Journal of Oncology

Journal of Oncology / 2021 / Article

Research Article | Open Access

Volume 2021 |Article ID 8865624 | https://doi.org/10.1155/2021/8865624

Deepti Bhatt, Amit Kumar Verma, Prahalad Singh Bharti, Yamini Goyal, Mohammed A. Alsahli, Ahmad Almatroudi, Arshad Husain Rahmani, Saleh Almatroodi, Prakash C. Joshi, Mohammad Mahtab Alam, Irfan Ahmad, Gaffar Sarwar Zaman, Kapil Dev, "BCL-2 (-938C>A), BAX (-248G>A), and HER2 Ile655Val Polymorphisms and Breast Cancer Risk in Indian Population", Journal of Oncology, vol. 2021, Article ID 8865624, 8 pages, 2021. https://doi.org/10.1155/2021/8865624

BCL-2 (-938C>A), BAX (-248G>A), and HER2 Ile655Val Polymorphisms and Breast Cancer Risk in Indian Population

Academic Editor: Peter F. Lenehan
Received09 Sep 2020
Revised13 Jan 2021
Accepted14 Feb 2021
Published25 Feb 2021

Abstract

Breast cancer is the most common carcinoma in women worldwide. The present case-control study was aimed to examine the association of BCL-2 (-938C> A), BAX (-248G > A), and HER2 (I655V i.e. A > G) polymorphisms with breast cancer risk in Indian population. This study enrolled 117 breast cancer cases and 104 controls. BCL-2 (-938C > A), BAX (-248G > A), and HER2 Ile655Val polymorphisms were screened by PCR-RFLP method. There was no significance difference in the allelic and genotype frequency of the BCL-2 (-938C > A) and BAX (-248G > A) polymorphisms between cases and controls. In relation to HER2 Ile655Val polymorphism, the statistical analysis of observed genotypic frequencies showed significant association (-0.0059). Compared to Ile/Ile (A/A) genotype, frequency of Ile/Val (A/G) genotype was significantly higher among cases than in control group and observed to increase the breast cancer risk (OR, 2.43; 95%CI, 1.32–4.46; -0.004). The frequency of Val (G) allele was significantly higher in cases as compared to controls (6.83% vs 2.88%, resp.). Compared to Ile (A) allele, significant increase in the risk of breast cancer was observed with Val (G) allele (OR, 2.21; 95% CI, 1.35–3.63; -0.0016). We observed significant association between HER2 Ile655Val polymorphism and breast cancer risk under the dominant (OR = 2.52; 95% CI: 1.41–4.51; -0.001) and codominant (OR, 2.24; 95% CI: 1.23–4.09; p-0.008) model. In our study, BCL-2 (-938C > A) and BAX (-248G > A) polymorphism were not found to be associated with breast cancer risk. This present study for the first time shows significant association of HER2 Ile655Val polymorphism with risk of breast cancer in Indian population. Therefore, we suggest that each population need to evaluate its own genetic profile for breast cancer risk that may be helpful for better understanding the racial and geographic differences reported for breast cancer incidence and mortality.

1. Introduction

Breast cancer is the leading cause of cancer-related deaths and it is the most common type of cancer among women worldwide [1]. In India, projected number of breast cancer cases is 179,790 in the year 2020 and will comprise approximately 10% of all cancers [2]. Various risk factors are associated with the development, pathogenesis, and progression of breast cancer, including genetic, environmental, biological, and lifestyle factors [3]. The relation between the occurrence of a cancer and the existence of genetic alterations is now well established [4]. For better understanding the etiology of breast cancer, recent approaches involve the molecular markers identification, which may help in prediction and prognosis of the disease [5, 6]. Apoptosis and cellular proliferation have a significant role in normal development and carcinogenesis of mammary gland [7]. Delicate homeostasis between apoptosis and proliferation in normal tissues is maintained by variety of proteins of the BCL-2 family. The BCL-2 family of proteins is divided into two main classes, proapoptotic members like BAX (BCL-2-associated X protein) and BAK, and antiapoptotic members like BCL-2 (B-cell leukemia/lymphoma 2) and BCL-xL [8]. BCL-2 gene is located on chromosome 18q21.3 [9] and comprises of three exons and two promoters (P1 and P2), both having different functions. The BAX gene is mapped to chromosome 19q13.3 q13.4 [10]. Dysregulation in the BCL-2 and BAX genes expression may cause disruption of cellular homeostasis and origin of malignancy. The functional promoter polymorphisms in BCL-2 and BAX genes were found to change the protein expression or function that may have an effect on the delicate balance in mechanisms which regulate apoptosis.

Human epidermal growth factor receptor 2 (HER2/neu/EGFR2/ERBB2/c-erbB-2) protooncogene encodes a 185 kDa transmembrane glycoprotein [11, 12] which plays important role in cell growth regulation, differentiation, and survival [13]. To date, no study has ever been conducted to evaluate the association of HER2 polymorphism with breast cancer risk in Indian population. Although the role of BCL-2, BAX, and HER2/neu is established in breast cancer pathogenesis, the exact molecular mechanism is still not clear. Therefore, the aim of the present case-control study was to investigate the association of BCL-2 (-938C>A), BAX (-248G>A), and HER2 Ile655Val polymorphisms with breast carcinoma risk in Indian population.

