Skip to main content
IOS Press Open Library logoLink to IOS Press Open Library
. 2024 Sep 19;41(1):41–54. doi: 10.3233/CBM-230303

Differentially expressed microRNA in prognosis of gastric cancer with Lauren classification

Wenjiao Chen a,1,b, Qin Guo c,1, Huo Zhang d,1, Yiping Du e, Yan Zhou b, Zebo Huang f,*, Meiling Zhang g,*, Songbing Qin a,*
PMCID: PMC11492042  PMID: 39177588

Abstract

BACKGROUND:

Gastric cancer (GC) is one of the most common tumors. There were several classifications of GC recently. The value of Lauren classification in evaluating the prognosis after radical gastrectomy was still unclear and the prognosis of gastric cancer remained relatively poor in the absence of prognostic biomarkers. This study aimed to explore microRNA (miRNA) in the prognosis of GC with different Lauren classification.

METHODS:

A retrospective study of 1144 patients was performed in this study. Quantificational reverse transcription-PCR (qRT-PCR) was used to examine the expression of miRNAs. Univariate and multivariate analysis were performed to evaluate prognosis value of Lauren classification.

RESULTS:

Total 1144 GC patients were recruited in this cohort, including 302 diffuse type (26.4%), 436 intestinal type (38.1%) and 406 mixed type (35.5%) GC. Multivariate analysis showed that Lauren classification, patients’ age, tumor size, tumor infiltrating depth, vascular nerve infiltrating and metastatic lymph nodes ration were significantly correlated with GC patients’ OS and DFS. The miR-141-3p, miR-200b-3p and miR-133a-5p were significantly down-regulated in diffuse type compared to intestinal type GC tissues, the miR-105-5p had significant lower expression in diffuse type compared with intestinal type and mixed type GC tissues. As a consequence of univariate analysis, low miR-141-3p in diffuse type GC showed significant worse OS and DFS than high miR-141-3p.

CONCLUSIONS:

Lauren classification was an independent prognostic factor in GC. MiR-141-3p was an independent prognostic factor and a promising prognostic biomarker in Lauren classification GC.

Keywords: Gastric cancer, Lauren classification, microRNA, prognosis

1. Introduction

Gastric cancer (GC) is the third leading contributor of cancer mortality worldwide [1]. To date, the anatomical American Joint Committee on Cancer (AJCC) and Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) staging system is the most widely used for describing GC states [2]. However, GC is a multifactorial and multistage disease [3]. It is hard to have better understanding on prognostic value just using TNM classification without reference to its pathology [4]. Since 1965, the Lauren classification has been proposed and become one of effective methods based on the histological structure of GC cells. GC is divided into diffuse type, intestinal type and mixed type according to the Lauren classification [5]. The histopathology of intestinal type is gland like structures and is considered to be associated with chronic inflammation induced by Helicobacter Pylori infection, smoking, obesity and other dietary factors [6, 7], diffuse type is isolated-cell carcinoma and induced by active inflammation which leads to poor prognosis [8]. Thus, the prognostic relevance of GC using Lauren classification still remains unilluminated.

Primary studies reported that different moleculars played important roles in GC prognosis prediction, such as KRAS, APC, TP53 and so on [9, 10]. MicroRNAs (MiRNAs), endogenous non-coding RNAs with 20–22 nucleotides in size, are known as oncogenes or tumor suppressors in various human cancers through regulating target mRNAs [11, 12]. MiR-205/miR-338-3p regulated BCL-2 expression to suppress prostate cancer cells apoptosis [13]. Besides, miRNAs become popular biomarkers for cancer diagnosis and prognosis [14]. MiR-16 was confirmed the diagnosis value in common cancer like lung cancer, gastric cancer and endometrioid endometrial cancer [15]. MiR-487a worked as prognostic biomarker in hepatocelluar carcinoma [16]. MiR-194 was verified as favourable prognosis biomarker in GC [17]. It was reported that the down-modulation of miR-375 is specifically linked to Lauren’s classification [18]. There is also research that suggests miR-18a-5p plays diagnostic and therapeutic potencies in mixed-type gastric cancer [19]. However, the application of miRNA on predicting prognosis in Lauren classification GC is still underway and needs further investigation.

To the point of controversy, we performed a retrospective study of 1144 patients who received radical gastrectomy and analyzed the clinical characteristics and significance in Lauren classification. In addition, we examined the expression levels and evaluated the prognostic value of related miRNAs from different Lauren classification GC tissues. This study provided the theoretical basis for the potential use of miRNAs in diagnosis and prognosis of gastric cancer with different Lauren classification.

2. Materials and methods

2.1. Study cohort

We collected data on 1144 patients who received radical gastrectomy at First Affiliated Hospital of Nanjing Medical University from January, 2005 to December, 2011. After surgery, GC patients were followed up every 3 months at first 2 years then every 6 months within 5 years, annually after 5 years, the last follow-up was in June, 2017. All patients from the cohort underwent radical gastrectomy and histologically confirmed. Clinical stage and histological classifications of GC were used the WHO classification criteria and the eighth edition of the AJCC TNM classification for GC.

2.2. Sample collection

We collected 145 GC tissues from the study cohort. Inclusion criteria include (1) complete clinical data, (2) Standard D2 lymph node dissection, (3) TNM stage I, to III, (4) no preoperative radiotherapy or chemotherapy, (5) postoperative chemotherapy regimen based on 5-FU and completed at least 4 cycles.

