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Back to Journal »Cancer Management and Research» Volume 13

Targeting oncogenic miR-181a-2-3p inhibits the growth of gastric cancer and inhibits cisplatin resistance

Authors: Jin Li, Ma Xin, Zhang Nan, Zhang Q, Chen Xin, Zhang Zhong, Ding Geng, Yu Hong

Published on November 16, 2021, the 2021 volume: 13 pages 8599-8609

DOI https://doi.org/10.2147/CMAR.S332713

Single anonymous peer review

Editor who approved for publication: Professor Harikrishna Nakshatri

Jin Lei,1,* Ma Xuemei,2,* Zhang Nan,3 Zhang Qian,4 Chen Xueming,1 Zhang Zhongtao,2 Ding Guoqian,2 Yu Hongzhi1 1Department of Vascular Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, People's Republic of China; 2Capital Department of General Surgery, Beijing Friendship Hospital Affiliated to Medical University, Beijing, People’s Republic of China; 3 Department of Radiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 4 Clinical Epidemiology and EBM Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China People’s Republic of China* These authors have contributed equally to this work Ding Guoqian Email [email protected]; [email protected] Purpose: This study aims to explore the value of miR-181a-2-3p in predicting the effect of cisplatin (DDP) treatment and reveal gastric cancer (GC) The potential role of patients in reversing DDP resistance. Methods: The miRNA expression datasets of three DDP-resistant GC cell lines and their DDP-sensitive parent cell lines were obtained from GEO DataSets and GenBank, and functional miRNAs were annotated by bioinformatics analysis. Serum samples and tumor samples were collected from 91 GC patients to understand the relationship between chemotherapy response and miRNA expression. RT-qPCR verified these miRNAs on the transcription level of gastric cancer cells and 91 gastric cancer patients. Analyze the correlation between miRNAs expression and patient clinical parameters. Receiver operating characteristic (ROC) analysis has been used to evaluate diagnostic performance. MTT and colony formation assays were performed to assess cell proliferation. Flow cytometry was used to detect cell apoptosis. Transfect DDP-resistant GC cells and their DDP-sensitive parent cells with miRNA mimics or inhibitor vectors to over-express or down-regulate miRNA expression. Result: miR-181a-2-3p is a unique miRNA, after screening and verification of miRNAs from three DDP-resistant and DDP-sensitive gastric cancer cell lines, among the common differentially expressed miRNAs (DE-miRNA) be found. Analysis of clinical data showed that the expression of miR-181a-2-3p increased significantly in larger tumors (≥ 5 cm), higher T stage (T4), and chemotherapy resistance. miR-181a-2-3p (AUC=0.926, SE=0.028, 95% CI: 0.872–0.980, p<0.0001) distinguishes chemotherapy-sensitive GC patients from chemotherapy-resistant GC patients. miR-181a-2-3p presents a high level in gastric cancer and can be used as an effective biomarker for predicting the overall survival of GC patients. Up-regulation of miR-181a-2-3p presents the apoptosis-inducing and anti-proliferative effects of DDP, while down-regulation will reduce these effects. Conclusion: miR-181a-2-3p can be used as a therapeutic target and tumor biomarker. Targeting oncogenic miR-181a-2-3p inhibits the growth of gastric cancer and inhibits cisplatin resistance. Key words: biomarker, miR-181a-2-3p, cisplatin resistance, gastric cancer, bioinformatics analysis

Gastric cancer is a malignant tumor that cannot be ignored. It is prevalent worldwide, making it the fourth most common cancer and the second leading cause of death from cancer. 1 In 2012, there were approximately 691,000 cases of gastric adenocarcinoma worldwide. 2 An estimated 720,000 patients died of gastric cancer. 3 Due to the high rates of metastasis, drug resistance, and recurrence, the current long-term survival rate of GC patients is poor. 4 Cisplatin (DDP) is considered the first-line drug patience for advanced GC. DDP exerts anti-tumor effects by activating a variety of apoptosis pathways. 5 In most GC patients, resistance to DDP is inevitable, leading to treatment failure. Therefore, there is an urgent need to find new targets and biomarkers and elucidate the underlying molecular mechanisms to improve the results.

miRNA is a class of existing non-coding small RNAs. 6 In many tumors, their dysregulation may cause DDP resistance, which is not fully understood. 7,8 In human serum specimens of a variety of tumors, miRNA may be used as a therapeutic biomarker 9-11 The underlying mechanism of anti-tumor drug resistance may be related to miRNA-mediated proliferation and apoptosis. 12 Some reports on the relationship between miRNA utilization and initiation, progression, diagnosis, appropriate treatment, and prognosis have been published. GC.13-15 Nevertheless, specific miRNAs as prognostic biomarkers of GC chemotherapy are still to be discovered.

