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PLK2 Single Nucleotide Variant in Gastric Cancer Patients Affects miR-23b-5p Binding

Purpose Chromosomal instability is a hallmark of gastric cancer (GC). It can be driven by single nucleotide variants (SNVs) in cell cycle genes. We investigated the associations between SNVs in candidate genes, PLK2, PLK3, and ATM, and GC risk and clinicopathological features. Materials and Methods The genotyping study included 542 patients with GC and healthy controls. Generalized linear models were used for the risk and clinicopathological association analyses. Survival analysis was performed using the Kaplan-Meier method. The binding of candidate miRs was analyzed using a luciferase reporter assay. Results The PLK2 Crs15009-Crs963615 haplotype was under-represented in the GC group compared to that in the control group (Pcorr=0.050). Male patients with the PLK2 rs963615 CT genotype had a lower risk of GC, whereas female patients had a higher risk (P=0.023; P=0.026). The PLK2 rs963615 CT genotype was associated with the absence of vascular invasion (P=0.012). The PLK3 rs12404160 AA genotype was associated with a higher risk of GC in the male population (P=0.015). The ATM Trs228589-Ars189037-Grs4585 haplotype was associated with a higher risk of GC (P<0.001). The ATM rs228589, rs189037, and rs4585 genotypes TA+AA, AG+GG, and TG+GG were associated with the absence of perineural invasion (P=0.034). In vitro analysis showed that the cancer-associated miR-23b-5p mimic specifically bound to the PLK2 rs15009 G allele (P=0.0097). Moreover, low miR-23b expression predicted longer 10-year survival (P=0.0066) in patients with GC. Conclusions PLK2, PLK3, and ATM SNVs could potentially be helpful for the prediction of GC risk and clinicopathological features. PLK2 rs15009 affects the binding of miR-23b-5p. MiR-23b-5p expression status could serve as a prognostic marker for survival in patients with GC.


INTRODUCTION
Gastric cancer (GC) is the fourth most common cause of cancer-related death worldwide [1]. GC is a complex, multifactorial disease influenced by intricate interactions between environmental and genetic factors [2]. In a large study conducted by The Cancer Genome Atlas (TCGA) involving 295 patients with gastric adenocarcinoma, approximately 50% of

DNA isolation
Genomic DNA was isolated from adjacent non-tumor gastric and tumor tissue samples from patients with GC and peripheral blood samples of controls using the Wizard Genomic DNA Purification Kit (Promega Corporation, Madison, WI, USA) following the manufacturer's instructions. The concentration and purity of isolated DNA were determined spectrophotometrically using a Synergy H4 Hybrid Microplate Reader (BioTek Instruments, Inc., Winooski, VT, USA).

SNV selection and genotyping
Seven SNVs in cell cycle genes were selected for genotyping: rs963615 and rs15009 in PLK2; rs17883304 and rs1204160 in PLK3; and rs228589, rs189037, and rs4585 in ATM. The SNVs were selected according to the following criteria: a) previous reports of gene associations with GC, b) minor allele frequency (MAF) of ≥10% in Utah residents with Northern and Western European ancestry (CEU) population according to the 1000 Genomes Project Phase 3 project, and c) in silico analysis of functional annotations in the selected candidate regions using the publicly available single nucleotide polymorphism selection tool, SNPinfo (http://www.niehs.nih.gov/snpinfo) [21]. The SNVs were genotyped using the following TaqMan allelic discrimination assays, which were supplied as predesigned SNV genotyping assays: C_8962866_10 (rs963615), C_2839927_1_ (rs15009), C_63720915_10 (rs17883304), C_159308_10 (rs12404160), C_2283144_1_ (rs228589), C_2283145_10 (rs189037), C_1039793_20 (rs4585) (Applied Biosystems, Foster City, CA, USA). Genotyping was performed in 5-µL reaction mixtures containing 20x SNV genotyping assay, 2x Taq-Man Genotyping Master Mix (Applied Biosystems), and 10 ng of genomic DNA. The polymerase chain reaction (PCR) was performed according to the manufacturer's protocol using ViiA TM 7 Real-Time PCR System and QuantStudio TM Real-Time PCR Software (Applied Biosystems) with the following cycling conditions: 60°C for 30 seconds, 95°C for 10 minutes followed by 45 cycles at 95°C for 15 seconds, 60°C for 1 minute, and 60°C for 30 seconds. Random samples were selected and re-genotyped to confirm the consistency of obtained genotypes.