2.3. RNA extraction

Sections (8 μm slices) were prepared from paraffin-embedded specimen. Paraffin was removed by dewaxing reagent to obtain GC tissues after centrifugation. Total RNA was extracted from samples using Trizol (Invitrogen, America) method [20]. The concentration and quality of total RNA were evaluated by the ultraviolet spectrophotometer.

2.4. Quantitative RT-PCR

The cDNA was conducted using the specific primers of reverse transcription (RT) (Exiqon, Denmark). The amplification of miRNA was used Bulge-Loop miRNA qRT-PCR Primer Set (RiboBio, China) and evaluated the product fluorescence by SYBR Green (TaKaRa, China). RT reaction was carried out at 42C for 60 min followed by 70C for 10 min. The quantitative RT-PCR (qRT-PCR) was carried on LightCycler® 480 Real-Time PCR System (Roche Diagnostics, Germany) in 384-well plates at 95C for 20 s, followed by 40 cycles of 95C for 10 s, 60C for 20 s and then 70C for 10 s, the melting curve program was run immediately. All reactions were performed in triplicate. The RNU6B (U6) was used as the standard for miRNA expression normalization [21]. The miRNA relative expression levels were calculated by the 2 - ΔΔCt method, ΔCt = Ct (miRNA) – Ct (U6).

2.5. Statistical analysis

The differential miRNAs expression levels between GC tissues and control tissues were analyzed by Mann-Whitney test. Clinical characteristics among Lauren classification groups and the relationship with miRNAs were analyzed by one-way ANOVA or χ2 test. Survival curves and univariate analysis were used the log-rank test. Five-year survival rates were estimated by life-table. Multivariate analysis was performed using Cox’s proportional hazards regression model. All the statistical analyses were performed using SPSS software (version 20.0, IBM, USA). P value < 0.05 was defined statistically significant.

3. Results

3.1. Clinicopathological characteristics of study subjects

Total 1144 GC patients (846 males and 298 females, mean age, 61 years) were recruited in this cohort, including 302 diffuse type (26.4%), 436 intestinal type (38.1%) and 406 mixed type (35.5%) GC, the demographic information of GC patients were summarized in Table 1. We conducted the correlation analysis between Lauren classification and the differentiated. The results indicated that GC patients with diffuse type were younger (< 45 years) (P< 0.001), female predominant (P< 0.001), distal stomach predominant (P< 0.001), more infiltrating type and vascular nerve (P< 0.001), higher incidence in signet ring carcinoma and mucinous carcinoma (P< 0.001), TNM III stage predominant (P< 0.001). The intestinal type GC patients showed that were older ( 60 years) (P< 0.001), less distal stomach predominant (P< 0.001), well differentiated (P< 0.001), Borrmann type predominant (P< 0.001), relative smaller tumor size (diameter 3 cm) (P< 0.001), less vascular nerve infiltrating (P< 0.001), less lymphovascular invasion (P< 0.001), TNM I stage predominant (P< 0.001).

Table 1.

The correlation analysis between Lauren classification and clinicopathological characteristics

Variables Lauren classification χ2 P value
Diffuse type Intestinal type Mixed type
Gender 24.48 < 0.001
 Male 191 (22.6%) 352 (41.6%) 303 (35.8%)
 Female 111 (37.2%) 84 (28.2%) 103 (34.6%)
Age 71.982 < 0.001
< 45 years 55 (59.1%) 9 (9.7%) 29 (31.2%)
 45–60 years 169 (26.8%) 248 (39.3%) 214 (33.9%)
60 years 78 (18.6%) 179 (42.6%) 163 (38.8%)
Tumor site 85.254 < 0.001
 Proximal 63 (13.5%) 236 (50.6%) 167 (35.8%)
 Middle 122 (32.4%) 116 (30.9%) 138 (36.7%)
 Distal 117 (38.7%) 84 (27.8%) 101 (33.4%)
Tumor subtype 58.011 < 0.001
 Non-infiltrating type 50 (25.5%) 101 (51.5%) 45 (23.0%)
 Borrmann type 207 (24.0%) 323 (37.4%) 333 (38.6%)
 Infiltrating type 45 (52.9%) 12 (14.1%) 28 (32.9%)
Pathological classifications 149.681 < 0.001
 Adenocarcinoma 217 (22.1%) 413 (42.0%) 354 (36.0%)
 Mucinous carcinoma 35 (32.7%) 23 (21.5%) 49 (45.8%)
 Signet ring carcinoma 50 (94.3%) 0 (0%) 3 (5.7%)
Tumor size 28.884 < 0.001
3 cm 120 (25.5%) 209 (44.4%) 142 (30.1%)
 3–6 cm 120 (23.8%) 187 (37.1%) 197 (39.1%)
> 6 cm 62 (36.7%) 40 (23.7%) 67 (39.6%)
Histopathology classification 487.347 < 0.001
 Well differentiated 1 (3.7%) 25 (92.6%) 1 (3.7%)
 Moderately differentiated 4 (1.5%) 247 (91.5%) 19 (7.0%)
 Poor differentiated 297 (35.1%) 164 (19.4%) 386 (45.6%)
Tumor infiltrating depth 51.995 < 0.001
 T1 59 (29.5%) 95 (47.5%) 46 (23.0%)
 T2 25 (14.7%) 84 (55.1%) 46 (30.1%)
 T3 14 (19.4%) 35 (47.8%) 23 (32.8%)
 T4 204 (28.5%) 222 (31.0%) 291 (40.6%)
Vascular nerve infiltrating 82.582 < 0.001
 Negative 154 (24.5%) 310 (49.4%) 164 (26.1%)
 Positive 148 (28.7%) 126 (24.4%) 242 (46.9%)
Number of metastatic lymph nodes 110.381 < 0.001
 N0 92 (21.9%) 222 (52.7%) 107 (25.4%)
 N1 37 (18.0%) 90 (43.7%) 79 (38.3%)
 N2 63 (27.4%) 79 (34.3%) 88 (38.3%)
 N3 110 (38.3%) 45 (15.7%) 132 (46.0%)
Metastatic lymph nodes ration 108.674 < 0.001
 0 92 (21.9%) 222 (52.7%) 107 (25.4%)
0.25 47 (19.5%) 112 (46.5%) 82 (34.0%)
0.5 66 (32.8%) 50 (24.9%) 85 (42.3%)
> 0.5 97 (34.5%) 52 (18.5%) 132 (47.0%)
AJCC 8th TNM stage 71.894 < 0.001
 I 64 (23.9%) 144 (53.7%) 60 (22.4%)
 II 54 (20.7%) 124 (47.5%) 83 (31.8%)
 III 184 (29.9%) 168 (27.3%) 263 (42.8%)

