What’s Known

Zinc Finger protein 365 (ZNF365) is one of the prominent loci confirmed in pooled and Genome Wide Association Studies (GWAS) analysis. The association of rs10822013 and rs10995190 polymorphisms with the risk of breast cancer in European and East-Asian countries has been confirmed. Moreover, this polymorphism is associated with the mammographic dense area and percent density.

What’s New

The present study illustrated the prognostic role of rs10822013 and rs10995190 in breast cancer in a group of the Iranian population. The C-A haplotype of rs10822013-rs10995190 was associated with breast density. According to Kaplan-Meier plots, the AG genotype of rs10995190 was significantly associated with overall survival in our examined population.

Introduction

Breast cancer is the most prevalent malignancy in women in developed and developing countries. ¹ While developed areas indicate a greater incidence the age of diagnosis is younger, ^{2 - 4} and the mortality rate is higher in developing regions. ¹ It might be due to the diagnosis at the late stages because of the lack of early diagnostic tests in such areas. ⁵ While breast cancer has an unknown etiology, there is abundant evidence supporting that genetic variations play a central role in the pathogenesis and progression of the disease. Genetic polymorphisms are critical elements of the differences in breast cancer susceptibility among individuals. ⁶ However, there is diversity in the distribution of alleles among populations, and various loci represent different risk rates. ^{3 , 7}

Genome-wide association studies (GWAS) have recognized several loci containing common variants that influence breast cancer risk and prognosis confirmed in different ethnicities. ^{8 , 9} Zinc Finger protein 365 (ZNF365) is one of the striking loci confirmed in meta-analysis and GWAS analysis. ^{10 - 12} ZNF365 encodes a Zinc Finger protein with several isoforms showing different expression patterns. It acts as a cell cycle regulator, and the lack of its function in the cell causes abnormal recombination and aneuploidy. ¹³ According to The Human Protein Atlas, RNA expression has been observed in normal breast tissue and MCF7, as a metastatic breast adenocarcinoma cell line. Evaluating breast tumors revealed a lower survival rate associated with a higher expression of the ZNF365. On the other hand, another report has represented the lower expression of ZNF365 in triple-negative breast cancer than others and a better survival associated with its higher expression level. ^{13 , 14} Therefore, data on the importance of ZNF365 in breast cancer development and prognosis is controversial.

Extensive studies have presented the significant effects of ZNF365 variants on chromosome 10q21.2 rejoin on breast cancer risk. ^{11 , 15 , 16} Genotyping analyses have confirmed the association of rs10822013 and rs10995190 polymorphisms with the risk of breast cancer in European and East-Asian populations. ¹¹ rs10995190 has also been confirmed as a breast cancer susceptibility locus in patients carrying BRCA2 mutations. ¹⁷ Besides, this polymorphism is associated with the mammographic dense area and percent density. ¹⁸ Although these variations are located in intronic places, these may confer their function via altering gene expression by affecting the binding of transcription factors to DNA or changing splice sites. ^{19 , 20} According to this information, ZNF365 may have a potential role in mammographic density, breast cancer development, and prognosis. However, there is no study concerning the association of the two common polymorphisms of this gene in the Iranian population. Therefore, this study was conducted to evaluate the association of rs10822013 and rs10995190 with breast density, cancer risk, and prognosis in a group of the Iranian population.

Patients and Methods

The study was approved by the Ethical Committee of Mashhad University of Medical Sciences (Ethical approval number: IR.MUMS.fm.REC.1394.472), and written informed consent was obtained from all participants.

Study Population

The current study was performed at Mashhad University of Medical Sciences, Mashhad, Iran. Sampling was done between 2017 and 2020 based on the convenience sampling method.

