Pilot Study to Determine Prevalence of CYP2B6*6,CYP2C19*2 and CYP2C19*3 in Breast Cancer Patients Versus Normal Healthy Controls Among Three Major Ethnic Groups in Singapore

doi:10.21203/rs.3.rs-1019029/v1

Background: Breast cancer is the top cancer suffered by women worldwide and has been identified to be the greatest killer for women living in Singapore. Unfortunately, most of breast cancer cases were detected only at later stage of disease development. This has crippled the effort of breast cancer therapy. As early detection of breast cancer could greatly improve the outcome of breast cancer therapy, it is of utmost importance to identify relevant biomarkers at the primitive stage of breast cancer development before the transformation of normal breast cells into cancerous cells. These biomarkers provide important clues leading to an efficient and targeted treatment approach in breast cancer preventive care.

Methods: 455 breast cancer patients were consented to join this study. Buccal swabs were collected for genotyping on CYP2B6*6, CYP2C19 *2 & CYP2C19*3. The genotyping data were then compared to data collected from healthy individuals. Clinical data were collected from patient notes and analysed. All the statistical analyses were done using SPSS statistical software, version 19.0. Chi-square or Fisher’s Exact test were performed to examine the difference between subject’s characteristics for categorical variables and One-Way Anova was performed to assess age difference across alleles of CYP2B6*6, CYP2C19*2 and CYP2C19*3. Binary logistics regression was performed to identify demographic factors associated with breast cancer.

Results: We reported thatCYP2B6*6 could be a risk factor leading to earlier onset of breast cancer among Indian population with OR found to be 1.69 (95% C.I.= 0.549-5.191, p=0.359). In the case of CYP2C19*2, OR is 1.57 for Malay (95% C.I. = 0.696-3.522, p=0.278); 1.15 for Chinese population (95% C.I. =0.862-1.545, p=0.335) and 1.03 for Indian (95% C.I. =0.301-3.496, p=0.968). CYP2C19*3 OR in Chinese population is 1.34 (95% C.I. =0.830-2.155, p=0.231) and 0.77 (95% C.I. =0.172-3.394, p=0.724) for Malay population. No CYP2C19*3 was detected in both cohorts of Indian patients and healthy controls.

Conclusions: CYP2B6*6 and CYP2C19*2 polymorphisms may confer a risk for breast cancer development in Singaporean breast cancer patients. This is an exploratory study to identify potential breast cancer susceptibility gene polymorphisms, a bigger sample size study could be done to corroborate these findings in future studies.

Cancer Biology

single nucleotide polymorphisms

chemotherapy

breast cancer

biomarkers

aromatase inhibitor

According to statistics from the Singapore Cancer Registry Annual Report 2018, breast cancer was the most common cancer (29.3%) among Singaporean women followed by colon-rectal (13.3%) and lung cancers (7.5%) between 2014 and 2018. Besides, breast cancer was also reported to be the leading cause of death in cancers affecting women in Singapore during the same period. The age standardized mortality rate for breast cancer has increased from 5.7 per 100,000 in 1968-1972 to 12.6 per 100,000 population in 2014-2018 in tandem with increasing incidence rate.

Early detection of cancers plays an important role in reducing the mortality rate of cancers. However, breast cancer is usually detected at later stages of diseases. (1) The reliability of existing breast cancer biomarkers as an efficient means of detection needs to be reviewed. There is continuous effort to search for efficient breast cancer biomarkers as an early measure to detect breast cancer. At the same time, the biomarkers could serve as an important indicator for prognosis in breast cancer treatment.

CYP2B6 enzyme and CYP2C19 enzyme belong to cytochrome P450 (CYP450) metabolic enzymes which are categorized under phase I superfamily metabolic enzymes. Phase I and II enzymes are of particular interest with respect to breast cancer due to their involvement in the metabolism of steroid hormones, chemical carcinogens, and other environment toxicants. (2, 3) During phase I metabolism reaction, substrates usually undergo reduction, oxidation or hydroxylation to become more polar metabolites. CYP450 enzymes are the predominant mediators. (4) Usually, phase I metabolism is followed by phase II conjugation reactions whereby phase I metabolites, phase II exogenous or endogenous compounds are conjugated to a more polar molecule that produces inactive and water soluble compounds to be excreted by urine or bile. (5, 6) The combined phase I and phase II metabolism is mainly a detoxification and elimination process, however, both phases bear the risk of formation of toxic and highly reactive compounds which can induce or promote serious health problems such as cancer. (5, 7) Therefore, altered activity of metabolic enzyme holds the potential to increase the exposure to carcinogenic compounds and consequently the risk of tumor formation. (8)

In a recent study done by Germany investigators, CYP2B6*6 variant had an increased breast cancer risk with OR of 1.1 (p=0.027) (9). In 2016, Joanne Siok et al. discovered that CYP2C19*2, loss of function polymorphism, as well as the CYP2C19 H2 haplotype were found to be significantly associated with lower plasma concentrations of NorEND and lower formation rates of NorEND (10). NorEND is an active metabolite of tamoxifen that inhibits both aromatase and estrogen receptors, variability in its plasma concentration can potentially influence the therapeutic outcomes of tamoxifen therapy. These data suggest that CYP2C19 may potentially serve as a complementary biomarker for the identification of patients who may or may not benefit from tamoxifen treatment.

Another group of Chinese investigators in China has discovered a possible association of gene polymorphism of CYP2C19*3 with breast cancer in Chinese Han population. The OR for carriers of AG+AA genotype for breast cancer was 2.31 (95% confidence interval= 1.27-4.43) (11).

It has been known that elevated sex hormone levels (2fold increase) were found in women with breast cancer (12). This effect was attributed to estrogen-induced gene expression of factors involved in cell growth and division (13) as well as genotoxic action of metabolic compounds such as 4-hydroxy-catechol estrogens and estrogen-3, 4-quinones (14). Besides, progesterone also plays a part to hormone induced carcinogenesis by promotion of estrogen synthesis, expression of estrogen receptor and cell proliferation (15, 16). Aside from hormonal factors, environmental carcinogenic factors like tobacco smoke, and genetic factors such as mutation and polymorphisms all contribute to breast cancer susceptibility. A family study on genetic basis of breast cancer indicated 2 fold increased risk in the first degree relatives of women with the disease (17). In 1990, BRCA1 and BRCA 2 were identified as two major breast cancer susceptibility genes (18). Harmful mutations in these two genes confer to a cumulative disease risk by age 70 years of 65 and 45%, respectively (19). Recent genome wide association studies revealed strong evidence for more than 18 common breast cancer susceptibility alleles including FGFR2, CCND1, TNRC9, MAP3K1 and LSP1 (20). Most of these genes are related to DNA repair, cell cycle control, apoptosis, cell growth and division representing the most important pathways for the protection of cells against carcinogenic processes. Low coverage of genes coding for phase I and phase II enzymes in commercial genotyping arrays and lack of well-designed studies have downplayed the roles of phase I and phase II enzymes play in conferring breast cancer risk (21).

