Abstract
Purpose
The main purpose of this study is to explore the predictive value of human epidermal growth factor receptor 3 (HER3) expression level and PIK3CA mutation for the efficacy of neoadjuvant therapy in human epidermal growth factor receptor 2 (HER2)–positive breast cancer patients.
Materials and Methods
The clinicopathological data of HER2-positive non-specific invasive breast cancer patients who received neoadjuvant treatment in the Second Affiliated Hospital of Anhui Medical University from June 2017 to June 2024 were retrospectively analyzed. The correlation between HER3 expression level detected by immunohistochemistry and PIK3CA gene mutation detected by amplification refractory mutation system–polymerase chain reaction and pathological complete response (pCR) was analyzed.
Results
Among 51 patients, 29 (56.9%) had positive HER3 expression, 15 (29.4%) had PIK3CA mutation, and 19 (37.3%) had pCR. The expression level of HER3 was correlated with the pCR rate (χ2=7.905, p=0.019). The PIK3CA mutation status was not correlated with the pCR rate (χ2=0.140, p=0.708). The HER3 expression level combined with PIK3CA mutation status affected the pCR rate (p=0.036). Multivariable regression further identified HER3 positivity as an independent negative predictor of pCR (odds ratio, 0.08; 95% confidence interval, 0.01 to 0.50; p=0.008), underscoring its role in therapeutic resistance.
Conclusion
HER3 expression may serve as a critical biomarker for guiding therapeutic strategies in HER2-positive breast cancer patients. The combinatorial effect of HER3 overexpression and PIK3CA mutations may exacerbate therapeutic resistance, while dual-targeted strategies against the HER3/phosphoinositide 3-kinase pathway could potentially improve clinical outcomes in treatment-resistant populations.
Keywords: Breast neoplasms, HER3, PIK3CA, Neoadjuvant therapy, Therapeutic uses, Pathological Complete Response
Introduction
Breast cancer is the most common malignant tumor and the second leading cause of cancer-related death among women worldwide, posing a serious threat to women’s health [1,2]. The molecular classification of breast cancer reveals its heterogeneous nature and guides therapeutic strategies [3]. Based on molecular characteristics, breast cancer can be classified into four subtypes: luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)–positive, and triple-negative [4]. HER2-positive breast cancer accounts for approximately 15%-20% of all breast cancer cases and is considered a highly aggressive subtype. Neoadjuvant therapy combining trastuzumab-based dual or single HER2-targeted agents with chemotherapy has become the standard treatment for early-stage HER2-positive breast cancer. However, studies indicate that some patients do not respond well to this treatment and fail to achieve pathological complete response (pCR) [5-7]. Molecular targeted therapy benefits only a subset of patients, highlighting the urgent need to develop novel multi-target drugs with higher efficacy and lower toxicity [8].
Human epidermal growth factor receptor 3 (HER3), a member of the HER family alongside HER2, has an unclear role and predictive value in breast cancer treatment, which remains a subject of debate. Additionally, the role of the phosphoinositide 3-kinase (PI3K) signaling pathway in breast cancer development is primarily studied in estrogen receptor (ER)–positive populations, with limited research in HER2-positive groups. This study aims to investigate the predictive value of HER3 expression levels and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutations on the efficacy of neoadjuvant therapy in HER2-positive breast cancer. The goal is to identify patients who are more likely to benefit from neoadjuvant treatment in HER2-positive breast cancer.
Materials and Methods
1. Source of specimens and analysis
Tissue samples were obtained from core needle biopsies performed before neoadjuvant therapy. Fifty-three patients’ clinical and pathological data were gathered from HER2-positive breast cancer patients who underwent neoadjuvant therapy at the Second Affiliated Hospital of Anhui Medical University between June 2017 and June 2024, but two of these patients were lost to follow-up (Fig. 1). This study has obtained ethical approval from Anhui Medical University (No. SL-YX2024-185).
Fig. 1.
Flowchart of human epidermal growth factor receptor 2 (HER2)–positive breast cancer patient cohort study: from neoadjuvant therapy to human epidermal growth factor receptor 3 (HER3) expression and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutational status analysis. IHC, immunohistochemistry.
