Single Nucleotide Polymorphisms of EXOC1, BCL2, CCAT2, and CARD8 Genes and Susceptibility to Cervical Cancer in the Northern Chinese Han Population

Cervical cancer (CC) is one of the main malignant tumors that threaten the health and lives of women around the world, and its morbidity and mortality rate ranks fourth. At present, most studies on the genetic background of CC focus on genetic polymorphisms. Single nucleotide polymorphisms (SNPs) are considered clinically as potential diagnostic and therapeutic biomarkers for a variety of tumors. Therefore, we aimed to explore the association between SNPs in different genes (EXOC1 gene, BCL2 gene, CCAT2 gene and CARD8 gene) and susceptibility to CC. This study is a case-control study based on women in northern Chinese, which included 492 women with CC and 510 healthy women. This study used multiplex PCR combined with next-generation sequencing to genotype the selected SNPs (rs13117307(C/T) in EXOC1 gene, rs2279115(C/A) in BCL2 gene, rs6983267(G/T) in CCAT2 gene and rs7248320(G/A) in CARD8 gene). The results of the study showed that there was no significant association between the four SNPs and the susceptibility to CC. However, in further stratified analysis, we found that rs13117307 and rs2279115 were significantly related to squamous cell carcinoma antigen (SCC-Ag) levels in women with CC, and rs6983267 was significantly related to the menopausal status of women with CC. Specifically, alleles T of rs13117307 and genoytpe AA of rs2279115 when SCC-Ag is greater than 1.5 ng/ml increase the risk of CC. The genotype TG/TG+TT of rs6983267 increases the risk of CC in premenopausal women. In conclusion, although we did not directly find a significant correlation between four SNPs, rs13117307 in EXOC1 gene,rs2279115 in BCL2 gene, rs6983267 in CCAT2 gene and rs7248320 in CARD8 gene, and CC susceptibility, we found that SNPs rs13117307, rs2279115, rs6983267 were associated with the clinical characteristics of several patients' CC patients. Therefore, this study provides us with new ideas for understanding CC and the diagnosis and treatment of CC in the future.

Introduction

Cervical cancer (CC) is one of the common malignant tumors in gynecology. It has a high morbidity and mortality rate worldwide, which seriously threatens the life and health of women. There are about 604000 new CC patients every year, of which 75-80% occur in developing countries (1), which brings a heavy economic burden to society and families (2). With the popularization of cervical cytology screening, the use of HPV vaccines and the improvement of protection awareness, the morbidity and mortality rate of CC has decreased, but CC is still a serious public health problem (3, 4). Early effective prevention and diagnosis are particularly important for the treatment of CC.

CC usually occurs at the junction of cervical squamous column, from atypical hyperplasia of cervical epithelium to intraepithelial carcinoma in situ, to invasive carcinoma, and finally to metastatic carcinoma. This process may take several years or more than ten years. Current research shows that viral infection, premature or disordered sexual life, early pregnancy, prolificacy and eating habits are all related to the increased risk of CC. Among them, HPV infection is recognized as a high risk factor for CC (5, 6). Studies have confirmed that the incidence of female first-degree relatives suffering from CC is higher than that of the general population, suggesting that genetic factors play an important role in the pathogenesis of CC (7–9). This fact encourages some research groups to look for susceptibility genes for CC. SNP is the most common genetic variation in human genes and is considered to be a new generation of genetic markers. Clinically, SNPs can be used as potential biomarkers for diagnosis and treatment of various tumors (10, 11). Tumor necrosis factor -α Promoter gene (12), polymerase II polypeptide E (POLR2E) (13), ganglioside biosynthesis gene (6), methylenetetrahydrofolate reductase (MTHFR) gene (14) polymorphisms were associated with CC.

The exocyst complex component 1 (EXCO1) protein encoded by the EXCO1 gene is one of the components of the exocyst complex (EXCO1-EXCO8). The complex promotes the regulation of cellular membrane exocytosis, secretion of the cell membrane and participate in cellular migration and secretion, and vesicle transport (15–18). Recently, some evidence suggests that the exocyst complex has an important role in the occurrence and development of various cancers (19). Apoptosis is an important mechanism for maintaining cell/tissue balance. Abnormal cell apoptosis is one of the important pathological basis of tumor formation, and it directly participates in the occurrence and development of tumors. The anti-apoptotic B cell lymphoma 2 (BCL2) gene is located on chromosome 18q21.3, encoding BCL2 protein, which is a typical apoptosis regulator (20, 21). BCL2 is found to be highly expressed in a variety of tumors, such as prostate cancer, non-small cell lung cancer, chronic lymphocytic leukemia, and diffuse large B-cell lymphoma (22–26). Caspase recruitment domain family member 8 (CARD8), also known as TUCAN, is a member of the amino acid protease recruitment domain family, which affects protein-protein interaction, apoptosis, caspase-1 activation, IL-1 and IL-8 activation and activation kappa-B (NFkB) (27, 28). NFkB is a key regulator of gene transcription and tumorigenesis. Colon Cancer-Associated Transcript 2 (CCAT2) long non-coding RNA is a transcript containing rs6983267 SNP (29), which can up-regulate MYC through TCF7L2-mediated transcription. Previous studies have shown that the rs6983267 SNP located in the MYC enhancer region is related to the susceptibility of various cancers, including prostate cancer, colorectal adenoma and cancer, thyroid cancer, endometrial carcinoma, and ovarian cancer (30–34).