2. Materials and Methods

2.1. Study Subjects

In the current case-control retrospective study, a total of 117 cases of primary breast cancer were included, which fulfilled the relevant selection criteria, and a total 104 nonmalignant lesions cases of the breast tissue were taken as control after obtaining the ethical clearance from Institute Ethics Committee (Proposal no. 27/07/2017/GKV/IEC/2017). Inclusion criteria were that the required tissue sample was retrieved from the paraffin blocks prepared from primary breast tumor site only cases, which were diagnosed as infiltrating ductal carcinoma, not otherwise specified (IDC, NOS). Exclusion criteria were patients with history of recurrence of breast tumor (only cases of primary breast carcinoma were included in the study), history of prior radiation exposure to the site (prior radiotherapy) and history of neoadjuvant chemotherapy. The sample size was estimated by using the following formula: N =  (where N is sample size, is expected prevalence, Z is the statistic corresponding to level of confidence, and d is precision (corresponding to effect size)). The written informed consent was collected from all participating subjects/individuals. The relevant clinical history of all the cases of the study was collected and clinical history was used for the selection of appropriate cases as per exclusion/inclusion criteria of the study. The mean age of cases was 48.69 years and median age was 48 years. Cases had age range between 18 and 73 years and age group of 45 to 60 years had a peak prevalence rate.

2.2. DNA Isolation and Genotyping

Genomic DNA was isolated from paraffin embedded tumor tissue blocks by phenol-chloroform method. Genotyping of the SNPs BCL-2-938C>A, BAX-248G>A, and HER2 (I655V, i.e., A>G) was performed by using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. PCR reactions were performed in a 25 µl reaction mixture containing 1 µl genomic DNA, 10X PCR buffer 2.5 µl, 2.5 µl dNTP, 0.5 µl of each primer, and 1 µl Taq DNA polymerase. For BCL-2, PCR conditions include initial denaturation at 96°C for 5 min followed by 35 cycles at 96°C–for 45 seconds, at 56°C for 45 seconds, and at 72°C for 30 s and a final extension step at 72°C for 10 minutes. For BAX, PCR conditions include initial denaturation at 95°C for 5 min followed by 35 cycles at 95°C–48 seconds, at 54°C for 45 seconds, and at 72°C for 40 s and a final extension step at 72°C for 8 minutes. For HER2, PCR conditions include initial denaturation at 94°C for 5 min followed by 35 cycles at 94°C–30 s, at 62°C–45 seconds, and at 72°C for 30 s and a final extension step at 72°C for 7 minutes.

After PCR reaction, 10 μl of each PCR product was digested with different restriction enzymes as shown in Table 1 at 37⁰C for overnight. In the case of BCL-2 polymorphism (-938C>A), after digestion wild-type allele (CC) yielded two bands of 189 and 111 bp; wild-type/variant allele (CA) yielded 111, 189, and 300 bp and the variant allele (AA) yielded a single 300 bp band. For BAX polymorphism (-248G>A), after digestion wild-type allele (GG) yielded two bands (89 and 20 bp); wild-type/variant allele (GA) yielded 20, 89, and 109 bp, and the variant allele (AA) yielded a single 109 bp band. In the case of HER2 polymorphism (I655V, i.e., A>G), after digestion wild-type allele (AA) produced one band (148 bp); wild-type/variant allele (AG) produced 116, 32, and 148 bp, and the variant allele (GG) produced two bands 116 and 32 bp band. The digested PCR products were visualized on a 2% agarose gel containing ethidium bromide. PCR primers, PCR product sizes, restriction enzymes, and enzyme digests are listed in Table 1 and Figures 1(a)1(c).


GenePosition and base changeGenotypingPrimerPCR productRestriction enzyme usedEnzyme digests

BCL-2-938C>APCR-RFLP5′-CTGCCTTCATTTAT
CCAGCA-3′ (forward)
5′-GGCGGCAGATGA
ATTACAA-3′ (reverse)
300 bpBccI (1 unit)C allele: 189 and 111 bp; A allele: 300 bp

BAX-248G>APCR-RFLP5′-CATTAGAGCTGCGA
TTGGACCG-3′ (forward)
5′-GCTCCCTCGGGAG
GTTTGGT-3′ (reverse)
109 bpMspI (1 unit)G allele: 89 and 20 bp
A allele: 109 bp

HER2I655V A>GPCR-RFLP5′-AGAGCGCCAGCCCTCT
GACGTCCAT-3′ (forward)
5′-TCCGTTTCCTGCAGCA
GTCTCCGCA-3′ (reverse)
148 bpBsmAI (1 unit)G allele: 116 and 32 bp; A allele: 148 bp

2.3. Statistical Analysis

Chi-square test was applied for comparing genotype and allele frequencies for statistical significance between breast cancer patients and controls. Observed and expected genotype frequencies of BCL-2, BAX, and HER2 gene polymorphism in controls showed no deviation from Hardy-Weinberg equilibrium. Chi-square test showed that there was no significant deviation from Hardy-Weinberg equilibrium for BCL-2, BAX, and HER2 SNP genotypes (). Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were determined to assess the strength of association of BCL-2 (-938C>A) and BAX (-248G>A) and HER2 Ile655Val polymorphism with breast cancer risk. Statistical significance was set at .

