Introduction: In hormone receptor-positive (ER+/PR+) and human epidermal growth factor receptor 2-negative (HER2−) early-stage breast cancer (EBC), gene expression tests such as the Prosigna are increasingly used since classic clinicopathological parameters and the proliferation factor Ki-67 often do not allow a definite therapy decision regarding an adjuvant chemotherapy. While the Prosigna test has been validated for postmenopausal patients, few data are available regarding its use in premenopausal patients. The present study compared the Prosigna test with the Ki-67 index in premenopausal patients. Materials and Methods: Premenopausal patients with HR+ HER2−, pN0-1, G1-2 EBC were retrospectively enrolled (n = 55). The Prosigna assay was performed in formalin-fixed paraffin-embedded tumor samples of surgical resection specimens. Ki-67 was reassessed in original diagnostic core needle biopsy specimens and defined as low, intermediate, or high with the threshold of <10%, 10–24%, ≥25%. Results: According to Ki-67, patients were in the low (LR)-, intermediate (IR)-, and high-risk (HR) groups in 40%, 36%, and 24% of the cases. The Prosigna gene signature assay assessed the risk of recurrence as LR for 45% of the patients, IR for 35%, and HR for 20%. The most frequent intrinsic subtypes were luminal A in 73% and luminal B in 24% of the patients. A moderate correlation was found between Prosigna and Ki-67 scores with a Pearson correlation coefficient of 0.51. In the overall cohort, 47% of the Ki-67-based therapy decision would correspond to those based on the Prosigna score. After exclusion of IR patients, matching of low/low or high/high results was observed in 57% of the cases. Conclusion: According to the present study, there is only limited concordance regarding the risk group stratification between Ki-67 and Prosigna-based risk assessment. The relevance and frequency of premenopausal breast cancer emphasizes the need for further evaluation of gene expression analyses in this setting and the correlation with classic clinicopathological parameters regarding therapy decision-making.

With around 2.1 million new cases, 11.6% of the total diagnosed cancer cases, breast cancer is the most commonly diagnosed cancer worldwide and the leading cause of cancer death with a lifetime risk of 12.8%. A little less than half (44%) of these cases occur in very high human development index countries, which represent only about 19% of the world female population [1]. Almost three out of ten women are younger than 55 years of age at diagnosis [2].

Therefore, premenopausal breast cancer patients represent a large and very important subgroup. Due to their young age, it is of paramount importance to optimize available tools in the therapy decision-making process. When it comes to the question of whether endocrine therapy alone is sufficient or additional neo-/adjuvant chemotherapy is necessary in luminal early-stage breast cancer (EBC), use of classic clinicopathological parameters such as age, tumor size, tumor grade, histological type, as well as nodal and hormone receptor status is not sufficient. Also, evaluation of proliferation markers like Ki-67 does not always allow a clear-cut therapy decision. Although Ki-67 may help distinguish luminal A (rather benign course of disease, usually without indication for chemotherapy) from luminal B tumors (more aggressive with indication for chemotherapy based on the patient’s risk profile), there is still no international consensus regarding definite Ki-67 cut-off values for this classification. Therefore, the use of gene expression tests such as the Prosigna (NanoString Technologies, Seattle, WA, USA) may facilitate assessment regarding chemotherapy use according to the latest recommendation of the American Society of Clinical Oncology (ASCO) Guidelines 2022 and the German Gynecological Oncology Group (AGO 2022) [3, 4]. This test can provide additional prognostic information compared to classical clinicopathological parameters and, therefore, support decision-making and avoid unnecessary chemotherapy [5]. The prognostic accuracy of Prosigna has been validated in two independent prospective-retrospective studies (ABCSG-8, transATAC) [6, 7]. Prosigna was highly prognostic for overall distant recurrence in postmenopausal patients with ER-positive EBC. The prognostic value of this test in premenopausal patients is largely unknown. Therefore, the present study aimed to assess the Prosigna test compared with Ki-67 in premenopausal patients.

Study Population

The database of the Breast Centre of the University of Munich (LMU) was screened to identify suitable patients over a 1-year period for the present project. Inclusion criteria were premenopausal status, hormone receptor-positive (ER/PR+), human epidermal growth factor type 2-negative (HER2−), lymph node 0 or 1, tumor grade 1 or 2 EBC. After patient identification, data were anonymized and Prosigna assays were performed.

