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ORIGINAL RESEARCH article

Front. Immunol., 04 February 2026

Sec. Cancer Immunity and Immunotherapy

Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1690888

This article is part of the Research TopicResearch on Nanomaterials in Tumor Diagnosis and Therapy, Volume IIView all 9 articles

Adjuvant pegylated liposomal doxorubicin versus epirubicin sequential paclitaxel in triple-negative breast cancer: comparable efficacy with a distinct safety profile

Shuanglong Cai&#x;Shuanglong Cai1†Shaohong Yu&#x;Shaohong Yu2†Xiuquan Lin&#x;Xiuquan Lin3†Quan Zhou&#x;Quan Zhou4†Xiaoxin Zheng&#x;Xiaoxin Zheng5†Hongdan ChenHongdan Chen6Tao MaTao Ma7Xiaogeng ChenXiaogeng Chen8Hong Sun*&#x;Hong Sun9*‡Yong Shi*&#x;Yong Shi1*‡
  • 1Comprehensive Breast Health Center, Department of Thyroid and Breast Surgery, The Lishui Hospital of Wenzhou Medical University, The First Affiliated Hospital of Lishui University, Lishui People’s Hospital, Lishui, Zhejiang, China
  • 2Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
  • 3Department for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, Fujian, China
  • 4Department of Gynecology, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
  • 5Department of Cardiology, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
  • 6First Department of Cadre Clinic, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
  • 7The Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China
  • 8Department of Breast Surgery, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China
  • 9Department of Pharmacy, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China

Objective: Pegylated liposomal doxorubicin (PLD), an improved formulation of doxorubicin, offers potential advantages in targeting and reduced systemic toxicity compared to conventional anthracyclines like epirubicin. This study aimed to compare the efficacy and safety of PLD followed by paclitaxel versus epirubicin followed by paclitaxel as postoperative adjuvant therapy for triple-negative breast cancer (TNBC).

Methods: A total of 1,036 patients with TNBC who received postoperative adjuvant chemotherapy with either PLD sequential paclitaxel or epirubicin sequential paclitaxel were enrolled. The primary endpoint was disease-free survival (DFS). Adverse events were systematically documented. Multivariate Cox regression identified prognostic factors, and a predictive nomogram was developed.

Results: At median follow-up, 1-, 3-, and 5-year DFS rates were 93.39%, 84.04%, and 84.04% for the PLD group versus 93.58%, 82.38%, and 81.73% for the epirubicin group (log-rank p = 0.58). Postoperative N stage, stromal tumor-infiltrating lymphocyte (sTIL) expression, and Ki67 expression were independent predictors of DFS. The prognostic model achieved C-indices of 0.874 (training set) and 0.853 (validation set). The PLD regimen was associated with a significantly lower incidence of most adverse events; however, nausea, mucositis, and hand-foot syndrome were more frequent in the PLD group.

Conclusion: In adjuvant therapy for TNBC, PLD sequential paclitaxel demonstrated comparable efficacy to epirubicin sequential paclitaxel. However, PLD exhibited a distinct and generally more favorable safety profile, except for specific toxicities such as hand-foot syndrome and mucositis. The developed nomogram may aid in individualized prognosis prediction.

1 Introduction

Triple-negative breast cancer (TNBC), characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, represents a distinct and aggressive subtype of breast cancer (1, 2). This subtype disproportionately affects premenopausal women and often presents at advanced stages, with higher rates of metastasis at diagnosis (3). Due to the lack of targetable receptors, TNBC is inherently resistant to traditional endocrine therapies and anti-HER2 agents, rendering chemotherapy the cornerstone of systemic treatment for these patients (4, 5).

Anthracyclines and taxanes have long formed the backbone of breast cancer chemotherapy, including regimens for TNBC (6, 7). Epirubicin, a widely used anthracycline, has demonstrated efficacy across breast cancer stages (8). However, its clinical application is constrained by cumulative toxicities, particularly cardiotoxicity—a life-threatening complication that limits long-term use (9). In contrast, pegylated liposomal doxorubicin (PLD) represents a technological advancement, encapsulating doxorubicin within polyethylene glycol-coated liposomes (10). This formulation reduces plasma levels of free doxorubicin, thereby mitigating off-target toxicity to healthy tissues while preserving antitumor efficacy (11). With an extended half-life compared to conventional doxorubicin, PLD facilitates enhanced tumor accumulation and potentially more potent cytotoxic effects (12).

Previous research has extensively investigated anthracycline-taxane combinations in TNBC, with this regimen established as a standard neoadjuvant and adjuvant approach in major clinical guidelines (13). Despite this, the optimal choice between anthracycline formulations—specifically, PLD versus epirubicin—for postoperative adjuvant therapy in TNBC remains unresolved. Although several studies have explored PLD’s role in breast cancer treatment, evidence directly comparing its efficacy and safety against epirubicin in TNBC patients remains scarce (14, 15).