Inclusion criteria were as follows: (1) female patients aged 18 to 75 years, (2) pathologically confirmed HER2-positive invasive breast cancer, (3) candidates for neoadjuvant chemotherapy, and (4) underwent neoadjuvant therapy with single or dual HER2-targeted agents combined with chemotherapy or chemotherapy alone, followed by surgical treatment.
Exclusion criteria were as follows: (1) HER2-negative cases, (2) incomplete clinical or pathological data, and (3) patients with distant metastases who could only receive palliative treatment and were not candidates for surgery.
2. Detection methods and criteria for results
1) HER3 immunohistochemical detection method
The levels of HER3 in tissue specimens were assessed through immunohistochemistry. The procedure is as follows: paraffin-embedded tissues were sectioned into 4 μm slices and placed on adhesive slides. After deparaffinization and hydration, antigen retrieval was performed using citrate buffer, followed by blocking of endogenous peroxidase activity with hydrogen peroxide. HER3 antibody (1:200 dilution, product No. 10369-1-AP, Wuhan Sanying) was applied to the sections and incubated at 37°C for 1 hour. Secondary antibody was added and incubated at room temperature for 20 minutes. The antigen-antibody reaction was visualized using diaminobenzidine as a chromogen. Brown deposits in the nucleus or cytoplasm indicated a positive reaction. The slides were then washed to terminate the reaction, stained with hematoxylin, blued, dehydrated, and mounted. HER3 expression was evaluated in both the cytoplasm and/or on the cell membrane, with assessment based on the criteria established by Connie G [6]. Two independent pathologists, blinded to the clinical and pathological data, reviewed the slides using a double-blind method. Discrepancies were resolved through discussion. HER3 staining intensity was scored as follows: (1) intensity “0”: no staining in tumor cells, (2) intensity “1”: staining in less than 20% of tumor cells or weak staining, and (3) intensity “2”: staining in more than 20% of tumor cells or strong staining.
Staining intensity of “0” was defined as HER3-negative, while intensities “1” and “2” were defined as HER3-positive. The immunohistochemical staining of HER3 is shown in Fig. 1.
2) PIK3CA amplification refractory mutation system–polymerase chain reaction detection method
Formalin-fixed, paraffin-embedded (FFPE) tumor blocks were analyzed under a microscope for tumor content and cellularity. A representative block containing at least 70% tumor cells was selected, and tumor tissue was scraped for DNA extraction. DNA was extracted using a manual column-based method, strictly following the instructions of the Aid FFPE Tissue DNA Extraction Kit. DNA concentration was adjusted to 3.0 ng/μL. The PIK3CA mutation detection was performed using the Aid Human PIK3CA Mutation Detection Kit (amplification refractory mutation system–polymerase chain reaction [ARMS-PCR] technology) following the manufacturer’s protocol, which specifically targets five high-frequency oncogenic mutations in PIK3CA: E542K and E545K and E545D in exon 9, and H1047R and H1047L in exon 20. PCR parameters were as follows: (1) 95°C for 5 minutes (1 cycle); (2) 95°C for 25 seconds, 64°C for 20 seconds, 72°C for 20 seconds (15 cycles); and (3) 93°C for 25 seconds, 60°C for 35 seconds, 72°C for 20 seconds (31 cycles).
Signals were collected at 60°C during the third stage.
3. Evaluation of therapeutic effectiveness
The histological response to neoadjuvant therapy was evaluated using the Miller-Payne grading system by comparing core needle biopsy results before treatment and post-surgical tissue specimens. pCR was defined as the absence of histological evidence of invasive carcinoma in the breast tissue after surgery, or the presence of only in situ carcinoma components (ypT0/Tis).
4. Statistical analysis
Data were analyzed using SPSS ver. 27.0 software (IBM Corp.). Chi-square tests were used for intergroup comparisons of qualitative data. Fisher’s exact test was applied when the sample size was ≤ 40, when more than 20% of cells had expected counts < 5, or when any cell had an expected count of 0. To identify independent predictors of pCR, a multivariable logistic regression model was constructed, incorporating clinicopathological variables (age, T category, N category, histological grade, hormone receptor status, HER2 expression level, Ki-67 index, targeted therapy, and molecular markers [HER3 expression status, PIK3CA mutation status]. Categorical variables were dummy-coded, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. A significance level of α=0.05 was set, with p < 0.05 indicating statistically significant differences.
