Evaluation of the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Tumor-infiltrating lymphocytes as a predictor of axillary and primary tumor pathological response after neoadjuvant chemotherapy in patients with breast cancer: a retrospective cohort study

PURPOSE

Tumor-infiltrating lymphocytes (TILs) can predict complete pathological response (pCR) of tumor in the breast but not so well-defined in the axilla after neoadjuvant chemotherapy. Since axillary surgery is being increasingly de-escalated after NACT, we aimed to investigate the relationship between TILs and pCR in the axilla and breast, as well as survival amongst NACT patients.

METHODS

Clinicopathological data on patients who underwent NACT between 2013 and 2020 were retrospectively examined. Specifically, pre-TILs (before NACT), post-TILs (after NACT) and ΔTIL (changes in TILs) were assessed. Primary endpoint was pCR and secondary endpoints were breast cancer-free interval (BCFI) and overall survival (OS).

RESULTS

Two hundred and twenty patients with nodal metastases were included. Overall axillary and breast pCR rates were 42.7% (94/220) and 39.1% (86/220), respectively, whereas the combined pCR rate was 32.7% (72/220). High pre-TILs (OR 2.03, 95% CI 1.02-4.05; p = 0.04) predicted axillary pCR whereas, high post-TILs (OR 0.33, 95% CI 0.14-0.76; p = 0.009) and increased ΔTILs (OR 0.25, 95% CI 0.08-0.79; p = 0.02) predicted non-axillary pCR. TILs were not a significant predictor for BCFI and OS.

CONCLUSIONS

This study supports the potential use of pre-TILs to select initially node-positive patients for axillary surgical de-escalation after NACT.

Ultrasound-based radiomics for early predicting response to neoadjuvant chemotherapy in patients with breast cancer: a systematic review with meta-analysis

OBJECTIVE

This study aims to evaluate the diagnostic accuracy of ultrasound imaging (US)-based radiomics for the early prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

METHODS

We comprehensively searched PubMed, Cochrane Library, Embase, and Web of Science databases up to 1 January 2023 for eligible studies. We assessed the methodological quality of the enrolled studies with Radiomics Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies-2 tools. We performed meta-analyses to summarize the diagnostic efficacy of US-based radiomics in response to NAC in breast cancer patients.

RESULTS

Eight studies proved eligible. Eligible studies exhibited an average RQS score of 12.88 (35.8% of the total score), with the RQS score ranging from 8 to 19. In the meta-analyses, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.87 (95% CI 0.81-0.92), 0.78 (95% CI 0.72-0.83), 4.02 (95% CI 3.18-5.08), 0.16 (95% CI 0.10-0.25), and 25.17 (95% CI 15.10-41.95), respectively. Results from subgroup analyses indicated that prospective studies apparently exhibited more optimal sensitivity than retrospective studies. Sensitivity analyses exhibited similar results to the primary analyses.

CONCLUSION

US-based radiomics may be a potentially crucial adjuvant method for evaluating the response of breast cancer to NAC. Due to limited data available and low quality of eligible studies, more multicenter prospective studies with rigorous methods are required to confirm our findings.

Inhibitory effects of medium-chain fatty acids on the proliferation of human breast cancer cells via suppression of Akt/mTOR pathway and modulating the Bcl-2 family protein

Medium-chain fatty acids (MCFAs) have 6-12 carbon atoms and are instantly absorbed into the bloodstream before traveling to the portal vein and the liver, where they are immediately used for energy and may have antitumor effects. Its role in breast cancer is poorly understood. To investigate the apoptosis-inducing effect of MCFAs in breast cancer cells, cell viability assay, colony formation assay, cell migration assay, cell invasion assay, nuclear morphology, cell cycle assay, intracellular reactive oxygen species (ROS), matrix metalloproteinase (MMP), apoptosis, RT-qPCR analysis, and Western blot analysis were performed. In the present study, MCFA treatments reduced proliferative capability, increased ROS level, increased the depletion of MMP, induced G0/G1 and S phase cell cycle arrest, and late apoptosis of breast cancer cells in an effective concentration. Besides, MCFA treatment contributed to the upregulation of proapoptotic protein (BAK) and caspase-3, and the downregulation of antiapoptotic protein (Bcl-2). Mechanistically, phosphorylation levels of EGFR, Akt, and mTOR were significantly reduced in breast cancer cells treated with MCFAs. However, no significant changes in apoptosis and signaling-related proteins were observed in lauric acid-treated ER-positive cancer cells. Our findings suggested that MCFAs suppressed breast cancer cell proliferation by modulating the PI3K/Akt/mTOR signaling pathway. MCFAs may be a promising therapeutic drug for treating breast cancer.

Investigation of efficacy of two different chemotherapy protocols used in neoadjuvant chemotherapy in clinical stages II-IV canine malignant mammary tumours

The first aim of this study is to demonstrate the clinical efficacy and reliability of two different neoadjuvant chemotherapy (NAC) protocols consisting of doxorubicin/cyclophosphamide (AC) and paclitaxel in dogs with clinical stages II-IV canine malignant mammary tumours (CMTs). Secondly, to determine the Luminal A, Luminal B, HER2-positive and triple-negative molecular subtypes and their value in predicting clinical response to NAC in biopsy samples, and thirdly, to reveal the changes in Ki-67, human epidermal growth factor receptor type 2 (HER2), oestrogen receptor (ER), and progesterone receptor (PgR) expression levels induced by NAC. Thirty dogs with clinical stages II-IV CMTs (T1-3N0-1M0) according to the modified TNM system were included in the study. Dogs in group-1 (n = 15) AC combination and dogs in group-2 (n = 15) were administered paclitaxel. Partial response (PR) was the most common clinical response in both treatment groups (66.66% and 86.66%, respectively). There was no difference between the groups regarding clinical response parameters (p = .001). The rate of treatment responders was higher than the rate of non-responders in both groups (p < .001). The adverse effects observed in both groups were mostly limited to grades 1 and 2 and all were easy to manage. The most frequently detected molecular subtype was Luminal A (59.25%). Complete response (CR) was achieved in 33.33% of dogs with triple-negative CMT in the AC group and 14.29% of the Luminal A subtype in the paclitaxel group. Alterations in Ki-67, HER2, ER, and PgR expressions after chemotherapy were not statistically significant (p > .05). As a result, we have shown that these neoadjuvant chemotherapy protocols are effective and safe alternative treatment options for CMTs.

The Impact of Neoadjuvant Chemotherapy on Patients With T1N0M0 Triple-Negative and HER-2 Positive Breast Cancer: A Retrospective Analysis Based on the SEER Database

BACKGROUND

The utilization of neoadjuvant chemotherapy (NAC) originated in the treatment of locally advanced breast cancer (BC). Our study is designed to elucidate the effects of NAC on patients with T1N0M0 triple-negative and HER-2 positive BC.

METHODS

This study involved the selection of 10,614 patients diagnosed with T1N0M0 triple-negative and HER-2 positive breast cancer (BC) from the surveillance, epidemiology, and end results (SEER) database. To ascertain the impact of neoadjuvant chemotherapy (NAC) on T1a, T1b, and T1c N0M0 BC, we conducted multivariate Cox regression analyses. Similarly, we performed multivariate Cox regression analyses to compare the effects of neoadjuvant chemotherapy against adjuvant chemotherapy on T1N0M0 BC. The Kaplan-Meier method was employed to delineate survival curves for different molecular subtypes and clinical stages.

RESULTS

The data results from the SEER database reveal a significant enhancement of overall survival (OS) in T1c BC patients as a result of NAC. For T1b BC patients, NAC does not present any significant effect. Contrarily, NAC seems to adversely impact the OS of T1a triple-negative BC patients. However, the prognosis comparison between neoadjuvant and adjuvant chemotherapy for T1N0M0 breast cancer did not show any significant difference, with the exception of T1a triple-negative BC.

CONCLUSIONS

Patients with T1cN0M0 triple-negative and HER-2 positive BC may derive OS benefits from NAC. Additionally, NAC could be detrimental to T1a triple-negative BC.

Neoadjuvant chemotherapy efficacy and prognosis in HER2-low and HER2-zero breast cancer patients by HR status: a retrospective study in China

Background

The promising efficacy of novel anti-HER2 antibody-drug conjugates (ADC) in HER2-low breast cancer has made HER2-low a research hotspot. However, controversy remains regarding the neoadjuvant chemotherapy (NAC) efficacy, prognosis, and the relationship with hormone receptor (HR) status of HER2-low.

Methods

A retrospective analysis was conducted on 975 patients with HER2-negative breast cancer undergoing NAC at Tianjin Medical University Cancer Institute and Hospital, evaluating pathological complete response (pCR) rate and prognosis between HER2-low and HER2-zero in the overall cohort and subgroups.

Results

Overall, 579 (59.4%) and 396 (40.6%) patients were HER2-low and HER2-zero disease, respectively. Compared with HER2-zero, the HER2-low cohort consists of more postmenopausal patients, with lower histological grade and higher HR positivity. In the HR-positive subgroup, HER2-low cases remain to exhibit lower histological grade, while in the HR-negative subgroup, they show higher grade. The HER2-low group had lower pCR rates than the HER2-zero group (16.4% vs. 24.0%). In the HR-positive subgroup, HER2-low consistently showed lower pCR rate (8.1% vs. 15.5%), and served as an independent suppressive factor for the pCR rate. However, no significant difference was observed in the pCR rates between HER2-low and HER2-zero in the HR-negative breast cancer. In the entire cohort and in stratified subgroups based on HR and pCR statuses, no difference in disease-free survival were observed between HER2-low and HER2-zero.

Conclusions

In the Chinese population, HER2-low breast cancer exhibits distinct characteristics and efficacy of NAC in different HR subgroups. Its reduced pCR rate in HR-positive subgroup is particularly important for clinical decisions. However, HER2-low is not a reliable factor for assessing long-term survival outcomes.