In the current work, microRNA profiles are analyzed in GC cells to discover unique miRNAs. Clinical specimens from GC patients after DDP treatment were used to assess the correlation between miRNA expression and clinical prognosis. We are trying to reveal unique biomarkers of chemotherapy response and their potential role in reversing DDP resistance in GC patients.

Human gastric cancer cell lines (AGS, NCI-N87, MGC-803, SGC-7901, BGC-823 and MKN-45) and human gastric epithelial cell line (GES-1) were purchased from Chinese Academy of Medical Sciences (Beijing), China).

DDP-resistant GC cell lines (SGC-7901/DDP, MGC-803/DDP and BGC-823/DDP) were produced and established by parental cell lines (SGC-7901, MGC-803 and BGC-823). The specific culture conditions and reagents for the experiment are as described above. 15-17

The expression plasmids of miR-181a-2-3p mimic control, miR-181a-2-3p mimic, miR-181a-2-3p inhibitor, and miR-181a-2-3p inhibitor control were obtained from Fulengene. Except for the concentration of RT-qPCR (2x105/well), MTT detection (3x103/well) and colony formation detection (2x102/well), the specific transfection procedures and reagents of the experiment are almost the same as previously described. 14

Serum and tumor samples of 91 GC patients were collected. The inclusion and exclusion criteria of the enrolled patients and the evaluation criteria of chemotherapy response effects are as described above. 14,16,18 Informed consent of all patients was obtained. This study was approved by the Ethics Committee of Beijing Friendship Hospital of Capital Medical University (approval number: 2018-P2-045-01). The study was conducted in accordance with the Declaration of Helsinki.

The GSE86195 data set derived from the GEO data set (http://www.ncbi.nlm.nih.gov/gds) contains four GC cell lines SGC-7901/DDP, SGC-7901, BGC-823/DDP and BGC- The miRNA expression profile of 823.19 PRJNA615333 and SRR11427197 obtained from GenBank (https://www.ncbi.nlm.nih.gov/genbank) contains the miRNA expression profile of MGC-803/DDP and MGC-803.15

|log2 (fold change)| ˃ 1 and a P value <0.05 is considered statistically significant to calculate the differentially expressed miRNA (DE-miRNA) between the cisplatin-resistant GC cell line and its sensitive parent cell line through the edgeR algorithm .

The common DE-miRNAs were selected by taking the intersection. The Venn diagrams of common DE-miRNAs are calculated and drawn using bioinformatics and evolutionary genomics network tools (http://bioinformatics.psb.ugent.be/webtools/Venn). Use Starbase database (http://starbase.sysu.edu.cn/index.php) to verify the expression level of DE-miRNAs in gastric cancer and normal tissues, and verify the correlation between DE-miRNAs and survival time in gastric cancer. Use OncomiR database (http://www.oncomir.org/), OncoLnc database (http://www.oncolnc.org/) and Kaplan-Meier Plotter database (http://kmplot.com) to verify DE-miRNA The association with overall survival of gastric cancer. 20-23

Caenorhabditis elegans cel-39-3p miRNA was selected as the external calibration of serum sample RNA extraction and RT-qPCR. The primer sequences for miRNA detection are shown in Table 1. The specific procedures for RNA extraction and RT-qPCR are the same as those described above. 14, 15 Table 1 RT-qPCR primers

Prior to this assay, cells were cultured under normal conditions or as indicated by DDP treatment conditions. The cells were counted into a 96-well plate at a concentration of 3×103/well. After adhesion, the cells were treated with the specified concentration of DDP (200 μL/well) for 48 hours. The specific MTT procedures and reagents used in the experiment are the same as previously described. 14

Except for the concentration for colony formation detection (2x102/well), the specific colony formation procedures and reagents used in the experiment are almost the same as previously described. 14