P< 0.05, statistical significance.

3.2. Univariate and multivariate analysis for prognosis of gastric cancer

Among 1144 GC patients, the overall survival (OS) of 1-year, 3-year and 5-year were 90%, 75% and 66%, while the disease free survival (DFS) of 1-year, 3-year and 5-year were 78%, 66% and 59% (Fig. 1A). The univariate analysis showed that Lauren classification was strongly related to the OS and DFS (P< 0.05), the OS and DFS of diffuse type, intestinal type, mixed type GC patients were 51%, 69%, 48% and 49%,67%, 47%, respectively ( Fig. 1B). In addition, the univariate analysis also showed that the prognosis of GC patients were strongly related to the patients’ age, tumor site and size, tumor subtype, pathological classifications, tumor infiltrating depth, vascular nerve infiltrating, number of metastatic lymph nodes and metastatic lymph nodes ration, AJCC 8th edition TNM classification (P< 0.05) (Tables 23).

Figure 1.

Figure 1.

Overall survival (OS) and disease free survival (DFS) curves plotted by the Kaplan-Meier method for (A) 1144 GC patients (B) GC patients with Lauren classification, diffuse type, intestinal type, mixed type.

Table 2.

The univariate analysis between disease free survival (DFS) and clinicopathological characteristics

Variables Numbers DFS (months) 5-year survival (%) χ2 P value
Lauren classification 41.731 < 0.001
 Diffuse type 302 44.7 49
 Intestinal type 436 * 67
 mixed type 406 36.933 47
Gender 0.924 0.336
 Male 846 * 54
 Female 298 * 58
Age 19.242 < 0.001
< 45 years 93 * 58
 45–60 years 631 * 60
60 years 420 37.267 47
Tumor site 8.355 0.015
 Proximal 466 49.267 49
 Middle 376 * 61
 Distal 302 * 56
Tumor subtype 84.799 < 0.001
 Non-infiltrating type 196 * 83
 Borrmann type 863 70.2 51
 Infiltrating type 85 18.9 32
Pathological classifications 2.228 0.328
 Adenocarcinoma 984 * 55
 Mucinous carcinoma 107 68.633 51
 Signet ring carcinoma 53 43.733 49
Tumor size 194.55 < 0.001
3 cm 471 * 77
 3–6 cm 504 31.433 43
> 6 cm 169 16.967 28
Histopathology classification 53.592 < 0.001
 Well differentiated 27 * 96
 Moderately differentiated 270 * 70
 Poor differentiated 847 46.5 49
Tumor infiltrating depth 258.912 < 0.001
 T1 200 * 97
 T2 155 * 79
 T3 72 * 68
 T4 717 26.167 37
Number of metastatic lymph nodes 404.815 < 0.001
 N0 421 * 87
 N1 206 52
 N2 230 31.533 42
 N3 287 13.233 20
Metastatic lymph nodes ration 458.228 < 0.001
 0 421 * 87
0.25 241 * 57
0.5 201 27.9 36
> 0.5 281 12.267 19
AJCC 8th TNM stage 382.954 < 0.001
 I 268 * 96
 II 261 * 72
 III 615 19.7 31
Vascular nerve infiltrating 144.147 < 0.001
 Negative 628 * 70
 Positive 516 26.167 36

*The median survival time was not reached by follow-up, P< 0.05, statistical significance.

Table 3.

