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Abstract

Background:

Immunohistochemical results are of vital importance in the classification of patients with breast cancer into subgroups and in treatment decision-making at every stage. However, differences can occur in biopsy results obtained from the same patient. In our study, we aimed to investigate the importance of pathological examination, which is a possible reason for the differences in patients’ immunohistochemistry results.

Methods:

For this purpose, patients were divided into 3 groups. The differences in estrogen receptor, progesterone receptor, HER2, and Ki-67 were examined between the following groups: patients who received neoadjuvant chemotherapy and then underwent surgery (41 patients), patients who underwent surgery without chemotherapy (50 patients), and the same specimen from a different center and our center (21 patients).

Results:

The pathological discordance rates were 34.1% in the neoadjuvant chemotherapy group, 28% in the surgery without chemotherapy group, and 38.1% in the comparison between our institution and an external center, with no statistically significant difference across the 3 groups (P = .667). When examining the changes within each group, statistically significant differences were found in HER2 (P = .002) for the tru-cut biopsy surgery group and Ki-67 (P = .025) for the group comparing our center to an external center.

Conclusions:

As a result, it was considered that one of the important reasons for the immunohistochemical differences in breast biopsies, which is a known fact, is the evaluating center and pathologist.

Keywords

Breast cancer immunohistochemistry estrogen receptor progesterone receptor HER2

Introduction

Breast cancer represents the most prevalent malignancy diagnosed in women globally.¹ Nonetheless, it is crucial to recognize that breast cancer encompasses a diverse spectrum of disease subtypes, each distinguished by unique molecular and clinical characteristics.² The assessment of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status, along with Ki-67, holds paramount significance in clinical oncology, guiding therapeutic strategies, prognostic evaluations, and disease classification.³ These immunohistochemical markers are essential for tailoring treatment approaches, predicting patient outcomes, and classifying breast cancer subtypes. In today’s scenario, where personalized medicine is increasingly emphasized, accurate and reliable immunohistochemistry (IHC) results are more critical than ever for optimal patient management.⁴ The IHC breast panel, comprising ER, PR, HER2, and Ki-67, plays a vital role in determining the most appropriate treatment options, such as hormone therapy, targeted therapy, or chemotherapy, thereby impacting the overall management of breast cancer.⁵

The evaluation of these clinically critical markers is conducted through immunohistochemical staining, a process contingent upon the expertise of pathologists.⁶ Consequently, therapeutic strategies employed by oncologists are inextricably linked to the support provided by pathology via these specialized staining techniques.⁷ The management of breast cancer has become increasingly reliant on accurate pathological assessments, to the extent that effective treatment planning is largely unattainable without the insights derived from these analyses.⁸ The evolution of treatment algorithms, which has moved beyond traditional chemotherapeutic regimens, has introduced hormone therapies, such as CDK4/6 inhibitors, and innovative approaches for HER2-low positive breast cancer.^9,10 This evolution underscores the heightened importance of immunohistochemical assessments of ER, PR, and HER2 expression, thereby enhancing the pathologist’s pivotal role in informing personalized treatment strategies and ultimately improving patient outcomes.¹¹

In our study, we considered 3 parameters that could potentially lead to alterations in immunohistochemical assessments. First, we examined the impact of neoadjuvant therapy on IHC results, an important consideration given the frequent use of this treatment modality in daily practice. Second, we investigated potential discrepancies between tru-cut biopsy samples and surgical specimens, aiming to understand the extent to which these differences may affect diagnostic accuracy. Finally, we sought to determine whether variations arise from pathologist-related factors, such as differing interpretations of the same specimen across 2 different centers. By exploring these potential sources of variability, our goal was to assess the reliability and reproducibility of IHC results, which hold critical importance in clinical decision-making. Ultimately, we aim to share our clinical data to provide valuable insights for clinical practice and future research endeavors, with the hope of optimizing the utilization of IHC in breast cancer management.

