Prediction of Tamoxifen Benefit in Premenopausal Breast Cancer Patients Evaluated by Three Methods for Determination of Hormone Receptor Status

doi:10.21203/rs.3.rs-3395413/v1

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Research Article

Prediction of Tamoxifen Benefit in Premenopausal Breast Cancer Patients Evaluated by Three Methods for Determination of Hormone Receptor Status

https://doi.org/10.21203/rs.3.rs-3395413/v1

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Background

Tamoxifen remains an important adjuvant treatment in premenopausal patients with hormone receptor-positive breast cancer. Thus, determination of hormone receptors is important. Here, we compare cytosol-based methods, immunohistochemistry (IHC), and gene expression (GEX) analysis for determining hormone receptor status in premenopausal breast cancer patients from a randomized tamoxifen trial, to determine if any method is superior at identifying patients that benefit from tamoxifen.

Methods

Premenopausal patients (n = 564) were randomized to two years of tamoxifen or no systemic treatment. Estrogen receptor (ER) and progesterone receptor (PR) status by protein expression measured by cytosol-based methods and IHC, and mRNA by GEX analysis were compared in 313 patients with available data from all methods. Kaplan Meier estimates and Cox regression were used to evaluate the treatment-predictive value for recurrence-free interval (RFi) and overall survival (OS). Median follow-up for event-free patients was 26 (RFi) and 33 (OS) years.

Results

The mRNA data of ESR1 and PGR distributed bimodally, patterns confirmed in an independent cohort. Kappa-values between all methods were 0.76 and 0.79 for ER and PR respectively. Tamoxifen improved RFi in patients with ER-positive (ER+) or PR-positive (PR+) tumors (Hazard Ratio (HR) and 95% confidence interval (CI)), cytosol-ER + 0.53 (0.36–0.79); IHC-ER + 0.55 (0.38–0.79); GEX-ER + 0.54 (0.37–0.77); cytosol-PR + 0.49 (0.34–0.72); IHC-PR + 0.58 (0.40–0.85); GEX-PR + 0.55 (0.38–0.80)). Results were similar for OS.

Conclusion

Cytosol-based methods, IHC, and GEX analysis can all identify patients that benefit from two years of tamoxifen with equal performance, indicating that GEX data might be used to guide adjuvant tamoxifen therapy.

The trial is registered on ISRCTN: ISRCTN12474687

Oncology

Personalized Medicine

breast cancer

tamoxifen

premenopausal patients

randomized trial

estrogen receptor status

progesterone receptor status

predictive information

Premenopausal patients have much to gain in life expectancy by evading breast cancer-related death. For premenopausal women with hormone-positive disease, tamoxifen is still an important adjuvant treatment option, alone or as chemo-endocrine therapy (1). Side effects associated with tamoxifen therapy include hot flashes, menopausal-like symptoms, uterine cancer, and venous thromboembolism, making validation of measurements of predictive factors important to avoid recommendation of tamoxifen to patients who do not benefit from therapy (2). The estrogen receptor (ER) is well known to be predictive of tamoxifen response, but the additional predictive value of progesterone receptor (PR) status, given the ER status, has been questioned (3).

For predicting tamoxifen benefit, different methods can be used to determine hormone receptor status. Immunohistochemistry (IHC) has been demonstrated to be as good as, or superior to the previously used cytosol-based methods in predicting tamoxifen responsiveness (4). The knowledge of the utility of ESR1 mRNA levels for tamoxifen prediction is limited. It has been proposed that high mRNA levels of ESR1 associate with greater tamoxifen benefit and that low mRNA levels are associated with tamoxifen resistance (5). Furthermore, mutations in the ESR1 gene have been associated with endocrine resistance (6). mRNA levels of the PGR gene are suggested to lack predictive value (5). Today, gene expression (GEX) analyses are recommended for patients with an ambiguous risk of recurrences, e.g., Endopredict^®, MammaPrint^®, Oncotype DX^®, or Prosigna^®. However, their predictive value is still unknown (7, 8, 9). In these patients, GEX of ESR1 and PGR could potentially be available for prediction of tamoxifen benefit.

In this study, we compare three methods for determining hormone receptor status in relation to the recurrence-free interval (RFi) and overall survival (OS) in premenopausal breast cancer patients treated with tamoxifen compared to a control group in a randomized trial with long-term follow-up. The aim was to investigate if any of the three methods; protein expression by cytosol-based methods or IHC, and mRNA levels by GEX analysis, is superior at identifying premenopausal primary breast cancer patients that will benefit from two years of tamoxifen.

