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Annals of Translational Medicine logoLink to Annals of Translational Medicine
. 2021 Jan;9(2):156. doi: 10.21037/atm-20-8052

Association study between KCNQ1 and KCNQ1OT1 genetic polymorphisms and gastric cancer susceptibility and survival in a Chinese Han population: a case-control study

Zhenyu Yang 1,#, Lijuan Yuan 1,#, Lin Yang 1,#, Shujia Peng 1, Ping Yang 1, Xianli He 1, Guoqiang Bao 1,
PMCID: PMC7867909  PMID: 33569458

Abstract

Background

The present study analyzed gene polymorphisms in the potassium voltage-gated channel KQT-like subfamily member 1 (KCNQ1) and the long noncoding RNA, KCNQ1OT1, and their impacts on genetic susceptibility and survival in a Chinese Han population with gastric cancer (GC).

Methods

We designed a case-control study that included 681 patients with GC and 756 healthy controls. Three single-nucleotide polymorphisms (SNPs) in the KCNQ1 gene region and eight SNPs in the KCNQ1OT1 gene region were selected for further research.

Results

Among the 11 SNPs, we found no significant differences in the genotype and allele frequencies between GC patients and the healthy population. Hierarchical analysis by the log-additive model indicated that the KCNQ1 rs231348 CT genotype was significantly associated with an increased GC risk in individuals aged ≥55 years, regardless of gender. The KCNQ1OT1 rs231352 CC and rs7128926 AA genotypes increased the risk of GC in individuals with stage III/IV tumors larger than 5 cm in diameter. On evaluating the genotype polymorphism and survival analysis, we detected that the AA genotypes of the KCNQ1OT1 rs7128926 and rs7939976 polymorphisms presented a significant survival advantage over the GA/GG genotypes, especially in patients with the following characteristics: age >55, Helicobacter pylori infection, BMI >24, tumor in the non-cardia region with a diameter greater than 5 cm, clinical stage II, and postoperative adjuvant chemotherapy.

Conclusions

Our results suggest that the KCNQ1 rs231348 and KCNQ1OT1 rs231352 polymorphisms might be independent predictors of the risk of GC susceptibility depending on certain factors, such as the age of the individual and the tumor stage and diameter. Simultaneously, genotype polymorphism of the rs7128926 and rs7939976 loci of the KCNQ1OT1 gene independently predicted the recurrence-free survival (RFS) and overall survival (OS) of GC patients.

Keywords: Polymorphisms, potassium voltage-gated channel KQT-like subfamily member 1 (KCNQ1), KCNQ1OT1, gastric cancer (GC), genetic susceptibility, survival, Chinese Han population

Introduction

Gastric cancer (GC), a common malignancy with a 5-year survival rate of <25%, is the second leading cause of cancer mortality worldwide (1). The highest GC incidence rate and mortality rate in both sexes are found in East Asia, with approximately 679,100 new cancer cases and 498,000 cancer deaths reported in 2018 in China (2). Carcinogenesis is a complex multistep process resulting from both genetic and environmental factors (3). The development of GC is caused by individual genetic susceptibility, potential environmental components, and/or dietary habits (4,5), such as tobacco smoking, alcohol use, water intake, and daily consumption of meat broth (6,7). Furthermore, genetic factors, among which single-nucleotide polymorphisms (SNPs) are the most common, also play an important role in the development and progression of tumors, including GC. With the continuous development of genetic research in recent years, especially the application of genome-wide association studies (GWAS), more GC susceptibility genes have been discovered (8). Thus far, all GWAS data are from East Asians, including Japanese, Korean, and Chinese populations. However, results from other populations are expected in the next few years (9).

The KCNQ1 gene is located on chromosome 11 and consists of 17 exons of different lengths, ranging from 47 bp (exon 14) to 1,122 bp (exon 16). KCNQ1 encodes the Q1 subfamily of the voltage-dependent potassium channel, a type of membrane protein ubiquitous in the body, that plays an important role in controlling gastric acid secretion and stabilizing resting potential (10). The KCNQ1 locus includes 8–10 maternal allele-encoded protein-coding genes and 1 long noncoding RNA (lncRNA), KCNQ1OT1 (11), which is an imprinted gene that is expressed from the paternal allele. The KCNQ1OT1 transcript regulates the silencing of other imprinted genes in the imprinted gene cluster at position 11p15.5. The KCNQ1 gene is highly expressed in peripheral blood leukocytes, the heart, prostate, inner ear blood vessels, stomach, small intestine, kidney, and pancreas, expressed in tissues that are critical for ion homeostasis (12,13). Humans carrying germline mutations in KCNQ1 develop a range of pathologies, most notably cardiac arrhythmia (long and short QT, Jervell and Lange-Nielsen syndrome), but also hearing loss, elevated gastrin levels, gastric hyperplasia, and in some cases gastric neoplasia (14-17). These phenotypes have been modeled in KCNQ1 knockout mice which develop inner ear defects, imbalance, chronic gastritis, gastric hyperplasia, and gastric metaplasia (18).