The specific flow cytometry procedures and experimental reagents are the same as previously described. 14

The specific statistical analysis is almost the same as previously described. 14,15 For in vitro experiments, use unpaired Student's t-test and one-way analysis of variance, followed by Tukey's multiple comparison test to analyze statistical differences. The Mann-Whitney test was used to analyze the correlation between patients' clinical parameters and their miRNA expression. The expression level distribution of miR-181a-2-3p in different groups is expressed in median and interquartile range [median (Q1 and Q3)]. All data are expressed as mean ± SD. Each experiment is repeated at least 3 times independently. Use SPSS 26.0, MedCalc and GraphPad Prism 8 to analyze and graph quantitative data. ****P<0.0001, ***P<0.001, **P<0.01 and *P<0.05.

MiRNA microarray analysis was used to determine the differentially expressed miRNA (DE-miRNA) in DDP-resistant GC cells and their parental DDP-sensitive cells. Scan and count DE-miRNAs, there are 68 miRNAs and 94 miRNAs between SGC-7901 and SGC-7901/DDP

35 miRNAs between BGC-823 and BGC-823/DDP and between MGC-803 and MGC-803/DDP (Supplementary Table 1). The common DE-miRNAs were selected by taking the intersection of these three paired cell lines and displayed using Venn diagrams (Figure 1A). miR-181a-2-3p was found in the intersection as a unique miRNA and was selected for further research. Figure 1 Screening and verification of miRNAs from DDP-resistant and DDP-sensitive gastric cancer cell lines. (A) Venn diagram of the total number of differentially expressed miRNAs (in parentheses) and the number of overlaps calculated in the cell line pair. These cell lines are composed of cisplatin-resistant (/DDP added to the name of the parent cell line), relative to Cisplatin-sensitive paternal cell line. (B) DDP resistance detected by RT-qPCR and the relative expression level of miR-181a-2-3p in DDP-sensitive cells.

Figure 1 Screening and verification of miRNAs from DDP-resistant and DDP-sensitive gastric cancer cell lines. (A) Venn diagram of the total number of differentially expressed miRNAs (in parentheses) and the number of overlaps calculated in the cell line pair. These cell lines are composed of cisplatin-resistant (/DDP added to the name of the parent cell line), relative to Cisplatin-sensitive paternal cell line. (B) DDP resistance detected by RT-qPCR and the relative expression level of miR-181a-2-3p in DDP-sensitive cells.

In addition, RT-qPCR analysis was performed to verify the expression level of miR-181a-2-3p. The results showed that miR-181a-2-3p expression was significantly up-regulated in SGC-7901/DDP cells by ~22.2 times (compared to SGC-7901 cells) and ~4.9 times in BGC-823/DDP cells (compared to BGC) -823 cells), approximately 17.1 times in MGC-803/DDP cells (compared to MGC-803 cells), which demonstrates the correlation between DDP resistance and miR-181a-2-3p expression levels (Figure 1B ). The above results indicate that miR-181a-2-3p may affect the DDP resistance of GC cells.

Table 2 summarizes the clinicopathological characteristics of 91 GC patients who received palliative care or neoadjuvant chemotherapy. RT-qPCR analysis is used to test miR-181a-2-3p levels in GC serum samples and tumor samples under different clinical parameters. Using the median ratio as the cutoff value of miR-181a-2-3p expression in GC serum specimens and tumor samples (fold change = 0), patients were divided into two groups: miR-181a-2-3plow and miR-181a-2 -3phigh. Table 2 Correlation between miR-181a-2-3p expression and clinical parameters in GC patients (n=91)

Table 2 Correlation between miR-181a-2-3p expression and clinical parameters in GC patients (n=91)