The univariate analysis between overall survival (OS) and clinicopathological characteristics

Variables Numbers OS (months) 5-year survival (%) χ2 P value
Lauren classification 46.781 < 0.001
 Diffuse type 302 62.633 51
 Intestinal type 436 * 69
 Mixed type 406 55.367 48
Gender 1.021 0.312
 Male 846 * 55
 Female 298 * 60
Age 19.161 < 0.001
< 45 years 93 * 63
 45–60 years 631 * 61
60 years 420 57.6 49
Tumor site 8.51 0.014
 Proximal 466 65.3 51
 Middle 376 * 62
 Distal 302 * 59
Tumor subtype 82.088 < 0.001
 Non-infiltrating type 196 * 86
 Borrmann type 863 114.567 52
 Infiltrating type 85 29.367 35
Pathological classifications 3.236 0.198
 Adenocarcinoma 984 * 58
 Mucinous carcinoma 107 70.133 53
 Signet ring carcinoma 53 59.933 49
Tumor size 193.159 < 0.001
3 cm 471 * 79
 3–6 cm 504 45.467 45
> 6 cm 169 25.933 30
Histopathology classification 56.797 < 0.001
 Well differentiated 27 * 96
 Moderately differentiated 270 * 72
 Poor differentiated 847 64.967 50
Tumor infiltrating depth 264.464 < 0.001
 T1 200 * 98
 T2 155 * 82
 T3 72 * 69
 T4 717 36.733 39
Vascular nerve infiltrating 145.628 < 0.001
 Negative 628 * 72
 Positive 516 36.367 38
Number of metastatic lymph nodes 412.207 < 0.001
 N0 421 * 88
 N1 206 * 56
 N2 230 43.7 44
 N3 287 20.233 22
Metastatic lymph nodes ration 462.637 < 0.001
 0 421 * 88
0.25 241 * 60
0.5 201 37.267 40
> 0.5 281 20.433 19
AJCC 8th TNM stage 386.133 < 0.001
 I 268 * 96
 II 261 * 75
 III 615 31.133 32

*The median survival time was not reached by follow-up, P< 0.05, statistical significance.

Multivariate analysis were introduced using Cox proportional hazards regression (forward LR stepwise procedure) to analyze independent prognostic predicting factors based on the statistically significant variants in univariate analysis. Multivariate analysis showed that Lauren classification, patients’ age, tumor size, tumor infiltrating depth, vascular nerve infiltrating and metastatic lymph nodes ration were significantly correlated with GC patients’ OS and DFS (P< 0.001) (Table 4). The Lauren classification was an independent prognostic predicting factor in GC and the diffuse type was an independent risk factors for poor prognosis of GC.

Table 4.

The multivariate COX risk model analysis of overall survival (OS) and between disease free survival (DFS)

Endpoint Variables β (regression coefficient) SE Wald value HR (risk ratio) 95% CI P value
DFS
Lauren classification 0.27 0.074 13.13 1.175 (1.041–1.328) < 0.001
Tumor size 0.283 0.069 16.777 1.336 (1.156-1.544) < 0.001
Tumor infiltrating depth 0.397 0.104 14.621 1.476 (1.187–1.836) < 0.001
Vascular nerve 0.359 0.096 13.833 1.433 (1.171–1.754) < 0.001
Metastatic lymph nodes ration 0.457 0.092 24.686 1.558 (1.293–1.879) < 0.001
OS
Lauren classification 0.309 0.075 16.723 1.183 (1.047–1.337) < 0.001
Tumor size 0.295 0.07 17.836 1.338 (1.156–1.548) < 0.001
Tumor infiltrating depth 0.464 0.098 13.579 1.612 (1.284–2.023) < 0.001
Vascular nerve 0.36 0.104 10.941 1.412 (1.151–1.732) < 0.001
Metastatic lymph nodes ration 0.472 0.092 26.185 1.568 (1.300–1.891) < 0.001

P< 0.05, statistical significance.

3.3. Identification of candidate differentially expressed miRNAs in GC

We searched keywords, gastric cancer, stomach cancer, miRNA and Lauren classification in PubMed website. The latest publication time of reference was January, 2017. Finally, a total of 8 references were in line with our topic idea after intensive reading. There were 22 candidate miRNAs, miR-105-5p, miR-100-5p, miR-199a-5p, miR-99a-5p, miR-133a-5p, miR-373-5p, miR-498, miR-202-5p, miR-32-5p, miR-141-3p, miR-182-5p, miR-125b-5p, miR-143-3p, miR-145-5p, miR-494-3p, miR-21-5p, miR-299-5p, miR-365b, miR-499a-5p, miR-200a-3p, miR-200b-3p and miR-200c-3p [22, 23, 24, 25, 26, 27, 28, 29].

Figure 2.

Figure 2.

continued.

The expression levels of 22 miRNAs were verified in 145 GC tissues, 47 diffuse type (32.4%), 50 intestinal type (33.1%), 48 mixed type (34.5%), the clinical features of patients were listed in Table 5. The expressed of miR-202-5p, miR-299-5p, miR-32-5p, miR-365b, miR-373-5p, miR-494-3p, miR-498 and miR-499a-5p were weakly expressed in GC tissues. As shown in Fig. 2, there were no significant difference in miR-100-5p, miR-199a-5p, miR-99a-5p, miR-182-5p, miR-125b-5p, miR-143-3p, miR-145-5p, miR-21-5p, miR-200a-3p, and miR-200c-3p among diffuse type, intestinal type and mixed type GC tissues. Compared to intestinal type GC tissues, the miR-141-3p, miR-200b-3p and miR-133a-5p were significantly down-regulated in diffuse type. Meanwhile, the miR-105-5p had significant lower expression in diffuse type compared with intestinal type and mixed type GC tissues.