Results of the Prosigna assay did not impact therapy decision-making. All patients had received a therapy recommendation according to the current guidelines at the time. Hormone receptor status was evaluated by immunohistochemistry (IHC) at the Institute of Pathology, LMU Munich. The institute is accredited according to DIN EN ISO/IEC 17020 and participates in external quality assurance programs of the QuIP GmbH (www.quip.eu/de). HER2 status was assessed by IHC and/or in situ hybridization (FISH). The clinical cut-off value of ≥1% for estrogen receptor positive was used, as this was the guideline recommended reference value for clinical routine. As a part of the therapy decision, Ki-67 was determined by IHC on the tumor material of all included patients according to the recommendations from the International Ki-67 in Breast Cancer Working Group [8]. All IHC and FISH studies were performed on formalin-fixed and paraffin-embedded (FFPE) core needle biopsy specimens. The data regarding tumor type, tumor stage, and the grade were extracted from the respective databases. Gene expression profiling in premenopausal patients was approved by the Institutional Review Board of the faculty of medicine, LMU Munich (Project 19–751).

Prosigna

Prosigna assays were performed on FFPE tumor samples from surgical resection specimens archived at the Institute of Pathology, LMU Munich. RNA for the Prosigna test was extracted from invasive tumor areas and manually microdissected from unstained tissue sections. Areas of tumor necrosis marked regressive changes and residues of the biopsy cavity were omitted. The RNA was tested using the NanoString nCounter® DX Analysis system via direct hybridization. The Breast Cancer Prognostic Gene Signature Assay Prosigna, which uses the PAM50 gene signature, is an in vitro diagnostic assay that provides the gene expression profile of cells found in breast cancer tissue. Based on the gene expression signature of the PAM50, the test can categorize the tumor into luminal A, luminal B, basal-like, and HER2-enriched subtypes [9]. The four intrinsic subtypes of breast cancer have been repeatedly shown to be of prognostic significance, first described in 2000 by Perou et al. [10] The luminal B-type is related to a higher risk profile compared to the luminal A-type [11]. Furthermore, the Prosigna test enables an estimation of the patient’s risk of distant recurrence (ROR). This so-called Prosigna ROR score is not only derived from the gene expression assay but also takes tumor size and nodal status into account. Based on the Prosigna ROR score, patients are divided into three risk groups. In nodal-negative patients, risk groups are defined as follows: low-risk 0–40, intermediate-risk 41–60, and high-risk 61–100. In 1–3 positive nodes, risk groups are defined as follows: low-risk 0–15, intermediate-risk 16–40, and high-risk 41–100.

Ki-67

Ki-67 IHC was performed using FFPE breast tumor tissues. It represents a continuous marker for proliferation activity, which is of high clinical impact since proliferating cells are targeted by chemotherapy. Furthermore, Ki-67 can be used to help for separation of luminal A and luminal B tumors. The exact cut-off value for the Ki-67 index concerning the differentiation of luminal A from luminal B tumors and guiding chemotherapy is still under discussion. The majority of the panelists from the St. Gallen international expert consensus 2013 stated that a cut-off between 20% and 25% is appropriate [12]. The new German S3 guideline of oncology 2021 also assumed a Ki-67 index ≥25% with an increased risk [13]. Based on these recommendations, the present study cohort was stratified into three risk groups according to the Ki-67 index: low-risk <10%, intermediate-risk 10–24%, and high-risk ≥25%.

For the present study, all original diagnostic Ki-67 IHC slides which originated from core needle biopsy specimens of a single institution (Institute of Pathology, LMU Munich) were reassessed by an experienced breast pathologist (K.S.). Ki-67 values were determined by considering the entire tumor area with a focus on the tumor periphery. The Ki-67 values were recorded in 5% increments and later stratified into three groups as described before.

Statistical Analysis

Continuous variables were reported as mean with standard deviation or as median with interquartile range. Categorical variables were expressed as numbers and percentages. Between-group comparisons were performed using student’s t test for normally distributed data and Mann-Whitney U test for non-normally distributed data. Categorial data were analyzed by χ2 or exact Fisher’s test. Correlation analysis was performed using Spearman’s rank correlation coefficient. A p value <0.05 was considered as significant. Statistical analyses were performed using SPSS, version 26 (IBM, Chicago, USA).

