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Excessive glutathione intake contributes to chemotherapy resistance in breast cancer: a propensity score matching analysis

World Journal of Surgical Oncology volume 22, Article number: 345 (2024) Cite this article

Abstract

Background

We aim to explore the impact of excessive glutathione (GSH) intake on chemotherapy sensitivity in breast cancer.

Methods

Clinicopathological data were collected from 460 breast cancer patients who underwent adjuvant chemotherapy from January 2016 to December 2019 from Zhengzhou University People’s Hospital. The clinicopathological characteristics following GSH treatment were collected and compared with those in Non-GSH group after 1:2 propensity score matching (PSM). Intracellular GSH levels and the expression of antioxidant enzymes (NRF2, GPX4 and SOD1) were evaluated in tumor tissues in 51 patients receiving neoadjuvant chemotherapy.

Results

The recurrence rate after adjuvant chemotherapy was significantly higher in the GSH group (n = 28, 31.8%) than that in the Non-GSH group (n = 39, 22.2%; P = 0.010). Additionally, patients in the HGSH group (high GSH intake, ≥ 16 days) exhibited an elevated recurrence rate compared to that in the LGSH group (low GSH intake, < 16 days) (n = 15 (46.8%) vs. n = 52 (22.4%); P = 0.003). Cox regression revealed that High GSH intake, Ki67 ≥ 30%, Triple negative and Lymphovascular invasion were independent risk factors of progression after adjuvant chemotherapy. Among patients receiving neoadjuvant chemotherapy, intracellular GSH levels and the expression levels of antioxidant enzymes (NRF2, GPX4 and SOD1) in the resistant patients were substantially higher (P < 0.001).

Conclusions

Excessive GSH intake may contribute to chemotherapy resistance in breast cancer, and the levels of intracellular GSH and antioxidant enzymes are elevated in resistant patients after neoadjuvant chemotherapy, indicating that the standardization of GSH intake may assist in reducing chemotherapy resistance.

Introduction

Breast cancer is the most common malignancy among women worldwide. Despite significant advancements in diagnosis and treatment, the prognosis of breast cancer patients remains unsatisfactory [1]. The main treatment options for breast cancer include surgery, chemotherapy, radiotherapy, endocrine therapy, and targeted therapy [2]. Treatment regimen is generally based on the stage of cancer, tumor characteristics, molecular subtype, immunohistochemistry, and the patient’s overall health status. Despite 80%–90% of patients are eligible for surgery, 30%–40% will inevitably experience recurrence and metastasis. Additionally, 10%–20% of patients may be deemed unsuitable for surgical intervention at the time of initial treatment [3]. To improve outcomes, around 60%-80% require adjuvant and neoadjuvant chemotherapy to diminish the recurrence risk [4, 5]. However, a large number of patients still exhibit primary or secondary resistance to chemotherapy drugs, leading to poor prognosis. In recent years, the Royal Marsden Hospital (RMH) Score has shown promise as a valuable prognostic tool for assessing patient outcomes, while reliable indicators to predict recurrence and mortality following chemotherapy resistance remain scarce [6].

Chemotherapy-induced apoptosis is widely recognized as a primary mechanism for tumor cell destruction [7]. Chemotherapy promotes the production of Reactive Oxygen Species (ROS), which triggers apoptosis and damages both tumor cells and healthy cells. In response to the oxidative stress-induced damage, tumor cells upregulate their antioxidant systems, upregulating intracellular GSH levels [8]. This adaptation, which mitigates chemotherapy-induced oxidative damage, inadvertently promotes drug resistance and undermines the treatment’s efficacy. Besides, chemotherapy may cause various adverse effects, including hepatotoxicity, cardiotoxicity, and neurotoxicity [9]. According to Chinese Society of Clinical Oncology (CSCO) and European Association for the Study of the Liver (EASL) Clinical Practice Guidelines [10, 11], hepatoprotective treatments are recommended when Alanine Aminotransferase (ALT) levels exceed three times the normal value or total bilirubin is more than twice the normal value. The guidelines, however, do not specify whether glutathione can be used or provide recommendations regarding its duration and the use of hepatoprotective drugs in clinical practice is not standardized. Previous studies have documented elevated GSH levels in various tumors, contributing to chemotherapy resistance and counteracting its cytotoxic effects [12]. Nevertheless, there are limited studies investigating the impact of non-standardized GSH intake in chemotherapy for breast cancer.

Utilizing a large cohort of breast cancer patients, we explored the relationship between GSH intake dosage and resistance to adjuvant or neoadjuvant chemotherapy. Furthermore, we assessed the intracellular levels of GSH and antioxidant enzymes in patients undergoing neoadjuvant chemotherapy. In selecting appropriate dosages of GSH as a hepatoprotective agent, we aspire to provide a thoughtful reflection on these considerations.

