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Cancer Biomarkers: Section A of Disease Markers logoLink to Cancer Biomarkers: Section A of Disease Markers
. 2018 May 29;22(2):301–310. doi: 10.3233/CBM-171017

Elevated MACC1 expression predicts poor prognosis in small invasive lung adenocarcinoma

Tao Guo a,1,b, Shilei Zhao a,1,b, Zhuoshi Li a,1,b, Fengzhou Li a,b, Jinxiu Li b, Chundong Gu a,b,*
PMCID: PMC13078428  PMID: 29630522

Abstract

BACKGROUND:

Patients with small ( 2 cm) invasive lung adenocarcinoma are at high risk of poor prognosis and disease recurrence after complete surgical resection. Therefore, identification of high-risk individuals from these patients emerges as an urgent problem. Elevated MACC1 expression predicts a poor prognosis in multiple types of cancer that are independent of TNM staging. This study investigated the prognostic value of MACC1 expression in patients with small invasive lung adenocarcinoma.

OBJECTIVE:

The current study aimed to evaluate the relationship between MACC1 expression in patients’ tumor tissue and prognosis in small invasive lung adenocarcinoma.

METHODS:

The records of 131 patients with small invasive lung adenocarcinoma who underwent complete surgical resection were reviewed. The MACC1 expression was detected by immunohistochemical staining in all specimens. Meanwhile, western blot and real-time quantitative PCR were used to examine the expression level of MACC1 in human lung adenocarcinoma cell lines. The effect of clinicopathological risk factors on patients’ survival was analyzed using the Kaplan-Meier approach and multivariable Cox models.

RESULTS:

Elevated MACC1 expression was observed in 53 (40.5%) specimens, and in A549, H358, H460 and H322 lung adenocarcinoma cell lines. MACC1 overexpression was associated with differentiation (P= 0.005) and blood vessel invasion (P= 0.001). Compared with low MACC1 expression, elevated MACC1 expression was associated with significantly shorter overall survival (odds ratio = 6.515; 95% confidence interval: 1.382–30.721; P= 0.018) and disease-free survival (odds ratio = 3.270; 95% confidence interval: 1.117–9.569; P= 0.031). Multivariate analyses demonstrated high MACC1 expression is an independent risk factor of worse overall survival (odds ratio = 5.684; 95% confidence interval: 1.145–28.210; P= 0.034) and disease-free survival (odds ratio = 4.667; 95% confidence interval: 1.372–15.877; P= 0.014).

CONCLUSION:

MACC1 is an independent prognostic marker in patients with small invasive lung adenocarcinoma after complete surgical resection. Differential outcomes are associated with MACC1 expression level.

Keywords: MACC1, lung adenocarcinoma, prognosis

1. Introduction

Lung cancer is the leading cause of cancer death worldwide [1]. As recent improvement in computed tomography (CT) technique, the detection of small ( 2 cm) lung cancer, especially adenocarcinoma, the leading aggressive histopathologic type of lung cancer, has been increasing [2]. However, the 5-year survival rate of patients with early stage is merely about 50%–70% as the malignant features of early metastasis and recurrence [3, 4]. Thus, it is critical to identify these small but aggressive tumors for accurate prediction and adjuvant therapy. Advances in genomic research of lung cancer have changed the classification of lung adenocarcinoma to a categorization based on different gene phenotypes [5]. These facts highlight the need for identification of precise molecular biomarkers, to predict the prognosis in patients with lung adenocarcinoma and develop appropriate therapy.

MACC1 is a prognostic biomarker for colorectal cancer metastasis and patient survival that was recently identified in human colon cancer tissues [6]. MACC1 is reported promotes many types of cancer cell proliferation, migration and invasion in cell culture, metastasis in mice model [6, 7]. Recent studies have shown that MACC1 promotes Warburg effect by enhancing the expressions and activities of a series of glycolytic enzymes, including hexokinase (HK), pyruvate dehydrogenase kinase (PDK) and lactate dehydrogenase (LDH) in gastric cancer cells [8]. Meanwhile, overexpression of MACC1 was also involved in drug resistance and enhanced Warburg effect through activation of PI3K/AKT signaling pathway [9]. Moreover, overexpression of MACC1 is associated with poor prognosis in a wide variety of tumor types [7, 10, 11, 12]. Nevertheless, the prognostic role of MACC1 expression in lung cancer, especially in resected small invasive lung adenocarcinoma has not been sufficiently investigated.

Here, we explored the expression of MACC1 in patients with resected small invasive lung adenocarcinoma and evaluated the prognostic role of MACC1 in these patients. Our results showed that elevated MACC1 expression correlates with poor prognosis and early recurrence in small invasive lung adenocarcinoma patients.