The results showed that miR-181a-2-3p was expressed in larger tumors (≥ 5 cm; Pserum = 0.0010, Figure 2A; Ptumor = 0.0002, Figure 2D), higher T stage (T4; Pserum = 0.0006, Figure 2B; Ptumor = 0.0016, Figure 2E) and chemotherapy resistance (SD PD; Pserum<0.0001, Figure 2C; Ptumor<0.0001, Figure 2F) in GC serum samples and tumor samples. Figure 2 The expression level and function of miR-181a-2-3p in clinical specimens of human gastric cancer. (AC) miR-181a-2-3p is expressed in larger tumor size (≥5 cm; P = 0.0010) (A), higher T stage (T4; P = 0.0006) (B) and chemotherapy resistance Significant increase (SD PD; P<0.0001) (C) in serum samples of gastric cancer. (DF) miR-181a-2-3p is expressed in larger tumor sizes (≥ 5 cm; P = 0.0002) (D), higher T stage (T4; P = 0.0016) (E) and chemotherapy resistance Significant increase (SD PD; P<0.0001) (F) in gastric cancer tumor samples. (G) Comparison of serum specimen group (miR-181a-2-3pserum) and tumor specimen group (miR-181a-2-3ptumor) showed that MedCalc showed no significant difference between the two comparison areas (P = 0.708) software. (H) The comparative area of ​​the two sample types group (miR-181a-2-3pserum tumor) and the serum specimen group (miR-181a-2-3pserum) compared by MedCalc software is significantly different (P=0.011). (I) MedCalc software compares the area of ​​the two sample type combination group (miR-181a-2-3pserum tumor) and the tumor sample group (miR-181a-2-3ptumor) with significant difference (P=0.006).

Figure 2 The expression level and function of miR-181a-2-3p in clinical specimens of human gastric cancer. (AC) miR-181a-2-3p is expressed in larger tumor size (≥5 cm; P = 0.0010) (A), higher T stage (T4; P = 0.0006) (B) and chemotherapy resistance Significant increase (SD PD; P<0.0001) (C) in serum samples of gastric cancer. (DF) miR-181a-2-3p is expressed in larger tumor sizes (≥ 5 cm; P = 0.0002) (D), higher T stage (T4; P = 0.0016) (E) and chemotherapy resistance Significant increase (SD PD; P<0.0001) (F) in gastric cancer tumor samples. (G) Comparison of serum specimen group (miR-181a-2-3pserum) and tumor specimen group (miR-181a-2-3ptumor) showed that MedCalc showed no significant difference between the two comparison areas (P = 0.708) software. (H) The comparative area of ​​the two sample types group (miR-181a-2-3pserum tumor) and the serum specimen group (miR-181a-2-3pserum) compared by MedCalc software is significantly different (P=0.011). (I) MedCalc software compares the area of ​​the two sample type combination group (miR-181a-2-3pserum tumor) and the tumor sample group (miR-181a-2-3ptumor) with significant difference (P=0.006).

In addition, in GC serum samples, the expression of miR-181a-2-3p at abnormal CEA levels (P=0.0200, Supplementary Figure 1A) and abnormal CA19-9 levels (P=0.0015, Supplementary Figure 1B) was significantly increased. In addition, miR-181a-2-3p was expressed in worse grade staging (G3 G4, P=0.0184, Supplementary Figure 1C), current lymph node metastasis (P=0.0280, Supplementary Figure 1D) and higher TNM staging (IV, P <0.0001, Supplementary Figure 1E) in GC tumor samples. These results indicate that in GC patients, miR-181a-2-3p may be used as a biomarker of DDP response and is related to tumor growth. However, in GC serum samples and tumor samples, the expression of miR-181a-2-3p has nothing to do with gender, age, CA724 level, CA125 level or M stage (Table 2).

miR-181a-2-3p can distinguish GC chemotherapy response sensitive group (CR PR) and GC chemotherapy response resistant group (SD PD). The receiver operating characteristic (ROC) curve is used to predict the diagnostic efficacy of miR-181a-2-3p. The area under the curve (AUC), standard error (SE), 95% confidence interval (CI) and P value of miR-181a-2-3p in GC serum samples and tumor samples are as follows: -181a-2-3pserum(AUC : 0.821, SE: 0.045, 95% CI: 0.733–0.909, p<0.0001, Figure 2G) and miR-181a-2-3ptumor (AUC: 0.843, SE: 0.909, P<0.0001, Figure 2G): 0.762, respectively –0.924, p<0.0001, Figure 2G).

The miR-181a-2-3p in GC serum samples and tumor samples provides potential AUC values ​​to distinguish between CR PR group and SD PD group.