Haplotype analysis
For SNVs in ATM, PLK2, and PLK3, raw genotyping data for genetic variants, rs228589, rs189037, and rs4585 in ATM; rs15009 and rs963615 in PLK2; and rs17883304 and rs12404160 in PLK3, were extracted. to perform haplotype analysis and generate the haplotype block structure, which entailed corrections for multiple comparisons by 10000 permutations, Haploview software version 4.2. [22] and SNP tools V1.80 (MS Windows, Microsoft Excel) [23] were used. In this regard, the solid spine of the linkage disequilibrium (LD) algorithm with a minimum Lewontin D′ value of 0.8 was chosen. To correct the occurrence of type I errors (false positive results), a permutation procedure was performed using Haploview (10000 permutations). This approach enables correction for multiple testing, but also considers the correlation between markers. Hence, permutation correction is less conservative than Bonferroni correction; however, it is suitable for independent tests with multiple markers [24]. https://jgc-online.org The miRANDA algorithm used in the MirSNP database uses criteria where the seed region contains at least seven nt long. However, we additionally excluded miRs that could potentially bind to one allele with a 6 nt seed region, as this possibility has been observed and described previously in the literature [28]. For PLK2, which lies on the reverse strand, all alleles are reported in the forward orientation. Gene orientation was considered for in silico functional analysis. Sequences for in silico analysis of the studied SNVs in FASTA format were extracted from Ensembl Release 99 (http://www.ensembl.org) [29].

Dual Luciferase reporter assay
The PLK2 3' UTR region with the wild-type (Wt) or polymorphic allele (Var) was cloned into the dual luciferase reporter vector pmirGLO (Promega Corporation). GC cells, MKN45, obtained from the Japanese Collection of Research Bio Resources Cell Bank (JCRB, Osaka, Japan) were transfected with miR-23a-5p, miR-23b-5p, or negative control mimics (Dharmacon, Lafayette, CO, USA) and pmirGLO-PLK2-3'UTR Wt, pmirGLO-PLK2-3'UTR Var, or pmirGLO as negative controls, using GenMute siRNA Transfection Reagent (SignaGen Laboratories, MD, USA) according to the manufacturer's protocol. Luciferase activity was measured using the Dual Luciferase Reporter Assay (Promega Corporation) on the Synergy H4 Hybrid Microplate Reader (BioTek) luminometer, 48 hours after transfection. Experiments were performed in triplicate and replicated four times. Data are represented as the mean ± standard deviation and were compared using GraphPad Prism version 8.0.2 for Windows. Statistical significance was set at P<0.05.

Statistical analysis
The agreement of genotype frequencies with Hardy-Weinberg equilibrium (HWE) and the differences in genotype distribution between cases and controls were calculated using the chi-squared test. Minor genotype and allele frequencies for candidate SNVs were compared to the frequencies in populations from the 1000 Genome Project Phase 3 release. A generalized linear model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to examine the association of selected SNVs with the risk of GC and clinicopathological features. Dominant, recessive, and co-dominant genetic models were used for the analysis, depending on the genotype frequencies. All associations were calculated using R studio version 3.5.3 [30] and the SNPAssoc package for R [31]. When more associations were significant for one SNV, the genetic model with the lowest Akaike information criterion value was selected [32]. The associations between SNVs genotypes and overall patient survival were estimated using the Kaplan-Meier (KM) method and log-rank test using GraphPad Prism version 8.0.2 for Windows (GraphPad Software, San Diego, CA, USA, www.graphpad.com). Statistical significance was set at P<0.05. KM miR survival curves were generated using the KM Plotter online tool (https://kmplot.com) [33] and TCGA datasets (n=436 patients with GC). The TCGA dataset is available using the following link: https://portal.gdc.cancer.gov/. Differential expression of hsa-miR-23b-5p in tumors vs. normal or high vs. low-grade GC samples was extracted from the dbDEMC 3.0 database (https://www.biosino.org/dbDEMC/index) [34]. Expression datasets in dbDEMC are based on microarray or miRNA-seq platforms obtained from public repositories, including Gene Expression Omnibus (GEO), Sequence Read Archive, ArrayExpress, and TCGA.