This study, therefore, aimed to directly compare the efficacy and toxicity profiles of PLD-sequenced paclitaxel versus epirubicin-sequenced paclitaxel in the postoperative adjuvant treatment of TNBC. By conducting a comprehensive analysis of a large, well-characterized patient cohort, we sought to inform evidence-based decisions regarding anthracycline selection in TNBC adjuvant chemotherapy. Our findings may ultimately guide clinicians in optimizing treatment outcomes while minimizing treatment-related toxicities for this vulnerable patient population.

2 Materials and methods

2.1 Patients and data collection​

This multicenter retrospective cohort study included 1,036 female patients with stages I–III TNBC who underwent surgery at Zhejiang Province Lishui People’s Hospital, Fuzhou University Affiliated Provincial Hospital, and Tianjin Medical University Cancer Institute & Hospital between 1 January 2015 and 31 December 2020. Patients were divided into two groups based on adjuvant chemotherapy regimen: epirubicin-sequential paclitaxel (n = 676) and PLD-sequential paclitaxel (n = 360). All cases had complete clinicopathological data according to the WHO Classification of Breast Tumors (2019 edition) (16).

As this was a retrospective study, the choice between the PLD-based and epirubicin-based regimens was at the discretion of the treating physician, introducing potential selection bias. To address this, we comprehensively collected and compared baseline clinicopathological characteristics between the two groups (Table 1), and these were well-balanced. Furthermore, multivariate Cox regression analysis was employed to adjust for identified prognostic factors when comparing outcomes.

Table 1
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Table 1. The clinical-pathological characteristics of patients in both the training and validation sets.

2.2 Collection of clinicopathological data

Clinical data included age, menstrual status, family history, surgical procedure, adjuvant chemotherapy agents, use of adjuvant radiotherapy, and recurrence/metastasis events. Pathological data comprised pathological pattern, tumor T stage, axillary lymph node N stage (17), tumor grade, lymph-vascular invasion, stromal tumor-infiltrating lymphocyte (sTIL) expression, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67 status.

2.3 Definition of key indicators

2.3.1 Clinicopathological metrics

Stromal tumor-infiltrating lymphocytes (sTILs): Classified as low (≤10%), intermediate (10%–40%), or high (>40%) expression.

ER and PR: Positive expression was defined as ≥1% immunoreactive cells by immunohistochemistry (IHC); <1% was negative (18).

HER2: Assessed by combined IHC and fluorescence in situ hybridization (FISH). Positivity was defined as IHC 3+ or IHC 2+ with FISH-amplified HER2; IHC 0/1+ or IHC 2+ with non-amplified HER2 was negative (19).

Ki-67: Dichotomized as low (≤20% positive cells) or high (>20% positive cells) (20).

2.3.2 Inclusion and exclusion criteria

Inclusion criteria were (1) pathologically confirmed stages I–III TNBC with negative ER, PR, and HER2 expression; (2) having undergone modified radical mastectomy or breast-conserving surgery followed by adjuvant chemotherapy; and (3) availability of complete clinicopathological and follow-up data. Exclusion criteria included (1) concurrent other malignant tumors; (2) receipt of neoadjuvant therapy preoperatively; (3) severe cardiac, hepatic, or renal dysfunction; and (4) follow-up of less than 6 months or loss to follow-up.

2.3.3 Adverse events

Adverse events (including myelosuppression, nausea, vomiting, cardiotoxicity, mucositis, hand-foot syndrome, and liver function abnormalities) were retrospectively extracted from electronic medical records and laboratory results and documented as present or absent.

Cardiotoxicity was specifically defined as the occurrence of any of the following: decreased left ventricular ejection fraction (LVEF ≤ 50% or a decline of ≥10% from baseline), congestive heart failure, clinically significant arrhythmia, or other cardiac dysfunction documented during clinical evaluation. Grading of adverse event severity was not performed due to the retrospective nature of the study.

2.4 Follow-up and survival analysis

Follow-up was conducted via outpatient visits, telephone, and electronic medical records, ending 1 June 2024. Patient survival status, recurrence/metastasis events, and treatment-related adverse events were recorded every 3–6 months.

The primary endpoint was disease-free survival (DFS), defined as the time from surgery to the first occurrence of local recurrence, regional or distant metastasis, or death from any cause. Patients without events were censored at the last follow-up.

2.5 Statistical analysis

Continuous variables underwent normality testing: non-normally distributed variables were reported as median (interquartile range) with the Mann-Whitney U test for between-group comparisons; normally distributed variables were reported as mean (standard deviation) with the t-test. Categorical data were expressed as proportions and compared via chi-squared test or Fisher’s exact test.

The dataset was divided into training (70%) and validation (30%) sets. In the training set, univariate and multivariate Cox regression identified independent predictors to construct a DFS prognostic model and nomograms for 1-, 3-, and 5-year DFS rates.