3. Results

3.1. Association of BCL-2 (-938C>A) Polymorphism with Breast Cancer

The genotype and allele frequencies of BCL-2 (-938C>A) polymorphism in cases and control are summarized in Table 2. The frequencies of CC, AC, and AA genotypes were 29.05%, 47.86%, and 23.07% in cases and 28.84%, 49.03%, and 22.11% in controls, respectively. The statistical analysis of observed genotypic frequencies did not show significant association (-0.980). Similarly, there was no significant difference in allele frequencies between cases and control (-0.937). Also, we did not find any significant association between BCL-2(-938C>A) polymorphism and breast cancer risk under recessive, dominant, and codominant models.


Genotype/alleleCases (n = 117)Control (n = 104)Odd ratio (95% CI) value

CC34 (29.05%)30 (28.84%)RefRef
AC56 (47.86%)51 (49.03%)0.968 (0.521–1.801)0.920
AA27(23.07%)23 (22.11%)1.035(0.493–2.175)0.925
value 0.980
Recessive modelAA27231.05 (0.56–1.98)0.864
AC+CC9081
Dominant modelAC+AA83740.98 (0.55–1.77)0.972
CC3430
Codominant modelAC56510.95 (0.56–1.61)0.861
CC+AA6153
Allele
C124 (52.99%)111 (53.37%)1.01 (0.69–1.47)0.937
A110 (47.01%)97 (46.63%)

OR: odds ratio, CI: confidence interval, and n: number of samples.
3.2. Association of BAX (-248G>A) Polymorphism with Breast Cancer

The frequencies of GG, AG, and AA genotypes in cases and controls were 79.48%, 17.09%, and 3.41%, and 77.88%, 18.26%, and 3.84%, respectively (Table 3). The statistical analysis of observed genotypic frequencies did not show significant association (-0.956). Similarly, no significant difference was observed in allele frequencies between cases and control (-0.747). Also, there was no significant relationship between BAX (-248G>A) polymorphism and risk of breast cancer under recessive, dominant and codominant models.


Genotype/alleleCases (n = 117)Control (n = 104)Odd ratio (95% CI) value

GG93 (79.48%)81 (77.88%)RefRef
AG20 (17.09%)19 (18.26%)0.916 (0.457–1.837)0.806
AA4 (3.41%)4 (3.84%)0.871 (0.211–3.594)0.848
value -0.956
Recessive modelAA440.88 (0.21–3.63)0.865
AG + GG113100
Dominant modelAG + AA24230.90 (0.47 to 1.73)0.771
GG9381
Codominant modelAG20190.92 (0.46–1.84)0.819
GG + AA9785
Allele
G206 (88.03%)181 (87.02%)0.91 (0.51 to 1.60)0.747
A28 (11.97%)27 (12.98%)

OR: odds ratio, CI: confidence interval, and n: number of samples.
3.3. Association of HER2 Ile655Val Polymorphism with Breast Cancer

The genotype and allele frequencies of HER2 Ile655Val polymorphism in cases and control are summarized in Table 4. The genotype frequencies for Ile/Ile (A/A), Ile/Val (A/G), and Val/Val (G/G) were 55.55%, 37.60%, and 6.83% in cases and 75.96%, 21.15%, and 2.88% in controls, respectively. With reference to Ile/Ile (A/A) genotype, frequency of Ile/Val (A/G) genotype was significantly higher among cases than in control group and observed to increase the breast cancer risk (OR, 2.43; 95% CI, 1.32–4.46; p-0.004). The statistical analysis of observed genotypic frequencies showed significant association (p-0.0059). The frequency of Val (G) allele was significantly higher in cases as compared to controls (6.83% vs 2.88%, resp.). Compared to Ile (A) allele, significant increase in the risk of breast cancer was observed with Val (G) allele (OR, 2.21; 95% CI, 1.35–3.63; p-0.0016).We observed significant association between HER2 Ile655Val polymorphism and breast cancer risk under the dominant (OR = 2.52; 95% CI: 1.41–4.51; -0.001) and codominant (OR, 2.24; 95% CI: 1.23–4.09; -0.008) model, whereas no significant relationship was found under the recessive model (OR, 2.47; 95% CI: 0.63–9.57; -0.190).


Genotype/alleleCases (n = 117)Control (n = 104)Odd ratio (95% CI) value

Ile(A)/Ile(A)65 (55.55%)79 (75.96%)RefRef
Ile(A)/Val(G)44 (37.60%)22 (21.15%)2.43 (1.32–4.46)0.004
Val(G)/Val(G)8 (6.83%)3 (2.88%)3.24 (0.82–12.7)0.091
value 0.0059
Recessive modelGG832.47 (0.63–9.57)0.190
AG + AA109101
Dominant modelAG + GG52252.52 (1.41–4.51)0.001
AA6579
Codominant modelAG44222.24 (1.23–4.09)0.008
AA + GG7382
Allele
Ile (A)174 (74.36%)180 (86.54%)2.21 (1.35–3.63)0.0016
Val (G)60 (25.64%)28 (13.46%)

n: number of samples, OR: odds ratio, and CI: confidence interval. Significant at  < 0.05.
3.4. Relationship of BCL-2 (−938C>A), BAX (−248G>A), and HER2 Ile655Val Polymorphism with Tumor Grade

In this present study, we reported no significant association of the BCL-2 (−938C>A), BAX (−248G>A), and HER2 Ile655Val polymorphism with tumor grade (Table 5).


