasion length of less than 1000 μm in the submucosal layer were classified as pSM1, and those with invasion of more than 1000 μm were classified as pSM2. In contrast, pedunculated lesions were categorized according to Haggitt's classification ⁴. Tumor budding was defined as an isolated single cancer cell or a cluster composed of fewer than five cancer cells ⁴. Tumor budding was scored into two subgroups: low/negative and high, according to the criteria used in the Classification of the Japanese Society for Cancer of the Colon and Rectum. Briefly, after selecting an area in which budding/sprouting was most intensive, the buds were counted in a field measuring 0.95 mm² through a 20× objective lens (WHK 10× ocular lens; Olympus, Tokyo, Japan) ²¹. Depending on the number of buds, the criteria by the Japanese Classification of Colorectal Cancer (JCCC) for estimation of tumor budding/sprouting were used as follows: low grade, 0-9 buds; and high grade, 10 or more buds ²². Clinicopathological findings, including histological diagnosis, tumor location, and macroscopic classification, were recorded according to the Classification of the Japanese Society for Cancer of the Colon and Rectum ²¹. In brief, whereas “well-differentiated adenocarcinoma” exhibited a relatively regular tubular structure, “moderately differentiated adenocarcinoma” was characterized by a cribriform or irregular tubular structure. In addition, “papillary adenocarcinoma” demonstrated papillary or villous structures. “Poorly differentiated adenocarcinoma” exhibited a solid or trabecular stricture; however, this histological type was only found in the submucosal invasion area (2 cases). Histological diagnosis of the tumor was determined by histological superiority within the same tumor. Lymphatic and vascular invasion of the examined cases was determined by D2-40 immunostaining and elastic staining, respectively. Although extensive desmoplasia, defined as a proliferation of active fibroblasts with expression of α-smooth muscle actin and loss of desmin expression, was frequently observed, lymphocytic infiltration in the submucosal area was not often detected. Therefore, extensive desmoplasia and scanty lymphocyte infiltration were common findings in the present cases we examined. The slides were independently evaluated by two experienced pathologists (S. T. and N. U.); in some cases in which the evaluation provided different results, a consensus interpretation was reached after re-examination.

Patient survival was confirmed through telephone interviews. There were no deaths from SiCRC. Patients did not undergo pre-operative chemoradiotherapy or radiotherapy. In addition, patients who showed evidence of hereditary nonpolyposis CRC or familial adenomatous polyposis were excluded from the study. The various clinicopathological parameters of the patients were confirmed by reviewing the patient medical records and pathology files and were evaluated according to the Classification of the Japanese Society for Cancer of the Colon and Rectum. The detailed clinicopathological findings are listed in Table 1.

Table 1.

Clinicopathological findings of submucosal invasive colorectal cancer

Findings		Cases (%)
Total		109
Sex	Men : Women	57 : 52
Age (year)	Range (median)	40-93 (67)
Size (mm)	Range (median)	5-80 (22.5)
Site	Right	36 (33.0)
	Left	73 (67.0)
Macroscopic type	0-I type	37 (33.9)
	0-IIa type	24 (22.0)
	0-IIc type	16 (14.7)
	0-IIa+IIc type	28 (25.7)
	LST type	5 (4.6)
Histological type	WDA	36 (33.0)
	MDA	69 (63.3)
	PAP	2 (1.8)
	POR	2 (1.8)
pSM depth	pSM1	8 (7.3)
	pSM2	101 (92.7)
Lymphatic invasion	Low	104 (95.4)
	High	5 (4.6)
Venous invasion	Low	102 (93.6)
	High	7 (6.4)
pN	pN0	80 (73.4)
	pN1	29 (26.6)
pM	pM0	109
	pM1	0
Tumor budding	Grade 1	99 (90.8)
	Grade 2	10 (9.2)

Macroscopic type: I, protruded type; IIa, flat elevated type; IIc, flat depressed type; LST, laterally spreading tumor; WDA, well-differentiated adenocarcinoma; MDA, moderately differentiated adenocarcinoma; PAP, papillary adenocarcinoma; POR, poorly differentiated adenocarcinoma.