Because the transcription of the KCNQ1OT1 gene overlaps with most of the KCNQ1 transcription unit on the anti-strand, it is possible to affect the transcription of KCNQ1 and other non-overlapping genes through transcriptional interference (19). Meanwhile, KCNQ1OT1 can cause transcriptional silencing in chromosomal regions and can serve as an example of lncRNA-mediated gene transcription silencing (20); it has also been associated with poor patient survival in several gastrointestinal cancers, including colorectal cancer (CRC) (21), esophageal cancer (22), and hepatocellular carcinoma (HCC) (23). lncRNAs are closely related to the occurrence and development of tumors (24). Multiple polymorphic sites in the KCNQ1 and KCNQ1OT1 gene region are related to the occurrence and outcome of GC, and genetic variations are also associated with increased risk and overall survival (OS). KCNQ1OT1 dysregulation participates in carcinogenesis and progression of human cancers (25,26). However, the expression and potential functions of this gene region in GC are largely unknown. Therefore, this study selected SNP loci from the KCNQ1 and KCNQ1OT1 gene region and observed the relationship between SNP genotypes and the susceptibility and survival prognosis in Chinese GC patients.

We present the following article in accordance with the MDAR reporting checklist (available at http://dx.doi.org/10.21037/atm-20-8052).

Methods

Study participants

From May 2010 to June 2016, 681 patients with GC were enrolled from the Second Affiliated Hospital of the Air Force Medical University and 756 healthy subjects were recruited as controls through strict physical examinations in the same hospital. All 681 patients were confirmed as having primary GC by endoscopic and histopathological analysis. Patients with other types of cancers, gastritis, or gastric ulcers, or those who underwent radiotherapy or chemotherapy were excluded. In addition, all participants were Chinese who were not directly related within the past three generations. Demographic and lifestyle habit data of all the participants were collected through a detailed questionnaire, including residence, age, ethnicity, sex, dietary habits, and previous disease history.

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The current study was approved by the institutional ethics committees of the Second Affiliated Hospital of the Air Force Medical University (No. K201009-03). All the participants provided signed informed consent documents and a donation of approximately 5 mL of blood as part of this research.

Genomic DNA extraction and genotyping

Approximately 5 mL of peripheral blood were collected from each subject. Genomic DNA from whole blood samples was extracted using the TIANamp Blood DNA Purification Kit (Gold Mag Co. Ltd., Xi’an City, China) according to the manufacturer’s instructions. Extracted DNA was stored at −20 °C. The concentration and purity of the genomic DNA were determined using a NanoDrop Spectrophotometer (ND-1000, Thermo Fisher Scientific). The KCNQ1 and KCNQ1OT1 gene polymorphisms was genotyped on Agena Mass ARRAY RS1000 platform according to the standard protocol.

The associations between the functional SNPs of the KCNQ1 and KCNQ1OT1 genes and GC development were evaluated. The tag SNPs that represent the polymorphisms of a block were included in our study. Finally, three SNPs (rs6578283, rs231348, and rs760419) in KCNQ1, and eight SNPs (rs10832514, rs231361, rs231359, rs7128926, rs231356, rs231354, rs231352, and rs7939976) in KCNQ1OT1 were selected for further research. The characteristics of the sequences in this study are summarized in Table S1. Then, Agena Typer 4.0 software (Agena Bioscience) was used to analyze and manage our data.

Statistical analysis

Continuous variables, such as demographic variables, risk factors, and KCNQ1 and KCNQ1OT1 genotype distribution between the case and control groups, are shown as the mean ± standard deviation (SD) and were compared by Student’s t-test. Categorical variables are presented as frequencies with percentages (%) and were compared with the χ2 test or Fisher’s exact test when appropriate. The χ2 test was also used to assess whether the distribution of genotypes was consistent with the Hardy-Weinberg equilibrium (HWE). Univariate and multivariate logistic regression analyses were used to test the association between the SNP genotypes and the progression of GC based on the generated odds ratios (ORs) and 95% confidence intervals (18). Adjusted ORs were calculated using multivariate analysis adjusting for age and gender. The Kaplan-Meier method was used to estimate the OS and recurrence-free survival (RFS), the log-rank test was used to compare survival distributions, and the Cox proportional hazards model was used to determine the hazards ratio (HR). All statistical analyses were performed using SAS 9.4 software (IBM Corp.). Statistical significance was defined as a P value <0.05 with a two-tailed test.

Results

Characteristics of the participants

This study contained 681 GC patients and 756 healthy controls. Overall, the variable distribution of the selected demographic data did not differ between GC patients and controls. Table 1 shows the distributions of age, gender, and clinical stages of the study subjects. There were no significant statistical differences between the groups in terms of gender and age (P<0.001). The mean age was 57.57±10.826 years for GC patients and 52.58±8.709 years for the controls. The proportion of male subjects was significantly higher in both groups (77.4% vs. 64.7%, respectively). A follow-up of all patients was carried out according to our standard protocol, the median follow-up period for GC patients was 6.04 years (range, 0.12–10.68 years) and 6.15 years (range, 0.92–10.68 years) for the control cases. The latest follow-up data in this analysis was obtained in October 2019.

Table 1. Characteristics and clinical features of the GC group and the control group.

Variables GC (%) N=681 Controls (%) N=756 Pa
Age (years) <0.001
   M ± SD 57.57±10.826 52.58±8.709
   ≥55 251 (36.86) 429 (56.75)
   <55 430 (63.14) 327 (43.25)
Gender <0.001
   Male 527 (77.4) 489 (64.7)
   Female 154 (22.6) 267 (35.3)
BMI <0.001
   <24 460 (67.5) 432 (57.2)
   ≥24 221 (32.5) 324 (42.8)
Diameterb
   <5 cm 380 (55.8)
   ≥5 cm 273 (40.8)
H. pylori b
   Yes 392
   No 187
Stageb
,0/I/II 458 (67.25)
   III/ IV 204 (29.96)
R/Mb
   No 287
   Yes 377
Family historyb
   No 282
   Yes 45
ACTb
   Yes 430
   No 233
Positionb
   Cardia 125 (18.34)
   No-cardia 425(62.41)

a, based on a two-sided χ2 test for distributions between gastric cancer and cancer-free controls; b, patient numbers may not add up to 100% of available subjects because of missing clinical data. P<0.05 indicates statistical significance. GC, gastric cancer; ACT, adjuvant chemotherapy; R/M, recurrence/metastasis.