2. Materials and methods

2.1. Patients and follow-up

One hundred and thirty-one patients with small invasive lung adenocarcinoma who underwent radical surgery of the primary tumor and systematic nodal dissection without any adjuvant therapy at the First Affiliated Hospital of Dalian Medical University from January 2009 to December 2011 were enrolled. The inclusion criteria of the study was based on invasive lung adenocarcinomas of the tumor 2 cm in diameter identified by routine histopathologic examination. Histologic classification of each tumor was independently examined by two pulmonary pathologists according to the WHO classification of tumors of the lung (4th Edition) which included T adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), acinar (Aci), papillary (Pap), micropapillary (MP), solid (Sol), mucinous (Mu). The tumor stage was classified according to the 8th revision of TNM (tumor, nodes, metastasis) staging of the international system for lung cancer. As our previous research [13], patients were followed every 3 months within the first year and at 6-month intervals thereafter. During the follow-up time, physical examination, chest radiography, analysis of blood chemistry, carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC) and serum cytokeratin-19 fragments (CYFRA21-1) test were performed. If any symptom or sign of recurrence appeared in these examinations, further evaluations to detect the recurrent site were carried out. The terminal follow-up time was January 2014 (median follow-up: 32 months). The study was approved by the Medical Ethical Committees of the First Affiliated Hospital of Dalian Medical University. All patients provided written informed consent and agreed their tissue samples could be used for clinical research but not commercial use.

2.2. Immunohistochemical staining (IHC)

All resected specimens were obtained from primary lesions, fixed with formalin, embedded with paraffins, serial 3 μm sections were prepared. The sections were briefly incubated with xylene, rehydrated with graded ethanol solutions, incubated with methyl alcohol containing 3% hydrogen peroxide and immersed in a citrate buffer for antigen retrieval. IHC staining was performed using Streptavidin-Peroxidase IHC assay kit (ZSGB-bio, China) following the manufacturer’s instructions. Antibodies of MACC1 (Abcam, ab12148) was diluted 1:200 in PBS containing 2% goat serum. Immunostaining was evaluated by two pulmonary pathologists using a blind protocol design. For each specimen, the total score of intensity expression (negative staining: 0 point; weak staining: 1point; moderate staining: 2 point; and strong staining: 3 point) multiplying stained cell numbers (positive cells as 25% of the cells: 1 point; 26–50% of the cells: 2 point; 51–75% of the cells: 3 point; > 75% of the cells: 4 point) of MACC1 was estimated. When the sample was scored 6 point, we defined it as high expression, otherwise low expression.

2.3. Cell lines and reagents

Human lung adenocarcinoma cell lines (A549, NCI-H358, NCI-H460 and NCI-H322) and normal human fetal lung fibroblasts cell line (HFL-1) were purchased from American Type Culture Collection (ATCC, Manassas, VA, USA). Cells were cultured in ATCC-recommended medium supplemented with 10% fetal bovine serum (FBS) and incubated at 37C in humidified 5% CO2 incubator.

2.4. Western blotting

Western blot analysis was performed according to the protocols for the routine measurement of antibodies against MACC1 (Rabbit, 1:2000, Abcam, ab12148), GAPDH (Mouse, 1:5000, Sigma, A5441), respectively. Goat-anti-rabbit IgG conjugated to hor- seradish peroxidase (HRP) (1:5000, Thermo, 31460) and goat-anti-mouse IgG conjugated to HRP (1:5000, Thermo, 31430) which was used as the secondary antibody.

2.5. RNA Isolation, reverse-transcription, and real-time quantitative PCR (q-PCR)

Total RNA was extracted by using TRIzol reagent (Invitrogen). Total RNA was used to generate cDNA by using PrimeScript reverse transcriptase reagent kit (Takara, RR014A) according to the manufacturer’s instructions. Real-time quantitative PCR was performed by using the specific SYBR Select Master Mix (Life technologies, 4472908) in a MX3000p cycler (Stratagene). Changes of mRNA levels were determined by the 2-CT method using Actin for internal crossing normalization. The following PCR primers were used: MACC1 (forward 5’-GGCTGTGATGCTACGAGAT A-3’; reverse 5’-ACACCAGGACAATGCCTACT-3’), ACTB (forward 5’-CATGTACGTTGCTATCCAGGC-3’; reverse 5’-CTCCTTAATGTCACGCACGAT-3’).

2.6. Statistical analysis

Student’s t-test or analysis of variance (ANOVA) was used to compare the values of the test and control samples in vitro and in vivo. Survival curves were calculated using the Kaplan Meier method. The log-rank test was used to analyze overall survival (OS) time between different clinicopathological factors in lung adenocarcinoma. Univariate and multivariate analysis were performed using the Cox regression model. Data was analyzed by the SPSS 20 software (Inc, Chicago, IL). Values of p< 0.05 were considered statistically significant difference.