Materials and methods

Patients

We retrospectively collected clinical data from 460 breast cancer patients who underwent surgery at Zhengzhou University People’s Hospital between January 2016 and December 2019. The inclusion criteria were: (I) a pathological diagnosis of breast cancer; (II) female patients; (III) complete and reliable clinical and pathological data. The exclusion criteria were: (I) severe underlying diseases; (II) conditions precluding surgery, such as multiple distant metastases, poor physical condition, or an unfavorable prognosis; (III) loss to follow-up or death from causes irrelevant to the study. Based on these criteria, we ultimately included 366 breast cancer patients. Additionally, 51 patients who received neoadjuvant chemotherapy between January 2016 and December 2019 were analyzed separately. The study was approved by the Ethics Committee of Zhengzhou University People’s Hospital. All patients or their families provided written informed consent.

Description of the chemotherapy process and the definition of GSH intake duration

According to the CSCO guidelines, indications for adjuvant chemotherapy involve lymph node metastasis, triple-negative, HER2-positive, and hormone receptor-positive cases with a 21-gene recurrence score (RS) exceeding 26. Most patients in the study received “AC-T” (Adriamycin, Cyclophosphamide followed by Docetaxel or Taxol) for 8 cycles, “TCb” (Docetaxel or Taxol, Carboplatin) for 6 cycles, “TC” (Docetaxel or Taxol, Cyclophosphamide) for 4 cycles, or “AC” (Adriamycin, Cyclophosphamide) for 4 cycles.

According to the CSCO guidelines, indications for neoadjuvant chemotherapy include lymph node metastasis, tumor diameter greater than 5 cm, HER2-positive, triple-negative, and relatively large tumors with a desire to preserve the breast. Most patients receiving neoadjuvant chemotherapy in the study received “TAC” (Docetaxel or Taxol, Adriamycin, Cyclophosphamide) for 6 cycles, or “TCb” (Docetaxel or Taxol, Carboplatin) for 6 cycles.

According to CSCO Guidelines, hepatoprotective treatment with drugs is required when ALT levels exceed three times the normal value. In this study, chemotherapy patients routinely had their liver function (ALT and AST) assessed post-chemotherapy. If ALT levels exceeded three times the normal value, chemotherapy was paused, and patients initiated oral GSH administration until liver function tests indicated normalized transaminase levels. The duration of GSH administration was defined as the cumulative number of days GSH was taken throughout each chemotherapy cycle. In addition, the dosage of GSH administered to the patient each time was based on the GSH instructions, with 400 mg orally three times a day. The total duration and dosage of glutathione use were recorded by reviewing electronic medical records and through telephone follow-ups.

The evaluation of chemotherapy adverse reactions follows the Common Terminology Criteria for Adverse Events (CTCAE) guidelines.

Follow-up

In this study, patients routinely began adjuvant chemotherapy approximately two weeks after surgery, with monitoring conducted during 4, 6, or 8 cycles of chemotherapy. Follow-up was conducted one month after surgery, with additional visits scheduled every three months during the first two years, and then every six months thereafter through either telephone consultations or outpatient visits. Follow-up assessments involved physical examinations, routine blood tests, serum tumor marker measurements, breast ultrasound, chest and abdominal computed tomography (CT) scans, magnetic resonance imaging (MRI), and ultrasound every three months for the first two years, and every six months afterward. Additionally, a full-body bone scan and positron emission tomography-computed tomography (PET-CT) were performed annually. All follow-up data collection was completed before July 1, 2024. The primary endpoints of this study were Overall Survival (OS) and Disease-Free Survival (DFS). OS was defined as the time from the surgery date to the end date of follow-up or death, while DFS was defined as the time from surgery to either disease recurrence or the end date of follow-up. Postoperative progression was defined as local tumor recurrence or the development of new metastatic lesions. Progression was confirmed through imaging studies, including breast ultrasound, chest and abdominal ultrasound, CT and/or MRI, PET-CT, or biopsy pathology results.

Patients undergoing neoadjuvant chemotherapy started treatment immediately after biopsy confirmation, with chemotherapy typically consisting of 6 or 8 cycles. Follow-up evaluations of the tumor were conducted before each chemotherapy cycle, including breast ultrasound, physical examinations, routine blood tests, and serum tumor marker measurements. Chest and abdominal ultrasound, CT and/or MRI were evaluated every two chemotherapy cycles. After all cycles of neoadjuvant chemotherapy, surgery or biopsy was performed followed by pathological evaluation to assess the efficacy of the treatment. The numbers of patients achieving pathological complete response (pCR), pathological partial response (pPR), and pathological no change (pNC) were recorded.

Clinicopathological indices

Clinicopathological data were collected for all patients, including menopausal status, age, hepatitis infection, preoperative liver function, preoperative blood routine, type of surgery, chemotherapy regimen, histological type and grade, tumor size, number of tumors, lymphovascular invasion, and treatment modalities such as radiotherapy and hormone therapy. Additional factors collected included Estrogen receptor/Progesterone receptor (ER/PR), Human Epidermal growth factor Receptor 2 (HER2), Ki67, molecular subtype, N stage, T stage, tumor-node-metastasis (TNM) stage, adverse reactions during chemotherapy, transaminase levels after chemotherapy, metastasis or recurrence, treatments after recurrence or metastasis, and survival status at the last follow-up.