Study population

Patients randomized between two years of tamoxifen or no systemic treatment between 1984 and 1991 in the SBII:2pre trial were included (n = 564). This multicenter trial with two coordinating centers included premenopausal (defined as having less than one year since last menstruation) patients with stage II (TNM, third edition) invasive breast cancer (10). The trial was registered in the ISRCTN database retrospectively on the 6/12-2019 (ID: ISRCTN12474687). Details regarding the study population are available in previous publications (10, 11, 12, 13). An inclusion flowchart for the present study is demonstrated in Fig. 1.

Validation cohort

Validation of the concept of distribution-based GEX cut-offs was performed using an independent cohort of patients with metastatic breast cancer, with GEX data from n = 124 primary tumors and n = 74 distant metastases. This study population and acquisition of GEX data have been described previously (14, 15).

Data acquisition

All data regarding patient and tumor characteristics, ER, PR, human epidermal growth factor receptor 2 (HER2), Ki67, subtyping, and outcome were available in the database of the SBII:2pre trial. For the purposes of this study, mRNA levels by GEX analysis of ESR1 and PGR were added to the database.

Hormone receptor analyses and cut-offs

Hormone receptor status was determined on fresh-frozen tumor tissue using cytosol-based methods as previously described (10, 16, 17). For ER determination, isoelectric focusing (IF) in polyacrylamide gels or enzyme-linked immunoassays (EIA) were used (10). For PR determination, EIA, IF, or dextran-coated charcoal (DCC) with Scatchard analysis was used (10). The cut-off for positive ER/PR status was ≥ 0.10 (IF) or ≥ 0.25 (EIA) fmol/ug DNA or ≥ 10 (IF and DCC) or ≥ 25 (EIA) fmol/mg protein according to the guidelines at the two study centers at the time of the original study (10). IHC analyses were performed on tissue microarrays (TMAs) from paraffin-embedded tumor samples (ER) or whole tissue sections from paraffin-embedded blocks collected in a follow-up study in 2020 (PR). The cut-off for positive ER/PR status by IHC was > 10% (10). Antibodies and protocols for IHC and RNA extraction are described previously (10, 18). mRNA expression was determined by Nanostring Technologies using the Nanostring Breast Cancer 360 ^TM assay on the Nanonstring nCounter© as previously described (18, 19). The GEX values are log-transformed relative mRNA measurements normalized to the expression of housekeeping genes. To identify biologically relevant cut-offs for positive ER and PR status based on GEX data, histograms demonstrating ESR1 and PGR mRNA levels were depicted (Fig. 2a-b) (20). The cut-offs were selected using the visual appearance of the bimodal distributions of the two genes, independently of outcome. Positive GEX was defined as ≥ 6 for ESR1 and ≥ 4.5 for PGR.

Follow-up and endpoints

Follow-up data from the regional cancer centers, the Swedish Cause of Death Registry, and the Swedish Cancer Registry were collected as previously described (10, 11, 18). Data cut-off was December 20, 2020 (18). The endpoints were RFi and OS. RFi was defined as the time to a first event of recurrence (ipsilateral, local, regional, or distant), ipsilateral ductal carcinoma in situ (DCIS), or death from breast cancer according to the Definition for the Assessment of Time-to-event Endpoints in Cancer trialist (DATECAN) guidelines for endpoints at the time of the original study (21). OS was defined at the time from randomization to death from all causes.

Ethics

The original study was approved by the ethical committees in Lund and Linköping. The follow-up study including information from patient records, the Swedish Cause of Death Registry, and the Swedish Cancer Registry was approved by the ethical committee of Lund University (LU 2015/350). Tissue retrieval for updated biomarker analyses and GEX analyses was approved by the ethical committee of Lund University (LU 2017/97).

Statistical analyses

The level of agreement between the three methods was presented as percentages and estimated using Fleiss’s kappa. The relations between continuous ER and PR data were assessed using Spearman’s Rho. Patients with available data for all three methods for both ER and PR were included in the survival analyses and treatment-interaction tests. Kaplan Meier graphs were used to demonstrate RFi and OS according to hormonal receptor status. Cox univariable regression was used to estimate hazard ratios (HR). Interaction between a dichotomous biomarker and tamoxifen treatment on the outcome was tested in Cox models including biomarker status, tamoxifen treatment, and an interaction term between the two dichotomous variables. HR_interaction is presented for the multiplicative interaction term between tamoxifen treatment and hormone receptor status. A HR_interaction of 1.00 reflects an effect of treatment which does not vary with hormone receptor status. A HR_interaction ≠1.00 suggests that positive hormone receptor status is associated with tamoxifen treatment being less effective (HR_interaction >1.00) or more effective (HR_interaction <1.00) in preventing the event of interest (recurrence or death).