3. Results

3.1. Clinicopathologic characteristics of patients

The overall clinicopathologic characteristics of the 131 patients were summarized in Table 1. Among 131 patients, 68 (51.9%) were male and 63 (48.1%) were female. Tumors were classified as MIA, lepidic, acinar, papillary, micropapillary, solid and mucinous in 11 (8.4%), 22 (16.8%), 50 (38.2%), 31 (23.7%), 3 (2.3%), 3 (2.3%) and 11 (8.4%) of the cases, respectively. The number of patients with well, moderate and poor differentiation was 76 (58.0%), 49 (37.4%) and 6 (4.6%), respectively. Seventeen (13.0%) and 10 (7.6%) patients appeared lymph node metastasis and blood vessel invasion, respectively. One hundred and thirteen (86.3%) patients with TNM stage I, 15 (11.5%) patients with TNM stage II and 3 (2.3%) patients with TNM stage III. The preoperative serum carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC) and cytokeratin-19 fragments (CYFRA21) level were elevated in 10 (7.6%), 53 (40.5%) and 53 (40.5%) patients, respectively.

Table 1.

Clinicopathologic characteristics in 131 patients with completely resected small ( 2 cm) invasive lung adenocarcinoma

Variable Number (%)
Total   131 (100)
Sex
 Male 68 (51.9)
 Female 63 (48.1)
Age
69 y 66 (50.4)
> 69 y 65 (49.6)
Smoking
 Non-smoker 50 (38.2)
 Ex-smoker 38 (29.0)
 Smoker 43 (32.8)
WHO classification (4th Edition)
 MIA 11 (8.4)
 Lepidic 22 (16.8)
 Acinar 50 (38.2)
 Papillary 31 (23.7)
 Micropapillary 3 (2.3)
 Solid 3 (2.3)
 Mucinous 11 (8.4)
Differentiation
 Well 76 (58.0)
 Moderate 49 (37.4)
 Poor 6 (4.6)
Lymph node metastasis
 Absent 114 (87.0)
 Present 17 (13.0)
Blood vessel invasion
 Absent 121 (92.4)
 Present 10 (7.6)
TNM stage
 I 113 (86.3)
 II 15 (11.5)
 III 3 (2.3)
CEA
 Abnormal 10 (7.6)
 Normal 121 (92.4)
SCC
 Abnormal 53 (40.5)
 Normal 78 (59.5)
CYFRA21-1
 Abnormal 53 (40.5)
 Normal 78 (59.5)
MACC1 expression
 High expression 53 (40.5)
 Low expression 78 (59.5)

Abbreviations: TNM, tumor, node, metastases; MIA, minimally invasive adenocarcinoma; CEA, carcinoembryonic antigen; SCC, squamous cell carcinoma antigen; CYFRA21-1, serum cytokeratin-19 fragments; MACC1, metastasis-associated in colon cancer 1.

3.2. Association between clinicopathologic characteristics and MACC1 expression

Among 131 patients, high MACC1 expression was observed in 53 (40.5%), and typical appearances of high and low MACC1 expression were shown in Fig. 1. Correlation between clinicopathologic characteristics and MACC1 expression were summarized in Table 2. MACC1 expression was positively correlated with differentiation (P= 0.005) and blood vessel invasion (P= 0.001) but not with sex, age, smoking status, lymph node metastasis, TNM stage, preoperative serum CEA, SCC and CYFRA21 level.

Figure 1.

Figure 1.

Representative IHC staining in small lung adenocarcinoma tissue. Notes: The typical appearances had shown high and low expression of MACC1 by IHC, respectively. Original magnification 200 × and 400 × in inset.

Table 2.

Relations between the expression of MACC1 and clinicopathologic characteristics in invasive lung adenocarcinoma

Variable MACC1 expression P-value
High (%) Low (%)
Total 53 (40.5) 78
Sex 0.596
 Male 29 (42.6) 39
 Female 24 (38.1) 39
Age 0.126
69 y 31 (47.0) 35
> 69 y 22 (33.8) 43
Smoking 0.149
 Non-smoker 15 (30.0) 35
 Ex-smoker 17 (44.7) 21
 Smoker 21 (48.8) 22
WHO classification 0.584
 MIA 2 9
 Lepidic 10 12
 Acinar 19 31
 Papillary 13 18
 Micropapillary 2 1
 Solid 1 2
 Mucinous 6 5
Differentiation 0.005
 Well 24 (31.6) 52
 Moderate 24 (49.0) 25
 Poor 5 (83.3) 1
Lymph node metastasis 0.098
 Absent 43 (37.7) 71
 Present 10 (58.8) 7
Blood vessel invasion 0.001
 Absent 44 (36.4) 77
 Present 9 (90.0) 1
TNM stage 0.144
 I 43 (38.1) 70
 II 8 (53.3) 7
 III 2 (66.7) 1
CEA 0.375
 Abnormal 5 (50.0) 5
 Normal 48 (39.7) 73
SCC 0.248
 Abnormal 6 (11.3) 47
 Normal 5 (6.4) 73
CYFRA21-1 0.894
 Abnormal 10 (18.9) 43
 Normal 14 (17.9) 64