Quantification of the GSH/GSSG ratio and the relative expression levels of NRF2, GPX4 and SOD1

To investigate the role of GSH in chemotherapy resistance, 51 patients who underwent neoadjuvant chemotherapy between January 2016 and December 2019 were enrolled in this study. None of these patients received neoadjuvant radiotherapy or endocrine therapy. In our study, participants who received neoadjuvant therapy were categorized as the sensitive group (patients with pCR and pPR, n = 30) or the resistant group (patients with pNC, n = 21). Moreover, we randomly selected 10 patients from both the sensitive and resistant groups. Tissue samples from both groups were collected post-surgery or biopsy to measure GSH levels, along with the relative expression levels of NRF2, GPX4 and SOD1.

GSH levels and the GSH/GSSG ratio were quantified using the GSH and GSSG Assay Kit (Biovision, K264) in accordance with the manufacturer’s instructions. The absorbance of GSH and GSSG at 412 nm was measured using a microplate reader. The results were normalized to protein concentration for accurate comparison. The expression levels of three mRNAs were quantified using qPCR. RNA was isolated with the RNA Isolation Kit V2 (Vazyme) according to the manufacturer’s protocol. Reverse transcription was performed using HiScript II Q Select RT SuperMix (+ gDNA wiper), following the manufacturer’s instructions. Quantitative PCR (qPCR) was subsequently carried out with ChamQ Universal SYBR qPCR Master Mix. Gene expression levels were normalized to β-actin levels in each sample. Primer sequences are provided in Supplementary Table 1.

Immunohistochemical analysis

The paraffin-embedded slides were first stained with hematoxylin and eosin (HE) prior to immunohistochemistry (IHC) analysis. For IHC staining, the tissue sections were incubated overnight at 4 °C with primary antibodies, including Anti-NRF2, Anti-GPX4 and Anti-SOD1, following the DAB substrate kit protocol (Zsbio Commerce Store). All IHC samples were evaluated by two independent pathologists, who were blinded to the source of the samples and the patient outcomes. Each core was assigned a score from 0 to 3 + based on the expression of NRF2, GPX4 or SOD1 in tumor cells. A score of 0 was assigned when expression was observed in less than 5% of tumor cells, 1 + for expression in 5–50%, 2 + for expression in 50–75%, and 3 + for expression in more than 75% of tumor cells. The final score for each tumor was calculated as the mean score of all tumor cores. Statistical analysis was performed based on the product of staining rate and staining intensity to assess the overall expression levels. The antibodies used in this study are listed in Supplementary Table 2.

Statistical analysis

Statistical analyses were performed using SPSS for Windows version 25.0. Categorical data were expressed as numbers and percentages, continuous variables were presented as the mean ± standard deviation (SD). The normality of continuous variables was assessed using the Shapiro–Wilk test. For normally distributed data, a two-tailed Student’s t test was used for comparisons between two groups. For non-normally distributed data, the Mann–Whitney U test was employed. Pearson’s chi-square test (χ2) was used to analyze categorical variables between LGSH (low GSH intake) group and HGSH (high GSH intake) group. Receiver operating characteristic (ROC) curves were applied to determine the cutoff value for the duration of glutathione intake. The Kaplan–Meier (KM) method was utilized to plot survival curves and calculate postoperative survival rates, with the log-rank test used to evaluate differences in survival times between groups. The Cox proportional hazards regression model was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to identify independent risk factors for patient prognosis. Univariate and multivariate Cox regression analyses were performed to assess predictors of long-term patient survival. In univariate logistic regression analysis, covariates with P-values less than 0.05 were considered statistically significant, and these variables were subsequently included in the multivariate analysis. PSM was employed to reduce bias due to differences in observed variables between the two groups in the retrospective observational study, and the analysis was conducted using R version 4.3.0. A P-value less than 0.05 was considered statistically significant.

Results

Baseline characteristics of breast cancer patients before and after PSM

After three years of follow-up, a total of 366 patients were included in this study, and were separated into GSH group (n = 120) and Non-GSH group (n = 246). Among them, 313 patients received mastectomy, while 37 patients underwent breast-conserving surgery. Additionally, 89 patients developed metastasis and recurrence, while 277 patients did not experience either.

PSM analysis was employed to balance the bias between the GSH and Non-GSH groups. Following 1:2 PSM, a total of 264 breast cancer patients were included in the analysis (Table 1 and Supplementary Table 3). The distributions of propensity scores before and after matching were summarized in Supplementary Fig. 1. Among these patients, there were 88 in the GSH group and 176 in the Non-GSH group. The mean age of these patients was 48.5 ± 10.84 years (range: 30—82 years), and the mean tumor size measured post-surgery was 1.819 ± 0.912 cm (range: 0.5—5.8 cm). The study workflow was illustrated in Fig. 1.

Table 1 Clinicopathological characteristics of enrolled breast cancer patients after surgery
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Fig. 1
figure 1

Flow diagram of the research strategy. Abbreviations: GSH: glutathione; PSM: propensity score matching

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Of those receiving GSH treatment, 39 were premenopausal (44.3%) and 49 were postmenopausal (55.7%). Among the 88 patients, 81 underwent mastectomy and 5 underwent breast conserving surgery. All surgical margins were negative. Furthermore, 58 patients received radiation therapy, and 54 received endocrine therapy.

