Research ArticleExperimental Studies
Open Access

Candidate Oncogenes, ARHGAP4, NOS3, and OR51B5, for the Development of Scirrhous-type Gastric Cancer

TOMOHIRO SERA, TAKASHI SAKUMA, KOJI MARUO, GEN TSUJIO, YURIE YAMAMOTO, ATSUSHI SUGIMOTO, SYUHEI KUSHIYAMA, SHINGO TOGANO, KENJI KURODA, HIROAKI KASASHIMA, MASAICHI OHIRA and KIYOSHI MAEDA
Anticancer Research November 2022, 42 (11) 5195-5203; DOI: https://doi.org/10.21873/anticanres.16026

Abstract

Background/Aim: Scirrhous-type gastric cancer (SGC), one of the most intractable cancer subtypes, is characterized by rapid cancer cell proliferation and infiltration accompanied by extensive stromal fibrosis. One of the reasons for its poor prognosis may be the lack of molecular target drugs for SGC, because of the unknown driver genes. Exploration of somatic mutations in the human samples of SGC using next-generation sequencing (NGS) has been hampered by abundant fibrous tissues in these samples. Therefore, this study aimed to determine a novel oncogene by RNA-sequencing using SGC cell lines, avoiding contamination with fibrosis. Materials and Methods: In silico analysis of RNA-sequencing public data of the gastric cancer cell line, and RNA- sequencing using five of our unique SGC cell lines, OCUM1, OCUM2MLN, OCUM8, OCUM12, and OCUM14 were performed. Results: We found three differentially expressed genes, ARHGAP4, NOS3, and OR51B5 that are significantly over-expressed in SGC cells. Immunohistochemical analysis indicated that the protein expression levels of these three genes were significantly higher in SGC than in other types of gastric cancer. The prognosis of patients with positive expression of these three genes was significantly poorer than those with negative expression. In particular, ARHGAP4 expression was an independent predictor of poor prognosis and recurrence. Conclusion: ARHGAP4, NOS3, and OR51B5 may be candidate driver genes for SGC. ARHGAP4 may be a promising molecular target for SGC.

Key Words:

Gastric cancer remains the third leading cause of cancer-related deaths, and annually, almost 1 million people are diagnosed with gastric cancer worldwide (1, 2). Scirrhous-type gastric cancer (SGC), diffusely infiltrating carcinoma, or Borrman type-4, also known as linitis plastica-type carcinoma, is an intractable cancer subtype with a 5-year survival rate of only 11%-16% (3, 4). One of the reasons for its poor prognosis is the lack of the identification of the driver genes for SGC. Fibroblast growth factor receptor 2 (FGFR2) (5-7), E-cadherin (8, 9), transforming growth factor β receptor (TGFβR) (10, 11), and CD44/insulin-like growth factor I receptor (IGFIR) (12), have been reported as candidate driver molecules for SGC. However, no useful molecularly targeted therapies for these driver molecules have been clinically approved to date. SGC is characterized by rapid cancer cell proliferation and infiltration, accompanied by extensive stromal fibrosis. Exploration of somatic mutations in human samples of SGC using next-generation sequencing (NGS) has been hampered by abundant fibrous tissues in these samples. Therefore, this study aimed to determine a novel oncogene by RNA-sequencing using SGC cell lines, avoiding contamination by fibrosis. The number of SGC cell lines is small, with only 19 SGC cell lines identified in the literature (13), and we originally established 8 out of the 19 SGC cell lines. In this study, we identified the characteristic genes of SGC cells using 8 of the 19 SGC cell lines, including 5 of our own original SGC cell lines.

Materials and Methods

Cell lines. Eight SGC cell lines, OCUM 1, OCUM 2MLN, OCUM 8, OCUM 12, OCUM 14, GCIY, KATO-3, and NUGC3; and 3 non-SGC cell lines, MKN7, MKN74, and NCI-N87, were used. Five out of the 8 SGC cell lines, OCUM 1, OCUM 2 MLN, OCUM 8, OCUM 12, and OCUM 14, were established in our laboratory; KATO-III, NUGC3, and MKN-74 were purchased from the Japanese Collection of Research Bioresources (14), and GCIY, MKN-7, and NCI-N87 were obtained from the RIKEN BioResource Center (15). A total of 10 gastric cell lines, excluding GCIY, were incubated in a culture medium consisting of Dulbecco’s modified Eagle’s medium (DMEM; Nikken, Kyoto, Japan) at 37°C, in 21% oxygen, with the addition of 10% fetal bovine serum (Nichirei, Tokyo, Japan), 100 IU/ml penicillin (Wako, Osaka, Japan) and 0.5 mmol/l sodium pyruvate (Wako). GCIY was cultured under similar conditions except that 15% fetal bovine serum was used.