The control group included healthy subjects aged between 18-65 years old, referred to clinicians for breast cancer screening, and clinical breast exams (and, in some participants, mammography) confirmed their health. All patients referred to Omid Hospital (Mashhad University of Medical Sciences, Mashhad, Iran) whose breast cancer was confirmed histopathologically, were included in the study without restricting age or histological type. Participants were excluded from the study in case of a positive history of hereditary cancers in the family after considering pedigrees.

Demographic data such as age at diagnosis, weight, height, history of lactation, history of abortion, physical activity, history of screening, age at menarche and menopause, and age at first pregnancy were collected using a data gathering form. Pathologic, mammographic, and clinical data were extracted from the patient’s clinical records. Standard protocols were utilized to categorize the clinical features. ^{21 , 22} Moreover, the mammographic density report was under Breast Imaging-Reporting and Data System (BI-RADS) classifications. ²³

Blood Collection, DNA Extraction, and Genotyping

After obtaining informed consent, 4 mL of peripheral blood sample was collected in K2-EDTA tubes (VACUETTE® TUBE 4 mL K2E K2EDTA, Greiner Bio-One International, Kremsmünster, Austria). Genomic DNA was extracted using the salting-out method. ²⁴ DNA concentration and purity were measured with the Epoch^TM Microplate Spectrophotometer (BioTek Instruments Inc., Winooski, VT, USA). The quality of DNA samples was evaluated by 1% agarose gel electrophoresis. Then, samples were stored at -80 °C until being used for analysis.

Genotype analysis of ZNF365 polymorphisms was performed using Allele-Specific PCR based on allele-specific primers. A PCR reaction tube was prepared to detect each allele in a 10 µL total volume, using 1 µL of DNA (200 ng), 5 µL Taq PreMix Master Mix (Parstous, Mashhad, Iran), 1µL of one of the forward primers (10 µM), 1 µL of common reverse primer (10 µM), and 2 µL nuclease-free water. Primers were designed by Web-based Allele-Specific PCR (WASP) online software (National Biobank of Thailand, Thailand) ²⁰ as follows: 

rs10822013 Forward C: 5 CCAGATGGCACAAGAAAATAC 3 (an amplicon with a size of 189 bp)

rs10822013 Forward T: 5 ACCAGATGGCACAAGAAAATGT 3 (an amplicon with a size of 190 bp)

rs10822013 Common Reverse: 5 ATCACCTGGCTGACATGACA 3

rs10995190 Forward G: 5 GTTGTGTCCAAGTGCATATTTAG 3 (an amplicon with a size of 194 bp)

rs10995190 Forward A: 5 GTTGTGTCCAAGTGCATATTGAA 3 (an amplicon with a size of 194 bp)

rs10995190 Common Reverse: 5 TTGCTAGCAACAATGAGGGGTG 3

PCR conditions included 10 min of initial denaturation at 95 °C. Then, 35 cycles were done, including denaturation at 95 °C for 15 sec, annealing at 56 °C for rs10995190-G and 58 °C for rs10995190-A and rs10822013 for 15 sec, and extension at 72 °C for 15 sec. The 10 min final extension was performed at 72 °C. Amplification was performed in a Veriti 96 well PCR Thermal Cycler (Applied Biosystems, Foster City, California, United States). Finally, all the samples underwent electrophoresis with 2% agarose gel (figure 1). 10% of samples were randomly re-genotyped to confirm the genotyping data.

Figure 1. Agarose gel electrophoresis (2%) shows various genotypes of rs10822013 and rs10995190 polymorphisms as follows. A: Represent rs10822013, lane A, C, and E; Polymerase chain reaction (PCR) product size for allele A (189 bp), lane B, D, and F; PCR product size for allele T (190 bp), lane M; Marker (DNA ladder 50 bp). B: Represent rs10995190, lane A, C, and E; PCR product size for allele C (194 bp), lane B, D, and F; PCR product size for allele G (194 bp), lane M; marker (DNA ladder 100 bp), lane CN; negative control.