However, report on the relationship between EXOC1, BCL2, CARD8, CCAT2 gene and CC is rarely. Therefore, we aimed to explore the possible effect of EXOC1, BCL2, CARD8, CCAT2 gene polymorphisms on the development of CC in the northern Chinese population.

Material and Methods

Study Subjects

This case-control study was recruited 492 CC patients and 510 healthy controls, which is carried out in Department of Gynecology, the Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China. The cases are all patients with primary CC without any treatment, and their histopathology has been confirmed by the Pathology Department of the Second Affiliated Hospital of Harbin Medical University. The exclusion criteria for the patients are: 1) cervical benign lesions; 2) cervical benign tumor; 3) other cervical malignant tumors or combined with other tumors; 4) cervical cancer patients with a history of radiotherapy and chemotherapy before surgery. The entry criteria of the healthy control group: 1) TCT negative; 2) No history of tumor; 3) Choose the same hospital at the same time. Exclusion criteria for healthy control group: 1) history of gynecological diseases and gynecological surgery; 2) immunocompromised and immune diseases; 3) skin or genital warts; 4) history of other diseases and family tumors. All participants are biologically unrelated han Chinese female living in northern China, and they are all non-probabilistic continuous samples.

All participants signed informed consent, which were approved by the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University.

Selection of SNPs

Based on previous studies and combined with the characteristics of East Asian population in the dbSNP database, we selected 4 SNPs: rs13117307(C/T) in EXOC1 gene, rs2279115(C/A) in BCL2 gene, rs6983267(G/T) in CCAT2 gene and rs7248320(G/A) in CARD8 gene. The minor allele frequency of the four SNPs is shown as follows: rs13117307 P_T = 0.1042; rs2279115 P_A = 0.43; rs6983267 P_T = 0.6121; rs7248320 P_A = 0.6587. Of the SNPs, rs13117307 and rs6983267 was located in the intron region, rs2279115 was located in promoter region, and rs7248320 was located in the 2kb upstream.

Extraction of DNA

When all subjects were admitted to the hospital, peripheral venous blood was collected, placed in a 2% EDTA-Na2 anticoagulation tube, and refrigerated at -80°C for DNA extraction. Genomic DNA of all subjects was extracted in strict accordance with the standard steps of the TIANamp Genomic DNA Kit (Tiangen Biotech, China). The four SNPs of EXOC1, BCL2, CCAT2 and CARD8 gene were genotyped by Shanghai BioWing Applied Biotechnology Company (http://www.biowing.com.cn) using the multiplex PCR method combined with next-generation sequencing methods. Primer 3 online software (Version 0.4.0, http://frodo.wi.mit.edu/) was used to design amplification primers for the four SNPs. The amplification primers are as follows: for rs13117307 sense primer ‘ACAGGTTAAAAGGTAGTTTTGTAG’ and anti-sense primer ‘AAATTAGTGTGTCATCCTTGCAC’; for rs2279115 sense primer ‘CCTTCATTTATCCAGCAGCTTTTC’ and anti-sense primer ‘CAGAAGTCCTGTGATGTTTTCC’; rs6983267 sense primer ‘AAGAGGTGTAGCCAGAGTTAATAC’ and anti-sense primer ‘CTGTATACACAGCCCAGTCTAAG’; rs7248320 sense primer ‘CGTGAGAAAACATCAAAGAAATCC’ and anti-sense primer ‘TGCAGACCTTATTTGAATTTTGTC’. The mixture of PCR products were purified by TIANgel Midi Purification Kit (Tiangen Biotech, China). The purified PCR products were then paired-end sequenced by Illumina HiSeq XTen platform according to the manufacturer’s instructions. The readings were aligned to the human reference genome reference using Burrows - Wheeler Aligner (BWA, v0.7.12) , and Samtools (v0.1.19) (35) was used for SNP calling and genotyping. Seventy-three samples were randomly selected for blind DNA replication to control the quality of genotyping.