Methods

Study design and participants

This study retrospectively evaluated the results of patients treated between 2014 and 2025 at Kütahya City Hospital and Kütahya Evliya Çelebi Training and Research Hospital, both of which are affiliated with Kütahya University of Health Sciences. Patients were categorized into 3 primary groups for comparative analysis. The first group consisted of 41 patients who underwent biopsy for initial diagnosis, followed by neoadjuvant chemotherapy and subsequent surgical resection. The study examined the differences in ER, PR, HER2, and Ki-67 marker results within this group to assess the impact of neoadjuvant treatment on biomarker expression. The second group included 50 patients who underwent tru-cut biopsy followed by surgical intervention without receiving chemotherapy. This cohort served as a control to evaluate the inherent discrepancies between biopsy and surgical specimen results, independent of chemotherapy-induced changes. The third group comprised 21 patients who had undergone biopsy or surgical procedures at an external medical center and whose cases were subsequently reviewed and re-evaluated at our institution. This group aimed to assess the inter-institutional variability in biomarker assessment and pathological interpretation. The STROBE checklist was used in our study to ensure comprehensive and transparent reporting of the observational research methodology.¹²

Inclusion criteria were as follows: (1) histopathologically confirmed breast cancer diagnosis; (2) availability of both core needle biopsy and surgical specimen IHC results for ER, PR, HER2, and Ki-67; and (3) complete medical records including demographic and treatment data.

Exclusion criteria included (1) missing IHC marker data in either biopsy or surgery samples, (2) recurrent or metastatic disease at the time of diagnosis, (3) prior systemic therapy unrelated to the neoadjuvant setting, and (4) poor sample quality or fixation issues preventing accurate immunohistochemical assessment.

Pathological assessment

Tumor grade, ER, PR, HER2, and Ki-67 ratio were evaluated in the first 2 groups of patients at our center to ensure uniform assessment by a single pathology team. For the third group, a comparative analysis was performed between the results obtained at the external center and those from our institution, allowing us to evaluate potential inter-institutional variability in pathological interpretation. Tumor grade was classified according to standard histological criteria as well, moderately, and poorly differentiated, reflecting the degree of aggressiveness and differentiation of the tumor cells. ER and PR status were categorized into 3 groups based on the percentage of cells exhibiting positive staining in the pathology report: less than 1%, 1% to 9%, and 10% and above. This categorization provides a semi-quantitative measure of hormone receptor expression, which is critical for determining eligibility for endocrine therapy. HER2 status was classified into 5 categories: 0, +1, +2 with fluorescence in situ hybridization (FISH) negative, +2 with FISH positive, and +3 positive, based on immunohistochemical staining intensity and FISH amplification status, which are key factors in determining eligibility for HER2-targeted therapies. Ki-67, a marker of cell proliferation, was grouped into 5 categories: 0% to 2.7%, 2.8% to 7.3%, 7.4% to 19.7%, 19.8% to 53.1%, and 53.2% and above, allowing for a detailed stratification of tumor cell proliferation rates. Patients were classified as having either discordance or no discordance based on differences in ER, PR, and HER2 status between paired samples. Discordance was defined as any difference in subgroup classification for these markers. However, when evaluating Ki-67, a difference in expression alone was not considered a pathological discordance unless accompanied by differences in ER, PR, or HER2 status, reflecting the understanding that Ki-67 expression can be more variable and less clinically significant in isolation.

Immunohistochemistry

Immunostaining evaluation was performed by experienced pathologists blinded to the clinical data. In cases where both biopsy and surgical specimens were available, both were assessed independently. For patients whose samples were evaluated both at an external institution and at our center, re-staining and interpretation were performed using the same standardized protocol.