Compared with a single sample type (serum sample or tumor sample), the combined sample type achieved significantly improved performance, determined by the following factors: miR-181a-2-3pserum tumor (AUC: 0.926, SE: 0.028, 95% CI : 0.872 -0.980, p<0.0001, Figure 2H). The risk scoring factor (RSF) of the Logistic model is calculated as 0.591 × miR-181a-2-3pserum 0.729 × miR-181a-2-3ptumor 0.231.

There was no significant difference between miR-181a-2-3pserum and miR-181a-2-3ptumor (P = 0.708, Figure 2G). The comparison area between miR-181a-2-3pserum tumor and miR-181a-2-3pserum was significantly different (P = 0.011, Figure 2H). The comparison area between miR-181a-2-3pserum tumor and miR-181a-2-3ptumor is significantly different (P = 0.006, Figure 2I).

The results indicate that higher levels of miR-181a-2-3pserum tumors are better biomarkers of chemoresistance in GC patients.

To determine the expression of miR-181a-2-3p in gastric cancer, the Starbase database and RT-qPCR were used for analysis and verification. The Starbase database showed that the expression of miR-181a-2-3p in 372 gastric cancer samples was higher than that of 32 gastric normal samples (Figure 3A). RT-qPCR confirmed that compared with GES-1, miR-181a-2-3p is at a relatively high level in most human GC cell lines (AGS, MGC-803, BGC-823 and SGC-7901) (Figure 3B). In addition, compared with adjacent non-tumor tissues, miR-181a-2-3p has higher levels in gastric cancer tissues (Figure 3C and D). Figure 3 Bioinformatics analysis and verification of miR-181a-2-3p in gastric cancer. (A) The Starbase database shows that the expression of miR-181a-2-3p in 372 gastric cancer samples is higher than that of 32 gastric normal samples. (B) RT-qPCR results proved that compared with human gastric epithelial cells, most human gastric cancer cell lines (AGS, SGC-7901, BGC-823, and MGC-803) have higher levels of miR-181a-2-3p Department of GES-1. (C and D) Compared with adjacent non-tumor tissues, miR-181a-2-3p showed higher levels in gastric cancer tissues. (EH) In the Kaplan-Meier Plotter database, the 10-year overall survival (OS) time of GC patients with higher miR-181a-2-3p levels was significantly shorter than that of patients with lower miR-181a-2-3p levels (P = 0.053) (E), OncoLnc database (P= 0.00506) (F), OncomiR database (P= 0.003906) (G) and Starbase database (P= 0.0045) (H).

Figure 3 Bioinformatics analysis and verification of miR-181a-2-3p in gastric cancer. (A) The Starbase database shows that the expression of miR-181a-2-3p in 372 gastric cancer samples is higher than that of 32 gastric normal samples. (B) RT-qPCR results proved that compared with human gastric epithelial cells, most human gastric cancer cell lines (AGS, SGC-7901, BGC-823, and MGC-803) have higher levels of miR-181a-2-3p Department of GES-1. (C and D) Compared with adjacent non-tumor tissues, miR-181a-2-3p showed higher levels in gastric cancer tissues. (EH) In the Kaplan-Meier Plotter database, the 10-year overall survival (OS) time of GC patients with higher miR-181a-2-3p levels was significantly shorter than that of patients with lower miR-181a-2-3p levels (P = 0.053) (E), OncoLnc database (P= 0.00506) (F), OncomiR database (P= 0.003906) (G) and Starbase database (P= 0.0045) (H).

Large-scale cohort analysis was performed on Kaplan-Meier survival data based on OncoLnc database, Kaplan-Meier Plotter database, OncomiR database and Starbase database to find out the function of miR-181a-2-3p as a potential prognostic factor. The results showed that in the Kaplan–Meier Plotter database (P=0.053, Figure 3E) and the OncoLnc database, the 10-year overall survival (OS) time of GC patients with higher miR-181a-2-3p levels was significantly shorter than those with higher levels. Low patients (P = 0.00506, Figure 3F), OncomiR database (P = 0.003906, Figure 3G) and Starbase database (P = 0.0045, Figure 3H), which indicates that miR-181a-2-3p can be used as a promising overall organism Survival rate of patients with GC marker.