In addition, of the 51 patients who received neoadjuvant chemotherapy, 30 achieved either a pathological partial response (n = 23, 45% patients) or complete response (n = 7, 14% patients), while 21 exhibited no pathological response. Moreover, among these patients, 31 were postmenopausal, and 20 were premenopausal (Table 2).

Table 2 Clinicopathological characteristics of patients receiving neoadjuvant chemotherapy
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Relationship between glutathione intake and clinicopathological indices in breast cancer patients

Glutathione intake was not significantly associated with preoperative clinical indicators. As shown in Supplementary Table 3, there were no significant differences between the GSH and Non-GSH groups regarding menopausal status, age, preoperative liver function, or other preoperative indicators. Before adjuvant chemotherapy, no significant differences were observed between GSH group and non-GSH group in terms of type of surgery, chemotherapy regimen, tumor size, number of tumors, histological grade, etc. (Table 1). However, GSH group had significantly higher levels of ALT (87.139 ± 2.731; P < 0.001) and AST (71.270 ± 1.113; P < 0.001) after chemotherapy and experienced more severe adverse reactions (P = 0.002), including a notably higher incidence of nausea and vomiting (P = 0.023). This is consistent with clinical practice, where chemotherapy patients with elevated transaminase levels usually use hepatoprotective drugs. Furthermore, GSH group showed a higher probability of recurrence and progression after adjuvant chemotherapy (P = 0.010) (Table 1).

Relationship between the duration of glutathione intake and clinical indicators in breast cancer patients

For the 88 participants who took GSH, the mean duration of GSH intake was 18 ± 0.82 days (range: 2—27 days). ROC analysis was carried out to screen the best cutoff value for GSH intake, and the curves with variable cutoff numbers were presented in Fig. 2. The duration of GSH administration was defined as the cumulative number of days GSH was taken throughout each chemotherapy cycle. In addition, the dosage of GSH administered to the patient each time was based on the GSH instructions. Specifically, recurrence after adjuvant chemotherapy was used as the outcome variable to generate the ROC curve. The optimal cutoff point for GSH intake duration was determined to be 16 days, based on the maximum Youden index (Youden index = specificity + sensitivity − 1). The area under the ROC curve was 0.858, with a sensitivity of 84.8% and specificity of 83.3% (Fig. 2).

Fig. 2
figure 2

ROC curve indicating that the highest sensitivity and specificity can be achieved using the average of 16 days, P < 0.001

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Patients were divided into HGSH (≥ 16 days, n = 32) group and LGSH (< 16 days, n = 232) group based on a cutoff value of 16 days. There were no significant associations between the duration of GSH administration and pre-chemotherapy indicators, such as menopausal status and preoperative liver function (P > 0.05) (Supplementary Table 4). However, patients in the HGSH group experienced more severe adverse chemotherapy reactions (P < 0.001), along with ALT and AST levels (P < 0.001). Moreover, patients in the HGSH group showed a higher incidence of postoperative recurrence and metastasis (P = 0.003) (Table 3), as well as reduced DFS (P = 0.001) and OS (P = 0.026) (Fig. 3C and D). These findings suggest that high GSH intake is a significant predictor of recurrence and metastasis in breast cancer patients after chemotherapy.

Table 3 Postoperative clinicopathological characteristics in the LGSH (Low GSH intake) group and the HGSH (High GSH intake) group
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Fig. 3
figure 3

Kaplan–Meier analysis for patients after adjuvant chemotherapy for breast cancer. A Survival curves of OS for the GSH group and the Non-GSH group. B Survival curves of DFS for the GSH group and the Non-GSH group. C Survival curves of OS for the LGSH (Low GSH intake) group and the HGSH (High GSH intake) group. D Survival curves of DFS for the LGSH group and HGSH group

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Survival analysis of patients receiving postoperative chemotherapy for breast cancer

The Kaplan–Meier curves for OS and DFS in the GSH and Non-GSH groups after PSM are presented in Fig. 3A and B. GSH administration was associated with shorter OS and DFS in breast cancer patients, with a median survival of 68 months in the GSH group, compared to 74 months in the Non-GSH group (P = 0.023). Additionally, we investigated the effect of the duration of GSH administration on OS and DFS. As illustrated in Fig. 3C and D, patients in the LGSH group exhibited significantly improved OS and DFS compared to those in the HGSH group (median OS: 70 months vs. 64 months, P = 0.026).

Risk factors on the prognosis of breast cancer patients receiving postoperative chemotherapy

Univariate logistic regression analysis identified Ki67 ≥ 30%, Lymphovascular invasion, Triple-negative status, TNM stage III, and High GSH intake as independent predictors of recurrence and metastasis in breast cancer patients after chemotherapy (P < 0.05). In comparison to Grade I and II histology, Grade III histology was found to be a risk factor for adverse breast cancer outcomes (P = 0.018). Multivariate analysis demonstrated that Ki67 ≥ 30% (P < 0.001), Lymphovascular invasion (P = 0.023), Triple-negative status (P < 0.001), and High GSH intake are independent predictors of poor prognosis (Table 4).