Clinical materials. A total of 722 patients who were histologically diagnosed with primary gastric cancer at Osaka Metropolitan University and underwent resection of the gastric tumor and regional lymph nodes were enrolled in this study. Patients who received preoperative radiation therapy or chemotherapy were omitted. Pathological diagnosis and classification were made according to the UICC TNM classification of malignancy. The study was approved by the Ethics Committee of Osaka Metropolitan University (Ref. No. 924), and informed consent was obtained from all patients.

RNA-seq data from a public database. To identify driver genes for SGC, we obtained RNA-seq analysis data from the Cancer Cell Line Encyclopedia (CCLE) database for SGC and non-SGC cell lines (16, 17). GCIY, KATO3, and NUGC3 were used as the SGC group and MKN7, MKN74, and NCIN87 as the non-SGC group.

Bioinformatics. All FASTQ files in the CCLE were pseudo-aligned using Kallisto (v0.46.2) to quantify transcript expression based on GRCh38. Gene expression quantification used the Kallisto/sleuth pipeline. Kallisto is a pseudo-alignment-based method that quantifies RNA amounts at the gene and transcription level in scaled read per base and TPM (transcripts per million) counts (18). Kallisto quant was performed for indexing with the number of bootstraps set to 100 using ENSEMBL cDNA transcripts [Human assembly hg38 (GRCh38), release 94] (19). To extract differentially expressed genes (DEGs) expression, we first used the Sleuth R package (v0.30.0) (18) to utilize Kallisto’s bootstrap estimates and output a model-based, gene-level normalized TPM matrix. Each gene was performed in the conditional parameters using both the likelihood ratio test and the Wald test (20). DEGs were those that met the FDR cutoff of <0.05 for both of the two tests (19). We used the Plot transcript heatmap function of the Sleuth package to visualize the cluster analysis. The Plot volcano and Plot ma functions were used to generate volcano plots and MA-plots, visual tools to display DEGs within the overall gene expression levels.

Next-generation sequencer analyses. RNA-seq was performed on the Ion Torrent S5 next-generation sequencing platform (Thermo Fisher Scientific, Waltham, USA) according to the manufacturer’s instructions. The RNeasy Plant Mini Kit (Qiagen, Venlo, the Netherlands) was selected as the method for extracting total RNA from each cell line. The quality of RNA was analyzed by NanoDrop 2000c (Thermo Fisher Scientific), and the concentration was determined using a Qubit RNA HS Assay Kit (Thermo Fisher Scientific) and the Qubit 2.0 Fluorometer (Thermo Fisher Scientific). For cDNA preparation, total RNA was adjusted to less than 1 μg and extracted using the SMART-Seq® v4 Ultra® Low Input RNA Kit for Sequencing (Clontech, CA, USA). After purification, cDNA was fragmented using the cDNA library preparation kit Ion Xpress Plus Fragment Library Kit (Thermo Fisher Scientific). Purified DNA was washed using Agencourt AMPure XP SPRI beads (Beckman Colter, CA, USA). The cDNA library was amplified using PCR to enrich for adapter binding fragments. Each library was measured using a Qubit 2.0 Fluorometer and quality checked with E-Gel 2% Agarose (Thermo Fisher Scientific). Furthermore, the library of each sample was diluted up to 100 pM and emulsion PCR was performed (Ion One Touch 2, Ion One Touch ES, Thermo Fisher Scientific). Subsequently, enriched template positive ion spherical particles were then loaded onto a 540 chip and sequenced in the ION S5 next-generation sequencing platform (Thermo Fisher Scientific). All raw FASTQ files obtained were subjected to pseudo-alignment using Kallisto (v0.46.2) to quantify transcript expression based on GRCh38. The same procedure as the in-silico analysis described above was also used to analyze the expression of our original SGC cell line.

Quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR). Total RNA was extracted from each cell line with RNeasy Plant Mini Kit (Qiagen) and the quality was analyzed with NanoDrop 2000c (Thermo Fisher Scientific). cDNA was reverse transcribed using ReverTra Ace qPCR RT Master Mix (Toyobo, Osaka, Japan). RT-PCR technique was performed using TaqMan Fast Advanced Master Mix (2×) and TaqMan Probe (20×) (Thermo Fisher Scientific), adjusted according to the manufacturer’s protocol at 20 μl per well and the study was performed on an ABI Prism 7000 (Applied Biosystems, Foster City, CA, USA). The amplification parameters were set at 95°C for 3 s and 60°C for 30 s. A total of 40 cycles were performed, and mRNA levels for each gene were normalized by the internal control HPRT1.

Western blot analysis. Proteins from each cell line were extracted by standard methods using PRO-PREP Protein Extraction Solution (iNtRON Biotechnology, Jungwon-Gu, Republic of Korea). The protein concentration of each sample was determined using the Coomassie Plus Assay Kit (Thermo Fisher Scientific). Proteins were electrophoretically transferred to a membrane followed by blocking in Tris-buffered saline (TBST) buffer containing 3.0% skim milk and 0.1% Tween-20. After washing with phosphate buffered saline with Tween-20 (PBS-T) solution, the membrane was placed in PBS-T containing each primary antibody [NOS3 (nitric oxide synthase 3; 1:750; Santa Cruz, Dallas, TX, USA), ARHGAP4 (Rho GTPase-activating protein 4; 1:1,000; Santa Cruz), OR51B5 (olfactory receptor family 51 subfamily b member 5; 1:200; Biorbyt, Cambridge, UK) and β-actin (1:5,000; Sigma-Aldrich)] at 4°C overnight. After further washing in PBS-T, they were incubated with secondary antibodies for 1 h and analyzed by enhanced chemiluminescence using ECL Prime (GE Health Care, Buckinghamshire, UK).

Immunohistochemical determination. The immunohistochemical determination of NOS3, ARHGAP4, and OR51B5 expression in gastric tumors was performed as follows: deparaffinization was performed, slides were heated, and endogenous peroxidase activity was blocked. The samples were incubated with anti-NOS3 (1:250; Santa Cruz), anti-ARHGAP4 (1:500; Santa Cruz), and anti-OR51B5 (1:500; Biorbyt, Cambridge, UK) overnight at 4°C. They were then incubated with biotinylated secondary antibodies, treated with streptavidin-peroxidase reagent, and contrast stained with Mayer’s hematoxylin. The expression levels of NOS3, ARHGAP4, and OR51B5 were evaluated by the staining intensity and percentage of stained cancer cells, respectively: Intensity was scored from 0 to 3 (0=none, 1=weak, 2=moderate, 3=intense) and the percentage of positive cells was scored from 0 to 3 (0=0%, 1=1-20%, 2=21-50%, 3=51-100%). The two scores were multiplied to gain the final result of 0-9. Expression was rated as positive when scores were ≥3 and negative when scores were ≤2. Scoring was performed by two double-blind independent observers, and any discrepancies in evaluation between the observers were rechecked and discussed.

Statistical analysis. The chi-square test was used to calculate the significance of differences between covariates. Survival rates were analyzed by the Kaplan–Meier method and calculated by the log-rank test, and cumulative survival rates in each patient group were compared. In addition, univariate hazard ratios for the study parameters were calculated using the Cox proportional hazards model. In general, p<0.05 was defined as statistically significant, and SPSS software (SPSS Japan, Tokyo, Japan) was used for analysis.

Results

RNA-seq data based on in silico analysis and our unique SGC cell lines. In silico analysis using 3 strains of SGC cell lines and 3 strains of non-SGC cell lines showed that 21 DEGs were more dominant (q<0.05) in SGC cells than in non-SGC cells (Figure 1A). RNA-seq of 5 SGC cell lines indicated that 3 of the 21 types of DEGs, ARHGAP4, NOS3, and OR51B5, were commonly expressed in all five cell lines (Figure 1B).

Figure 1.
Figure 1.