All analyses were performed using the intention-to-treat rule. The nominal P-values presented should be cautiously interpreted as evidence against each null hypothesis without reference to a cut-off for significance. Results are presented adhering to the Recommendation of Tumor Marker Prognostic Studies (REMARK) criteria (22). Statistical calculations were performed using IBM SPSS Statistics, version 28.0. Histograms and Kaplan Meier graphs were created using STATA, version 17.0. Boxplots were constructed in R 4.2.2. using RStudio 2023.06.0.

Patient and tumor characteristics are presented in Table 1. The two study arms within the study cohort with available hormone receptor status by all three methods (n = 313) were well balanced. For the 313 patients with hormone receptor status by all methods, the median follow-up for event-free patients was 26 (RFi) and 33 (OS) years.

ESR1 and PGR GEX and its correlation to protein expression

mRNA levels of ESR1 and PGR within the study population appeared to be bimodally distributed (Fig. 2a-b). To evaluate whether this data-driven cutoff may be generalizable to other cohorts and thus a feasible clinical strategy, we assessed the distribution of the ESR1 and PGR expression in an independent cohort of metastatic breast cancer that includes GEX data from primary tumors and distant metastases. Indeed, the ESR1 and PGR GEX in that cohort exhibited bimodal distributions comparable to the patterns in the current study (Figure A1). Additionally, for both genes, the distribution of the primary tumors and the distant metastases were similar, with consistent cutoffs.

The correlation between ESR1 and PGR mRNA was 0.75 (Rho, 95% confidence interval (CI) 0.68–0.81, P < 0.0001) (Fig. 2c). The relationship was similar when all the samples with available mRNA data were included (Fig. 2d). A strong correlation between mRNA expression and protein expression by IHC was found for ER (Rho 0.80, 95% CI 0.75–0.84, P < 0.0001) (Fig. 2e) as well as for PR (Rho 0.84 95% CI 0.80–0.88, P < 0.0001) (Fig. 2f). When all the samples with available mRNA data were included, corresponding patterns were observed (Fig. 2g-h). Additionally, mRNA expression correlated with protein expression by cytosol-based methods from both study centers, for ER (Fig. 2i-k) and PR (Fig. 2j-l).