Table 4 Univariate and multivariate Cox regression analyses of risk factors in breast cancer patients undergoing chemotherapy
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Measurement of the levels of intracellular GSH and the relative expression of NRF2, GPX4 and SOD1 in tissue samples following neoadjuvant chemotherapy

To further verify the role of GSH metabolism in chemotherapy resistance, we analyzed breast cancer data from the Gene Expression Omnibus (GEO) dataset (GEO: GSE140494). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Variation Analysis (GSVA) analysis revealed significant activation of the glutathione metabolism pathway in drug-resistant breast cancer tissues compared to sensitive tissues after FEC (5-Fluorouracil, Epirubicin, and Cyclophosphamide) + docetaxel treatment (Fig. 4A and B).

Fig. 4
figure 4

High levels of intracellular GSH contribute to chemotherapy resistance in breast cancer. A KEGG analysis highlighted the glutathione metabolism pathway as the most significantly upregulated in the resistant patients. B GSVA revealed notable upregulation of the glutathione metabolism pathway in the resistant patients. C The levels of intracellular GSH in chemotherapy-resistant and chemotherapy-sensitive patients. D Relative expression levels of NRF2, GPX4 and SOD1 in chemotherapy-resistant and chemotherapy-sensitive tumor tissues. All assays were performed independently in triplicate. E Representative case illustrates the comparison between chemotherapy-sensitive (pCR + pPR, n = 32) and chemotherapy-resistant (pNC, n = 19) breast cancer patients of representative before and after neoadjuvant chemotherapy assessed by MRI images. Scale bar: 2 cm. F Representative case illustrates the comparison between high and low expression levels of NRF2, GPX4 and SOD1 in chemotherapy-sensitive (pCR + pPR, n = 32) and chemotherapy-resistant (pNC, n = 19) breast cancer tissues assessed by immunohistochemistry(IHC) staining. Scale bar: 200 µm. G ROC curves were used to determine the optimal cutoff value for intracellular GSH levels distinguishing between drug-resistant and sensitive cells in the context of neoadjuvant chemotherapy. H Evaluation of the pathological response to neoadjuvant chemotherapy in 51 patients based on modified RECIST criteria. I Waterfall plots displaying pathological responses in subgroups with IGH (n = 19) and IGL (n = 32) groups after neoadjuvant chemotherapy. J Kaplan‒Meier survival curves depicting OS and DFS for the IGH group and the IGL group were generated using SPSS 25.0. Statistical significance was assessed via two-tailed unpaired Student’s t test or one-way analysis of variance (ANOVA). Each bar represents the mean ± SD. Statistical notation: ns (not significant), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001

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Therefore, we assessed the levels of GSH and GSH metabolism-related antioxidant enzymes in the tissues of patients undergoing neoadjuvant chemotherapy. In our study, 51 participants who received neoadjuvant therapy were categorized as the sensitive group (patients with pCR and pPR, n = 30) or the resistant group (patients with pNC, n = 21) (Table 2). Subsequently, we randomly selected 10 patients from both the sensitive and resistant groups to measure the expression levels of intracellular antioxidant enzymes and antioxidant substrate — GSH. The results indicated that, compared to the sensitive group, intracellular GSH levels in the resistant group were significantly higher, (Fig. 4C) and the relative expression levels of NRF2, GPX4 and SOD1 were substantially elevated (Fig. 4D). Applying the modified Response Evaluation Criteria in Solid Tumors (mRECIST), we observed that patients with higher intracellular GSH levels responded worse to neoadjuvant chemotherapy, as indicated by MRI scans, than those with lower intracellular GSH levels (Fig. 4E). Immunohistochemistry analysis indicated that chemotherapy-resistant patients had significantly higher expression levels of NRF2, GPX4 and SOD1 in tumor tissues compared to the sensitive ones. These results collectively confirmed that enhanced expression of GSH metabolism and antioxidant enzymes contributes to chemotherapy resistance in breast cancer patients (Fig. 4F).

Additionally, the ROC curve demonstrated strong predictive performance in distinguishing between drug-resistant and sensitive cells in the context of neoadjuvant chemotherapy (Fig. 4G). A cutoff value of 10.2 nmol/mg for GSH was identified, and the area under the ROC curve was 0.913, with a sensitivity of 90.2% and a specificity of 81.8%, demonstrating significant predictive capability in differentiating between the resistant group and sensitive group. Based on the ROC curve, we defined the IGH group (intracellular GSH high, ≥ 10.2 nmol/mg) and the IGL group (intracellular GSH low, < 10.2 nmol/mg). Detailed clinicopathological characteristics were presented in Table 5. Specifically, 28 of the 32 patients (87.5%) in the IGL group achieved pPR/pCR, which was significantly greater than the 4/19 (21.1%) in the IGH group (P < 0.001) (Fig. 4H). Notably, only four patients of pNC were observed in the IGL group, whereas the majority were in the IGH group (Fig. 4I). Moreover, Kaplan–Meier survival curve revealed that the IGH group had poorer DFS (P = 0.038) and OS (P = 0.037) compared with the IGL group (Fig. 4J).

