Human Epidermal Growth Factor Receptor 2 (HER2) positive breast cancer is associated with Indigenous American ancestry in Latin American women

Abstract

Women of Latin American origin in the United States (U.S.) are more likely to be diagnosed with advanced breast cancer and have a higher risk of mortality than non-Hispanic White women. Studies in U.S. Latinas and Latin American women have reported a high incidence of Human Epidermal Growth Factor Receptor 2 (HER2) positive (+) tumors; however, the factors contributing to this observation are unknown. Genome-wide genotype data for 1,312 patients from the Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC) was used to estimate genetic ancestry. We tested the association between HER2 status and genetic ancestry using logistic and multinomial logistic regression models. Findings were replicated in 616 samples from Mexico and Colombia. Average Indigenous American (IA) ancestry differed by subtype. In multivariate models, the odds of having an HER2+ tumor increased by a factor of 1.20 with every 10% increase in IA ancestry proportion (95%CI 1.07–1.35, p-value 0.001). The association between HER2 status and IA ancestry was independently replicated in samples from Mexico and Colombia. Results suggest that the high prevalence of HER2+ tumors in Latinas could be due in part to the presence of population-specific genetic variant(s) affecting HER2 expression in breast cancer.

Introduction

Globally, more than two million women are diagnosed with breast cancer each year(1). The incidence of breast cancer varies by country, and within the United States risk of breast cancer differs among racial/ethnic subpopulations(2). The age-adjusted incidence rate for breast cancer in non-Hispanic White women in the United States is the highest at 126.1 per 100,000, followed by African American at 124 per 100,000, Hispanic/Latina at 93.9 per 100,000, Asian/Pacific Islander at 93.0 per 100,000, and American Indian/Alaska Native at 74.2 per 100,000(2). Mortality rates also differ by race/ethnicity, being highest in African American women at 28.1 per 100,000, followed by non-Hispanic Whites at 20.1 per 100,000, Hispanic/Latinas at 14.2, and with lowest rates among Asian/Pacific Islanders and American Indian/Alaska Natives at 11.2 and 11.4 respectively(2). Multiple studies have shown that while Hispanics/Latinas (Latinas) have lower breast cancer incidence and mortality rates than non-Hispanic White women, they have a higher risk of breast cancer specific mortality with hazard ratio estimates ranging from 1.1 to 1.3(3–7). This disparity could be in part explained by the fact that Latinas are more likely to be diagnosed with the more aggressive human epidermal growth factor receptor 2 positive (HER2+) and hormone receptor negative subtypes of the disease than non-Hispanic White women(8–15).

Previous studies suggest that reproductive factors or other behavior related exposures could explain some of the observed differences in the incidence of particular tumor subtypes between populations(16–18). In addition, genetic variants that are more strongly associated with particular tumor subtypes have been described(19). However, only few studies have reported specific factors associated with HER2+ subtypes and reports have been inconsistent(11, 19–21).

We have previously shown that a higher degree of Indigenous American (IA) genetic ancestry is associated with a lower incidence of breast cancer(22–24), and discovered a single nucleotide polymorphism (SNP) in the 6q25 chromosomal region near the estrogen receptor 1 (ESR1) gene that explained a large fraction of that lower risk with an allele that originated from IA ancestry and is highly protective for breast cancer, particularly estrogen receptor negative (ER-) tumors(25). In this study, we evaluated the association between continental genetic ancestry and breast cancer subtype among highly IA breast cancer patients from Peru, Mexico and Colombia, to gain insight into the possibility that differences in tumor subtype distribution between racial/ethnic groups might be in part driven by underlying population-specific genetic variants.

Methods

Study Participants

The Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC): As of October 2019, we have recruited 1,842 participants from the Instituto Nacional de Enfermedades Neoplásicas (INEN) in Lima, Peru. Women were invited to participate in the study if they had a diagnosis of invasive breast cancer in the year 2010 or later, and were between 21–79 years of age. A recruiter working locally at INEN, identified eligible breast cancer patients who had upcoming appointments. During the appointment check-in, the recruiter approached eligible patients, provided the patients with information about the study, and reviewed the written informed consent with them if they showed interest in participating in the study. At the end of their oncology clinic visit, blood was drawn by a certified phlebotomist at the INEN central laboratory.