Although, CYP2B6 contributes about 2-5% of the total liver cytochrome content, it is also expressed in extra-hepatic tissues such as the breast; notably with higher expression level in breast tumor than normal breast. (8, 22)

A study also indicated that, estrogen receptor (ER) positive breast tumours show a higher CYP2B6 levels than ER-negative tumors (23, 24). Impaired CYP2B6 activity had increased the level of both estradiol and testosterone whereby testosterone conferred a stronger influence on breast cancer risk than estradiol in postmenopausal women (25).

In this pilot study, we investigated the percentage of CYP2B6*6, CYP2C19*2 and CYP2C19*3 in our breast cancer patients against the healthy population in Singapore. At the same time, we examined the prevalence of these SNPs in different demographic groups for instance ethnicity, marital status, family history, use of hormone therapy, amongst others. Furthermore, characteristics of breast cancer were studied to unravel the distribution of these SNPs in different stages of breast cancer. Besides, the percentage of these SNPs in different treatments for breast cancer were also presented.

In total, 455 breast cancer patients were recruited from Changi General Hospital Breast Centre Outpatient Clinic. This study had been approved by local ethics committee (CIRB 2014/371/B). Written informed consent were obtained from all patients. Inclusion criteria for selection of study subjects were subject must have been diagnosed of having breast cancer at any stages and must be descendant of similar ethnicity through 3 generations, either Chinese, Malay or Indian. Besides, subject must be able to do buccal swab at inner lining of mouth. Clinical data were collected from patient notes. Ethnically matched healthy control data was gathered from healthy volunteer’s databank which was available from Singapore Breast Cancer Cohort Project. Buccal swab was obtained from each patient and genomic DNA was then extracted from the buccal swab by using E.Z.N.A. Blood DNA Mini Kit -buccal swabs protocol (Omega Bio-tek) based on manufacturer’s guideline. Laboratory genotyping analysis was performed on all samples for SNPs on CYP2B6*6, CYP2C19*2 * CYP2C19*3 using Taqman SNP assay kit and Taqman GT express Master Mix (Life Technologies). RT PCR was run on Step One Plus RT PCR Systems (Applied Biosystems). Details of SNPs are as indicated in Table 1.

Table 1

SNP investigated in this study

Gene	Ref. SNP ID	Genotype	Mutation
CYP2B6 *6	rs3745274	G516T	Gln172His
CYP2C19*2	rs4244285	G681A	Splice variant
CYP2C19*3	rs4986893	G636A	Trp212Ter

Statistics

All the statistical analyses were done using SPSS statistical software, version 19.0 (IBM Corp. Armonk, NY).Chi-square or Fisher’s Exact test were performed to examine the difference between subject’s characteristics for categorical variables and One-Way Anova was performed to assess age difference across alleles of CYP2B6*6, CYP2C19*2 and CYP2C19*3 Binary logistics regression was performed to identify demographic factors associated with breast cancer. A two-tailed, p-value <0.05 was predefined as statistically significant.

Study subjects’ demographic profile and medical history

A total of 455 breast cancer patients participated in this study. Among them, 365 are of Chinese origin, 45 Malays and 45 Indians. Participants aged from 20 to 89 years old with an average age of 51.5 years. 48% of them aged from 20 to 50 years old. It was found that the lowest age of breast cancer diagnosis for both CYP2B6*6 & CYP2C19*3 homozygous mutant genotype was around 41 years old as compared to a younger age at diagnosis for homozygous mutant CYP2C19*2 which was reported at 27 years old. Please refer to Tables 4(a) to 4 (c) which indicate distribution of participants’ ages for different variants studied:

BMI of participants ranged from 21.9(±0.07) to 25.7 (±0.83) kg/m² .81% of participants were post-menopausal. 74.7% were married women; 3.3% were divorced;18.5% were single and 3.5% were widowed. Majority of participants (94.1%) had never smoked before; 3.7% were former smokers and 2.2 % are current smokers. 92% of participants had never used hormone therapy and only 1% used hormone therapy. Similarly, 78% of participants had never used oral contraceptives in contrast to 1.8% who used oral contraceptives for more than 10 years. Most of the participants (77%) did not have first degree relatives with breast or ovarian cancer compared to 22% of participants who had first degree relatives with breast or ovarian cancer during the course of study. Table 2 shows the distribution of participants in the various breast cancer risk groups.

Table 2

showing distribution of subjects under different epidemiological breast cancer risk factors

Factors	Number	Percentage
Smoking Status
Never smoke	428	94.1
Former smoker	17	3.7
Current smoker	10	2.2

Status of Menopause
% pre-menopausal	88	19
% post-menopausal	367	81

Use of Hormone Therapy
Never use	419	92
>0<10 years	29	6
>10 years	5	1

Use of oral contraceptive
Never use	353	78
0-5 years	78	17
5-10 years	12	3
>10 years	8	2

1^st degree relative with breast or ovarian cancer
Yes	102	22
No	351	77

Marital Status
Married	340	74.7
Divorced	15	3.3
Single	84	18.5
Widowed	16	3.5

Age at diagnosis
20-30 years old	7	1.5
31-40 years old	49	10.8
41-50 years old	162	35.7
51-60 years old	153	33.7
61-70 years old	63	13.9
71-80 years old	18	4
81-90 years old	2	0.5

Genotyping results

The data analysis of the genotyping results revealed that CYP2B6*6 could be a risk factor leading to earlier onset of breast cancer among Indian population. A subgroup analysis with ethnicity was performed for genotyping CYP2B6*6, CYP219*2 and CYP2C19*3 with results as indicated in Table 3. It was discovered that Indian subjects with mutant allele “T” in CYP2B6*6 tend to have higher risk of getting breast cancer (OR: 1.69, 95%C.I.: 0.549- 5.191, P=0.359). Whereas Chinese and Malay subjects who have mutant allele in CYP2C19*2 are more likely to have breast cancer. (OR: 1.15, 95% C.I.:0.862-1.545, P=0.335; OR: 1.57, 95% C.I.:0.696-3.522, P=0.278 respectively)

Table 3

indicates odds ratio, 95% confidence interval and p-value for mutants CYP2B6*6 , CYP2C19*2, CYP2C19*3 in case-control study among 3 main races in Singapore

*CYP2B66**	Odds ratio		95% Confidence Interval				P-value
			Lower		Upper
Chinese	0.749		0.555		1.010		0.058
Malay	0.770		0.347		1.708		0.52
Indian	1.688		0.549		5.191		0.359

*CYP2C192**
Chinese		1.154		0.862		1.545		0.335
Malay		1.565		0.696		3.522		0.278
Indian		1.026		0.301		3.496		0.968

*CYP2C193**
Chinese		1.337		0.830		2.155		0.231
Malay		0.765		0.172		3.394		0.724
Indian		N.A.		N.A.		N.A.		N.A.