Results
1. Clinicopathological characteristics
All 51 patients were female, and their specific clinicopathological characteristics are detailed in Table 1. The table provides comprehensive information, including age, tumor size, lymph node status, hormone receptor status, HER2 expression levels, Ki-67 index, targeted therapy, HER3 expression status, and PIK3CA mutation status, offering a thorough overview of the clinical and pathological profiles of the patients involved in the study.
Table 1.
Clinicopathologic characteristics of patients by HER3 expression and PIK3CA mutation status
| Clinicopathologic characteristic | Total cohort (n=51) | No. (%) |
No. (%) |
|||||
|---|---|---|---|---|---|---|---|---|
| HER3 IHC0 (n=22) | HER3 IHC1 (n=20) | HER3 IHC2 (n=9) | p-value | PIK3CA wild (n=36) | PIK3CA mutation (n=15) | p-value | ||
| Age (yr) | ||||||||
| ≤ 50 | 19 | 8 (42.1) | 7 (36.8) | 4 (21.2) | 0.863 | 11 (57.9) | 8 (42.1) | 0.203 |
| > 50 | 32 | 14 (43.8) | 13 (40.6) | 5 (15.6) | 25 (78.1) | 7 (21.9) | ||
| At the initial treatment, T | ||||||||
| T1 | 7 | 1 (14.3) | 5 (71.4) | 1 (14.3) | 0.353 | 6 (85.7) | 1 (14.3) | 0.831 |
| T2 | 26 | 13 (50.0) | 9 (34.6) | 4 (15.4) | 18 (69.2) | 8 (30.8) | ||
| T3 | 18 | 8 (44.5) | 6 (33.3) | 4 (22.2) | 12 (66.7) | 6 (33.3) | ||
| At the initial treatment, N | ||||||||
| Negative | 20 | 10 (50.0) | 6 (30.0) | 4 (20.0) | 0.645 | 13 (65.0) | 7 (35.0) | 0.539 |
| Positive | 31 | 12 (38.7) | 14 (45.2) | 5 (16.1) | 23 (74.2) | 8 (25.8) | ||
| Histological grade | ||||||||
| I-II | 37 | 12 (32.4) | 18 (48.7) | 7 (18.9) | 0.039 | 25 (67.6) | 12 (32.4) | 0.513 |
| III | 14 | 10 (71.4) | 2 (14.3) | 2 (14.3) | 11 (78.6) | 3 (21.4) | ||
| Estrogen receptor | ||||||||
| Negative | 27 | 17 (63.0) | 7 (25.9) | 3 (11.1) | 0.010 | 20 (74.1) | 7 (25.9) | 0.759 |
| Positive | 24 | 5 (20.8) | 13 (54.2) | 6 (25.0) | 16 (66.7) | 8 (33.3) | ||
| Progesterone receptor | ||||||||
| Negative | 20 | 12 (60.0) | 5 (25.0) | 3 (15.0) | 0.149 | 15 (75.0) | 5 (25.0) | 0.755 |
| Positive | 31 | 10 (32.3) | 15 (48.3) | 6 (19.4) | 21 (67.7) | 10 (32.3) | ||
| Hormone receptor | ||||||||
| Negative | 16 | 11 (68.7) | 3 (18.8) | 2 (12.5) | 0.041 | 12 (75.0) | 4 (25.0) | 0.640 |
| Positive | 35 | 11 (31.4) | 17 (48.6) | 7 (20.0) | 24 (68.6) | 11 (31.4) | ||
| HER2 expression | ||||||||
| IHC2 | 4 | 2 (50.0) | 1 (25.0) | 1 (25.0) | 0.824 | 4 (100) | 0 | 0.307 |
| IHC3 | 47 | 20 (42.6) | 19 (40.4) | 8 (17.0) | 32 (68.1) | 15 (31.9) | ||
| Ki-67 (%) | ||||||||
| < 30 | 19 | 6 (31.6) | 11 (57.9) | 2 (10.5) | 0.122 | 14 (73.7) | 5 (26.3) | 0.761 |
| ≥ 30 | 32 | 16 (50.0) | 9 (28.1) | 7 (21.9) | 22 (68.7) | 10 (31.3) | ||
| Targeted therapy | ||||||||
| Not receiving | 6 | 3 (50.0) | 1 (16.7) | 2 (33.3) | 0.236 | 4 (66.7) | 2 (33.3) | 0.129 |