Notes: Statistical significance was evaluated using the chi-square test. Differences were considered to be statistically significant for P-value < 0.05 which are shown in bold. Abbreviations: TNM, tumor, node, metastases; MIA, minimally invasive adenocarcinoma; CEA, carcinoembryonic antigen; SCC, squamous cell carcinoma antigen; CYFRA21-1, serum cytokeratin-19 fragments; MACC1, metastasis-associated in colon cancer 1.

3.3. MACC1 is over-expressed in human lung adenocarcinoma cell lines

Next, we investigated the MACC1 expression in 4 human lung adenocarcinoma cell lines (A549, H358, H460, H322) and 1 normal human fetal lung fibroblast (HFL-1) by Western blotting and real-time quantitative PCR assays. As shown in Fig. 2, higher expression of MACC1 was observed in lung adenocarcinoma cell lines compared with normal human fetal lung fibroblast.

Figure 2.

Figure 2.

MACC1 is over-expressed in human lung adenocarcinoma cell lines. Notes: (A) Expression of MACC1 protein detected by Western blot analysis in cell lines. (B) Expression of MACC1 mRNA detected by Q-PCR in cell lines (P*< 0.05, P**< 0.01). Error bars represent mean ± SD. Abbreviations: GAPDH, glyceraldehyde-3-phosphate dehydrogenase; SD, standard deviation.

3.4. Impact of risk factor on survival and recurrence

As shown in Table 3 and Fig. 3, poor differentia- tion (P= 0.010), lymph node metastasis (P= 0.001), blood vessel invasion (P= 0.006), advanced TNM stage (P< 0.001) and high MACC1 expression (P= 0.018) had a shorter overall survival (OS) by univariate analysis. In multivariate analysis, blood vessel invasion (odds ratio [OR] = 9.116; 95% confidence interval [CI], 1.822–45.618; P= 0.007), advanced TNM stage (OR = 0.015; 95% CI, 0.002–0.115; P< 0.001) and high MACC1 expression (OR = 5.684; 95% CI, 1.145–28.210; P= 0.034) were shown as independent risk factors of OS (Table 4). Meanwhile, the results showed that poor differentiation (P= 0.006), lymph node metastasis (P< 0.001), advanced TNM stage (P< 0.001), high level of serum SCC (P= 0.006) and high MACC1 expression (P= 0.031) were related to worse disease-free survival (DFS) by univariate analysis (Table 3 and Fig. 4). Furthermore, lymph node metastasis (OR = 0.054; 95% CI, 0.004–0.656; P= 0.022), advanced TNM stage (OR = 0.003; 95% CI, 0.001–0.072; P< 0.001), high level of serum SCC (OR = 4.598; 95% CI, 1.233–17.147; P= 0.023) and high MACC1 expression (OR = 4.667; 95% CI, 1.372–15.877; P= 0.014) were shown as independent risk factors of DFS, according to Cox proportional hazards model (Table 5).

Table 3.

Univariate analysis overall survival (OS) and disease-free survival (DFS) on different clinicopathological factors by Cox regression