The dataset was randomly split into a training set (70%) and a validation set (30%). In the training set, univariate and multivariate Cox regression analyses were performed to identify independent predictors to construct a DFS prognostic model and nomograms for 1-, 3-, and 5-year DFS rates. Model discrimination was evaluated via ROC curves, and calibration was assessed using bootstrap 1000 resampling to compare predicted versus observed outcomes. Kaplan–Meier survival analysis with the log-rank test was used to estimate DFS rates and compare outcomes between treatment groups in the training set.

3 Results

3.1 Disease-free survival rates at 1-, 3-, and 5-year time points, and Kaplan–Meier curve analysis

Among the 1,036 postoperative TNBC patients in the study cohort, the median follow-up duration was 74.4 months (95% CI: 72.3–76.2 months). During the follow-up period, DFS rates at 1, 3, and 5 years for patients receiving PLD or epirubicin are presented in Table 2. Kaplan–Meier curves comparing DFS between groups showed no significant difference (log-rank test, p = 0.58; Figure 1).

Table 2
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Table 2. Disease-free survival (DFS) rates of patients in the pegylated liposomal doxorubicin group and epirubicin group at different time points.

Figure 1
A Kaplan-Meier survival curve compares disease-free survival (DFS) probabilities between Epirubicin-based (red line) and PLD-based (blue line) treatments over 3000 days. The lines show similar survival trends, with no significant difference (p = 0.58). The y-axis represents DFS probability, and the x-axis represents time in days.

Figure 1. Kaplan–Meier curves for disease-free survival in patients receiving pegylated liposomal doxorubicin or epirubicin.

Among the 1,036 postoperative TNBC patients in the study cohort, the median follow-up duration was 74.4 months (95% CI: 72.3–76.2 months). During the follow-up period, DFS rates at 1, 3, and 5 years for patients receiving PLD or epirubicin are presented in Table 2. The Kaplan–Meier curves for DFS are shown in Figure 1. No significant difference in DFS was observed between the two groups (log-rank p = 0.58). The hazard ratio (HR) for disease recurrence or death in the PLD group compared to the epirubicin group was 0.902 (95% CI: 0.625–1.300).

3.2 Follow-up outcomes and clinicopathological characteristics in training and validation sets

The training cohort included 725 female TNBC patients with a median follow-up of 74.3 months, during which 596 DFS events and 129 deaths occurred. The validation cohort comprised 311 female TNBC patients (median follow-up: 74.4 months), with 250 DFS events and 61 deaths. Clinicopathological characteristics of patients in both sets are detailed in Table 1, indicating that the baseline characteristics were well-balanced between the two cohorts.

3.3 Nomogram model for predicting DFS in TNBC patients receiving postoperative adjuvant chemotherapy

In the training cohort, a multivariable Cox regression model identified postoperative N stage, stromal tumor-infiltrating lymphocyte (sTIL) expression, and Ki67 expression as independent prognostic factors (Table 3). Based on these variables, we developed a nomogram (Figure 2) to predict DFS in TNBC patients after adjuvant chemotherapy. Each subtype of these variables was assigned a point score; by inputting patient-specific values, individualized 1-, 3-, and 5-year DFS probabilities were calculated. The nomogram demonstrated good discriminative ability, with concordance indices (C-indices) of 0.874 in the training set and 0.853 in the validation set. Area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.875, 0.915, and 0.913 in the training set (Figure 3), and 0.904, 0.907, and 0.880 in the validation set (Figure 4). Calibration curves for corresponding time points are shown in Figures 5A–C (training set), and Figures 6A–C (validation set). The strong association of high Ki67 (>20%) with shortened DFS underscores the role of proliferative capacity in TNBC aggressiveness, while the protective effect of high sTILs highlights the importance of the host immune response within the tumor microenvironment.

Table 3
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Table 3. Univariate and multivariate analysis of DFS in the training set TNBC patients.

Figure 2
Nomogram displaying prognostic factors for disease-free survival (DFS) probability, incorporating pathological N staging, post-sTIL levels, and post-Ki67 levels. It predicts 1-year, 3-year, and 5-year DFS probabilities based on total points accumulated.

Figure 2. Nomogram for predicting disease-free survival in patients with triple-negative breast cancer receiving postoperative adjuvant therapy.

Figure 3
ROC curve graph comparing three models over time, showing sensitivity against 1-specificity. The curves represent AUC values for 1-year (0.875, yellow), 3-year (0.915, blue), and 5-year (0.913, red). The diagonal line represents random classification.

Figure 3. ROC curve of the training set.

Figure 4
ROC curve graph showing three lines representing the AUCs for 1-year (0.904 in yellow), 3-year (0.907 in blue), and 5-year (0.880 in red). Sensitivity is on the Y-axis and 1-Specificity on the X-axis, with a diagonal reference line.

Figure 4. ROC curve of the validation set.

Figure 5
Three calibration plots labeled A, B, and C, showing actual versus predicted probabilities. Each graph has a dotted diagonal line representing perfect calibration. Blue dots with error bars indicate observed data points. Graph A and C show more clustered data near higher probabilities, while graph B has more spread across mid-range probabilities. All axes range from zero to one.