Associations between KCNQ1 and KCNQ1OT1 SNPs and GC risk

The basic data on the three KCNQ1 SNP genotype frequencies (rs6578283, rs231348, and rs760419) and eight KCNQ1OT1 SNP genotype frequencies (rs10832514, rs231361, rs231359, rs7128926, rs231356, rs231354, rs231352, and rs7939976) are shown in Table S1, which contains the position, alleles, minor allele frequency (MAF) distribution, HWE P value, ORs, and 95% CIs of all the candidate SNPs. The MAF values for each SNP in the controls were similar to the values for the Chinese population in the database (0.208 vs. 0.195, 0.115 vs. 0.106, 0.335 vs. 0.332, 0.118 vs. 0.111, 0.214 vs. 0.217, 0.213 vs. 0.219, 0.090 vs. 0.092, 0.217 vs. 0.225, 0.123 vs. 0.133, 0.122 vs. 0.132, and 0.087 vs. 0.089, respectively). The HWE P values of the 11 SNPs were more than 0.05, and none showed a significant departure from the HWE. Using the Pearson χ2 test, we compared the SNP genotype and allele frequencies of KCNQ1 and KCNQ1OT1 between the casegroup and the control group and calculated ORs to evaluate associations with the GC risk. However, there were no statistically significant differences in genotype and allele frequencies between GC cases and controls in the Chinese population (P>0.05, Table S1). To further assess the possible association between the KCNQ1 and KCNQ1OT1 polymorphisms and the risk of GC under different genetic models, we applied logistic regression analysis and assumed four genetic models (codominant, dominant, recessive, and log-additive) with adjustments for age and gender (shown in Table S2). Again, we observed no statistically significant differences between patients and controls (P>0.05, Table S2).

We next performed a stratified analysis according to age, gender, clinical stage and tumor diameter to evaluate the effect of these 11 SNPs on GC risk. Stratified analysis by age revealed significant associations between the rs231348 genotype and the risk of GC, as displayed in Table S3. The rs231348 CT genotype in KCNQ1 was identified to increase the risk of GC in individuals aged ≥55 years using the log-additive model (OR =1.48, CI: 1.01–2.16, P=0.042). No significant associations with GC risk were observed in either females or males (Table S3). Stratified analysis by clinical stage revealed significant associations between the KCNQ1OT1 rs231352 genotype and the risk of GC, as displayed in https://cdn.amegroups.cn/static/public/10.21037atm-20-8052-1.pdf. The rs231352 CC genotype in KCNQ1OT1 was identified to decrease the risk of GC in individuals at stages I–II as opposed to stages III–IV according to the recessive model (OR =0.31, CI: 0.08–1.12, P=0.048). In addition, stratified analysis by tumor diameter revealed a significant association between the KCNQ1OT1 rs7128926 genotype and the risk of GC, as displayed in https://cdn.amegroups.cn/static/public/10.21037atm-20-8052-1.pdf. The rs7128926 AA genotype in KCNQ1OT1 was identified to decrease the risk of GC in individuals with a tumor diameter <5 cm as opposed to ≥5 cm according to the recessive model (P=0.026) (https://cdn.amegroups.cn/static/public/10.21037atm-20-8052-1.pdf).

Recurrence risk evaluation and survival analysis

Recurrent and mortality events were recorded, and the RFS was calculated for the prognosis assessment. Of the 681 patients diagnosed with GC, more than half were classified as the most common stages 0 [26], I [126], and II [316]. Most patients showed a tumor diameter less than 5 cm [380], and during the entire observation period, 377 patients experienced recurrence. To further estimate the correlation between the KCNQ1 and KCNQ1OT1 polymorphisms and the recurrence or metastasis risk and survival analysis of GC, univariate analysis, multivariate analysis, and multiple inheritance models (dominant, recessive, and additive models) were applied to analyze potential associations by a logistic regression analysis adjusted for age and gender. As shown in https://cdn.amegroups.cn/static/public/10.21037atm-20-8052-2.pdf, after adjusting for age and gender, rs7128926 in KCNQ1OT1 decreased the GC recurrence and metastasis risk in both the codominant model (P=0.047) and the recessive model (P=0.026). Moreover, according to the recessive model, the KCNQ1OT1 rs7939976 GG genotype was associated with a decreased recurrence and metastasis risk of GC (P=0.026) compared with the rs7939976 AA/AG genotypes (https://cdn.amegroups.cn/static/public/10.21037atm-20-8052-2.pdf).