Statistical Analysis

Genotype distribution and allele frequencies were compared between groups using the X² test of independence with a 2 × 2 contingency. The SHEsis software (http://analysis.bio-x.cn/myAnalysis.php) (36, 37) was used to test the haplotype analysis between controls and CC group. The lowest frequency threshold for haplotype was 0.03. Under the appropriate conditions, the odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated and used as a measure of the association between the SNPs genotype and the phenotype of the disease. P < 0.05 was considered statistically significant. Multivariable logistic regression analysis (SPSS V21.0 for Windows) was used to assess the association of allele and genotype of SNPs with CC after adjustment for age, height and weight. Multiple comparisons were counteracted by using the Bonferroni correction to adjust the statistical significance level for possible statistical and clinical confounders.

Results

SNP Genotype and Quality

Linkage disequilibrium among the SNPs was tested using SHEsis software. All SNPs were found to be in Hardy - Weinberg equilibrium in controls (p > 0.05, Table 1). The genotype calling rate in quality control samples were 98.5%, suggesting the reliability of subsequent studies.

TABLE 1

Table 1 Hardy-Weinberg equilibrium test results of target SNPs in controls.

Clinical Characteristics of the Study Population

The average age of CC patients was 49.245 ± 9.412 years, and the average age of healthy controls was 39.490 ± 8.227 years. There is a significant difference in age between CC patients and healthy controls (p < 0.001). The distribution of clinical features of CC patients are shown in Table 2.

TABLE 2

Table 2 The distribution of clinical features of CC patients and controls.

SNPs and CC Risk

The frequencies of genotypes and alleles in gene between CC patients and healthy controls were demonstrated in Table 3. There was no statistically significant difference in genotype and allele frequencies between CC patients and controls. After using logistic regression analysis to adjusted age, height and weight factors, there was no association between CC patients and control (p > 0.05, all). Similarly, no SNPs were found to be associated with CC risk after Bonferroni correction (p > 0.05, all)

TABLE 3

Table 3 The frequencies distribution of genotypes and alleles of four SNPs in CC patients and healthy controls.

SNPs and CC-Related Risk Factors

For SNP rs13117307, we found that the allele C/T of patients with CC is significantly correlated with squamous cell carcinoma antigen (SCC-Ag), that is, women with CC with allele T have higher risk when SCC-Ag is greater than 1.5ng/ml (p = 0.029). But after adjusting for factors such as age, height, and weight, the correlation disappeared (p_adj = 0.159). Moreover, when SCC-Ag is greater than 1.5 ng/ml, the significant correlation between rs2279115 and CC is observed (CC vs. AA: p = 0.025). But after adjusting for factors such as age, height, and weight, the correlation disappeared (p_adj = 0.27). The genotype TG/TG+TT of rs6983267 can increase the risk of CC in premenopausal women (GG vs. TG: p_adj = 0.003, GG vs. TG+TT: p_{adj =} 0.023). After Bonferroni correction, compared with CC patients carrying the GG genotype, there was an association between CC women carrying the TG genotype and SNP rs6983267 (Bonferroni-corrected p = 0.009); however, the correlation did not exist in the comparative analysis of GG and TG+TT(Bonferroni-corrected p = 0.069). However, SNP rs7248320 was not significantly different from CC - related risk factors (Table 4).

TABLE 4

Table 4 Genetypic association between four SNPs (rs13117307, rs2279115, rs6983267 and rs7248320) and CC-related risk factors.

Haplotype Analysis

To further investigate the relationship between CC and haplotype distributions of EXOC1, BCL2, CCAT2 and CARD8 gene, we conducted haplotype analysis. However, there were no significant differences observed controls and patient groups (p > 0.05, data not shown).

Discussion

CC is the fourth most common cancer in the world and the leading cause of cancer deaths in women worldwide (1). Persistent infection of carcinogenic human papilloma virus (HPV) and chronic inflammation are currently more recognized causes of CC. However, studies have shown that only a small percentage of women infected with HPV will eventually develop CC (38). Therefore, the development of CC is affected by many factors, among which genetic susceptibility cannot be ignored. Gene polymorphism is the simultaneous and frequent presence of two or more discontinuous variants or genotypes or alleles in a biological population, including DNA fragment length polymorphism, DNA repetitive sequence polymorphism and SNP. SNP is characterized by the most common, high density, representativeness and genetic stability. This study was a hospital-based case-control study. We observed the distribution of the genotypes, alleles and haplotypes of EXOC1, BCL2, CCAT2 and CARD8 gene in CC patients and healthy controls.

