Predicting Pathological Complete Response in Neoadjuvant Dual Blockade With Trastuzumab and Pertuzumab in HER2 Gene Amplified Breast Cancer

Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy

INTRODUCTION

For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplification status detection with a deep learning model, and apply the model to predict the efficacy of neoadjuvant therapy.

METHODS

We combined Next-Generation Sequencing (NGS) data and IHC staining images of 606 breast cancer patients and developed a Vision Transformer (ViT) deep learning model to identify the amplification of HER2 through these IHC staining images. This model was then applied to predict the efficacy of neoadjuvant therapy in 399 HER2-positive breast cancer patients.

RESULTS

The NGS data of 606 patients were split into training (N = 404), validation (N = 101), and testing (N = 101) sets. The top 3 genes with highest mutation frequency were TP53, ERBB2 and PIK3CA. With the NGS results as deep learning model labels, the accuracy of our ViT model was 93.1% for HER2 amplification recognition. The misidentifications was likely due to the heterogeneity of HER2 expression in cancer tissues. For predicting the efficacy of neoadjuvant therapy, receiver operating characteristic (ROC) curves were plotted, and the combination of image recognition result and clinical pathological features yielded an area under the curve (AUC) value of 0.855 in the training set and 0.841 in the testing set.

CONCLUSIONS

Our study provided a method of HER2 status recognition based on IHC images, improving the efficiency and accuracy of HER2 status assessment, and can be used for predicting the efficacy of anti-HER2 targeted neoadjuvant therapy. We intend our deep learning model to assist pathologists in HER2 amplification recognition.

Rapid Real-Time PCR Based on Core-Shell Tecto-Dendrimer-Entrapped Au Nanoparticles

Rapid real-time PCR (generally <1 h) has broad prospects. In this study, we synthesized a new type of nanomaterial core-shell tecto-dendrimer coated with Au nanoparticles (Au CSTDs) for research in this field. The experimental results showed that Au CSTDs could significantly shorten the time of real-time PCR (from 72 to 28 min) with different templates, while the detection limit reached 10 copies and the nonspecific amplification was significantly reduced. Furthermore, experimental analyses and theoretical studies using the finite element simulation method confirmed that Au CSTDs function by synergistically enhancing electrostatic adsorption and thermal conductivity. These properties play a key role in improving real-time PCR, especially in particle-particle interactions. This study contributes an advanced method to rapid real-time PCR, which is expected to remarkably improve the efficiency, lower the detection limit, and enhance the specificity of molecular detection.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

Pathological response and safety of albumin-bound paclitaxel as a neoadjuvant treatment for HER2-positive breast cancer compared to docetaxel combined with anti-HER2 therapy: a real-world study

Background

This study aimed to retrospectively analyse the pathological response and safety of combining albumin-bound paclitaxel (nab-paclitaxel) or docetaxel with anti-HER2 therapy as a neoadjuvant treatment for HER2-positive breast cancer.

Methods

From June 2020 to August 2023, 225 HER2-positive breast cancer patients who underwent radical surgery following neoadjuvant treatment were enrolled in this study. The patients were divided into two groups based on the drugs they received: the nab-paclitaxel group (n=166, receiving nab-paclitaxel + platinum along with trastuzumab and pertuzumab) and the docetaxel group (n=59, receiving docetaxel + platinum along with trastuzumab and pertuzumab). The pathological response and adverse events related to the drugs were collected and evaluated in both groups.

Results

In the nab-paclitaxel group, the rates of breast and total pathological complete response (bpCR and tpCR) were significantly greater than those in the docetaxel group (69.27% vs. 47.45%, P=0.003; 68.67% vs. 45.76%, P=0.002). For patients who did not achieve pCR after chemotherapy, the pathological response of chemotherapy was analysed using MP grading and RCB grading. The results showed that there was a statistically significant difference between the two groups (P<0.05). Multivariate analysis revealed that therapeutic drugs, clinical stage, ER status, and Ki-67 level were independent predictors of pCR. The nab-paclitaxel group had a significantly greater proportion of patients with peripheral sensory neuropathy than did the docetaxel group (58.43% vs. 38.98%, P=0.035), while the docetaxel group had a greater proportion of patients with allergies and elevated ALT (31.93% vs. 69.49%, P=0.000; 23.49% vs. 40.68%, P=0.021).

Conclusions

Our real-world study revealed that nab-paclitaxel combined with anti-HER2 therapy was an effective neoadjuvant therapy for HER2-positive breast cancer. The multivariate analysis revealed that chemotherapy drugs, clinical stage, ER status, and Ki-67 level was the significant factor influencing treatment outcome. These findings offer a valuable reference for the neoadjuvant treatment of patients with HER2-positive breast cancer.