The results of the survival analysis in relation to the SNPs are listed in Table 2. Among the 11 SNPs, 2 KCNQ1OT1 SNPs, rs7939976 and rs7128926, were significantly associated with survival. Three genotypes, AA, GA and GG, were detected at the rs7939976 and rs7128926 loci of the KCNQ1OT1 gene. Compared with patients with the GG and GA genotype of the KCNQ1OT1 SNP rs7939976, we found that patients with the AA genotypes had longer OS and RFS after 1 year (Figure 1A,B), and patients carrying the A alleles had a substantially higher median OS compared with patients with no A allele (OR =20.749, CI: 2.68–160.616, P=0.004) (Table 2). Among all the cases, the MST was 57 months for those with the rs7939976 AA genotype (two A alleles), 47.8 months for those with the GA genotype (one A allele), and 4 months for those with the GG genotype (no A allele). This trend was also similar for the MST with RFS, with 32 months for AA, 11.2 months for GA, and 4 months for GG (P<0.01) (Table 2).

Table 2. Genotypes of KCNQ1 and KCNQ1OT1 polymorphisms with clinical outcome of gastric cancer patients.

SNP ID Genotype Total/event OS Total/event RFS
Log-rank P MST HR (95% CI) P Log-rank P MST HR (95% CI) P
rs6578283 AA 421/140 62 0.804 421/179 41 0.503
GA 211/77 0.773 57 0.958 (0.696–1.32) 0.795 211/94 0.986 31 0.880 (0.660–1.174) 0.386
GG 32/9 47.3 1.234 (0.594–2.565) 0.573 32/14 29 1.223 (0.670–2.231) 0.512
Dominant 243/86 0.781 57 0.985 (0.725–1.339) 0.925 243/108 0.87 30 0.918 (0.699–1.207) 0.542
rs231348 CC 520/173 57 0.781 520/221 37 0.621
TC 131/48 0.766 57 1.001 (0.704–1.451) 0.953 131/59 0.343 32 0.996 (0.722–1.374) 0.981
TT 12/5 41.039 1.436 (0.524–3.937) 0.481 12/7 17 1.561 (0.635–3.836) 0.331
Dominant 143/53 0.754 57 1.040 (0.735–1.473) 0.824 143/66 0.675 29 1.032 (0.757–1.406) 0.842
rs760419 AA 304/105 62 0.174 304/131 31 0.302
GA 281/90 0.517 59 0.787 (0.565–1.096) 0.157 281/117 0.609 41 0.845 (0.632–1.128) 0.253
GG 79/31 39 1.165 (0.743–1.825) 0.507 79/39 22 1.127 (0.752–1.687) 0.563
Dominant 360/121 0.88 57 0.866 (0.638–1.176) 0.358 360/156 0.953 37 0.904 (0.690–1.183) 0.462
r231356 TT 406/138 57 0.827 406/172 40 0.358
TA 228/79 0.961 57 1.038 (0.758–1.421) 0.818 228/102 0.864 31 1.063 (0.806–1.403) 0.664
AA 30/9 46.776 1.289 (0.561–2.959) 0.55 30/12 26 1.637 (0.827–3.241) 0.157
Dominant 258/88 0.986 57 1.056 (0.778–1.433) 0.726 258/115 0.613 31 1.102 (0.843–1.441) 0.478
rs231354 CC 507/172 57 0.917 507/213 40 0.556
TC 150/52 0.961 57 1.043 (0.740–1.470) 0.812 150/71 0.636 29 1.150 (0.854–1.550) 0.356
TT 7/2 47.7 0.714 (0.099–5.167) 0.739 7/3 17 0.582 (0.081–4.193) 0.591
Dominant 157/54 0.925 57 1.032 (0.734–1.450) 0.858 157/74 0.342 29 1.132 (0.842–1.521) 0.413
rs231352 CC 509/172 57 0.914 509/214 40 0.545
TC 148/52 0.936 57 1.045 (0.741–1.473) 0.803 148/70 0.634 26 1.154 (0.857–1.555) 0.346
TT 7/2 47.7 0.714 (0.099–5.169) 0.739 7/3 17 0.582 (0.081–4.195) 0.591
Dominant 155/54 0.826 57 1.034 (0.736–1.453) 0.848 155/73 0.34 26 1.135 (0.844–1.526) 0.401
rs7939976 AA 550/193 57 0.014 550/243 32 0.010
GA 112/31 0.048 47.832 0.929 (0.595–1.449) 0.745 112/42 <0.001 11.258 1.030 (0.704–1.508) 0.878
GG 2/2 4 20.749 (2.680–160.616) 0.004 2/2 2 23.238 (3.026–178.479) 0.002
Dominant 114/33 0.263 47.06 0.972 (0.628–1.504) 0.897 114/44 0.322 40.59 1.063 (0.730–1.548) 0.750
rs10832514 AA 517/174 57 0.155 517/219 37 0.081
GA 139/49 0.809 41.823 1.359 (0.955–1.933) 0.088 139/64 0.812 29 1.346 (0.984–1.840) 0.063
GG 8/3 36.964 1.821 (0.574–5.783) 0.309 8/4 20 2.041 (0.750–5.558) 0.163
Dominant 147/52 0.517 41.778 1.383 (0.982–1.949) 0.064 147/68 0.522 29 1.379 (1.017–1.870) 0.039
rs231361 AA 409/142 57 0.975 409/179 35 0.608
GA 225/76 0.832 57 1.031 (0.752–1.413) 0.849 225/96 0.981 37 1.038 (0.787–1.371) 0.791
GG 29/8 48.286 1.066 (0.432–2.633) 0.89 29/12 38.76 1.437 (0.700–2.952) 0.323
Dominant 254/84 0.768 44.71 1.034 (0.761–1.405) 0.832 254/108 0.856 37 1.066 (0.814–1.395) 0.642
rs231359 AA 410/143 57 0.943 410/176 40 0.617
CA 224/75 0.788 57 0.950 (0.692–1.303) 0.749 224/99 0.986 31 1.029 (0.780–1.357) 0.840
CC 29/8 48.286 1.038 (0.420–2.562) 0.936 29/12 38.76 1.433 (0.698–2.945) 0.327
Dominant 253/83 0.611 45.069 0.956 (0.703–1.300) 0.775 253/111 0.865 31 1.056 (0.808–1.381) 0.690
rs7128926 AA 547/192 57 0.012 547/242 32 0.010
GA 115/32 0.05 47.667 0.863 (0.553–1.346) 0.515 115/43 <0.001 11.293 0.946 (0.647–1.385) 0.777
GG 2/2 4 20.585 (2.659–159.37) 0.004 2/2 2 22.981 (2.992–176.541) 0.003
Dominant 117/34 0.277 46.924 0.902 (0.583–1.395) 0.642 117/45 0.315 40.64 0.976 (0.670–1.421) 0.899

