Neoadjuvant chemotherapy in breast cancer: significantly enhanced response with docetaxel

Development of nanobiosensor for therapeutic drug monitoring in personalized cancer treatment approach

Docetaxel is one of the most effective and safe chemotherapy drugs according to the World Health Organization, but its clinical use has been discontinued due to its various side effects. To reduce these side effects, the amount of docetaxel drug should be kept at the most effective level, it should be monitored in body fluids. Due to the limitations of traditional analytical methods used for this purpose, such as expensive and low sensitivity, labor-intensive and time-consuming complex preliminary preparation, efficient methods are required for the determination of the docetaxel level in the body. The increasing demand for the development of personalized therapy has recently spurred significant research into biosensors for the detection of drugs and other chemical compounds. In this study, an electrochemical-based portable nanobiosensor system was developed for the rapid, low-cost, and sensitive determination of docetaxel. In this context, mg-p(HEMA)-IMEO nanoparticles to be used as nanobiosensor bioactive layer was synthesized, characterized, and docetaxel determination conditions were optimized. According to the results obtained, the developed nanobiosensor system can detect docetaxel with a sensitivity of 2.22 mg/mL in a wide calibration range of 0.25-10 mg/mL, in only 15 min, in mixed media such as commercially available artificial blood serum and urine. determined. We concluded that the developed nanobiosensor system can be successfully used in routine drug monitoring as a low-cost biomedical device capable of direct, rapid, and specific drug determination within the scope of personalized treatment, providing point-of-care testing.

Phase 2 study of neoadjuvant enzalutamide and paclitaxel for luminal androgen receptor-enriched TNBC: Trial results and insights into "ARness"

Luminal androgen receptor (LAR)-enriched triple-negative breast cancer (TNBC) is a distinct subtype. The efficacy of AR inhibitors and the relevant biomarkers in neoadjuvant therapy (NAT) are yet to be determined. We tested the combination of the AR inhibitor enzalutamide (120 mg daily by mouth) and paclitaxel (80 mg/m2 weekly intravenously) (ZT) for 12 weeks as NAT for LAR-enriched TNBC. Eligibility criteria included a percentage of cells expressing nuclear AR by immunohistochemistry (iAR) of at least 10% and a reduction in sonographic volume of less than 70% after four cycles of doxorubicin and cyclophosphamide. Twenty-four patients were enrolled. Ten achieved a pathologic complete response or residual cancer burden-I. ZT was safe, with no unexpected side effects. An iAR of at least 70% had a positive predictive value of 0.92 and a negative predictive value of 0.97 in predicting LAR-enriched TNBC according to RNA-based assays. Our data support future trials of AR blockade in early-stage LAR-enriched TNBC.

The Role of Circulating MicroRNAs in the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer in the Indian Population

INTRODUCTION

MicroRNAs (miRNAs) are known to play an important role in cancer cell proliferation, susceptibility of cancer cells to chemotherapy, and patient survival. Identifying miRNAs that can predict response to chemotherapy in locally advanced breast cancer (LABC), the most common variant, can help to choose appropriate drug regimens to suit the epigenetic profile of individual patients.

OBJECTIVE

To investigate the expression of the differentially expressed miRNAs identified by next-generation sequencing from a pilot study involving cases and controls, in peripheral blood mononuclear cells (PBMC) of patients with LABC during the course of neoadjuvant chemotherapy (NAC) and determine their role in response to chemotherapy.

METHODS

This study included 30 newly diagnosed LABC patients. Peripheral blood from every participant was collected before the start of chemotherapy, at the end of the third cycle, and at the end of the seventh cycle of NAC. Based on the results of a pilot study in a similar population with suitable controls, four differentially expressed miRNAs namely miR-24-2, miR-192-5p, miR-3609, and miR-664b-3p were considered to be validated in this study. The expression of these four miRNAs was examined by qRT-PCR, and their association with response to chemotherapy was analyzed.

RESULT

 A significant change in the expression of miR-192-5p was found in responders (p = 0.001) over a period of seven cycles and the difference between the expression of miR-24-2 from baseline to the seventh cycle of NAC was higher in responders while compared to the non-responders (p < 0.05).

CONCLUSION

miR-192-5p and miR-24-2 were identified as predictive biomarkers for response to NAC in south Indian patients with LABC.

Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy

Locally advanced breast cancer (LABC) is a severe type of cancer with a poor prognosis, despite advancements in therapy. As the disease is often inoperable, current guidelines suggest upfront aggressive neoadjuvant chemotherapy (NAC). Complete pathological response to chemotherapy is linked to improved survival, but conventional clinical assessments like physical exams, mammography, and imaging are limited in detecting early response. Early detection of tissue response can improve complete pathological response and patient survival while reducing exposure to ineffective and potentially harmful treatments. A rapid, cost-effective modality without the need for exogenous contrast agents would be valuable for evaluating neoadjuvant therapy response. Conventional ultrasound provides information about tissue echogenicity, but image comparisons are difficult due to instrument-dependent settings and imaging parameters. Quantitative ultrasound (QUS) overcomes this by using normalized power spectra to calculate quantitative metrics. This study used a novel transfer learning-based approach to predict LABC response to neoadjuvant chemotherapy using QUS imaging at pre-treatment. Using data from 174 patients, QUS parametric images of breast tumors with margins were generated. The ground truth response to therapy for each patient was based on standard clinical and pathological criteria. The Residual Network (ResNet) deep learning architecture was used to extract features from the parametric QUS maps. This was followed by SelectKBest and Synthetic Minority Oversampling (SMOTE) techniques for feature selection and data balancing, respectively. The Support Vector Machine (SVM) algorithm was employed to classify patients into two distinct categories: nonresponders (NR) and responders (RR). Evaluation results on an unseen test set demonstrate that the transfer learning-based approach using spectral slope parametric maps had the best performance in the identification of nonresponders with precision, recall, F1-score, and balanced accuracy of 100, 71, 83, and 86%, respectively. The transfer learning-based approach has many advantages over conventional deep learning methods since it reduces the need for large image datasets for training and shortens the training time. The results of this study demonstrate the potential of transfer learning in predicting LABC response to neoadjuvant chemotherapy before the start of treatment using quantitative ultrasound imaging. Prediction of NAC response before treatment can aid clinicians in customizing ineffectual treatment regimens for individual patients.

18F-FDG PET/CT-based deep learning radiomics predicts 5-years disease-free survival after failure to achieve pathologic complete response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

This study aimed to assess whether a combined model incorporating radiomic and depth features extracted from PET/CT can predict disease-free survival (DFS) in patients who failed to achieve pathologic complete response (pCR) after neoadjuvant chemotherapy.

RESULTS

This study retrospectively included one hundred and five non-pCR patients. After a median follow-up of 71 months, 15 and 7 patients experienced recurrence and death, respectively. The primary tumor volume underwent feature extraction, yielding a total of 3644 radiomic features and 4096 depth features. The modeling procedure employed Cox regression for feature selection and utilized Cox proportional-hazards models to make predictions on DFS. Time-dependent receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were utilized to evaluate and compare the predictive performance of different models. 2 clinical features (RCB, cT), 4 radiomic features, and 7 depth features were significant predictors of DFS and were included to develop models. The integrated model incorporating RCB, cT, and radiomic and depth features extracted from PET/CT images exhibited the highest accuracy for predicting 5-year DFS in the training (AUC 0.943) and the validation cohort (AUC 0.938).

CONCLUSION

The integrated model combining radiomic and depth features extracted from PET/CT images can accurately predict 5-year DFS in non-pCR patients. It can help identify patients with a high risk of recurrence and strengthen adjuvant therapy to improve survival.

FTO-mediated epigenetic upregulation of LINC01559 confers cell resistance to docetaxel in breast carcinoma by suppressing miR-1343-3p

This study was to explore the regulatory effect of long non-coding RNA LINC01559 on Docetaxel resistance in breast carcinoma (BCa) and its underlying mechanism. In the present study, we found that LINC01559 expression was elevated and LINC01559 overexpression facilitated docetaxel resistance in BCa cells. Moreover, it was revealed that the upregulation of LINC01559 in BCa cells was induced by FTO-mediated demethylation in an m6A-YTHDF2-dependent manner. Additionally, Dual-luciferase reporter assay confirmed the binding ability between LINC01559 and miR-1343-3p, and Pearson correlation analysis showed a negative correlation between them. Particularly, miR-1343-3p inhibition partly abolished the suppression on docetaxel resistance in BCa cells caused by LINC01559 knockdown. To sum up, FTO-mediated epigenetic upregulation of LINC01559 promoted cell resistance to Docetaxel in BCa by negatively regulating miR-1343-3p.