Characteristics of study participants and genotype distributions of studied SNVs
A total of 221 patients with GC were enrolled in this study. Clinical and histological data were extracted from registered medical records and are presented in Table 1. Male patients accounted for 62.25%, and female patients accounted for 37.75% of the study cohort. Their mean age at diagnosis was 67.3 years. Data on histological type, according to Lauren's classification; location; grade of differentiation; and vascular, perineural, and lymphatic invasion were included in the study. SNVs from the three cell cycle genes, PLK2, PLK3, and ATM, are presented in Table 2. All selected SNVs were located in the non-coding regions of the genes. Genotype and allele frequencies in patients with GC and controls were comparable to those in populations from public databases (Supplementary Fig. 1). The distribution of genotype frequencies and HWE in patients with GC and controls for each studied SNV were analyzed using the chi-square test (Supplementary Table 1

PLK2 and PLK3 SNVs are associated with GC risk in male and female populations
We performed analyses based on generalized linear models to evaluate the association between candidate SNV genotypes and GC risk. Genotyping was performed on DNA isolated from non-tumor gastric tissues ( Table 3). There were no significant associations between the cell cycle genes SNVs, PLK2 rs963615, rs15009, PLK3 rs17883304, and rs12404160, or ATM rs228589, rs189037, and rs4585 and GC risk. In the stratified analysis, there were significant associations between the PLK2 rs963615 CT genotype and lower GC

ATM, PLK2, and PLK3 haplotypes are associated with GC risk
For haplotype analysis, a single haplotype block was created that included either PLK2, PLK3, or ATM SNVs with an average Lewontin D' > 0.8 (D'=1.0 value shows the strongest LD between the two polymorphisms) (Fig. 1). Haplotype frequencies of the cases and controls are presented in Table 4. The frequency of the PLK2 C rs15009 -C rs963615 haplotype was lower in the GC group than that in the control group, with borderline significance (P corr =0.050). This association was marginal; therefore, our results should be interpreted with caution and further validated in a larger cohort. The frequency of the PLK3 A rs17883304 -T rs12404160 haplotype was significantly lower in the GC group than that in the control group (P corr =0.001).
Additionally, the frequency of the ATM A rs228589 -G rs189037 -T rs4585 haplotype was significantly lower, and that of the T rs228589 -A rs189037 -G rs4585 haplotype was significantly higher in the GC group than in the control group (P corr <0.001).

PLK2 and ATM SNVs are associated with the presence of vascular and perineural invasion
Association analysis between SNVs genotypes and clinicopathological tumor features was performed on genotyping results from gastric tumor tissue DNA, given that variations in tumor tissue define the behavior and characteristics of the tumor. The categories with the most significant results are presented in

Associations between candidate SNV genotypes and survival prognosis of patients
The survival interval in our GC patient cohort ranged from 1.6-133.5 months (mean, 40.0 months). Survival analysis was performed to examine the effect of candidate SNVs on the prognosis of patients with GC ( Fig. 2). Analysis was performed on SNVs where each genotype group comprised a minimum of five participants. No significant associations were found between candidate SNV genotypes and overall survival in patients with GC. However, a trend was observed for patients with the PLK2 rs15009 GG genotype, who had a 10-

In silico SNV functional analysis
Next, we performed in silico functional analysis of the candidate SNVs with statistically significant associations, including SNVs with observed trends in survival analysis. The 5'-UTR regions and introns typically contain enhancer and silencer regions and bind transcription factors to enhance or repress gene transcription [35,36]. These motifs may also be present in the 3' UTR [37]. Additionally, variations in the 3' UTR may affect the binding of miRs and, therefore, the mRNA expression levels. The results of the disruption of transcription factor binding sites due to polymorphic sites and identification of miRs that differentially bind to these polymorphic sites are summarized in Table 6.
In PLK2 rs963615, a TATA-binding protein (TBP) binding motif was created if the T allele was present. In PLK2 rs15009 Enkephalin transcription factor 1 (ENKTF-1) appeared to bind in the presence of the C allele, whereas Retinoid X receptor α:Retinoic acid receptor β (RXRα:RAR-β), Multiprotein bridging factor-1 and vitamin D receptor binding motifs were created when the G allele was present. Moreover, putative binding sites for miR-23a-5p and miR-23b-5p were formed when the G allele of PLK2 rs15009 was present, in contrast with the C allele. In PLK3 rs12404160, a binding motif for Purine Rich Box-1 (PU. 1     c-erythroblast transformation-specific transcription factor-1 (c-Ets-1), and erythroblast transformation-specific Like-1 protein (Elk-1) were generated. In ATM rs189037, a binding motif for retinoblastoma-associated protein-1 (E2f-1) is created in the presence of the G allele. Finally, in the presence of the T allele in ATM rs4585, binding sites for X-box binding protein-1 (XBP-1) and general transcription factor IID, as well as the binding site for miR-2964a-5p, were created.