Figure 5. (A) Calibration curve of the training set at 1 year. (B) Calibration curve of the training set at 3 year. (C) Calibration curve of the training set at 5 year.

Figure 6
Three calibration plots labeled A, B, and C compare predicted probability with actual probability. Each plot shows points along a diagonal line indicating perfect calibration, with error bars representing variability. Plot A has data clustered at higher probabilities, plot B shows wider distribution at mid-range probabilities, and plot C displays a balanced spread across the diagonal.

Figure 6. (A) Calibration curve of the validation set at 1 year. (B) Calibration curve of the validation set at 3 year. (C) Calibration curve of the validation set at 5 year.

3.4 Analysis of adverse drug reactions

Based on medical records, common adverse events included myelosuppression, nausea, vomiting, cardiotoxicity, mucositis, hand-foot syndrome, and liver function abnormalities (Table 4). The PLD group had higher incidences of hand-foot syndrome (24.7% vs. 8.5%) and mucositis (22.5% vs. 17.4%) compared with the epirubicin group. Conversely, the PLD group exhibited lower rates of myelosuppression, vomiting, cardiotoxicity, and liver function abnormalities, although the incidence of nausea was higher (5.5% vs. 2.0%).

Table 4
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Table 4. Drug-related adverse reactions.

4 Discussion

TNBC, defined by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, represents an aggressive subtype with limited therapeutic options and poor prognosis (21, 22). Postoperative adjuvant chemotherapy remains a cornerstone of treatment; however, the efficacy and safety profiles of different regimens vary substantially. PLD sequential paclitaxel and epirubicin sequential paclitaxel are commonly used adjuvant chemotherapy regimens for TNBC. PLD, a nanoparticle-mediated antineoplastic agent, prolongs circulation time and enhances tumor accumulation via liposomal encapsulation, demonstrating higher rates of pathological complete response (pCR) in select clinical studies (23, 24). In contrast, our adjuvant study found comparable DFS between the two strategies. This divergence invites a refined discussion on the relationship between pCR and long-term outcomes in TNBC. While achieving pCR is a well-validated surrogate for survival benefit in TNBC, supported by major trials and meta-analyses (25, 26), its translation is not absolute. The observed discrepancy likely underscores the fundamental distinction between neoadjuvant and adjuvant therapy contexts. Neoadjuvant therapy evaluates tumor response in situ (pCR), whereas adjuvant therapy tests the ability to prevent recurrence after macroscopic tumor removal (DFS). The pharmacological properties and efficacy drivers of a drug may differ between these settings. Factors such as differences in study populations, baseline tumor burden, and the specific endpoints measured (pCR vs. DFS) contribute to the variance in results. Thus, the comparable DFS in our adjuvant study does not contradict the potential utility of PLD in neoadjuvant therapy but highlights that therapeutic efficacy must be evaluated within its specific clinical context. Further research is warranted to delineate the distinct roles and optimal applications of liposomal versus conventional anthracyclines across the continuum of TNBC management.

Regarding safety, our study revealed distinct adverse event profiles between the two regimens. The PLD group exhibited higher incidences of hand-foot syndrome (24.7% vs. 8.5%) and mucositis (22.5% vs. 17.4%), likely due to prolonged drug retention and accumulation in skin and mucosal tissues (27). A meta-analysis of multicenter data attributed these effects to the unique nanoparticle structure of PLD, which causes drug sequestration in cutaneous capillary beds (28). Conversely, the PLD group had lower rates of myelosuppression, vomiting, cardiotoxicity, and liver function abnormalities, consistent with previous findings that liposomal formulations mitigate anthracycline-induced cardiotoxicity (9, 29). Notably, nausea occurred more frequently in the PLD group (5.5% vs. 2.0%), potentially related to differential drug metabolism and gastrointestinal mucosal irritation mechanisms (30). These findings highlight the critical importance of individualized treatment selection, balancing efficacy with the specific toxicity profile most suitable for a given patient. It is important to note that this was a retrospective analysis where treatment allocation was not randomized, which may introduce selection bias. Although we observed balanced baseline characteristics between the two groups and used multivariate analysis to adjust for known prognostic factors, unmeasured confounders (such as subtle differences in performance status, physician preference based on unrecorded patient factors, or precise drug dose intensity) could still influence the outcomes. A prospective, randomized trial would be the gold standard to definitively confirm these findings.

Previous studies have identified multiple factors influencing DFS in TNBC, including tumor stage, molecular marker expression, and immune microenvironment (3133). Our study employed Cox regression analysis to identify postoperative N1–N3 nodal stage, high stromal tumor-infiltrating lymphocyte (sTIL) expression, and Ki67 >20% as key independent predictors of DFS. These findings have significant implications for precise prognosis assessment and personalized treatment planning (21, 22).