Statistical Analysis

The Hardy-Weinberg Equilibrium (HWE) assumption was assessed in the case and control samples using the Chi square test. Descriptive statistics were determined for all variables, including mean±SD, frequency, and percentage. Normal distribution was assessed using the Kolmogorov–Smirnov statistic. Quantitative and qualitative variables were compared between groups using independent t tests and Chi Square test, respectively. Binary logistic regression analysis was performed to assess the association between SNPs and the risk of breast cancer and calculate odds ratios. Multivariate analysis was then undertaken for the baseline variables, with a P<0.05 found in the univariate analysis.

The period from breast cancer diagnosis based on the first pathology result until death due to cancer or the end of the study date was defined as overall survival (January 31, 2021). The designed survival curves using the Kaplan-Meier method and the log-rank test were used to estimate differences between the groups. Statistical significance was set at P<0.05. Data were analyzed using SPSS version 16.0 (IBM, USA).

The distribution of haplotypes was assumed using the PHASE program version 2, a program implementing the method for reconstructing haplotypes from population data. ^{25 , 26} Diplotyping was also done using PHASE haplotype outputs. Linkage disequilibrium (LD) was calculated by the 2LD program version 1.00. ²⁷ Using SPSS version 16.0, odds ratios and 95% CI were calculated to estimate the degree of the association between haplotypes and the risk of breast cancer. A statistical P value less than 0.05 was considered significant.

Results

Characteristics of the Study Population

The current study collected 342 breast cancer samples and 390 healthy subjects. The characteristics of the study population are summarized in table 1. There was no significant difference in the mean age, menarche age, menopause age, and the history of abortion and lactation between cases and controls. However, the age at first pregnancy varied significantly. Evaluation of menopause status indicated that a significantly higher percentage of the patients belonged to the post-menopause group. History of screening (clinical breast exam, mammography, MRI) and BMI were significantly different between cases and controls. Evaluation of breast density indicated higher areas of dense breasts (BI-RADS 3 & 4 or C & D) in breast cancer patients with a significant difference between groups.

Tumor features of breast cancer patients are summarized in table 2. According to the World Health Organization (WHO) classification for the types of breast cancer tumors in 2012, ²¹ invasive ductal carcinoma (IDC), with 85.9% of all identified types of tumors, indicated the highest frequency. According to the pathologic subtyping, most patients were hormone receptor-positive. Evaluating HER2 status by IHC was performed based on the American Society of Clinical Oncology (ASCO) recommendation for Her2 IHC testing. ²² The results showed that the majority of patients were HER2^-.

Association of Breast Cancer Risk, Breast Density, and Clinical Characteristics of the Tumor with Genotypes, Haplotypes, and Diplotypes

Allele and genotype frequencies are summarized in table 3. All genotypic frequencies of rs10822013 were in Hardy–Weinberg equilibrium in the healthy controls (P=0.89). The T allele, as the risky allele, was significantly higher in the patients than in the controls. The TT genotype, as a risky genotype, indicated significantly higher frequency in cases than in the control group. Evaluation of genetic models revealed that the distribution of the TT genotype compared with C allele carriers (TC+CC) in the recessive model was significantly different between breast cancer and control people.

The genotype frequencies of rs10995190 followed the Hardy–Weinberg equilibrium in controls (P=0.90). There was a significant difference in allele frequency between patients and healthy individuals. GG genotype was the most frequent genotype in breast cancer, with a higher frequency in cases than in controls. Furthermore, the dominant model indicated a significant difference between the groups, as the GG+GA genotypes were higher in patients than in controls. A significant difference was also observed between groups in the recessive model.

Further investigation indicated no significant difference in the distribution of genotypes and alleles of ZNF365rs10822013 and rs10995190 between dense and non-dense breasts and tumor characteristics.

The frequencies of haplotypes and diplotypes are shown in table 4. The most frequent haplotype was T-G, with a significant difference between groups. The C-A haplotype was also significantly different between patients and healthy groups.