KCNQ1, potassium voltage-gated channel KQT-like subfamily member 1; OS, overall survival; RFS, recurrence-free survival; MST, median survival time;

Figure 1.

Figure 1

Kaplan-Meier curves of OS and RFS in patients with different KCNQ1OT1 rs7939976 and rs7128926 genotypes. (A,B) Median OS and RFS were longer in patients with KCNQ1OT1 rs7939976 AA genotypes than in those with GA + GG genotypes after 1 year (log-rank P=0.173 and 0.201, respectively). (C,D) Median OS and RFS were longer in patients with KCNQ1OT1 rs7128926 AA genotypes than in those with GG and GA genotypes after 1 year (log-rank P=0.185 and 0.197, respectively). OS, overall survival; RFS, recurrence-free survival. KCNQ1, potassium voltage-gated channel KQT-like subfamily member 1; OS, overall survival; RFS, recurrence-free survival.

Meanwhile, patients with the AA genotype of the KCNQ1OT1 rs7128926 SNP had longer OS and RFS after 1 year compared with patients with the GG and GA genotypes (Figure 1C,D), although there was no statistically significant difference (log-rank P=0.185 and 0.197, respectively). Meanwhile, as shown in Table 2, patients carrying the A allele of rs7128926 had a substantially higher OS (OR =0.863, CI: 0.553–1.346, P=0.012) and RFS (OR =0.946, CI: 0.647–1.385, P=0.01) compared with patients without the A allele. Among all the cases, the median survival time (MST) was 57 months for those with the rs7128926 AA genotype (two A alleles), 47 months for those with the GA genotype (one A allele), and only 4 months for those with the GG genotype (no A allele). This trend was similar for the MST with RFS, with 32 months for AA, 11.2 months for GA, and 2 months for GG (P<0.01). The other six SNP loci (rs10832514, rs231361, rs231359, rs231356, rs231354, and rs231352) of KCNQ1OT1 and the three SNP loci (rs6578283, rs231348 and rs760419) of KCNQ1 showed no significant correlation with OS and RFS in patients with GC (Table 2).

To further investigate the relationship between the KCNQ1OT1 rs7128926 and rs7939976 SNPs and survival time in GC patients, we carried out a stratified analysis of the correlation between the two SNP loci in patients with GC, and the effect of age, gender, BMI, Helicobacter pylori infection status, clinical stage, tumor diameter, and chemotherapy status on OS and RFS were evaluated using a codominant model (Tables 3,4). The analysis revealed that MST and OS were the lowest in patients with the GG genotype at the KCNQ1OT1 rs7128926 locus, especially in females over 60 years of age, followed by H. pylori infection, BMI >24, tumor in the non-cardia region with a diameter greater than 5 cm, clinical stage II, and postoperative adjuvant chemotherapy. This trend was similar for the MST and RFS among patients with the GG genotype at the KCNQ1OT1 rs7939976 locus (Table 3). We also found that patients carrying the GG genotype at the KCNQ1OT1 rs7939976 locus had a poorer MST with OS and RFS (Table 4).

Table 3. Stratified analysis of the KCNQ1OT1 rs7128926 polymorphism with gastric cancer OS and RFS.