This study was approved by the Ethical Research Committee of Iwate Medical University.

Construction of tissue microarrays (TMAs)

The construction of tissue microarrays (TMAs) has been described previously ²². Briefly, formalin-fixed, paraffin-embedded tissue blocks containing CRC samples were retrieved from the archives of the Iwate Medical University Department of Diagnostic Molecular Pathology. Areas of submucosal invasive cancer were identified on corresponding H&E-stained slides, and the tissue blocks were cored and transferred to a recipient “master” block using a TMA.

Immunohistochemistry

Immunostaining was carried out as follows. First, 3-μm-thick tissue sections were cut from paraffin-embedded blocks. After deparaffinization and rehydration, the sections were heated in Envision^TM FLEX target retrieval solution (pH 6.0 or 9.0; Dako) for 20 min and washed twice for 5 min in phosphate-buffered saline (PBS). Three percent hydrogen peroxide was used to block endogenous peroxidase for 5 min. Nonspecific binding was blocked with 1.5% normal serum in PBS for 35 min at room temperature. Immunohistochemical staining was performed as described previously ^{23, 24}.

Antibodies targeting α-smooth muscle actin (α-SMA), CD10, podoplanin, fibroblast specific protein 1 (FSP1; S100A4), and adipocyte enhancer-binding protein 1 (AEBP1) for CAFs and Zinc finger E-box binding homeobox 1 (ZEB1) and Twist-related protein 1 (TWIST1) for the EMT were used in this study (Table 2). CAFs were recognized as “spindle-shaped cells” by experienced pathologists (T.S. and N.U.). Cytoplasmic staining of tumor cells stained with α-SMA, CD10, podoplanin, FSP1, and AEBP1 was considered positive, and nuclear staining of fibroblasts with ZEB1 and TWIST1 was regarded as positive.

Table 2.

Antibodies used in this study

Antibody	Source	Clone	Dilution	Treatment
α SMA	Dako	1A4	Ready to use	Heating (pH9)
CD10	Dako	56C6	Ready to use	Heating (pH9)
Podoplanin	Dako	D2-40	Ready to use	Heating (pH9)
FSP1	Dako	Polyclonal	1:400	Heating (pH6)
AEBP1	Abcam	ab54820	1:100	Heating (pH6)
ZEB1	Sigma-Aldrich	Polyclonal	1:200	Heating (pH9)
TWIST	Abcam	Twist2C1a	1:500	Heating (pH9)

Quantitative analysis of α-SMA, CD10, podoplanin, FSP1, AEBP1, ZEB1, and TWIST1 expression was performed using digital pathology with Aperio software (Leica Biosystems). Tissue sections were scanned on an Aperio AT2 scanner with an average scan time of 120 s (compression quality: 70). Images were analyzed using color deconvolution and colocalization. The Aperio Pixel Count v9 Algorithm in Aperio Image Analysis software (for cytoplasmic analysis) was used, and the Nuclear v9 algorithm was applied to detect the nuclear staining of individual tumor cells in the selected regions for nuclear analysis. The intensity of staining was measured on a continuous scale from 0 (black) to 255 (bright white) and was automatically calculated by the software as the ratio of positively stained nuclei to all nuclei (negative, well, moderate, strong, and very strong). Greater than “moderate intensity” (moderate, strong, and very strong) was considered to be positive. Stained areas were color separated from hematoxylin-counterstained sections and measured by the software. Then, the score for the area of the positively stained cells (percentage of positive cells) was based on the average score observed in 10 hot spots at 400×. Based on the cell staining proportion, all cases were individually classified as 0 (less than 1%), 1+ (1% ≤ positive tumor cells < 25%), 2+ (25% ≤ positive tumor cells < 50%), 3+ (50% ≤ positive tumor cells < 75%), and 4+ (≥ 75%) based on the cytoplasm/nuclear staining intensity and completeness. Representative images are shown in Figure 1.