Patient and Tumor Characteristics

After exclusion of patients with bilateral breast cancer and those with lack of sufficient tumor tissue, a total of 55 patients were included in the present study. Patient and tumor characteristics are summarized in Table 1. The majority of patients had a pT1, pN0, G2 tumor. All patients were premenopausal with ER- and PR-positive as well as HER2-negative tumors. According to Ki-67, patients were grouped in the low-risk in 40% (22/55), in the intermediate-risk in 36% (20/55), and in the high-risk group in 24% (13/55) of the cases. The Prosigna gene signature assay assessed the risk of recurrence as low risk for 45% (25/55) of the patients, intermediate risk for 35% (19/55), and high risk for 20% (11/55).

Table 1.

Patient and histological type

Patient characteristicsStudy population (n = 55), n (%)
Menopausal and receptor status 
 Pre-menopausal 55 (100) 
 ER/PR+ 55 (100) 
 HER− 55 (100) 
Tumor stage 
 pT1 34 (61.8) 
 pT2 16 (29.1) 
 pT3 4 (7.3) 
 pT4 1 (1.8) 
Nodal status 
 pN0 36 (65.5) 
 pN1 19 (34.5) 
Tumor grade 
 I 9 (16.4) 
 II 46 (83.6) 
Histo type 
 Invasive ductal 46 (83.6) 
 Invasive lobular 9 (164) 
Ki-67 
 Low 22 (40.0) 
 Intermediate 20 (36.4) 
 High 13 (23.6) 
Prosigna 
 Low 25 (45.5) 
 Intermediate 19 (34.5) 
 High 11 (20.0) 
Luminal subtype 
 Luminal A 40 (72.7) 
 Luminal B 13 (23.6) 
 Basal-like 2 (3.7) 
Patient characteristicsStudy population (n = 55), n (%)
Menopausal and receptor status 
 Pre-menopausal 55 (100) 
 ER/PR+ 55 (100) 
 HER− 55 (100) 
Tumor stage 
 pT1 34 (61.8) 
 pT2 16 (29.1) 
 pT3 4 (7.3) 
 pT4 1 (1.8) 
Nodal status 
 pN0 36 (65.5) 
 pN1 19 (34.5) 
Tumor grade 
 I 9 (16.4) 
 II 46 (83.6) 
Histo type 
 Invasive ductal 46 (83.6) 
 Invasive lobular 9 (164) 
Ki-67 
 Low 22 (40.0) 
 Intermediate 20 (36.4) 
 High 13 (23.6) 
Prosigna 
 Low 25 (45.5) 
 Intermediate 19 (34.5) 
 High 11 (20.0) 
Luminal subtype 
 Luminal A 40 (72.7) 
 Luminal B 13 (23.6) 
 Basal-like 2 (3.7) 

Comparison of Prosigna Results with Ki-67

Figure 1 illustrates the median Prosigna ROR scores dependent on different Ki-67 risk groups. The median Prosigna ROR score was 24 (21–40) in the low-risk group, 37 (25–49) in the intermediate-risk group, and 54 (44–62) in the high-risk group according to Ki-67 (p = 0.006). In the scatter plot shown in Figure 2, a moderate correlation was found between Prosigna and Ki-67 scores with a Pearson correlation coefficient of 0.51. The distribution of the Prosigna-defined risk groups within the three different Ki-67 groups is shown in Figure 3a. In all three Ki-67 risk groups, different results were found with regard to the risk group stratification of the Prosigna test. An exact match of the results regarding risk group assignment between Prosigna and Ki-67 was found only in 67% (10/15) of patients with Ki-67 < 10%, in 37% (10/27) of patients with Ki-67 10–24%, and in 46% (6/13) in patients with Ki-67 ≥25%. In the overall cohort, 47% (26/55) of the Ki-67-based therapy decision would correspond with the Prosigna score (Fig. 3b). After exclusion of intermediate-risk patients, matching of low/low or high/high results was observed in 57% (16/28) of the cases.

Fig. 1.

Boxplots of Prosigna ROR scores in different Ki-67-based risk groups. It illustrates the median Prosigna risk of recurrence scores dependent on different Ki-67 risk groups. The Prosigna ROR score was 24 (21–40) in the low-risk group, 37 (25–49) in the intermediate-risk group, and 54 (44–62) in the high-risk group (p = 0.006).

Fig. 1.

Boxplots of Prosigna ROR scores in different Ki-67-based risk groups. It illustrates the median Prosigna risk of recurrence scores dependent on different Ki-67 risk groups. The Prosigna ROR score was 24 (21–40) in the low-risk group, 37 (25–49) in the intermediate-risk group, and 54 (44–62) in the high-risk group (p = 0.006).