We also analysed the distribution of CYP2B6*6, CYP2C19*2 and CYP2C19*3 variants based on the epidemiological risk factors (Tables 4(a) to 4(c)).

Table 4

(a), (b), (c) Association between subjects’ characteristics and variants for genotype CYP2B6*6, CYP2C19*2 and CYP2C19*3

Table 4 (a) CYP2B6*6

CYP2B6*6 (c.516 G>T)

(n=455)

P value

GG (n=275)

GT (n=151)

TT (n=29)

Race

Chinese

Malay

Indian

235(64%)

22(51.2%)

18(40%)

117(31.9%)

14(32.6%)

20(44.4%)

15(4.1%)

7(16.3%)

7(15.6%)

<0.001

Age of onset

Min - Max age

51.71(±0.63)

21 - 81

51.0 (±0.88)

20 - 89

52.0 (±1.33)

41 - 77

0.771

Marital status

Married

Widow/ Divorced

Single

210(61.8%)

65(56.5%)

109(32.1%)

42(36.5%)

21(6.2%)

8(7.0%)

0.610

BMI

24.4(±0.28)

24.5(±0.41)

25.7(±0.83)

0.375

Menopause status

Pre-menopausal

Post-menopausal

50(56.8%)

225(61.3%)

31(35.2%)

120(32.7%)

7(8.0%)

22(6.0%)

0.670

Family history of at least one 1st degree relative with Breast or Ovarian Cancer

No

Yes

211(60.1%)

62(60.8%)

117(33.3%)

34(33.3%)

23(6.6%)

6(5.9%)

0.970

Use of oral contraceptives

Never

0 – 5 years

5 – 10 years

>10 years

214(60.6%)

49(62.8%)

6(50.0%)

4(50.0%)

116(32.9%)

26(33.3%)

4(33.3%)

4(50.0%)

23(6.5%)

3(3.8%)

2(16.7%)

0(0%)

0.611

Use of hormone therapy

Never

>0- <10 years

>10 years

252(60.1%)

16(55.2%)

5(100%)

138(32.9%)

13(44.8%)

0(0%)

29(6.9%)

0(0%)

0.157

Smoking status

Never

Former/ Current

259(60.7%)

15(55.6%)

141(33%)

10(37.0%)

27(6.3%)

2(7.4%)

0.870

Presence of Estrogen Receptor

Negative

Positive

68(61.8%)

199(60.3%)

35(31.8%)

109(33%)

7(6.4%)

22(6.7%)

0.961

Presence of Progesterone Receptor

Negative

Positive

100(66.2%)

165(58.5%)

42(27.8%)

98(34.8%)

9(6.0%)

19(6.7%)

0.285

ERBB2 status

Negative

Positive

Equivocal

151(60.6%)

85(59%)

11(64.7%)

79(31.7%)

52(36.1%)

5(29.4%)

19(7.6%)

7(4.9%)

1(5.9%)

0.776

Histological tumour type

Ductal non-specific

Lobular

Others

11(62.2%)

8(42.1%)

55(57.3%)

110(32.4%)

10(52.6%)

31(32.3%)

18(5.3%)

1(5.3%)

10(10.4%)

0.151

Tumour size

<20.0mm

20.0-49.9mm

50.0+mm

Multifocal

91(64.1%)

123(58.0%)

31(59.6%)

25(67.6%)

40(28.2%)

79(37.3%)

20(38.5%)

9(24.3%)

11(7.7%)

10(4.7%)

1(1.9%)

3(8.1%)

0.291

Tumour grade

I

II

III

42(62.7%)

105(59.7%)

113(60.1%)

22(32.8%)

64(36.4%)

58(30.9%)

3(4.5%)

7(4.0%)

17(9.0%)

0.283

Number of involved axillary lymph nodes

None

1-3

4+

170(60.5%)

54(60%)

38(62.3%)

96(34.2%)

30(33.3%)

20(32.8%)

15(5.3%)

6(6.7%)

3(4.9%)

0.987

Table 4 (b) CYP2C19*2

CYP2C19*2 (c.681G>A)

(n=455)

P value

AA (n=57)

GA (n=186)

GG (n=212)

Race

Chinese

Malay

Indian

42(11.4%)

5(11.6%)

10(22.2%)

149(40.6%)

15(34.9%)

22(48.9%)

176(48%)

23(53.5%)

13(28.9%)

0.076

Age of onset

Min - Max age

53.2(±1.31)

27 - 81

51.7(±0.79)

26 - 89

50.86(±0.69)

20 - 77

0.311

Marital status

Married

Widow/divorced/

Single

46(13.5%)

11(9.6%)

135(39.7%)

51(44.3%)

159(46.8%)

53(46.1%)

0.463

BMI

25.4(±0.64)

24.5(±0.37)

24.3(±0.32)

0.296

Menopause status

Pre-menopausal

Post-menopausal

10(11.4%)

47(12.8%)

33(37.5%)

153(41.7%)

45(51.1%)

167(45.5%)

0.636

Family history of at least one 1st degree relative with Breast or Ovarian Cancer

No

Yes

43(12.3%)

14(13.7%)

139(39.6%)

45(44.1%)

169(48.1%)

43(42.2%)

0.566

Use of oral contraceptives

Never

0 – 5 years

5 – 10 years

>10 years

49(13.9%)

6(7.7%)

2(16.7%)

0(0%)

144(40.8%)

33(42.3%)

2(16.7%)

4(50%)

160(45.3%)

39(50%)

8(66.7%)

4(50%)

0.38

Use of hormone therapy

Never

>0- <10 years

>10 years

51(12.2%)

5(17.2%)

1(20%)

167(39.9%)

14(48.3%)

3(60%)

201(48%)

10(34.5%)

1(20%)

0.471

Smoking status

Never

Former/current

53(12.4%)

4(14.8%)

174(40.7%)

11(40.7%)

200(46.8%)

12(44.4%)

0.929

Presence of Estrogen Receptor

Negative

Positive

16(14.5%)

39(11.8%)

45(40.9%)

136(41.2%)

49(44.5%)

155(47%)