Figure 1.

Representative illustration of submucosal invasive colorectal cancer with lymph node metastasis. a. HE section. b. α-SMA staining, showing 84.1% expression. c. CD10 staining, showing 67.8% expression. d. Podoplanin staining, showing 85.8% level. e. FSP1 staining, showing 41.6% expression. f. AEBP1 staining, showing 42.8% expression. g. Zeb1 staining, showing 51.8% expression. h. Twist staining, showing 13.3% expression.

Hierarchical analysis of the expression of CAF and EMT markers

Hierarchical cluster analysis was performed for clustering of the samples according to the above scoring (0-4+) in order to achieve maximal homogeneity for each group and the greatest difference between the groups using open-access clustering software (Cluster 3.0 software; bonsai.hgc.jp/~mdehoon/software/cluster/software.htm). The clustering algorithm was set to centroid linkage clustering, which is the standard hierarchical clustering method used in biological studies.

Statistical analysis

Data were analyzed using Stat Mate-III software (Atom, Tokyo, Japan). Data obtained for clinicopathological features (sex, macroscopic type, location, histological type, classification of submucosal invasion, and lymph node metastasis) and immunohistochemical patterns of CAFs (i.e., α-SMA, CD10, podoplanin, FSP1, AEBP1) and EMT-related proteins (TWIST1 and ZEB1) based on each subgroup were analyzed using chi-squared tests.

For statistical analysis of the expression of α-SMA, CD10, podoplanin, FSP1 (S100A4), and AEBP1 for CAFs and ZEB1 and TWIST1 in SiCRC and their associations with various clinicopathological factors and lymph node metastasis, we used χ² tests, Fisher's exact tests, and Mann-Whitney U-tests with a 2 × 2 table to compare the categorical data. Univariate and multivariate analyses were conducted with logistic regression tests to identify statistical differences for prediction of lymph node metastasis. The level of significance was P < 0.05, and the confidence interval (CI) was determined at the 95% level. Statistical analyses were performed with the JMP 10.0 software package (SAS Institute, Inc., Cary, NC, USA) for Mac.

Results

The expression of α-SMA, AEBP1, and ZEB1 was diffusely observed in the invasive area, whereas that of CD10, podoplanin, FSP1, and TWIST1 was heterogeneously observed in the same area. In the present study, in such cases, the primary “hot spot” of immunostaining was selected.

1. Hierarchical clustering based on marker scores

First, we performed hierarchical clustering based on marker scores to evaluate differences in expression patterns of CAFs- and EMT-related markers in patients with SiCRC. Four distinct subgroups emerged, as shown in Figure 2. The vertical line shows the expression of each marker in fibroblasts, and the horizontal lines denote “relatedness” between samples.

Figure 2.

Hierarchical cluster analysis of submucosal invasive colorectal cancer (SiCRC) based on the expression patterns of cancer-associated fibroblast (CAF)- and EMT-related proteins. The examined SiCRCs were subclassified into 4 subgroups.

Subgroup 1 was characterized by high expression of α-SMA, AEBP1, and ZEB1 and low expression of CD10, podoplanin, and TWIST1 (Figure 3), whereas subgroup 2 was closely associated with high expression of α-SMA, CD10, podoplanin, FSP1, AEBP1, ZEB1, and TWIST1 (Figure 3). In addition, significantly high expression of α-SMA, podoplanin, AEBP1, and ZEB1 was observed in subgroup 3 (Figure 3), and high expression of α-SMA, podoplanin, FSP1, AEBP1, ZEB1, and TWIST1 and low expression of CD10 were distinctive features in subgroup 4 (Figure 3).

Figure 3.

Expression levels of α-SMA (a), CD10 (b), podoplanin (c), FSP1 (d), AEBP1 (e), ZEB1 (f), and TWIST1 (g) in each subgroup.