Table 1. Patient and tumor characteristics by study arm; for the whole study cohort, for the subgroup with available hormone receptor status analyzed by all three methods, and for the excluded subgroup without available hormone receptor status analyzed by all three methods
Characteristics	Whole study cohort (n = 560)		Cohort with available hormone receptor status analyzed by all three methods (n = 313)		Cohort without hormone receptor status analyzed by all three methods (n = 247)
Characteristics	TAM (n = 276) No. (%)	Control (n = 284) No. (%)	TAM (n = 153) No. (%)	Control (n = 160) No. (%)	TAM (n = 123) No (%)	Control (n = 124) No (%)
Age (years)
Median	45	45	44	45	45	46
Range	25–57	26–58	25–57	26–53	30–56	27–58
>40	51 (19)	59 (21)	28 (18)	36 (23)	23 (19)	23 (19)
40–49	178 (65)	183 (64)	109 (71)	110 (69)	69 (56)	73 (59)
50–59	47 (17)	42 (15)	16 (11)	14 (9)	31 (25)	28 (23)
Missing data	0	0	0	0	0	0
Tumor size (mm)
Median	25	22	25	25	25	21
Range	5–75	2–50	8–75	2–50	5–60	4–50
≤20	86 (31)	121 (43)	46 (30)	59 (37)	40 (33)	62 (50)
>20	189 (69)	163 (57)	107 (70)	101 (63)	82 (67)	62 (50)
Missing data	1	0	0	0	1	0
Number of positive nodes
Median	1	1	1	2	2	1
Range	0–21	0–22	0–20	0–20	0–21	0–22
Node-positive	192 (70)	208 (74)	105 (69)	121 (76)	87 (71)	87 (70)
Node-negative	83 (30)	75 (27)	48 (31)	38 (24)	35 (29)	37 (30)
Missing data	1	1	0	1	1	0
NHG
1	27 (11)	32 (12)	13 (9)	13 (8)	14 (14)	19 (18)
2	105 (42)	115 (44)	56 (38)	68 (43)	49 (49)	47 (45)
3	117 (47)	116 (44)	79 (53)	78 (49)	38 (38)	38 (37)
Missing data	27	21	5	1	22	20
ER, IHC
Positive (> 10%)	151 (66)	173 (71)	102 (67)	111 (69)	49 (65)	62 (74)
Negative (≤ 10%)	78 (34)	71 (29)	51 (33)	49 (31)	27 (36)	22 (26)
Missing data	47	40	0	0	47	40
ER, cytosol
Positive	133 (60)	140 (61)	92 (60)	96 (60)	41 (59)	44 (62)
Negative	89 (40)	91 (39)	61 (40)	64 (40)	28 (41)	27 (38)
Missing data	54	53	0	0	54	53
ER, GEX^a
Positive	156 (72)	164 (75)	108 (71)	115 (72)	48 (75)	49 (82)
Negative	61 (28)	56 (25)	45 (29)	45 (28)	16 (25)	11 (18)
Missing data	59	64	0	0	59	64
PR, IHC
Positive (> 10%)	141 (62)	161 (69)	90 (59)	103 (64)	51 (67)	58 (77)
Negative (≤ 10%)	88 (38)	74 (32)	63 (41)	57 (36)	25 (33)	17 (23)
Missing data	47	49	0	0	47	49
PR, cytosol
Positive	138 (63)	151 (65)	95 (62)	107 (67)	43 (65)	44 (62)
Negative	81 (37)	80 (35)	58 (38)	53 (33)	23 (35)	27 (38)
Missing data	57	53	0	0	57	53
PR, GEX^b
Positive	151 (70)	157 (71)	100 (65)	109 (68)	51 (80)	48 (80)
Negative	66 (30)	63 (29)	53 (35)	51 (32)	13 (20)	12 (20)
Missing data	59	64	0	0	59	64
Ki67 (%)
Low 0–13	34 (15)	26 (11)	20 (13)	10 (6)	14 (19)	16 (21)
Intermediate 14–19	27 (12)	25 (11)	11 (7)	13 (8)	16 (21)	12 (16)
High 20–100	167 (73)	184 (78)	122 (80)	136 (86)	45 (60)	48 (63)
Missing data	48	49	0	1	48	48
Subtype, St Gallen 2013
Luminal-like	132 (61)	148 (64)	85 (60)	93 (60)	47 (63)	55 (71)
HER2-positive	30 (14)	38 (16)	18 (13)	32 (21)	12 (16)	6 (8)
TNBC	54 (25)	46 (20)	38 (27)	29 (19))	16 (21)	17 (22)
Missing data	60	52	12	6	48	46
PAM50
Luminal A	90 (42)	101 (46)	57 (37))	68 (43)	33 (52)	33 (55)
Luminal B	42 (19)	41 (19)	32 (21)	29 (18)	10 (16)	12 (20)
HER2-E	35 (16)	39 (18)	24 (16)	36 (23)	11 (17)	3 (5)
Basal	50 (23)	39 (18)	40 (26)	27 (17)	10 (16)	12 (20)
Missing data	59	64	0	0	59	64
GEX, gene expression; TAM, tamoxifen; NHG, Nottingham histological grade; ER, estrogen receptor; IHC, immunohistochemistry; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2; TNBC, triple-negative breast cancer; PAM50, prediction analysis of microarray 50; HER2-E, human epidermal growth factor receptor 2-enriched. ^a Positive ER-status by mRNA expression of ESR1 defined as ≥ 6 on the normalized logarithmic scale presented from Nanostring. ^b Positive PR-status by mRNA expression of PGR defined as ≥ 4.5 on the normalized logarithmic scale presented from Nanostring.

Concordance between the three methods

The number of patients for each combination of positive and negative results for the three methods is demonstrated in Table A2. Between all three methods, the concordance for ER was 84% (kappa 0.76, 95% CI 0.69–0.82, P < 0.0001) and for PR 85% (kappa 0.79, 95% CI 0.72–0.85, P < 0.0001). Because of the small number of patients with discordant ER and

PR status; 51 (16%) and 46 (15%) respectively, no survival statistical analysis including only patients with discordant results was performed.

Tamoxifen effect in terms of RFi and OS

To determine the predictive performance of each hormone receptor measuring method, we assessed the benefit of tamoxifen in subgroups classified as receptor-positive according to each method separately. Two years of tamoxifen prolonged RFi at ten years and at full follow-up in patients with ER-positive (ER+) or PR-positive (PR+) tumors by each method (HR and 95% CI) at ten years: cytosol-ER + 0.56 (0.36–0.89), P = 0.014; IHC-ER + 0.58 (0.38–0.88), P = 0.011; GEX-ER + 0.58 (0.39–0.87), P = 0.009; cytosol-PR + 0.54 (0.35–0.83), P = 0.005; IHC-PR + 0.60 (0.38–0.93), P = 0.021; GEX-PR + 0.60 (0.39–0.91), P = 0.016. HRs at full follow-up time: cytosol-ER + 0.53 (0.36–0.79), P = 0.002; IHC-ER + 0.55 (0.38–0.79), P = 0.001; GEX-ER + 0.54 (0.37–0.77), P < 0.001; cytosol-PR + 0.49 (0.34–0.72), P < 0.001; IHC-PR + 0.58 (0.40–0.85), P = 0.006; GEX-PR + 0.55 (0.38–0.80), P = 0.002) as presented in Fig. 3–4 and Table 2.