Close modal
Fig. 2.

Correlation analysis between Prosigna ROR score and Ki-67 index.

Fig. 2.

Correlation analysis between Prosigna ROR score and Ki-67 index.

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Fig. 3.

Proportion of Prosigna risk groups among different Ki-67 risk groups (a) and overlap of same risk classification between Prosigna and Ki-67 (b).

Fig. 3.

Proportion of Prosigna risk groups among different Ki-67 risk groups (a) and overlap of same risk classification between Prosigna and Ki-67 (b).

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The results of molecular subtyping by the Prosigna assay dependent on different Ki-67 risk groups are shown in Figure 4. While 93% of the patients in the Ki-67 low-risk group were assigned to intrinsic subtype luminal A by Prosigna testing, such result was found in 70% of the patients in the Ki-67 intermediate-risk group and in 54% of the patients in the Ki-67 high-risk group. Luminal B intrinsic subtype was detected in 7% of patients in the Ki-67 low-risk group and in 38% of the patients in the Ki-67 high-risk group, respectively.

Fig. 4.

Breakdown of molecular subtypes by Prosigna within different Ki-67 risk groups.

Fig. 4.

Breakdown of molecular subtypes by Prosigna within different Ki-67 risk groups.

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Agreement of Molecular Subtypes according to Prosigna and Other Methods of Subtyping

Table 2 shows the agreement regarding subtyping between Prosigna and surrogate subtyping according to St. Gallen 2013, St. Gallen 2017, and tumor grade-based subtyping. Agreement of Prosigna with subtyping according to St. Gallen 2013 was 73% (40/55). The agreement rate was 71% (39/55) with grade-based subtyping. The assessment of surrogate subtyping according to St. Gallen 2017 is limited since a large proportion of patients were classified as intermediate without the possibility to compare with molecular subtyping according to Prosigna. Of note, the majority of patients with luminal B tumors according to Prosigna were classified as intermediate according to St. Gallen 2017.

Table 2.

Distribution of molecular subtypes according to Prosigna and different definitions of surrogate and grading-based subtyping

Prosigna luminal A (n = 40)Prosigna luminal B (n = 13)Prosigna basal-like (n = 2)
Surrogate subtyping according to St. Gallen 2013 
 Luminal A 75% (30) 31% (4) 1 (50%) 
 Luminal B 25% (10) 69% (9) 1 (50%) 
Surrogate subtyping according to St. Gallen 2017 
 Luminal A 48% (19) 8% (1) 0% (0) 
 Intermediate 52% (21) 92% (12) 100% (2) 
 Luminal B 0% (0) 0% (0) 0% (0) 
Grading-based subtyping 
 Luminal A 80% (32) 54% (7) 1 (50%) 
 Luminal B 20% (8) 46% (6) 1 (50%) 
Prosigna luminal A (n = 40)Prosigna luminal B (n = 13)Prosigna basal-like (n = 2)
Surrogate subtyping according to St. Gallen 2013 
 Luminal A 75% (30) 31% (4) 1 (50%) 
 Luminal B 25% (10) 69% (9) 1 (50%) 
Surrogate subtyping according to St. Gallen 2017 
 Luminal A 48% (19) 8% (1) 0% (0) 
 Intermediate 52% (21) 92% (12) 100% (2) 
 Luminal B 0% (0) 0% (0) 0% (0) 
Grading-based subtyping 
 Luminal A 80% (32) 54% (7) 1 (50%) 
 Luminal B 20% (8) 46% (6) 1 (50%) 

Surrogate subtyping according to St. Gallen 2013: luminal A = low Ki-67 (<20%) and high PR (≥20%); luminal B = high Ki-67 (≥20%) and/or low PR (<20%). Surrogate subtyping according to St. Gallen 2017: luminal A = high ER/PR, clearly low Ki-67, grade 1; intermediate: uncertainty persists about degree of risk and responsiveness to endocrine and cytotoxic therapies; luminal B = lower ER/PR, clearly high Ki-67, grade 3.

Grading-based subtyping: luminal A = grade 1 or grade 2 and Ki-67 < 14% or grade 2 and Ki-67 14–19% and PR ≥20%; luminal B = grade 3 or grade 2 and Ki-67 ≥20% or grade 3 and Ki-67 14–19% and PR <20%.