Formalin-fixed, paraffin-embedded tissue sections were used for immunohistochemical staining. IHC was performed using the Ventana BenchMark XT automated system in accordance with the manufacturer’s protocols. The following primary antibodies were used:

Estrogen Receptor: Clone SP1, ready-to-use, Ventana, Cat# 790-4325, RRID:AB_2335986

Progesterone Receptor: Clone 1E2, ready-to-use, Ventana, Cat# 790-4296, RRID:AB_2335872

HER2/neu: Clone 4B5, ready-to-use, Ventana, Cat# 790-2991, RRID:AB_2335978

Ki-67: Clone 30-9, ready-to-use, Ventana, Cat# 790-4286, RRID:AB_2335984

Data analysis

The statistical analyses were performed using IBM SPSS Statistics for Windows, Version 25.0, a comprehensive software package designed for statistical analysis. Descriptive statistics were generated to summarize the demographic and clinical characteristics of the study population, with categorical variables presented as frequencies and percentages to provide a clear overview of the distribution of these variables. To determine the appropriate statistical tests, the normality of the study data was rigorously evaluated using established methods such as the Shapiro-Wilk test and visual inspection of histograms and Q-Q plots. Based on these assessments, nonparametric tests were selected as the preferred analytical approach, given their robustness to deviations from normality. Specifically, to assess whether there was a statistically significant difference among the 3 groups in terms of ER, PR, HER2, and Ki-67 values, the marginal homogeneity test was employed, which is suitable for assessing the equality of proportions in related samples with more than 2 categorical variables. Furthermore, to evaluate the association between pathological discordance and the 3 comparison groups, the χ² test was used, allowing for a comparative analysis of the observed and expected frequencies of discordance across the groups. A statistical significance threshold of P < .05 was consistently applied across all statistical tests to determine the presence of statistically significant differences or associations.

Results

Table 1 presents the patient and tumor characteristics across 3 groups: the neoadjuvant chemotherapy group, the tru-cut biopsy and surgical specimen group, and the group from the authors’ institution and an external center. In the neoadjuvant chemotherapy group, there were more postmenopausal patients than premenopausal, and the majority had hormone receptor–positive and HER2-negative tumors. The tru-cut biopsy and surgical specimen group had a similar distribution, with more postmenopausal patients and higher proportions of hormone receptor–positive, and HER2-negative tumors. The group from the authors’ institution and an external center had fewer patients overall, with a predominance of postmenopausal patients, as well as hormone receptor–positive and HER2-negative tumors.

Table 1.

Patient and tumor characteristics across 3 groups.

Variable	Neoadjuvant chemotherapy group (N, %)	Tru-cut biopsy and surgical specimen group (N, %)	Our institution and an external center group (N, %)
Menopausal Status
Premenopausal	14 (34.1%)	15 (30.0%)	6 (28.6%)
Postmenopausal	27 (65.9%)	35 (70.0%)	15 (71.4%)
Grade
1	6 (14.6%)	22 (44.0%)	5 (23.8%)
2	22 (53.7%)	17 (34.0%)	12 (57.1%)
3	13 (31.7%)	11 (22.0%)	4 (19.0%)
Hormone Receptor
Negative	10 (24.4%)	12 (24.0%)	4 (19.0%)
Positive	31 (75.6%)	38 (76.0%)	17 (81.0%)
CerbB2 Status
Negative	33 (80.5%)	39 (78.0%)	14 (66.7%)
Positive	8 (19.5%)	11 (22.0%)	7 (33.3%)

Abbreviations: N, number of patients; %, the percentages of patients.

Table 2 presents a detailed comparison of the ER, PR, HER2 status, and Ki-67 proliferation index in patients before and after receiving neoadjuvant chemotherapy. For ER status, 8 patients had ER-negative disease prior to treatment, with 2 of these converting to ER 1-9% after treatment. Within the ER 1% to 9% group, 7 patients remained in this range, while 1 converted to ER ⩾ 10%. Most patients maintained a high ER expression of ⩾10% both before and after therapy. Regarding PR status, most patients were PR-negative prior to treatment, and 1 patient converted to PR 1% to 9% after treatment. In the PR ⩾ 10% group, 14 patients sustained this high progesterone receptor level. HER2 status also showed some changes, with 1 patient initially HER2 0 converting to HER2 2+ FISH-negative after treatment. Although discordance rates were 21.9% for ER, 9.7% for PR, and 19.5% for HER2, these differences were not statistically significant (ER: P = .317, PR: P = .257, HER2: P = .394). The analysis further revealed a statistically significant decrease in the Ki-67 proliferation index following neoadjuvant chemotherapy (P = .025). Notably, a discordance rate of 31.7% was observed in the Ki-67 levels between pretreatment and posttreatment assessments.