1-a. Association of the expression of CAF- and EMT-related markers with each subgroup

The frequency in CD10 expression of fibroblasts in subgroup 2 was significantly higher than that in subgroups 1, 3, and 4 (p < 0.01). There were significant differences in the frequencies of podoplanin expression between subgroups 2, 3, and 1 (subgroup 1 < subgroups 2 and 3; p < 0.01 and 0.05). Furthermore, FSP1 expression was significantly higher in subgroup 2 than in subgroups 1 and 3 (p < 0.01). Although there were significant differences in the expression of TWIST1 between subgroup 2 and subgroups 1, 3, and 4 (p < 0.05 and p < 0.01), no differences were observed in the expression of ZEB1 among subgroups. The associations are shown in Figure 3.

1-b. Association of clinicopathological variables and expression patterns of CAF- and EMT-related markers with lymph node metastasis in SiCRC using univariate and multivariate analyses

To determine whether the clinicopathological variables and expression patterns of CAF- and EMT-related markers were independent predictors of lymph node metastasis among patients with SiCRC, we used univariate analysis for preliminary screening of the variables, followed by a stepwise logistic regression of the risk of mortality with the significant univariate predictors. The univariate analysis (Table 3a) identified 5 factors, including age, tumor location, histological type, subgroup 1 versus 2, subgroup 2 versus 3, and subgroup 4 versus 2, as associated with increased lymph node metastasis in patients with SiCRC.

Table 3.

Univariate and multivariate regression analysis of relationships between lymph node metastasis and clinicopathological factors, subgroup classification

		a.				b.
Variables			Univariate regression				Multivariate regression
		OR	95% CI	P value		OR	95% CI	P value
Sex	Men vs Women	1.341	0.5657-3.1784	0.5052		2.9363	0.8322-10.3605	0.094
Age (year)		1.0547	1.0095-1.1019	0.0136		1.042	0.9807-1.1072	0.0857
Size (mm)		1.0147	0.9827-1.0564	0.3954		1.0082	1.0654-0.9918	0.1769
Site	Right vs Left	3.7959	1.3130-13.8392	0.0123		4.4896	0.7479-26.9502	0.1005
Microscopic type	I vs IIc	0.1041	0.01239-0.8743	0.0372		0.2629	0.01839-3.7578	0.3249
	IIc vs IIa+IIc	8.5000	0.9708-72.4243	0.0532		3.3592	0.2519-44.7973	0.3593
Histologic type	WDA vs MDA	3.000	0.9357-9.6181	0.0016		5.3146	0.8776-32.1840	0.0691
pSM depth	pSM1 vs pSM2	2.589	0.4318-49.5508	0.3342		1.9859	0.1449-27.2242	0.6075
Lymph vessel invasion	Low vs High	4.680	0.73954-29.6163	0.1011		2.2791	0.1327-39.1316	0.5701
Venous invasion	Low vs High	2.280	0.47736-10.8900	0.3016		1.779	0.0233-13.5495	0.7227
Tumor budding	Grade 1 vs 2	1.4444	0.3348-9,9812	0.6453		7.4263	0.4455-123.7920	0.1625
Subgroup	Subgroup 1 vs 2	6.000	1.1717-30.7246	0.0315		4.7729	0.4148-54.9239	0.2099
	Subgroup 3 vs 2	4.3125	1.1644-15.9717	0.0287		5.9167	0.8423-41.5633	0.0739
	Subgroup 4 vs 2	7.3125	2.0273-26.3760	0.0024		15.2232	2.2060-105.0544	0.0057

Macroscopic type: I, protruded type; IIa, flat elevated type; IIc, flat depressed type; LST, laterally spreading tumor; WDA, well-differentiated adenocarcinoma; MDA, moderately differentiated adenocarcinoma; PAP, papillary adenocarcinoma; POR, poorly differentiated adenocarcinoma.

Table 3b shows the single factor that was retained in the multivariate logistic regression analysis. We found that subgroup 4 versus 2 (odds ratio, 15.2332; 95% CI, 2.2060-105.0544; p < 0.0057) remained significant predictors of lymph node metastasis, even after controlling for the other variables. These results are summarized in Table 3.