Phase III study of HR-positive/HER2-negative/lymph node-positive breast cancer non-responsive to primary chemotherapy: a randomized trial

There are few studies focus on post-neoadjuvant treatment in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-)/lymph node-positive (LN+) breast cancer, a multi-center, open-label, randomized, controlled phase III trial was conducted to evaluate pathological response-guided non-cross-resistant adjuvant chemotherapy in patients with HR+/HER2-/LN+ breast cancer who were non-responsive to primary chemotherapy. Patients received four cycles of non-cross-resistant adjuvant chemotherapy plus endocrine therapy (ET), or ET alone. Forty patients responsive to neoadjuvant chemotherapy and with Miller and Payne G4 or G5 and LN- status were assigned to the observation group. Distant disease-free survival was the primary endpoint. The final intention-to-treat analysis comprised 379 patients. After a median follow-up period of 72.4 months, the 5-year distant disease-free survival was 92% and 90% in the chemotherapy plus ET and ET-alone groups, respectively. Comparatively, the observation group showed a trend towards better distant disease-free survival. For patients non-responsive to neoadjuvant chemotherapy, adjuvant non-cross-resistant chemotherapy did not significantly improve distant disease-free survival compared to ET alone.

Pathologic response and residual tumor cellularity after neo-adjuvant chemotherapy predict prognosis in breast cancer patients

INTRODUCTION

Residual tumor cellularity (RTC) and pathologic complete response (pCR) after neo-adjuvant chemotherapy (NAC) are prognostic factors associated with improved outcomes in breast cancer (BC). However, the majority of patients achieve partial pathologic response (pPR) and no clear correlation between RTC patterns and outcomes was described. Our aims were to define predictive factors for pCR and compare different outcomes of patients with pCR or pPR and with different RTC patterns.

MATERIALS AND METHODS

Baseline and post-NAC demographics, clinicopathological characteristics, post-operative data, survival and recurrence status were recorded from our institutional database. A multivariable analysis was performed using a logistic regression model to identify independent predictors of pCR. Disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS) analyses were performed using the Kaplan-Meier method.

RESULTS

Overall, of the 495 patients analyzed, 148 (29.9%) achieved pCR, 347 (70.1%) had pPR, and the median RTC was 40%. Multivariable analysis identified 3 independent factors predictive of pCR: tumor stage before NAC (cT1-2 84.5% versus cT3-4 15.5%), BC sub-type (HER2-positive 54.7% versus triple-negative 29.8% versus luminal-like 15.5%), and vascular invasion (absence 98.0% versus presence 2.0%). We found statistically significant longer DFS, DDFS, and OS in patients with pCR and with RTC <40%; no difference was observed in terms of OS between RTC <40% and RTC ≥40% groups.

CONCLUSIONS

Tumor stage before NAC, BC sub-type, and vascular invasion are significant and independent factors associated with pCR. Patients with pCR and with RTC <40% have longer DFS, DDFS, and OS compared with patients with pPR.

A phase II study of neoadjuvant atezolizumab and nab-paclitaxel in patients with anthracycline-resistant early-stage triple-negative breast cancer

PURPOSE

Neoadjuvant anti-PD-(L)1 therapy improves the pathological complete response (pCR) rate in unselected triple-negative breast cancer (TNBC). Given the potential for long-term morbidity from immune-related adverse events (irAEs), optimizing the risk-benefit ratio for these agents in the curative neoadjuvant setting is important. Suboptimal clinical response to initial neoadjuvant therapy (NAT) is associated with low rates of pCR (2-5%) and may define a patient selection strategy for neoadjuvant immune checkpoint blockade. We conducted a single-arm phase II study of atezolizumab and nab-paclitaxel as the second phase of NAT in patients with doxorubicin and cyclophosphamide (AC)-resistant TNBC (NCT02530489).