Table 5.

Clinicopathological characteristics used in miRNA expression detection

Age
< 45 years 13 (9.0%)
 45–60 years 80 (55.1%)
60 years 52 (35.9%)
Gender
 Male 101 (69.7%)
 Female 44 (30.3%)
Tumor site
 Proximal 62 (42.8%)
 Middle 44 (30.3%)
 Distal 39 (26.9%)
Tumor subtype
 Non-infiltrating type 29 (20.0%)
 Borrmann type 101 (69.7%)
 Infiltrating type 15 (10.3%)
Pathological classifications
 Adenocarcinoma 118 (81.4%)
 Mucinous carcinoma 10 (6.9%)
 Signet ring carcinoma 17 (11.7%)
Tumor size
3 cm 62 (42.8%)
 3–6 cm 57 (39.3%)
> 6 cm 26 (17.9%)
Histopathology classification
 Well differentiated 3 (2.1%)
 Moderately differentiated 30 (20.7%)
 Poor differentiated 112 (77.2%)
Tumor infiltrating depth
 T1 40 (27.6%)
 T2 15 (10.3%)
 T3 30 (20.7%)
 T4 60 (41.4%)
Number of metastatic lymph nodes
 N0 65 (44.8%)
 N1 18 (12.4%)
 N2 31 (21.4%)
 N3 31 (21.4%)
Metastatic lymph nodes ration
 0 65 (44.8%)
0.25 30 (20.7%)
0.5 20 (13.8%)
> 0.5 30 (20.7%)
AJCC 8th TNM stage
 I 47 (32.4%)
 II 28 (19.3%)
 III 70 (48.3%)
Vascular nerve infiltrating
 Negative 94 (64.8%)
 Positive 51 (35.2%)
Lauren classification
 Diffuse type 47 (32.4%)
 Intestinal type 50 (33.1%)
 Mixed type 48 (34.5%)

Figure 2.

Figure 2.

Expression levels of 14 candidate miRNAs in the diffuse type, intestinal type and mixed type GC tissues. Horizontal line: mean with 95% CI. Each P value was calculated by the Mann–Whitney test. P< 0.05 was defined statistically significant.

3.4. Diagnostic and prognostic value of miRNAs in different Lauren classification GC

During the followed up, the median DFS and OS of 145 GC patients was 47.9 ± 17.9 and 50.1 ± 14.8 months, 114 (78.6%) were still alive. To further explore the prognostic value of miRNAs, log-rank test was introduced to analyze the OS and DFS between high miRNA expression and low expression of 14 miRNAs (miR-100-5p, miR-199a-5p, miR-99a-5p, miR-182-5p, miR-125b-5p, miR-143-3p, miR-145-5p, miR-21-5p, miR-200a-3p, miR-200c-3p, miR-141-3p, miR-200b-3p, miR-133a-5p and miR-105-5p) (Table 6). The results showed that only low expression of miR-141-3p lead to worse OS and DFS in contrast to high miR-141-3p (P< 0.05). There was no significant difference of OS and DFS between low miRNA expression and high miRNA expression of remaining miRNAs.

Table 6.

Log-rank test analysis of overall survival (OS) and disease-free survival (DFS) of candidate miRNA

miRNA Expression status Overall survival (OS) Disease-free survival (DFS)
Mean ±SD (months) P-value Mean ±SD (months) P-value
miR-99a-5p Low 48.8 ± 14.1 0.201 46.2 ± 17.9 0.47
High 51.5 ± 15.2 49.7 ± 17.8
miR-100-5p Low 50.3 ± 13.7 0.956 48.4 ± 16.6 0.602
High 49.9 ± 15.8 47.4 ± 19.3
miR-105-5p Low 50.3 ± 13.5 0.396 48.6 ± 16.0 0.287
High 50.3 ± 15.8 47.6 ± 19.4
miR-125b-5p Low 50.6 ± 12.7 0.71 48.7 ± 15.7 0.346
High 49.6 ± 16.7 47.1 ± 19.9
miR-133a-5p Low 48.9 ± 14.3 0.205 46.2 ± 18.3 0.457
High 51.3 ± 15.2 49.7 ± 17.4
miR-141-3p Low 47.7 ± 16.0 0.007 44.8 ± 19.8 0.036
High 52.8 ± 12.8 51.3 ± 15.0
miR-143-3p Low 50.1 ± 13.6 0.653 47.5 ± 17.8 0.953
High 50.1 ± 15.9 48.3 ± 18.3
miR-145-5p Low 50.1 ± 13.9 0.654 48.0 ± 17.1 0.896
High 50.1 ± 15.6 47.8 ± 18.7
miR-182-5p Low 50.5 ± 15.1 0.396 48.1 ± 18.7 0.903
High 49.3 ± 14.7 47.3 ± 17.4
miR-199a-5p Low 48.2 ± 15.3 0.083 45.7 ± 18.8 0.251
High 52.0 ± 13.9 50.2 ± 16.8
miR-200a-3p Low 48.9 ± 14.6 0.203 46.2 ± 18.4 0.457
High 51.4 ± 14.9 49.6 ± 17.3
miR-200b-3p Low 48.8 ± 14.6 0.577 46.4 ± 17.6 0.48
High 51.5 ± 14.9 49.4 ± 18.1
miR-200c-3p Low 51.7 ± 11.6 0.236 50.0 ± 14.9 0.086
High 48.5 ± 17.3 45.8 ± 20.4
miR-21-5p Low 52.1 ± 13.1 0.146 50.6 ± 15.7 0.089
High 48.1 ± 16.0 45.1 ± 19.6

P< 0.05, statistical significance.