The predictive performance of the three hormone receptor measuring methods was equal also with regards to OS, with HRs for tamoxifen treatment at ten years follow-up around 0.80 for patients with tumors that were ER + or PR + by any method, and around 0.65 at full follow-up (Figure A3-A4 and Table 2).

Table 2

Cox univariate regression (n = 313)
	10-year RFi		10-year OS		Full follow-up time RFi		Full follow-up time OS
	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P
ER
Cytosol-positive (n = 188)	0.56 (0.36–0.89)	0.014	0.75 (0.46–1.24)	0.265	0.53 (0.36–0.79)	0.002	0.62 (0.44–0.89)	0.010
Cytosol-negative (n = 125)	1.00 (0.65–1.68)	0.859	1.02 (0.63–1.65)	0.947	0.96 (0.61–1.50)	0.847	0.90 (0.60–1.35)	0.615
IHC-positive (n = 213)	0.58 (0.38–0.88)	0.011	0.83 (0.53–1.30)	0.407	0.55 (0.38–0.79)	0.001	0.65 (0.47–0.91)	0.013
IHC-negative (n = 100)	1.10 (0.64–1.90)	0.730	0.91 (0.53–1.56)	0.728	1.00 (0.60–1.65)	0.993	0.88 (0.55–1.38)	0.568
GEX-positive (n = 223)	0.58 (0.39–0.87)	0.009	0.79 (0.51–1.23)	0.287	0.54 (0.37–0.77)	< 0.001	0.65 (0.47–0.90)	0.010
GEX-negative (n = 90)	1.21 (0.69–2.14)	0.504	1.03 (0.59–1.80)	0.926	1.13 (0.66–1.93)	0.655	0.93 (0.57–1.51)	0.757
Triple-positive (n = 178)	0.55 (0.34–0.88)	0.013	0.78 (0.47–1.30)	0.337	0.54 (0.36–0.81)	0.003	0.63 (0.44–0.92)	0.016
Triple-negative (n = 84)	1.24 (0.68–2.25)	0.481	1.02 (0.57–1.84)	0.938	1.23 (0.69–2.17)	0.481	0.97 (0.58–1.62)	0.911
PR
Cytosol-positive (n = 202)	0.54 (0.35–0.83)	0.005	0.77 (0.48–1.24)	0.290	0.49 (0.34–0.72)	< 0.001	0.60 (0.42–0.84)	0.003
Cytosol-negative (n = 111)	1.17 (0.69–1.97)	0.568	0.95 (0.57–1.59)	0.848	1.12 (0.68–1.85)	0.657	0.96 (0.62–1.50)	0.853
IHC-positive (n = 193)	0.60 (0.38–0.93)	0.021	0.86 (0.53–1.39)	0.540	0.58 (0.40–0.85)	0.006	0.69 (0.48–0.97)	0.035
IHC-negative (n = 120)	0.98 (0.59–1.62)	0.943	0.84 (0.51–1.38)	0.483	0.85 (0.53–1.37)	0.507	0.78 (0.51–1.18)	0.776
GEX-positive (n = 209)	0.60 (0.39–0.91)	0.016	0.87 (0.55–1.38)	0.541	0.55 (0.38–0.80)	0.002	0.64 (0.45–0.89)	0.009
GEX-negative (n = 104)	1.07 (0.63–1.82)	0.794	0.86 (0.51–1.45)	0.574	1.00 (0.61–1.63)	0.985	0.91 (0.58–1.43)	0.690
Triple-positive (n = 177)	0.59 (0.37–0.93)	0.023	0.91 (0.55–1.52)	0.727	0.55 (0.37–0.82)	0.003	0.67 (0.47–0.97)	0.035
Triple-negative (n = 90)	1.20 (0.68–2.11)	0.530	0.98 (0.56–1.73)	0.955	1.15 (0.67–1.96)	0.621	1.01 (0.62–1.65)	0.954
ER, estrogen receptor; PR, progesterone-receptor; RFi, recurrence-free interval; OS, overall survival; HR, hazard ratio, CI; confidence interval; cytosol, cytosol-based method; IHC, immunohistochemistry; GEX, gene expression.