In the TNM staging system, nodal (N) stage reflects regional lymph node involvement. Our results showed a strong association between N1–N3 stages and DFS, indicating that increased lymph node metastasis burden elevates the risk of systemic dissemination and shortens DFS (34, 35). This aligns with extensive literature demonstrating that regional lymph node metastasis is a robust prognostic marker across cancers, including TNBC (36). Longitudinal studies of breast cancer patients have consistently reported higher recurrence rates and lower 5-year survival among those with nodal involvement, underscoring the clinical importance of accurate lymph node assessment in TNBC.

Tumor-infiltrating lymphocytes (TILs) are integral to the tumor microenvironment and play a central role in anti-tumor immunity. Our study found that high postoperative sTIL expression correlated with longer DFS. Mechanistically, elevated sTILs enhance tumor cell recognition and cytotoxicity, inhibit angiogenesis, and delay recurrence (37, 38). Prior research has shown that TNBC patients with high TILs exhibit higher pCR rates and improved survival outcomes. However, the context-dependent nature of TIL function across patients and tumor stages warrants further investigation.

Ki67, a nuclear protein associated with cell proliferation, directly reflects tumor cell mitotic activity. Our analysis revealed that Ki67 >20% significantly shortened DFS, consistent with its role in promoting tumor aggressiveness and metastasis. Multiple breast cancer cohorts have reported higher recurrence rates and shorter DFS in patients with high Ki67 expression (39, 40), supporting its utility as a prognostic biomarker for treatment stratification.

5 Limitations

This study has several limitations. First, due to its non-randomized, retrospective design, residual confounding from unmeasured variables (e.g., detailed performance status, cardiac risk profiles, physician preference, socioeconomic factors, precise chemotherapy dose intensity, compliance, or patient-reported outcomes) may persist despite our efforts to adjust for known prognostic factors. The lack of granular data also precluded the use of propensity score matching or sensitivity analyses to further mitigate selection bias. Second, reliance on medical records introduces potential information bias and prevented the assessment of patient-reported outcomes such as quality of life, which are important for a holistic evaluation of treatment benefit. Third, the analysis was limited to selected clinicopathological factors and did not include lifestyle, genetic, or additional molecular variables that could influence DFS. Fourth, the follow-up duration was insufficient to evaluate long-term survival and late-onset toxicities. Finally, although the nomogram showed good performance in internal validation, external validation in larger, independent, prospective multicenter cohorts is necessary to confirm its generalizability and clinical utility before widespread adoption.

6 Conclusion

In postoperative adjuvant therapy for stage I-III TNBC, PLD sequential paclitaxel and epirubicin sequential paclitaxel showed comparable DFS outcomes, supporting the role of nanoparticle formulations in oncology. However, their distinct toxicity profiles require careful consideration: PLD offers advantages in myelosuppression, cardiotoxicity, and liver function, but increased vigilance for hand-foot syndrome and mucositis is necessary. The developed nomogram provides a practical tool for predicting individual DFS probabilities, which could aid in patient counseling and follow-up planning. Future prospective, large-scale studies with external validation are warranted to confirm these findings and further refine adjuvant therapy strategies for TNBC.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by the Ethics Committee of Zhejiang Province Lishui People’s Hospital, Fuzhou University Affiliated Provincial Hospital, and Tianjin Medical University Cancer Institute and Hospital. The studies were conducted in accordance with the local legislation and institutional requirements. The written informed consent was not required due that the design of this study was retrospective.

Author contributions

S-lC: Formal analysis, Investigation, Data curation, Software, Funding acquisition, Validation, Writing – review & editing, Supervision, Conceptualization. SY: Data curation, Methodology, Conceptualization, Investigation, Writing – review & editing, Software. XL: Software, Data curation, Methodology, Investigation, Writing – review & editing. QZ: Investigation, Methodology, Data curation, Software, Writing – review & editing. XZ: Formal analysis, Writing – review & editing, Resources, Funding acquisition. H-dC: Data curation, Writing – review & editing, Investigation, Software. TM: Writing – review & editing, Resources, Funding acquisition, Formal Analysis. XC: Writing – review & editing, Resources, Funding acquisition, Formal analysis. HS: Formal analysis, Funding acquisition, Supervision, Validation, Writing – review & editing. YS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Software, Supervision, Validation, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This study was supported in part by grants from the Doctoral Research Initiation Fund (No.2025bs001) from Lishui Hospital of Wenzhou Medical University, the First Affifiliated Hospital of Lishui University, and Lishui People’s Hospital, Zhejiang Province. This study was supported in part by grants from the Natural Science Foundation of Fujian (No.2022J011004), the Fujian provincial health technology project (No.2022CXB001), Joint Funds for the innovation of science and Technology, Fujian Province (No.2023Y9298), the Startup Fund for Scientifific Research of Fujian Medical University (grant number 2021QH1118), the Natural Science Foundation of Fujian Province (2025J01080), and Zhejiang Provincial Medical and Health Science and Technology Plan Project (No.2022KY1446).