miR-23b-5p targets PLK2 rs15009
Haplotype analysis results suggested that the PLK2 C rs15009 -C rs963615 haplotype may have a marginal protective role in GC risk (P corr =0.050). We performed luciferase reporter assays to evaluate how the presence of different alleles (C/G) in the PLK2 3'-UTR region affects the binding of miR-23a-5p and miR-23b-5p, as both have been previously associated with GC [38,39]. The relative luciferase activity of the pmirGLO-PLK2-3'UTR Var (G allele) was decreased by 12% when the cells were co-transfected with the miR-23a-5p mimic (P=0.085) and by 41% when they were co-transfected with the miR-23b-5p mimic (P=0.0097) compared to miR co-transfection in the negative control (Fig. 3B). The relative luciferase activity of the pmirGLO-PLK2-3'UTR Wt (C allele) was unaffected by co-transfection with both mimics (Fig. 3B). These results suggest that miR-23b-5p directly targets PLK2 when the G allele is present in PLK2 rs15009.
We used the KM plotter online tool to analyze whether miR-23b-5p could have prognostic value in patients with GC (Fig. 3C). The analysis showed that low miR-23b-5p expression predicted longer 10-year survival in patients with GC (hazard ratio=1.52, P=0.0066). There was no significant correlation between miR-23a-5p expression and overall survival in GC patients using the KM plotter tool (P=0.304, data not shown). We also analyzed differential miR-23b-5p expression in the TCGA_STAD (The Cancer Genome Atlas Stomach Adenocarcinoma) dataset as well as available GEO datasets to evaluate miR-23b-5p expression in tumor vs. normal or high-grade vs. low-grade samples: the results are shown in Fig. 3D and E. MiR-23b-5p was downregulated (log FC=-1.26) in tumor sample compared to normal samples (TCGA_STAD dataset, P adj = 4.88×10 -3 ) (Fig. 3D). Notably, in the GSE33743 dataset, miR-23b-5p was upregulated in tumors compared to normal samples (log FC=0.76, P adj =3.21×10 -2 ). MiR-23b-5p expression was downregulated in high grade vs. low grade tumour samples from the TCGA_STAD dataset (Fig. 3E) Higher risk Transcription factors and miRs that differentially bind to polymorphic sites are presented in the table. SNV = single nucleotide variant; TF = transcription factor; miR = micro ribonucleic acid. * Alleles are reported in the forward orientation; † Observed trend.