The rationale of the present study was to compare the diagnostic results of the Prosigna assay with Ki-67 and different approaches of tumor subtyping in premenopausal patients with HR+ HER2− EBC. We were able to demonstrate that despite a certain correlation of the Prosigna ROR score with Ki-67, agreement of classification into distinct risk groups was relatively low between these two measures. Also, the agreement of subtyping into luminal A and B tumors between Prosigna and different methods using Ki-67 was suboptimal.

Anti-Ki-67 IHC utilizing the MiB1 clone is generally regarded as a very robust test with a high tolerability against preanalytical variables, especially duration of formalin fixation time [14]. Compared to surgical specimens, core needle biopsy specimens are rapidly and evenly fixed, resulting in more homogenous staining results [15]. Nevertheless, no significantly different results had been observed when Ki-67 values determined in core needle biopsies and surgical resection specimens were compared [16]. The lack of standardization in Ki-67 scoring procedures and the known interobserver variability are so far unresolved problem [8, 16].

While Prosigna has been validated in several retrospective studies in postmenopausal women [17‒19], data for premenopausal women are still scarce and, hence, Prosigna testing is only approved for postmenopausal patients. In such a cohort of postmenopausal patients, the Ki-67 index was recently compared with the Prosigna assay by Fernandez-Martinez et al. [20]. In this study, the authors found a low correlation between Ki-67 and the Prosigna assay. The proportion of medium/high Prosigna ROR scores within the Ki-67 low risk group (Ki-67 0–10%) was 42.7% in patients with tumor size less than 2 cm and 33.9% with tumor size greater than 2 cm, respectively. A similar finding was observed in the study by Cheang et al., showing 25% misclassified results [21]. These data implicate, that the correlation of Ki-67 and Prosigna is moderate.

There are limited data published indicating that the Prosigna ROR score as well as the Prosigna-based molecular subtyping may have a predictive value regarding therapy-dependent outcome in premenopausal patients [22]. However, no studies are available assessing the risk prediction of the Prosigna assay compared to Ki-67-based risk models in premenopausal patients. In the present study, only approximately 1 half of patients had consistent results with respect to risk group classification. In particular, patients in the intermediate-risk group according to Ki-67 (10–20%) showed a low rate of risk group matching with Prosigna. In this group, intermediate risk according to Prosigna was present in only 37% of the cases. A relevant proportion of these intermediate-risk patients were classified as low-risk (in 37% of the patients) or high-risk (in 26% of the patients) by Prosigna. Agreement between Prosigna and a Ki-67-based approach with respect to molecular subtyping was slightly better than risk group classification.

Consistent results between Prosigna and surrogate IHC-based subtyping according to St. Gallen 2013 in defining luminal A and B tumors were found in approximately 75% of patients. Yet, these results imply that 25% of patients would have been treated with additional chemotherapy and 31% would only be treated with endocrine therapy according to St. Gallen 2013 surrogate subtyping despite luminal A classification according to Prosigna.

To date, there are several molecular assays besides Prosigna ROR (Oncotype DX, MammaPrint, EndoPredict [EP]) that have shown clinical utility in patients with ER/PR-positive, HER2-negative, node-negative/positive breast cancer [23, 24]. Noske et al. [25] compared Ki-67 with EP-generated risk groups. In this relatively large study (N = 373), the authors also found only a moderate correlation between the EP and Ki-67-based risk group classifications. Particularly, low and intermediate Ki-67 values showed limited consistency with EP results. Therefore, EP testing in this subset of patients might be very useful. However, high overlap of Ki-67 ≥ 25% with high-risk EP results was detected indicating that EP testing provides limited additional prognostic information in this subgroup.

In a subsidy of the Optima Prelim trial, which randomized patients to standard therapy or Oncotype DX test-directed therapy, five additional multiparameter tests including the Prosigna ROR were performed in each patient [26]. Interestingly, Oncotype DX predicted a higher proportion of tumors as low risk (82.1%), than were predicted as low/intermediate risk using Prosigna (65.5%). Overall, the five tests showed only modest agreement: only 119 (39.4%) tumors were classified uniformly as either low/intermediate risk or high risk, and 183 (60.6%) were assigned to different risk categories by different tests. These results show that multigene tests may provide differing risk prognostication in the same patient. Hence, it underlines the challenge in correct risk prediction and proves that not one test can be used by a single discriminator regarding therapy decision.