METHODS

Patients with stage I-III, AC-resistant TNBC, defined as disease progression or a < 80% reduction in tumor volume after 4 cycles of AC, were eligible. Patients received atezolizumab (1200 mg IV, Q3weeks × 4) and nab-paclitaxel (100 mg/m² IV,Q1 week × 12) as the second phase of NAT before undergoing surgery followed by adjuvant atezolizumab (1200 mg IV, Q3 weeks, × 4). A two-stage Gehan-type design was employed to detect an improvement in pCR/residual cancer burden class I (RCB-I) rate from 5 to 20%.

RESULTS

From 2/15/2016 through 1/29/2021, 37 patients with AC-resistant TNBC were enrolled. The pCR/RCB-I rate was 46%. No new safety signals were observed. Seven patients (19%) discontinued atezolizumab due to irAEs.

CONCLUSION

This study met its primary endpoint, demonstrating a promising signal of activity in this high-risk population (pCR/RCB-I = 46% vs 5% in historical controls), suggesting that a response-adapted approach to the utilization of neoadjuvant immunotherapy should be considered for further evaluation in a randomized clinical trial.

Predicting Pathological Complete Response in Breast Cancer After Two Cycles of Neoadjuvant Chemotherapy by Tumor Reduction Rate: A Retrospective Case-Control Study

PURPOSE

We aimed to identify effectiveness-associated indicators and evaluate the optimal tumor reduction rate (TRR) after two cycles of neoadjuvant chemotherapy (NAC) in patients with invasive breast cancer.

METHODS

This retrospective case-control study included patients who underwent at least four cycles of NAC at the Department of Breast Surgery between February 2013 and February 2020. A regression nomogram model for predicting pathological responses was constructed based on potential indicators.

RESULTS

A total of 784 patients were included, of whom 170 (21.68%) reported pathological complete response (pCR) after NAC and 614 (78.32%) had residual invasive tumors. The clinical T stage, clinical N stage, molecular subtype, and TRR were identified as independent predictors of pCR. Patients with a TRR > 35% were more likely to achieve pCR (odds ratio, 5.396; 95% confidence interval [CI], 3.299-8.825). The receiver operating characteristic (ROC) curve was plotted using the probability value, and the area under the ROC curve was 0.892 (95% CI, 0.863-0.922).

CONCLUSION

TRR > 35% is predictive of pCR after two cycles of NAC, and an early evaluation model using a nomogram based on five indicators, age, clinical T stage, clinical N stage, molecular subtype, and TRR, is applicable in patients with invasive breast cancer.

Predictive and prognostic values of tumor infiltrating lymphocytes in breast cancers treated with neoadjuvant chemotherapy: A meta-analysis

BACKGROUND

This meta-analysis assessed the predictive and prognostic value of tumor infiltrating lymphocytes (TILs) in neoadjuvant chemotherapy (NACT) treated breast cancer and an optimal threshold for predicting pathologic complete response (pCR).

METHODS

A systematic search of PubMed, EMBASE and Web of Science electronic databases was conducted to identify eligible studies published before April 2022. Either a fixed or random effects model was applied to estimate the pooled hazard ratio (HR) and odds ratio (OR) for prognosis and predictive values of TILs in breast cancer patients treated with NACT. The study is registered with PROSPERO (CRD42020221521).

RESULTS

A total of 29 published studies were eligible. Increased levels of TILs predicted response to NACT in HER2 positive breast cancer (OR = 2.54 95%CI, 1.50-4.29) and triple negative breast cancer (TNBC) (OR = 3.67, 95%CI, 1.93-6.97), but not for hormone receptor (HR) positive breast cancer (OR = 1.68, 95 %CI, 0.67-4.25). A threshold of 20% of H & E-stained TILs was associated with prediction of pCR in both HER2 positive breast cancer (P = 0.035) and TNBC (P = 0.001). Moreover, increased levels of TILs (either iTILs or sTILs) were associated with survival benefit in HER2-positive breast cancer and TNBC. However, an increased level of TILs was not a prognostic factor for survival in HR positive breast cancer (pooled HR = 0.64, 95%CI: 0.03-14.1, P = 0.78).

CONCLUSIONS

Increased levels of TILs were associated with increased rates of response to NACT and improved prognosis for the molecular subtypes of TNBC and HER2-positive breast cancer, but not for patients with HR positive breast cancer. A threshold of 20% TILs was the most powerful outcome prognosticator of pCR.