Demographic and clinical data were abstracted from the electronic medical records and included place of birth, current residence, age at diagnosis, height, weight, and family history of breast cancer, as well as tumor characteristics (i.e. histological type, grade and stage, tumor size and ER, progesterone receptor (PR) and HER2 status). A short study survey complemented the information obtained from the medical records and included reproductive history (i.e. age at menarche, age at first pregnancy, number of pregnancies, breastfeeding history, and menopause status) and lifestyle factors (i.e. alcohol consumption and smoking status).

The present analysis includes 1,312 patients with available genome wide genotype data. This study was approved by the INEN and the University of California San Francisco institutional review boards and all individuals provided written informed consent to participate.

The Post Columbian Study of Environmental and Heritable Causes of Breast Cancer (COLUMBUS) is a case-control study of breast cancer with individuals recruited throughout large cancer hospitals in Colombia and Mexico. In Mexico, breast cancer patients were recruited at the Oncology Hospital, Centro Médico Nacional Siglo XXI, and Gynecology Hospital No. 4, Instituto Mexicano del Seguro Social, in Mexico City, Mexico, between 2008 and 2013. The study was approved by the ethics committee of each hospital and written informed consent was obtained from all patients prior to enrollment in the study. Cases were histologically confirmed by a local pathologist. Genomic DNA was isolated from whole blood obtained by a certified phlebotomist. In Colombia, breast cancer patients diagnosed between 2011 and 2016 were recruited through large cancer hospitals in five Colombian cities (Bogota, Ibague, Medellin, Neiva, and Pasto). After providing written informed consent, patients were interviewed in person by trained research nurses. The information collected includes sociodemographic characteristics, anthropometric measures, smoking and drinking habits, family history of cancer, and the complete pathology report. Genomic DNA was isolated from whole blood samples obtained by a certified phlebotomist. The study adhered to the Helsinki Declaration and received Institutional Review Board (IRB) approvals from University of Tolima and from all hospitals where recruitment was carried out.

Genotyping and Quality Control

In PEGEN-BC, DNA was extracted from whole blood following standard protocols and genotypic profiles were generated using the Affymetrix Precision Medicine Research Array(26). This array is designed to include a genome-wide imputation grid with about 800,000 markers and to cover five ancestral population groups, including African, admixed American, East Asian, European, and South Asian. Currently, 1,380 samples from 1,320 individuals have been genotyped. Quality control of the genotyped data was performed in PLINK(27). First, we removed 4 individuals with a genotype call rate less than 90%. After individual genotype call rate filtering, we removed markers on sex chromosomes and those with call rates below 98% (21,752 markers were removed). We used identity by descent to identify any related individuals. There were 60 sets of duplicates and only one sample per individual was kept. The concordance rate for these duplicate individuals was 0.99. There were four sets of first-degree relatives, of which only one sample per pair was included in downstream analyses. The final data set for association analyses included 1,312 samples. Markers with a minor allele frequency (MAF) < 1% were removed. The total number of markers included for imputation was 451,350. We imputed missing genotypes using the Michigan Imputation Server(28) (1000 Genomes Project (1000G) phase 3 samples as reference) and after imputation filtered out markers with r2 < 0.8 and MAF of <1%, which resulted in a total number of 6,915,815 markers.

The 447 Colombian samples included in the replication analysis were genotyped using Affymetrix Axiom UKBiobank Array and the 169 Mexican samples were genotyped on Affymetrix Precision Medicine Research Array. Quality control of the genotyped data has been previously described(29).