Table 2.

Comparison of biomarkers before and after neoadjuvant chemotherapy.

Marker	Pretreatment status	Postoperative					P ^a
		Negative		1-9		⩾10
ER	Negative	8		2		0	.317
	1-9	3		7		1
	⩾10	0		3		17
PR	Negative	18		1		0
	1-9	1		5		0	.257
	⩾10	1		1		14
		Zero	1+	2+ (FISH−)	2+ (FISH+)	3+
HER2	Zero	20	0	0	1	0
	1+	3	7	1	0	0	.394
	2+ (FISH−)	1	0	0	0	0
	2+ (FISH+)	0	0	1	0	0
	3+	0	0	1	0	6
		0%-2.7%	2.8%-7.3%	7.4%-19.7%	19.8%-53.1%	⩾53.2%
Ki-67	0%-2.7%	1	0	0	0	0
	2.8%-7.3%	1	10	3	0	0	.025
	7.4%-19.7%	0	3	10	0	0
	19.8%-53.1%	0	1	1	5	0
	⩾53.2%	0	0	1	4	1

Abbreviations: ER, estrogen receptor; FISH, fluorescence in situ hybridization; PR, progesterone receptor.

The marginal homogeneity test was statistically significant at P < .05.

Table 3 compares the biomarker status between tru-cut biopsy and surgical specimens. The study shows that for estrogen receptor, 11 patients had ER-negative disease on tru-cut biopsy, with 2 of these converting to ER 1-9 on the surgical specimen. In the ER 1-9 group, 10 patients remained in this range, while 26 had ⩾10 ER expression on both samples. For progesterone receptor, 22 patients were PR-negative on biopsy, with 1 converting to PR 1-9 on the surgical specimen. In the PR ⩾ 10 group, 11 patients maintained this high level of progesterone receptor expression. HER2 results showed a statistically significant change, with 4 patients initially HER2 0 converting to HER2 1+, and 4 patients converting to HER2 2+ on the surgical specimen. In addition, 3 patients who were initially HER2 1+ were found to be HER2 2+ and FISH positive. The Ki-67 proliferation index also exhibited variability between the 2 sample types. Statistical analysis revealed that the only significant difference was observed in HER2 results, with discordance rates of 6% for ER, 8% for PR, 26% for HER2, and 34% for Ki-67 between the biopsy and surgical specimens (ER: P = .564; PR: P = .257; HER2 P = .002; Ki-67: P = .239).

Table 3.

Comparison of biomarkers between tru-cut biopsy and surgical specimen in patients who did not receive neoadjuvant chemotherapy.

Marker	Tru-cut biopsy	Surgical specimen					P ^a
		Negative		1-9		⩾10
ER	Negative	11		2		0	.564
	1-9	1		10		0
	⩾10	0		0		26
PR	Negative	22		1		0
	1-9	1		13		0	.257
	⩾10	1		1		11
		Zero	1+	2+ (FISH−)	2+ (FISH+)	3+
HER2	Zero	18	4	4	0	0
	1+	1	8	0	3	0	.002
	2+ (FISH−)	0	0	4	0	0
	2+ (FISH+)	0	0	0	2	1
	3+	0	0	0	0	5
		0%-2.7%	2.8%-7.3%	7.4%-19.7%	19.8%-53.1%	⩾53.2%
Ki-67	0%-2.7%	5	5	1	0	0
	2%.8-7.3%	0	13	1	0	0	.239
	7.4%-19.7%	1	3	9	3	1
	19.8%-53.1%	0	0	2	2	0
	⩾53.2%	0	0	0	0	4

Abbreviations: ER, estrogen receptor; FISH, fluorescence in situ hybridization; PR, progesterone receptor.