Optimal Choice of Neoadjuvant Chemotherapy for HER2-Negative Breast Cancer: Clinical Insights

The neoadjuvant setting provides immense opportunities for translational research and drug development. The acceptance of pathological complete response (pCR) as a surrogate endpoint for clinical benefit has led to the widespread use of neoadjuvant treatment. Optimal neoadjuvant therapies are determined based on their ability to achieve the highest rates of pCR. Predicted rates of pCR for triple negative breast cancer (TNBC) treated with sequential taxane/anthracycline regimens range from 35% to 48%. With the addition of a platinum agent pCR rates of 55% are predicted. Further increases have been observed with the addition of immune checkpoint inhibitors to this standard chemotherapy backbone. In the pivotal KEYNOTE-522 clinical trial pCR rates of 65% and 69% were reported for chemotherapy plus pembrolizumab in the overall and PD-L1-positive subgroup respectively. The role of the neoadjuvant chemotherapy is less clear in hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative breast cancer. In general, HR–positive cancers have the least chance of achieving a pCR after neoadjuvant chemotherapy, especially if they are low-grade. If neoadjuvant chemotherapy is given for high-risk HR-positive, HER2-negative breast cancer, standard adjuvant anthracycline/taxane regimens are appropriate. Optimum endocrine therapy is the standard-of-care in the adjuvant setting regardless of pCR. There are several genomic signatures available to guide decisions regarding adjuvant chemotherapy use however these assays are not routinely used in the neoadjuvant setting. For high-risk patients meeting the criteria for the monarchE trial adjuvant abemaciclib in addition to endocrine therapy is associated with an improvement in disease free survival (DFS) at 3 years. Based on the OlympiA trial patients with germline BRCA mutations should be considered for adjuvant olaparib therapy. In this article we review neoadjuvant clinical trials that guide optimum treatment options for TNBC and HR-positive, HER2-negative breast cancer.

Hyaluronic acid-based nano drug delivery systems for breast cancer treatment: Recent advances

Breast cancer (BC) is the most common malignancy among females worldwide, and high resistance to drugs and metastasis rates are the leading causes of death in BC patients. Releasing anti-cancer drugs precisely to the tumor site can improve the efficacy and reduce the side effects on the body. Natural polymers are attracting extensive interest as drug carriers in treating breast cancer. Hyaluronic acid (HA) is a natural polysaccharide with excellent biocompatibility, biodegradability, and non-immunogenicity and is a significant component of the extracellular matrix. The CD44 receptor of HA is overexpressed in breast cancer cells and can be targeted to breast tumors. Therefore, many researchers have developed nano drug delivery systems (NDDS) based on the CD44 receptor tumor-targeting properties of HA. This review examines the application of HA in NDDSs for breast cancer in recent years. Based on the structural composition of NDDSs, they are divided into HA NDDSs, Modified HA NDDSs, and HA hybrid NDDSs.

Treatment Strategies for Residual Disease following Neoadjuvant Chemotherapy in Patients with Early-Stage Breast Cancer

Breast cancer continues to be the most diagnosed cancer among women worldwide. Neoadjuvant chemotherapy is the standard of care for breast cancer patients with locally advanced disease and patients with poor pathological features, such as triple-negative (TN) or human epidermal growth factor receptor-2 (HER2)-positive subtypes. Neoadjuvant therapy offers several advantages, including better surgical outcomes, early systemic treatment for micro-metastases, and accurate tumor biology and chemosensitivity assessment. Multiple studies have shown that achieving pathological complete response (pCR) following neoadjuvant chemotherapy is associated with better prognosis and better treatment outcomes; almost half of such patients may fail to achieve pCR. Tumor proliferative index, hormone receptor (HR) status, and HER2 expression are the major predictors of pCR. Strategies to improve pCR have been dependent on augmenting neoadjuvant chemotherapy with the addition of taxanes and dual anti-HER2 targeted therapy in patients with HER2-positive tumor, and more recently, immunotherapy for patients with TN disease. The clinical management of patients with residual disease following neoadjuvant chemotherapy varies and depends mostly on the level of HR expression and HER2 status. Recent data have suggested that switching trastuzumab to trastuzumab-emtansine (T-DM1) in patients with HER2-positive disease and the addition of capecitabine for patients with HER2-negative and HR-negative subtype is associated with a better outcome; both strategies are incorporated into current clinical practice guidelines. This paper reviews available and ongoing studies addressing strategies to better manage patients who continue to have residual disease following neoadjuvant chemotherapy.

Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies

Complete pathological response (pCR) to neoadjuvant chemotherapy (NAC) is a prognostic factor for breast cancer (BC) patients and is correlated with improved survival. However, pCR rates are variable to standard NAC, depending on BC subtype. This study investigates quantitative digital histopathology coupled with machine learning (ML) to predict NAC response a priori. Clinicopathologic data and digitized slides of BC core needle biopsies were collected from 149 patients treated with NAC. The nuclei within the tumor regions were segmented on the histology images of biopsy samples using a weighted U-Net model. Five pathomic feature subsets were extracted from segmented digitized samples, including the morphological, intensity-based, texture, graph-based and wavelet features. Seven ML experiments were conducted with different feature sets to develop a prediction model of therapy response using a gradient boosting machine with decision trees. The models were trained and optimized using a five-fold cross validation on the training data and evaluated using an unseen independent test set. The prediction model developed with the best clinical features (tumor size, tumor grade, age, and ER, PR, HER2 status) demonstrated an area under the ROC curve (AUC) of 0.73. Various pathomic feature subsets resulted in models with AUCs in the range of 0.67 and 0.87, with the best results associated with the graph-based and wavelet features. The selected features among all subsets of the pathomic and clinicopathologic features included four wavelet and three graph-based features and no clinical features. The predictive model developed with these features outperformed the other models, with an AUC of 0.90, a sensitivity of 85% and a specificity of 82% on the independent test set. The results demonstrated the potential of quantitative digital histopathology features integrated with ML methods in predicting BC response to NAC. This study is a step forward towards precision oncology for BC patients to potentially guide future therapies.

Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy

To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as potential earlier indicators of pathological Complete Response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). However, they work either for sagittal or axial MRI protocols. More flexible AI tools, to be used easily in clinical practice across various institutions in accordance with its own imaging acquisition protocol, are required. Here, we addressed this topic by developing an AI method based on deep learning in giving an early prediction of pCR at various DCE-MRI protocols (axial and sagittal). Sagittal DCE-MRIs refer to 151 patients (42 pCR; 109 non-pCR) from the public I-SPY1 TRIAL database (DB); axial DCE-MRIs are related to 74 patients (22 pCR; 52 non-pCR) from a private DB provided by Istituto Tumori “Giovanni Paolo II” in Bari (Italy). By merging the features extracted from baseline MRIs with some pre-treatment clinical variables, accuracies of 84.4% and 77.3% and AUC values of 80.3% and 78.0% were achieved on the independent tests related to the public DB and the private DB, respectively. Overall, the presented method has shown to be robust regardless of the specific MRI protocol.

Platinum and Taxane Based Adjuvant and Neoadjuvant Chemotherapy in Early Triple-Negative Breast Cancer: A Narrative Review

Platinum (Pt) derivatives such as cisplatin and carboplatin are the class of drugs with proven activity against triple-negative breast cancer (TNBC). This is due to the ability of Pt compounds to interfere with the DNA repair mechanisms of the neoplastic cells. Taxanes have been efficacious against estrogen receptor-negative tumors and act by disruption of microtubule function. Due to their distinct mechanisms of action and routes of metabolism, the combination of the Pt agents and taxanes results in reduced systemic toxicity, which is ideal for treating TNBC. Also, the sensitivity of BRCA1-mutated cells to taxanes remains unsolved as in vitro evidence indicates resistance against taxanes due to BRCA1 mutations. Recent evidence suggests that the combination of carboplatin and paclitaxel resulted in better pathological complete response (pCR) in patients with TNBC, both in neoadjuvant and adjuvant settings. In vitro studies showed sequential dependency and optimal time scheduling of Pt- and taxane-based chemotherapy. Also, combining carboplatin with docetaxel in the NAC regimen yields an excellent pCR in patients with BRCA-associated and wild-type TNBC. TNBC is a therapeutic challenge that can be tackled by identifying new therapeutic sub-targets and specific cross-sections that can be benefitted from the addition of Pt- and taxane-based chemotherapy. This review summarizes the merits as well as the mechanism of Pt- and taxane-based adjuvant and neoadjuvant chemotherapies in early TNBC from the available and ongoing clinical studies.