Multiple evidences indicate that CD8+ T cell-mediated immune response is very important in HPV infection and virus-related neoplasia (39, 40). EXCO1 protein is one of the components of the exocyst complex. The binding of the exocyst complex and NEF protein may play an important role in down regulating MHC-I coding genes and regulating T cell signaling pathways (41–43). In addition, the fusion of NEF mutation with HPV-16 type protein E7 induced an anti-E7 CD8+ cytotoxic T lymphocyte response, which is related to the protection of HPV-related tumors (44). The disruption of the balance between exocyst complexes and T cell signaling pathways may be an important reason for the progression of CC (45). In this study, we did not find that the EXOC1 gene rs13117307 SNP is associated with CC susceptibility. In the stratified study, we found that alleles T of rs13117307 when SCC-Ag is greater than 1.5 ng/ml will increase the risk of CC. However after adjusting for factors such as age, height, and weight, the correlation disappeared. Rs13117307 SNP was not associated with CC age, menarche age, menopausal status, and tumor size. A genome-wide correlation study based on the Chinese population by Shi et al. showed that the rs13117307 SNP located in the EXOC1 gene is significantly associated with cervical cancer susceptibility (45). The study by Sebastian Łaźniak et al. confirmed that the rs13117307 SNP variant may up-regulate EXCO1 transcription and is involved in the occurrence and spread of cervical squamous cell carcinoma in Poland (46).

The role of BCL2 in the development of tumors is still unclear. BCL2 was originally considered to be an anti-apoptotic regulatory protein (47), but it also has the effect of inhibiting proliferation (21). Therefore, BCL2 has both carcinogenic and tumor suppressive effects. This also explains why the prognostic significance of BCL2 expression depends on the type of cancer. Studies have shown that HPV E6 oncogenic protein is related to a variety of apoptosis regulators, such as BCL2 (48, 49). In the unit point analysis of this study, the rs2270115 located in the BCL2 gene did not show a significant association with CC. In the stratified study, it was found that compared with rs2270115 wild genotype CC, the genotype AA was association with CC when SCC-Ag is greater than 1.5 ng/ml. Fernandes et al. published a study on BCL2 gene polymorphism and cervical intraepithelial neoplasia (CIN), and found that rs2279115 SNP is not significantly related to CIN, but confirmed that the promoter SNP rs2279115 is related to elevated BCL2 protein expression (50). In addition, Ahmed HS and Qiu XG et al. found that rs2279115 SNP can increase the risk of HCV-related hepatocellular carcinoma and glioma (51, 52). Bozovic-Spasojevic found that high expression of BCL2 is associated with a good prognosis of breast cancer (53). Therefore, whether the BCL2 gene polymorphism is related to the risk of CC or cervical precancerous lesions still needs a large sample size and multi-center further research.

The lncRNAs of CCAT2 contain the transcript of rs6983267 SNP (54), which is located at 335kb downstream of MYC proto-oncogene (55). MYC oncogene is a target gene of Wnt signaling pathway, which is constitutively activated in the early development of various cancers including CC. Previous articles showed that the rs6983267 SNP located in the MYC enhancer region is related to the susceptibility of various cancers (30–34, 56, 57). However, it is controversial whether there is a correlation between SNP rs6983267 and the proto-oncogene MYC (58, 59). In this study, we did not find that rs6983267 SNP is related to the risk of CC. However, compared with rs6983267 wild genotype GG, genotype TG/TG+TT may increase the risk of CC in premenopausal women. The report by Sebastian Łaźniak et al. showed that CCAT2 rs6983267 SNP can contribute to the increase of MYC expression and the development and spread of cervical squamous cell carcinoma (29). The difference in genetic background and living environment may be the reason why this study is inconsistent with the report of Sebastian Łaźniak et al.

CARD8, a member of the caspase recruitment domain family, is an important part of the inflammasome. It can affect protein-protein, apoptosis, caspase-1 activity, regulate caspase-1-mediated activation of IL-1 and IL-8, and activate kappa -B (NFkB) (27, 28). NFkB is a key regulator of genes and tumorigenesis. Studies have reported that human papillomavirus 16 E5 tumor protein can up-regulate COX-2 expression through NFkB and mediate the occurrence of CC (60). The Rs7248320 SNP is located in the upstream region of CARD8 gene, which may affect the normal expression of CARD8. CARD8 may affect the progress of tumor biology by inhibiting cell apoptosis and participating in the NFkB signaling pathway. In this study, we did not find a significant association between the CARD8 gene rs7248320 SNP and the risk of CC in Heilongjiang Province, China. In further stratification studies, it still did not show significant statistical significance. However, Jian Yin et al. reported that rs7248320 SNP can increase the risk of CC, especially for premenopausal women (61). Compared with the study of Jian Yin et al., the sample size of this study is relatively small, so we will further expand the sample size to improve this study.

The occurrence and development of CC is a long-term, continuous, multi-factor, multi-step process. In order to evaluate the impact of multi-gene loci on CC, we conducted a haplotype study, which showed that there was no significant difference between CC and healthy controls.

This study was the first to analyze the gene polymorphisms of EXCO1, BCL2, CCAT2 and CARD8 in women with CC in the northern Chinese Han population. Successfully confirmed that EXCO1, BCL2 and CCAT2 gene polymorphisms may be involved in the occurrence and development of CC. This discovery gives us a deeper understanding of the incidence of CC and provides new ideas for the treatment of CC in the future.