Donafenib as neoadjuvant therapy in locally advanced thyroid cancer: protocol for the DONATHYCA phase II prospective single-arm trial in China

INTRODUCTION

The invasion of important structures in locally advanced thyroid cancer (LATC) hinders radical resection, increases the risk of recurrence and even prevents surgery. Creating the opportunity for radical operation in patients with LATC is critical for improving their prognosis. Multitarget tyrosine kinase inhibitors were used as neoadjuvant therapy in several studies. Donafenib produced survival benefits over placebo in Chinese patients with radioiodine-refractory differentiated thyroid cancer in a recent study, but its efficacy in the neoadjuvant setting remains unknown. This study thus aims to assess the efficacy and safety of donafenib as neoadjuvant therapy in LATC.

METHODS AND ANALYSIS

DONATHYCA is a prospective, exploratory, single-arm phase II study evaluating the efficacy and safety of donafenib as neoadjuvant therapy in patients with LATC. 13 patients will be enrolled. The primary endpoint is the objective response rate as per Response Evaluation Criteria in Solid Tumours V.1.1. The secondary objectives include progression-free survival, the duration of response, the disease control rate, the R0/R1 resection rate, quality of life and toxicity during treatment according to Common Terminology Criteria for Adverse Events V.4.0. Patients will receive donafenib 300 mg two times a day continuously in a 21-day treatment cycle for six cycles.

ETHICS AND DISSEMINATION

This study was approved by the Ethics Committee of Fujian Cancer Hospital (K2023-144-02) on 27 July 2023 and registered in the China Clinical Trial Registry on 20 September 2023. The results of the study will be presented at academic conferences and published in scientific publications.

TRIAL REGISTRATION NUMBER

ChiCTR2300075973.

Impact of treatment interval between neoadjuvant immunochemotherapy and surgery in lung squamous cell carcinoma

OBJECTIVE

The optimal timing for surgery following neoadjuvant immunochemotherapy for lung squamous cell carcinoma appears to be a topic of limited data. Many clinical studies lack stringent guidelines regarding this timing. The objective of this study is to explore the effect of the interval between neoadjuvant immunochemotherapy and surgery on survival outcomes in patients with lung squamous cell carcinoma.

METHODS

This study conducted a retrospective analysis of patients with lung squamous cell carcinoma who underwent neoadjuvant immunochemotherapy between January 2019 and October 2022 at The First Affiliated Hospital, Zhejiang University School of Medicine. Patients were divided into two groups based on the treatment interval: ≤33 days and > 33 days. The primary observational endpoints of the study were Disease-Free Survival (DFS) and Overall Survival (OS). Secondary observational endpoints included Objective response rate (ORR), Major Pathological Response (MPR), and Pathological Complete Remission (pCR).

RESULTS

Using the Kaplan-Meier methods, the ≤ 33d group demonstrated a superior DFS curve compared to the > 33d group (p = 0.0015). The median DFS for the two groups was 952 days and 590 days, respectively. There was no statistical difference in the OS curves between the groups (p = 0.66), and the median OS was not reached for either group. The treatment interval did not influence the pathologic response of the tumor or lymph nodes.

CONCLUSIONS

The study observed that shorter treatment intervals were associated with improved DFS, without influencing OS, pathologic response, or surgical safety. Patients should avoid having a prolonged treatment interval between neoadjuvant immunochemotherapy and surgery.

Synergistic Effect of Layered Double Hydroxides Nanodosage Form to Induce Apoptosis and Ferroptosis in Breast Cancer

Background

Breast cancer is the most common cancer in women and one of the leading causes of cancer death worldwide. Ferroptosis, a promising mechanism of killing cancer cells, has become a research hotspot in cancer therapy. Simvastatin (SIM), as a potential new anti-breast cancer drug, has been shown to cause ferroptosis of cancer cells and inhibit breast cancer metastasis and recurrence. The purpose of this study is to develop a novel strategy boosting ferroptotic cascade for synergistic cancer therapy.

Methods

In this paper, iron base form of layered double hydroxide supported simvastatin (LDHs-SIM) was synthesized by hydrothermal co-precipitation method. The characterization of LDHs-SIM were assessed by various analytical techniques, including ultraviolet-visible (UV-vis) spectroscopy, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and transmission electron microscopy (TEM). Biological activity, ferroptosis mechanism and biocompatibility were analyzed through in vivo and in vitro analysis, so as to evaluate its therapeutic effect on breast cancer.

Results

The constructed LDHs-SIM nanosystem can not only release SIM through mevalonate (MVA) pathway, inhibit the expression of glutathione peroxidase 4 (GPX4), inhibit the expression of SLC7A11 and reduce the synthesis efficiency of GSH, but also promote the accumulation of Fe2+ in cells through the release of Fe3+, and increase the intracellular ROS content. In addition, LDHs-SIM nanosystem can induce apoptosis of breast cancer cells to a certain extent, and achieve the synergistic effect of apoptosis and ferroptosis.

Conclusion

In the present study, we demonstrated that nanoparticles of layered double hydroxides (LDHs) loaded with simvastatin were more effective than a free drug at inhibiting breast cancer cell growth, In addition, superior anticancer therapeutic effects were achieved with little systemic toxicity, indicating that LDHs-SIM could serve as a safe and high-performance platform for ferroptosis-apoptosis combined anticancer therapy.

Influence of Gut Microbiota-Mediated Immune Regulation on Response to Chemotherapy

The involvement of the gut microbiota in anti-cancer treatment has gained increasing attention. Alterations to the structure and function of the gut bacteria are important factors in the development of cancer as well as the efficacy of chemotherapy. Recent studies have confirmed that the gut microbiota and related metabolites influence the pharmacological activity of chemotherapeutic agents through interactions with the immune system. This review aims to summarize the current knowledge of how malignant tumor and chemotherapy affect the gut microbiota, how the gut microbiota regulates host immune response, and how interactions between the gut microbiota and host immune response influence the efficacy of chemotherapy. Recent advances in strategies for increasing the efficiency of chemotherapy based on the gut microbiota are also described. Deciphering the complex homeostasis maintained by the gut microbiota and host immunity provides a solid scientific basis for bacterial intervention in chemotherapy.

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer

RATIONALE AND OBJECTIVES

To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer.

MATERIALS AND METHODS

In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA).

RESULTS

The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models.

CONCLUSION

The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Nomogram Based on US and Clinicopathologic Characteristics: Axillary Nodal Evaluation Following Neoadjuvant Chemotherapy in Patients With Node-Positive Breast Cancer

BACKGROUND

To develop a convenient modality to predict axillary response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

MATERIALS AND METHODS

In this multi-center study, a total of 1019 breast cancer patients with biopsy-proven positive lymph node (LN) receiving NAC were randomly assigned to the training and validation groups at a ratio of 7:3. Clinicopathologic and ultrasound (US) characteristics of both primary tumors and LNs were used to develop corresponding prediction models, and a nomogram integrating clinicopathologic and US predictors was generated to predict the axillary response to NAC.

RESULTS

Axillary pathological complete response (pCR) was achieved in 47.79% of the patients. The expression of estrogen receptor, human epidermal growth factor receptor -2, Ki-67 score, and clinical nodal stage were independent predictors for nodal response to NAC. Location and radiological response of primary tumors, cortical thickness and shape of LNs on US were also significantly associated with nodal pCR. In the validation cohort, the discrimination of US model (area under the curve [AUC], 0.76) was superior to clinicopathologic model (AUC, 0.68); the combined model (AUC, 0.85) demonstrates strong discriminatory power in predicting nodal pCR. Calibration curves of the nomogram based on the combined model demonstrated that substantial agreement can be observed between the predictions and observations. This nomogram showed a false-negative rates of 16.67% in all patients and 10.53% in patients with triple negative breast cancer.

CONCLUSION

Nomogram incorporating routine clinicopathologic and US characteristics can predict nodal pCR and represents a tool to aid in treatment decisions for the axilla after NAC in breast cancer patients.

Discussing the safety and effectiveness of transcatheter arterial embolization combined with intravenous chemotherapy in treating locally advanced breast cancer

To investigate the efficacy and safety of drug-eluting bead-transarterial chemoembolization (DEB-TACE) combined with systemic chemotherapy in HR+/Her2- locally advanced breast cancer (LABC) patients. A controlled study was conducted on LABC patients treated at Jianyang People's Hospital and the First Affiliated Hospital of Chengdu Medical College from December 2020 to June 2022. The patients were randomly divided into the experimental group and the control group. The experimental group received DEB-TACE combined with the TAC regimen (175 mg/m2 paclitaxel-loaded albumin, 50 mg/m2 Doxorubicin, and 500 mg/m2 cyclophosphamide), while the control group received the TAC regimen intravenously. The therapeutic efficacy was evaluated using the mRECIST criteria. Statistical analysis was performed using SPSS 22.0 software, and baseline characteristics, overall response rate (ORR), pathological complete response (PCR), adverse reactions, and complications were compared between the two groups using paired t-test and chi-square test. A total of 60 patients were included, with 30 patients in the experimental group (50%) and 30 patients in the control group (50%). After the first treatment, the ORR was 90% in the experimental group and 60% in the control group (P < 0.05). The overall ORR was 100% in the experimental group and 83% in the control group (P < 0.05). PCR was achieved in 14 patients (47%) in the experimental group and 4 patients (13%) in the control group. The main adverse reactions in the experimental group were skin blistering, pigmentation, and pain. There was no statistically significant difference in vomiting and grade II or above bone marrow suppression between the two groups. No grade III or above adverse events occurred in either group. The comparison of tumor shrinkage between the two groups was P = 0.051, and axillary lymph node shrinkage was P < 0.05. The use of drug-eluting beads in combination with neoadjuvant chemotherapy is a feasible and safe treatment option for locally advanced breast cancer patients.