Continental and subcontinental structure characterization

After pruning 1000G reference samples (in Plink: window size =50, number of variants=5, Variance Inflation Factor (VIF) threshold=2), we merged them with the PEGEN-BC study imputed dataset which resulted in a total of 520,450 markers for downstream analyses. Individual genetic ancestry was determined using ADMIXTURE(30), unsupervised, with four populations to capture IA, European, African, and East Asian continental ancestry based on the known major continental influences to the population of Peru(31). Global genetic ancestry estimates and core analysis variables are available upon request. To further characterize the continental and subcontinental structure of the PEGEN-BC study participants we conducted Principal Component Analysis (PCA) using the program Plink 1.9(27) and T-Distributed Stochastic Neighbor Embedding (Rt-SNE) analyses with the Rtsne Package(32–34) using the first 50 principal components, in R 3.6.0(35). Rt-SNE was run multiple times (n=4) obtaining consistent clusters.

Individual genetic ancestry was also estimated with the program ADMIXTURE(30) in the replication samples. After pruning, 63,811 and 93,813 genotyped markers were used for the Colombian and Mexican samples respectively.

Breast Tumor Subtype Determination

Different approaches have been used to define breast cancer subtypes based on ER, PR and HER2 status by immunohistochemistry (IHC)(36). We used a cutoff of 1% to define ER/PR positivity(37). HER2 positivity was defined as cases with 3+ staining by IHC or with gene amplification by Fluorescence In Situ Hybridization (FISH) testing following a 2+ IHC result. For quality control, two independent pathologists from the University of California San Francisco reviewed the IHC slides at INEN for a subset of 52 patients. The concordance rate was high: 100% for ER, 87% for PR and 85% for HER2 (most of the discordant calls for HER2 were scored as ‘negative’ or 1+ at INEN and 2+ by the independent pathologists). Tumor subtypes were defined as: ER/PR+ HER2−, ER/PR+ HER2+, ER/PR- HER2+ and ER/PR- HER2−.

The IHC HER2 status for the Colombian and Mexican samples was obtained from pathology reports and medical records. The hospitals from where patients were recruited used the same HER2 positivity criteria as INEN.

Statistical Analysis

Patient characteristics were compared based on breast cancer subtype. T-tests were performed on normally distributed continuous variables, Kruskal-Wallis tests were performed on non-normally distributed continuous variables, and Chi-squared tests were used on categorical variables.

Logistic regression models were used to compare individuals with HER2− vs. HER2+ tumors. Multinomial logistic regression models defining the ER/PR+ HER2− group as the reference were used to test the association between tumor subtypes and IA genetic ancestry. Age at diagnosis, African ancestry and height were included as covariates. Height was included in the models due to its potential role as a confounder based on the comparison of patient characteristics between tumor subtypes. An additional model including stage (I-II, vs. III-IV) and region of residence (Coastal, Mountain or Amazonian) was run to assess the possible bias in the distribution of subtype by ancestry due to the potential correlation between IA ancestry and severity of the cases that are seen at INEN.

The replication analyses in the COLUMBUS consortium samples from Mexico and Colombia were conducted using logistic regression models comparing HER2+ vs. HER2− cases. Additional subtyping of HER2+ tumors in the replication analysis was not conducted due to the limited sample size.

All analyses were performed using Plink 1.9(27), R 3.6.0(35), or ADMIXTURE(30).

Results

Patient Characteristics

PEGEN-BC study patient characteristics by tumor subtype are presented in Table 1 (N=1,312). ER/PR+ HER2− tumors had a frequency of 49%, ER/PR+ HER2+ 18%, ER/PR- HER2+ 12% and ER/PR- HER2– 15%. Average age at diagnosis for all patients was 50 (SD = 11) and there was a non-significant trend towards younger age among women in the ER/PR- HER2− group. Average body mass index (BMI) for all subtypes was 28 (SD = 5), and was similar between groups. There was a statistically significant difference between the subtypes in measured height, where women with ER/PR- HER2+ tumors were shorter than those with other tumor subtypes (p-value= 0.033). Differences regarding reproductive variables by tumor subtype were not observed with the exception of menopausal status. There was a higher percent of pre-menopausal women among those with ER/PR- HER2− tumors (p-value = 0.023). We also observed statistically significant differences by histopathologic subtype (p-value <0.001), and clinical stage and grade (p-value <0.001) (Table 1). Lobular subtype had a frequency of 10% among women with ER/PR+ HER2− group compared to less than 3% in other groups. Stage and grade were higher in the ER/PR- subgroups (HER2+ and HER2−) compared to ER/PR+ tumors (Table 1).