GenotypeTumor grade ITumor grade IITumor grade III value

BCL-2 (-938C>A)C/C10 (30.30%)17 (28.33%)7 (29.16%)0.980
A carrier (AC + AA)23 (69.69%)43 (71.66%)17 (70.83%)

BAX (-248G>A)G/G24 (72.72%)47 (78.33%)22 (91.67%)0.206
A carrier (AG + AA)9 (27.27%)13 (21.66%)2 (8.33%)

HER2 Ile655ValIle(A)/Ile(A)21 (63.64%)32 (53.33%)12 (50%)0.523
Val (G) carrier (AG + GG)12 (36.36%)28 (46.66%)12 (50%)

4. Discussion

Apoptosis is highly programmed cell death and has a significant role in functionality and development of multicellular organism. Damaged and redundant cells are eliminated by activation of apoptosis through various physiological or pathological death signals for maintaining homeostasis [14]. Apoptosis can be attained through two main pathways: mitochondrial pathway and death-receptor pathway and both are propagated through a caspase cascade which results into activation of apoptosis [15, 16]. During carcinogenesis, apoptosis is evaded by three different mechanisms: caspase activity loss, disturbed death receptors signaling, and imbalance between proapoptotic and antiapoptotic proteins [1720].

BCL-2 protein plays significant function in the regulation of apoptosis and cell cycle delay. BCL-2 overexpression is found to be associated with different types of cancers such as prostate cancer, chronic lymphocytic leukemia, non-small cell lung cancer, breast cancer, esophageal cancer, lung cancer, and endometrial cancer [2125]. Dysregulation of apoptosis due to imbalances in BAX/BCL-2 levels may result in breast cancer pathogenesis [26]. In our study, there was no significance difference in the allelic and genotype frequency of the BCL-2 (−938C>A) polymorphism between cases and controls. We observed no significant relationship between BCL-2 (−938C>A) polymorphism and risk of breast cancer under recessive, dominant, and codominant model. Our results showed that BCL-2 (−938C>A) polymorphism was not associated with breast cancer risk. The findings of our study showed discrepancy from a study from Hyderabad, India, which reported the association of AA genotype with increased risk (AAVs AC + CC) for breast cancer by 2.86-fold (p-0.07) and the frequency of A allele was also increased in the breast cancer cases than in controls (95 % CI, 1.41 (0.97–2.04) p-0.06) [14]. Similarly, another study also found that AA genotype of BCL-2 (−938C>A) may be associated with breast cancer susceptibility and increase the breast cancer risk in Chinese women [27], which was also inconsistent with our findings.

BAX is a proapoptotic protein which controls apoptosis through regulation of mitochondrial outer membrane permeabilization [28]. In numerous cancers, protein expression and function are found to be affected by mutations in the promoter and coding regions of the BAX gene [29]. Genetic alterations in the BAX gene may play important role in cancer initiation and progression as it contains series of target genes involving various tumor suppressor genes and oncogenes [3034]. In the current study, we did not observe statistically significant difference in the genotype and allele frequencies of BAX (−248G>A) polymorphism among cases and control. No significant association was found between BAX (−248G>A) polymorphism and breast cancer under recessive, dominant, and codominant model. We failed to find an association between BAX (−248G>A) polymorphism and breast cancer risk. Our results were in concordance with a study conducted by Yildiz et al. [35] where no significant difference was observed in genotype and allele frequencies for BAX(−248G>A) among breast cancer patients and controls in Turkish women. Similarly, a meta-analysis study conducted by Sahu and Choudhuri on seven independent case-control studies (1772 cases and 1708 controls) did not find any association of BAX(−248G>A) genotype and allele frequency with human cancer risk under different genetic models [36].

SNP at codon 655 of the HER2 gene shows isoleucine (ATC) to valine (GTC) substitution (I655V) in the transmembrane domain-coding region and was found to be associated with breast cancer risk [37]. HER2 belongs to epidermal growth factor receptor (EGFR) family and has intrinsic tyrosine kinase activity [38]. The members of this family regulate various cellular functions like differentiation and proliferation as they play significant function in signal transduction pathway [39]. Dimerization of the HER receptors leads to the activation of signaling pathways [40]. HER2 appears to be the favored heterodimerization partner for all HER members [41]. HER2 triggers various cellular signaling pathways involving mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K) cascades [42]. In our study, the allelic frequency and genotype distribution of HER2 Ile655Val polymorphism exhibited significant difference between cases and controls. We found significant association between HER2 Ile655Val polymorphism and breast cancer risk under the dominant and codominant model. This present study is the first one to show significant association between HER2 Ile655Val polymorphism and risk of breast cancer in Indian population, suggesting the potential role of this polymorphism in development of breast cancer. Previously, a meta-analysis study by Tao et al. [43] in overall analysis found that Val allele frequency was significantly higher in breast cancer cases than in controls (OR = 1.1, 95% CI 1–1.2, p-0.04) on 20 eligible reports of 10,642 cases and 11,259 controls. Xie et al. [37] also reported that HER2 Ile655Val polymorphism may be a susceptibility biomarker for breast cancer among younger Chinese women. Furthermore, finding of our study was in accordance with previous studies in which presence of Val allele in HER2 polymorphism was associated with breast cancer risk among Portuguese [44] and Slovak populations [45].