1-c. Association of clinicopathological variables with the different subgroups

There was a significant difference in the frequency of tumor location (left versus right) between subgroups 2 and 4 (subgroup 4 > subgroup 2; p < 0.05; Table 4). The frequency of moderately differentiated type adenocarcinoma was significantly higher in subgroup 4 than in subgroup 1 (p < 0.01; Table 4). In addition, a significant difference in the frequency of lymph node metastasis between subgroups 2 and 4 was found (subgroup 2 > subgroup 4; Table 4). However, there was no significant difference in the frequency of submucosal depth and tumor budding among subgroups (Table 4).

Table 4.

Comparison of clinicopathological findings in each subgroup

		Total	Subgroup 1 (%)	Subgroup 2 (%)	Subgroup 3 (%)	Subgroup 4 (%)	p value
Total		109	15 (13.8)	15 (13.8)	32 (43.0)	47 (43.1)
Sex	Men : Women	57 : 52	13 : 2	8 : 7	15 : 17	21 : 26	N. S.
Age (year)	Range (median)	40-93 (67.0)	55-85 (71.5)	46-79 (70.4)	44-79 (64.5)	40-78 (67.9)	N. S.
Site	Right	40 (36.7)	7 (46.7)	10 (66.7)	12 (37.5)	11 (23.4)	< 0.05
	Left	69 (63.3)	8 (53.3)	5 (33.3)**	20 (62.5)	36 (76.6)**
Macroscopic type	0-I type	37 (33.9)	8 (53.3)	6 (40.0)	11 (34.3)	12 (29.8)	N. S.
	0-IIa type	24 (22.0)	1 (6.7)	2 (13.3)	11 (34.3)	10 (21.3)
	0-IIc type	16 (14.7)	4 (26.7)	2 (13.3)	3 (9.4)	7 (14.9)
	0-IIa+IIc type	28 (25.7)	1 (6.7)	4 (26.6)	5 (15.7)	17 (36.2)
	LST type	5 (4.6)	1 (6.7)	1 (6.7)	2 (6.3)	1 (2.1)
Histological type	WDA	36 (33.0)	9 (60.0)	7 (46.7)	11 (34.3)	9 (19.1)	< 0.01
	MDA	69 (63.3)	5 (33.3)*	7 (46.7)	19 (59.4)	38 (80.9)*
	PAP	2 (1.8)	0	1 (6.7)	1 (3.1)	0
	POR	2 (1.8)	1 (6.7)	0	1 (3.1)	0
pSM depth	pSM1	8 (7.3)	1 (6.7)	1 (6.7)	4 (12.5)	2 (4.3)	N. S.
	pSM2	101 (92.7)	14 (93.3)	14 (93.3)	28 (87.5)	45 (95.7)
Lymphatic invasion	Low	104 (95.4)	14 (93.3)	15	29 (90.6)	46	N. S.
	High	5 (4.6)	1 (6.7)	0	3 (9.4)	1
Venous invasion	Low	102 (93.6)	14 (93.3)	15	28 (87.5)	45 (95.7)	N. S.
	High	7 (6.4)	1 (6.7)	0	4 (12.5)	2 (4.3)
pN	pN0	80 (73.4)	12 (80.0)	6 (40.0)	24 (75.0)	38 (80.9)	< 0.05
	pN1	29 (26.6)	3 (20.0)	9 (60.0)*, **	8 (25.0)*	9 (19.1)**
Tumor budding	Low	99 (90.8)	14 (93.3)	13 (86.7)	29 (90.6)	43 (91.5)	N. S.
	High	10 (9.2)	1 (6.7)	2 (13.3)	3 (9.4)	4 (8.5)

*: p < 0.05, **: p < 0.01

Macroscopic type: I, protruded type; IIa, flat elevated type; IIc, flat depressed type; LST, laterally spreading tumor; WDA, well-differentiated adenocarcinoma; MDA, moderately differentiated adenocarcinoma; PAP, papillary adenocarcinoma; POR, poorly differentiated adenocarcinoma.