Table 1.

Patient and tumor characteristics by ER, PR, HER2 based subtype in women with breast cancer from Lima, Peru (N=1,312).

Variables	Overall	ER/PR+HER2−	ER/PR+HER2+	ER/PR-HER2+	ER/PR-HER2-010869Mc	P-value
	1,312*	638(49)	239(18)	156(12)	200(15)
Age at diagnosis, yrs. (mean (SD))	50(11)	50(11)	49(10)	51(10)	49(11)	0.254
First-degree family history (N (%))
Yes	98(8)	49(8)	16(7)	7(4)	15(8)	0.561
No	1,214(92)	589(92)	223(93)	149(96)	185(92)
rs140068132 genotype (N (%))
AA	970(74)	446(70)	182(76)	124(80)	156(78)	0.006
AG	326(25)	185(29)	56(23)	30(19)	38(19)
GG	16(1)	7(1)	1(1)	2(1)	6(3)
Anthropometric variables
Weight, Kg. (mean (SD))	64(12)	65(13)	65(12)	62(11)	64(13)	0.146
Height, cm. (mean (SD))	153(7)	153(7)	154(6)	151(6)	153(7)	0.033
Body Mass Index (BMI) (mean (SD))	28(5)	28(5)	28(5)	27(5)	27(5)	0.731
Reproductive variables
Age at menarche, yrs. (mean (SD))	13(2)	13(2)	13(2)	13(2)	13(2)	0.678
Age at first pregnancy, yrs. (mean (SD))	23(6)	24(6)	23(5)	23(6)	22(6)	0.153
Number of pregnancies (mean (SD))	3(2)	3(2)	3(2)	3(2)	3(2)	0.968
Post-menopausal (N (%))
Yes	1,071(82)	530(83)	194(81)	128(82)	160(80)	0.023
No	149(11)	55(9)	33(14)	15(10)	32(16)
Missing	92(7)	53(8)	12(5)	13(8)	8(4)
Breastfeeding history (N (%))
Yes	988(75)	453(71)	182(76)	126(81)	168(84)	0.924
No	44(3)	21(3)	9(4)	5(3)	6(3)
Missing	280(21)	164(26)	48(20)	25(16)	26(13)
Demographic variables and lifestyle
Genetic ancestry (mean (SD))
Indigenous American	76(16)	75(18)	77(16)	80(14)	77(16)	0.023
European	17(12)	17(12)	17(12)	15(10)	16(11)	0.12
African	4(7)	4(8)	5(8)	3(5)	5(7)	0.319
East Asian	2(7)	3(9)	2(4)	1(2)	2(4)	0.32
Region of Residence (N (%))
Amazonas	81(6)	39(6)	13(5)	7(4)	17(8)	0.237
Coast	1,090(83)	535(84)	203(85)	125(80)	157(78)
Mountains	137(10)	62(10)	23(10)	24(15)	25(12)
Missing	4(<1)	2(<1)	0(0)	0(0.0)	1(<1)
Alcohol intake (N (%))
Never	389(30)	186(29)	77(32)	42(27)	69(34)	0.755
< one glass/day	705(54)	338(53)	126(53)	87(56)	101(51)
> one glass/day	133(10)	63(10)	26(11)	14(9)	25(13)
Missing	85(6)	51(8)	10(4)	13(8)	5(2)
Smoking history (N (%))
Never	894(68)	422(66)	171(72)	107(69)	146(73)	0.281
Past	329(25)	164(26)	58(24)	36(23)	46(23)
Current	6(<1)	3(<1)	0(0)	0(0)	3(2)
Missing	83(6)	49(8)	10(4)	13(8)	5(2)
Tumor characteristics
Histopathological variety (N (%))
Ductal	1,166(89)	563(88)	225(94)	149(96)	183(92)	<0.001
Lobular	83(6)	63(10)	8(3)	4(3)	5(2)
Other	22(2)	10(2)	3(1)	2(1)	7(4)
Missing	41(3)	2(<1)	3(1)	1(<1)	5(2)
Grade (N (%))
Low	55(4)	41(6)	6(2)	1(<1)	5(2)	<0.001
Intermediate	515(39)	363(57)	75(31)	21(14)	32(16)
High	691(53)	224(35)	152(64)	132(85)	160(80)
Missing	51(4)	10(2)	6(2)	2(1)	3(2)
Clinical stage (N (%))
I	67(5)	36(6)	11(5)	5(3)	13(7)	<0.001
II	442(34)	256(40)	75(31)	36(23)	53(26)
III	454(35)	192(30)	84(35)	77(49)	88(44)
IV	60(5)	27(4)	13(5)	8(5)	9(4)
Missing	289(22)	127(20)	56(23)	30(19)	37(19)