An ultrasound-based nomogram model in the assessment of pathological complete response of neoadjuvant chemotherapy in breast cancer

Introduction

We aim to predict the pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) in breast cancer patients by constructing a Nomogram based on radiomics models, clinicopathological features, and ultrasound features.

Methods

Ultrasound images of 464 breast cancer patients undergoing NAC were retrospectively analyzed. The patients were further divided into the training cohort and the validation cohort. The radiomics signatures (RS) before NAC treatment (RS1), after 2 cycles of NAC (RS2), and the different signatures between RS2 and RS1 (Delta-RS/RS1) were obtained. LASSO regression and random forest analysis were used for feature screening and model development, respectively. The independent predictors of pCR were screened from clinicopathological features, ultrasound features, and radiomics models by using univariate and multivariate analysis. The Nomogram model was constructed based on the optimal radiomics model and clinicopathological and ultrasound features. The predictive performance was evaluated with the receiver operating characteristic (ROC) curve.

Results

We found that RS2 had better predictive performance for pCR. In the validation cohort, the area under the ROC curve was 0.817 (95%CI: 0.734-0.900), which was higher than RS1 and Delta-RS/RS1. The Nomogram based on clinicopathological features, ultrasound features, and RS2 could accurately predict the pCR value, and had the area under the ROC curve of 0.897 (95%CI: 0.866-0.929) in the validation cohort. The decision curve analysis showed that the Nomogram model had certain clinical practical value.

Discussion

The Nomogram based on radiomics signatures after two cycles of NAC, and clinicopathological and ultrasound features have good performance in predicting the NAC efficacy of breast cancer.

Evaluation of cleaved caspase-3 and Ki-67 index on diagnostic biopsy in response to neoadjuvant chemotherapy in the context of post-treatment tumour ypT stage, ypN stage, grade, and molecular subtype

Introduction

Breast carcinoma is a heterogeneous disease, characterised by diverse clinical behaviour. The aim of this study was to assess how cleaved caspase-3 and Ki-67 index, evaluated on diagnostic biopsy, are related to response to neoadjuvant chemotherapy in the context of molecular subtype, post-treatment tumour, N category, and grade.

Material and methods

A retrospective analysis was carried out among 110 breast cancer patients. Ki-67 levels and caspase-3 expression on diagnostic biopsy were explored regarding their relation to tumour grade and molecular subtype, ypT, ypN categories, and T and N categories according to Sataloff tumour response evaluation.

Results

A statistically significant relationship was found between Ki-67 levels and tumour grade K-W = 24.2932, p < 0.0001; molecular subtype K-W = 28.5439, p < 0.00000967538; size and invasion of the primary tumour after neoadjuvant chemotherapy K-W = 11.7944, p < 0.0377169; caspase-3 expression after neoadjuvant therapy, evaluated according to the Sataloff classification χ2 = 5.97, df = 1, p = 0.0145.

Discussion

No significant difference was found between Ki-67 expression in patients with pathological complete response, compared to those with partial and no response, a statistically significant difference in cases with different molecular subtype, histology grade, and tumour stage after neoadjuvant therapy. Cleaved caspase-3-positive breast cancer cases are often better responders to neoadjuvant therapy, but with no significant correlation to molecular subtype, high-grade categories, or tumour stage.

Conclusions

The caspase-3 and Ki-67 index on diagnostic biopsy are related to post-neoadjuvant treatment prognostic factors (ypT stage, grade), proving them useful for prediction of treatment response to neoadjuvant therapy and further patient management.

HER2-positive is an independent indicator for predicting pathological complete response to neoadjuvant therapy and Ki67-changed after neoadjuvant chemotherapy predicts favorable prognosis in Chinese women with locally advanced breast cancer

The growing body of evidence suggests that breast cancer (BC) who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) may experience a more favorable prognosis. The objective of this study is to investigate the correlation between clinicopathologic parameters of locally advanced breast cancer (LABC) patients and the outcomes of NAC, with the aim of identifying predictive indicators for pCR. Additionally, we seek to examine the conversion of IHC markers in pCR patients following NAC and its impact on the prognosis of BC patients. We conducted a study involving 126 patients with LABC. Clinicopathological parameters associated with pCR were subjected to univariate and multivariate analysis. Kaplan-Meier (KM) curves and the log-rank test were used to compare the statistical difference in prognosis in different groups of patients. Additionally, we used difference and consistency tests to examine the conversion of immunohistochemistry (IHC) markers following NAC. The status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and molecular subtypes of BC were associated with pCR in the univariate analysis (all P < .05), which may be potential markers to predict pCR. HER2 was identified as an independent factor for predicting pCR in the multivariate analysis. The pCR rate of HER2-positive patients who received NAC combined targeted therapy was higher than that of patients who only received NAC (P = .003). The disease-free survival (DFS) rate of TNBC patients who achieved pCR was significantly higher than that of non-pCR TNBC patients (P = .026). The IHC marker conversion after NAC mainly existed in PR (P = .041). Ki67 expression decreased in the luminal B subtype and increased in the HER2 enriched subtype after NAC (all P < .001). Patients with Ki67 expression change after NAC had longer overall survival (OS) and DFS than unchanged patients (all P < .05). HER2-positive is an independent indicator for predicting pCR, and HE2-positive patients who received NAC combined targeted therapy were favorable to achieving pCR. IHC markers of BC patients exhibit varying degrees of alterations after NAC, and changes in Ki67 expression after NAC could serve as a marker to predict a better prognosis.

Relationship between immune checkpoint proteins and neoadjuvant chemotherapy response in breast cancer

INTRODUCTION

Following major developments in cancer immunotherapy, treatments targeting immune checkpoint proteins (ICP) gained interest in breast cancer, though studies mostly focus on patients with metastatic disease as well as patients nonresponsive to the conventional treatments. Herein, we aimed to investigate the levels of ICP in tumor stroma and tumor infiltrating lymphocytes, and tumor tissue prior to neoadjuvant chemotherapy administration to evaluate the relationship between ICP levels, clinicopathological parameters, and NAC response.

MATERIALS AND METHODS

This study was conducted with 51 patients where PD-1, PD-L1, CTLA-4, TIM-3, CD24 and CD44 levels were investigated in CD45+ cells while CD326, CD24, CD44 and PD-L1 protein expression levels were investigated in CD45- population. In addition, CD44 and CD24 levels were evaluated in the tumor stroma. TIL levels were investigated according to the TILS Working Group. Treatment responses after NAC were evaluated according to the MD Anderson RCB score.

RESULTS

Our results revealed positive correlation between CTLA-4 and CD44 expression in cases with high TIL levels as well as TIL levels and CTLA-4 expression in cases with partial response. Similarly, positive correlation was detected between TIM3 and PD-L1 levels in cases with good response. In addition, a negative correlation between TILs after NAC and PD-1/PD-L1 expression in lymphocytes in cases with partial complete response.

CONCLUSIONS

Our study provides preliminary data about the correlation between ICP and clinicopathological status and NAC response in breast cancer, in addition to underlining the requirement for further research to determine their potential as therapeutic targets.

The residual cancer burden index as a valid prognostic indicator in breast cancer after neoadjuvant chemotherapy

PURPOSE

The residual cancer burden index (RCB) was proposed as a response evaluation criterion in breast cancer patients treated with Neoadjuvant Chemotherapy (NAC). This study evaluated the relevance of RCB with replase-free survival (RFS).

METHODS

The clinical data of 254 breast cancer patients who received NAC between 2016 and 2020 were retrospectively collected. The relationship between clinicopathologic factors and RFS was evaluated using Cox proportional hazards regression models. RFS estimates were determined by Kaplan-Meier(K-M) analysis and compared using the log-rank test. Multivariate logistic regression analysis was used to evaluate the risk factors associated with RCB. Receiver operating characteristic (ROC) curves showed the potential of the RCB and MP grading systems as biomarkers for RFS.

RESULTS

At a median follow-up of 52 months, 59 patients(23.23%) developed relapse. Multivariate Cox regression showed that older age (P = 0.022), high Pathologic T stage after NAC (P = 0.023) and a high RCB score(P = 0.003) were risk factors for relapse. The outcomes of the multivariate logistic analysis indicated that RCB 0 (pathologic complete response [pCR]) was associated with HER2-positive patients (P = 0.002) and triple-negative breast cancer (TNBC) patients (P = 0.013). In addition, the RCB and MP scoring systems served as prognostic markers for patients who received NAC, and their area under curves (AUCs) were 0.691 and 0.342, respectively.

CONCLUSION

These data suggest that RCB can be equally applied to predict RFS in Chinese patients with NAC. The application of RCB may help guide the selection of treatment strategies.

The Accuracy of Breast Cancer Diagnostic Tools

Background Breast cancer (BC) remains a significant health concern, leading to illness and death among women globally. It is essential to detect BC early using imaging techniques that accurately reflect the final pathology, guiding suitable intervention strategies. Objectives This study aimed to evaluate the agreement between radiological findings and histopathological results in BC cases. Methods We conducted a retrospective review of breast core needle biopsies (CNBs) in women over a six-year period (2017-2022) at Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia. The pathological diagnoses were compared with the findings from preceding radiological investigations. We also compared the tumour sizes in the resection specimens with their radiological counterparts. Results A total of 641 cases were included in the study. Ultrasound (US), mammography, and magnetic resonance imaging (MRI) yielded diagnostic accuracies of 85%, 77.9%, and 86.9%, respectively. MRI had the highest sensitivity at 72.2%, while US had the lowest at 61%. MRI provided the best agreement with the final resected tumor size. By contrast, mammography tended to overestimate the size (41.9%), and US most frequently underestimated it (67.7%). The connection between basal-like molecular subtypes and the Breast Imaging Reporting and Data System (BIRADS)-5 classifications was only statistically significant for MRI (p = 0.04). The luminal subtype was more likely to show speculation in mammography. Meanwhile, BIRADS-4 revealed a considerable number of benign pathologies across all the three modalities. Conclusions MRI demonstrated the highest accuracy, sensitivity, specificity, and positive predictive value (PPV) for diagnosing and estimating the tumor size. Mammography outperformed US in terms of sensitivity and yielded the highest negative predictive value (NPV). US, meanwhile, offered superior specificity, PPV, and accuracy. Therefore, combining these diagnostic methods could yield significant benefits.