The above results indicate that miR-181a-2-3p expression is significantly up-regulated in SGC-7901/DDP cells ~22.2 times (compared to SGC-7901 cells) and ~17.1 times in MGC-803/DDP cells (compared to MGC- 803 cells), higher than BGC-823/DDP cells (~4.9 times, compared with BGC-823 cells) (Figure 1B). Therefore, we selected these two pairs of cell lines (MGC-803 and MGC-803/DDP, and SGC-7901 and SGC-7901/DDP) for further study. In order to explore the function of miR-181a-2-3p in DDP resistance, miR-181a-2-3p was subsequently overexpressed in MGC-803 and SGC-7901 cells, and in MGC-803/DDP and SGC-7901/ DDP is down-regulated by transiently transfecting cells.

RT-qPCR proved that the miR-181a-2-3p levels in MGC-803 and SGC-7901 cells transfected with miR-181a-2-3p mimics were significantly increased compared with mock control cells (Figure 4A). To verify the correlation between miR-181a-2-3p overexpression and DDP resistance, MGC-803 and SGC-7901 cells were transfected with miR-181a-2-3p mimic or mimic control. Cell viability was tested after 48 hours (Figure 4B). Compared with the mimic control, MGC-803 and SGC-7901 cells transfected with miR-181a-2-3p mimic showed a significantly increased survival rate and higher DDP IC50 value (Figure 4C). In addition, higher levels of miR-181a-2-3p were associated with increased cell proliferation after 0.2 μg/mL DDP in SGC-7901 cells or 0.8 μg/mL DDP in MGC-803 cells (Figure 4D). Compared with mock control cells, the relative colony formation efficiency of MGC-803 and SGC-7901 cells mock-transfected with miR-181a-2-3p was significantly increased (Figure 4E). In addition, compared with mock control cells, MGC-803 and SGC-7901 cells transfected with miR-181a-2-3p mimics showed reduced apoptosis after cultured with 0.2 μg/mL DDP and 0.8 μg/mL DDP, respectively. Death rate (Figure 4F and G). Therefore, overexpression of miR-181a-2-3p increases DDP resistance, which is caused by apoptosis and decreased cytotoxicity. The above results confirm that the overexpression of miR-181a-2-3p leads to resistance of gastric cancer cells to DDP. Figure 4 Overexpression of miR-181a-2-3p makes gastric cancer cells resistant to DDP. (A) RT-qPCR results confirmed that compared with mock control cells, miR-181a-2-3p levels in SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimics were significant Increase. (B) After 48 hours of treatment with different concentrations of DDP, compared with mock control cells, cells were detected in SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimic active. (C) Compared with mock control cells, SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimic showed a significant increase in survival rate and higher DDP IC50 value. (D) After adding 0.2 μg/mL DDP to SGC-7901 cells or adding 0.8 μg/mL DDP to MGC-803 cells to culture for 2 weeks, higher levels of miR-181a-2-3p are associated with increased cell proliferation. (E) Compared with the mock control cells, the relative colony formation efficiency of SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimics were significantly improved. (F and G) Compared with mock control cells, SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimic were cultured with 0.2 μg/mL DDP and 0.8 μg/mL DDP The apoptotic rate decreased for 48 hours.

Figure 4 Overexpression of miR-181a-2-3p makes gastric cancer cells resistant to DDP. (A) RT-qPCR results confirmed that compared with mock control cells, miR-181a-2-3p levels in SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimics were significant Increase. (B) After 48 hours of treatment with different concentrations of DDP, compared with mock control cells, cells were detected in SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimic active. (C) Compared with mock control cells, SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimic showed a significant increase in survival rate and higher DDP IC50 value. (D) After adding 0.2 μg/mL DDP to SGC-7901 cells or adding 0.8 μg/mL DDP to MGC-803 cells to culture for 2 weeks, higher levels of miR-181a-2-3p are associated with increased cell proliferation. (E) Compared with the mock control cells, the relative colony formation efficiency of SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimics were significantly improved. (F and G) Compared with mock control cells, SGC-7901 cells and MGC-803 cells transfected with miR-181a-2-3p mimic were cultured with 0.2 μg/mL DDP and 0.8 μg/mL DDP The apoptotic rate decreased for 48 hours.