In the Brazilian population, HER2 Ile655Val polymorphism was suggested as a candidate marker for breast cancer susceptibility, although negatively associated with breast cancer susceptibility [46]. Similarly, Parvin et al. [47] showed association of HER2 rs1136201 polymorphisms with breast cancer in Bangladesh population. Moreover, Ozturk et al. [48] also suggested Ile/Val genotype of HER2 may act as a genetic risk factor for breast cancer in Turkish population.

Our finding was inconsistent with the previous studies which did not find any association of Her2 Ile655Val gene polymorphisms with the breast cancer risk in Turkish [4951], Korean [52], Malaysian [53], and Iranian [54] populations. Many studies suggested that HER2V655 allele is not a risk factor for breast cancer in British population [55] and Caucasians, African–Americans, or Latinas [56]. Another meta-analysis study by Dahabreh and Murray also reported no association between HER2 Ile655Val polymorphism and breast cancer development which was based on 33 case-control studies including 20,461 cases and 23,832 controls [57]. Likewise, in a previous study from our group [58], we found no significant association of HER2 Ile655Val polymorphism with colorectal cancer in Indian population.

There were some limitations in the present study. Firstly, the sample size was small. Indian population is thought to be most diverse due to different sociocultural traditions. A single larger study with diverse sample size may help us in better understanding the association of the genetic variation of these genes with breast cancer risk. Secondly, the gene-environment and gene-gene interactions have not been taken into account. Combination of gene-environment interactions and gene polymorphisms should be taken into consideration to better understand the genetic background of breast cancer. Further studies on larger sample size are needed to confirm our findings.

5. Conclusion

In conclusion, the present case-control study concludes that BCL-2 (-938C>A) and BAX (-248G>A) polymorphism were not significantly associated with breast cancer risk. This current study for the first time revealed significant association of HER2 Ile655Val polymorphism with high risk of breast cancer in Indian population. These genetic risk factors identification can be useful in predicting the occurrence of breast cancer and defining high risk individuals. Hence, we suggest that each population need to evaluate its own genetic profile for breast cancer risk that may be helpful for better understanding the racial and geographic differences reported for breast cancer incidence and mortality.

Abbreviations

BCL-2:B -cell leukemia/lymphoma 2
BAX:BCL-2-associated X protein
HER2:Human epidermal growth factor receptor 2
IDC:Infiltrating ductal carcinoma
NOS:Not otherwise specified
PCR-RFLP:Polymerase chain reaction-restriction fragment length polymorphism
OR:Odds ratio
CI:Confidence interval
SNP:Single nucleotide polymorphism
EGFR:Epidermal growth factor receptor
MAPK:Mitogen-activated protein kinase
PI3K:Phosphatidylinositol 3-kinase.

Data Availability

The datasets used and/or analyzed during the present study are available from the corresponding author.

Additional Points

(i) BCL-2 (-938C>A) and BAX (-248G>A) polymorphism were not associated with breast cancer risk. (ii) Significant association of HER2 Ile655Val polymorphism with risk of breast cancer indicates the potential role of this polymorphism in development of breast cancer. (iii) No significant association of the BCL-2 (-938C>A), BAX (-248G>A), and HER2 Ile655Val polymorphism was found with tumor grade.

Ethical Approval

Institute Ethics Committee of GKV (Proposal no. 27/07/2017/GKV/IEC/2017) approved the present study.

A written informed consent before inclusion was obtained from all the participants of the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Authors’ Contributions

Amit Kumar Verma and Deepti Bhatt contributed equally to this work. K. Dev contributed to conceptualization; D. Bhatt, A. K. Verma, and K. Dev contributed to methodology, formal analysis, and data curation; D. Bhatt, A. K. Verma, and P. S. Bharti contributed to software; K. Dev and A. H. Rahmani performed validation; D. Bhatt and A. K. Verma contributed to writing the original draft; Y. Goyal, K. Dev, A. Almatroudi, M. A. Alsahli, and P. S. Bharti reviewed and edited the article; K. Dev and P. C. Joshi performed visualization and supervision; M. M. Alam, I. Ahmad, S. Almatroodi, and G. S. Zaman performed revision and review.

Acknowledgments

The authors are thankful to the Deanship of Scientific Research, King Khalid University, Abha, Saudi Arabia, for financially supporting this work through the General Research Project under Grant no. R.G.P.2/205/42.