Neoadjuvant pyrotinib plus trastuzumab and chemotherapy for HER2-positive breast cancer: a prospective cohort study

BACKGROUND

This prospective study aims to investigate the efficacy and safety of pyrotinib (P) combined with 4 cycles of epirubicin and cyclophosphamide followed by 4 cycles of taxane and trastuzumab (P + EC-TH) regimen as neoadjuvant therapy for human epidermal growth factor receptor 2 (HER2) positive breast cancer and to investigate the predictive value of p53, p63, and epidermal growth factor receptor (EGFR) status for neoadjuvant efficacy.

METHODS

A total of 138 HER2-positive breast cancer patients who received neoadjuvant therapy and underwent surgery were included. Case group: 55 patients received P + EC-TH regimen.

CONTROL GROUP

83 patients received EC-TH regimen. The chi-square test, Fisher's exact test, and logistic regression analysis were applied. The primary endpoint was total pathologic complete response (tpCR), and the secondary endpoints were breast pathologic complete response (bpCR), overall response rate (ORR), and adverse events (AEs).

RESULTS

In the case group, the tpCR rate was 63.64% (35/55), the bpCR rate was 69.09% (38/55), and the ORR was 100.00% (55/55). In the control group, the tpCR rate was 39.76% (33/83), the bpCR rate was 44.58% (37/83), and the ORR was 95.18% (79/83). The case group had significantly higher tpCR and bpCR rates than those of the control group (P < 0.05), but there was no significant difference in ORR (P > 0.05). The tpCR was associated with the status of estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR), and the patients with any negative ER, PR, AR, or combined, were more likely to achieve tpCR than those with positive results (P < 0.05). The p53-positive patients were more likely to achieve tpCR and bpCR than p53-negative patients (P < 0.05). The incidence of hypokalemia and diarrhea in the case group was higher than that in the control group (P < 0.05). The AEs developed were all manageable, and no treatment-related death occurred.

CONCLUSION

The efficacy and safety of the P + EC-TH regimen were verified by this study. The HER2-positive breast cancer patients treated with the EC-TH neoadjuvant regimen were more likely to achieve tpCR or bpCR if pyrotinib was administered simultaneously.

Localised breast cancer: neoadjuvant chemotherapy impact evaluation on the pathological complete response (PCR) in a lower middle-income country

Introduction

Neoadjuvant chemotherapy followed by surgery remains the current recommended therapeutic strategy for the management of locally advanced breast cancer. The standard chemotherapy protocol is sequential with anthracycline followed by taxanes. However public hospitals in Morocco are confronted with a shortage in healthcare products. We, therefore, evaluated the efficacy of the different protocols proposed to patients, by evaluating the clinical response after chemotherapy especially through the pathological complete response (PCR) after surgery.

Methods

We focused on the database of the medical oncology department of the only public hospital covering middle and southern Morocco. We included patients diagnosed between 2018 and 2020. Two groups of patients distinguished in group A (GA) received the standard therapy, and group B (GB) received a non-standard protocol. The therapeutic response was assessed clinically before surgery and then by pathological examination of the surgical specimens. The Sataloff classification defined the histological response for both tumour and lymph nodes. We included both groups in one variable to determine their impact on outcomes. A logistic regression-based analysis was adopted to define variables related to the PCR.

Results

Over the study period, 120 patients met our inclusion criteria. They were distinguished at 72% in GA and 28% in GB. 60.8% over 120 got a partial response, whereas, only 33.3% achieved a complete response. The general PCR rate was 28% with 14.3% in GB and 85.7% in GA. The tumour PCR was obtained in 40 (33.3%) over 120 patients and 51.7% of lymph node PCR. The multivariate logistic regression analysis results show no relative factors associated with general PCR achievement.

Conclusion

These first interesting results from an institutional database inform us about our clinical practice and require additional research using prospective randomised controlled studies.

Comparative Evaluation of Contrast-Enhanced Spectral Mammography and Digital Breast Tomosynthesis for Diagnosing and Treating Breast Cancer

BACKGROUND The aim of this study was to evaluate the efficacy of contrast-enhanced spectral mammography (CESM) and digital breast tomosynthesis (DBT) in the diagnosis and chemotherapy of breast cancer. MATERIAL AND METHODS We retrospectively analyzed data on 125 lesions of 115 patients with breast diseases in Lanzhou First People's Hospital from January 2020 to June 2022. Patients were examined by digital breast tomographic fusion and contrast-enhanced spectral mammography after chemotherapy. We compared the diagnostic accuracy of the 2 imaging techniques, and the diagnostic efficacy was evaluated with ROC curves. RESULTS There were significant differences in the type and degree of CESM enhancement between benign and malignant lesions. Malignant lesions mostly showed moderate to severe enhancement, while benign lesions mostly showed mild to moderate enhancement. There was no significant difference in DBT manifestations between benign and malignant lesions. After neoadjuvant chemotherapy, 88 patients had pathological remission, and the remission rate was 70.40%. Thirty-seven patients did not respond (nonresponse rate: 29.60%). The accuracy of CESM lesion size assessment was 84.00% (105/125), with high consistency. The accuracy of DBT lesion size assessment was 68.00% (85/125), and the consistency was poor. BI-RADS 4B was the truncation point. CESM had significantly higher sensitivity, specificity, accuracy, positive predictive value, and negative predictive value than DBT. In premenopausal patients and patients aged less than 50 years, the diagnostic efficacy of DBT and CESM was significantly different. CONCLUSIONS The diagnostic efficacy of CESM was significantly better than DBT in premenopausal women and patients under age 50. Diagnosis and treatment of breast diseases may be enhanced by the use of CESM.

Right Common Femoral Vein Invasion: A Unique Case of Inguinal Ectopic Breast Cancer

OBJECTIVES

Ectopic breast cancer may present anywhere in the milk line, from the axilla to the groin which is extremely rare in the inguinal region. Despite morphologic differences, ectopic breast tissue presents characteristics related to orthotopic breast tissue in terms of function and pathologic degeneration. The case report describes the treatment of a unique ectopic breast carcinoma which was located in the inguinal region with a common femoral vein invasion.

METHODS

We present a unique case of an ectopic breast carcinoma presenting in an unusual anatomic location along the milk line. The study was approved by the local Ethics Committee (protocol no: 12.01.2023-2023/02) Informed consent was obtained from the patient.

RESULTS

The patient is surgically treated and supplemented with neoadjuvant chemotherapy,radiotherapy and endocrine therapy. Histopathological examination revealed the diagnosis of invasive ductal carcinoma. The right common femoral vein was reconstructed with bovine pericardial patch after totally removal of the mass.

CONCLUSIONS

This report alerts the reader to be cognizant of the unusual location of an ectopic breast cancer which was detected in the inguinal region with a common femoral vein invasion and discusses the treatment, suggesting novel therapeutic advice that could bring considerable clinical advantages. A multidisciplinary approach should be warranted in such cases to confirm a complete remission.

Design and Synthesis of Novel Chalcone Derivatives: Anti-Breast Cancer Activity Evaluation and Docking Study

Chalcone is a common simple fragment of natural products with anticancer activity. In a previous study, the research group discovered a series of chalcone derivatives with stronger anticancer activities. To find better anticancer drugs, novel chalcone derivatives A1-A14, B1-B14 have continuously been designed and synthesized. The antiproliferative activity of these compounds against breast cancer cells (MCF-7) was investigated by the Cell Counting Kit-8 (CCK-8) method with 5-fluorouracil (5-Fu) as the control drug. The results showed that compound A14 exhibited excellent antiproliferative ability compared to the control drug 5-Fu. Scratch experiments and cloning experiments further confirmed that compound A14 could inhibit the proliferation and colony formation activity of MCF-7 cells. In addition, molecular docking primarily explains the interaction between compound and protein. These results suggested that compound A14 could be a promising chalcone derivative for further anti-breast cancer research.

Identification and validation of molecular subtypes and a 9-gene risk model for breast cancer

The long-term efficacy of treatment, heterogeneity, and complexity in the tumor microenvironment remained a clinical challenge in breast cancer (BRCA). There is a need to classify and refine appropriate therapeutic intervention decisions. A stable subtype classification based on gene expression associated with neoadjuvant chemotherapy (NAC) prognosis and assessment on the clinical features, immune infiltration, and mutational characteristics of the different subcategories was performed using ConsensusClusterPlus. We constructed a prognostic model by the least absolute shrinkage and selection operator regression (LASSO) and univariate Cox regression method and further investigated the association between the risk model and clinical features, mutation and immune characteristics of BRCA. We constructed 3 molecular clusters associated with NAC. We found that cluster 1 had the best prognosis, while cluster 3 showed a poor prognosis. Cluster 3 were associated with the advance stage, higher mutation score, activated oncogenic, and lower tumor immune dysfunction and exclusion (TIDE) score. Subsequently, we constructed a prognosis-related risk model comprising 9 genes (RLN2, MSLN, SAPCD2, LY6D, CACNG4, TUBA3E, LAMP3, GNMT, KLHDC7B). The higher-risk group exhibited lower immune infiltration and demonstrated improved overall survival (OS) in both the independent validation cohort. Finally, by combining clinicopathological features with the NAC-related prognostic risk model, we enhanced the accuracy of survival prediction and model performance. Here, we revealed 3 new molecular subtypes based on prognosis-related genes for BRCA NAC and developed a prognostic risk model. It has the potential to aid in the selection of appropriate individualized treatment and the prediction of patient prognosis.