ER: estrogen receptor; PR: progesterone receptor; HER2: Human Epidermal Growth Factor Receptor 2. SD: Standard Deviation

^*ER, PR and HER2 status missing for 79 individuals (6%)

Distribution of Genetic Ancestry

Results from the model-based continental genetic ancestry proportion estimation showed high IA ancestry proportions in the PEGEN-BC study patients (Table 1). The estimated average IA ancestry was 76%, the average European ancestry 18%, the average African ancestry 4%, and the average East Asian ancestry 2% (Table 1, Figure 1A, B and C). The PEGEN-BC study includes 128 (9.8%) participants with an estimated genetic IA ancestry of more than 95% and 75 (5.7%) had estimated genetic IA ancestry of more than 98%. PCA analysis shows that most of the INEN patients are concentrated in the highly IA range of genetic variation of the 1000G Admixed American populations, with few patients clustering with the Asian and African samples (Figure 1D). We were able to identify genetic structure at the subcontinental level using PCA and Rt-SNE approaches (Figure 2). The IA component of the study participants can be divided into three groups that correlate with the place of birth reported by the patient. We found two relatively small clusters with high IA ancestry cores, each of them composed mainly of patients from the Amazonian and the Coastal regions (Figure 2A, AM and CO clusters, respectively). A larger and more dispersed cluster, including patients mainly from the Coast and the Mountains (Figure 2A, CO/MO cluster), also contained patients with high IA ancestry. This observation is in line with previously described IA population migration patterns and genetic admixture in Peru(38). A small number of individuals in the study were identified who had high proportion of Asian or African ancestry (>50%), each group accounting for ~0.5% of the patients. Those with high East Asian ancestry clustered with the 1000G Japanese (Figure 2B), while patients with high degree of African ancestry clustered with West African populations (Figure 2B).

Figure 1:

Population structure of 1,312 Peruvian breast cancer patients. A and B) ADMIXTURE clustering analysis using unsupervised models assuming K = 4 for all patients and by region of birth, respectively. AM= Amazonian, CO= Coastal, MO= Mountain. C) Boxplots show the distribution of each ancestry component. Median ancestry value is represented as a solid line, interquartile range [IQR] as a box, and whiskers extend up to 1.5*IQR. Potential outliers are depicted as solid points. D) PCA including the PEGEN-BC study patients and 1000G samples. PC1, PCA2 and PC3: first three principal components.