Variable 5-OS 5-DFS
OR 95% CI P-value OR 95% CI P-value
Sex
 Male 1.000 1.000
 Female 0.742 0.209–2.633 0.643 0.690 0.246–1.939 0.482
Age
69 y 1.000 1.000
> 69 y 1.096 0.314–3.789 0.885 0.487 0.166–1.425 0.189
Smoking
 Non-smoker 0.315 0.061–1.624 0.167 0.549 0.155–1.944 0.352
 Ex-smoker 0.679 0.162–2.844 0.596 0.956 0.292–3.132 0.940
 Smoker 1.000 1.000
WHO classification
 MIA < 0.001 0.974 < 0.001 0.984
 Lepidic < 0.001 0.963 0.142 0.015–1.368 0.091
 Acinar 0.278 0.078–0.986 0.047 0.204 0.041–1.012 0.052
 Papillary 0.147 0.027–0.803 0.027 0.111 0.110–1.066 0.057
 Micropapillary 0.864 0.096–7.742 0.896 1.714 0.175–16.766 0.643
 Solid 3.068 0.558–16.860 0.197 1.215 0.125–11.822 0.867
 Mucinous 1.000 1.000
Differentiation
 Well 0.092 0.015–0.564 0.010 0.066 0.009–0.466 0.006
 Moderate 0.230 0.043–1.212 0.083 0.593 0.131–2.681 0.498
 Poor 1.000 1.000
Lymph node metastasis
 Absent 1.000 1.000
 Present 9.996 2.673–37.382 0.001 9.821 3.545–27.202 < 0.001
Blood vessel invasion
 Absent 1.000 1.000
 Present 7.098 1.769–28.488 0.006 3.506 0.988–12.439 0.052
TNM stage
 I 0.033 0.006–0.185 < 0.001 0.041 0.008–0.208 < 0.001
 II 0.209 0.035–1.268 0.089 0.456 0.094–2.227 0.332
 III 1.000 1.000
CEA
 Abnormal 1.406 0.178–11.104 0.747 0.899 0.118–6.836 0.918
 Normal 1.000 1.000
SCC
 Abnormal 3.739 0.768–18.195 0.102 4.966– 1.576–15.647 0.006
 Normal 1.000 1.000
CYFRA21-1
 Abnormal 2.044 0.525–7.957 0.303 1.101 0.311–3.901 0.882
 Normal 1.000 1.000
MACC1
 High expression 6.515 1.382–30.721 0.018 3.270 1.117–9.569 0.031
 Low expression 1.000 1.000

Notes: Statistical significance was evaluated using the Cox regression test. Differences were considered to be statistically significant for P-value < 0.05 which are shown in bold. Abbreviations: OR, odds ratio; MIA, minimally invasive adenocarcinoma; TNM, tumor, node, metastases; CEA, carcinoembryonic antigen; SCC, squamous cell carcinoma antigen; CYFRA21-1, serum cytokeratin-19 fragments; MACC1, metastasis-associated in colon cancer 1.

Figure 3.

Figure 3.

Kaplan-Meier survival curves for OS in 131 patients with small invasive lung adenocarcinoma after complete resection. Notes: (A) and (B) Patients with blood vessel invasion (P= 0.007) or advanced TNM stage (P< 0.001) had a shorter OS. (C) High expression of MACC1 was associated with worse OS (P= 0.034) in lung adenocarcinoma. Abbreviation: TNM, tumor, node, metastases.

Table 4.

Multivariate analysis of overall survival using Cox regression

Variable Overall survival
OR 95% CI P-value
Differentiation
 Well 0.913 0.068–12.182 0.945
 Moderate 0.827 0.093–7.377 0.865
 Poor 1.000
Lymph node metastasis
 Absent 0.550 0.244–1.320 0.644
 Present 1.000
Blood vessel invasion
 Absent 1.000
 Present 9.116 1.822–45.618 0.007
TNM stage
 I 0.015 0.002–0.115 < 0.001
 II 0.112 0.016–0.767 0.026
 III 1.000
MACC1
 High expression 5.684 1.145–28.210 0.034
 Low expression 1.000

Notes: Statistical significance was evaluated using the Cox regression test. Differences were considered to be statistically significant for P-value < 0.05 which are shown in bold. Abbreviations: OR, odds ratio; TNM, tumor, node, metastases; MACC1, metastasis-associated in colon cancer 1.

Figure 4.

Figure 4.

Kaplan-Meier survival curves for DFS in 131 patients with small invasive lung adenocarcinoma after complete resection. Notes: (A) and (B) Patients with lymph node metastasis (P= 0.022) or advanced TNM stage (P< 0.001) had a shorter DFS. (C) High level of serum SCC (P= 0.023)or high expression of MACC1 (P= 0.014) was associated with worse DFS. Abbreviation: TNM, tumor, node, metastases; SCC, squamous cell carcinoma antigen.

Table 5.

Multivariate analysis of disease-free survival using Cox regression

Variable Disease-free survival
OR 95% CI P-value
Differentiation
 Well 0.447 0.046–4.356 0.488
 Moderate 1.522 0.275–8.429 0.631
 Poor 1.000
Lymph node metastasis
 Absent 0.054 0.004–0.656 0.022
 Present 1.000
TNM stage
 I 0.003 0.001–0.072 < 0.001
 II 0.264 0.048–1.453 0.126
 III 1.000
SCC
 Abnormal 4.598 1.233–17.147 0.023
 Normal 1.000
MACC1
 High expression 4.667 1.372–15.877 0.014
 Low expression 1.000

Notes: Statistical significance was evaluated using the Cox regression test. Differences were considered to be statistically significant for P-value < 0.05 which are shown in bold. Abbreviations: OR, odds ratio; TNM, tumor, node, metastases; SCC, squamous cell carcinoma antigen; MACC1, metastasis-associated in colon cancer 1.