When assessing the effect of tamoxifen on tumors found to be “triple-positive” (positive by all available methods), the HR for RFi and OS for tamoxifen was equal to each measuring method separately for both ER and PR (Table 2).

Interaction Analysis

The interaction effects on RFi at full-follow up time between tamoxifen treatment and ER or PR status was on average almost a factor two downwards, i.e. a two-fold larger reduction of incidence of events in receptor-positive compared to receptor-negative patients (HR_interaction (95% CI), ER-cytosol 0.60 (0.33–1.09), P = 0.095; ER-IHC 0.56 (0.30–1.04), P = 0.067; ER-GEX 0.48 (0.25–0.92), P = 0.026; PR-cytosol 0.46 (0.24–0.85), P = 0.014; PR-IHC 0.73 (0.40–1.35), P = 0.32; PR-GEX 0.58 (0.31–1.08), P = 0.084) as demonstrated in Table 3. The corresponding figures for interactions at ten years’ follow-up are displayed in Table 3. The evidence against the null hypothesis that the effect of tamoxifen was equal regardless of ER or PR status, was lower in the analysis of interactions on OS compared to RFi (Table 3).

Table 3

Interaction HR for the interaction effect between ER or PR status by each method and tamoxifen treatment (n = 313)
	10-year RFI		10-years OS		Full follow-up RFi		Full follow-up OS
	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P
ER, cytosol	0.56 (0.29–1.09)	0.087	0.73 (0.36–1.46)	0.371	0.60 (0.33–1.09)	0.095	0.73 (0.43–1.26)	0.257
ER, IHC	0.54 (0.27–1.06)	0.074	0.91 (0.45–1.84)	0.785	0.56 (0.30–1.04)	0.067	0.79 (0.45–1.38)	0.400
ER, GEX	0.48 (0.24–0.97)	0.041	0.75 (0.37–1.53)	0.429	0.48 (0.25–0.92)	0.026	0.74 (0.41–1.32)	0.302
PR, cytosol	0.47 (0.24–0.94)	0.031	0.81 (0.40–1.63)	0.533	0.46 (0.24–0.85)	0.014	0.66 (0.38–1.15)	0.142
PR, IHC	0.64 (0.33–1.25)	0.192	1.03 (0.52–2.07)	0.931	0.73 (0.40–1.35)	0.315	0.95 (0.55–1.64)	0.855
PR, GEX	0.58 (0.30–1.14)	0.116	1.01 (0.50–2.03)	0.977	0.58 (0.31–1.08)	0.084	0.73 (0.42–1.28)	0.274
HR_interaction are presented for the multiplicative interaction term between hormone receptor status and tamoxifen treatment. RFi, recurrence-free interval; OS, overall survival; HR, hazard ratio; CI, confidence interval; ER, estrogen receptor; PR, progesterone receptor; IHC, immunohistochemistry; GEX, gene expression.

In the present study, we demonstrate that positive ER or PR status measured by cytosol-based methods, IHC, and GEX analysis, is predictive of tamoxifen benefit for premenopausal patients with invasive breast cancer. The methods were equally good at predicting benefit of tamoxifen supporting that the methods can be interchangeable. Tamoxifen is still widely used as an adjuvant therapy in premenopausal women and the present finding that mRNA levels of hormone receptors carry tamoxifen predictive information is thus clinically relevant. In the present trial, two years of tamoxifen was evaluated in contrast to today´s recommendation of five or more years. However, prediction of the effect of two years of tamoxifen is today important for patients aiming to get pregnant after a breast cancer diagnosis, since these patients will be recommended to interrupt adjuvant endocrine therapy after two years. Additionally, side effects prevent some patients from completing the specified treatment course of at least five years (23).

mRNA levels of ESR1 and PGR had bimodal distributions, suggesting that there may be a clear discrimination between patients with hormone receptor-positive and -negative tumors at the mRNA level. To our knowledge, no previous publication has demonstrated this bimodal distribution of mRNA levels of the ESR1 and PGR genes. Furthermore, mRNA levels strongly correlated to protein expression analyzed by cytosol-based methods and IHC, indicating that mRNA levels are a good surrogate marker for protein expression when analyzing hormone receptors.

In line with the findings of this study, where the concordances between all three methods were 84% (ER) and 85% (PR), previous studies have reported concordance around 87% (ER) and 86% (PR) between cytosol-based methods and IHC for assessment of protein expression, and around 92% (ER) and 89% (PR) between protein expression by IHC and GEX analysis (24, 25, 26, 27). The slightly lower concordance reported in the present study may be due to the comparison of three methods instead of two, and the relatively small number of exclusively premenopausal patients included. To our knowledge, no previous publication has compared all three methods.