Figure 2:

Rt-SNE analysis clusters continental subpopulations. A) IA ancestry values of Peruvian patients is shown. AM= Amazonian, CO= Coastal, MO= Mountain. B) Same plot showing continents and Latin American subpopulations in colors. Other continental subpopulations are annotated in the plot. ACB: African Caribbeans in Barbados; ASW: Americans of African Ancestry in SW USA; CDX: Chinese Dai in Xishuangbanna, China; CEU: Utah Residents (CEPH) with Northern and Western European Ancestry; CHB: Han Chinese in Beijing, China; CHS: Southern Han Chinese; ESN: Esan in Nigeria; FIN: Finnish in Finland; GBR: British in England and Scotland; GWD: Gambian in Western Divisions in the Gambia; IBS: Iberian Population in Spain; JPT: Japanese in Tokyo, Japan; KHV: Kinh in Ho Chi Minh City, Vietnam; LWK: Luhya in Webuye, Kenya; MSL: Mende in Sierra Leone; TSI: Toscani in Italy; YRI: Yoruba in Ibadan, Nigeria. C1 and C2: two t-SNE components.

Among women in the Amazonian cluster, the incidence of ER/PR-HER2− tumors was higher compared to other patients (19% vs. ~13%, respectively), concordant with what has been previously reported(39). However, likely due to the small size of the Amazonian cluster, this association is not statistically significant (p=0.89).

Subtypes and Continental Genetic Ancestry

As described above, univariate analysis showed a statistically significant difference in proportion of IA genetic ancestry between tumor subtypes (p-value = 0.023, Table 1). The average IA ancestry among participants with ER/PR- HER2+ tumors was 80% compared to 75% among participants with the ER/PR+ HER2− subtype. The results of a logistic regression model testing the association between HER2 status and IA ancestry showed a strong association with and without covariates (Table 2). The odds of having a HER2+ tumor increased by a factor of 1.19 per every 10% increase in IA ancestry (p-value=0.002). The results of the multinomial logistic regression analysis showed that the odds of ER/PR- HER2+ breast cancer increased by a factor of 1.22 per every 10% increase in IA ancestry (The ER/PR+ HER2− was defined as the reference group). This association remained statistically significant in the multivariable model (OR = 1.30, 95% CI = 1.10–1.55, p = 0.002) (Table 2). As expected given the high correlation between the IA and European components of ancestry, we observed a decrease in the odds of developing ER/PR- HER2+ disease with increasing European ancestry (Supplementary Table S1).

Table 2.

Association between ER/PR/HER2 defined groups and Indigenous American genetic ancestry (for every 10% increase)

Covariates	Subtype	N	OR	95% CI	P-value
By HER2 status
Univariate	HER2−	837	Ref.
	HER2+	392	1.10	1.02–1.19	0.012
Age dx + Afr + Height	HER2−	688	Ref.
	HER2+	335	1.19	1.06–1.33	0.002
Age dx + Afr + Height + rs140068132	HER2−	688	Ref.
	HER2+	335	1.20	1.07–1.35	0.001
By ER/PR/HER2 status
Univariate	ER/PR+ HER2−	638	Ref.
	ER/PR- HER2+	156	1.22	1.08–1.37	0.001
	ER/PR+ HER2+	239	1.06	0.97–1.16	0.175
	ER/PR/HER2−	200	1.07	0.97–1.18	0.165
Age dx + Afr + Height	ER/PR+ HER2−	531	Ref.
	ER/PR- HER2+	129	1.30	1.08–1.55	0.004
	ER/PR+ HER2+	209	1.17	1.02–1.33	0.024
	ER/PR/HER2−	158	1.10	0.95–1.27	0.196
Age dx + Afr + Height + rs140068132	ER/PR+ HER2−	531	Ref.
	ER/PR- HER2+	129	1.32	1.10–1.57	0.002
	ER/PR+ HER2+	209	1.18	1.03–1.35	0.014
	ER/PR/HER2−	158	1.11	0.96–1.29	0.141

Age dx: age at diagnosis; Afr: African genetic ancestry proportion

We also conducted the logistic regression analysis including the rs140068132-G protective SNP at 6q25 to test if the association between the HER2+ status and IA ancestry could be driven by this polymorphism. However, the association between HER2 status and IA ancestry was not explained by this protective variant (Table 2).