The marginal homogeneity test was statistically significant at P < .05.

The results of the biomarker analysis between our institution and an external center are detailed in Table 4. Regarding estrogen receptor status, the external center reported 3 negative cases, 1 case with 1% to 9% positivity, and 8 cases with ⩾10% positivity. In contrast, our institution reported 0 negative cases, 9 cases with 1% to 9% positivity, and 0 cases with ⩾10% positivity (P = .317). For progesterone receptor status, the external center reported 6 negative cases, 2 cases with 1% to 9% positivity, and 6 cases with ⩾10% positivity, while our institution reported 0 negative cases, 6 cases with 1% to 9% positivity, and 1 case with ⩾10% positivity (P = .083). Concerning HER2 status, the external center reported 5 cases with a score of 0, 2 cases with a score of 1+, 4 cases with a score of 2+, and 4 cases with a score of 3+, whereas our institution reported 6 cases with a score of 0, 1 case with a score of 1+, 5 cases with a score of 2+, and 4 cases with a score of 3+ (P = .527). For the Ki-67 proliferation index, the external center reported 7 cases with 2.8% to 7.3% positivity, 5 cases with 7.4% to 19.7% positivity, and 1 case with 19.8% to 53.1% positivity. Our institution reported 2 cases with 2.8% to 7.3% positivity, 5 cases with 7.4% to 19.7% positivity, and 1 case with 19.8% to 53.1% positivity (P = .059). The percentage of difference in results for the same samples analyzed at the external center and our center was 4.7% for ER, 14.2% for PR, 33.3% for HER2, and 42.8% for Ki-67.

Table 4.

Comparison of biomarker findings in the same specimen between our institution and an external center.

Marker	External center	Our institution					P ^a
		Negative		1-9		⩾10
ER	Negative	3		0		0	.317
	1-9	1		9		0
	⩾10	0		0		8
PR	Negative	6		0		0
	1-9	2		6		0	.083
	⩾10	0		1		6
		Zero	1+	2+ (FISH−)	2+ (FISH+)	3+
HER2	Zero	5	1	0	0	0
	1+	2	2	1	0	0	.527
	2+ (FISH−)	0	0	4	0	1
	2+ (FISH+)	0	0	0	0	1
	3+	0	0	0	1	3
		0%-2.7%	2.8%-7.3%	7.4%-19.7%	19.8%-53.1%	⩾53.2%
Ki-67	0%-2.7%	0	0	0	0	0
	2.8%-7.3%	0	7	2	2	0	.059
	7.4%-19.7%	0	1	5	2	1
	19.8%-53.1%	0	0	1	0	0
	⩾53.2%	0	0	0	0	0

Abbreviations: ER, estrogen receptor; FISH, fluorescence in situ hybridization; PR, progesterone receptor.

The marginal homogeneity test was statistically significant at P < .05.

Table 5 presents a comparison of pathological discordance among the 3 groups. In the neoadjuvant chemotherapy group, 27 patients (65.9%) had no pathological discordance, and 14 patients (34.1%) had pathological discordance. In the tru-cut biopsy and surgical specimen group, 36 patients (72%) had no pathological discordance, and 14 patients (28%) had pathological discordance. For the comparison between our institution and the external center, 13 patients (61.9%) had no pathological discordance, and 8 patients (38.1%) had pathological discordance. No statistically significant difference was observed in discordance rates among the 3 groups (P = .667).

Table 5.

Comparison of pathological discordance among the 3 groups.

	Pathological discordance		P ^a
Group	Absent (N, %)	Present (N, %)
Neoadjuvant Chemotherapy	27 (65.9)	14 (31.9)
Tru-cut Biopsy and Surgical Specimen	36 (72)	14 (28)	.667
Our Institution and External Center	13 (61.9)	8 (38.1)

Abbreviations: N, number of patients; %, percentage of the patients.

The Pearson χ² test was statistically significant at the P < .05 level.