Table 5 Clinicopathological characteristics in the IGL (intracellular GSH low) group and the IGH (intracellular GSH high) group
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Discussion

Research on the influence of GSH on breast cancer chemotherapy sensitivity remains limited. In this study, by collecting clinicopathological data from patients receiving adjuvant chemotherapy, we found that high GSH intake increases the risk of recurrence after adjuvant chemotherapy. Additionally, our molecular experiments confirmed that chemotherapy drugs increase the expression levels of intracellular GSH and antioxidant enzymes, leading to chemotherapy resistance during neoadjuvant chemotherapy. We propose that the dosage and duration of GSH administration in clinical treatment be carefully evaluated and standardized to prevent overuse and mitigate the risk of chemotherapy resistance.

Increasing evidence indicates that elevated GSH level may contribute to chemotherapy resistance. Nevertheless, GSH is commonly used as a liver-protective drug after chemotherapy for breast cancer patients to mitigate chemotherapy-induced hepatotoxicity. Although many types of hepatoprotective drugs are available, GSH is often overused by clinicians, with its effects on tumors being overlooked. Previous studies have shown that the mechanism by which chemotherapy drugs induce tumor cell death primarily involves the promotion of ROS production [14]. An increase in ROS accelerates tumor cell death, while GSH, as a key component in redox homeostasis, plays a crucial role in scavenging ROS and neutralizing exogenous metabolites in tumor cells [15]. Thus, GSH is essential for tumor cell survival. Previous literature has demonstrated that GSH levels are elevated in various tumors, including breast, colon, laryngeal, gastric, and lung cancers [16]. Moreover, elevated GSH levels can protect tumor cells by reducing the cytotoxic effects of several chemotherapy drugs, including cisplatin, doxorubicin, melphalan, and paclitaxel, ultimately leading to drug resistance [17]. In clinical practice, during chemotherapy for patients with impaired liver function, the liver-protective effect of GSH is often prioritized, while the potential risk of chemotherapy resistance due to its non-standardized intake is frequently overlooked. This issue warrants deeper consideration. However, no systematic studies have been published to investigate the relationship between GSH intake and post-chemotherapy recurrence in breast cancer patients. Our study provides compelling speculation that GSH intake may adversely affect the prognosis of breast cancer patients undergoing chemotherapy.

After PSM, our study identified significant differences in transaminase levels, recurrence rates, and mortality after adjuvant chemotherapy between breast cancer patients between GSH group and Non-GSH group, indicating that GSH intake may have adverse effects on chemotherapy outcomes. To enhance risk stratification and optimize treatment selection, we divided the patients into two groups based on GSH intake duration: HGSH (≥ 16 days, n = 32) group and LGSH (< 16 days, n = 232) group. Patients in the HGSH group exhibited significantly higher recurrence rates, and mortality compared to the LGSH group. Kaplan–Meier survival analysis also revealed a significantly decreased survival rate in the HGSH group. These findings suggest that high GSH intake correlates with poorer prognosis in breast cancer patients who underwent adjuvant chemotherapy. Specifically, the use of chemotherapy drugs resulted in elevated levels of ALT and AST, and an increase in the severity of side effects such as nausea and vomiting, contributing to high GSH intake. This, in turn, increased the likelihood of chemotherapy resistance, recurrence, and worsened prognosis. Previous in vitro studies demonstrated that reduced GSH levels in tumor cells promoted cell death, while elevated levels inhibited cell death [18]. Our findings align with these previous studies, leading us to hypothesize that GSH levels are higher in the tumor tissues of chemotherapy-resistant breast cancer patients compared to chemotherapy-sensitive patients.

In these retrospective studies, Triple-negative status, Lymphovascular invasion, Ki67 ≥ 30%, and High GSH intake were identified as independent risk factors for poor postoperative prognosis in breast cancer chemotherapy patients. Ki67 is commonly used as a marker for breast cancer proliferation [19]. In early-stage breast cancer, high Ki67 expression is associated with poor prognosis [20]. Additionally, elevated Ki67 levels are considered high-risk factors when selecting chemotherapy regimens [21]. It is well established that triple-negative breast cancer (TNBC) is highly aggressive [22], with significantly higher rates of metastasis and recurrence compared to other breast cancer subtypes [23], especially in isceral and brain metastasis [24]. To improve the prognosis of metastatic TNBC patients, antibody–drug conjugates (ADCs), such as sacituzumab govitecan, have been utilized to specifically deliver potent chemotherapy agents directly to cancer cells expressing targeted antigens, demonstrating promising efficacy [25]. Furthermore, lymphovascular invasion is a critical step in tumor dissemination and a strong adverse prognostic factor for breast cancer survival [26]. These pathways enable tumor cells to metastasize to distant organs [27]. Our study is consistent with previous research, revealing that Triple-negative status, Lymphovascular invasion, and Ki67 ≥ 30% are risk factors for recurrence after chemotherapy. Additionally, our study confirmed that High GSH intake is an independent risk factor for poor prognosis, offering critical cautionary note for clinical interventions in postoperative breast cancer treatment strategies.