RT-qPCR proved that compared with inhibitor control cells, miR-181a-2-3p levels in MGC-803/DDP and SGC-7901/DDP cells transfected with miR-181a-2-3p inhibitor were significantly reduced ( Figure 5A). To demonstrate the association between DDP resistance and miR-181a-2-3p down-regulation, MGC-803/DDP and SGC-7901/DDP cells were transfected with miR-181a-2-3p inhibitor or inhibitor control dye. Then, MGC-803/DDP and SGC-7901/DDP cells were cultured with different DDP concentrations, and then viability was evaluated (Figure 5B). Compared with inhibitor control cells, miR-181a-2-3p knockdown in MGC-803/DDP and SGC-7901/DDP cells resulted in higher DDP IC50 values ​​and increased survival (Figure 5C). After cultured with 0.5 μg/mL DDP in SGC-7901/DDP cells and 3 μg/mL DDP in MGC-803/DDP cells, the decrease in miR-181a-2-3p levels was also associated with less proliferation and colony formation ( Figure 5D and E). In addition, flow cytometry showed that after adding 0.1 μg/mL DDP to SGC-7901/DDP cells and 0.5 μg/mL DDP to MGC-803/DDP cells, the miR-transfected MGC-803/DDP and SGC- Compared with the inhibitor control cells, the -181a-2-3p inhibitor showed an increased apoptosis rate in 7901/DDP cells (Figure 5F and G). Therefore, due to increased apoptosis and cytotoxicity, miR-181a-2-3p knockdown in MGC-803/DDP and SGC-7901/DDP cells showed weak DDP resistance. The above results confirm that the down-regulation of miR-181a-2-3p makes gastric cancer cells sensitive to DDP. Figure 5 Down-regulation of miR-181a-2-3p makes gastric cancer cells sensitive to DDP. (A) RT-qPCR results confirmed that the miR-181a-2-3p levels of SGC-7901/DDP cells and MGC-803/DDP cells transfected with miR-181a-2-3p inhibitors were significantly lower than those of the inhibitors Control cells. (B) SGC-7901/DDP cells and MGC-803/DDP cells transfected with miR-181a-2-3p inhibitor or inhibitor control were treated with a series of DDP concentrations for 48 hours, and then the viability was assessed. (C) Compared with inhibitor control cells, miR-181a-2-3p knockdown in SGC-7901/DDP cells and MGC-803/DDP cells resulted in increased survival rates and increased DDP IC50 values. (D and E) After treatment with 0.5 μg/mL DDP in SGC-7901/DDP cells and 3 μg/mL DDP in MGC-803/DDP cells for 2 weeks, the reduction in miR-181a-2-3p levels was also consistent with the With the reduction of proliferation and colony formation. (F and G) Flow cytometry analysis showed that after treatment with 0.1 μg/mL DDP in SGC-7901/DDP cells and 0.5 μg/mL DDP in MGC-803/DDP cells for 48 hours, SGC-7901/DDP Compared with inhibitor control cells, cells and MGC -803/DDP cells transfected with miR-181a-2-3p inhibitor showed a higher rate of apoptosis.

Figure 5 Down-regulation of miR-181a-2-3p makes gastric cancer cells sensitive to DDP. (A) RT-qPCR results confirmed that the miR-181a-2-3p levels of SGC-7901/DDP cells and MGC-803/DDP cells transfected with miR-181a-2-3p inhibitors were significantly lower than those of the inhibitors Control cells. (B) SGC-7901/DDP cells and MGC-803/DDP cells transfected with miR-181a-2-3p inhibitor or inhibitor control were treated with a series of DDP concentrations for 48 hours, and then the viability was assessed. (C) Compared with inhibitor control cells, miR-181a-2-3p knockdown in SGC-7901/DDP cells and MGC-803/DDP cells resulted in increased survival and increased DDP IC50 values. (D and E) After treatment with 0.5 μg/mL DDP in SGC-7901/DDP cells and 3 μg/mL DDP in MGC-803/DDP cells for 2 weeks, the reduction in miR-181a-2-3p levels was also consistent with the With the reduction of proliferation and colony formation. (F and G) Flow cytometry analysis showed that after treatment with 0.1 μg/mL DDP in SGC-7901/DDP cells and 0.5 μg/mL DDP in MGC-803/DDP cells for 48 hours, SGC-7901/DDP Compared with inhibitor control cells, cells and MGC -803/DDP cells transfected with miR-181a-2-3p inhibitor showed a higher rate of apoptosis.