Data Availability Statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://figshare.com/s/227c1afeffd8d6240684.

Ethics Statement

The studies involving human participants were reviewed and approved by the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin. Written informed consent was obtained from the individual(s), and minor(s)’ legal guardian/next of kin, for the publication of any potentially identifiable images or data included in this article.

Author Contributions

YF: data collection, data analysis, and manuscript writing. ZW: language modification and data analysis in the revised manuscript. MZ and SL: correction of the revised manuscript. TJ, SD, and LG: data collection and reviewing of relevant literature. XL and SZ: data collection and data analysis. XK: collecting and analyzing of patient information and data. JT: correction in the revised manuscript, LS: experimental design and overall planning. All of the authors contributed to the article and approved the submitted version.

Funding

This study was supported by the National Natural Science Foundation of China (No. 82071929).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We are deeply grateful to all study participants. We are grateful for the National Natural Science Foundation of China (No. 82071929).

References

1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin (2021) 71:209–49. doi: 10.3322/caac.21660

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Brocker KA, Alt CD, Gebauer G, Sohn C, Hallscheidt P. Magnetic Resonance Imaging of Cervical Carcinoma Using an Endorectal Surface Coil. Eur J Radiol (2014) 83:1030–5. doi: 10.1016/j.ejrad.2014.02.011

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Zheng R, Zeng H, Zhang S, Chen T, Chen W. National Estimates of Cancer Prevalence in China 2011. Cancer Lett (2016) 370:33–8. doi: 10.1016/j.canlet.2015.10.003

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Siegel RL, Miller KD, Jemal A. Cancer Statistic. CA Cancer J Clin (2017) 67:7–30. doi: 10.3322/caac.21387

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Walboomers JM, Jacobs MV, Manos MM, Bosch FX, Kummer JA, Shah KV, et al. Human Papillomavirus is a Necessary Cause of Invasive Cervical Cancer Worldwide. J Pathol (1999) 189:12–9. doi: 10.1002/(SICI)1096-9896(199909)189:1<12::AID-PATH431>3.0.CO;2-F

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Danolic D, Heffer M, Wagner J, Skrlec I, Alvir I, Mamic I, et al. Role of Ganglioside Biosynthesis Genetic Polymorphism in Cervical Cancer Development. J Obstet Gynaecol (2020) 40:1127–32. doi: 10.1080/01443615.2019.1692801

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Hemminki K, Chen B. Familial Risks for Cervical Tumors in Full and Half Siblings: Etiologic Apportioning. Cancer Epidemiol Biomarkers Prev (2006) 15:1413–4. doi: 10.1158/1055-9965.EPI-05-0933

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Pu X, Gu Z, Wang X. Polymorphisms of the Interleukin 6 Gene and Additional Gene-Gene Interaction Contribute to Cervical Cancer Susceptibility in Eastern Chinese Women. Arch Gynecol Obstet (2016) 294:1305–10. doi: 10.1007/s00404-016-4175-x

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Yi K, Yang L, Lan Z, Xi M. The Association Between MTHFR Polymorphisms and Cervical Cancer Risk: A System Review and Meta Analysis. Arch Gynecol Obstet (2016) 294:579–88. doi: 10.1007/s00404-016-4037-6

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Shastry BS. SNPs: Impact on Gene Function and Phenotype. Methods Mol Biol (2009) 578:3–22. doi: 10.1007/978-1-60327-411-1_1

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Tan H. The Association Between Gene SNPs and Cancer Predisposition: Correlation or Causality? EBioMedicine (2017) 16:8–9. doi: 10.1016/j.ebiom.2017.01.047

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Li X, Yin G, Li J, Wu A, Yuan Z, Liang J, et al. The Correlation Between TNF-Alpha Promoter Gene Polymorphism and Genetic Susceptibility to Cervical Cancer. Technol Cancer Res Treat (2018) 17:1533033818782793. doi: 10.1177/1533033818782793

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Chen B, Jiao Y, Yaolong F, Li T, Liu Y, Wang M, et al. The POLR2E Rs3787016 Polymorphism is Strongly Associated With the Risk of Female Breast and Cervical Cancer. Pathol Res Pract (2019) 215:1061–5. doi: 10.1016/j.prp.2019.02.015

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Gong JM, Shen Y, Shan WW, He YX. The Association Between MTHFR Polymorphism and Cervical Cancer. Sci Rep (2018) 8:7244. doi: 10.1038/s41598-018-25726-9

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Sugihara K, Asano S, Tanaka K, Iwamatsu A, Okawa K, Ohta Y. The Exocyst Complex Binds the Small GTPase RalA to Mediate Filopodia Formation. Nat Cell Biol (2002) 4:73–8. doi: 10.1038/ncb720