0.742

Presence of Progesteron Receptor

Negative

Positive

21(13.9%)

33(11.7%)

61(40.4%)

119(42.2%)

69(45.7%)

130(46.1%)

0.793

ERBB2 status

Negative

Positive

Equivocal

33(13.3%)

19(13.2%)

1(5.9%)

105(42.2%)

55(38.2%)

7(41.2%)

111(44.6%)

70(48.6%)

9(52.9%)

0.823

Histological tumour type

Ductal non-specific

Lobular

Others

38(11.2%)

4(21.1%)

15(15.6%)

136(40.1%)

4(21.1%)

45(46.9%)

165(48.7%)

11(57.9%)

36(37.5%)

0.109

Tumour size

<20.0mm

20.0-49.9mm

50.0+mm

Multifocal

16(11.3%)

27(12.7%)

10(19.2%)

4(10.8%)

60(42.3%)

93(43.9%)

12(23.1%)

14(37.8%)

66(46.5%)

92(43.4%)

30(57.7%)

19(51.4%)

0.189

Tumour grade

I

II

III

7(10.4%)

26(14.8%)

19(10.1%)

31(46.3%)

71(40.3%)

74(39.4%)

29(43.3%)

79(44.9%)

95(50.5%)

0.514

Number of involved axillary lymph nodes

None

1-3

4+

35(12.5%)

6(6.7%)

14(23%)

119(42.3%)

38(42.2%)

18(29.5%)

127(45.2%)

46(51.1%)

29(47.5%)

0.036

Table 4 (c) CYP2C19*3

CYP2C19*3 (c.636G>A)

(n=454)

P value

AA (n=2)

GA (n=45)

GG (n=407)

Race

Chinese

Malay

Indian

2(0.5%)

0(0.0%)

42(11.5%)

3(7.0%)

0(0.0%)

322(88.0%)

40(93.0%)

45 (100.0%)

0.14

Age of onset

Min - Max age

52.5(±12.5)

40 - 65

50.6(±1.63)

30 - 75

51.6(±0.51)

20 - 89

0.813

Marital status

Married

Widow/ Divorced/

Single

2(0.6%)

0(0%)

27(7.9%)

18(15.8%)

311(91.5%)

96(84.2%)

0.039

BMI

21.9(±0.07)

24.5(±0.7)

24.5(±0.24)

0.743

Menopause status

Pre-menopausal

Post-menopausal

0 (0%)

2 (0.5%)

12 (13.6%)

33(9.0%)

76 (86.4%)

331(90.4%)

0.343

Family history of at least one 1st degree relative with Breast or Ovarian Cancer

No

Yes

2 (0.6%)

0(0%)

31 (8.8%)

14(13.9%)

318 (90.6%)

87(86.1%)

0.254

Use of oral contraceptives

Never

0 – 5 years

5 – 10 years

>10 years

1(0.3%)

0(0%)

1(8.3%)

0(0%)

32 (9.1%)

10(12.8%)

2(16.7%)

1(12.5%)

319(90.6%)

68(87.2%)

9(75%)

7(87.5%)

0.004

Use of hormone therapy

Never

>0- <10 years

>10 years

2(0.5%)

0(0%)

40(9.6%)

4(13.8%)

1(20.0%)

377(90.0%)

25(86.2%)

4(80.0%)

0.867

Smoking status

Never

Former/current

2 (0.5%)

0 (0%)

43(10.1%)

2(7.4%)

381(89.4%)

25(92.6%)

0.844

Presence of Estrogen Receptor

Negative

Positive

0(0%)

2(0.6%)

7 (6.4%)

37 (11.2%)

103(93.6%)

290(88.1%)

0.234

Presence of Progesteron Receptor

Negative

Positive

0(0%)

2(0.7%)

11(7.3%)

33(11.7%)

140(92.7%)

246(87.5%)

0.193

ERBB2 status

Negative

Positive

Equivocal

0(0%)

1(0.7%)

1(5.9%)

21(8.5%)

16(11.1%)

4(23.5%)

227(91.5%)

127(88.2%)

12(70.6%)

0.003

Histological tumour type

Ductal non-specific

Lobular

Others

2(0.6%)

0(0%)

33(9.7%)

2(10.5%)

10(10.5%)

304(89.7%)

17(89.5%)

85(89.5%)

0.948

Tumour size

<20.0mm

20.0-49.9mm

50.0+mm

Multifocal

0(0%)

1(0.5%)

0(0%)

1(2.7%)

18(12.8%)

16(7.5%)

5(9.6%)

6(16.2%)

123(87.2%)

195(92%)

47(90.4%)

30(81.1%)

0.160

Tumour grade

I

II

III

0(0%)

2(1.1%)

8(11.9%)

14(8.0%)

20(10.6%)

59(88.1%)

161(92%)

166(88.3%)

0.438

Number of involved axillary lymph nodes

None

1-3

4+

0(0%)

1(1.1%)

1(1.6%)

32(11.4%)

7(7.9%)

5(8.2%)

249(88.6%)

81(91%)

55(90.2%)

0.277

Breast cancer patients receiving different cancer treatments were categorized according to the variants in CYP2B6*6, CYP2C19*2 and CYP2C19*3, as shown in Table 5 (a) to Table 5 (c). Summary of variants found in patients receiving either chemotherapy or endocrine therapy were recorded in Table 6.

Table 5

(a), (b), (c) indicating percentage of CYP2B6*6, CYP2C19*2 & CYP2C19*3 variants found in patients receiving treatments for breast cancer

5 (a) CYP2B6*6

CYP2B6*6 (c.516 G>T)

(n=455)

P value

GG (n=275)

GT (n=151)

TT (n=29)

Adjuvant treatment R

No

Yes

32(65.3%)

243(59.9%)

12(24.5%)

139(34.2%)

5(10.2%)

24(5.9%)

0.255

Adjuvant Chemo

No

Yes

140(61.9%)

135(59.0%)

72(31.9%)

79(34.5%)

14(6.2%)

15(6.6%)

0.806

Adjuvant Radiotherapy

No

Yes

157(62.8%)

118(57.6%)

76(30.4%)

75(36.6%)

17(6.8%)

12(5.9%)

0.374

Adjuvant endocrine

No

Yes

99(65.1%)

176(58.1%)

42(27.6%)

109(36.0%)

11(7.2%)

18(5.9%)

0.2

Adjuvant Herceptin

No

Yes

238(60.4%)

37(60.7%)

131(33.2%)

20(32.8%)

25(6.3%)

4(6.6%)

0.996

Chemo Anthracyclines

No

Yes

212(60.9%)

63(58.9%)

113(32.5%)

38(35.5%)