Given the Hospital-based nature of the study we evaluated the possibility that ancestry was associated with tumor subtype due to IA ancestry being higher among women from remote regions who would more likely be referred to INEN with aggressive tumors. However, in analyses that included stage at diagnosis and region of residence as covariates the association between genetic ancestry and tumor subtype was unchanged (Supplementary Table S2).

Replication of the association was conducted in samples from Mexico and Colombia. Given the relatively small sample size for replication we tested the association by HER2 status only (positive or negative), and analyzed samples from the two countries together including country as a covariate in the model (Table 3). The analysis showed a strong association between HER2 status and IA ancestry in the same direction as our analysis in the PEGEN-BC study patients (Table 3). For every 10% increase in IA ancestry among Mexican and Colombian breast cancer patients we observed a 28% increase in the odds of having a HER2+ tumor (Table 3). There was no evidence of heterogeneity by country (Colombia OR = 1.28, 95%CI 1.03–1.60; Mexico OR = 1.20, 95%CI 0.90–1.59).

Table 3:

Replication of Association between HER2^* status and Indigenous American ancestry in Colombian and Mexican breast cancer patients, N=616

Covariates	Subtype	N	OR	95% CI	P-value
Country	HER2−	460	Ref.
	HER2+	156	1.26	1.08–1.49	0.004
Age dx + Afr + Country	HER2−	460	Ref.
	HER2+	156	1.27	1.07–1.52	0.006

Age dx: age at diagnosis; Afr: African genetic ancestry proportion.

^*Colombia ER/PR+ HER2– 231, ER/PR+ HER2+ 70, ER/PR− HER2+ 59 and ER/PR/HER2– 87; Mexico ER/PR+ HER2– 120, ER/PR+ HER2+ 18, ER/PR− HER2+ 9 and ER/PR/HER2– 22.

Discussion

Breast cancer subtype is a strong predictor of prognosis. Women diagnosed with ER/PR+ tumors tend to have better outcomes compared to women diagnosed with ER/PR- disease(36, 40). Multiple studies have been conducted evaluating factors (genetic, behavioral and environmental) that could explain subtype specific breast cancer risk(21, 41–45). Information about factors contributing to risk of developing HER2+ subtypes is limited but includes common germline variants(11, 19–21).

We evaluated the association between genetic ancestry and breast cancer subtype in a Latin America population with a high degree of IA genetic ancestry in order to assess the possibility that the previously reported higher relative frequency of HER2+ tumors among women of Latin American origin could be in part due to ancestry-specific genetic predisposition embedded within the IA ancestral component.

The clinical characteristics of the Peruvian breast cancer patients included in this study were similar to those described in other Latin American populations with young age and relatively high proportion of the most aggressive tumor subtypes (ER/PR-)(7, 46, 47). Furthermore, it reflects well the tumor characteristics of the overall patient population at INEN based on the similarities between our study patient characteristics and those included in a previously published review on INEN patient characteristics(48, 49). The average IA genetic ancestry in the Peruvian breast cancer patients was 76%, which was consistent with previous estimates of 70–80% IA ancestry in Peru(31, 50), including the 1000G Peruvians, who were also recruited in Lima. Taken together, these data suggest that our samples, even though they are clinic-based, are representative of the expected levels of IA ancestry in the general population of Peru.

Multiple studies have reported a higher incidence of HER2+ tumors in women of Latin American origin(8–12, 14). The results of the current analysis in breast cancer patients from Peru, and including independent replication in patients from Mexico and Colombia, strongly suggest there could be population-specific genetic variant(s) increasing the risk of HER2+ tumors among women with IA ancestry. These results are consistent with the previously reported suggestive association between IA ancestry and erbb2 gene expression (which codes for the HER2 protein) in breast tumors from Colombia(51).