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Munson M, Novick P. The Exocyst Defrocked, a Framework of Rods Revealed. Nat Struct Mol Biol (2006) 13:577–81. doi: 10.1038/nsmb1097

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Rosse C, Formstecher E, Boeckeler K, Zhao Y, Kremerskothen J, White MD, et al. An aPKC-Exocyst Complex Controls Paxillin Phosphorylation and Migration Through Localised JNK1 Activation. PloS Biol (2009) 7:e1000235. doi: 10.1371/journal.pbio.1000235

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Martin-Urdiroz M, Deeks MJ, Horton CG, Dawe HR, Jourdain I. The Exocyst Complex in Health and Disease. Front Cell Dev Biol (2016) 4:24. doi: 10.3389/fcell.2016.00024

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Tanaka T, Goto K, Iino M. Diverse Functions and Signal Transduction of the Exocyst Complex in Tumor Cells. J Cell Physiol (2017) 232:939–57. doi: 10.1002/jcp.25619

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Tsujimoto Y, Gorham J, Cossman J, Jaffe E, Croce CM. The T(14;18) Chromosome Translocations Involved in B-Cell Neoplasms Result From Mistakes in VDJ Joining. Science (1985) 229:1390–3. doi: 10.1126/science.3929382

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Zinkel S, Gross A, Yang E. BCL2 Family in DNA Damage and Cell Cycle Control. Cell Death Differ (2006) 13:1351–9. doi: 10.1038/sj.cdd.4401987

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Johnson MI, Robinson MC, Marsh C, Robson CN, Neal DE, Hamdy FC. Expression of Bcl-2, Bax, and P53 in High-Grade Prostatic Intraepithelial Neoplasia and Localized Prostate Cancer: Relationship With Apoptosis and Proliferation. Prostate (1998) 37:223–9. doi: 10.1002/(sici)1097-0045(19981201)37:4<223::aid-pros3>3.0.co;2-o

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Bonnefoy-Berard N, Aouacheria A, Verschelde C, Quemeneur L, Marcais A, Marvel J. Control of Proliferation by Bcl-2 Family Members. Biochim Biophys Acta (2004) 1644:159–68. doi: 10.1016/j.bbamcr.2003.10.014

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Anagnostou VK, Lowery FJ, Zolota V, Tzelepi V, Gopinath A, Liceaga C, et al. High Expression of BCL-2 Predicts Favorable Outcome in non-Small Cell Lung Cancer Patients With non Squamous Histology. BMC Cancer (2010) 10:186. doi: 10.1186/1471-2407-10-186

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Davis RE, Staudt LM. Molecular Diagnosis of Lymphoid Malignancies by Gene Expression Profiling. Curr Opin Hematol (2002) 9:333–8. doi: 10.1097/00062752-200207000-00011

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Sanchez-Beato M, Sanchez-Aguilera A, Piris MA. Cell Cycle Deregulation in B-Cell Lymphomas. Blood (2003) 101:1220–35. doi: 10.1182/blood-2002-07-2009

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Razmara M, Srinivasula SM, Wang L, Poyet JL, Geddes BJ, DiStefano PS, et al. CARD-8 Protein, a New CARD Family Member That Regulates Caspase-1 Activation and Apoptosis. J Biol Chem (2002) 277:13952–8. doi: 10.1074/jbc.M107811200

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Garcia-Bermudez M, Lopez-Mejias R, Gonzalez-Juanatey C, Corrales A, Castaneda S, Ortiz AM, et al. CARD8 Rs2043211 (P.C10X) Polymorphism is Not Associated With Disease Susceptibility or Cardiovascular Events in Spanish Rheumatoid Arthritis Patients. DNA Cell Biol (2013) 32:28–33. doi: 10.1089/dna.2012.1836

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Lazniak S, Lutkowska A, Warenczak-Florczak Z, Sowinska A, Tsibulski A, Roszak A, et al. The Association of CCAT2 Rs6983267 SNP With MYC Expression and Progression of Uterine Cervical Cancer in the Polish Population. Arch Gynecol Obstet (2018) 297:1285–92. doi: 10.1007/s00404-018-4740-6

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Troutman SM, Sissung TM, Cropp CD, Venzon DJ, Spencer SD, Adesunloye BA, et al. Racial Disparities in the Association Between Variants on 8q24 and Prostate Cancer: A Systematic Review and Meta-Analysis. Oncologist (2012) 17:312–20. doi: 10.1634/theoncologist.2011-0315

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Wang YP, Zhang J, Zhu HY, Qian CL, Liu H, Ji F, et al. Common Variation Rs6983267 at 8q24.1 and Risk of Colorectal Adenoma and Cancer: Evidence Based on 31 Studies. Tumour Biol (2014) 35:4067–75. doi: 10.1007/s13277-013-1532-2