23(6.6%)

6(5.6%)

0.813

Chemo_Taxanes

No

Yes

206(62.2%)

69(55.6%)

109(32.9%)

42(33.9%)

16(4.8%)

13(10.5%)

0.075

Chemo 5- FU

No

Yes

266(60.0%)

9(75.0%)

148(33.4%)

3(25.0%)

29(6.5%)

0(0.0%)

0.480

Chemo_

Cyclophosphamide

No

Yes

220(62.1%)

55(54.5%)

113(31.9%)

38(37.6%)

21(5.9%)

8(7.9%)

0.363

Chemo_

Carboplatin

No

Yes

269(60.6%)

6(54.5%)

147(33.1%)

4(36.4%)

28(6.3%)

1(9.1%)

0.892

Chemo_

Vinorelbine

No

Yes

275(60.6%)

0(0.0%)

150(33%)

1(100.0%)

29(6.4%)

0(0.0%)

0.365

Chemo_

Capecitabine

No

Yes

271(60.5%)

4(57.1%)

148(33.0%)

3(42.9%)

29(6.5%)

0(0.0%)

0.717

Chemo_ Doxil

No

Yes

275(60.4%)

0(0.0%)

151(33.2%)

0(0.0%)

29(6.4%)

0(0.0%)

N.A.

Chemo_Gemcitabine

No

Yes

275(60.4%)

0(0.0%)

151(33.2%)

0(0.0%)

29(6.4%)

0(0.0%)

N.A.

Chemo_

Mitoxantrone

No

Yes

275(60.4%)

0(0.0%)

151(33.2%)

0(0.0%)

29(6.4%)

0(0.0%)

N.A.

Chemo_Abraxane

No

Yes

271(60.4%)

4(66.7%)

150(33.4%)

1(16.7%)

28(6.2%)

1(16.7%)

0.461

Chemo_Halaven

No

Yes

275(60.4%)

0(0.0%)

151(33.2%)

0(0.0%)

29(6.4%)

0(0.0%)

N.A.

Endocrine_Tamoxifen

No

Yes

145(62.8%)

130(58.0%)

68(29.4%)

83(37.1%)

18(7.8%)

11(4.9%)

0.143

Endocrine_Anastrozole

No

Yes

253(60.5%)

22(59.5%)

138(33.0%)

13(35.1%)

27(6.5%)

2(5.4%)

0.946

Endocrine_Exemestane

No

Yes

269(60.4%)

6(60.0%)

148(33.3%)

3(30.0%)

28(6.3%)

1(10.0%)

0.886

Endocrine_Letrozole

No

Yes

202(60.5%)

73(60.3%)

112(33.5%)

39(32.2%)

20(6.0%)

9(7.4%)

0.844

5 (b) CYP2C19*2

CYP2C19*2(c.681G>A)

(n=455)

P value

AA (n=57)

GA (n=186)

GG (n=212)

Adjuvant treatment R

No

Yes

9(18.4%)

48(11.8%)

23(46.9%)

163(40.1%)

17(34.7%)

195(48.0%)

0.161

Adjuvant Chemo

No

Yes

29(12.8%)

28(12.2%)

90(39.8%)

96(41.9%)

107(47.3%)

105(45.9%)

0.900

Adjuvant Radiotherapy

No

Yes

34(13.6%)

23(11.2%)

105(42.0%)

81(39.5%)

111(44.4%)

101(49.3%)

0.534

Adjuvant endocrine

No

Yes

20(13.2%)

37(12.2%)

68(44.7%)

118(38.9%)

64(42.1%)

148(48.8%)

0.389

Adjuvant Herceptin

No

Yes

51(12.9%)

6(9.8%)

159(40.4%)

27(44.3%)

184(46.7%)

28(45.9%)

0.736

Chemo Anthracyclines

No

Yes

46(13.2%)

11(10.3%)

141(40.5%)

45(42.1%)

161(46.3%)

51(47.7%)

0.724

Chemo_Taxanes

No

Yes

43(13.0%)

14(11.3%)

137(41.4%)

49(39.5%)

151(45.6%)

61(49.2%)

0.766

Chemo 5- FU

No

Yes

56(12.6%)

1(8.3%)

179(40.4%)

7(58.3%)

208(47.0%)

4(33.3%)

0.459

Chemo_

Cyclophosphamide

No

Yes

49(13.8%)

8(7.9%)

139(39.3%)

47(46.5%)

166(46.9%)

46(45.5%)

0.197

Chemo_

Carboplatin

No

Yes

55(12.4%)

2(18.2%)

184(41.4%)

2(18.2%)

205(46.2%)

7(63.6%)

0.300

Chemo_

Vinorelbine

No

Yes

57(12.6%)

0(0.0%)

186(41.0%)

0(0.0%)

211(46.5%)

1(100.0%)

0.563

Chemo_

Capecitabine

No

Yes

56(12.5%)

1(14.3%)

184(41.1%)

2(28.6%)

208(46.4%)

4(57.1%)

0.798

Chemo_ Doxil

No

Yes

57(12.5%)

0(0.0%)

186(40.9%)

0(0.0%)

212(46.6%)

0(0.0%)

N.A.

Chemo_Gemcitabine

No

Yes

57(12.5%)

0(0.0%)

186(40.9%)

0(0.0%)

212(46.6%)

0(0.0%)

N.A.

Chemo_

Mitoxantrone

No

Yes

57(12.5%)

0(0.0%)

186(40.9%)

0(0.0%)

212(46.6%)

0(0.0%)

N.A.

Chemo_Abraxane

No

Yes

57(12.7%)

0(0.0%)

183(40.8%)

3(50.0%)

209(46.5%)

3(50.0%)

0.637

Chemo_Halaven

No

Yes

57(12.5%)

186(40.9%)

212(46.6%)

N.A.