2. Association of clinicopathological variables and expressions of individual CAF- and EMT-related marker with lymph node metastasis in SiCRC using univariate and multivariate analyses

We analyzed the associations of expression of individual markers with lymph node metastasis in SiCRC. Although univariate analysis revealed that several clinicopathological factors, including age, tumor location, histological type, and CD10 and podoplanin expression, were significantly associated with lymph node metastasis (Table 5a; p < 0.05), these factors, with the exception of histological type, were not retained in multivariate analysis (Table 5b). A significant difference was observed in histological type (well differentiated versus moderately differentiated) between SiCRCs with and without lymph node metastasis (p < 0.05). These relationships are depicted in Table 5.

Table 5.

Univariate and multivariate regression analysis of the relationships between lymph node metastasis and clinicopathological factors, expression of CAFs and EMT markers

		a.				b.
Variables			Univariate regression				Multivariate regression
		OR	95% CI	P value		OR	95% CI	P value
Sex	Men vs Women	1.341	0.5657-3.1784	0.5052		3.9628	0.6684-23.4957	0.1060
Age (year)		1.0547	1.0095-1.1019	0.0136		1.0830	0.8333-1.0085	0.0774
Size (mm)		1.0147	0.9827-1.0564	0.3954		1.0223	0.9078-1.0566	0.5433
Site	Right vs Left	3.7959	1.3130-13.8392	0.0123		4.4896	0.7479-26.9502	0.1005
Microscopic type	I vs IIc	0.1041	0.01239-0.8743	0.0372		0.1035	0.2066-452.02	0.2476
	IIc vs IIa+IIc	8.5000	0.9708-74.4243	0.0532		0.09135	0.0018-4.6766	0.2334
Histologic type	WDA vs MDA	3.000	0.9357-9.6181	0.0016		50.9464	1.7405-1491.2263	0.0225
pSM depth	pSM1 vs pSM2	2.589	0.4318-49.5508	0.3342		22.8022	0.4064-1279.43	0.1281
Lymph vessel invasion	Low vs High	4.680	0.73954-29.6163	0.1011		6.9505	0.0023-8.8773	0.3566
Venous invasion	Low vs High	2.280	0.47736-10.8900	0.3016		2.6893	0.0062-22.3959	0.6361
Tumor budding	Grade 1 vs 2	1.4444	0.3348-9.9812	0.6453		31.7338	0.0011-0.9364	0.0457 (CI: -7.5030 - -0.4963)*
αSMA		0.6895	0.16282-12.9186	0.7334		1.2396	0.3130-2.0184	0.6432
CD10		1.2747	1.05536-1.5607	0.0120		1.4922	1.10196-2.3862	0.0604
Podoplanin		0.1077	1.2364-69.7862	0.0181		1.4169	0.8990-2.4065	0.1563
FSP1		1.0127	0.8635-1.1934	0.8773		1.2247	0.8635-1.7818	0.2635
AEBP1		0.9467	0.76339-1.1961	0.6301		0.7447	0.4821-1.0967	0.1467
TWIST1t		1.4703	0.4556-5.1679	0.5255		1.0073	0.7413-1.3684	0.962
ZEB1		0.0809	0.6266-1.043821	0.1051		5.8386	0.0455-0.4342	0.0016 (CI: -3.0910 - -0.8342)*

Macroscopic type: I, protruded type; IIa, flat elevated type; IIc, flat depressed type; OR, odds ratio; WDA, well-differentiated adenocarcinoma; MDA, moderately differentiated adenocarcinoma; CI, confidence interval; *, not significant.