4. Discussion

The prevalence of low-dose spiral computed tomography screening has significantly increased the detection of small ( 2 cm) lung adenocarcinoma [14]. The main treatment for small ( 2 cm) lung adenocarcinoma is complete surgical resection with mediastinal lymph node dissection or systematic sampling. Unfortunately, in clinical practice, part of patients with small ( 2 cm) lung adenocarcinoma showed early metastasis and relapse after complete surgical resection [15, 16]. Therefore, identification of patients with poor prognosis through effective molecular biomarker is of significant importance, because such patients require more intensive follow-up and adjuvant treatment.

Our compelling evidence revealed that MACC1 is an independent prognostic marker in patients with small invasive lung adenocarcinoma after complete surgical resection. Specifically, we report the following findings: (1) the incidence of MACC1 positive staining was significantly higher in recurrent cases than in non-recurrent ones; (2) the protein and mRNA expression levels of MACC1 were much higher in lung adenocarcinoma cell lines than in HFL-1 cell line; (3) clinically, univariate and multivariate Cox regression analysis showed that MACC1 was an independent risk factor prognostic indicator for patients with small ( 2 cm) lung adenocarcinoma. These results indicate that the expression of MACC1 is a useful prognostic marker for patients with small lung adenocarcinoma.

MACC1 was previously reported to regulate invasion and metastasis through regulating HGF/c-Met pathway in several cancer types [6, 17, 18]. We previously found that MACC1 was a useful marker for predicting postoperative recurrence in patients with lung adenocarcinoma following surgery [19]. However, the prognostic role of MACC1 expression in resected small invasive lung adenocarcinoma remains unclear. In the present study, we found that 53 (40.5%) patients with small invasive lung adenocarcinoma had high MACC1 expression primarily distributed in cytoplasm. Nevertheless, this study focused on invasive adenocarcinoma and especially those with the diameter 2 cm in the enrolled patients, our previous study and other researchers reported the higher proportion of MACC1 expression appeared in lung cancer [19, 20, 21]. Furthermore, we confirmed the high expression of MACC1 in lung adenocarcinoma through detecting the protein and mRNA expression in human lung adenocarcinoma cell lines (A549, H358, H460 and H322). The Western blotting and real-time quantitative PCR results showed that lung adenocarcinoma cells exhibited higher expression of MACC1 than HFL-1 cells.

According to our results, high expression of MACC1 was positively correlated with differentiation (P= 0.005) and blood vessel invasion (P= 0.001) but not with other clinical pathologic factors. Consistent with our data, recent reports have shown that the expression of MACC1 is positively correlated with differentiation grade [20, 21]. Meanwhile, blood vessel invasion is a well-established adverse prognostic factor for non-small cell lung carcinoma (NSCLC) [22, 23]. Recently, blood vessel invasion has been demonstrated as a independent predictor of worse OS and recurrence in small-sized NSCLC [24]. In our study, poor differentiation (P= 0.010), lymph node metastasis (P= 0.001), blood vessel invasion (P= 0.006), advanced TNM stage (P< 0.001) and high MACC1 expression (P= 0.018) affected the OS of the 131 patients with small lung adenocarcinoma by univariate analysis; poor differentiation (P= 0.006), lymph node metastasis (P< 0.001), advanced TNM stage (P< 0.001), high level of serum SCC (P= 0.006) and high MACC1 expression (P= 0.031) were related to the DFS by univariate analysis. In the further multivariate analysis, blood vessel invasion (OR = 9.116; 95% CI, 1.822–45.618; P= 0.007), advanced TNM stage (OR = 0.015; 95% CI, 0.002–0.115; P< 0.001) and high MACC1 expression (OR = 5.684; 95% CI, 1.145–28.210; P= 0.034) were shown as independent risk factors of OS. Furthermore, lymph node metastasis (OR = 0.054; 95% CI, 0.004–0.656; P= 0.022), advanced TNM stage (OR = 0.003; 95% CI, 0.001–0.072; P< 0.001), high level of serum SCC (OR = 4.598; 95% CI, 1.233–17.147; P= 0.023) and high MACC1 expression (OR = 4.667; 95% CI, 1.372–15.877; P= 0.014) were shown as independent risk factors of DFS.

The limitations of this study should be taken into consideration. We did not record the information of treatment after recurrence, which may result in bias to OS. In addition, this retrospective analysis is a single institutional analysis, and focus on small-sized tumor samples. Thus, the inherent bias is inevitable.