To demonstrate the role of GSH in chemotherapy resistance, we analyzed transcriptomic data from chemotherapy patient samples in the GEO database and collected post-chemotherapy samples from patients who underwent neoadjuvant chemotherapy, assessing the expression levels of GSH and GSH synthesis-related antioxidant enzymes. Our study revealed a significant upregulation of the GSH metabolic pathway in chemotherapy-resistant patients. Moreover, in fresh samples from patients who underwent neoadjuvant chemotherapy, the GSH/GSSG levels in the resistant group were significantly higher than those in the sensitive group, which is consistent with previous research [28]. Additionally, studies have shown that antioxidant enzymes GPX4 and SOD1, along with the transcription factor NRF2, are involved in intracellular GSH redox reactions [29, 30]. The upregulation of NRF2 and SOD1, along with the activation of ROS scavenging pathways, can lead to resistance to chemotherapy or targeted therapy in various tumors. For instance, activation of NRF2 promotes ROS clearance in drug-resistant liver cancer cell lines [31]. Specifically, NRF2 is a transcription factor that governs the antioxidant pathway by targeting GSH metabolism-related genes. In chemotherapy-sensitive patients, Keap1 (Kelch-like ECH-associated protein 1) binds to NRF2 and mediates NRF2 ubiquitination via the Cul3-E3 ligase complex, promoting its degradation and maintaining NRF2 at low levels [32]. However, in resistant patients, oxidative stress causes a conformational change in Keap1, leading to the release of NRF2, which translocates to the nucleus and binds to antioxidant response element (ARE), activating the expression of downstream antioxidant genes, including GPX4, NQO1, HO-1 and SOD1 [33], and promoting the synthesis of GSH, as illustrated in Fig. 5.

Fig. 5
figure 5

Diagram of antioxidant mechanisms in chemotherapy-resistant and chemotherapy-sensitive patients

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GSH is synthesized in two steps: First, gamma-glutamylcysteine (γ-GC) is formed from glutamate and cysteine, which is the rate-limiting step in GSH production. In the second step, glutathione synthetase (GS) adds glycine to γ-GC to produce GSH. NRF2 plays a critical role in this process by upregulating the expression of genes involved in the synthesis of γ-GC, thereby increasing the overall production of GSH [34]. Elevated GSH levels help neutralize ROS by reacting with hydrogen peroxide (H2O2), which is produced from superoxide radicals (·O2-). This reaction converts H2O2 and GSH into water and GSSG, thereby reducing ROS-induced cellular damage [35]. Through NRF2-driven GSH synthesis, tumor cells are protected from oxidative stress, which contributes to chemotherapy resistance by reducing the cytotoxic effects of ROS generated during treatment.

In addition, the high expression of NRF2 enhances the expression of downstream SOD1, an important antioxidant enzyme that plays a crucial role in protecting cells from oxidative damage [36]. Specifically, SOD1 catalyzes the conversion of ·O2- into H2O2, thereby reducing the levels of ROS and mitigating oxidative stress [37]. By activating the expression of SOD1, NRF2 helps maintain cellular redox balance and protects cells from oxidative injury [38].

GPX4 is an antioxidant enzyme that primarily reduces lipid peroxides, especially lipid hydroperoxides, into their corresponding alcohols, thus protecting cell membranes from oxidative damage [39]. This reaction is essential in lipid-rich environments, such as cellular membranes, where lipid peroxidation can lead to cell death. GPX4 works in conjunction with GSH, as it utilizes GSH as a cofactor to catalyze the reduction of lipid peroxides. By promoting the expression of GPX4 and GSH, the cellular defense mechanisms of the cell membrane are enhanced, reducing damage from lipid peroxides and maintaining cellular integrity [40].

Immune regulation within the tumor microenvironment plays a critical role in tumor progression and chemotherapy resistance. Zhang’s study demonstrated that the synthesis of GSH is intricately linked to serine metabolism, with its metabolic byproducts lactate and 2-hydroxyglutarate (2-HG) suppressing the cytotoxic function of T cells. The metabolic pathways promote the development of an immunosuppressive vascular microenvironment, thereby facilitating resistance to chemotherapy [41]. In addition, Yang et al. found that active GSH metabolism within tumors further suppresses immune responses, such as IFN-γ signaling and PD-1/PD-L1 interactions, while reducing the number of M1 macrophages and increasing the proportion of M2 macrophages. Moreover, GPX4 promotes immune evasion by inhibiting ferroptosis. The combination of GPX4 inhibitors with immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis increases the proportion of CD8 + T cells, enhances their cytotoxic activity and induces ferroptosis, thereby promoting chemotherapy resistance [42]. In addition, the incorporation of ICIs into neoadjuvant chemotherapy regimens has been shown to increase the pCR rate [43]. However, despite their significant therapeutic potential in cancer treatment, it is essential to also focus on managing immune-related adverse events (irAEs). These adverse effects, including peripheral neuropathy and hearing loss, can have a profound impact on patient quality of life and require careful monitoring throughout treatment [44, 45].