Variables Genotype OS RFS
Total/event MST HR (95% CI) P Total/event MST HR (95% CI) P
Age1
   ≥55 AA 244/89 56 1 0.033 244/109 26 1 0.012
GA 43/13 46.124 1.182 (0.622–2.243) 0.61 43/17 40.207 1.282 (0.731–2.248) 0.386
GG 2/2 4 16.444 (1.976–136.829) 0.01 2/2 2 23.626 (2.808–198.769) 0.004
   <55 AA 303/103 57 1 303/133 38 1
GA 72/19 46.867 0.759 (0.407–1.416) 0.386 72/26 40.437 0.798 (0.473–1.3484) 0.399
GG NA NA
Gender3
   Male AA 423/145 57 1 423/182 34 1
GA 88/22 49.604 0.760 (0.448–1.290) 0.309 88/30 43.837 0.937 (0.597–1.470) 0.776
GG 1/1 32 1/1 5
   Female AA 124/47 49 1 0.029 124/60 28 1 0.025
GA 27/10 57 1.111 (0.483–2.555) 0.805 27/13 18 0.912 (0.429–1.941) 0.812
GG 1/1 4 20.590 (2.226–190.458) 0.008 1/1 2 20.027 (2.225–180.28) 0.008
BMIa
   <24 AA 142/42 44.062 1 142/55 42 1 0.18
GA 21/4 53.505 0.664 (0.233–1.891) 0.443 21/5 49.591 0.493 (0.175–1.387) 0.18
GG NA NA
   ≥24 AA 338/114 45.062 1 0.026 338/140 50 1 0.012
GA 77/20 46.393 0.926 (0.566–1.515) 0.761 77/29 37 1.082 (0.715–1.638) 0.709
GG 1/1 4 16.775 (2.129–132.171) 0.007 1/1 2 22.835 (2.891–180.37) 0.003
H. pylori infectiona
   Yes AA 331/108 46.099 1 0.028 331/128 41.846 1 0.017
GA 60/17 47.416 0.946 (0.556–1.608) 0.837 60/20 44.019 0.963 (0.593–1.565) 0.879
GG 1/1 4 16.661 (2.099–132.243) 0.008 1/1 2 20.207 (2.547–160.309) 0.004
   No AA 149/48 35.121 1 0.329 149/67 25 1 0.706
GA 38/7 36.069 0.661 (0.288–1.517) 0.329 38/14 37 0.886 (0.471–1.665) 0.706
GG NA NA
GA 70/18 47.349 0.796 (0.427–1.486) 0.457 70/25 40.684 0.857 (0.507–1.448) 0.564
GG NA NA
ACTa
   No AA 190/51 62 1 0.145 190/55 45.538 1 0.092
GA 43/7 50.692 0.520 (0.216–1.252) 0.145 43/8 49.297 0.495 (0.218–1.122) 0.092
GG NA NA
   Yes AA 357/141 48 1 <0.001 357/187 24 1 0.002
GA 71/25 57 1.184 (0.702–1.997) 0.527 71/35 26 1.179 (0.763–1.822) 0.458
GG 1/1 4 21.275 (2.295–197.256) 0.007 1/1 2 20.576 (2.282–185.538) 0.007
Tumor sitea
   Cardia AA 106/44 39 1 0.696 106/54 18 1 0.56
GA 19/6 44.485 0.836 (0.340–2.055) 0.696 19/8 37 0.794 (0.366–1.722) 0.56
GG NA NA
   Non-cardia AA 348/103 47.599 1 0.005 348/130 42.709 1 0.005
GA 76/16 50.944 0.879 (0.514–1.504) 0.638 76/25 43.566 1.086 (0.695–1.697) 0.716
GG 1/1 4 32.242 (3.866–268.872) 0.001 1/1 2 30.802 (3.815–248.709) 0.001
Tumor diametera
   <5 AA 309/82 48.422 1 0.307 309/107 43.251 1 0.617
GA 68/11 54.953 0.701 (0.354–1.386) 0.307 68/21 46.036 1.138 (0.686–1.889) 0.617
GG NA NA
   ≥5 AA 227/106 33 1 0.019 227/131 18 1 0.005
GA 44/20 38 1.005 (0.551–1.833) 0.987 44/20 31 0.709 (0.383–1.311) 0.273
GG 2/2 4 20.254 (2.481–165.381) 0.005 2/2 2 26.207 (3.200–214.648) 0.002
Clinical stagea
   Early AA 110/11 1 0.98 110/14 57.535 1 0.416
GA 30/0 0 0.98 30/1 62.87 0.421 (0.052–3.383) 0.416
GG NA NA
   Middle AA 384/143 48 1 0.036 384/184 25 1 0.035
GA 78/27 57 0.882 (0.538–1.446) 0.618 78/38 26 0.920 (0.609–1.390) 0.692
GG 2/2 4 14.270 (1.810–112.511) 0.012 2/2 2 14.416 (1.859–111.822) 0.011
   Late AA 49/36 13 1 0.269 49/41 7 1 0.336
GA 6/5 15 0.530 (0.172–1.635) 0.269 6/4 6 0.531 (0.146–1.930) 0.336
GG NA NA

1, adjusted by gender; 3, adjusted by age. a, patient numbers may not add up to 100% of available subjects because of missing clinical data. KCNQ1, potassium voltage-gated channel KQT-like subfamily member 1; OS, overall survival; RFS, recurrence-free survival; MST, median survival time; ACT, adjuvant chemotherapy; R/M, recurrence/metastasis.

Table 4. Stratified analysis of the KCNQ1OT1 rs7939976 polymorphism with gastric cancer OS and RFS.