PHASE software identified nine diplotypes according to genotype data. Four diplotypes, including T-G/C-A, C-G/T-G, T-G/T-G, and T-G/T-A, had frequencies over 10%. The comparison of diplotype distribution between breast cancer cases and healthy controls indicated that the frequency of T-G/T-G diplotype was significantly different between cases and controls.

Evaluation of dense and non-dense breasts indicated a significant difference in the C-A haplotype. However, there was no association between haplotypes/diplotypes and clinical features of breast cancer, including grade, stage, hormone receptors, and HER2 status.

Survival Analysis in Association with Genotypes, Haplotypes, and Diplotypes

Univariate Cox regression analysis indicated the stage (Late vs. Early) (P=0.007, HR=3.17, 95% CI [1.36-7.38]), ER status (Positive vs. Negative) (P<0.001, HR=0.19 95% CI [0.08-0.41]) and PR status (Positive vs. Negative) (P=0.002, HR=0.29, 95% CI [0.13-0.64]) were associated with overall survival. Results of multivariate analysis demonstrated that the stage (P=0.024, HR=2.67, 95% CI [1.14-6.29]) of the disease and ER status (P=0.001, HR=0.26, 95% CI [0.11-0.60]) were independently and significantly associated with overall survival. Therefore, the survival analysis of polymorphisms, haplotypes, and diplotypes was adjusted for pathologic features.

According to Kaplan-Meier plots, the AG genotype of rs10995190 was significantly associated with overall survival. Patients carrying rs10995190 AG compared with GG genotype ones were significantly associated with overall survival. This result was also observed in the recessive model (GG v. AG+AA). However, after adjustment for stage and ER status, the GG genotype was significantly related to better overall survival in the recessive model (P=0.042, HR=0.37 95% CI [0.14-0.97]). Moreover, rs10822013 revealed no association with survival both before and after adjustment. The results are shown in figure 2.

Figure 2. Plots indicate the association of ZNF365rs10822013 and rs10995190 polymorphisms with overall survival. A: Plot for rs10822013 genotypes with no difference in overall survival (P=0.169). B: Plot for rs10822013 using the dominant model (TC+TT vs. CC) with no difference in overall survival (P=0.107). C: Plot for rs10822013 using the recessive model (TT vs. TC+CC) with no difference in overall survival (P=0.133). D: Plot for rs10995190 genotypes with a significant difference in overall survival (P=0.044). Patients carrying the rs10995190 AG genotype tended to have lower survival than those carrying the GG genotype, with a hazard ratio (HR) of 2.68 and 95% CI (1.14-6.28). E: Plot for rs10995190 using the dominant model (GG+AG vs. AA) with no difference in overall survival (P=0.360). F: Plot for rs10995190 using the recessive model (GG vs. AG+AA) with a difference in overall survival (P=0.014). Patients carrying the rs10995190 GG genotype tended to have higher survival than those carrying AG+AA genotypes, with a hazard ratio (HR) of 0.36 and 95% CI (0.16-0.84). A statistical P value less than 0.05 was considered significant.

Analysis of Kaplan–Meier curves for haplotypes of rs10822013 and rs10995190 polymorphisms demonstrated that the C-G haplotype carrying the protective allele of rs10822013 (C) and risky allele of rs10995190 (G) was significantly associated with better overall survival. This observation was not changed after adjustment of stage and ER status (P=0.019. HR=0.09, 95% CI [0.01-0.67]). The results are shown in figure 3.