Discussion

The risk of lymph node metastasis in SiCRC is estimated to be 10-15%. ^{1, 2, 3} Although several attempts have been made to predict the risk of lymph node metastasis in SiCRCs ^1-3, it is still unclear which method is the best for predicting lymph node metastasis ^{3, 4}. Previous studies have shown that submucosal invasion depth, lymphatic/vascular invasion, tumor differentiation (poorly differentiated versus differentiated), and tumor budding were significantly associated with lymph node metastasis ²⁵. However, there are some problems with determining the risk of lymph node metastasis in SiCRCs ²⁵. For example, measurement of the depth of submucosal invasion when the muscularis mucosa is completely disrupted by tumor invasion may be inconsistent between pathologists ^{2, 3}. In addition, although desmoplasia is defined as active fibroblastic (myofibroblastic) proliferation at the invasive area, desmoplasia may not be a reliable marker to predict lymph node metastasis. In this study, we aimed to predict lymph node metastasis in patients with SiCRC using a new biological approach (expression patterns of CAF- and EMT-related markers in fibroblasts surrounding cancer nests at the invasive area).

CAFs are defined as proliferative fibroblasts in the invasive area ^{26, 27}. This definition is similar to that of desmoplasia, which is proliferation of active fibroblasts that express α-SMA and exhibit loss of desmin ^{26, 27}. In the present study, the CAFs we examined were similar to desmoplastic fibroblasts, showing extensive expression of α-SMA, which characterizes desmoplastic fibroblasts. Although desmplasia is closely associated with tumor invasion, the presence of desmoplasia alone cannot predict lymph node metastasis in SiCRC given that desmoplasia was a common finding in the submucosal area in the present study. Therefore, our current findings revealed an important alternative for predicting lymph node metastasis in SiCRC.

To examine CAFs in tumors, a specific marker for CAFs is needed ^10-13. The most widely used marker for CAFs is α-SMA, a specific marker of myofibroblasts ^11-13. Additional markers for CAFs include CD10 ^{28, 29}, podoplanin ³⁰, FSP1 ^{24, 31}, and AEBP1; these markers are also thought to be associated with tumor invasion and metastasis ^{32, 33}. In addition, EMT-related markers, including TWIST1 ³⁴ and ZEB1 ³⁵, were also used in the present study because EMT-related proteins may also be markers of CAFs (e.g., co-expression of CAF- and EMT-related proteins is observed in the same fibroblasts). The antibodies we used in this study are widely available and are reliably and reproducibly used in studies of CRC ^{24, 28, 31, 32}. Thus, these markers, i.e., α-SMA, CD10, podoplanin, FSP1, AEBP1, TWIST1, and ZEB1, are thought to be suitable for identifying the roles of CAFs and the EMT in SiCRC.

We attempted to identify differences in the expression patterns of CAF- and EMT-related proteins in patients with SiCRC based on hierarchical clustering. As a result, each subgroup was stratified according to the expression patterns of CAF- and EMT-related markers. In the present study, tumors in subgroup 2 were closely associated with lymph node metastasis compared with those in subgroup 4, as supported by the finding that subgroup 2 was retained in the multivariate logistic regression analysis. Thus, high expression of all of the examined markers (pattern of subgroup 2) may contribute to lymph node metastasis in SiCRC.

In the present study, the expression of α-SMA, AEBP1, and ZEB1 was commonly found in all subgroups, suggesting that these proteins play a common role in the formation of the submucosal invasive area. Although α-SMA has been shown to label smooth muscle cells in the muscularis mucosae and muscularis propria as well as CAFs, ^{11, 12} α-SMA may confer cellular mobility as a basic function in the tumor microenvironment ³⁴. AEBP1 was originally reported as a novel pro-inflammatory mediator that induces nuclear factor-κB activity ^{32, 33, 37} and is expressed in many tissues ^{32, 33}, with highest expression observed in pre-adipocytes and macrophages of the mammary stroma ^{32, 33}. AEBP1 plays a critical role in a subset of human tumors, as supporting by the finding that AEBP1 is upregulated in the tumor tissue ^{32, 33, 37}. However, the role of this marker in CAFs remains unknown. In fact, very few studies have focused on the expression of AEBP1 in CAFs. Our present findings suggested that this marker may be useful for labeling CAFs in the microenvironment of the invasive area. ZEB1 is also a common marker of the microenvironment of the invasive area in the submucosal region and indicates the occurrence of the EMT and cellular senescence ^{36, 37}. In previous studies, the expression of ZEB1 has suggested that the EMT may be associated with the formation of submucosal invasion ^{38, 39}. Taken together, our findings showed that several markers, including α-SMA, AEBP1, and ZEB1, contribute to the microenvironment of submucosal invasion.