Heatmap of 21 differentially expressed genes (DEGs) that have significantly higher expression in Scirrhous-type gastric cancer (SGC) cell lines, obtained from RNA-seq data from public data. A) Heat map of 21 DEGs as a result of in silico analysis. B) Heat map of 21 DEGs extracted by in silico analysis by performing RNA-seq on our unique 5 SGC cell lines. C) Volcano plot and MA-plot in silico analysis. The log 2-fold change of 3 DEGs was 2.5 or higher, indicating that it is highly expressed in the SGC group. DEGs that satisfy q<0.05 are shown in red plots. The higher the expression level, the darker the color. The scaled read per base is a scale derived from Kallisto that quantifies expression at the gene level.

The log2 fold change (log2FC) of ARHGAP4, NOS3, and OR51B5 was 2.5 or higher, indicating high expression levels in the SGC group. Moreover, the average abundance in all the samples was relatively high for all three DEGs. The q value and log2FC were as follows: ARHGAP4 q=3.095×10−3, log2FC=3.043; NOS3 q=6.405×10−3, log2FC=3.140; and OR51B5 q=1.524×10−3, log2FC=4.262 (Figure 1C).

Expression levels of the three DEGs were reproducible in each cell line at both the RNA and protein levels. In RT-PCR evaluation, it was in the SGC group that the three DEGs showed significantly higher expression levels in each cell line: ARHGAP4 showed high expression in GCIY, KATO3, NUGC3, and OCUM14; NOS3 in KATO3, OCUM1, OCUM2MLN, OCUM8, and OR51B5 in GCIY, KATO3, NUGC3, OCUM2MLN, and OCUM12. In contrast, no cell lines showed high DEG expression levels in the non-SGC group (Figure 2A). Western blot analysis results correlated with the RT-PCR evaluation results and showed that the three DEGs were not expressed in the non-SGC group, even at the protein level. Additionally, in cell lines with high expression by RT-PCR, the bands were clearly recognized and reproducible in Western blot analysis as well (Figure 2B).

Figure 2.
Figure 2.

qPCR analysis and western blot analysis of 3DEGs in each cell line. A) The expression level of each cell line was evaluated by qPCR analysis. The relative amount is shown, with the expression level of MKN7=1.0, as a control. B) The results of qPCR analysis and western blot analysis show similar expression patterns, and reproducibility was confirmed.

ARHGAP4-positive, NOS3-positive, and OR51B5-positive patients. ARHGAP4, NOS3, and OR51B5 were mainly expressed in the cytoplasm of the SGC cells (Figure 3). Among the 722 gastric cancer cases, ARHGAP4, NOS3, and OR51B5 were positive in 270 cases (37.5%), 217 cases (30.1%), and 194 cases (26.9%), respectively. The relationship between the clinicopathologic features and the three DEGs’ expression are summarized in Table I. All three DEGs were more highly expressed in Macroscopic type-4 and diffuse type disease. Other factors were also found to be significantly up-regulated in patients with malignant potential.

Figure 3.
Figure 3.

Representative images of NOS3, ARHGAP4, and OR51B5 expression in gastric cancer. NOS3, ARHGAP4, and OR51B5 are mainly expressed in the cytoplasm of cancer cells (×200). Bar, 100 μm.

View this table:
Table I.

Patient demographics in resected cases according to 3 differentially expressed genes (DEGs) expression status.

Correlation between the three DEGs’ expression and the patients’ survival. The overall survival of gastric cancer patients with ARHGAP4, NOS3, and OR51B5 expression was significantly poorer than that of patients without (p<0.001, p=0.042, and p<0.001, respectively) (Figure 4A). Recurrence-free survival was significantly lower in gastric cancer patients expressing ARHGAP4 and OR51B5 than in patients without ARHGAP4 and OR51B5 expression (p<0.001 for both) (Figure 4B).

Figure 4.
Figure 4.

Survival curve of patients with gastric cancer. A) The overall survival of 722 patients with gastric carcinoma according to each expression status. B) Recurrence-free survival of 548 patients with gastric carcinoma according to each expression status.