Locally advanced breast cancer

Locally advanced breast cancer (LABC) is defined here as inoperable breast adenocarcinoma without distant metastases. Patients with LABC require a multidisciplinary approach. Given the risk of distant metastasis, staging exams are necessary. The incidence of LABC (stages IIIB and IIIC) has decreased in recent years. LABC has rarely been investigated separately: patients with LABC have participated both in clinical trials of palliative and of neoadjuvant therapy. Most trials did not analyze responses and long-term outcomes independently; thus, the treatment of patients with LABC is extrapolated from studies of patients with less or more advanced disease. Pathologic confirmation and molecular profiling are essential for the choice of neoadjuvant chemotherapy. Preoperative endocrine therapy may be considered in certain clinical situations; the addition of a CDK4/6 inhibitor is being investigated. HER2 positive LABCs are targeted with anti-HER2 agents combined with chemotherapy. PD-1 and PD-L1 antibodies in ‘triple-negative’ LABC are promising. Excellent responses to neoadjuvant therapy enable conservative surgery in many patients; however, inflammatory breast cancer may still indicate mastectomy. Postoperative radiotherapy is usually indicated. Target volumes include breast/chest wall, axillary, supraclavicular and internal mammary nodal basins. Preoperative radiation therapy can be useful in patients without response to systemic therapies. Palliative surgery for poor responders after neoadjuvant systemic and radiation therapy can be considered. Multidisciplinary teams can optimize local control and prevent relapses. However, modest improvement in survival was achieved between 2000 and 2014 underscoring the unmet need in patients with LABC who will benefit from specific research efforts in this disease entity.

Neoadjuvant hormonal therapy before radical prostatectomy in high-risk prostate cancer

Patients with high-risk prostate cancer treated with curative intent are at an increased risk of biochemical recurrence, metastatic progression and cancer-related death compared with patients treated for low-risk or intermediate-risk disease. Thus, these patients often need multimodal therapy to achieve complete disease control. Over the past two decades, multiple studies on the use of neoadjuvant treatment have been performed using conventional androgen deprivation therapy, which comprises luteinizing hormone-releasing hormone agonists or antagonists and/or first-line anti-androgens. However, despite results from these studies demonstrating a reduction in positive surgical margins and tumour volume, no benefit has been observed in hard oncological end points, such as cancer-related death. The introduction of potent androgen receptor signalling inhibitors (ARSIs), such as abiraterone, apalutamide, enzalutamide and darolutamide, has led to a renewed interest in using neoadjuvant hormonal treatment in high-risk prostate cancer. The addition of ARSIs to androgen deprivation therapy has demonstrated substantial survival benefits in the metastatic castration-resistant, non-metastatic castration-resistant and metastatic hormone-sensitive settings. Intuitively, a similar survival effect can be expected when applying ARSIs as a neoadjuvant strategy in high-risk prostate cancer. Most studies on neoadjuvant ARSIs use a pathological end point as a surrogate for long-term oncological outcome. However, no consensus yet exists regarding the ideal definition of pathological response following neoadjuvant hormonal therapy and pathologists might encounter difficulties in determining pathological response in hormonally treated prostate specimens. The neoadjuvant setting also provides opportunities to gain insight into resistance mechanisms against neoadjuvant hormonal therapy and, consequently, to guide personalized therapy.

Radiomics Analysis of Multi-Phase DCE-MRI in Predicting Tumor Response to Neoadjuvant Therapy in Breast Cancer

Objective: To explore whether the pretreatment dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and radiomics signatures were associated with pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer. Method: A retrospective review of 70 patients with breast invasive carcinomas proved by biopsy between June 2017 and October 2020 (26 patients were pathological complete response, and 44 patients were non-pathological complete response). Within the pre-contrast and five post-contrast dynamic series, a total of 1037 quantitative imaging features were extracted from in each phase. Additionally, the Δfeatures (the difference between the features before and after the comparison) were used for subsequent analysis. The least absolute shrinkage and selection operator (LASSO) regression method was used to select features related to pCR, and then use these features to train multiple machine learning classifiers to predict the probability of pCR for a given patient. The area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the predictive performances of the radiomics model for each of the five phases of time points. Result: Among the five phases, each individual phase performed with AUCs ranging from 0.845 to 0.919 in predicting pCR. The best single phases performance was given by the 3rd phase (AUC = 0.919, sensitivity 0.885, specificity 0.864). 5 of the features have significant differences between pCR and non-pCR groups in each phase, most features reach their maximum or minimum in the 2nd or 3rd phase. Conclusion: The radiomic features extracted from each phase of pre-treatment DCE-MRI possess discriminatory power to predict tumor response.