| Trastuzumab | 21 | 9 (42.9) | 11 (52.3) | 1 (4.8) | 18 (85.7) | 3 (14.3) | ||
| Trastuzumab+pertuzumab | 24 | 10 (41.7) | 8 (33.3) | 6 (25.0) | 14 (58.3) | 10 (41.7) | ||
| Pathologic response | ||||||||
| pCR | 19 | 13 (68.4) | 4 (21.1) | 2 (10.5) | 0.019 | 14 (73.7) | 5 (26.3) | 0.708 |
| Non-pCR | 32 | 9 (28.1) | 16 (50.0) | 7 (21.9) | 22 (68.7) | 10 (31.3) | ||
HER3, human epidermal growth factor receptor 3; IHC, immunohistochemistry; pCR, pathological complete response; PIK3CA, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha.
2. Analysis of the correlation between HER3 and pCR
HER3 expression was detected in 29 patients (56.9%), and a significant correlation between HER3 expression levels and pCR was observed (χ2=7.905, p=0.019). This indicates that higher HER3-positive expression may be associated with pCR outcomes, as detailed in Table 2 and Fig. 2.
Table 2.
Correlation analysis between HER3 expression and pCR
| HER3 expression | No./Total No. (%) |
χ2 | p-value | |
|---|---|---|---|---|
| pCR (n=19) | Non-pCR (n=32) | |||
| IHC0 | 13 (59.1) | 9 (40.9) | 7.905 | 0.019 |
| IHC1 | 4 (20.0) | 16 (80.0) | ||
| IHC2 | 2 (22.2) | 7 (77.8) | ||
HER3, human epidermal growth factor receptor 3; IHC, immunohistochemistry; pCR, pathological complete response.
Fig. 2.
Immunohistochemical (IHC) staining results of human epidermal growth factor receptor 3 (HER3) expression in human epidermal growth factor receptor 2 (HER2)–positive breast cancer specimens after neoadjuvant therapy. (A) HER3 expression level IHC0 (×100). (B) HER3 expression level IHC0 (×400). (C) HER3 expression level IHC1 (×100). (D) HER3 expression level IHC1 (×400). (E) HER3 expression level IHC2 (×100). (F) HER3 expression level IHC2 (×400).
3. Analysis of the correlation between PIK3CA and pCR
PIK3CA mutations were present in 15 patients (29.4%), including 10 cases of H1047R, two cases of E542K, two cases of E545K, and one case of H1047L. No E545D mutation was detected, and all the mutations were single-point mutations. However, the PIK3CA mutation status was not associated with the pCR rate (χ2=0.140, p=0.708), as detailed in Table 3.
Table 3.
Correlation analysis between PIK3CA mutational status and pCR
| PIK3CA mutational status | No./Total No. (%) |
χ2 | p-value | |
|---|---|---|---|---|
| pCR (n=19) | Non-pCR (n=32) | |||
| Wild | 14 (38.8) | 22 (61.1) | 0.140 | 0.708 |
| Mutation | 5 (33.3) | 10 (66.7) | ||
pCR, pathological complete response; PIK3CA, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha.
4. Analysis of the correlation between HER3 and PIK3CA
Among patients with HER3 overexpression, 11 out of 29 (37.9%) had PIK3CA mutations, while among HER3-negative patients, four out of 22 (18.2%) had PIK3CA mutations, a difference that is statistically significant (χ2=6.743, p=0.027), as detailed in Table 4.
Table 4.