Acknowledgments

We thank all the patients who participated in our study.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The author(s) declared that generative AI was not used in the creation of this manuscript.

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Abbreviations

TNBC, Triple-negative breast cancer; ER, Estrogen receptor; PR, Progesterone receptor; HER2, Human epidermal growth factor receptor 2; PLD, Pegylated liposomal doxorubicin; DFS:Disease-free survival; sTIL, Stromal tumor-infiltrating lymphocyte; IHC, Immunohistochemistry; FISH, Fluorescence in situ hybridization; AUC, The area under the curve; ROC, Receiver operating characteristic curve.

References

1. Rakha EA, El-Sayed ME, Green AR, S Lee AH, Robertson JF, and Ellis IO. Prognostic markers in triple-negative breast cancer. Cancer. (2007) 1):25–32. doi: 10.1002/cncr.22381

PubMed Abstract | Crossref Full Text | Google Scholar

2. Dent R, Trudeau M, Pritchard KI, Hanna WM, Kahn HK, Sawka CA, et al. Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res. (2007) 13:4429–34. doi: 10.1158/1078-0432.CCR-06-3045

PubMed Abstract | Crossref Full Text | Google Scholar

3. Carey LA, Dees EC, Sawyer L, Gatti L, Moore DT, Collichio F, et al. The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res. (2007) 13:2329–34. doi: 10.1158/1078-0432.CCR-06-1109

PubMed Abstract | Crossref Full Text | Google Scholar

4. Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. (2001) 344:783–92. doi: 10.1056/NEJM200103153441101

PubMed Abstract | Crossref Full Text | Google Scholar

5. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. (2005) 365:1687–717. doi: 10.1016/S0140-6736(05)66544-0

PubMed Abstract | Crossref Full Text | Google Scholar

6. Chang A, Botteri E, Gillis RD, Löfling L, Le CP, Ziegler AI, et al. Beta-blockade enhances anthracycline control of metastasis in triple-negative breast cancer. Sci Transl Med. (2023) 15:eadf1147. doi: 10.1126/scitranslmed.adf1147

PubMed Abstract | Crossref Full Text | Google Scholar

7. Waks AG and Winer EP. Breast cancer treatment: a review. JAMA. (2019) 321:288–300. doi: 10.1001/jama.2018.19323

PubMed Abstract | Crossref Full Text | Google Scholar

8. Slamon DJ, Godolphin W, Jones LA, Holt JA, Wong SG, Keith DE, et al. Studies of the HER-2/neu proto-oncogene in human breast and ovarian cancer. Science. (1989) 244:707–12. doi: 10.1126/science.2470152

PubMed Abstract | Crossref Full Text | Google Scholar

9. Swain SM, Whaley FS, and Ewer MS. Congestive heart failure in patients treated with doxorubicin: a retrospective analysis of three trials. Cancer. (2003) 97:2869–79. doi: 10.1002/cncr.11407

PubMed Abstract | Crossref Full Text | Google Scholar

10. Duggan ST and Keating GM. Pegylated liposomal doxorubicin: a review of its use in metastatic breast cancer, ovarian cancer, multiple myeloma and AIDS-related Kaposi’s sarcoma. Drugs. (2011) 71:2531–58. doi: 10.2165/11207510-000000000-00000

PubMed Abstract | Crossref Full Text | Google Scholar

11. Gabizon A, Shmeeda H, and Barenholz Y. Pharmacokinetics of pegylated liposomal Doxorubicin: review of animal and human studies. Clin Pharmacokinet. (2003) 42:419–36. doi: 10.2165/00003088-200342050-00002

PubMed Abstract | Crossref Full Text | Google Scholar

12. Gabizon AA, Patil Y, and La-Beck NM. New insights and evolving role of pegylated liposomal doxorubicin in cancer therapy. Drug Resist Update. (2016) 29:90–106. doi: 10.1016/j.drup.2016.10.003

PubMed Abstract | Crossref Full Text | Google Scholar

13. Gradishar WJ, Moran MS, Abraham J, Abramson V, Aft R, Agnese D, et al. Breast cancer, version 3.2024, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. (2024) 22:331–57. doi: 10.6004/jnccn.2024.0035

PubMed Abstract | Crossref Full Text | Google Scholar

14. Yang FO, Hsu NC, Moi SH, Lu YC, Hsieh CM, Chang KJ, et al. Efficacy and toxicity of pegylated liposomal doxorubicin-based chemotherapy in early-stage breast cancer: a multicenter retrospective case-control study. Asia Pac J Clin Oncol. (2018) 14:198–203. doi: 10.1111/ajco.12771

PubMed Abstract | Crossref Full Text | Google Scholar

15. Schneeweiss A, Möbus V, Tesch H, Hanusch C, Denkert C, Lübbe K, et al. Intense dose-dense epirubicin, paclitaxel, cyclophosphamide versus weekly paclitaxel, liposomal doxorubicin (plus carboplatin in triple-negative breast cancer) for neoadjuvant treatment of high-risk early breast cancer (GeparOcto-GBG 84): A randomised phase III trial. Eur J Cancer. (2019) 106:181–92. doi: 10.1016/j.ejca.2018.10.015