Patients receiving tamoxifen had longer RFi if their tumor was ER + or PR + regardless of the applied method for receptor determination. In patients with tumors that were ER + or PR + by either method, the HRs for tamoxifen were similar, indicating that the methods are equally good at identifying patients who benefit from tamoxifen. Combining all three methods to consider “triple-positive” tumors did not seem to improve the predictive performance, as “triple-positive” tumors had equal benefit of tamoxifen as “single-positives”. These results suggest that cytosol-based methods or IHC assessment for protein expression, and GEX analysis of hormone receptors perform equally well and are interchangeable as predictive tools. A larger cohort study would be needed to determine this. Finally, a larger study could address patients with discordant results that in this study, due to the small number (ER: 51/313; PR 46/313), were not further tested statistically.

It is well known that both cytosol-based methods and IHC for determining hormone receptor status can be used for prediction of tamoxifen benefit (3, 28). Interestingly, this study found that GEX of ESR1 and PGR could be used as well. In a study by Kim et al. (5) patients were randomized to tamoxifen or placebo irrespectively of menopausal status and distant RFi at ten years were compared according to mRNA levels of ESR1 and PGR. The authors found that high ESR1 mRNA levels were associated with tamoxifen benefit, while GEX of PGR lacks predictive function (5). Throughout this study, also positive PR status determined by any method seemed to be predictive of tamoxifen benefit. This result may differ from the EBCTCG report that stated that, given the ER status, PR status does not give any additional predictive information (3). In the present study, including premenopausal patients only, most PR + patients were ER+, which might be a reason for the tamoxifen response observed in the PR + subgroups. Nevertheless, several studies have demonstrated a predictive value for PR independently of ER status (29, 30, 31).

In the analysis of OS at ten years, the evidence for tamoxifen benefit was lower compared to the analysis of RFi. Although, HRs for patients positive for ER and PR by any method were lower in the tamoxifen arm than the control arm. With around three decades of follow-up, tamoxifen improved OS, as previously reported by Ekholm et al. (11) for patients with ER + tumors in this trial. They also found a trend of decreased cumulative mortality (including death of all causes) for ER + patients receiving tamoxifen for the same follow-up time. In a study by Khoshnoud et al. (24), IHC, and cytosol-based methods for the determination of ER status in postmenopausal women were compared regarding the ability to predict benefit of tamoxifen. Patients were randomized to two years of adjuvant tamoxifen or no systemic treatment (24). The authors found that both IHC and cytosol-based methods could identify patients that had benefit from tamoxifen in terms of recurrence-free survival, but also had lower evidence against the null hypothesis of no difference in OS. The authors concluded that IHC and cytosol-based methods were interchangeable for the prediction of tamoxifen benefit, which supports the results of the present study (24).

For RFi, ER status by GEX analysis and PR-status by cytosol-based methods had the lowest interaction P-values with tamoxifen treatment. In the study by Kim et. al (5), the authors also found a tamoxifen treatment interaction with high mRNA levels of ESR1 in relation to distant RFi. A larger study population is needed for more statistical power and reliability in interaction analyses.

The strengths of this study are its randomized design, long follow-up, and that most of the patients only received tamoxifen as systemic treatment, or no systemic treatment. The latter provides an opportunity to study the effects of tamoxifen independent of other systemic treatments. Another strength is that we provide a proof-of-concept analysis for the proposed data-driven cutoff strategy for GEX of ESR1 and PGR in an independent cohort of metastatic breast cancer. Observing that the GEX of both genes is bimodally distributed in both primary tumors and distant metastases – with similar cutoff – suggests that this method is transferrable to other cohorts and tumor stages. Limitations include the number of patients. The selection of 313 patients with data available for all three measuring methods out of the 564 patients that were originally randomized could potentially lead to bias. However, patients and tumor characteristics of the included and excluded subgroups showed no noticeable differences between the two groups (Table 1). A limitation in transferability includes the use of the cut-off > 10% for IHC, which differs from the cutoffs often used globally (4). Furthermore, today patients are given at least five years of tamoxifen instead of two, and receive additional treatments (7, 32). However, five to ten years of treatment can be problematic for premenopausal patients wishing to become pregnant, making studies of shorter treatment regimens of tamoxifen interesting. Importantly, the recently presented trial by Partridge et al. (33) concluded that interruption of endocrine treatment after 18–30 months, was not associated with an increased risk of recurrence compared to an external control cohort which did not interrupt treatment. Furthermore, when the SBII:2pre trial was conducted, the overall prognosis for premenopausal breast cancer patients was worse than today (34). As an example, HER2-positive patients included in the study did not receive trastuzumab, which would have affected their prognosis.