Correlation analysis between HER3 expression and PIK3CA mutational status
| HER3 expression | No./Total No. (%) |
χ2 | p-value | |
|---|---|---|---|---|
| Wild (n=36) | Mutation (n=15) | |||
| IHC0 | 18 (81.8) | 4 (18.2) | 6.743 | 0.027 |
| IHC1 | 15 (75.0) | 5 (25.0) | ||
| IHC2 | 3 (33.3) | 6 (66.7) | ||
HER3, human epidermal growth factor receptor 3; IHC, immunohistochemistry; PIK3CA, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha.
5. The effects of HER3 and PIK3CA on pCR
Based on Tables 2 and 3, HER3 was found to be associated with pCR (χ2=7.905, p=0.019), while PIK3CA was not (χ2=0.140, p=0.708). However, considering the significant clinical relevance of PIK3CA mutations, patients were divided into four groups based on HER3 expression and PIK3CA mutation status. The analysis of their correlation with pCR revealed that HER3 and PIK3CA jointly influence pCR, as shown in Table 5 and Fig. 3.
Table 5.
The impact of combination of HER3 expression and PIK3CA mutational status on pCR
| HER3 expression and PIK3CA mutational status | No./Total No. (%) |
χ2 | p-value | |
|---|---|---|---|---|
| pCR (n=19) | Non-pCR (n=32) | |||
| HER3+ & PIK3CA mutation | 2 (18.2) | 9 (81.8) | 8.47 | 0.036 |
| HER3+ & PIK3CA wild | 4 (22.2) | 14 (77.8) | ||
| HER3– & PIK3CA mutation | 3 (75.0) | 1 (25.0) | ||
| HER3– & PIK3CA wild | 10 (55.6) | 8 (44.4) | ||
HER3, human epidermal growth factor receptor 3; pCR, pathological complete response; PIK3CA, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha.
Fig. 3.
Impact of human epidermal growth factor receptor 3 (HER3) expression and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) status on pathological response. (A) Relationship between HER3 expression and pathological response. (B) Relationship between PIK3CA status and pathological response. (C) Combined impact of HER3 expression and PIK3CA status on pathological response. pCR, pathological complete response.
6. Analysis of the correlation between targeted therapy and pCR
To evaluate the impact of different HER2-targeted regimens on pCR, patients were stratified by therapeutic strategy: trastuzumab monotherapy (n=21), dual HER2-targeted therapy (trastuzumab+pertuzumab) with chemotherapy (n=24), and no targeted therapy due to financial reasons (n=6). The pCR rates were 33.3% (7/21) in the trastuzumab group, 41.7% (10/24) in the dual-targeted group, and 33.3% (2/6) in the non-targeted group. No statistically significant association was observed between therapeutic regimen and pCR (χ2=0.377, p=0.828) (Table 6). This suggests that the addition of pertuzumab to trastuzumab-based neoadjuvant therapy did not significantly improve pCR rates in this cohort, though the small sample size may limit statistical power.
Table 6.
Correlation analysis between targeted therapy and pCR
| Targeted therapy | No./Total No. (%) |
χ2 | p-value | |
|---|---|---|---|---|
| pCR (n=19) | Non-pCR (n=32) | |||
| Not receiving | 2 (33.3) | 4 (66.7) | 0.377 | 0.828 |
| Trastuzumab | 7 (33.3) | 14 (66.7) | ||
| Trastuzumab+pertuzumab | 10 (41.7) | 14 (58.3) | ||
pCR, pathological complete response.
7. Multivariable analysis of clinicopathological and molecular predictors for pCR
A multivariable logistic regression model incorporating clinicopathological variables (age, tumor size, nodal status, histological grade, hormone receptor status, HER2 expression, Ki-67 index, therapeutic regimen) and molecular markers (HER3 expression, PIK3CA mutation status) was performed to identify independent predictors of pCR. HER3-positive expression emerged as a significant negative predictor of pCR (OR, 0.08; 95% CI, 0.01 to 0.50; p=0.008). In contrast, PIK3CA mutation status showed no independent association with pCR (OR, 1.23; 95% CI, 0.23 to 6.68; p=0.813). None of the other variables, including therapeutic regimen (trastuzumab±pertuzumab), age, tumor stage, nodal involvement, hormone receptor status, or Ki-67 index, demonstrated statistically significant associations with pCR in the adjusted model (all p > 0.05) (Table 7). These results underscore HER3 expression as a robust independent biomarker for predicting resistance to neoadjuvant therapy in HER2-positive breast cancer.