DISCUSSION
In this study, we investigated the associations between SNVs in cell cycle genes, PLK2, PLK3, and ATM, and GC risk and the clinicopathological features of patients with GC. Candidate SNVs with significant associations were further functionally analyzed to determine their potential regulatory effects on transcription factors and miRNA-binding sites. We also confirmed the putative PLK2 binding site for miR-23b-5p in vitro.
GC is approximately twice as likely to be diagnosed in men than in women [1]. Incidence variation by sex has been attributed to sex-specific lifestyles and potential underlying hormonal mechanisms. The PLK2 rs963615 CT genotype could be used for selection of female persons at higher GC risk and as a determinant for lower GC risk in the male population. In the presence of the T allele, a binding motif for the transcription factor, TBP, was formed according to in silico functional analysis. The expression level of TBP has been confirmed to affect cell proliferation and transformation potential [40]. Additional sex-specific cellular factors may also contribute to TBP levels. Next, the PLK3 rs12404160 AA genotype could be used as a biomarker for the selection of male individuals at higher GC risk. In silico functional analysis implied a binding motif for the transcription factor, PU.1, in the presence of the G allele, suggesting that PU.1 may increase PLK3 transcriptional activity, which may result in tumor suppression. PU.1 has been previously identified as a tumor suppressor or oncogene in different types of leukemias, breast cancers [41], and gliomas [42]. PU.1 inhibition by small-molecule inhibitors or RNA interference decreases the tumor burden and increased the survival of patients with acute myeloid leukemia [43]. Further studies are necessary to confirm how PU.1 affects PLK3 transcription, how PU.1-associated actions differ in male and female patients, and whether it would be beneficial to inhibit or promote its activity in patients with GC.
Haplotype analysis results suggest that the PLK2 C rs15009 -C rs963615 haplotype may have a protective role against GC, although the significance was borderline. To our knowledge, PLK2 rs15009, which lies in the 3' UTR region of the gene, has been studied only in association with the Reelin signaling pathway in Alzheimer's disease, where the authors showed that CC and GG genotypes had a protective effect [44]. In silico analysis results for PLK2 rs15009 suggested that binding of RXR-α and RAR-β proteins in the presence of the G allele and binding of ELK-1 and ENKTF-1 in the presence of the C allele may alter the level of PLK2 expression. RXR-α and RAR-β are retinoic acid nuclear receptors that regulate apoptosis, cell cycle, and differentiation [45]. Lower RXR-α expression has been reported in patients with GC and is significantly associated with advanced disease stages [46]. RAR-β hypermethylation is predominantly associated with diffuse GC [44]. Notably, in this study, it was further established that RAR-β methylation status was statistically associated with invasion, differentiation, and location of the tumor in diffuse types, whereas these histopathological features were not associated with RAR-β methylation status in intestinal types of GC [47]. This indicates that different levels of DNA binding factors or their differential binding to polymorphic sites could profoundly affect their downstream pathways and, thus, influence the development of distinct tumor types. Similarly, it has been found that ELK-1 activity promotes cell migration and invasion and is involved in cancer development due to inflammation [48,49]. Therefore, aberrant ELK-1 activity due to SNVs can affect PLK2 transcription and mRNA-associated processes. https://jgc-online.org Using a luciferase reporter assay, we analyzed the binding of miR-23a-5p and miR-23b-5p to PLK2 rs15009, which was selected as the best potential binding candidate for in silico analysis. We confirmed that miR-23b-5p binds specifically to the PLK2 rs15009 G allele. It has been proposed that miR-23b plays a dichotomous role in cancer, either as a tumor suppressor or as an oncogene. MiR-23b expression is downregulated in human glioma, prostate, bladder, breast, and gastrointestinal cancers and has been shown to suppress tumor growth, invasion, angiogenesis, and metastasis and affect chemoresistance and tumor cell dormancy [50][51][52][53][54][55]. In contrast, some studies have shown that the expression of miR-23b is upregulated, and that it may also function as an oncogene by promoting tumor growth, proliferation, and metastasis in prostate and breast cancer, as well as in GC [56][57][58]. Analysis of paired tumor-normal samples from 160 gastric adenocarcinoma patients demonstrated that coexpression of miR-23a and miR-23b was significantly upregulated, particularly in specimens from patients at advanced stages (II-IV), and correlated with lymph node metastasis [38]. In addition, miR-23a/b enhanced tumor growth in a GC xenograft mouse model by inhibiting apoptosis of GC cells by directly targeting a tumor suppressor, programmed cell death 4 protein.