The finding that GEX of ESR1 and PGR can be used to predicting tamoxifen benefit is clinically useful since GEX analysis already is routinely performed in patient subgroups with early breast cancer. Importantly, several gene assays used for this purpose, including Oncotype DX^® and Prosigna^®, include data on ESR1 and PGR expression (7, 8, 9, 20, 35). In the future, ESR1 and PGR data from these patients could potentially be used for hormone receptor determination as an alternative to IHC.

In the present study, three methods for determination of hormone receptor status were applied in relation to RFi and OS in premenopausal breast cancer patients treated with tamoxifen in comparison to a control group in a randomized trial with long-term follow-up. Breast tumor measurement of hormone receptors by protein expression through cytosol-based methods and IHC, as well as mRNA levels by GEX analysis, can all identify patients that benefit from two years of tamoxifen. The methods seem equally good at predicting tamoxifen benefit, indicating that also mRNA data might be used to guide adjuvant tamoxifen therapy.

Acknowledgments

The authors thank Charlotte Levin Tykjær Jørgensen for expert technical contribution, all patients in the SBII:2pre trial, and investigators at the participating hospitals and cancer centers.

Funding details

The study was supported by grants from the Swedish Cancer Society (no 19 0388 Pj, 22 2137 Pj), Anna and Edwin Berger Foundation (no 2019-2022), Governmental Funding of Clinical Research within the Swedish National Health Service (no 2022-40304), and The Berta Kamprad Foundation (no FBKS-2021-11).

Disclosure statement

Co-author MF has an advisory role in Mavatar and contract with PFS Genomics/Exact Sciences regarding genomic profiling and co-inventor on patent applications. The other authors declare no competing interests.

Data availability statement

The data supporting the findings of this study are not publicly available due to restrictions related to data sensitivity, but available from the corresponding author upon reasonable request.

Author contributions

Conception and design: T.E., L.R., P.-O.B. Data acquisition: C.L., M.E., L.R., P.-O.B., O.S., M.F. Formal analysis: T.E., J.T, P.-O.B. Data interpretation: all authors. Funding acquisition: L.R. Project administration: J.T., L.R., P.-O.B. Software: T.E., J.T. P.-O.B. Supervision: L.R., J. T, P.-O.B. Validation: J. T., P.-O.B. Writing—original draft: T.E, L.R. Writing—review & editing: all authors. The final version was approved by all authors.

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AdditionalFigureA1.jpg
Figure A1 Distribution of mRNA expression levels of ESR1 (a, c, e) and PGR(b, d, f) in an independent cohort of patients with metastatic breast cancer containing GEX data from paired primary tumor and distant metastasis samples previously described in detail (14, 15). The data distribution is shown separately for primary tumors (a-b), distant metastasis (c-d), and both primary tumors and distant metastases pooled together (e-f). The vertical grey dotted lines mark a suggested cutoff for positive/negative ESR1 and PGR status respectively, selected as described in the manuscript.
AdditionalTableA2.docx
Table A2
AdditionalFigureA3.jpg
Figure A3 Overall survival according to positive or negative ER status by different methods. Patients with available data for all methods for ER and PR were included (n=313). P-value by log-rank test, 5% significance level. a-b) cytosol-based method. c-d) IHC, e-f) gene expression, g-h) same result for all methods. ER, Estrogen receptor; cytosol, cytosol-based method; IHC, immunohistochemistry; GEX, gene expression; PR, Progesterone receptor; TAM, Tamoxifen.
AdditionalFigureA4.jpg
Figure A4 Overall survival according to positive or negative PR status by different methods. Patients with available data for all methods for ER and PR were included (n=313). P-value by log-rank test, 5% significance level. a-b) cytosol-based method. c-d) IHC, e-f) gene expression, g-h) same result for all methods. ER, Estrogen receptor; cytosol, cytosol-based method; IHC, immunohistochemistry; GEX, gene expression; PR, Progesterone receptor; TAM, Tamoxifen.

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Prediction of Tamoxifen Benefit in Premenopausal Breast Cancer Patients Evaluated by Three Methods for Determination of Hormone Receptor Status

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Abstract

Figures

Introduction

Patients and methods

Study population

Validation cohort

Data acquisition

Hormone receptor analyses and cut-offs

Follow-up and endpoints

Ethics

Statistical analyses

Results

ESR1 and PGR GEX and its correlation to protein expression

Concordance between the three methods

Tamoxifen effect in terms of RFi and OS

Interaction Analysis

Discussion

Conclusion

Declarations

References

Supplementary Files

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