Endocrine_Tamoxifen

No

Yes

31(13.4%)

26(11.6%)

97(42.0%)

89(39.7%)

103(44.6%)

109(48.7%)

0.655

Endocrine_Anastrozole

No

Yes

52(12.4%)

5(13.5%)

170(40.7%)

16(43.2%)

196(46.9%)

16(43.2%)

0.912

Endocrine_Exemestane

No

Yes

54(12.1%)

3(30.0%)

184(41.3%)

2(20.0%)

207(46.5%)

5(50.0%)

0.165

Endocrine_Letrozole

No

Yes

41(12.3%)

16(13.2%)

145(43.3%)

41(33.9%)

148(44.3%)

64(52.9%)

0.179

5 (c) CYP2C19*3

CYP2C19*3 (c.636G>A)

(n=454)

P value

AA (n=2)

GA (n=45)

GG (n=407)

Adjuvant treatment R

No

Yes

0(0.0%)

2(0.5%)

8(16.3%)

37(9.1%)

41(83.7%)

366(90.4%)

0.254

Adjuvant Chemo

No

Yes

1(0.4%)

28(12.4%)

17(7.5%)

197(87.2%)

210(92.1%)

0.213

Adjuvant Radiotherapy

No

Yes

1(0.4%)

1(0.5%)

26(10.4%)

19(9.3%)

223(89.2%)

184(90.2%)

0.92

Adjuvant endocrine

No

Yes

0(0.0%)

2(0.7%)

15(9.9%)

30(9.9%)

137(90.1%)

270(89.4%)

0.603

Adjuvant Herceptin

No

Yes

2(0.5%)

0(0.0%)

40(10.2%)

5(8.2%)

351(89.3%)

56(91.8%)

0.757

Chemo Anthracyclines

No

Yes

1(0.3%)

1(0.9%)

34(9.8%)

11(10.4%)

313(89.9%)

94(88.7%)

0.658

Chemo_Taxanes

No

Yes

2(0.6%)

0(0.0%)

35(10.6%)

10(8.1%)

294(88.8%)

113(91.9%)

0.502

Chemo 5- FU

No

Yes

2(0.5%)

0(0.0%)

43(9.7%)

2(16.7%)

397(89.8%)

10(83.3%)

0.713

Chemo_

Cyclophosphamide

No

Yes

2(0.6%)

0(0.0%)

36(10.2%)

9(9.0%)

316(89.3%)

91(91.0%)

0.705

Chemo_

Carboplatin

No

Yes

2(0.5%)

0(0.0%)

44(9.9%)

1(9.1%)

397(89.6%)

10(90.9%)

0.971

Chemo_

Vinorelbine

No

Yes

2(0.4%)

0(0.0%)

45(9.9%)

0(0.0%)

406(89.6%)

1(100.0%)

0.944

Chemo_

Capecitabine

No

Yes

2(0.4%)

0(0.0%)

45(10.1%)

0(0.0%)

400(89.5%)

7(100.0%)

0.663

Chemo_ Doxil

No

Yes

2(0.4%)

0(0.0%)

45(9.9%)

0(0.0%)

407(89.6%)

0(0.0%)

N.A.

Chemo_Gemcitabine

No

Yes

2(0.4%)

0(0.0%)

45(9.9%)

0(0.0%)

407(89.6%)

0(0.0%)

N.A.

Chemo_

Mitoxantrone

No

Yes

2(0.4%)

0(0.0%)

45(9.9%)

0(0.0%)

407(89.6%)

0(0.0%)

N.A.

Chemo_Abraxane

No

Yes

2(0.4%)

0(0.0%)

45(10.0%)

0(0.0%)

401(89.5%)

6(100.0%)

0.704

Chemo_Halaven

No

Yes

2(0.4%)

0(0.0%)

45(9.9%)

0(0.0%)

407(89.6%)

0(0.0%)

N.A.

Endocrine_Tamoxifen

No

Yes

1(0.4%)

21(9.1%)

24(10.8%)

209(90.5%)

198(88.8%)

0.837

Endocrine_Anastrozole

No

Yes

2(0.5%)

0(0.0%)

42(10.1%)

3(8.1%)

373(89.4%)

34(91.9%)

0.847

Endocrine_Exemestane

No

Yes

2(0.5%)

0(0.0%)

44(9.9%)

1(10.0%)

398(89.6%)

9(90.0%)

0.978

Endocrine_Letrozole

No

Yes

1(0.3%)

1(0.8%)

33(9.9%)

12(9.9%)

299(89.8%)

108(89.3%)

0.756

Table 6

Summary of CYP2B6*6, CYP2C19*2 and CYP2C19*3 variants found in patients under chemotherapy or endocrine treatment respectively

CYP2B6*6 (c.516 G>T)

(n=455)

P value

GG (n=275)

GT (n=151)

TT (n=29)

Chemo treatment

No

Yes

161(62.6%)

114(57.6%)

81(31.5%)

70(35.4%)

15(5.8%)

14(7.1%)

0.538

CYP2B6*6 (c.516 G>T)

(n=455)

P value

GG (n=275)

GT (n=151)

TT (n=29)

Endocrine treatment

No

Yes

99(64.7%)

176(58.3%)

43(28.1%)

108(35.8%)

11(7.2%)

18(6.0%)

0.256

CYP2C19*2(c.681G>A)

(n=455)

P value

AA (n=57)

GA (n=186)

GG (n=212)

Chemo treatment

No

Yes

37(14.4%)

20(10.1%)

101(39.3%)

85(42.9%)

119(46.3%)

93(47.0%)

0.364

CYP2C19*2(c.681G>A)

(n=455)

P value

AA (n=57)

GA (n=186)

GG (n=212)

Endocrine treatment

No

Yes

20(13.1%)

37(12.3%)

68(44.4%)

118(39.1%)

65(42.5%)

147(48.7%)

0.448

CYP2C19*3 (c.636G>A)

(n=454)

P value

AA (n=2)

GA (n=45)

GG (n=407)

Chemo treatment

No

Yes

1(0.4%)

1(0.5%)

31(12.1%)

14(7.1%)

225(87.5%)

182(92.4%)

0.213

CYP2C19*3 (c.636G>A)

(n=454)

P value

AA (n=2)

GA (n=45)

GG (n=407)

Endocrine treatment

No

Yes

0(0.0%)

2(0.7%)

15(9.8%)

30(10.0%)

138(90.2%)

269(89.4%)

0.598

The conventional epidemiological breast cancer risk factors did not show significant association of risk factors to breast cancer. Although post-menopausal, age of diagnosis between 41 to 50 years, and first degree of relative having breast or ovarian cancer have obviously elevated the risk factor, the use of hormone therapy and smoking did not cause a significant increase in the breast cancer cases. Use of oral contraceptive between 0 to 5 years seemed to have an increase in percentage in breast cancer population studied. And most of the breast cancer patients were diagnosed between 40 to 50 years. This is in consistent with the National Cancer Registry which recorded the peak of breast cancer cases during this period of time in women’s life (1). First degree relatives with breast cancer or ovarian cancer elevated the percentage of risk factor to get breast cancer in this cohort as well especially in the variant of CYP2C19*2 with 13.7% of the cohort showed homogzygous mutant in CYP2C19*2. It is well known that inheritance plays an important risk factor among environmental factors mentioned especially BRACA1 and BRACA 2 gene (26).