The univariate analysis indicated that the prognostic value of GC patients was related to tumor size, tumor infiltrating depth, vascular nerve infiltrating, number of metastatic lymph nodes and metastatic lymph nodes ration, TNM stage, Lauren classification and miR-141-3p. Multivariate analysis of OS and DFS revealed that metastatic lymph nodes ration, Lauren classification and miR-141-3p were independent prognostic factors (Table 7).

Table 7.

The COX risk model analysis of overall survival (OS) and disease-free survival (DFS) of miR-141-3p

Variables Overall survival (OS) Disease free survival (DFS)
Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis
P value HR 95%CI P value P value HR 95%CI P value
Age 0.288 0.689
Gender 0.106 0.108
Tumor site 0.858 0.768
Tumor subtype 0.063 0.057
Pathological classifications 0.054 0.106
Tumor size 0.002 1.421 0.665–3.036 0.364 0.002 1.589 0.770–3.276 0.21
Histopathology classification 0.0503 0.062
Tumor infiltrating depth < 0.001 1.95 0.709–5.364 0.196 < 0.001 1.974 0.770–5.061 0.157
Number of metastatic lymph nodes < 0.001 1.488 0.867–2.555 0.149 < 0.001 1.508 0.877–2.592 0.138
Metastatic lymph nodes ration < 0.001 0.217 0.065–0.729 0.013 < 0.001 0.244 0.084–0.705 0.009
AJCC 8th TNM stage < 0.001 0.757 0.131–4.384 0.756 < 0.001 0.941 0.194–4.571 0.94
Vascular nerve infiltrating 0.007 0.971 0.448–2.106 0.942 0.009 0.899 0.430–1.878 0.776
adjuvant chemotherapy 0.346 0.196
Lauren classification 0.012 0.562 0.347–0.911 0.019 0.004 0.502 0.314–0.804 0.004
miR-141-3p 0.007 0.408 0.169–0.988 0.047 0.036 0.563 0.258–1.228 0.149

P< 0.05, statistical significance.

To explore the prognostic value of miR-141-3p in Lauren classification GC, we conducted univariate analysis of miR-141-3p among diffuse type, intestinal type and mixed type GC. As a consequence of univariate analysis, low miR-141-3p in diffuse type GC showed significant worse OS and DFS than high miR-141-3p (P< 0.05). There was no significant difference of miR-141-3p in intestinal type and mixed type GC (Fig. 3).

Figure 3.

Figure 3.

Overall survival (OS) and disease free survival (DFS) curves of low miR-141-3p and high miR-141-3p group plotted by the Kaplan-Meier method in (A–B) diffuse type, (C–D) intestinal type, (E–F) mixed type GC. Each P value was calculated by the log-rank test. P< 0.05 was defined statistically significant.

4. Discussion

Currently, there are several classifications of GC, including histologically and molecular [30]. It is hard to say which classification is the best one due to the morphological characteristics of GC. Choosing one classification system is insufficient to provide precise prognosis for individual treatment. Lauren classification is the most-used one, however, there is still controversial whether Lauren classification plays better roles on prognosis performance of GC. In this study, we performed a retrospective study of 1144 patients who received radical gastrectomy. The results indicated that intestinal type GC (38.1%) had higher incidence than diffuse type GC (26.4%) which was line with previous study [31]. The difference with the study was that mixed type GC had higher incidence due to regional diversity. In diffuse type, the incidence was higher in younger ones than elder ones and females were predominant which may be related with oestrogen receptor [32]. The signet ring carcinoma, mucinous carcinoma, poor differentiated, deeper infiltration and higher metastatic lymph nodes ration were found in diffuse type GC than intestinal type GC, resulting in poor prognosis in diffuse type GC. The OS, DFS and 5-year survival of intestinal type GC had obvious survival advantages than diffuse type GC. According to multivariate analysis, Lauren classification was an independent prognostic factor and diffuse type GC was an independent risk factor for poor prognosis. In addition, our study showed that diffuse type GC was predominant in younger population in our country, the late TNM stage, large tumor size, lymphatic metastasis. It may be strongly correlated with heredity and may help to further understand the tumorigenesis of diffuse type GC.