The univariate analysis showed that overall survival was significantly correlated with ARHGAP4, NOS3, and OR51B5 positivity, age, histological type, invasion depth, lymph node metastasis, and metastasis. Furthermore, the multivariate analysis revealed that ARHGAP4 positivity (p<0.001), invasion depth (p<0.001), lymph node metastasis (p<0.001), and metastasis (p<0.001) were significantly correlated with overall survival (Table II). In the case of recurrence-free survival, univariate analysis revealed that it was significantly correlated with ARHGAP4 and OR51B5 positivity, age, histological type, invasion depth, and lymph node metastasis. Multivariate analysis revealed that ARHGAP4 positive (p<0.001), invasion depth (p<0.001), and lymph node metastasis (p<0.001) were significantly correlated with recurrence-free survival (Table III).

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Table II.

Univariate and multivariate Cox multiple regression analysis with respect to overall survival after surgery in 722 patients with gastric carcinoma.

View this table:
Table III.

Univariate and multivariate Cox multiple regression analysis with respect to recurrence free survival after surgery in 548 patients with gastric carcinoma.

Discussion

In this study, we identified three candidate oncogenes, ARHGAP4, NOS3, and OR51B5, which may be associated with the development of SGC.

In our study, ARHGAP4 was expressed in SGC cell lines more than in non-SGC cell lines. ARHGAP4 is a member of the Rho-GTPase activating proteins (Rho-GAPs) family and has an SH3 structure that interacts with proline-rich domains of many proteins. It is involved in cell scaffold formation, intracellular vesicle transport and endocytosis (21), and cell motility (22). ARHGAP4 has been reported to increase the expression of matrix metalloproteinase 2 and 9, resulting in the stimulation of the invasion and migration activity of pancreatic (23) and breast cancer cells (24). ARHGAP4 has also been reported to decrease the protein expression levels of E-cadherin and claudin-1 (24), which is closely associated with the characteristic findings of SGC. Our study also indicated that ARHGAP4 was an independent prediction factor of both overall survival and recurrence-free survival. These findings may suggest that ARHGAP4 is both a useful predictor of prognosis for patients with gastric cancer and a promising molecular target for SGC.

NOS3 was highly expressed in SGC cell lines. In our immunohistochemical analysis, the NOS3-positive group was significantly higher in the clinicopathological factors with any malignant potential such as diffuse type, lymph node metastasis positive, peritoneal metastasis positive. It has been reported that NOS3 promotes peritoneal dissemination by promoting epithelial-mesenchymal transition (EMT), through the mitogen-activated protein kinase (MAPK) signaling pathway (25). NOS3 has been reported to enhance migration and invasion of breast cancer and colon cancer cells through soluble guanylate cyclase and the MAPK pathway (25-28). Because EMT is one of the characteristic features of SGC cells, NOS3 might be associated with the EMT of SGC. OR51B5 has been reported to be associated with cell survival and collagen biosynthesis, which is one of the characteristic findings of SGC.

In conclusion, ARHGAP4, NOS3, and OR51B5 may be candidate driver genes for SGC, and ARHGAP4 may be an especially promising molecular target for SGC.

Acknowledgements

The Authors thank Masakazu Yashiro (Molecular Oncology and Therapeutics, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan) for the helpful advice in the experimental design and paper preparation.

Footnotes

  • Authors’ Contributions

    R.A, T.S, K.M, G.T, Y.Y, A.S, S.K, S.T, K.K and H.K collected the tumor specimens and contributed to the in vitro experiments. M.O and K.M suggested and co-designed the study. All Authors read and approved the final manuscript.

  • Conflicts of Interest

    All Authors declare no conflicts of interest in relation to this study.

  • Received September 6, 2022.
  • Revision received September 24, 2022.
  • Accepted September 26, 2022.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

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Candidate Oncogenes, ARHGAP4, NOS3, and OR51B5, for the Development of Scirrhous-type Gastric Cancer
TOMOHIRO SERA, TAKASHI SAKUMA, KOJI MARUO, GEN TSUJIO, YURIE YAMAMOTO, ATSUSHI SUGIMOTO, SYUHEI KUSHIYAMA, SHINGO TOGANO, KENJI KURODA, HIROAKI KASASHIMA, MASAICHI OHIRA, KIYOSHI MAEDA
Anticancer Research Nov 2022, 42 (11) 5195-5203; DOI: 10.21873/anticanres.16026
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