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.

Radiomics Based on DCE-MRI for Predicting Response to Neoadjuvant Therapy in Breast Cancer

RATIONALE AND OBJECTIVES

To compare the value of radiomics and diameter% based on pre- and early-treatment dynamic enhanced MR (DCE-MRI) of the breast in predicting response to neoadjuvant therapy (NAT) in breast cancer and to construct a tool for early noninvasive prediction of NAT outcomes.

MATERIALS AND METHODS

Retrospective analysis of clinical and imaging data of 142 patients with primary invasive breast cancer who underwent DCE-MRI before and after two cycles of NAT at our institution. Enroled patients were randomly assigned in a 7:3 ratio to the training group and the test group. Patients were divided into pathological complete response (pCR) and non-pathological complete response groups based on surgical pathology findings after NAT. The maximum diameter relative regression values (Diameter%) before and after treatment were calculated and the conventional imaging Diameter% model was constructed. Based on pre- and early-NAT DCE-MRI, the optimal features of pre-NAT, early-NAT, and delta radiomics were screened using redundancy analysis, least absolute shrinkage, and selection operator methods to construct the corresponding radiomics model and calculate the Radscores. Indicators that were statistically significant in the univariate analysis of clinical data were further screened by stepwise regression and combined with Radscores to construct the fusion model. All models were evaluated and compared.

RESULTS

In the test set, the area under the curve (AUC) of the delta radiomics model (0.87) was higher than that of the pre-NAT, early-NAT radiomics models (0.57, 0.78) and the Diameter% model (0.83). The fusion model had the best efficacy in predicting pCR after NAT, with AUCs of 0.91 in the training and test sets. And its nomogram plot showed that Radscore of early-NAT radiomics had the greatest weight. In the test set, the fusion model and Delta radiomics model improved the efficacy of predicting pCR by 35.56% and 14.19%, respectively, compared to the Diameter% model (P = 0 and .039). Clinical decision curves showed the highest overall clinical benefit for the fusion model.

CONCLUSION

Radiomics, especially delta and early-NAT radiomics, may be potential biomarkers for early noninvasive prediction of NAT outcomes. And a fusion model constructed from meaningful clinicopathological indicators combined with radiomics can effectively predict NAT response.

Mammary carcinoma: Comparative oncology between small animals and humans-New therapeutic tools

The poor outcomes associated with mammary carcinomas (MCs) in dogs and cats in terms of locoregional recurrence, distant metastasis and survival, highlight the need for better management of mammary cancers in small animals. By contrast, the outcomes of women with breast cancer (BC) have dramatically improved during the last 10 years, notably thanks to new therapeutic strategies. The aim of this article was to imagine what could be the future of therapy for dogs and cats with MCs if it became inspired from current practices in human BC. This article focuses on the importance of taking into account cancer stage and cancer subtypes in therapeutic plans, on locoregional treatments (surgery, radiation therapy), new developments in endocrine therapy, chemotherapy, PARP inhibitors and immunotherapy. Ideally, multimodal treatment regimens would be chosen according to cancer stage and cancer subtypes, and according to predictive factors that are still to be defined.

Effect of caspase-1 (CASP1) combined with multimodal ultrasound features on the prognosis of breast cancer patients

Background

Breast cancer (BRCA) is the malignant tumor with the highest incidence rate among women in the world, and its mortality rate ranks second. The purpose of our study is to explore the correlation between caspase-1 (CASP1) and the prognosis of BRCA patients and the potential mechanism of action, and to analyze the clinical value of CASP1 combined with multimodal ultrasound features in early screening and prognosis of BRCA.

Methods

We analyzed The Cancer Genome Atlas (TCGA) database to confirm that CASP1 was expressed in BRCA patients and determine whether its expression was correlated with patient prognosis. The relationship between CASP1 expression and survival was measured by the clinicopathological parameters. Multivariate analysis was performed using Cox regression, and a nomogram was developed using these results for quality assurance purposes. The correlations between CASP1 and immune cells were investigated using the Tumor Immune Estimation Resource (TIMER) and TCGA databases. Next, we performed gene set enrichment analysis (GSEA) to determine the potential mechanism of action. Finally, to analyze the effect of CASP1 combined with multimodal ultrasonography characteristics on the prognosis of BRCA patients was studied by analyzing the clinical data of patients.

Results

CASP1 expression was lower in BRCA tumor tissues than in the surrounding tissues. Patients with high CASP1 expression had better overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) than those with low CASP1 expression. GSEA suggested that CASP1 may affect the cell cycle, immune environment, inflammation, apoptosis, the HIPPOMERLIN pathway, Natural killer (NK) cell regulation of cytotoxicity, p53 expression, the Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway, the mitogen-activated protein kinase (MAPK) pathway, extracellular matrix, etc., thereby influencing the biological events in BRCA. Among conventional ultrasound features and contrast-enhanced ultrasound (CEUS) features, mass margin status and blood flow grade were associated with the expression of CASP1. Meanwhile, patients with poor ultrasound features tended to have low CASP1 expression.

Conclusions

CASP1 may be a novel predictive marker for BRCA patients. CASP1 combined with multimodal ultrasound features has good clinical value in the early screening and prognostic prediction of BRCA.

Cardiac tamponade, a rare complication of gastric cardia cancer resection after neoadjuvant chemotherapy combined with immunotherapy: a case report and literature review

Transthoracic cardia resection is a technically well-established surgical procedure. However, acute cardiac tamponade in the early postoperative period is extremely rare. The occurrence is life-threatening to the patient. It also poses a great clinical challenge for perioperative management. To date, few cases of pericardial tamponade have been reported in gastric cancer resection performed after neoadjuvant chemotherapy combined with immunotherapy. We present the case of a 62-year-old woman who received neoadjuvant chemotherapy combined with immunotherapy before surgery, followed by transthoracic surgery. A life-threatening complication, pericardial tamponade, occurred in the early postoperative period. The successful outcome was achieved in through multidisciplinary collaboration.

ABVS-Based Radiomics for Early Predicting the Efficacy of Neoadjuvant Chemotherapy in Patients with Breast Cancers

Background

Neoadjuvant chemotherapy (NAC) plays a significant role in breast cancer (BC) management; however, its efficacy varies among patients. Current evaluation methods may lead to delayed treatment alterations, and traditional imaging modalities often yield inaccurate results. Radiomics, an emerging field in medical imaging, offers potential for improved tumor characterization and personalized medicine. Nevertheless, its application in early and accurately predicting NAC response remains underinvestigated.

Objective

This study aims to develop an automated breast volume scanner (ABVS)-based radiomics model to facilitate early detection of suboptimal NAC response, ultimately promoting personalized therapeutic approaches for BC patients.

Methods

This retrospective study involved 248 BC patients receiving NAC. Standard guidelines were followed, and patients were classified as responders or non-responders based on treatment outcomes. ABVS images were obtained before and during NAC, and radiomics features were extracted using the PyRadiomics toolkit. Inter-observer consistency and hierarchical feature selection were assessed. Three machine learning classifiers, logistic regression, support vector machine, and random forest, were trained and validated using a five-fold cross-validation with three repetitions. Model performance was comprehensively evaluated based on discrimination, calibration, and clinical utility.

Results

Of the 248 BC patients, 157 (63.3%) were responders, and 91 (36.7%) were non-responders. Radiomics feature selection revealed 7 pre-NAC and 6 post-NAC ABVS features, with higher weights for post-NAC features (min >0.05) than pre-NAC (max <0.03). The three post-NAC classifiers demonstrated AUCs of approximately 0.9, indicating excellent discrimination. DCA curves revealed a substantial net benefit when the threshold probability exceeded 40%. Conversely, the three pre-NAC classifiers had AUCs between 0.7 and 0.8, suggesting moderate discrimination and limited clinical utility based on their DCA curves.

Conclusion

The ABVS-based radiomics model effectively predicted suboptimal NAC responses in BC patients, with early post-NAC classifiers outperforming pre-NAC classifiers in discrimination and clinical utility. It could enhance personalized treatment and improve patient outcomes in BC management.

Machine Learning-Based Prediction of Distant Recurrence in Invasive Breast Carcinoma Using Clinicopathological Data: A Cross-Institutional Study

Breast cancer is the most common type of cancer worldwide. Alarmingly, approximately 30% of breast cancer cases result in disease recurrence at distant organs after treatment. Distant recurrence is more common in some subtypes such as invasive breast carcinoma (IBC). While clinicians have utilized several clinicopathological measurements to predict distant recurrences in IBC, no studies have predicted distant recurrences by combining clinicopathological evaluations of IBC tumors pre- and post-therapy with machine learning (ML) models. The goal of our study was to determine whether classification-based ML techniques could predict distant recurrences in IBC patients using key clinicopathological measurements, including pathological staging of the tumor and surrounding lymph nodes assessed both pre- and post-neoadjuvant therapy, response to therapy via standard-of-care imaging, and binary status of adjuvant therapy administered to patients. We trained and tested four clinicopathological ML models using a dataset (144 and 17 patients for training and testing, respectively) from Duke University and validated the best-performing model using an external dataset (8 patients) from Dartmouth Hitchcock Medical Center. The random forest model performed better than the C-support vector classifier, multilayer perceptron, and logistic regression models, yielding AUC values of 1.0 in the testing set and 0.75 in the validation set (p < 0.002) across both institutions, thereby demonstrating the cross-institutional portability and validity of ML models in the field of clinical research in cancer. The top-ranking clinicopathological measurement impacting the prediction of distant recurrences in IBC were identified to be tumor response to neoadjuvant therapy as evaluated via SOC imaging and pathology, which included tumor as well as node staging.