In this healthy case-control matched study, we found that Indian breast cancer patients with CYP2B6*6 are more likely to have breast cancer. This mutant was not significant in Chinese and Malay groups. Germany investigators found that CYP2B6*6 was associated with breast cancer risk in patients of European ancestry. (9) However, this is not the case in majority Singaporean population except population of Indian descent in Singapore.

CYP2C19*2 appeared to be more frequent in Chinese and Malay breast cancer patients but it was found less in Indian breast cancer patients.

Nevertheless, CYP2C19*3 was found most frequently in Chinese breast cancer patients. . Although the p-value is not significant but this trend is in consistent to the finding reported by C.Q. Gan et al in their study that discovered association of CYP2C19*3 with onset of breast cancer in Chinese Han population (10). CYP2C19*3 was not found in this cohort study of Indian population either in patients or healthy control. CYP2C19*3 was found to be low in Caucasian population with 0.04% frequency compared to 5-11% in Asian population groups. (27) (28). Percentage of breast cancer patients with CYP2C19*3 homozygous mutant receiving both chemotherapy and endocrine treatment are the lowest compared to the other two homozygous mutants studied. Among the 3 mutants studied, CYP2C19*2 homozygous mutant recorded the highest percentage among breast cancer patients receiving either chemotherapy treatment or endocrine treatment, 10.1% and 12.3% respectively. Whereas 7.1% of breast cancer patients with CYP2B6*6 homozygous mutant receiving chemotherapy and 6.0% of them receiving endocrine treatment. This could be due to the fact that CYP2C19*2 is found in approximately 23–39% of Asians, 10–20% of Caucasians, and 15% of Africans (29) (30).

Patient’s Characteristics classified by SNP

This study showed significant difference in breast cancer patients with CYP2B6*6, p-value <0.001 in all 3 major races in Singapore; the mutant homozygous TT appears in higher proportion in both Malay & Indian groups. Similarly, mutant in CYP2C19*2 also recorded the highest percentage (13.7%) in breast cancer patients under risk factor with the family history of first degree relative with breast cancer or ovarian cancer. CYP2C19*2 homozygous mutant also recorded the highest percentage (13.9%) in the group of breast cancer patients who have never used any oral contraceptives. Homozygous mutant in CYP2C19*2 was found to be prevalent in various characteristics of breast cancer studied, for instance usage of hormone therapy, smoking status, presence of estrogen receptor, progesterone receptor, ERBB2 status, histological tumour type (ductal non-specific, lobular or others), various tumour size and grade, number of involved axillary lymph nodes (from none, 1-3 to 4+).

It was shown by Joanne Siok et al that patients with CYP2C19*2 polymorphism and the CYP2C19 H2 haplotype have significant lower plasma concentrations of NorEND and lower formation rates of NorEND (10). It was reported by Lu et al that NorEND inhibited recombinant human aromatase competitively, with a K i of 35 nm, and these effects were shown to be comparable with that of the commonly used aromatase inhibitor letrozole (31). NorEND has been previously shown to antagonize the activity of estrogen receptors in breast tissues, although its antagonism is reportedly weaker than those observed with (Z)‐4‐OHT and endoxifen, which are other well‐characterized active metabolites of tamoxifen (32). As NorEND is an active metabolite of tamoxifen that inhibits both aromatase and estrogen receptors, variability in its plasma concentration can potentially influence the therapeutic outcomes of tamoxifen therapy. Notwithstanding, Damkier et al showed no association of CYP2C19 *2 with association of breast cancer in larger group of patients (33). Early Breast Cancer Trialist Collaborative Group found that in oestrogen receptor (ER) positive patients, treatment with tamoxifen for 5 years had substantially reduced the recurrence rates throughout the first 10 years (34). A. B. Sanchez-Spitman et al demonstrated that CYP2C19 polymorphisms have no or little impact on concentration levels and metabolic rate of tamoxifen, endoxifen, 4-hydroxy-tamoxifen and NDM-tamoxifen, or clinical outcomes in breast cancer patients (35).

Both CYP2B6*6 and CYP2C19*2 homozygous mutants seemed to exacerbate the spread of breast cancer in patients with higher percentage of patients found in bigger tumour size, tumour grade and larger number of axillary lymph nodes involved. Although this finding was not significant but the trend shown in this study could serve as a factor for consideration in the treatment regimen of breast cancer patients.

In conclusion, the findings of this study suggest that CYP2B6*6 and CYP2C19*2 polymorphisms may confer a risk for breast cancer development in Singaporean breast cancer patients. Moreover, polymorphisms in these 2 genes have been found to be associated with prognostic factors though not significantly, resulting in potentially worsened prognoses for carriers of those polymorphisms. However, this is an exploratory study, by identifying potential breast cancer susceptibility gene polymorphisms, a bigger sample size study could be done to corroborate these findings in future studies. In addition, the impact of SNPs found in metabolic enzymes (for instance CYP2C19) or transporters on pharmacokinetics and pharmacodynamics of anticancer drug metabolism maybe examined in future studies.

Ethical Approval & Consent to participate

This study has been approved by Singhealth Centralised Institutional Review Board (CIRB) with CIRB reference number 2014/371/B

Every participant had signed patient informed consent form (PICF) to join this study. PICF copies are available for inspection upon request

Consent For Publication

Yes

Availability of supporting data

Yes, data are available upon request

Competing interests

The authors declare that they have no competing interests

Funding

This project was funded by Changi General Hospital Research Grant (Grant Ref. No.: CHF 2013.14-P)

Authors contributions

Gaik-Hong Soon- Designed, executed the study, analysed and wrote the manuscript

Seok Hwee Koo – Designed, as a back-up to run the study when required, review the manuscript

Pei Ting Tan- Analysed the data by using the SPSS software

Lawrence Soon-U Lee-Provided idea and advice

Chee Kian Tham – Provided idea and advice

Mikael Hartman -Provided the normal healthy control data

Su Ming Tan – Supported the study with research grant

Acknowledgements

We thank Ms. Sim Hong Chui and Clinical Trials & Research Unit for coordinating this study. This study was funded by Changi General Hospital Research Grant (CHF 2013.14-P) awarded to Prof. Tan Su Ming