Our study also found that NRF2, GPX4 and SOD1 expression levels were higher in the neoadjuvant chemotherapy-resistant group compared to the sensitive group, further supporting our hypothesis and demonstrating the adverse effects of GSH on chemotherapy in breast cancer patients. Additionally, we discovered that a GSH threshold of 10.2 nmol/mg effectively differentiates resistant cells from sensitive cells, with an AUC of 0.913, providing a robust distinction between chemotherapy-resistant and sensitive patients. Patients were classified into IGH and IGL groups according to the cutoff value of intracellular GSH levels. Kaplan–Meier survival analysis revealed that the IGH group exhibited significantly poorer survival outcomes compared to the IGL group, suggesting that GSH may contribute to neoadjuvant chemotherapy resistance and lead to a worse prognosis in breast cancer patients. These findings offer a theoretical basis for precision treatment of breast cancer chemotherapy involving GSH.

Further investigation into the role and mechanisms of GSH and its associated antioxidant enzymes is essential for reversing chemotherapy resistance [46]. Several research teams have targeted GSH synthesis inhibitors as potential therapeutic agents. For instance, Li et al. examined the impact of GSH synthesis inhibitors on the cytotoxicity of cisplatin and gemcitabine in bile duct cancer cells [47]. Their findings revealed that low concentrations of GSH synthesis inhibitors significantly enhanced cancer cell death. This effect was similarly observed in a separate study on ovarian cancer [48]. Additionally, researchers have developed a range of glutathione-depleting nanodrugs for efficient cancer treatment [49], particularly in addressing chemotherapy resistance in TNBC [50]. Collectively, these studies underscore the significance of investigating the role of GSH in breast cancer patient prognosis, stressing the necessity of regulating GSH usage to prevent non-standardized intake and decrease post-chemotherapy recurrence.

However, our study has several limitations. As a single-center retrospective analysis, it may be subject to selection bias, and conclusions should be validated in large-scale multicenter prospective studies. Furthermore, the precise mechanisms of glutathione’s impact remain unclear, and future research should investigate its specific roles in chemotherapy resistance and cell survival. Additionally, we primarily focus on the duration of GSH intake, without examining the effect of specific dosage on the prognosis of breast cancer patients undergoing chemotherapy. Future studies should employ stratified analyses or dose–response curves to explore the influence of different GSH doses on prognosis, offering guidance for more precise clinical application.

Conclusion

In conclusion, this study reveals that excessive GSH intake may contribute to chemotherapy resistance in breast cancer patients, identifying high GSH intake as an independent risk factor for tumor recurrence. Chemotherapy may induce tumor cells to produce GSH to counteract oxidative damage. These findings urge researchers and clinicians to assess the implications of GSH in promoting chemotherapy resistance and to evaluate the duration of GSH intake during treatment to optimize outcomes.

Data availability

No datasets were generated or analysed during the current study.

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Synopsis

This study investigates the impact of excessive glutathione intake on breast cancer chemotherapy resistance, showing that higher intake is linked to increased recurrence rates and poor prognosis, emphasizing the need for standardized glutathione usage during treatment.

Funding

This work was supported by the Henan Provincial Breast Cancer Precision Prevention and Control Engineering Research Center (ZC20220050), the Henan Provincial People’s Hospital—23456 Talent Engineering Project (ZC23456026) and the study on the Effect and Mechanism of Macrophage-Derived Exosomes Loaded with Doxorubicin for Targeted Therapy of Triple-Negative Breast Cancer (ZC20220114).

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Author notes

  1. Zhiyuan Zhang, Jiaru Gao and Linjiao Jia contributed equally to this work.

Authors and Affiliations

  1. Department of Breast Surgery, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital, No.7 Weiwu Road, Zhengzhou, Henan, 450003, China

    Zhiyuan Zhang, Jiaru Gao, Linjiao Jia, Shuxin Kong, Maosen Zhai, Shuai Wang, Wenwen Li, Shoukai Wang, Yuqing Su, Changzheng Zhu, Yuanxiang Lu & Wentao Li

  2. Henan Provincial Engineering Research Center of Breast Cancer Precise Prevention and Treatment, Zhengzhou, Henan, 450003, China

    Zhiyuan Zhang, Jiaru Gao, Linjiao Jia, Shuxin Kong, Maosen Zhai, Shuai Wang, Wenwen Li, Shoukai Wang, Yuqing Su, Changzheng Zhu, Yuanxiang Lu & Wentao Li

  3. Department of Radiology, Henan Provincial People’s Hospital, Zhengzhou University People’s Hospital, Zhengzhou, Henan, 450003, China

    Wanyue Li

  4. Department of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

    Wenkang Wang

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  1. Zhiyuan Zhang
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Contributions

Wentao Li, Yuanxiang Lu conceived and designed the experiments. Zhiyuan Zhang, Jiaru Gao, Wenwen Li, Shoukai Wang, Yuqing Su, Changzheng Zhu performed the experiments and analyzed the data. Zhiyuan Zhang, Jiaru Gao wrote the manuscript. Yuanxiang Lu, Linjiao Jia, Shuxin Kong contributed to project administration and revised the paper. Maosen Zhai, Wanyue Li, Wenkang Wang contributed to data collection and data analysis.

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Correspondence to Yuanxiang Lu or Wentao Li.

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Zhang, Z., Gao, J., Jia, L. et al. Excessive glutathione intake contributes to chemotherapy resistance in breast cancer: a propensity score matching analysis. World J Surg Onc 22, 345 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12957-024-03626-9

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World Journal of Surgical Oncology

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