A nomogram for predicting pathologic node negativity after neoadjuvant chemotherapy in breast cancer patients: a nationwide, multicenter retrospective cohort study (CSBrS-012)

Purpose

This study aimed to investigate the factors associated with pathologic node-negativity (ypN0) in patients who received neoadjuvant chemotherapy (NAC) to develop and validate an accurate prediction nomogram.

Methods

The CSBrS-012 study (2010-2020) included female patients with primary breast cancer treated with NAC followed by breast and axillary surgery in 20 hospitals across China. In the present study, 7,711 eligible patients were included, comprising 6,428 patients in the primary cohort from 15 hospitals and 1,283 patients in the external validation cohort from five hospitals. The hospitals were randomly assigned. The primary cohort was randomized at a 3:1 ratio and divided into a training set and an internal validation set. Univariate and multivariate logistic regression analyses were performed on the training set, after which a nomogram was constructed and validated both internally and externally.

Results

In total, 3,560 patients (46.2%) achieved ypN0, and 1,558 patients (20.3%) achieved pathologic complete response in the breast (bpCR). A nomogram was constructed based on the clinical nodal stage before NAC (cN), ER, PR, HER2, Ki67, NAC treatment cycle, and bpCR, which were independently associated with ypN0. The area under the receiver operating characteristic curve (AUC) for the training set was 0.80. The internal and external validation demonstrated good discrimination, with AUCs of 0.79 and 0.76, respectively.

Conclusion

We present a real-world study based on nationwide large-sample data that can be used to effectively screen for ypN0 to provide better advice for the management of residual axillary disease in breast cancer patients undergoing NAC.

Real-world data on neoadjuvant chemotherapy with dual-anti HER2 therapy in HER2 positive breast cancer

BACKGROUND

Neoadjuvant chemotherapy with dual-targeted therapy is the standard treatment for human epidermal growth factor 2 (HER2)-positive breast cancer. Although the dual-targeted therapy has significantly improved the pathological complete response (pCR) rate, further investigation is needed to identify biomarkers that predict the response to neoadjuvant therapy.

METHODS

This retrospective study analyzed 353 patients with HER2-positive breast invasive ductal carcinoma. The correlation between clinicopathological factors and pCR rate was evaluated. A nomogram was constructed based on the results of the multivariate logistic regression analysis to predict the probability of pCR.

RESULTS

The breast pCR (b-pCR) rate was 56.1% (198/353) and the total pCR (t-pCR) rate was 52.7% (186/353). Multivariate analysis identified ER status, PR status, HER2 status, Ki-67 index, and neoadjuvant chemotherapy regimens as independent indicators for both b-pCR and t-pCR. The nomogram had an area under the receiver operating characteristic curve (AUC) of 0.73 (95% CI: 0.68-0.78). According to the nomogram, the t- pCR rate was highest in the ER-PR- HER2-positive patients (131/208) and lowest in the ER + PR + HER2-positive patients (19/73). The subgroup analyses showed that there was no significant difference in pCR rate among the neoadjuvant chemotherapy regimens in ER positive, PR positive, HER2 IHC 2 + , Ki67 index < 30% population. However, for ER-PR-HER2-positive patients, the neoadjuvant chemotherapy regimen has a great influence on the pCR rates.

CONCLUSIONS

Patients with ER-negative, PR-negative, HER2 3 + and high KI-67 index were more likely to achieve pCR. THP may be used as an alternative to AC-THP or TCbHP in selected HER2-positive patients.

Neoadjuvant chemotherapy reduces the levels of HMGB1 and E-cadherin in patients with breast cancer

This study investigated the changes in serum tumor marker levels in patients with breast cancer (BC) after neoadjuvant chemotherapy (NACT) and their potential as prognostic factors in NACT. A total of 134 consecutive patients with BC treated at our hospital between January 2019 and December 2021 were retrospectively analyzed. Patients were treated with NACT based on the docetaxel, epirubicin, and cyclophosphamide (TEC) regimen and assessed for marker levels, T cell subsets, and therapeutic outcomes. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of the markers. Outcome assessments showed that NACT effectively reduced the tumor size, leading to increased complete remission, partial remission, stable disease, and significantly reduced disease progression. Improved immune function has also been observed after NACT. The levels of two (E-cadherin and HMGB1) out of five markers (CA153, CK19, CEA, E-cadherin, and HMGB1) were significantly reduced after NACT before surgery compared with those at admission, suggesting that NACT modulates the levels of biomarkers. ROC analysis revealed that the area under the curve (AUC) of HMGB1 and E-cadherin combination was 0.87 for discrimination of therapeutic response with a sensitivity and specificity of 91.3% and 88.4%, respectively. Serum tumor marker levels were reduced after NACT in patients with BC. The reduction was most prominent for HMGB1, followed by E-cadherin. These biomarkers can be used to predict the therapeutic response to NACT with an AUC of 0.87, thus offering a new tool to monitor treatment progress in NACT for patients with BC.