5. Conclusions

These evidences revealed that MACC1 is an independent indicator in patients with small invasive lung adenocarcinoma after complete surgical resection. Detection of the MACC1 expression may be useful to for identifying patients with small lung adenocarcinoma who require more intensive follow-up and adjuvant treatment following a complete resection.

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (81173453, 81774078). Natural Science Foundation of Liaoning Province, China (201602227).

Conflict of interest

The authors declare that they have no competing interests.

References

  • [1]. Siegel R.L., Miller K.D. and Jemal A., Cancer statistics, 2016, CA: a cancer journal for clinicians 66(1) (2016), 7–30. [DOI] [PubMed] [Google Scholar]
  • [2]. The National Lung Screening Trial Research, Church T.R., Black W.C., Aberle D.R., Berg C.D., Clingan K.L., Duan F., Fagerstrom R.M., Gareen I.F., Gierada D.S., Jones G.C., Mahon I., Marcus P.M., Sicks J.D., Jain A. and Baum S., Results of initial low-dose computed tomographic screening for lung cancer, The New England journal of medicine 368(21) (2013), 1980–1991. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [3]. Goldstraw P., Chansky K., Crowley J., Rami-Porta R., Asamura H., Eberhardt W.E., Nicholson A.G., Groome P., Mitchell A. and Bolejack V., S. International Association for the Study of Lung Cancer, A.B. Prognostic Factors Committee, I. Participating, S. International Association for the Study of Lung Cancer, B. Prognostic Factors Committee Advisory, I. Participating, The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer, Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer 11(1) (2016), 39–51. [DOI] [PubMed] [Google Scholar]
  • [4]. Sawabata N., Prognosis of lung cancer patients in Japan according to data from the Japanese Joint Committee of Lung Cancer Registry, Respiratory investigation 52(6) (2014), 317–321. [DOI] [PubMed] [Google Scholar]
  • [5]. Cancer Genome Atlas Research Network, Comprehensive molecular profiling of lung adenocarcinoma, Nature 511(7511) (2014), 543–550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6]. Stein U., Walther W., Arlt F., Schwabe H., Smith J., Fichtner I., Birchmeier W. and Schlag P.M., MACC1, a newly identified key regulator of HGF-MET signaling, predicts colon cancer metastasis, Nature medicine 15(1) (2009), 59–67. [Google Scholar]
  • [7]. Wang L., Wu Y., Lin L., Liu P., Huang H., Liao W., Zheng D., Zuo Q., Sun L., Huang N., Shi M., Liao Y. and Liao W., Metastasis-associated in colon cancer-1 upregulation predicts a poor prognosis of gastric cancer, and promotes tumor cell proliferation and invasion, International journal of cancer 133(6) (2013), 1419–1430. [DOI] [PubMed] [Google Scholar]
  • [8]. Lin L., Huang H., Liao W., Ma H., Liu J., Wang L., Huang N., Liao Y. and Liao W., MACC1 supports human gastric cancer growth under metabolic stress by enhancing the Warburg effect, Oncogene 34(21) (2015), 2700–2710. [DOI] [PubMed] [Google Scholar]
  • [9]. Liu J., Pan C., Guo L., Wu M., Guo J., Peng S., Wu Q. and Zuo Q., A new mechanism of trastuzumab resistance in gastric cancer: MACC1 promotes the Warburg effect via activation of the PI3K/AKT signaling pathway, Journal of hematology & oncology 9(1) (2016), 76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [10]. Lederer A., Herrmann P., Seehofer D., Dietel M., Pratschke J., Schlag P. and Stein U., Metastasis-associated in colon cancer 1 is an independent prognostic biomarker for survival in Klatskin tumor patients, Hepatology 62(3) (2015), 841–850. [DOI] [PubMed] [Google Scholar]
  • [11]. Hagemann C., Fuchs S., Monoranu C.M., Herrmann P., Smith J., Hohmann T., Grabiec U., Kessler A.F., Dehghani F., Lohr M., Ernestus R.I., Vince G.H. and Stein U., Impact of MACC1 on human malignant glioma progression and patients’ unfavorable prognosis, Neuro-oncology 15(12) (2013), 1696–1709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12]. Muendlein A., Hubalek M., Geller-Rhomberg S., Gasser K., Winder T., Drexel H., Decker T., Mueller-Holzner E., Chamson M., Marth C. and Lang A.H., Significant survival impact of MACC1 polymorphisms in HER2 positive breast cancer patients, European journal of cancer 50(12) (2014), 2134–2141. [DOI] [PubMed] [Google Scholar]