Table 7.
Multivariable logistic regression analysis of clinicopathological and molecular predictors for pCR in HER2-positive breast cancer
| Variable | β | SE | Wald | OR (95%CI) | p-value |
|---|---|---|---|---|---|
| Age (> 50 yr vs. ≤ 50 yr) | 0.563 | 0.988 | 0.325 | 1.76 (0.25–12.18) | 0.596 |
| At the initial treatment, T (T2 vs. T1) | –1.322 | 1.240 | 1.137 | 0.27 (0.02–3.03) | 0.286 |
| At the initial treatment, T (T3 vs. T1) | –1.148 | 1.386 | 0.686 | 0.32 (0.21–4.80) | 0.407 |
| At the initial treatment, N (positive vs. negative) | –0.965 | 0.789 | 1.496 | 0.38 (0.08–1.79) | 0.221 |
| Histological grade (III vs. I-II) | –0.360 | 1.034 | 0.121 | 0.69 (0.09–5.29) | 0.720 |
| Hormone receptor (positive vs. negative) | 1.335 | 0.895 | 2.411 | 3.80 (0.71–20.47) | 0.120 |
| HER2 expression (IHC3 vs. IHC2) | 0.454 | 1.525 | 0.088 | 1.57 (0.08–31.29) | 0.766 |
| Ki-67 index (≥ 30% vs. < 30%) | 0.424 | 0.942 | 0.202 | 1.53 (0.24–9.68) | 0.653 |
| Therapeutic regimens (trastuzumab+chemotherapy vs. not receiving) | –0.062 | 1.279 | 0.002 | 0.94 (0.08–11.53) | 0.961 |
| Therapeutic regimens (trastuzumab+pertuzumab+chemotherapy vs. not receiving) | 0.222 | 1.387 | 0.026 | 1.25 (0.08–18.91) | 0.873 |
| HER3 expression (positive vs. negative) | –2.590 | 0.971 | 7.115 | 0.08 (0.01–0.50) | 0.008 |
| PIK3CA mutation status (mutation vs. wild) | 0.205 | 0.864 | 0.056 | 1.23 (0.23–6.68) | 0.813 |
CI, confidence interval; HER2, human epidermal growth factor receptor 2; HER3, human epidermal growth factor receptor 3; IHC, immunohistochemistry; OR, odds ratio; pCR, pathological complete response; PIK3CA, phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha; SE, standard error.
Discussion
HER2 is overexpressed in approximately 15%-20% of breast cancers [9]. Previously, HER2-positive breast cancer was highly aggressive, with a high risk of recurrence and metastasis. With the application of dual-targeted therapy combined with chemotherapy in neoadjuvant treatment, the treatment paradigm and prognosis of HER2-positive breast cancer have been completely transformed. However, approximately 40%-60% of patients still fail to achieve pCR [7,10].