Singapore Cancer Registry Annual Report 2018
Influence of pharmacogenetics on response and toxicity in breast cancer patients treated with doxorubicin and cyclophosphamide. British Journal of Cancer,102,p1003-1009,2010 J. Bray et al
Higher frequency of genetic variants confering increased risk for adverse drug responses for commonly used drugs treating cancer, AIDS and tuberculosis in persons of African descent. The Pharmacogenomics J,1-11,2013, F Aminkeng et al
Molecular epidemiology of genetic polymorphisms in estrogen metabolizing enzymes in human breast cancer. J.Natl.Cancer Inst. Monographs 27,125-134,2000,Thompson, P.A. et al.
Genetic polymorphism of xenobiotic metabolising enzymes,diet, and cancer susceptibility.Br.J.Nutr.96,609-619,2006,Reszka,E. et al.
CytochromeP-450 3A4: regulation and role in drug metabolism. Annu.Rev.Pharmacol. Toxicol.39,1-17,1999,Guengerich,F.P.
Genetic polymorphisms in xenobiotic metabolism.Eur.J.Cancer 30A,1921-1935,1994,Smith C.A.et al.
Analyses of bulky DNA adduct levels in human breast tissue and genetic polymorphisms of cytochrome P450 (CYPs),myeloperoxidase (MPO), quinone oxidoreductase (NQO1), and glutathione S-transferases (GSTs). Mutat.Res.516,41-47, 2002,Brockstedt,U. et al.
CYP2B6*6 is associated with increased breast cancer risk. International Journal of Cancer 2013 Justenhoven C. et al
Association of CYP2C19*2 and associated haplotypes with lower norendoxifen concentrations in tamoxifen-treated Asian breast cancer patients. Br. J.Clin. Pharmaco 2016 Jun 81(6):1142–1152, Joanne Siok et al.
Association of CYP2C19*3 gene polymorphism with breast cancer in Chinese Women. Genetic & Molecular Research 10(4):3514-3519 (2011) C.Q. Gan et al.
Polymorphisms of phase I and phase II enzymes and breast cancer risk Frontiers In Genetics Nov. Vol 3,2012 Justenhoven C.
Transformation of MCF-10A human breast epithelial cells by zeranol and estradiol-17 beta. Breast J. 10, 514-521,2004 Liu, S. et al.
Estrogen carcinogenesis in breast cancer. N. Eng.J.Med 354,270-282,2006, Yager,J.D.et al.
Role of 17 beta-hydroxysteroid dehydrogenase type 1 in endocrine and intracrine estradioal biosysnthesis. J. Steroid Biochem. Mol.biol. 55,525-532,1995, Poutanen,M. et al.
Cellular expression of estrogen and progesterone receptors in mammary glands: regulation by hormones, development and aging. J.steroid Biochem.Mol.Biol.80,137-148, 2002,Shyamala, G. et al.
Familial breast cancer:collaborative reanalysis of individual data from 52 epidemiological studies including 58,209 women with breast cancer and 101,986 women without the disease. Lancet 358,1389-1399,2001, Collaborative group on hormonal factors in breast cancer.
A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science 266, 66–71, 1994, Miki,Y. et al.
Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. Am.J.Hum.Genet.72, 1117–1130,2003,Antoniou,A. et al.
A common coding variant in CASP8 is associated with breast cancer risk. Nat.Genet.39,352-358,2007, Cox,A. et al
The limits of genome-wide methods for pharmacogenomic testing. Pharmacogenet. Genomics 22, 261-272, 2012, Gamazon,E.R. et al.
Cytochrome p450 and glutathione transferase expression in human breast cancer.Clin Cancer Res 9:1705-9,2003, El-Rayes BF,Ali S,Heilbrun LK, et al
The expression of cytochrome P450 enzymes in human breast tumours and normal breast tissue. Breast Cancer Res. Treat. 70:47-54, 2001, Iscan M, Klaavuniemi T., Coban T. et al.
Identification of novel genes that co-cluster with estrogen receptor alpha in breast tumour biopsy specimens, using a large-scale real-time reverse transciption PCR approach. Endocr Relat Cancer.
Estrogen receptor-dependent regulation of CYP2B6 in human breast cancer cells. Biochim Biophys Acta;1799:469-79,2010,Lo R.,Burgoon L.,Macpherson L., et al
Breast and Ovarian cancer risks due to inherited mutations in BRACA 1and BRACA 2. May-Claire King et al. Science, 2003: Oct 24;302 (5645):643–6
The prevalence of CYP2D6 and CYP2C19 genotypes in a population of healthy Dutch volunteers. Tamminga WJ, et al. Eur. J. Clin. Pharmacol. 2001; 57:717–722.
Limited frequency of the CYP2C19*17 allele and its minor role in a Japanese population. Sugimoto K, Uno T, Yamazaki H, Tateishi T. Br. J. Clin. Pharmacol. 2008; 65:437–439.
Pharmacogenomics of tamoxifen: roles of drug metabolizing enzymes and transporters. Kiyotani K, Mushiroda T, Nakamura Y, Zembutsu H. Drug Metab Pharmacokinet. 2012; 27:122–31.
Clinical Pharmacogenetics Implementation Consortium guidelines for cytochrome P450-2C19 (CYP2C19) genotype and clopidogrel therapy. Scott SA, et al. Clin Pharmacol Ther. 2011; 90:328–32.
The tamoxifen metabolite norendoxifen is a potent and selective inhibitor of aromatase (CYP19) and a potential lead compound for novel therapeutic agents. Lu WJ, Xu C, Pei Z, Mayhoub AS, Cushman M, Flockhart DA. Breast Cancer Res Treat 2012; 133: 99–109
Synthesis of mixed (E,Z)-, (E)‐, and (Z)‐norendoxifen with dual aromatase inhibitory and estrogen receptor modulatory activities. Lv W, Liu J, Lu D, Flockhart DA, Cushman M. J Med Chem 2013; 56: 4611–8
CYP2C19*2 and CYP2C19*17 variants and effect of tamoxifen on breast cancer recurrence: Analysis of the International Tamoxifen Pharmacogenomics Consortium dataset. Per Damkier et al Scientific Reports 2017; 7: 7727.
Early Breast Cancer Trialists’ Collaborative Group, et al. Relevance of breast cancer hormone receptors and other factors to the efficacy of adjuvant tamoxifen: patient-level meta-analysis of randomised trials. Lancet. 2011; 378:771–784. doi: 10.1016/S0140-6736(11)60993-8.
Effect of CYP2C19 genotypes on tamoxifen metabolism and early-breast cancer relapse. A. B. Sanchez-Spitman et al. Science Reports. 2021; 11: 415

Pilot Study to Determine Prevalence of CYP2B66,CYP2C192 and CYP2C19*3 in Breast Cancer Patients Versus Normal Healthy Controls Among Three Major Ethnic Groups in Singapore

Status:

Version 1

Abstract

Introduction

Methodology

Statistics

Results

Study subjects’ demographic profile and medical history

Genotyping results

Discussion

Patient’s Characteristics classified by SNP

Conclusion

Declarations

Ethical Approval & Consent to participate

Consent For Publication

Availability of supporting data

Competing interests

Funding

Authors contributions

Acknowledgements

References

Status:

Version 1