Previous researches have confirmed that miRNAs have clinical implications in pathogenesis, diagnosis and prognosis of human cancers [11, 12, 33]. To have better understanding on targeted therapies in GC, we analyzed the expression levels of miRNAs in Lauren classification GC to seek for a prognostic biomarker. In our study, the expression levels of miR-141-3p were significantly down-regulated in diffuse type compared to intestinal type GC tissues using qRT-PCR. Multivariate analysis of OS and DFS revealed that metastatic lymph nodes ration, Lauren classification and miR-141-3p were independent prognostic factors. The low expression of miR-141-3p lead to worse OS and DFS in contrast to high miR-141-3p in diffuse type GC. MiR-141 was demonstrated as tumor suppressor through regulating target gene TAZ in GC. Inhibition of miR-141 resulted in promoting GC cells proliferation, invasion and migration in vitro [34]. MiR-141-3p, a member of miR-200 family, and its target gene ZEB1 and ZEB2 (E-cadherin transcriptional repressors) were associated with epithelial to mesenchymal transition (EMT). Enhanced expression of miR-141-3p suppressed EMT, while inhibition of miR-141-3p induced EMT. Downregulation of miR-141-3p played important roles on tumor progression [35]. The results were consistent with the low expression of miR-141-3p lead to worse OS and DFS in diffuse type GC. Using DIANA-miRPath v3.0 online software to assess miR-141-3p regulatory roles and the identification of controlled pathways [36]. As shown in Table S1, KEGG molecular pathways showed that miR-141-3p was associated with P53 signaling pathway. It was confirmed that overexpression P53 indicated the poor prognosis in GC, especially in diffuse type [37]. GO pathway analysis showed that miR-141-3p was associated with epidermal growth factor receptor signaling pathway, which was confirmed to be an independent prognostic factor influenced prognosis of GC [38].

There were some limitations in our study, the number of candidate miRNAs in predicting prognosis of GC and subtype of GC were relatively small. Also, neoadjuvant chemotherapy, Helicobacter Pylori infection and HER-2 gene amplification were not included in the prognostic factors.

5. Conclusions

Taken together, the present study suggested that Lauren classification was an independent prognostic factor in GC and the diffuse type was an independent risk factors for poor prognosis of GC. Lauren classification may help clinical doctors provide a reasonable plan for individual treatment combining with other clinicopathological characteristic. MiR-141-3p was an independent prognostic factor and may become a promising prognostic biomarker in Lauren classification GC. However, the mechanism of miR-141-3p in prognosis of Lauren classification still need further investigation.

Ethics statement

The medical ethical committee of First Affiliated Hospital of Nanjing Medical University. Written informed consent was obtained from all GC patients included in the study.

Author contributions

Conception: WC, ZH, MZ and SQ.

Interpretation or analysis of data: WC, QG, ZH, and ZH. WC, QG, YD and ZH performed the experiments.

Preparation of the manuscript: WC, QG and ZH.

Revision for important intellectual content: YZ, MZ and SQ.

Supervision: MZ and SQ.

Acknowledgments

The staff authors are sincerely grateful to all volunteers who participated in this follow-up study. The work was supported by the Jiangsu Provincial Medical Key Discipline (Grant number: ZDXK202235).

Conflict of interest

The authors have declared that no potential conflict of interest exists.