PubMed Abstract | Crossref Full Text | Google Scholar

16. Tan PH, Ellis I, Allison K, Brogi E, Fox SB, Lakhani S, et al. The 2019 World Health Organization classification of tumours of the breast. Histopathology. (2020) 77:181–5. doi: 10.1111/his.14091

PubMed Abstract | Crossref Full Text | Google Scholar

17. Giuliano AE, Edge SB, and Hortobagyi GN. Eighth edition of the AJCC cancer staging manual: breast cancer. Ann Surg Oncol. (2018) 25:1783–5. doi: 10.1245/s10434-018-6486-6

PubMed Abstract | Crossref Full Text | Google Scholar

18. Hammond ME H, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, et al. American Society of Clinical Oncology/College Of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol. (2010) 28:2784–95. doi: 10.1200/JCO.2009.25.6529

PubMed Abstract | Crossref Full Text | Google Scholar

19. Wolff AC, Hammond ME H, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. Arch Pathol Lab Med. (2007) 131:18–43. doi: 10.5858/2007-131-18-ASOCCO

PubMed Abstract | Crossref Full Text | Google Scholar

20. Azambuja ED, Cardoso F, Castro GD Jr., Colozza M, Mano MS, Durbecq V, et al. Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients. Br J Cancer. (2007) 96:1504–13. doi: 10.1038/sj.bjc.6603756

PubMed Abstract | Crossref Full Text | Google Scholar

21. Huo DZ, Hu H, Rhie SK, Gamazon ER, Cherniack AD, Liu JF, et al. Comparison of breast cancer molecular features and survival by african and european ancestry in the cancer genome atlas. JAMA Oncol. (2017) 3:1654–62. doi: 10.1001/jamaoncol.2017.0595

PubMed Abstract | Crossref Full Text | Google Scholar

22. Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA. 295:2492–502. doi: 10.1001/jama.295.21.2492

PubMed Abstract | Crossref Full Text | Google Scholar

23. Dong MJ, Luo L, Ying XG, Lu XQ, Shen JG, Jiang ZN, et al. Comparable efficacy and less toxicity of pegylated liposomal doxorubicin versus epirubicin for neoadjuvant chemotherapy of breast cancer: a case-control study. Onco Targets Ther. (2018) 11:4247–52. doi: 10.2147/OTT.S162003

PubMed Abstract | Crossref Full Text | Google Scholar

24. Zhang J, Jiang HC, Zhang J, Bao GQ, Zhang GQ, Wang HB, et al. Effectiveness and safety of pegylated liposomal doxorubicin versus epirubicin as neoadjuvant or adjuvant chemotherapy for breast cancer: a real-world study. BMC Cancer. (2021) 21:1301. doi: 10.1186/s12885-021-09050-6

PubMed Abstract | Crossref Full Text | Google Scholar

25. Cortazar P, Zhang LJ, Untch M, Mehta K, Costantino JP, Wolmark N, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. (2014) 384:164–72. doi: 10.1016/S0140-6736(13)62422-8

PubMed Abstract | Crossref Full Text | Google Scholar

26. Litton JK, Regan MM, Pusztai L, Rugo HS, Tolaney SM, Garrett-Mayer E, et al. Standardized definitions for efficacy end points in neoadjuvant breast cancer clinical trials: neoSTEEP. J Clin Oncol. (2023) 41:4433–42. doi: 10.1200/JCO.23.00435

PubMed Abstract | Crossref Full Text | Google Scholar

27. Monk BJ, Brady MF, Aghajanian C, Lankes HA, Rizack T, Leach J, et al. A phase 2, randomized, double-blind, placebo- controlled study of chemo-immunotherapy combination using motolimod with pegylated liposomal doxorubicin in recurrent or persistent ovarian cancer: a Gynecologic Oncology Group partners study. Ann Oncol. (2017) 28:996–1004. doi: 10.1093/annonc/mdx049

PubMed Abstract | Crossref Full Text | Google Scholar

28. Gill PS, Wernz J, Scadden DT, Cohen P, Mukwaya GM, von Roenn JH, et al. Randomized phase III trial of liposomal daunorubicin versus doxorubicin, bleomycin, and vincristine in AIDS-related Kaposi’s sarcoma. J Clin Oncol. (1996) 14:2353–64. doi: 10.1200/JCO.1996.14.8.2353

PubMed Abstract | Crossref Full Text | Google Scholar

29. Yamaguchi N, Fujii T, Aoi S, Kozuch PS, Hortobagyi GN, and Blum RH. Comparison of cardiac events associated with liposomal doxorubicin, epirubicin and doxorubicin in breast cancer: a Bayesian network meta-analysis. Eur J Cancer. (2015) 51:2314–20. doi: 10.1016/j.ejca.2015.07.031