Variables Genotype Total/event OS Total/event RFS
MST HR (95% CI) P MST HR (95% CI) P2
Age1
   ≥55 AA 245/89 56 1 0.031 245/109 26 1 0.009
GA 42/13 45.762 1.221 (0.643–2.32) 0.542 42/17 37 1.378 (0.784–2.424) 0.265
GG 2/2 4 16.54 (1.988–137.641) 0.009 2/2 2 24.131 (2.866–203.164) 0.003
   <55 AA 305/104 57 1 305/134 38 1
GA 70/18 47.349 0.796 (0.427–1.486) 0.457 70/25 40.684 0.857 (0.507–1.448) 0.564
GG NA NA
Gender3
   Male AA 424/145 57 424/182 34
GA 87/22 49.503 0.800 (0.470–1.360) 0.41 87/30 43.725 1.018 (0.646–1.604) 0.938
GG 1/1 32 1/1 5
   Female AA 126/48 49 1 0.025 126/61 28 1 0.026
GA 25/9 57 1.272 (0.552–2.929) 0.572 25/12 18 1.025 (0.482–2.179) 0.949
GG 1/1 4 21.275 (2.295–197.256) 0.007 1/1 2 20.576 (2.282–185.538) 0.007
BMIa
   <24 AA 140/42 43.675 1 140/55 42 1
GA 23/4 54.558 0.594 (0.209–1.687) 0.328 23/5 51.132 0.439 (0.156–1.229) 0.117
GG NA NA 0.439 (0.156–1.229) 0.117
   ≥24 AA 343/115 45.225 1 0.027 343/141 50 1 0.008
GA 72/19 45.961 1.043 (0.638–1.706) 0.866 72/28 37 1.239 (0.818–1.876) 0.313
GG 1/1 4 16.941 (2.151–133.427) 0.007 1/1 2 23.274 (2.948–183.783) 0.003
H. pylori infectiona
   Yes AA 333/109 46.116 1 0.028 333/129 41.865 1 0.017
GA 58/16 47.68 1.028 (0.605–1.747) 0.918 58/19 43.953 1.026 (0.632–1.666) 0.916
GG 1/1 4 16.764 (2.113–133.028) 0.008 1/1 2 20.401 (2.572) 0.004
   No AA 150/448 35.046 1 0.382 150/67 25 1
GA 37/7 36.294 0.689 (0.299–1.589) 0.382 37/14 37 0.974 (0.512–1.850) 0.935
GG NA NA
ACTa
   No AA 192/51 62 1 0.233 192/55 45.801 1 0.144
GA 41/7 50.023 0.587 (0.244–1.410) 0.233 41/8 48.662 0.544 (0.240–1.230) 0.144
GG NA NA
   Yes AA 358/142 48 1 <0.001 358/188 23 1 0.001
GA 70/24 57 1.268 (0.750–2.143) 0.375 70/34 29 1.296 (0.837–2.007) 0.244
GG 2/2 4 89.316 (9.807–813.41) <0.001 2/2 2 42.558 (5.243–345.483) <0.001
Tumor sitea
   Cardia AA 105/44 35 1 0.383 105/54 18 1 0.331
GA 20/6 45.681 0.656 (0.254–1.693) 0.383 20/8 37 0.667 (0.295–1.510) 0.331
GG NA NA
   Non-cardia AA 351/103 47.847 1 0.006 351/130 42.963 1 0.004
GA 73/16 50 0.993 (0.581–1.697) 0.98 73/25 42.314 1.233 (0.789–1.924) 0.357
GG 1/1 4 32.587 (3.909–271.665) 0.001 1/1 2 31.240 (3.870–252.142) 0.001
Tumor diametera
   <5 AA 308/82 48.354 1 0.261 308/107 43.174 1 0.692
GA 69/11 55.114 0.675 (0.341–1.338) 0.261 69/21 46.241 1.108 (0.666–1.844) 0.692
GG NA NA
   ≥5 AA 230/106 33 1 0.017 230/131 18 1 0.008
GA 41/20 38 1.159 (0.634–2.119) 0.631 41/20 23 0.852 (0.458–1.585) 0.613
GG 2/2 4 20.426 (2.503–166.657) 0.005 2/2 2 26.846 (3.278–219.865) 0.002
Clinical stagea
   Early AA 109/11 1 0.976 109/14 57.497 1 0.378
GA 31/0 0 0.976 31/1 62.958 0.393 (0.049–3.146) 0.378
GG NA NA
   Middle AA 387/143 49 1 0.04 387/184 25 1 0.038
GA 75/27 57 0.959 (0.584–1.576) 0.87 75/38 25 0.999 (0.661–1.511) 0.997
GG 2/2 4 14.354 (1.821–113.143) 0.011 2/2 2 14.494 (1.869–112.392) 0.011
   Late AA 50/37 13 1 0.269 50/42 7 1 0.336
GA 5/4 17 0.530 (0.172–1.635) 0.269 5/3 4 0.531 (0.146–1.930) 0.336
GG NA NA

1, adjusted by gender; 3, adjusted by age. a, patient numbers may not add up to 100% of available subjects because of missing clinical data. KCNQ1, potassium voltage-gated channel KQT-like subfamily member 1; OS, overall survival; RFS, recurrence-free survival; MST, median survival time; ACT, adjuvant chemotherapy; R/M, recurrence/metastasis.

Discussion

We collected data from 681 GC patients and 756 normal controls, detected 3 functional SNPs in the KCNQ1 gene and 8 functional SNPs in the KCNQ1OT1 gene, and assessed their associations with GC risk and survival in a Chinese population. There were no significant differences to the genotype and allele frequencies between the GC cases and risk in the healthy population; however, in the stratification analyses, the log-additive model indicated that the CT genotype at the KCNQ1 rs231348 locus was significantly associated with a decreased risk of GC in individuals aged ≥55 years. The CC genotype at the KCNQ1OT1 rs231352 locus also decreased the risk of GC in individuals at stages I–II as opposed to stages III–IV. In addition, a stratified analysis by tumor diameter revealed significant associations between the KCNQ1OT1 rs7128926 AA genotype and a decreased risk of GC for individuals with a tumor diameter <5 cm.