The observed function of miR-23b as an oncomir is in line with our survival analysis results using the KM plotter on GC samples from the TCGA database. Lower miR-23b expression was associated with a higher 10-year survival rate. These results suggest that miR-23b-5p may serve as a prognostic factor for tumor progression and survival. Significantly shorter 5-year overall survival and disease-free survival were observed in patients with higher plasma miR-23b expression [59].
Notably, public dataset expression analysis showed that miR-23b-5p was downregulated in the TCGA_STAD cohort and upregulated in the GSE33743 cohort. It is worth noting that the first cohort included 436 tumor and 41 normal samples in the analysis, whereas the latter only analyzed 37 tumor and four normal samples. When comparing expression in high-vs. low-grade samples, miR-23b-5p was mostly downregulated, with the exception of the grade 3 vs. grade 2 comparison, where it was upregulated. These results suggest that miR-23b-5p may serve as a prognostic factor for tumor progression. Low miR-23b-5p expression appears to be associated with greater overall survival. Furthermore, comparison of its expression in high-and low-grade tumor tissues indicated that its expression could gradually decrease during tumor progression. This confirmed the dichotomous role of miR-23b, as discussed above. For better interpretation, analysis of samples grouped by sex, clinical and histological parameters, whether therapy is administered, and outcome, is necessary. Overall, the perplexing behavior of miRs confirms that in complex and heterogenic diseases such as GC, it is necessary to develop systems medicine approaches to decipher oncogenic mechanisms.
Therefore, the protective role of the PLK2 C rs15009 -C rs963615 haplotype in GC could be explained by PLK2 repression through miR-23b-5p binding to the G allele. To draw more definite conclusions from our study, we wanted to analyze a cohort in which the PLK2 rs15009 genotype, miR-23b-5p expression, and PLK2 mRNA expression would be known, possibly together with data on patient survival or response to therapy. Unfortunately, we were unable to obtain such datasets from publicly available databases. Nevertheless, we can theoretically consider two scenarios in which data on PLK2 rs15009 and miR-23b-5p expression levels would have clinical value. In the first scenario, individuals with the risk PLK2 rs15009 haplotype would also have overexpression of miR-23b-5p. This combination could result in the decreased expression and functional activity of PLK2 during the cell cycle. This would lead to tumor progression since PLK2 acts as a tumor suppressor [10][11][12]. In the second scenario, individuals with the PLK2 risk haplotype, who have miR-23b-5p underexpression, would have PLK2 mRNA levels higher than usual. High PLK2 levels are associated with a protective role in cancer, but might also lead to chemoresistance in individuals receiving chemotherapy. Previous observations have shown that at higher expression levels, PLK2 significantly predicted a poorer outcome in patients with colorectal cancer by enhancing chemoresistance [60]. PLK2 has also been proposed to be an important determinant of chemotherapy sensitivity in ovarian cancer [61]. Its repression through miR-23b-5p in the presence of the rs15009 G allele could reduce chemoresistance. Therefore, depending on the disease grade and whether therapy is administered, PLK2 rs15009 could be useful as a biomarker of chemotherapy resistance prediction in GC in combination with miR-23b expression levels. This could be exploited in the future for the development of novel targeted PLK2 therapies using either miR or PLK2 inhibitors or miR mimics [62]. Interactions between other proteins and miRNAs should also be considered.
The PLK2 rs963615 CT genotype was significantly associated with the absence of vascular invasion, whereas ATM rs228589, rs189037, and rs4585 were significantly associated with the absence of perineural invasion. These SNVs could be used in clinical settings to aid in prognosis and possibly in the determination of the most suitable treatment options for patients. The A allele of ATM rs228589 has been previously associated with a higher risk of chronic myeloid leukemia in the Indian population [63], whereas the T allele has been associated with a higher risk of breast cancer in the Jewish female population [64]. In a metaanalysis conducted by Zhao et al., the A allele in ATM rs189037 was significantly associated with breast, oral, and lung cancer risk in East Asian and Latino populations, but not in Caucasians [65]. Moreover, the AA genotype of rs189037 is significantly associated with a higher GC risk in the Chinese population [66]. It was also associated with higher TNM stage, overall tumor size, and survival prognosis. This is in concordance with our results, where ATM rs189037 AG + GG genotypes were associated with the absence of perineural invasion. ATM SNV rs4585 is associated with a lower risk of papillary thyroid carcinoma in the ATM haplotype, C rs373759 -G rs664143 -T rs4585 [67]. Notably, our results indicated that the ATM haplotype, T rs228589 -A rs189037 -G rs4585, was significantly more frequent, whereas A rs228589 -G rs189037 -T rs4585 was significantly reduced in patients with GC. The differences in associations between specific alleles and cancer risk may be due to the different ethnicities of the studied populations and different cancer types.