pCR is defined as the absence of invasive primary cancer and negative regional lymph nodes (ypT0/Tis ypN0). In clinical practice, individuals who did not achieve pCR with neoadjuvant therapy have shorter disease-free survival and overall survival, and poorer outcomes compared to those who achieved pCR [11]. Of the 51 patients included in this study, 32 did not achieve pCR, accounting for 62.7% (Table 1). Previous studies have found that HER3 overexpression and PIK3CA gene mutation are associated with poor prognosis of breast cancer [12,13]. Therefore, this study aims to explore the predictive value of HER3 expression levels and PIK3CA mutations for the efficacy of neoadjuvant therapy in HER2-positive breast cancer patients, with the goal of identifying patient populations that may benefit from neoadjuvant treatment. HER2 and HER3 both belong to the HER family, and the dimer formed by HER2 and HER3 is crucial for the activation of HER2-mediated signaling pathways. It is also the most potent heterodimeric form within the HER family [14]. This heterodimer activates protein fragments on the inner side of the cell membrane containing tyrosine residues, leading to their phosphorylation and subsequently activating downstream signaling pathways. These pathways are associated with cell proliferation, invasion, and metastasis [15]. According to the literature, HER3 overexpression is observed in 30%-75% of invasive breast cancers [16]. We analyzed the expression levels of HER3 in breast cancer tissues, and the positive expression rate was 56.9% (Table 1), consistent with the aforementioned literature reports. Pascual et al. [17] found that HER3 overexpression is more prevalent in hormone receptor-positive cases. In this study, HER3 overexpression was observed in 10 out of 27 (37.0%) ER-negative cases and 19 out of 24 (79.2%) ER-positive cases (Table 1), showing a statistically significant difference, consistent with the aforementioned studies. HER3-positive patients had higher histological grades and a higher proportion of lymph node metastasis, factors that contribute to greater tumor progression, invasiveness, metastasis, and potential for recurrence [18]. Based on such research findings, breast cancer patients with co-expression of HER2 and HER3 may have a poorer prognosis. In evaluating the short-term efficacy of neoadjuvant therapy in 51 HER2-overexpressing breast cancer patients from this study, we found that 13 out of 22 (59.1%) HER3-negative patients achieved pCR, while only 6 out of 29 (20.7%) HER3-positive patients achieved pCR, a statistically significant difference (Table 2, Fig. 2). This preliminary result confirms that HER3 overexpression is associated with a lower likelihood of achieving pCR. We speculate that this may be due to compensatory overexpression of HER3 following the use of anti-HER2 targeted drugs, leading to the formation of HER2-HER3 heterodimers, which activate downstream signaling pathways such as PI3K/Akt and RAS/mitogen-activated protein kinase (MAPK), thereby promoting breast cancer cell proliferation [19,20].
The PI3K/protein kinase B (PKB, AKT)/mechanistic target of rapamycin (mTOR) signaling pathway is a highly conserved major transduction network in all higher eukaryotic cells, promoting cell survival, growth, and proliferation in response to external stimuli. PI3K is a heterodimer composed of a p110 catalytic subunit and a p85 regulatory subunit. The p85α subunit is recruited to tyrosine-phosphorylated receptors, activating the p110α catalytic subunit, or p110α directly binds to RAS, transmitting signals downstream to tyrosine kinases associated with the plasma membrane, thereby regulating cell growth, metabolism, survival, and proliferation. PIK3CA encodes the p110α subunit of the PI3K protein. Activation of the p110 subunit of PI3K is crucial for the PI3K/AKT pathway, and activating mutations in PIK3CA are among the most common oncogenic mutations detected across various tumor types [21]. PIK3CA mutations are commonly found across all subtypes of breast cancer, with 70%-80% of these mutations occurring at the E545K and E542K sites in exon 9, and the H1047R site in exon 20, which are closely associated with oncogenic activity. The mutation rate of PIK3CA in HER2-positive breast cancer is 25%-30% [22]. This study found that the most common PIK3CA mutation in HER2-positive breast cancer is H1047R, followed by E545K and E542K. Among the patients in this study, 15 cases (29.41%) had PIK3CA mutations, including 10 cases of H1047R, two cases of E542K, two cases of E545K, and one case of H1047L. No E545D mutation was detected, and all mutations were point mutations. Some studies have found that in HER2-positive breast cancer, PIK3CA mutations are associated with a lower pCR rate, particularly in HER2-positive breast cancer patients receiving neoadjuvant trastuzumab and lapatinib [23]. However, some studies have found that in HER2-positive breast cancer patients receiving dual-targeted therapy combined with chemotherapy, the PIK3CA mutation status is not clearly associated with pCR, and PIK3CA mutations cannot be used as biomarkers to predict patient outcomes [24]. This study aimed to evaluate the correlation between PIK3CA mutations and pCR in HER2+ breast cancer. However, it found no statistically significant correlation between PIK3CA mutation status and pCR (Table 3), possibly due to the small sample size and the lack of detailed molecular subtyping in the analysis of the correlation between PIK3CA mutations and pCR.