The panelists of the latest St. Gallen consensus agreed that the distinction between luminal A and luminal B by IHC describes important categories in the biology of luminal breast cancer and that these two categories should be used for therapy decision [27]. A majority of the panelists also stated that subtypes can be more appropriately determined by multigene tests and that all approved multigene tests provide valuable information on prognosis and risk, thus helping omit chemotherapy [27‒29]. In light of the present results, more research is necessary to assess risk prediction and therapy guidance by the Prosigna assay in premenopausal patients to justify the recommendations for its use in this patient cohort.

Our study has several limitations. First, there was a small sample size, limiting statistical robustness. Second, the present study was conducted in a single center, limiting the transferability of the results to other patient cohorts. Third, Ki-67 determination and Prosigna testing were performed on different tissues (i.e., core needle biopsy specimens and surgical resection specimens), potentially influencing results. Fourth, the follow-up period was too short to analyze. Therefore, long-term outcome based on the results of the Prosigna and Ki-67 testing could not be assessed.

Due to the relevance and frequency of premenopausal patients with breast cancer, it is important to improve the estimation of relapse risk and potential benefit from adjuvant systemic therapy. According to the present study, there is only limited consistency in the results of the Prosigna assay and Ki-67-based analysis with respect to risk classification and tumor subtyping into luminal A and B categories. Thus, it is necessary to further evaluate gene expression analyses and compare them with classic clinicopathological parameters obtained on identical tissues to improve decision-making concerning adjuvant treatment. Furthermore, prospective studies with larger numbers of patients and different cut-offs of the Prosigna ROR score are needed.

We thank all employees of the Institute of Pathology of the Ludwig Maximilians University in Munich (LMU), especially the members of the scientific workgroup AG Sotlar, who performed the Prosigna assay on tumor samples using the DS encounter system and made the data available to us.

The correlation of tumor factors, determined as part of the clinical routine, was part of a quality assurance project within the LMU breast center. Ethical approval for gene expression analysis in premenopausal patients was obtained from the Institutional Review Board of the faculty of medicine, LMU Munich (Project 19-751). Written informed consent from participants was not required in accordance with local/national guidelines. The authors have no ethical conflicts to disclose.

Harbeck, Nadia: honoraria for lectures and/or consulting from AstraZeneca, Daiichi-Sankyo, Gilead, Lilly, MSD, Novartis, Pierre-Fabre, Pfizer, Roche, Sanofi, Sandoz, and Seagen. Kolben, Thomas: relative employed at Bayer AG, holds stock in Roche, BioNTech, and Valneva. Sotlar Karl: consultant fees, travel support, research funding from NanoString Technologies (former owner of the Prosigna assay, which became a product of Veracyte). Wuerstlein Rachel: served as advisor, consultant, speaker, and travel grant for Agendia, Amgen, Aristo, AstraZeneca, Celgene, Clovis Oncology, Daiichi-Sankyo, Eisai, Exact Sciences, Gilead, Glaxo Smith Kline, Hexal, Lilly, Medstrom Medical, MSD, Mundipharma, Mylan, NanoString, Novartis, Odonate, Paxman, Palleos, Pfizer, Pierre-Fabre, PINK, Prosigna, Puma Biotechnolgogy, Riemser, Roche, Sandoz/Hexal, Sanofi Genzyme, Seattle Genetics/Seagen, Stemline, Tesaro Bio, Teva, Veracyte, Viatris, FOMF, Aurikamed, Clinsol, Pomme Med, MedConcept, and MCI. All other authors received no funding for this study and declare no conflict of interest.

We thank Veracyte and NanoString Technologies for supplying the nCounter® Dx Analysis System.

Rachel Wuerstlein, Nadia Harbeck, and Karl Sotlar encouraged Cordula Ziegler to compare the biomarkers Ki-67 with the gene expression analysis PAM50 in premenopausal patients with EBC and supervised the finding of this work. Cordula Ziegler designed the figures and wrote the manuscript with support from Rachel Wuerstlein, Nadia Harbeck, Karl Sotlar, and Thomas Kolben. Rachel Wuerstlein, Nadia Harbeck, and Karl Sotlar aided Cordula Ziegler in interpreting the results. All authors provided critical feedback and discussed the results. Daniel Hoffmann helped Cordula Ziegler perform the measurements of the Prosigna assay. All authors read and approved the final manuscript.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

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