Discussion

Discrepancies in IHC results, which play a central role in treatment decisions in oncology practice, have been frequently reported in the literature based on classifying patients as either HER2, ER and PR negative or positive, or into luminal A, luminal B, HER2-positive, and triple-negative subtypes.^13
-15 However, such broad classifications may obscure critical nuances in hormone receptor expression and HER2 status that could impact treatment strategies. Therefore, considering current data regarding the prognostic and predictive significance of nuanced hormone receptor expression and HER2-low positivity (HER2 negative with IHC+ 1 positivity, or +2 positivity with FISH negativity), as well as the varied treatment options and potential clinical courses for these groups, our study adopted a more granular approach.^16,17 To investigate discordance, patients were categorized not only as positive or negative for hormone receptors and HER2, but into 3 groups based on hormone receptor status and 5 categories for HER2. Specifically, hormone receptor status was defined as negative, 1-9, or ⩾10, and HER2 status was defined by IHC scores of 0, 1, 2 FISH-negative, 2 FISH-positive, and 3+. This approach may allowed for a more detailed assessment of heterogeneity.

In the existing body of literature, one study documented discordance rates following neoadjuvant chemotherapy, specifically 15.1% for ER, 22.1% for PR, and 15.1% for HER2.¹⁸ A separate investigation identified discordance rates between tru-cut biopsies and surgically excised specimens, with values of 7.9% for ER, 20.6% for PR, and 19% for HER2.¹⁹ Among samples procured from 10 distinct centers and subjected to quality control in a central laboratory, observed discordance rates were 17.8% for ER, 13.6% for PR, and 26.6% for HER2.²⁰ Within our present study, the neoadjuvant chemotherapy cohort exhibited discordance rates of 21.9% for ER, 9.7% for PR, and 19.5% for HER2. The tru-cut biopsy and surgical specimen group demonstrated discordance rates of 6% for ER, 8% for PR, and 26% for HER2. The discordance rates observed between external centers and our facility were 4.7% for ER, 14.2% for PR, and 33.3% for HER2. However, statistical analysis revealed no significant correlation between the aforementioned groups, with the exception of HER2 in the tru-cut and surgical specimen group, with respect to increases or decreases in expression. In our study, the statistically significant increase in HER2 expression between tru-cut biopsies and surgical specimens was not observed for ER, PR, or HER2 in the other groups. This can be attributed to our approach, which differed from previous studies. Those prior studies focused on the classical negative-positive discordance in cases with clinical 0, 1+, or 2+ scores and negative FISH results versus 2+ FISH-positive or 3+ cases. In contrast, in our cohort, when we categorized patients as negative or positive, we observed a discordance in only 3(6%) patients. However, the clinical significance of low-positive HER2 expression has recently been recognized, and this discrepancy is considered important.¹⁷

In our study, when the discordance rates between the 3 groups were compared categorically, no statistically significant difference was observed. This finding may not be consistent with the literature reporting increased discordance after neoadjuvant chemotherapy.¹⁴ Instead, it could suggest that pathological evaluation may be the most important factor in determining discordance rates.

In our study, although pathological discordances was not determined by the presence or absence of Ki-67, the discordance in Ki-67 was also examined. A statistically significant decrease in Ki-67 was observed only in the neoadjuvant chemotherapy group after treatment. However, the discordance rates were high in all 3 groups, and they appeared to be higher proportionally for ER, PR, and HER2. Interestingly, a high rate of 42.8% was observed in the discordance between an external center and our center when examining the same sample. The decrease in Ki-67 after neoadjuvant chemotherapy has been reported in the literature and can be interpreted as the elimination of faster-growing clones.²¹ However, considering the discrepancy in the same sample, the main mechanism of the Ki-67 difference may be attributed to the pathological evaluation. The literature has also reported that the assessment of Ki-67 can depend on the pathology center and the evaluating pathologist.²² Therefore, it may be beneficial for clinicians to consider this factor when making treatment decisions and evaluating the prognosis of patients.