References

  1. F. Bray, J. Ferlay, I. Soerjomataram, R. L. Siegel, L. A. Torre, and A. Jemal, “Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries,” CA: A Cancer Journal for Clinicians, vol. 68, no. 6, pp. 394–424, 2018. View at: Publisher Site | Google Scholar
  2. National Cancer Registry Programme, Three-year Report of Population Based Cancer Registries: 2012–2014, Chapter-10 Trends over Time for All Sites and on Selected Sites of Cancer and Projection of Burden of Cancer, Indian Council of Medical Research, New Delhi, India, 2016.
  3. P. L. Porter, “Global trends in breast cancer incidence and mortality,” Salud Pública de México, vol. 51, pp. s141–s146, 2009. View at: Publisher Site | Google Scholar
  4. J. Voortman, J.-H. Lee, J. K. Killian et al., “Array comparative genomic hybridization-based characterization of genetic alterations in pulmonary neuroendocrine tumors,” Proceedings of the National Academy of Sciences, vol. 107, no. 29, pp. 13040–13045, 2010. View at: Publisher Site | Google Scholar
  5. L. N. AL-Eitan, D. M. Rababa’h, M. A. Alghamdi, and R. H. Khasawneh, “Correlation between candidate single nucleotide variants and several clinicopathological risk factors related to breast cancer in Jordanian women: a genotype-phenotype study,” Journal of Cancer, vol. 10, no. 19, pp. 4647–4654, 2019. View at: Publisher Site | Google Scholar
  6. S. Nowsheen, K. Aziz, M. I. Panayiotidis, and A. G. Georgakilas, “Molecular markers for cancer prognosis and treatment: have we struck gold?” Cancer Letters, vol. 327, no. 1-2, pp. 142–152, 2012. View at: Publisher Site | Google Scholar
  7. R. Kumar, R. K. Vadlamudi, and L. Adam, “Apoptosis in mammary gland and cancer,” Endocrine-related Cancer, vol. 7, no. 4, pp. 257–269, 2000. View at: Publisher Site | Google Scholar
  8. S. Cory and J. M. Adams, “The Bcl2 family: regulators of the cellular life-or-death switch,” Nature Reviews Cancer, vol. 2, no. 9, p. 647, 2002. View at: Publisher Site | Google Scholar
  9. Y. Tsujimoto, J. Gorham, J. Cossman, E. Jaffe, and C. Croce, “The t(14;18) chromosome translocations involved in B-cell neoplasms result from mistakes in VDJ joining,” Science, vol. 229, no. 4720, pp. 1390–1393, 1985. View at: Publisher Site | Google Scholar
  10. S. S. Apte, M.-G. Mattei, and B. R. Olsen, “Mapping of the human BAX gene to chromosome 19q13.3-q13.4 and isolation of a novel alternatively spliced transcript, BAXδ,” Genomics, vol. 26, no. 3, pp. 592–594, 1995. View at: Publisher Site | Google Scholar
  11. T. Akiyama, C. Sudo, H. Ogawara, K. Toyoshima, and T. Yamamoto, “The product of the human c-erbB-2 gene: a 185-kilodalton glycoprotein with tyrosine kinase activity,” Science, vol. 232, no. 4758, pp. 1644–1646, 1986. View at: Publisher Site | Google Scholar
  12. S. Tommasi, V. Fedele, R. Lacalamita et al., “Molecular and functional characteristics of erbB2 in normal and cancer breast cells,” Cancer Letters, vol. 209, no. 2, pp. 215–222, 2004. View at: Publisher Site | Google Scholar
  13. Y. Yarden, “Biology of HER2 and its importance in breast cancer,” Oncology, vol. 61, no. 2, pp. 1–13, 2001. View at: Publisher Site | Google Scholar
  14. P. Bhushann Meka, S. Jarjapu, S. K. Vishwakarma et al., “Influence of BCL2-938 C>A promoter polymorphism and BCL2 gene expression on the progression of breast cancer,” Tumor Biology, vol. 37, no. 5, pp. 6905–6912, 2016. View at: Publisher Site | Google Scholar
  15. J. F. R. Kerr, A. H. Wyllie, and A. R. Currie, “Apoptosis: a basic biological phenomenon with wide ranging implications in tissue kinetics,” British Journal of Cancer, vol. 26, no. 4, pp. 239–257, 1972. View at: Publisher Site | Google Scholar
  16. G. Majno and I. Joris, “Apoptosis, oncosis, and necrosis. An overview of cell death,” American Journal of Pathology, vol. 146, no. 1, pp. 3–15, 1995. View at: Google Scholar
  17. N. N. Danial and S. J. Korsmeyer, “Cell death,” Cell, vol. 116, no. 2, pp. 205–219, 2004. View at: Publisher Site | Google Scholar
  18. M. A. O’Brien and R. Kirby, “Apoptosis: a review of pro-apoptotic and anti-apoptotic pathways and dysregulation in disease,” Journal of Veterinary Emergency and Critical Care, vol. 18, no. 6, pp. 572–585, 2008. View at: Publisher Site | Google Scholar
  19. P. Schneider and J. Tschopp, “Apoptosis induced by death receptors,” in Pharmacochemistry Library, U. Gulini, M. Gianella, W. Quaglia, and G. Marucci, Eds., vol. 31, pp. 281–286, Elsevier, Amsterdam, Netherlands, 2000. View at: Google Scholar
  20. R. S. Wong, “Apoptosis in cancer: from pathogenesis to treatment,” Journal of Experimental & Clinical Cancer Research, vol. 30, no. 1, p. 87, 2011. View at: Publisher Site | Google Scholar