DDP resistance is a barrier to effective treatment of GC. The identification of specific biomarkers for DDP resistance will greatly promote the accurate diagnosis and effective treatment of gastric cancer. The role of miRNA in DDP treatment remains unclear. miRNA plays a vital role in the occurrence and development of tumors, which may be related to drug resistance. 24-26 For example, it has been reported that down-regulation of miR-21 in GC cells alters survival rates by increasing DDP sensitivity. 27

Several reports have been published on the relationship between the use of miRNA and the occurrence, progression, diagnosis, appropriate treatment, and prognosis of GC. Fang et al. reported that some cancer-related miRNAs (miR-338, miR-223, miR-21 and miR-10b) and tumor suppressor miRNAs (let-7a, miR-126 and miR-30a-5p) can be used as prognostic factors for gastric cancer patients. Biomarkers. 13 A large number of studies have reported the combined use of circulating miRNAs to improve diagnostic accuracy, with AUC greater than 0.8.28. 29 There are few reports on the application of miRNAs in the screening and diagnosis of DDP reactions in gastric cancer. This study used sRNA-seq technology to establish the differences in the expression profiles of miRNAs in chemotherapy-resistant and chemotherapy-sensitive GC cells, and screened out potential miRNAs through bioinformatics analysis. Our results show that miR-181a-2-3p is significantly upregulated in GC cells and patients who are resistant to chemotherapy. Although some miRNAs are considered to be prognostic or diagnostic biomarkers for gastric cancer, our study is the first to explore their promising use in DDP response. In addition, our observations indicate that for the chemoresistance of GC patients, higher levels of miR-181a-2-3pserum tumors are better biomarkers than miR-181a-2-3pserum or miR-181a-2-3ptumor . The miR-181a-2-3pserum tumor can obtain an AUC of 0.926. The equation is 0.591 × miR-181a-2-3pserum 0.729 × miR-181a-2-3ptumor 0.231. Large-scale cohort analysis was performed on Kaplan-Meier survival data based on OncoLnc database, Kaplan-Meier Plotter database, OncomiR database and Starbase database to find out the function of miR-181a-2-3p as a potential prognostic factor. The results indicate that miR-181a-2-3p overexpression can be used as an effective biomarker for poor overall survival and chemical resistance.

Previous studies have shown that in cervical cancer, miR-181a-2-3p is essential for maintaining cancer stem cells. 30 In pancreatic ductal adenocarcinoma, miR-181a-2-3p can be used as a biomarker for early detection. 31 In this study, an increase in miR-181a-2-3p was found in DDP-resistant GC cell lines and DDP-resistant GC patients, and an elevated level of miR-181a-2-3p was associated with a poor prognosis and a poorer prognosis Related to the clinical parameters. In addition, the correlation between miR-181a-2-3p level and tumor size in this study indicates that miR-181a-2-3p may play an important role in tumor cell proliferation. The study showed that up-regulation of miR-181a-2-3p increased cell proliferation and inhibited cell apoptosis. Therefore, the validated selective miR-181a-2-3p response modifier may be a viable and attractive treatment option. Some experiments should be conducted to clarify the function and clinical therapeutic potential of miR-181a-2-3p as a therapeutic target.

Summarizing the shortcomings of the study, the sample size of bioinformatics analysis needs to be further expanded, and more animal studies or human trials should be conducted in the future.

This study reports the potential of miR-181a-2-3p to predict the benefit of DDP treatment in patients with gastric cancer. Targeting oncogenic miR-181a-2-3p can inhibit the growth of gastric cancer and inhibit cisplatin-mediated drug resistance. In addition, the down-regulation of DDP combined with miR-181a-2-3p may be a promising treatment option for DDP-resistant GC patients in the future.

Thank you for funding from the Beijing Friendship Hospital Affiliated to Capital Medical University Scientific Research Fund (yyqdkt2020-9 and yyqdkt2020-13).

All authors who have contributed to data analysis, drafting or revising the article agree to the journal to which the article will be submitted, finally approve the version to be published, and agree to be responsible for all aspects of the work.

The authors report no conflicts of interest.

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