To our knowledge, our study is the first in the literature to compare 3 different groups designed like ours to understand the mechanism of discordance. Until now, the main mechanism of discordance after neoadjuvant treatment has been considered the effect of chemotherapy and the difference between biopsy and surgical samples due to tumor heterogeneity.^18,19 However, in our study, the similar discordance observed in the results of the same specimen examined at different centers, as a third group, suggests the vital importance of the pathology center and the pathologist in this process. The relatively high discordance in Ki-67 in our study results appears to be another point supporting our current view, as the importance of the evaluator in this marker is known.

Our study, while not providing definitive conclusions, can be said to primarily contribute by raising new questions. In cases of breast cancer recurrence or newly developed metastases, are the known immunohistochemical differences truly solely due to tumor biology, or does the evaluation process also contribute additional factors, as observed in the neoadjuvant chemotherapy group? Could a centralized recheck system, aimed at expanding the standardization of pathological evaluations, be implemented routinely in certain regions? If such a routine were to be established, to what extent would repeated immunohistochemical evaluation on each biopsy be necessary? Breast cancer is one of the most commonly encountered medical conditions, and immunohistochemical examinations have been applied for a long time, yet there are still questions that need to be answered. Our study may serve as a basis for new investigations to address these important questions.

Limitations

Given the retrospective nature of the study, a formal sample size calculation was not conducted. While all eligible patients were included, the absence of such a calculation, coupled with the limited sample size, potentially compromises the statistical power of the analysis. Specifically, the inclusion of only 21 patients in both the external and our center control groups suggests that a larger cohort might yield more definitive results. In addition, a fourth control group comparing biopsies from the same patient with local recurrence, axillary metastasis, or newly developed metastasis to their previous IHC could have been informative.

Conclusions

Breast cancer is a heterogeneous disease, and immunohistochemical analysis is indispensable for patient classification and treatment decisions. The existing literature acknowledges the discordance in IHC results from different biopsy samples of the same patient, attributing it to factors such as tumor heterogeneity, variations in sampling techniques, and pre-analytical variables. Our study supports these findings and suggests that variability in pathological evaluation also significantly contributes to these discrepancies. Differences in interpretation criteria, the selection of antibody clones, staining protocols, and the pathologists’ experience levels can lead to inconsistent results, thereby affecting subsequent treatment strategies. Therefore, the implementation of standardized IHC protocols and stringent quality control measures is essential to ensure accurate and reproducible results, ultimately leading to optimal patient management. Further research and inter-laboratory collaborations should focus on refining IHC techniques and interpretation, to minimize variability and improve patient outcomes.

Footnotes

Acknowledgements

Not applicable

ORCID iD

Mustafa Ersoy

Ethical Considerations

The study was approved by the Non-Interventional Research Ethics Committee of Kütahya Health Sciences University (Decision No: 2025/05-19, Date: April 7, 2025), and all procedures were conducted in accordance with the principles of the Declaration of Helsinki. In addition, the necessary permissions were obtained from the hospital administration and the Department of Pathology.

Consent to Participate

The requirement for informed consent was waived by the ethics committee due to the retrospective nature of the study, in accordance with national and institutional guidelines.

Author Contributions

ME: Study conception, data collection, designed data analysis, wrote first draft of the manuscript, approved final version to be published.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

All data used in my article is available in the database and can be requested from Dr Mustafa Ersoy if desired.

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References

Bray

Laversanne

Sung

, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74:229-263.

Rivenbark

O’Connor

Coleman

. Molecular and cellular heterogeneity in breast cancer: challenges for personalized medicine. Am J Pathol. 2013;183:1113-1124.

Wang

Ming

. Research progress on estrogen receptor-positive/progesterone receptor-negative breast cancer. Transl Oncol. 2025;56:102387.

Xiong

Zheng

Ding

, et al. Breast cancer: pathogenesis and treatments. Signal Transduct Target Ther. 2025;10:49.

Kay

Martínez-Pérez

Meehan

, et al. Current trends in the treatment of HR+/HER2+ breast cancer. Future Oncol. 2021;17:1665-1681.