  21. V. K. Anagnostou, F. J. Lowery, V. Zolota et al., “High expression of BCL-2 predicts favorable outcome in non-small cell lung cancer patients with non squamous histology,” BMC Cancer, vol. 10, no. 1, p. 186, 2010. View at: Publisher Site | Google Scholar
  22. N. Bonnefoy-Berard, A. Aouacheria, C. Verschelde, L. Quemeneur, A. Marçais, and J. Marvel, “Control of proliferation by Bcl-2 family members,” Biochimica et Biophysica Acta (BBA)-Molecular Cell Research, vol. 1644, no. 2-3, pp. 159–168, 2004. View at: Publisher Site | Google Scholar
  23. R. E. Davis and L. M. Staudt, “Molecular diagnosis of lymphoid malignancies by gene expression profiling,” Current Opinion in Hematology, vol. 9, no. 4, pp. 333–338, 2002. View at: Publisher Site | Google Scholar
  24. M. I. Johnson, M. C. Robinson, C. Marsh, C. N. Robson, D. E. Neal, and F. C. Hamdy, “Expression of Bcl-2, bax, and p53 in high-grade prostatic intraepithelial neoplasia and localized prostate cancer: relationship with apoptosis and proliferation,” The Prostate, vol. 37, no. 4, pp. 223–229, 1998. View at: Publisher Site | Google Scholar
  25. M. Sánchez-Beato, A. Sánchez-Aguilera, and M. A. Piris, “Cell cycle deregulation in B-cell lymphomas,” Blood, vol. 101, no. 4, pp. 1220–1235, 2003. View at: Publisher Site | Google Scholar
  26. S. Rehman, J. Crow, and P. A. Revell, “Bax protein expression in DCIS of the breast in relation to invasive ductal carcinoma and other molecular markers,” Pathology & Oncology Research, vol. 6, no. 4, pp. 256–263, 2000. View at: Publisher Site | Google Scholar
  27. N. Zhang, X. Li, K. Tao et al., “BCL-2 (-938C>A) polymorphism is associated with breast cancer susceptibility,” BMC Medical Genetics, vol. 12, no. 1, p. 48, 2011. View at: Publisher Site | Google Scholar
  28. A. Antignani and R. J. Youle, “How do bax and bak lead to permeabilization of the outer mitochondrial membrane?” Current Opinion in Cell Biology, vol. 18, no. 6, pp. 685–689, 2006. View at: Publisher Site | Google Scholar
  29. O. Moshynska, K. Sankaran, and A. Saxena, “Molecular detection of the G(-248)A BAX promoter nucleotide change in B cell chronic lymphocytic leukaemia,” Molecular Pathology, vol. 56, no. 4, pp. 205–209, 2003. View at: Publisher Site | Google Scholar
  30. G. Dewson and R. M. Kluck, “Mechanisms by which bak and bax permeabilise mitochondria during apoptosis,” Journal of Cell Science, vol. 122, no. 16, pp. 2801–2808, 2009. View at: Publisher Site | Google Scholar
  31. H. Kim, H.-C. Tu, D. Ren et al., “Stepwise activation of BAX and BAK by tBID, BIM, and PUMA initiates mitochondrial apoptosis,” Molecular Cell, vol. 36, no. 3, pp. 487–499, 2009. View at: Publisher Site | Google Scholar
  32. T. Kuwana, L. Bouchier-Hayes, J. E. Chipuk et al., “BH3 domains of BH3-only proteins differentially regulate bax-mediated mitochondrial membrane permeabilization both directly and indirectly,” Molecular Cell, vol. 17, no. 4, pp. 525–535, 2005. View at: Publisher Site | Google Scholar
  33. L. Ming, P. Wang, A. Bank, J. Yu, and L. Zhang, “PUMA dissociates bax and bcl-XL to induce apoptosis in colon cancer cells,” Journal of Biological Chemistry, vol. 281, no. 23, pp. 16034–16042, 2006. View at: Publisher Site | Google Scholar
  34. T. Miyashita, S. Krajewski, M. Krajewska et al., “Tumor suppressor p53 is a regulator of bcl-2 and bax gene expression in vitro and in vivo,” Oncogene, vol. 9, no. 6, pp. 1799–1805, 1994. View at: Google Scholar
  35. Y. Yildiz, “Bax promoter G(-248)A polymorphism in a Turkish clinical breast cancer patients: A case-control study,” American Journal of Molecular Biology, vol. 3, no. 1, pp. 10–16, 2013. View at: Publisher Site | Google Scholar
  36. S. K. Sahu and T. Choudhuri, “Lack of association between bax promoter (-248G>A) single nucleotide polymorphism and susceptibility towards cancer: evidence from a meta-analysis,” PLoS ONE, vol. 8, no. 10, Article ID e77534, 2013. View at: Publisher Site | Google Scholar
  37. D. Xie, “Population-based, case-control study of HER2 genetic polymorphism and breast cancer risk,” Journal of the National Cancer Institute, vol. 92, no. 5, pp. 412–417, 2000. View at: Publisher Site | Google Scholar
  38. M. Tan and D. Yu, “Molecular mechanisms of erbB2-mediated breast cancer chemoresistance,” Advances in Experimental Medicine and Biology, vol. 608, pp. 119–129, 2007. View at: Publisher Site | Google Scholar
  39. S. Goel, S. Mani, and R. Perez-Soler, “Tyrosine kinase inhibitors: a clinical perspective,” Current Oncology Reports, vol. 4, no. 1, pp. 9–19, 2002. View at: Publisher Site | Google Scholar