PubMed Abstract | Crossref Full Text | Google Scholar

30. R O’Brien ME, Wigler N, Inbar M, Rosso R, Grischke E, Santoro A, et al. Reduced cardiotoxicity and comparable efficacy in a phase III trial of pegylated liposomal doxorubicin HCl (CAELYX/Doxil) versus conventional doxorubicin for first-line treatment of metastatic breast cancer. Ann Oncol. (2004) 15:440–9. doi: 10.1093/annonc/mdh097

PubMed Abstract | Crossref Full Text | Google Scholar

31. Leon-Ferre RA, Jonas SF, Salgado R, Loi S, Jong VD, Carter JM, et al. Tumor-infiltrating lymphocytes in triple-negative breast cancer. JAMA. (2024) 331:1135–44. doi: 10.1001/jama.2024.3056

PubMed Abstract | Crossref Full Text | Google Scholar

32. Geurts VC M, Balduzzi S, Steenbruggen TG, Linn SC, Siesling S, Badve SS, et al. Tumor-infiltrating lymphocytes in patients with stage I triple-negative breast cancer untreated with chemotherapy. JAMA Oncol. (2024) 10:1077–86. doi: 10.1001/jamaoncol.2024.1917

PubMed Abstract | Crossref Full Text | Google Scholar

33. Denkert C, Loibl S, Noske A, Roller M, Müller BM, Komor M, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol. (2010) 28:105–13. doi: 10.1200/JCO.2009.23.7370

PubMed Abstract | Crossref Full Text | Google Scholar

34. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thürlimann B, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol. (2013) 24:2206–23. doi: 10.1093/annonc/mdt303

PubMed Abstract | Crossref Full Text | Google Scholar

35. Giuliano AE, Connolly JL, Edge SB, Mittendorf EA, Rugo HS, Solin LJ, et al. Breast Cancer-Major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin. (2017) 67:290–303. doi: 10.3322/caac.21393

PubMed Abstract | Crossref Full Text | Google Scholar

36. Fisher B, Anderson S, Bryant J, Margolese RG, Deutsch M, Fisher ER, et al. Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy plus irradiation for the treatment of invasive breast cancer. N Engl J Med. (2002) 347:1233–41. doi: 10.1056/NEJMoa022152

PubMed Abstract | Crossref Full Text | Google Scholar

37. Harris MA, Savas P, Virassamy B, R O’Malley MM, Kay J, Mueller SN, et al. Towards targeting the breast cancer immune microenvironment. Nat Rev Cancer. (2024) 24:554–77. doi: 10.1038/s41568-024-00714-6

PubMed Abstract | Crossref Full Text | Google Scholar

38. Tutt A, Robson M, Garber JE, Domchek SM, Audeh MW, Weitzel JN, et al. Oral poly(ADP-ribose) polymerase inhibitor olaparib in patients with BRCA1 or BRCA2 mutations and advanced breast cancer: a proof-of-concept trial. Lancet. (2010) 376:235–44. doi: 10.1016/S0140-6736(10)60892-6

PubMed Abstract | Crossref Full Text | Google Scholar

39. Dowsett M, Nielsen TO, A’Hern R, Bartlett J, Coombes RC, Cuzick J, et al. Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer working group. J Natl Cancer Inst. (2011) 103:1656–64. doi: 10.1093/jnci/djr393

PubMed Abstract | Crossref Full Text | Google Scholar

40. Prat A, Parker JS, Karginova O, Fan C, Livasy C, Herschkowitz JI, et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. (2010) 12:R68. doi: 10.1186/bcr2635

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: adjuvant chemotherapy, efficacy and safety, epirubicin, pegylated liposomal doxorubicin, triple-negative breast cancer

Citation: Cai S, Yu S, Lin X, Zhou Q, Zheng X, Chen H, Ma T, Chen X, Sun H and Shi Y (2026) Adjuvant pegylated liposomal doxorubicin versus epirubicin sequential paclitaxel in triple-negative breast cancer: comparable efficacy with a distinct safety profile. Front. Immunol. 17:1690888. doi: 10.3389/fimmu.2026.1690888

Received: 22 August 2025; Accepted: 19 January 2026; Revised: 12 January 2026;
Published: 04 February 2026.

Edited by:

Shenglong Li, Dalian University of Technology, China

Reviewed by:

Sangeeta Ghuwalewala, Icahn School of Medicine at Mount Sinai, United States
Zhenjun Huang, Sun Yat-sen Memorial Hospital, China

Copyright © 2026 Cai, Yu, Lin, Zhou, Zheng, Chen, Ma, Chen, Sun and Shi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hong Sun, c3VuaG9uZzc3NzdAZmptdS5lZHUuY24=; Yong Shi, c2hpeW9uZzExMUAxNjMuY29t

These authors have contributed equally to this work and share first authorship

These authors have contributed equally to this work

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