Lin

Yang

Liu

Huang

Chen

. Immunohistochemical stain-aided annotation accelerates machine learning and deep learning model development in the pathologic diagnosis of nasopharyngeal carcinoma. Diagnostics. 2023;13:3685.

Leong

Zhuang

. The changing role of pathology in breast cancer diagnosis and treatment. Pathobiology. 2011;78:99-114.

Bhushan

Gonsalves

Menon

. Current state of breast cancer diagnosis, treatment, and theranostics. Pharmaceutics. 2021;13:723.

Hortobagyi

Stemmer

Burris

, et al. Overall survival with ribociclib plus letrozole in advanced breast cancer. N Engl J Med. 2022;386:942-950.

10.

Shirman

Lubovsky

Shai

. HER2-low breast cancer: current landscape and future prospects. Breast Cancer (Dove Med Press). 2023;15:605-616.

11.

Ajabnoor

Zhang

, et al. Breast cancer with HER2 immunohistochemical score 2 and average HER2 signals/cell 6 or more and HER2/CEP17 ratio less than 2 (“ISH group 3”): a multiinstitutional cohort analysis emphasizing outcome and molecular subtype. Mod Pathol. 2024;37:100530.

12.

Elm

Altman

Egger

, et al. The strengthening the reporting of observational studies in epidemiology [STROBE] statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61:344-349.

13.

Dutta

Chowdhury

Sarkar

Ghosh

. Concordance between core needle biopsy and surgical specimens in determining molecular biological subtypes of breast cancer by immunohistochemistry. J Med Sci. 2023;9:182-189.

14.

Yang

Liao

Xie

Peng

. Changes in ER, PR and HER2 receptors status after neoadjuvant chemotherapy in breast cancer. Pathol Res Pract. 2013;209:797-802.

15.

Danzinger

Spornberger

Vietzen

, et al. Influence of histopathological changes after neoadjuvant chemotherapy on the survival of breast cancer patients. Cancer Treat Res Commun. 2025;43:100886.

16.

Malainou

Stachika

Damianou

, et al. Estrogen-receptor-low-positive breast cancer: pathological and clinical perspectives. Curr Oncol. 2023;30:9734-9745.

17.

Modi

Jacot

Yamashita

, et al. Trastuzumab deruxtecan in previously treated HER2-low advanced breast cancer. N Engl J Med. 2022;387:9-20.

18.

Jaime Dos Santos

Balabram

Mara Reis Gomes

, et al. Changes in invasive breast carcinomas after neoadjuvant chemotherapy can influence adjuvant therapeutic decisions. Cancer Res Treat. 2024;56:178-190.

19.

Khan

Qamar

Nadeem

Khan

Mushtaq

Jan

. Discordance of diagnostic core biopsy and final histopathology performed after surgical resection of breast cancer. Pak Armed Forces Med J. 2022;72:1094-1098.

20.

Orlando

Viale

Schiavone

, et al. Discordance in pathology report after central pathology review in early breast cancer and its impact on treatment choice. J Clin Oncol. 2011;29:585-585.

21.

Nyqvist-Streng

Helou

Chamalidou

Kovács

Parris

. The prognostic value of changes in Ki67 following neoadjuvant chemotherapy in residual triple-negative breast cancer: a Swedish nationwide registry-based study. Breast Cancer Res Treat. 2025;210:719-736.

22.

Fulawka

Halon

. Ki-67 evaluation in breast cancer: the daily diagnostic practice. Indian J Pathol Microbiol. 2017;60:177-184.

Discordance in Immunohistochemistry Results in Breast Pathologies: Effect of Chemotherapy,Specimen Characteristics,or Pathology Center?

Abstract

Background:

Methods:

Results:

Conclusions:

Keywords

Introduction

Methods

Study design and participants

Pathological assessment

Immunohistochemistry

Data analysis

Results

Discussion

Limitations

Conclusions

Footnotes

Acknowledgements

ORCID iD

Ethical Considerations

Consent to Participate

Author Contributions

Funding

Declaration of Conflicting Interests

Data Availability Statement

Copyright Transfer Form

References