Studies have shown that HER3 possesses some kinase activity, but it is 1,000 times weaker than the fully activated EGFR. HER3 can only activate its intracellular domain by forming heterodimers with other receptors. The intracellular domain of HER3 contains nine tyrosine phosphorylation sites with known functions, six of which serve as docking sites for the p85 regulatory subunit of PI3K. Therefore, HER3 is a strong activator of the PI3K/AKT signaling pathway and is crucial for tumor cell survival. HER3 can also activate the MAPK signaling pathway, stimulating cell proliferation. HER3 primarily functions through the activation of the PI3K/AKT signaling pathway, playing a vital role in tumor cell survival. In this study, we found that among patients with HER3 overexpression, 11 out of 29 (37.9%) had PIK3CA mutations, while among HER3-negative patients, 4 out of 22 (18.2%) had PIK3CA mutations, a difference that is statistically significant (Table 4). This suggests a correlation between HER3 overexpression and PIK3CA mutations. Therefore, patients were divided into four groups based on HER3 overexpression and PIK3CA mutation status to analyze their correlation with pCR. The findings indicate that HER3 overexpression and PIK3CA mutations jointly influence pCR in HER2-positive breast cancer patients (Table 5, Fig. 3). This may be because HER3 overexpression primarily activates the PI3K/AKT signaling pathway, but PI3K can also be activated through other upstream pathways, such as other receptor tyrosine kinases and G-protein coupled receptors [25].
This study demonstrates that HER3 overexpression makes it difficult for patients to achieve pCR, and that HER2-positive breast cancer patients with HER3 overexpression and PIK3CA mutations have poorer responses to neoadjuvant therapy. However, this study has several limitations. First, the small cohort size (n=51) may reduce statistical power.
Limited PIK3CA-mutated subgroup and targeted therapy subgroup potentially contribute to the non-significant association as a type II error. Second, the single-center retrospective design introduces selection bias and treatment heterogeneity (e.g., variable chemotherapy/HER2-targeted regimens), limiting generalizability. Third, while HER3 overexpression correlated with poor pCR, our hypothesis that HER2/HER3 heterodimers drive PI3K/AKT-mediated resistance remains unverified mechanistically. Fourth, ARMS-PCR restricted PIK3CA profiling to five high-frequency mutations (E542K, E545K/D, H1047R/L), omitting 6/11 clinically actionable variants (e.g., C420R, Q546K), which may underestimate mutational impacts. Future multi-center prospective studies with standardized therapies should validate these findings in larger cohorts. Comprehensive PIK3CA profiling via next-generation sequencing is required to delineate mutation-specific therapeutic vulnerabilities. Functional studies using HER2+/HER3+ models should quantify heterodimer-driven PI3K/AKT activation and test combinatorial strategies (e.g., HER3/PI3K inhibitors). Integrated multi-omics (phosphoproteomics, spatial transcriptomics) may unravel resistance mechanisms, while biomarker-driven trials could optimize patient stratification for HER2-targeted neoadjuvant regimens.
Footnotes
Ethical Statement
All procedures followed the ethical guidelines of the Declaration of Helsinki in 1964 and its subsequent amendments. The study received approval from the Ethics Committee of the Second Affiliated Hospital of Anhui Medical University (No. SL-YX2024-185). This study declared that informed consent has been obtained from all participating patients.
Author Contributions
Conceived and designed the analysis: Xia X, Zong Z, Li F, Wang H.
Collected the data: Xia X, Zong Z, Shen J, Zhou L, Li J, Zheng L, Li F, Wang H.
Contributed data or analysis tools: Xia X, Zong Z, Lei Y, Li F, Wang H.
Performed the analysis: Xia X, Shen J, Zhou L, Lei Y, Li F, Wang H.
Wrote the paper: Xia X, Shen J, Li F, Wang H.
Conflict of Interest
Conflict of interest relevant to this article was not reported.
Funding
This work is supported by the Anhui Province Key Research and Development Plan (Grant No. 2022e07020038), and Postgraduate Innovation Research and Practice Program of Anhui Medical University (YJS20240102).
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