  • [13]. Zhao S., Guo T., Li J., Uramoto H., Guan H., Deng W. and Gu C., Expression and prognostic value of GalNAc-T3 in patients with completely resected small (<⁣/⁣= 2 cm) peripheral lung adenocarcinoma after IASLC/ATS/ERS classification, Onco Targets and therapy 8 (2015), 3143–3152. [Google Scholar]
  • [14]. Lee H.Y., Han J., Lee K.S., Koo J.H., Jeong S.Y., Kim B.T., Cho Y.S., Shim Y.M., Kim J., Kim K. and Choi Y.S., Lung adenocarcinoma as a solitary pulmonary nodule: prognostic determinants of CT, PET, and histopathologic findings, Lung cancer 66(3) (2009), 379–385. [DOI] [PubMed] [Google Scholar]
  • [15]. Zhou Q., Suzuki K., Anami Y., Oh S. and Takamochi K., Clinicopathologic features in resected subcentimeter lung cancer-status of lymph node metastases, Interactive cardiovascular and thoracic surgery 10(1) (2010), 53–57. [DOI] [PubMed] [Google Scholar]
  • [16]. Liu S., Wang R., Zhang Y., Li Y., Cheng C., Pan Y., Xiang J., Zhang Y., Chen H. and Sun Y., Precise Diagnosis of Intraoperative Frozen Section Is an Effective Method to Guide Resection Strategy for Peripheral Small-Sized Lung Adenocarcinoma, Journal of clinical oncology: official journal of the American Society of Clinical Oncology 34(4) (2016), 307–313. [DOI] [PubMed] [Google Scholar]
  • [17]. Galimi F., Torti D., Sassi F., Isella C., Cora D., Gastaldi S., Ribero D., Muratore A., Massucco P., Siatis D., Paraluppi G., Gonella F., Maione F., Pisacane A., David E., Torchio B., Risio M., Salizzoni M., Capussotti L., Perera T., Medico E., Di Renzo M.F., Comoglio P.M., Trusolino L. and Bertotti A., Genetic and expression analysis of MET, MACC1, and HGF in metastatic colorectal cancer: response to met inhibition in patient xenografts and pathologic correlations, Clin Cancer Res 17(10) (2011), 3146–3156. [DOI] [PubMed] [Google Scholar]
  • [18]. Arlt F. and Stein U., Colon cancer metastasis: MACC1 and Met as metastatic pacemakers, Int J Biochem Cell Biol 41(12) (2009), 2356–2359. [DOI] [PubMed] [Google Scholar]
  • [19]. Chundong G., Uramoto H., Onitsuka T., Shimokawa H., Iwanami T., Nakagawa M., Oyama T. and Tanaka F., Molecular diagnosis of MACC1 status in lung adenocarcinoma by immunohistochemical analysis, Anticancer research 31(4) (2011), 1141–1145. [PubMed] [Google Scholar]
  • [20]. Wang Z., Li Z., Wu C., Wang Y., Xia Y., Chen L., Zhu Q. and Chen Y., MACC1 overexpression predicts a poor prognosis for non-small cell lung cancer, Medical oncology 31(1) (2014), 790. [DOI] [PubMed] [Google Scholar]
  • [21]. Zhou L., Yu L., Zhu B., Wu S., Song W., Gong X. and Wang D., Metastasis-associated in colon cancer-1 and aldehyde dehydrogenase 1 are metastatic and prognostic biomarker for non-small cell lung cancer, BMC cancer 16(1) (2016), 876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [22]. Dziedzic D.A., Rudzinski P., Langfort R. and Orlowski T., Polish Lung Cancer Study Group, Risk Factors for Local and Distant Recurrence After Surgical Treatment in Patients With Non-Small-Cell Lung Cancer, Clinical lung cancer 17(5) (2016), e157–e167. [DOI] [PubMed] [Google Scholar]
  • [23]. Okada S., Mizuguchi S., Izumi N., Komatsu H., Toda M., Hara K., Okuno T., Shibata T., Wanibuchi H. and Nishiyama N., Prognostic value of the frequency of vascular invasion in stage I non-small cell lung cancer, General thoracic and cardiovascular surgery 65(1) (2017), 32–39. [DOI] [PubMed] [Google Scholar]
  • [24]. Shimada Y., Saji H., Kato Y., Kudo Y., Maeda J., Yoshida K., Hagiwara M., Matsubayashi J., Kakihana M., Kajiwara N., Ohira T. and Ikeda N., The Frequency and Prognostic Impact of Pathological Microscopic Vascular Invasion According to Tumor Size in Non-Small Cell Lung Cancer, Chest 149(3) (2016), 775–785. [DOI] [PubMed] [Google Scholar]

Articles from Cancer Biomarkers: Section A of Disease Markers are provided here courtesy of SAGE Publications

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