Image-guided focused ultrasound-mediated molecular delivery to breast cancer in an animal model

Tumors become inoperable due to their size or location, making neoadjuvant chemotherapy the primary treatment. However, target tissue accumulation of anticancer agents is limited by the physical barriers of the tumor microenvironment. Low-intensity focused ultrasound (FUS) in combination with microbubble (MB) contrast agents can increase microvascular permeability and improve drug delivery to the target tissue after systemic administration. The goal of this research was to investigate image-guided FUS-mediated molecular delivery in volume space. Three-dimensional (3-D) FUS therapy functionality was implemented on a programmable ultrasound scanner (Vantage 256, Verasonics Inc.) equipped with a linear array for image guidance and a 128-element therapy transducer (HIFUPlex-06, Sonic Concepts). FUS treatment was performed on breast cancer-bearing female mice (N= 25). Animals were randomly divided into three groups, namely, 3-D FUS therapy, two-dimensional (2-D) FUS therapy, or sham (control) therapy. Immediately prior to the application of FUS therapy, animals received a slow bolus injection of MBs (Definity, Lantheus Medical Imaging Inc.) and near-infrared dye (IR-780, surrogate drug) for optical reporting and quantification of molecular delivery. Dye accumulation was monitored viain vivooptical imaging at 0, 1, 24, and 48 h (Pearl Trilogy, LI-COR). Following the 48 h time point, animals were humanely euthanized and tumors excised forex vivoanalyzes. Optical imaging results revealed that 3-D FUS therapy improved delivery of the IR-780 dye by 66.4% and 168.1% at 48 h compared to 2-D FUS (p= 0.18) and sham (p= 0.047) therapeutic strategies, respectively.Ex vivoanalysis revealed similar trends. Overall, 3-D FUS therapy can improve accumulation of a surrogate drug throughout the entire target tumor burden after systemic administration.

Early Prediction of Response to Neoadjuvant Chemotherapy Using Quantitative Parameters on Automated Breast Ultrasound Combined with Contrast-Enhanced Ultrasound in Breast Cancer

OBJECTIVE

This prospective study was aimed at evaluating the role of automated breast ultrasound (ABUS) and contrast-enhanced ultrasound (CEUS) in the early prediction of treatment response to neoadjuvant chemotherapy (NAC) in patients with breast cancer.

METHODS

Forty-three patients with pathologically confirmed invasive breast cancer treated with NAC were included. The standard for evaluation of response to NAC was based on surgery within 21 d of completing treatment. The patients were classified as having a pathological complete response (pCR) and a non-pCR. All patients underwent CEUS and ABUS 1 wk before receiving NAC and after two treatment cycles. The rising time (RT), time to peak (TTP), peak intensity (PI), wash-in slope (WIS) and wash-in area under the curve (Wi-AUC) were measured on the CEUS images before and after NAC. The maximum tumor diameters in the coronal and sagittal planes were measured on ABUS, and the tumor volume (V) was calculated. The difference (∆) in each parameter between the two treatment time points was compared. Binary logistic regression analysis was used to identify the predictive value of each parameter.

RESULTS

∆V, ∆TTP and ∆PI were independent predictors of pCR. The CEUS-ABUS model achieved the highest AUC (0.950), followed by those based on CEUS (0.918) and ABUS (0.891) alone.

CONCLUSION

The CEUS-ABUS model could be used clinically to optimize the treatment of patients with breast cancer.

Sentinel Lymph Node Identification in Post Neoadjuvant Chemotherapy Breast Cancer Patients Undergoing Surgical Excision Using Lymphosonography

OBJECTIVES

This study evaluated the efficacy of lymphosonography in the identification of sentinel lymph nodes (SLNs) in post neoadjuvant chemotherapy patients with breast cancer scheduled to undergo surgical excision.

METHODS

Seventy-nine subjects scheduled for breast cancer surgery with SLN excision completed this IRB-approved study, out of which 18 (23%) underwent neoadjuvant chemotherapy before surgery. Subjects underwent percutaneous Sonazoid (GE Healthcare) injections around the tumor area for a total of 1.0 mL. Lymphosonography was performed using CPS on an S3000 HELX scanner (Siemens Healthineers) with a linear probe. Subjects received blue dye and radioactive tracer as part of their standard of care. Excised SLNs were classified as positive or negative for the presence of blue dye, radioactive tracer and Sonazoid. The results were compared between methods and pathology findings.

RESULTS

Seventy-two SLNs were surgically excised from 18 subjects, 29 were positive for blue dye, 63 were positive for radioactive tracer and 57 were positive for Sonazoid. Comparison with blue dye showed that both radioactive tracer and lymphosonography achieved an accuracy of 53% (P > .50). Comparison with radioactive tracer showed that blue dye had an accuracy of 53%, while lymphosonography achieved an accuracy of 67% (P < .01). Of the 72 SLNs, 15 were determined malignant by pathology; the detection rate was 47% for blue dye (7/15), 67% for radioactive tracer (10/15) and 100% for lymphosonography (15/15) (P < .001).

CONCLUSIONS

Lymphosonography achieved similar accuracy as radioactive tracer and higher accuracy than blue dye for identifying SLNs. The 15 SLNs positive for malignancy were all identified by lymphosonography.

Compression OCT-elastography combined with speckle-contrast analysis as an approach to the morphological assessment of breast cancer tissue

Currently, optical biopsy technologies are being developed for rapid and label-free visualization of biological tissue with micrometer-level resolution. They can play an important role in breast-conserving surgery guidance, detection of residual cancer cells, and targeted histological analysis. For solving these problems, compression optical coherence elastography (C-OCE) demonstrated impressive results based on differences in the elasticity of different tissue constituents. However, sometimes straightforward C-OCE-based differentiation is insufficient because of the similar stiffness of certain tissue components. We present a new automated approach to the rapid morphological assessment of human breast cancer based on the combined usage of C-OCE and speckle-contrast (SC) analysis. Using the SC analysis of structural OCT images, the threshold value of the SC coefficient was established to enable the separation of areas of adipose cells from necrotic cancer cells, even if they are highly similar in elastic properties. Consequently, the boundaries of the tumor bed can be reliably identified. The joint analysis of structural and elastographic images enables automated morphological segmentation based on the characteristic ranges of stiffness (Young's modulus) and SC coefficient established for four morphological structures of breast-cancer samples from patients post neoadjuvant chemotherapy (residual cancer cells, cancer stroma, necrotic cancer cells, and mammary adipose cells). This enabled precise automated detection of residual cancer-cell zones within the tumor bed for grading cancer response to chemotherapy. The results of C-OCE/SC morphometry highly correlated with the histology-based results (r =0.96-0.98). The combined C-OCE/SC approach has the potential to be used intraoperatively for achieving clean resection margins in breast cancer surgery and for performing targeted histological analysis of samples, including the evaluation of the efficacy of cancer chemotherapy.

Development and validation of a radiopathomic model for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer patients

BACKGROUND

Neoadjuvant chemotherapy (NAC) has become the standard therapeutic option for early high-risk and locally advanced breast cancer. However, response rates to NAC vary between patients, causing delays in treatment and affecting the prognosis for patients who do not sensitive to NAC.

MATERIALS AND METHODS

In total, 211 breast cancer patients who completed NAC (training set: 155, validation set: 56) were retrospectively enrolled. we developed a deep learning radiopathomics model(DLRPM) by Support Vector Machine (SVM) method based on clinicopathological features, radiomics features, and pathomics features. Furthermore, we comprehensively validated the DLRPM and compared it with three single-scale signatures.

RESULTS

DLRPM had favourable performance for the prediction of pathological complete response (pCR) in the training set (AUC 0.933[95% CI 0.895-0.971]), and in the validation set (AUC 0.927 [95% CI 0.858-0.996]). In the validation set, DLRPM also significantly outperformed the radiomics signature (AUC 0.821[0.700-0.942]), pathomics signature (AUC 0.766[0.629-0.903]), and deep learning pathomics signature (AUC 0.804[0.683-0.925]) (all p < 0.05). The calibration curves and decision curve analysis also indicated the clinical effectiveness of the DLRPM.

CONCLUSIONS

DLRPM can help clinicians accurately predict the efficacy of NAC before treatment, highlighting the potential of artificial intelligence to improve the personalized treatment of breast cancer patients.

Prediction of clinical response to neoadjuvant therapy in advanced breast cancer by baseline B-mode ultrasound, shear-wave elastography, and pathological information

Background

Neoadjuvant therapy (NAT) is the preferred treatment for advanced breast cancer nowadays. The early prediction of its responses is important for personalized treatment. This study aimed at using baseline shear wave elastography (SWE) ultrasound combined with clinical and pathological information to predict the clinical response to therapy in advanced breast cancer.

Methods

This retrospective study included 217 patients with advanced breast cancer who were treated in West China Hospital of Sichuan University from April 2020 to June 2022. The features of ultrasonic images were collected according to the Breast imaging reporting and data system (BI-RADS), and the stiffness value was measured at the same time. The changes were measured according to the Response evaluation criteria in solid tumors (RECIST1.1) by MRI and clinical situation. The relevant indicators of clinical response were obtained through univariate analysis and incorporated into a logistic regression analysis to establish the prediction model. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the prediction models.

Results

All patients were divided into a test set and a validation set in a 7:3 ratio. A total of 152 patients in the test set, with 41 patients (27.00%) in the non-responders group and 111 patients (73.00%) in the responders group, were finally included in this study. Among all unitary and combined mode models, the Pathology + B-mode + SWE model performed best, with the highest AUC of 0.808 (accuracy 72.37%, sensitivity 68.47%, specificity 82.93%, P<0.001). HER2+, Skin invasion, Post mammary space invasion, Myometrial invasion and Emax were the factors with a significant predictive value (P<0.05). 65 patients were used as an external validation set. There was no statistical difference in ROC between the test set and the validation set (P>0.05).