The expression of CD10 in tumor cells is thought to predict poor prognosis in patients with CRC ⁴⁰, although contrasting data have also been reported ⁴¹. These findings were supported by the observation that CD10 expression in CRC cells enhances liver metastasis ⁴². In addition, CD10 status is not significantly associated with lymph node metastasis and is no better than lymphovascular invasion alone when predicting lymph node status ⁴¹. However, the role of CD10 expression in CAFs is not understood, and CD10 expression in CAFs has not been recognized as an important parameter to date ⁴³. In the present study, we did not find that expression of CD10, which characterizes tumors in subgroup 2 (a subgroup predicting lymph node metastasis in SiCRC), was an important marker for CAFs for prediction of lymph node metastasis in SiCRC. Thus, further studies are needed to determine the usefulness of CD10 expression as a CAF-associated marker.

Histological parameters are simple and easy to determine them in routine pathological diagnosis ^{1, 2, 3}. In the present study, although histological type (well differentiated versus moderately differentiated type) was useful for predicting lymph node metastasis in the analysis of individual markers, tumor budding (low versus high) was not significant. It is well accepted that tumor budding is an important additional prognostic factor for patients with CRC ⁴⁰. Although a recent study showed that a high level of tumor budding is closely associated with lymph node metastasis in SiCRC ⁴⁴, the decision regarding the identification of tumor budding is known to show intra-observer variation ⁴⁴. Thus, we suggest that the differences between the previous study and our current data may have resulted from intra- and/or interobserver variations. On the other hand, it is not clear whether histological type (differentiated-type) is correlated with lymph node metastasis in SiCRC. In the present study, histological type was not correlated with lymph node metastasis in multivariate analysis of expression patterns defined by hierarchical clustering based on marker scores but was significantly associated with lymph node metastasis in multivariate analysis of the expression of individual markers. Although the reason for this difference is unclear, tumor differentiation (or tumor grade, well versus moderately differentiated) may be associated with expression patterns of CAF markers.

There were some limitations to the present study. First, if immunostaining was heterogeneous in the invasive area, interpretation of the immunostaining was limited in biopsy specimens. However, if the “hot spot” region was observed in the submucosal invasive area, expression of CAF- and EMT-related markers may help to predict lymph node metastasis in SiCRC. Second, in the present study, we used specimens collected during operation to examine CAF- and EMT-related proteins in SiCRC; specimens obtained from endoscopic materials were not used in the present study. Further studies are needed to predict lymph node metastasis in SiCRC using endoscopic specimens.

In conclusion, we studied the expression patterns of CAF- and EMT-related proteins in submucosal CRCs using hierarchical cluster analysis. Consequently, four distinct subgroups were categorized as SiCRC based on the expression patterns of CAF- and EMT-related markers. Subgroup 2 was characterized by frequent expressions of all 6 markers, with particularly high expression of CD10 and FSP1. In addition, subgroup 2 was correlated with lymph node metastasis of SiCRC compared with subgroup 4. Finally, tumor differentiation was correlated with lymph node metastasis in SiCRC in the analysis of individual markers. Thus, we showed that stratification of the expression patterns of CAF- and EMT-related markers and specific expression of the biomarkers we analyzed provided insights into the prediction of lymph node metastasis in patients with SiCRC.

Abbreviations

AEBP1

adipocyte enhancer-binding protein 1

CAF

cancer associated fibroblast

CRC

colorectal cancer

EMT

epithelial-mesenchymal transition

FSP1 (S100A4)

fibroblast specific protein 1

SiCRC

submucosal invasive colorectal cancer

TMAs

tissue microarrays

Twist 1

Twist-related protein 1

ZEB

Zinc finger E-box binding homeobox 1.