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Li J, Wang X, Dong J. Association of Rs6983267 Polymorphism and Thyroid Cancer Susceptibility: A Systematic Review and Meta-Analysis. Med Sci Monit (2016) 22:1866–71. doi: 10.12659/msm.896507

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Zhao X, Wei X, Zhao L, Shi L, Cheng J, Kang S, et al. The Rs6983267 SNP and Long non-Coding RNA CARLo-5 are Associated With Endometrial Carcinoma. Environ Mol Mutagen (2016) 57:508–15. doi: 10.1002/em.22031

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Han J, Zhou J, Yuan H, Zhu L, Ma H, Hang D, et al. Genetic Variants Within the Cancer Susceptibility Region 8q24 and Ovarian Cancer Risk in Han Chinese Women. Oncotarget (2017) 8:36462–8. doi: 10.18632/oncotarget.16861

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Li H. A Statistical Framework for SNP Calling, Mutation Discovery, Association Mapping and Population Genetical Parameter Estimation From Sequencing Data. Bioinformatics (2011) 27:2987–93. doi: 10.1093/bioinformatics/btr509

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Shi YY, He L. Shesis, a Powerful Software Platform for Analyses of Linkage Disequilibrium, Haplotype Construction, and Genetic Association at Polymorphism Loci. Cell Res (2005) 15(2):97–8. doi: 10.1038/sj.cr.7290272

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Li Z, Zhang Z, He Z, Tang W, Li T, Zeng Z, et al. A Partition-Ligation-Combination-Subdivision Em Algorithm for Haplotype Inference with Multiallelic Markers: Update of the Shesis (Http://Analysis.Bio-X.Cn). Cell Res (2009) 194:519–23. doi: 10.1038/cr.2009.33

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Ho GY, Burk RD, Klein S, Kadish AS, Chang CJ, Palan P, et al. Persistent Genital Human Papillomavirus Infection as a Risk Factor for Persistent Cervical Dysplasia. J Natl Cancer Inst (1995) 87:1365–71. doi: 10.1093/jnci/87.18.1365

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Bourgault Villada I, Moyal Barracco M, Ziol M, Chaboissier A, Barget N, Berville S, et al. Spontaneous Regression of Grade 3 Vulvar Intraepithelial Neoplasia Associated With Human Papillomavirus-16-Specific CD4(+) and CD8(+) T-Cell Responses. Cancer Res (2004) 64:8761–6. doi: 10.1158/0008-5472.CAN-04-2455

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Nicol AF, Nuovo GJ, Salomao-Estevez A, Grinsztejn B, Tristao A, Russomano F, et al. Immune Factors Involved in the Cervical Immune Response in the HIV/HPV Co-Infection. J Clin Pathol (2008) 61:84–8. doi: 10.1136/jcp.2007.047290

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Kuchta G, Szulc A, Slominski JM. [Telomerase and Telomeres in Lung Neoplasms–Biological and Clinical Significance]. Pneumonol Alergol Pol (1998) 66:568–73.

PubMed Abstract | Google Scholar

42. Fenard D, Yonemoto W, de Noronha C, Cavrois M, Williams SA, Greene WC. Nef is Physically Recruited Into the Immunological Synapse and Potentiates T Cell Activation Early After TCR Engagement. J Immunol (2005) 175:6050–7. doi: 10.4049/jimmunol.175.9.6050

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Roeth JF, Collins KL. Human Immunodeficiency Virus Type 1 Nef: Adapting to Intracellular Trafficking Pathways. Microbiol Mol Biol Rev (2006) 70:548–63. doi: 10.1128/MMBR.00042-05

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Di Bonito P, Grasso F, Mochi S, Petrone L, Fanales-Belasio E, Mei A, et al. Anti-Tumor CD8+ T Cell Immunity Elicited by HIV-1-Based Virus-Like Particles Incorporating HPV-16 E7 Protein. Virology (2009) 395:45–55. doi: 10.1016/j.virol.2009.09.012

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Shi Y, Li L, Hu Z, Li S, Wang S, Liu J, et al. A Genome-Wide Association Study Identifies Two New Cervical Cancer Susceptibility Loci at 4q12 and 17q12. Nat Genet (2013) 45:918–22. doi: 10.1038/ng.2687

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Lazniak S, Roszak A, Balcerek A, Warenczak-Florczak Z, Prokop E, Sowinska A, et al. Role of Rs13117307 Single Nuclear Polymorphism in the Risk of Uterine Cervical Cancer From Polish Population and its Impact on Exocyst Complex Component 1 Expression. Gene (2017) 627:524–9. doi: 10.1016/j.gene.2017.07.012

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Cory S, Adams JM. The Bcl2 Family: Regulators of the Cellular Life-or-Death Switch. Nat Rev Cancer (2002) 2:647–56. doi: 10.1038/nrc883