Conclusion

As the non-invasive imaging biomarkers, baseline SWE ultrasound combined with clinical and pathological information can be used to predict the clinical response to therapy in advanced breast cancer.

Deep learning based registration of serial whole-slide histopathology images in different stains

For routine pathology diagnosis and imaging-based biomedical research, Whole-slide image (WSI) analyses have been largely limited to a 2D tissue image space. For a more definitive tissue representation to support fine-resolution spatial and integrative analyses, it is critical to extend such tissue-based investigations to a 3D tissue space with spatially aligned serial tissue WSIs in different stains, such as Hematoxylin and Eosin (H&E) and Immunohistochemistry (IHC) biomarkers. However, such WSI registration is technically challenged by the overwhelming image scale, the complex histology structure change, and the significant difference in tissue appearances in different stains. The goal of this study is to register serial sections from multi-stain histopathology whole-slide image blocks. We propose a novel translation-based deep learning registration network CGNReg that spatially aligns serial WSIs stained in H&E and by IHC biomarkers without prior deformation information for the model training. First, synthetic IHC images are produced from H&E slides through a robust image synthesis algorithm. Next, the synthetic and the real IHC images are registered through a Fully Convolutional Network with multi-scaled deformable vector fields and a joint loss optimization. We perform the registration at the full image resolution, retaining the tissue details in the results. Evaluated with a dataset of 76 breast cancer patients with 1 H&E and 2 IHC serial WSIs for each patient, CGNReg presents promising performance as compared with multiple state-of-the-art systems in our evaluation. Our results suggest that CGNReg can produce promising registration results with serial WSIs in different stains, enabling integrative 3D tissue-based biomedical investigations.

Influence of cyclin D1 splicing variants expression on breast cancer chemoresistance via CDK4/CyclinD1-pRB-E2F1 pathway

Cyclin D1 (CCND1), a mediator of cell cycle control, has a G870A polymorphism which results in the formation of two splicing variants: full-length CCND1 (CCND1a) and C-terminally truncated CCND1 species (CCND1b). However, the role of CCND1a and CCND1b variants in cancer chemoresistance remains unknown. Therefore, this study aimed to explore the molecular mechanism of alternative splicing of CCND1 in breast cancer (BC) chemoresistance. To address the contribution of G870A polymorphism to the production of CCND1 variants in BC chemoresistance, we sequenced the G870A polymorphism and analysed the expressions of CCND1a and CCND1b in MCF-7 and MCF-7/ADM cells. In comparison with MCF-7 cells, MCF-7/ADM cells with the A allele could enhance alternative splicing with the increase of SC-35, upregulate the ratio of CCND1b/a at both mRNA and protein levels, and activate the CDK4/CyclinD1-pRB-E2F1 pathway. Furthermore, CCND1b expression and the downstream signalling pathway were analysed through Western blotting and cell cycle in MCF-7/ADM cells with knockdown of CCND1b. Knockdown of CCND1b downregulated the ratio of CCND1b/a, demoted cell proliferation, decelerated cell cycle progression, inhibited the CDK4/CyclinD1-pRB-E2F1 pathway and thereby decreased the chemoresistance of MCF-7/ADM cells. Finally, CCND1 G870A polymorphism, the alternative splicing of CCDN1 was detected through Sequenom Mass ARRAY platform, Sanger sequencing, semi-quantitative RT-PCR, Western blotting and immunohistochemistry in clinical BC specimens. The increase of the ratio of CCND1b/a caused by G870A polymorphism was involved in BC chemoresistance. Thus, these findings revealed that CCND1b/a ratio caused by the polymorphism is involved in BC chemoresistance via CDK4/CyclinD1-pRB-E2F1 pathway.

PD‑1/PD‑L1 immune checkpoint inhibitors in neoadjuvant therapy for solid tumors (Review)

A comprehensive search regarding programmed cell death protein 1 (PD‑1)/programmed death‑ligand 1 (PD‑L1) inhibitor monotherapy or combination therapy in neoadjuvant settings of 11 types of solid cancer was performed using the PubMed, Cochrane and Embase databases, and the abstracts of various conferences were screened. Data presented in 99 clinical trials indicated that preoperative treatment with PD‑1/PD‑L1 combined therapy, particularly immunotherapy plus chemotherapy, could achieve a higher objective response rate, a higher major pathologic response rate and a higher pathologic complete response rate, as well as a lower number of immune‑related adverse events compared with PD‑1/PD‑L1 monotherapy or dual immunotherapy. Although PD‑1/PD‑L1 inhibitor combination caused more treatment‑related adverse events (TRAEs) in patients, most of the TRAEs were acceptable and did not cause marked delays in operation. The data suggest that patients with pathological remission after neoadjuvant immunotherapy exhibit improved postoperative disease‑free survival compared with those without pathological remission. Further studies are still required to evaluate the long‑term survival benefit of neoadjuvant immunotherapy.

High Dynamic Range Dual-Modal White Light Imaging Improves the Accuracy of Tumor Bed Sampling After Neoadjuvant Therapy for Breast Cancer

OBJECTIVES

Accurate evaluation of residual cancer burden remains challenging because of the lack of appropriate techniques for tumor bed sampling. This study evaluated the application of a white light imaging system to help pathologists differentiate the components and location of tumor bed in specimens.

METHODS

The high dynamic range dual-mode white light imaging (HDR-DWI) system was developed to capture antiglare reflection and multiexposure HDR transmission images. It was tested in 60 specimens of modified radical mastectomy after neoadjuvant therapy. We observed the differential transmittance among tumor tissue, fibrosis tissue, and adipose tissue.

RESULTS

The sensitivity and specificity of HDR-DWI were compared with x-ray or visual examination to determine whether HDR-DWI was superior in identifying tumor beds. We found that tumor tissue had lower transmittance (0.12 ± 0.03) than fibers (0.15 ± 0.04) and fats (0.27 ± 0.07) (P < .01).

CONCLUSIONS

HDR-DWI was more sensitive in identifying fiber and tumor tissues than cabinet x-ray and visual observation (P < .01). In addition, HDR-DWI could identify more fibrosis areas than the currently used whole slide imaging did in 12 samples (12/60). We have determined that HDR-DWI can provide more in-depth tumor bed information than x-ray and visual examination do, which will help prevent diagnostic errors in tumor bed sampling.

Neoadjuvant pegylated liposomal doxorubicin- and epirubicin-based combination therapy regimens for early breast cancer: a multicenter retrospective case-control study

PURPOSE

This study aimed to compare the effectiveness and safety of pegylated liposomal doxorubicin (PLD)-based and epirubicin-based combination therapy regimen as neoadjuvant therapy for early breast cancer.

METHODS

Patients with stage I-III breast cancer who underwent neoadjuvant therapy followed by surgery between January 2018 and December 2019 were retrospectively reviewed. The primary outcome was pathological complete response (pCR) rate. The secondary outcome was radiologic complete response (rCR) rate. Outcomes were compared between treatment groups PLD-cyclophosphamide followed by docetaxel (LC-T group) or epirubicin-cyclophosphamide followed by docetaxel (EC-T group), using both propensity-score matched (matched) and unmatched data.

RESULTS

Data were analyzed from patients who received neoadjuvant LC-T (n = 178) or EC-T (n = 181) treatment. The overall pCR rate and rCR rate were higher in the LC-T group compared with the EC-T group (unmatched pCR: 25.3% vs. 15.5%, p = 0.026; rCR: 14.7% vs. 6.7%, p = 0.016; matched pCR: 26.9% vs. 16.1%, p = 0.034; rCR: 15.5% vs. 7.4%, p = 0.044). Analysis by molecular subtype showed that compared with EC-T treatment, LC-T treatment achieved significantly greater pCR rate in triple-negative subtype and greater rCR rate in Her2 (+) subtype.

CONCLUSIONS

Neoadjuvant PLD-based therapy may be a potential option for patients with early-stage breast cancer. The current results warrant further investigation.

Integrated tumor genomic and immune microenvironment analysis identifies predictive biomarkers associated with the efficacy of neoadjuvant therapy for triple-negative breast cancer

BACKGROUND

Although neoadjuvant chemotherapy (NAC) is currently the best therapy for triple-negative breast cancer (TNBC), resistance still occurs in a considerable proportion, thus it is crucial to understand resistance mechanisms and identify predictive biomarkers for patients selection.

METHODS

Biopsy samples were collected from 21 patients with TNBC who underwent NAC. Whole-exome sequencing (WES), targeted sequencing, and multiplex immunohistochemistry (mIHC) were carried out on the clinical samples and used to identify and validate potential biomarkers associated with response to NAC. In addition, data on 190 TNBC patients who had undergone chemotherapy were obtained from The Cancer Genome Atlas (TCGA) and analyzed to further validate our findings.

RESULTS

Both the tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were significantly higher in responders than in non-responders. Higher response rates and longer survival rates were observed in patients with higher TMB. Patients with higher ratios of CD8 to M2 macrophages had higher response rates and improved survival rates. Finally, the integrated analysis demonstrated that the combination of TMB and the ratio of CD8 T cells to M2 macrophages could further distinguish patients who benefitted from the treatment in both enrolled patients and public data.

CONCLUSIONS

The findings of this study indicated that the combination of TMB and the ratio of CD8 T cells to M2 macrophages may be a potential biomarker for improving the recognition of NAC responders, thereby providing a basis for developing precision NAC regimens.

The Role of Nomogram Based on the Combination of Ultrasound Parameters and Clinical Indicators in the Degree of Pathological Remission of Breast Cancer

Background

The mortality rate of breast cancer (BC) ranks first among female tumors worldwide and presents a trend of younger age, which poses a great threat to women's health and life. Neoadjuvant chemotherapy (NAC) for breast cancer is defined as the first step of treatment for breast cancer patients without distant metastasis before planned surgical treatment or local treatment with surgery and radiotherapy. According to the current NCCN guidelines, patients with different molecular types of BC should receive neoadjuvant chemotherapy (NAC), which can not only achieve tumor downstaging, increase the chance of surgery, and improve the breast-conserving rate. In addition, it can identify new genetic pathways and drugs related to cancer, improve patient survival rate, and make new progress in breast cancer management.