References

  • [1]. Thrift A.P. and El-Serag H.B., Burden of gastric cancer, Clin Gastroenterol Hepatol 18 (2020), 534–542. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2]. Zubarayev M., Min E.K. and Son T., Clinical and molecular prognostic markers of survival after surgery for gastric cancer: tumor-node-metastasis staging system and beyond, Transl Gastroenterol Hepatol 4 (2019), 59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [3]. Machlowska J. et al., Gastric cancer: Epidemiology, risk factors, classification, genomic characteristics and treatment strategies, Int J Mol Sci 21 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [4]. Ning F.L. et al., Prognostic value of modified Lauren classification in gastric cancer, World J Gastrointest Oncol 13 (2021), 1184–1195. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5]. Lauren P., The two histological main types of gastric carcinoma: diffuse and So-called Intestinal-type carcinoma. An attempt at a Histo-clinical classification, Acta Pathol Microbiol Scand 64 (1965), 31–49. [DOI] [PubMed] [Google Scholar]
  • [6]. Quach D.T., Ha D.V. and Hiyama T., The endoscopic and clinicopathological characteristics of early-onset gastric cancer in Vietnamese patients, Asian Pac J Cancer Prev 19 (2018), 1883–1886. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7]. Tang C.T. et al., Analysis of the incidence and survival of gastric cancer based on the Lauren classification: A large population-based study using SEER, Front Oncol 10 (2020), 1212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8]. Zurlo I.V. et al., Treatment of Locally advanced gastric cancer (LAGC): Back to Lauren’s classification in pan-cancer analysis era? Cancers (Basel) 12 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9]. Oue N. et al., Molecular carcinogenesis of gastric cancer: Lauren classification, mucin phenotype expression, and cancer stem cells, Int J Clin Oncol 24 (2019), 771–778. [DOI] [PubMed] [Google Scholar]
  • [10]. Venizelos A. et al., The molecular characteristics of high-grade gastroenteropancreatic neuroendocrine neoplasms, Endocr Relat Cancer 29 (2021), 1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11]. Hill M. and Tran N., miRNA interplay: mechanisms and consequences in cancer, Dis Model Mech 14 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12]. Lee Y.S. and Dutta A., MicroRNAs in cancer, Annu Rev Pathol 4 (2009), 199–227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13]. Zhang X. et al., microRNA-205 and microRNA-338-3p reduces cell apoptosis in prostate carcinoma tissue and LNCaP prostate carcinoma cells by directly targeting the B-Cell lymphoma 2 (Bcl-2) Gene, Med Sci Monit 25 (2019), 1122–1132. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14]. He B. et al., miRNA-based biomarkers, therapies, and resistance in Cancer, Int J Biol Sci 16 (2020), 2628–2647. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15]. Huang Z. et al., Serum miR-16 as a potential biomarker for human cancer diagnosis: results from a large-scale population, J Cancer Res Clin Oncol 145 (2019), 787–796. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [16]. Chang R.M. et al., miRNA-487a promotes proliferation and metastasis in hepatocellular carcinoma, Clin Cancer Res 23 (2017), 2593–2604. [DOI] [PubMed] [Google Scholar]
  • [17]. Gillen S., Advancing early gastric cancer detection, FEBS Open Bio 11 (2021), 1812–1813. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18]. Lorenzon L. et al., Down-regulated miRs specifically correlate with non-cardial gastric cancers and Lauren’s classification system, Journal of surgical oncology 116 (2017), 184–194. [DOI] [PubMed] [Google Scholar]
  • [19]. Wang L. et al., Diagnostic and therapeutic potencies of miR-18a-5p in mixed-type gastric adenocarcinoma, J Cell Biochem 122 (2021), 1062–1071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20]. Fu Z. et al., Construction of miRNA-mRNA-TF regulatory network for diagnosis of gastric cancer, Biomed Res Int 2021 (2021), 9121478. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21]. Das M.K. et al., Identification of endogenous controls for use in mirna quantification in human cancer cell lines, Cancer Genomics Proteomics 13 (2016), 63–68. [PubMed] [Google Scholar]
  • [22]. Ahn D.H. et al., Association of the miR-146aC>G, miR-149T>C, miR-196a2T>C, and miR-499A>G polymorphisms with gastric cancer risk and survival in the Korean population, Mol Carcinog 52(Suppl 1) (2013), E39–51. [DOI] [PubMed] [Google Scholar]
  • [23]. Azarbarzin S. et al., The value of miR-299-5p in diagnosis and prognosis of intestinal-type gastric adenocarcinoma, Biochem Genet 54 (2016), 413–420. [DOI] [PubMed] [Google Scholar]
  • [24]. Cui L. et al., Gastric juice MicroRNAs as potential biomarkers for the screening of gastric cancer, Cancer 119 (2013), 1618–1626. [DOI] [PubMed] [Google Scholar]
  • [25]. Fassan M. et al., The HER2-miR125a5p/miR125b loop in gastric and esophageal carcinogenesis, Hum Pathol 44 (2013), 1804–1810. [DOI] [PubMed] [Google Scholar]
  • [26]. Li X. et al., Identification of new aberrantly expressed miRNAs in intestinal-type gastric cancer and its clinical significance, Oncol Rep 26 (2011), 1431–1439. [DOI] [PubMed] [Google Scholar]
  • [27]. Ueda T. et al., Relation between microRNA expression and progression and prognosis of gastric cancer: a microRNA expression analysis, Lancet Oncol 11 (2010), 136–146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28]. Wu Y.F. et al., Association of Polymorphisms in three pri-miRNAs that target pepsinogen C with the risk and prognosis of gastric cancer, Sci Rep 7 (2017), 39528. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29]. Yasui W. et al., Molecular pathology of gastric cancer: research and practice, Pathol Res Pract 207 (2011), 608–612. [DOI] [PubMed] [Google Scholar]
  • [30]. Chia N.Y. and Tan P., Molecular classification of gastric cancer, Ann Oncol 27 (2016), 763–769. [DOI] [PubMed] [Google Scholar]
  • [31]. Chen Y.C. et al., Clinicopathological variation of Lauren classification in gastric cancer, Pathol Oncol Res 22 (2016), 197–202. [DOI] [PubMed] [Google Scholar]
  • [32]. Shimada S. et al., Identification of selective inhibitors for diffuse-type gastric cancer cells by screening of annotated compounds in preclinical models, Br J Cancer 118 (2018), 972–984. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [33]. Ali Syeda Z. et al., Regulatory Mechanism of MicroRNA Expression in Cancer, Int J Mol Sci 21 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34]. Zuo Q.F. et al., MicroRNA-141 inhibits tumor growth and metastasis in gastric cancer by directly targeting transcriptional co-activator with PDZ-binding motif, TAZ, Cell Death Dis 6 (2015), e1623. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [35]. Gregory P.A. et al., The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1, Nat Cell Biol 10 (2008), 593–601. [DOI] [PubMed] [Google Scholar]
  • [36]. Vlachos I.S. et al., DIANA-miRPath v3.0: deciphering microRNA function with experimental support, Nucleic Acids Res 43 (2015), W460–466. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37]. Kim K.W. et al., Different effects of p53 protein overexpression on the survival of gastric cancer patients according to Lauren histologic classification: a retrospective study, Gastric Cancer 24 (2021), 844–857. [DOI] [PubMed] [Google Scholar]
  • [38]. Xu W. et al., Human epidermal growth factor receptor 2 expressions and Janus-activated kinase/signal transducer and activator of transcription 3-suppressor of cytokine signaling 3 pathway may be associated with clinicopathological features and prognosis of gastric cancer, J Cancer Res Ther 14 (2018), S311–S318. [DOI] [PubMed] [Google Scholar]

Articles from Cancer Biomarkers are provided here courtesy of IOS Press

RESOURCES