There are various potential mechanisms behind the association between HER2 status and genetic ancestry, both environmental and/or genetic. Genetic risk factors could be acting in cis as well as in trans. Some examples of possible cis regulated mechanisms that could lead to differences in HER2 protein expression would be the presence of population-specific expression quantitative trait loci (eQTLs)(52), splice variants(53) or variants affecting the probability that erbb2 is amplified in tumor cells(54). Trans regulation of HER2 protein expression could result from eQTLs or splice variants for genes that regulate erbb2 expression. The reported associations between rare and common germline mutations in TP53 and HER2+ breast cancer (19, 55, 56) provide some support for this hypothesis. The exact mechanism for the association between TP53 mutations, SNPs, and HER2+ tumors is not well-understood, but is part of a larger body of subtype-specific common and rare variant associations with breast cancer(44, 57, 58). Large Admixture Mapping and genome wide association studies (GWAS) by tumor subtype in women of IA ancestry will be needed to identify the relevant germline variants and gain clarity regarding specific mechanisms for the observed association between IA ancestry and HER2 status.

The ER/PR- HER2+ tumor category had a larger OR than ER/PR+ HER2+ in the PEGEN-BC study, indicating that germline regulation of HER2 expression may not be the only mechanism at play in the relationship between HER2 status and IA ancestry. The difference between ER/PR+ vs. ER/PR- subtype could be random -both estimates are within each other’s 95% CI- or could be reflecting hormone receptor-context dependent expression and/or amplification of HER2(59).

In addition, environmental risk factors may also account for our observation. People of IA ancestry may have more exposure to risk factors that specifically increase the risk of HER2+ tumors. Some risk factors, such as body mass index, are known to differentially affect the risk of luminal vs. basal breast cancer subtypes(43). Although the HER2+ breast cancers are not known to have any specific environmental risk factors to date, additional studies including migration studies may help us understand whether this observation is related to environmental and/or genetic causes.

This is, to our knowledge, the first study evaluating the association between genetic ancestry and breast cancer subtypes in a sample of highly IA women. The IA genome is largely understudied. In 2016, Latinos made up 17.8% of the United States population(60). In that same year, however, that population made up only 0.54% of participants in GWAS(61). And just 0.05% of participants in GWAS were of non-admixed IA ancestry(61). Our study not only included admixed Latinas but a population in which 9.8% of the individuals had over 95% IA genetic ancestry. Additionally, our study collected detailed clinical data on tumor characteristics and other relevant patient information from electronic medical records, which allowed us to compare breast cancer subtypes. Discovering common variants of small effects contributing to breast cancer in non-White populations is challenging due to the relatively limited number of samples available for these groups. However, as was the case in the discovery of the 6q25 protective variant, leveraging genetic admixture could provide a shortcut for identifying specific areas that are likely to carry subtype specific risk variants (24, 25).

The PEGEN-BC study followed a hospital-based case-only design. As a result, the distribution of the subtypes in our study population might not represent the distribution of subtypes in the overall population of Peruvian breast cancer patients. It is possible that women with slow growing or easily treatable tumors either are never treated or receive care somewhere else. However, because this is the main cancer hospital in Peru and equally accessible (or inaccessible) to patients in remote areas such as the jungle lowlands or the mountains, our study participants are likely to be a good representation of patients from all over the country and of diverse breast cancer phenotypes, though likely from the lower end of the country’s income distribution. To account for this potential bias, we evaluated models that included stage and region of residence as covariates (Supplementary Table 1). Our results were unchanged.

This study reported a strong association between IA ancestry and HER2 status. The strongest association was observed for the ER/PR- HER2+ subtype, with individuals from this group having higher average IA ancestry compared to individuals with ER/PR+ HER2− tumors. Our results provide support for the hypothesis that there might be population-specific genetic risk factors predisposing women of IA ancestry to develop HER2+ tumors. Further studies are needed to confirm the genetic basis of this association and discover specific regions or variants within the IA genome. Ultimately, a better understanding of these and other etiological factors explaining breast cancer HER2 status will result in better subtype-specific polygenic risk prediction and improved targeted treatments, not only for women of Latin American origin, but in all women.

Statement of significance.

The positive association between Indigenous American genetic ancestry and HER2+ breast cancer suggests that the high incidence of HER2+ subtypes in Latinas might be due to population and subtype-specific genetic risk variants.