Figure 3. Plots indicate the association of ZNF365rs10822013 and rs10995190 haplotypes with overall survival. A: Plot for rs10822013-rs10995190 CG haplotype compared with other haplotypes with a difference in overall survival (P=0.001). Patients carrying the rs10822013-rs10995190 CG haplotype tended to have higher survival than those carrying other haplotypes, with a hazard ratio (HR) of 0.14 and 95% CI (0.03-0.57). B: Plot for rs10822013-rs10995190 TG haplotype compared with other haplotypes with no difference in overall survival (P=0.478). C: Plot for rs10822013-rs10995190 AC haplotype compared with other haplotypes with no difference in overall survival (P=0.224). D: Plot for rs10822013-rs10995190 AT haplotype compared with other haplotypes with no difference in overall survival (P=0.065). A statistical P value less than 0.05 was considered significant.

The survival plots designed by the Kaplan-Meier test displayed that breast cancer patients with C-G/T-G diplotype had better overall survival (P=0.030). However, this result was not confirmed after adjustment for stage and ER status. The results are shown in figure 4.

Figure 4. Plots indicate the association of ZNF365rs10822013 and rs10995190 dipolotypes with overall survival. A: Plot for rs10822013-rs10995190 (TG-CA) diplotype compared with other diplotype with no difference in overall survival (P=0.149). B: Plot for rs10822013-rs10995190 (CG-TG) diplotype compared with other diplotype with a difference in overall survival (P=0.030). However, cox regression analysis did not confirm this finding, P=0.062, hazard ratio (HR) 0.15, and 95% CI (0.02-1.10). C: Plot for rs10822013-rs10995190 (TG-TG) diplotype compared with other diplotype with no difference in overall survival (P=0.786). D: Plot for rs10822013-rs10995190 (TG-TA) diplotype compared with other diplotype with no difference in overall survival (P=0.111). A statistical P value less than 0.05 was considered significant.

Discussion

In the present study, the role of ZNF365rs10822013 and rs10995190 polymorphisms was evaluated in the mammographic density, breast cancer risk, and prognosis in an Iranian population for the first time. Our results represented that the rs10995190-G and the rs10822013-T alleles were significantly associated with the increased risk of breast cancer. Moreover, haplotype and diplotype analyses were significantly associated with density values, breast cancer risk, and overall survival.

Considering rs10822013 in the Iranian population revealed a significantly higher frequency of the T allele in breast cancer patients than in healthy people, with an effect size of 30% as a risky allele. The rs10822013-T allele distribution has been reported as 18% in Africans and almost 50% in Asians, Europeans, and Americans. However, the frequency varies between 11% and 55% in different sources. ^{28 - 31} The TT genotype of rs10822013, compared with TC+CC genotypes, increased the risk of breast cancer by up to 44%. Based on a GWAS, rs10822013 presents a 10% risk of breast cancer in East-Asian women. ¹¹ Furthermore, it was associated with the risk of breast cancer in the Han Chinese population ³⁰ but not in the Singapore Chinese population. ²⁹ Controversial results may arise from the sample size and a highly different allele frequency of rs10822013 between populations, conferring breast cancer susceptibility in some ethnicities but not others.

The rs10995190-G allele frequency was 66.4% in the present study. ALelle FREquency Database (ALFRED) database has reported the frequency of this allele between 57% in Europe to 100% in Africa, Asia, and other continents. Despite the variation in allele frequency between different ethnicities, the G allele is the most frequent in all populations. ^{30 , 32} Our data indicated an increased risk of breast cancer of about 29% for the rs10995190-G allele in the multiplicative model (G vs. A) and 79% in the dominant model (GG+GA vs. AA). According to previous studies, despite the lack of association in Asia, rs10995190 was associated with breast cancer in the European population. ^{11 , 33} However, further assessment is needed in different ethnicities to confirm or reject this hypothesis of whether rs10995190 is precisely associated with breast cancer. Besides its association with breast cancer risk, some evidence confirmed the impact of rs10995190 on breast density, and the A allele decreases mammographic density by up to 18% even after excluding breast cancer cases or adjusting for case-control status. ¹⁸ Moreover, another study reported the association between mammographic density measurements and rs10995190. ³⁴ The lack of relevance in our study may be due to insufficient sample size or a different genetic basis in the study population compared to others. As a result, breast density may be a confounding factor in assessing the association of rs10995190 with breast cancer. Therefore, evaluating the susceptibility rate of breast cancer in relationship with rs10995190 needs adjustment for breast density. On the other hand, this variant is not related to the impact of menopausal hormone therapy on mammographic density. ³⁵ Inconsistent with our findings, a previous study in the Han Chinese population reported an association between rs10822013 and ER status. ³⁰ Thus, the influence of rs10995190 on breast density and cancer may happen via hormonal and non-hormonal pathways, including estrogen hormone and developmental signaling. Although its higher expression causes better survival, ¹³ no analysis reports the involvement of ZNF365 pathways in cancer.