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Brickner SJ, Gaikema JJ, Zurenko GE, Greenfield LJ, Manninen PR, Ulanowicz DA. N-Acyl 3-Alkylidenyl- and 3-Alkyl Azetidin-2-Ones: A New Class of Monocyclic Beta-Lactam Antibacterial Agents. 1. Structure-Activity Relationships of 3-Isopropylidene and 3-Isopropyl Analogs. J Antibiot (Tokyo) (1992) 45:213–26. doi: 10.7164/antibiotics.45.213

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Filippova M, Parkhurst L, Duerksen-Hughes PJ. The Human Papillomavirus 16 E6 Protein Binds to Fas-Associated Death Domain and Protects Cells From Fas-Triggered Apoptosis. J Biol Chem (2004) 279:25729–44. doi: 10.1074/jbc.M401172200

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Fernandes AT, Rocha NP, Vendrame E, Russomano F, Grinsztejn BJ, Friedman RK, et al. Polymorphism in Apoptotic BAX (-248g>A) Gene But Not in Anti-Apoptotic BCL2 (-938c>A) Gene and its Protein and mRNA Expression are Associated With Cervical Intraepithelial Neoplasia. Apoptosis (2015) 20:1347–57. doi: 10.1007/s10495-015-1156-7

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Qiu XG, Chen YD, Yuan J, Zhang N, Lei T, Liu J, et al. Functional BCL-2 Rs2279115 Promoter Noncoding Variant Contributes to Glioma Predisposition, Especially in Males. DNA Cell Biol (2019) 38:85–90. doi: 10.1089/dna.2018.4318

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Ahmed HS, Wahab EA, Elhady HA, Elgerby MM. Association of Genetic Polymorphism of BCL-2 (Rs2279115) With Susceptibility to HCV-Related Hepatocellular Carcinoma. Immunol Res (2020) 68:189–97. doi: 10.1007/s12026-020-09143-7

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Bozovic-Spasojevic I, Ameye L, Paesmans M, Larsimont D, Di Leo A, Dolci S, et al. Prognostic, Predictive Abilities and Concordance of BCL2 and TP53 Protein Expression in Primary Breast Cancers and Axillary Lymph-Nodes: A Retrospective Analysis of the Belgian Three Arm Study Evaluating Anthracycline vs CMF Adjuvant Chemotherapy. Breast (2014) 23:473–81. doi: 10.1016/j.breast.2014.03.012

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Wood DE. Invited Commentary: Video-Assisted Tracheal Resection-a Long Walk for No Slide. Surgery (2005) 137:253–4. doi: 10.1016/j.surg.2004.07.012

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Pomerantz MM, Ahmadiyeh N, Jia L, Herman P, Verzi MP, Doddapaneni H, et al. The 8q24 Cancer Risk Variant Rs6983267 Shows Long-Range Interaction With MYC in Colorectal Cancer. Nat Genet (2009) 41:882–4. doi: 10.1038/ng.403

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Bertucci F, Lagarde A, Ferrari A, Finetti P, Charafe-Jauffret E, Van Laere S, et al. 8q24 Cancer Risk Allele Associated With Major Metastatic Risk in Inflammatory Breast Cancer. PloS One (2012) 7:e37943. doi: 10.1371/journal.pone.0037943

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Gong WJ, Yin JY, Li XP, Fang C, Xiao D, Zhang W, et al. Association of Well-Characterized Lung Cancer lncRNA Polymorphisms With Lung Cancer Susceptibility and Platinum-Based Chemotherapy Response. Tumour Biol (2016) 37:8349–58. doi: 10.1007/s13277-015-4497-5

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Prokunina-Olsson L, Hall JL. No Effect of Cancer-Associated SNP Rs6983267 in the 8q24 Region on Co-Expression of MYC and TCF7L2 in Normal Colon Tissue. Mol Cancer (2009) 8:96. doi: 10.1186/1476-4598-8-96

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Shang S, Hua F, Hu ZW. The Regulation of Beta-Catenin Activity and Function in Cancer: Therapeutic Opportunities. Oncotarget (2017) 8:33972–89. doi: 10.18632/oncotarget.15687

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Mojiminiyi OA, Stretch JR, Shepstone BJ, Soper ND, Godfrey AM, Poole MD. Preclinical Detection of Metastatic Melanoma. J Nucl Biol Med (1991) 35:73–5.

PubMed Abstract | Google Scholar

61. Yin J, Wen J, Hang D, Han J, Jiang J, Song C, et al. Expression Quantitative Trait Loci for CARD8 Contributes to Risk of Two Infection-Related Cancers–Hepatocellular Carcinoma and Cervical Cancer. PloS One (2015) 10:e0132352. doi: 10.1371/journal.pone.0132352

PubMed Abstract | CrossRef Full Text | Google Scholar