In silico analysis resulted in several transcription factor candidates that may, through ATM activation or silencing, depending on specific allele binding, contribute to higher GC risk (haplotype analysis) or the absence of perineural invasion. Low ATM expression is generally associated with more aggressive tumors. In contrast, overexpression of ATM may lead to cisplatin resistance, resulting in a less favorable prognosis [68]. The A allele of ATM rs228589 forms a binding site for YY1 and PEA3; however, this binding motif is lost if an individual is a carrier of the T allele. YY1 expression is upregulated in GC cell lines and tissues, contributing to gastric carcinogenesis [69]. YY1 is also considered a potential therapeutic target [70]. PEA3 was upregulated in gastric adenocarcinoma samples, and together with the ERK signaling pathway, indicated poor survival prognosis [71]. In the presence of the G allele of ATM rs189037, a binding motif for E2f-1 is formed. E2f-1 has been previously associated with poor overall survival in GC [72]. However, E2f-1 overexpression in the MGC-803 GC cell line results in cell growth and proliferation inhibition, reduced invasion, and a higher apoptotic rate [73]. When the G allele is present, a binding site for STAT-4 and c-Ets-1 is formed. High STAT expression has been associated with better clinical outcomes in GC [74]. C-Ets-1 expression is correlated with H. pylori infection, a major risk factor for GC [75]. The T allele of ATM rs4585 https://doi.org/10.5230/jgc.2022.22.e31 PLK2 SNV Affects miR-23b-5p Binding participates in the formation of a binding motif for XBP-1. XBP-1 is involved in endoplasmic reticulum stress and unfolded protein response and it generally promotes cancer cell survival and tumor progression [76]. XBP-1 is a crucial factor that promotes tumor growth and invasion in GC while inhibiting apoptosis and autophagy [77]. Additionally, the hsa-miR-29641-5p binding site is formed in the presence of the T allele. Binding has been confirmed in vitro, and results in decreased ATM expression [78]. MiR-29641-5p has been characterized as an oncomiR in periampullary adenocarcinoma [79] and breast cancer [80].
Histological type, degree of differentiation, and molecular type of the tumor, as well as genetic background and cooperation between multiple miRs and miRNA-transcription factors may affect the final role of particular miR on gene expression. There are a few limitations to the power of SNV association studies. In complex diseases, the contribution of a particular SNV is usually modest. Study population size, allele frequencies, LD, and other parameters affect the power of the study [81]. We performed a candidate gene association study, which is a targeted approach compared to genome-wide association studies, where screening is untargeted and associations for marker SNVs are studied. Candidate gene association studies enhance the power of the study and are important when studying lowfrequency SNVs or when the study population is small, as in our case. Our study included 221 patients with GC and 321 healthy controls. In small study populations, larger effects are easier to detect, whereas smaller effects might be missed, leading to false negatives. Another limiting factor is the minimum MAF, which is typically 0.05 [82]. To compensate for the small sample size, we selected SNPs with MAFs≥0.10. Enriching for more common alleles increases the power to detect associations. However, it is important to keep in mind that rarer SNVs may have larger effect sizes, and omitting them may be potentially counterproductive [83]. Moreover, we assessed the MAF in our study group and CEU to ensure that they were comparable. When performing the analyses of risk-associated haplotypes, we included adjustments for multiple comparisons to avoid false positives. In some cases, the sample sizes were small for association tests between SNVs and clinicopathological features. Unfortunately, clinical data were not available for all the patients. Additionally, some reported associations are marginal; therefore, our results should be interpreted with caution and further validated in a larger cohort.
Our study indicates a possible role for PLK2, PLK3, and ATM SNVs in gastric tumorigenesis. We also show that PLK2 is targeted by miR-23b-5p in vitro and that low expression of miR-23b-5p in tumors is associated with better survival prognosis. Analyses of inter-individual genetic variability are of paramount importance in precision medicine, as they can significantly influence occurrence, course, and response to treatment. Low-penetrating variations in cell cycle genes may affect transcription factor and miR binding and can serve as biomarkers for tailored therapy selection, such as small-molecule or RNA inhibitors of transcription factors or oncomiR inhibitors. The current understanding of the molecular etiology and progression of GC is limited, and there is a critical need to explore novel genetic and molecular candidates that might contribute to the better management of this multifaceted disease.

ACKNOWLEDGMENTS
We express our gratitude to Dubravka Germ and Urša Adamič for their technical assistance with DNA isolation.