To the best of our knowledge, the present study was the first report evaluating the haplotype patterns of the ZNF365 common variations. Identified haplotypes potentially involve one or more susceptibility alleles, and recognizing their action approach will aid individual-level risk prediction. According to the results, the considered variants are not observed most often together in our population, because these SNPs are not in tight LD (D’ coefficient=0.04, P=0.177). Further analysis indicated that the T-G haplotype (rs10822013-rs10995190), with a higher frequency in breast cancer patients, was a risky haplotype that could increase the risk of the disease by up to 44%. It was along with the impact of T and G alleles on the risk of breast cancer. Conversely, a haplotype containing C and A alleles (C-A haplotype) had a protective effect of up to 32%. Moreover, the C-A haplotype of rs10822013-rs10995190 was associated with breast density.

Evaluation of breast cancer prognosis revealed the association of rs10995190-GG genotype and C-G haplotype of rs10822013-rs10995190 with better overall survival. While the rs10995190-G allele and GG genotype were associated with the increased risk of breast cancer, genotypes and haplotypes carrying the G allele could cause a better prognosis. This contradictory role may be influenced by different pathways that ZNF365 is involved in and the role of other contributors and modulator variants. In this regard, triple-negative breast cancer, a poor prognosis type of tumor, has been associated with a decreased level of ZNF365 expression. ¹³ Analysis of the expression profile in association with rs10995190 may help clear the dual role of the GG genotype as a hazard generator of breast cancer development and increasing survival.

Conclusion

The present study introduced the potential risk of rs10822013 and rs10995190 in breast cancer. Furthermore, it provided some evidence of involving ZNF365 haplotypes in mammographic density. However, the genetic background of diverse ethnicities influences the distribution of alleles. Therefore, it may modify the association of the variants with different disease characteristics. Since accumulating data support the role of these variants in breast cancer, further studies are required to investigate the association of ZNF365 variations with the risk of breast cancer and clinical features of the disease. Expression and functional in silico/in vitro analyses are also essential for investigating the role of ZNF365 intronic and deep intronic variations on the stability and activity of ZNF365 protein and other potential non-coding RNAs in the pathogenesis of breast cancer and survival. A better understanding of the mechanism of carcinogenesis will help pave the path toward personalized medicine for patients with breast cancer and the implementation of breast cancer prevention.

Acknowledgment

The authors thank all participants in this research and also like to thank Mashhad University of Medical Sciences and Omid Hospital for supporting the project. This work was based on the Master of Science thesis of Mr. Seyed Reza Ghadamgahi and was financially supported by Mashhad University of Medical Sciences under Grant 940780.

Authors’ Contribution

SR.Gh: Laboratory work, revision; L.H: Laboratory work, drafting; S.AKh: Data collection, revision; MR.N: Laboratory work, drafting; M.A: Laboratory work, revision; Sh.E: Data collection, revision; A.KhSh: Data collection, laboratory work, revision; F.HSh: Data collection, revision; A.P: Study design, statistical analysis, drafting; F.A: Study design, data collection, statistical analysis, drafting; All authors have read and approved the final manuscript and agree to be 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.

Conflict of Interest:

None declared.

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