  40. U. Eppenberger and H. Mueller, “Growth factor receptors and their ligands,” Journal of Neuro-Oncology, vol. 22, no. 3, pp. 249–254, 1994. View at: Publisher Site | Google Scholar
  41. Y. Yarden and G. Pines, “The ERBB network: at last, cancer therapy meets systems biology,” Nature Reviews Cancer, vol. 12, no. 8, p. 553, 2012. View at: Publisher Site | Google Scholar
  42. R. Nahta, D. Yu, M.-C. Hung, G. N. Hortobagyi, and F. J. Esteva, “Mechanisms of disease: understanding resistance to HER2-targeted therapy in human breast cancer,” Nature Clinical Practice Oncology, vol. 3, no. 5, p. 269, 2006. View at: Publisher Site | Google Scholar
  43. W. Tao, C. Wang, R. Han, and H. Jiang, “HER2 codon 655 polymorphism and breast cancer risk: a meta-analysis,” Breast Cancer Research and Treatment, vol. 114, no. 2, pp. 371–376, 2009. View at: Publisher Site | Google Scholar
  44. D. Pinto, A. Vasconcelos, S. Costa et al., “HER2 polymorphism and breast cancer risk in Portugal,” European Journal of Cancer Prevention, vol. 13, no. 3, pp. 177–181, 2004. View at: Publisher Site | Google Scholar
  45. P. Žúbor, “HER-2 [Ile655Val] polymorphism in association with breast cancer risk: a population-based case-control study in Slovakia,” Neoplasma, vol. 53, no. 1, pp. 49–55, 2006. View at: Google Scholar
  46. F. C. de Almeida, “HER2 Ile655Val polymorphism is negatively associated with breast cancer susceptibility,” Journal of Clinical Laboratory Analysis, vol. 32, no. 6, Article ID e22406, 2018. View at: Publisher Site | Google Scholar
  47. S. Parvin, M. S. Islam, M. M. A. Al-Mamun et al., “Association of BRCA1, BRCA2, RAD51, and HER2 gene polymorphisms with the breast cancer risk in the Bangladeshi population,” Breast Cancer, vol. 24, no. 2, pp. 229–237, 2017. View at: Publisher Site | Google Scholar
  48. O. Oztürk, E. Canbay, O. T. Kahraman et al., “HER2 Ile655Val and PTEN IVS4 polymorphisms in patients with breast cancer,” Molecular Biology Reports, vol. 40, no. 2, p. 1813, 2012. View at: Publisher Site | Google Scholar
  49. E. Akisik and N. Dalay, “Estrogen receptor codon 594 and HER2 codon 655 polymorphisms and breast cancer risk,” Experimental and Molecular Pathology, vol. 76, no. 3, pp. 260–263, 2004. View at: Publisher Site | Google Scholar
  50. N. Kara, N. Karakus, A. N. Ulusoy, C. Ozaslan, B. Gungor, and H. Bagci, “P53 codon 72 and HER2 codon 655 polymorphisms in Turkish breast cancer patients,” DNA and Cell Biology, vol. 29, no. 7, pp. 387–392, 2010. View at: Publisher Site | Google Scholar
  51. E. Sezgin, F. I. Sahin, M. C. Yagmurdur, and B. Demirhan, “HER-2/neu gene codon 655 (Ile/Val) polymorphism in breast carcinoma patients,” Genetic Testing and Molecular Biomarkers, vol. 15, no. 3, pp. 143–146, 2011. View at: Publisher Site | Google Scholar
  52. H. J. An, N. K. Kim, D. Oh et al., “Her2 V655 genotype and breast cancer progression in Korean women,” Pathology International, vol. 55, no. 2, pp. 48–52, 2005. View at: Publisher Site | Google Scholar
  53. R. Naidu, C. H. Yip, and N. A. Taib, “Polymorphisms of HER2 Ile655Val and cyclin D1 (CCND1) G870A are not associated with breast cancer risk but polymorphic allele of HER2 is associated with nodal metastases,” Neoplasma, vol. 55, no. 2, pp. 87–95, 2008. View at: Google Scholar
  54. E. Kamali-Sarvestani, A.-R. Talei, and A. Merat, “Ile to Val polymorphism at codon 655 of HER-2 gene and breast cancer risk in Iranian women,” Cancer Letters, vol. 215, no. 1, pp. 83–87, 2004. View at: Publisher Site | Google Scholar
  55. S. W. Baxter and I. G. Campbell, “Re: population-based, case-control study of HER2 genetic polymorphism and breast cancer risk,” JNCI Journal of the National Cancer Institute, vol. 93, no. 7, pp. 557-558, 2001. View at: Publisher Site | Google Scholar
  56. C. Keshava, E. C. McCanlies, N. Keshava, M. S. Wolff, and A. Weston, “Distribution of HER2V655 genotypes in breast cancer cases and controls in the United States,” Cancer Letters, vol. 173, no. 1, pp. 37–41, 2001. View at: Publisher Site | Google Scholar
  57. I. J. Dahabreh and S. Murray, “Lack of replication for the association between HER2 I655V polymorphism and breast cancer risk: a systematic review and meta-analysis,” Cancer Epidemiology, vol. 35, no. 6, pp. 503–509, 2011. View at: Publisher Site | Google Scholar
  58. R. Hasan, D. Bhatt, S. Khan et al., “Frequency of I655V SNP of HER-2/neu in colorectal cancer: a study from India,” 3 Biotech, vol. 9, no. 1, p. 11, 2019. View at: Publisher Site | Google Scholar

Copyright © 2021 Deepti Bhatt et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views141
Downloads156
Citations

Related articles