Objective

To explore the role of the nomogram established by the combination of ultrasound parameters and clinical indicators in the degree of pathological remission of breast cancer.

Methods

A total of 147 breast cancer patients who received neoadjuvant chemotherapy and elective surgery in the Department of Ultrasound, Nantong Cancer Hospital, from May 2014 to August 2021 were retrospectively included. Postoperative pathological remission was divided into two groups according to Miller-Payne classification: no significant remission group (NMHR group, n = 93) and significant remission group (MHR group, n = 54). Clinical characteristics of patients were recorded and collected. The multivariate logistic regression model was used to screen the information features related to the MHR group, and then, a nomogram model was constructed; ROC curve area, consistency index (C-index, CI), calibration curve, and H-L test were used to evaluate the model. And the decision curve is used to compare the net income of the single model and composite model.

Results

Among 147 breast cancer patients, 54 (36.7%) had pathological remission. Multivariate logistic regression showed that ER, reduction/disappearance of strong echo halo, Adler classification after NAC, PR + CR, and morphological changes were independent risk factors for pathological remission (P < 0.05). Based on these factors, the nomogram was constructed and verified. The area under the curve (AUC) and CI were 0.966, the sensitivity and specificity were 96.15% and 92.31%, and the positive predictive value (PPV) and negative predictive value (NPV) were 87.72% and 97.15%, respectively. The mean absolute error of the agreement between the predicted value and the real value is 0.026, and the predicted risk is close to the actual risk. In the range of HRT of about 0.0∼0.9, the net benefit of the composite evaluation model is higher than that of the single model. H-L test results showed that χ ² = 8.430, P=0.393 > 0.05.

Conclusion

The nomogram model established by combining the changes of ultrasound parameters and clinical indicators is a practical and convenient prediction model, which has a certain value in predicting the degree of pathological remission after neoadjuvant chemotherapy.

Early Assessment of Neoadjuvant Chemotherapy Response Using Multiparametric Magnetic Resonance Imaging in Luminal B-like Subtype of Breast Cancer Patients: A Single-Center Prospective Study

This study aimed to evaluate the performance of multiparametric breast magnetic resonance imaging (mpMRI) for predicting response to neoadjuvant chemotherapy (NAC) in patients with luminal B subtype breast cancer. The prospective study included thirty-five patients treated with NAC for both early and locally advanced breast cancer of the luminal B subtype at the University Hospital Centre Zagreb between January 2015 and December 2018. All patients underwent breast mpMRI before and after two cycles of NAC. Evaluation of mpMRI examinations included analysis of both morphological (shape, margins, and pattern of enhancement) and kinetic characteristics (initial signal increase and post-initial behavior of the time-signal intensity curve), which were additionally interpreted with a Göttingen score (GS). Histopathological analysis of surgical specimens included grading the tumor response based on the residual cancer burden (RCB) grading system and revealed 29 NAC responders (RCB-0 (pCR), I, II) and 6 NAC non-responders (RCB-III). Changes in GS were compared with RCB classes. A lack of GS decrease after the second cycle of NAC is associated with RCB class and non-responders to NAC.

A novel PTEN mutant caused by polymorphism in cis-regulatory elements is involved in chemosensitivity in breast cancer

Phosphatase and tensin homolog (PTEN) is one of the most important tumor suppressor genes. Although studies have shown the association between cancer and genetic polymorphisms of PTEN, the underlying molecular mechanisms of breast cancer (BC) chemosensitivity that results from PTEN polymorphism is still unclear. This study aims to investigate potential links between PTEN polymorphisms in cis-regulatory elements and BC chemosensitivity in the Chinese population. A total of 172 BC patients who received neoadjuvant chemotherapy were included in the study, including 104 chemosensitive cases and 68 chemoresistant cases. The results showed a significant association between the rs786204926 polymorphism and BC chemosensitivity. Logistic multivariate regression analysis showed that age, lymph node metastasis, and the rs786204926 genotype were risk factors for BC chemoresistance. The G allele of rs786204926 is more prone to increasing the risk of chemosensitivity in BC. Additionally, analysis using Alamut Visual showed a preference of the G allele of rs786204926 to produce a novel PTEN mutant with an insertion of 18 bases from intron 4. While the transcriptional level of PTEN remained similar in chemosensitivity and chemoresistant samples, its protein level changed significantly. Interestingly, there were significant differences in both transcription and protein levels of the novel PTEN mutant between the two groups. Furthermore, we found that the mutant was more susceptible to dephosphorylation compared with wildtype PTEN, leading to chemosensitivity through the PI3K-AKT signaling pathway. These findings indicate that novel PTEN mutants caused by polymorphisms in cis-regulatory elements may be involved in BC chemosensitivity.

Neoadjuvant checkpoint blockade in combination with Chemotherapy in patients with tripe-negative breast cancer: exploratory analysis of real-world, multicenter data

PURPOSE

Despite the poor prognosis of triple-negative breast cancer (TNBC), it has been demonstrated that neoadjuvant immunotherapy in combination with chemotherapy can improve the pathologic complete response (pCR) rate and/or long-term outcome of TNBC. However, there have been no real-world studies reporting on the effectiveness of neoadjuvant checkpoint inhibitors in early TNBC.

METHODS

Between November 2019 and December 2021, 63 early TNBC patients treated with anti-PD-1 antibodies (pembrolizumab or camrelizumab) or anti-PD-L1 antibody (atezolizumab) in combination with chemotherapy at seven institutions were included. PCR1 defined as ypT0/Tis and ypN0 was the primary endpoint. Secondary endpoints included pCR2 defined as ypT0/Tis, overall response rate (ORR), disease-free survival (DFS), drug-related adverse events (AEs) and biomarkers.

RESULTS

Among the patients in the current study, 34.9% of patients were able to achieve pCR1, and 47.6% of patients had achieved pCR2. The ORR was 82.5%. 33 patients with non-pCR2 tumors were found to have a median DFS of 20.7 months (95% CI 16.3 months-not reached). The DFS of patients with pCR2 and non-pCR2 after neoadjuvant therapy was significantly different (HR = 0.28, 95% CI 0.10-0.79; P = 0.038). The most common AEs were nausea (63.4%), fatigue (42.7%), leucopenia (30.0%) and elevated transaminase (11.7%).

CONCLUSION

It is possible to achieve a meaningful pCR rate and DFS by combining neoadjuvant checkpoint blockade with chemotherapy in patients with high-risk TNBC. Compared to clinical trials, however, there was a slightly lower pCR rate in this multicentered real-world study.

Metabolic syndrome is a risk factor for breast cancer patients receiving neoadjuvant chemotherapy: A case-control study

Purpose

To investigate the impact of metabolic syndrome (MetS) on pathologic complete response (pCR) and clinical outcomes in breast cancer (BC) patients who received neoadjuvant chemotherapy (NAC).

Methods

We analyzed 221 female BC patients at Harbin Medical University Cancer Hospital who received NAC and divided them into MetS and non-MetS groups according to National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) criteria to investigate the association between MetS and clinicopathological characteristics, pathologic response, and long-term survival and to observe the changes in metabolic parameters after NAC.

Results

A total of 53 (24.0%) BC patients achieved pCR after NAC in our study. MetS status was an independent predictor of pCR, and pCR was more difficult to obtain in the MetS group than the non-MetS group (P=0.028). All metabolic parameters deteriorated significantly after NAC, especially the blood lipid index (P<0.010). The median follow-up time was 6 years. After adjusting for other prognostic factors, MetS was found to be strongly associated with an increased risk of recurrence (P=0.007) and mortality (P=0.004) in BC patients receiving NAC. Compared to individuals without any MetS component, the risk of death and disease progression increased sharply as the number of MetS components increased.

Conclusions

In BC patients who received NAC, MetS was associated with poor outcomes, including a lower pCR rate and increased risks of recurrence and mortality.

Multiparametric MRI radiomics fusion for predicting the response and shrinkage pattern to neoadjuvant chemotherapy in breast cancer

Purpose

During neoadjuvant chemotherapy (NACT), breast tumor morphological and vascular characteristics are usually changed. This study aimed to evaluate the tumor shrinkage pattern and response to NACT by preoperative multiparametric magnetic resonance imaging (MRI), including dynamic contrast-enhanced MRI (DCE-MRI), diffuse weighted imaging (DWI) and T2 weighted imaging (T2WI).

Method

In this retrospective analysis, female patients with unilateral unifocal primary breast cancer were included for predicting tumor pathologic/clinical response to NACT (n=216, development set, n=151 and validation set, n=65) and for discriminating the tumor concentric shrinkage (CS) pattern from the others (n=193; development set, n=135 and validation set, n=58). Radiomic features (n=102) of first-order statistical, morphological and textural features were calculated on tumors from the multiparametric MRI. Single- and multiparametric image-based features were assessed separately and were further combined to feed into a random forest-based predictive model. The predictive model was trained in the testing set and assessed on the testing dataset with an area under the curve (AUC). Molecular subtype information and radiomic features were fused to enhance the predictive performance.

Results

The DCE-MRI-based model showed higher performance (AUCs of 0.919, 0.830 and 0.825 for tumor pathologic response, clinical response and tumor shrinkage patterns, respectively) than either the T2WI or the ADC image-based model. An increased prediction performance was achieved by a model with multiparametric MRI radiomic feature fusion.

Conclusions

All these results demonstrated that multiparametric MRI features and their information fusion could be of important clinical value for the preoperative prediction of treatment response and shrinkage pattern.