Consistent with our research, another recent study showed that KCNQ1 mutant mice are a powerful new tool for investigating the connection between acid balance, Helicobacter infection, and mucin disruption in the progression to GC, and that KCNQ1 mutations predispose mutant mice to metaplastic and pre-neoplastic changes in the stomach (27). In our study, KCNQ1 rs231348 and KCNQ1OT1 rs231352 independently predicted the risk of GC susceptibility under certain patient conditions, including the individual’s age, tumor stage, and tumor diameter. Simultaneously, polymorphism of the rs7128926 and rs7939976 loci of the KCNQ1OT1 gene independently predicted the OS and RFS of GC patients. One possible mechanism for this was that these genes for GC act as multiple DNA transposon-based forward genetic screens in patients (28). Than et al. (17) found that KCNQ1 was a potential tumor suppressor gene, and low expression of KCNQ1 was significantly associated with poor OS in patients with CRC. However, the relationship between KCNQ1 rs231348 and GC has not been reported previously, and this study provides the first report of an association between the KCNQ1 rs231348 polymorphism and the risk of GC susceptibility.

We also identified associations between the KCNQ1OT1 gene polymorphisms, rs7128926 and rs7939976, and OS and RFS, even after adjustment for other clinical factors. These represent novel associations that have not been identified previously. Because the transcription of the KCNQ1OT1 gene overlaps with most of the KCNQ1 transcription unit on the anti-strand, the transcription of KCNQ1 and other non-overlapping genes can be affected by transcriptional interference. In the evaluation of genotype polymorphism and survival analysis, we discovered that as the number of A alleles of the rs7128926 and rs7939976 loci of the KCNQ1OT1 gene increased, the MST with OS and RFS of GC cases showed an increasing trend, and that the AA plus GA genotypes presented a significant survival advantage over the GG genotypes. A further stratified investigation also showed that the AA/GA genotypes of the rs7128926 and rs7939976 polymorphisms improved survival in those with the following characteristics: age over 55, the presence of H. pylori infection, BMI >24, tumor in the non-cardia region with a diameter greater than 5 cm, clinical stage II, and postoperative adjuvant chemotherapy.

The KCNQ1 gene plays an important role in encoding the Q1 subfamily of the voltage-dependent potassium channel, and includes one paternally expressed lncRNA, KCNQ1OT1. The functions of ion channels influence a variety of cellular processes, many of which overlap heavily with these hallmarks of cancer (29). For these reasons, cancer has been described as a channelopathy (30). K+ channels play a major role in the maintenance of plasma membrane (PM) potential (29). With 77 genes coding for K+ channels, they are the largest and most diverse group of ion channels in the human genome. There is increasing evidence that K+ channels are implicated in a variety of cellular and tissue functions, including cell proliferation, differentiation, invasion, migration, and metastasis. KCNQ1 downregulation has also been observed in CRC, where KCNQ1 expression is associated with improved RFS at stages II–IV of the disease (29). Meanwhile, in agreement with our findings, previous studies found a significant association between a common KCNQ1OT1 promoter polymorphism (rs11023840) and the risk of symptomatic prolonged QT interval (31). The Previous study also examined the expression levels of KCNQ1OT1, which showed no significant alterations in early GC tissues compared with normal adjacent tissues by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) (32).

The limitations of our study included its relatively small sample size and retrospective nature. Furthermore, the mechanisms whereby the identified SNPs influence the risk of GC susceptibility and GC survival were not elucidated. Further prospective studies with larger sample sizes are needed to clarify the correlations between the KCNQ1 and KCNQ1OT1 genes and GC. More basic studies using GC cells are also needed to identify the molecular mechanisms responsible for the effects of the KCNQ1 and KCNQ1OT1 genes on the susceptibility, risk, and survival of GC patients.

Conclusions

Our study showed that polymorphisms in the KCNQ1 and KCNQ1OT1 genes might have predictive or prognostic value in determining the susceptibility, risk, and survival of Chinese Han patients with GC. However, these results were only demonstrated to be good predictors in a specific population as a result of the heterogeneity of the tumor population and the relatively small sample size included in this study. Furthermore, the association between genetic factors and environmental factors was not fully investigated because of a lack of data regarding traits such as drinking and dietary habits. Further results are expected to clarify the influence and specific mechanisms by which KCNQ1 and KCNQ1OT1 gene polymorphisms affect the susceptibility, risk, and/or survival of GC patients.

Supplementary

The article’s supplementary files as

atm-09-02-156-rc.pdf (100.4KB, pdf)
DOI: 10.21037/atm-20-8052
atm-09-02-156-dss.pdf (65.7KB, pdf)
DOI: 10.21037/atm-20-8052
atm-09-02-156-coif.pdf (147.1KB, pdf)
DOI: 10.21037/atm-20-8052
DOI: 10.21037/atm-20-8052

Acknowledgments

The authors appreciate the contributions of the patients who participated in this study. We thank Catherine Perfect from Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac) for editing the English text of a draft of this manuscript.

Funding: None.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The authors state that they have obtained appropriate institutional review board approval (No. K201009-03) and have followed the principles outlined in the Declaration of Helsinki (as revised in 2013) for all human experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.

Footnotes

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at http://dx.doi.org/10.21037/atm-20-8052

Data Sharing Statement: Available at http://dx.doi.org/10.21037/atm-20-8052

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm-20-8052). The authors have no conflicts of interest to declare.

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Associated Data

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Supplementary Materials

The article’s supplementary files as

atm-09-02-156-rc.pdf (100.4KB, pdf)
DOI: 10.21037/atm-20-8052
atm-09-02-156-dss.pdf (65.7KB, pdf)
DOI: 10.21037/atm-20-8052
atm-09-02-156-coif.pdf (147.1KB, pdf)
DOI: 10.21037/atm-20-8052
DOI: 10.21037/atm-20-8052

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