Bioactive nanotherapeutic trends to combat triple negative breast cancer

The management of aggressive breast cancer, particularly, triple negative breast cancer (TNBC) remains a formidable challenge, despite treatment advancement. Although newer therapies such as atezolizumab, olaparib, and sacituzumab can tackle the breast cancer prognosis and/or progression, but achieved limited survival benefit(s). The current research efforts are aimed to develop and implement strategies for improved bioavailability, targetability, reduce systemic toxicity, and enhance therapeutic outcome of FDA-approved treatment regimen. This review presents various nanoparticle technology mediated delivery of chemotherapeutic agent(s) for breast cancer treatment. This article also documents novel strategies to employ cellular and cell membrane cloaked (biomimetic) nanoparticles for effective clinical translation. These technologies offer a safe and active targeting nanomedicine for effective management of breast cancer, especially TNBC.

Effectiveness of ADC Difference Value on Pre-neoadjuvant Chemotherapy MRI for Response Evaluation of Breast Cancer

Background: Neoadjuvant chemotherapy (NAC) is known to be a suitable treatment and first-line defense for locally advanced breast cancer. However, the NAC response may include unexpected outcomes, and it is not easy to predict the NAC response precisely. Especially, early detection of those patients who do not benefit from NAC is needed to reduce unnecessary therapy and side effects. Objective: The purpose of this study was to determine whether the pretreatment apparent diffusion coefficient (ADC) value is effective for predicting the response of breast cancer to NAC. Method: Forty-nine breast cancer cases with pre- and post-NAC breast MRI were enrolled. MRI was performed using a 1.5-T scanner with the basic protocol including diffusion-weighted imaging. ADC difference value (ADC-diff) was calculated in all cases. Results: ADC-diff was high in complete response and partial response cases (p < .05). ADC-diff correlated with the DWI rim sign, with a positive DWI rim sign being associated with a higher ADC-diff (p < .05). Conclusion: High-ADC difference value on the pretreatment MRI can provide information for a better response of NAC on breast cancer.

Response to Induction Neoadjuvant Hormonal Therapy Using Upfront 21-Gene Breast Recurrence Score Assay-Results From the SAFIA Phase III Trial

Luminal, human epidermal growth factor receptor 2–negative breast cancer represents the most common subtype of breast malignancies. Neoadjuvant strategies of operable breast cancer are mostly based on chemotherapy, whereas it is not completely understood which patients might benefit from neoadjuvant hormone therapy (NAHT).

Assessment and Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Comparison of Imaging Modalities and Future Perspectives

Neoadjuvant chemotherapy (NAC) is becoming the standard of care for locally advanced breast cancer, aiming to reduce tumor size before surgery. Unfortunately, less than 30% of patients generally achieve a pathological complete response and approximately 5% of patients show disease progression while receiving NAC. Accurate assessment of the response to NAC is crucial for subsequent surgical planning. Furthermore, early prediction of tumor response could avoid patients being overtreated with useless chemotherapy sections, which are not free from side effects and psychological implications. In this review, we first analyze and compare the accuracy of conventional and advanced imaging techniques as well as discuss the application of artificial intelligence tools in the assessment of tumor response after NAC. Thereafter, the role of advanced imaging techniques, such as MRI, nuclear medicine, and new hybrid PET/MRI imaging in the prediction of the response to NAC is described in the second part of the review. Finally, future perspectives in NAC response prediction, represented by AI applications, are discussed.

Chemotherapeutic effects on breast tumor hemodynamics revealed by eigenspectra multispectral optoacoustic tomography (eMSOT)

Non-invasive monitoring of hemodynamic tumor responses to chemotherapy could provide unique insights into the development of therapeutic resistance and inform therapeutic decision-making in the clinic.

Methods: Here, we examined the longitudinal and dynamic effects of the common chemotherapeutic drug Taxotere on breast tumor (KPL-4) blood volume and oxygen saturation using eigenspectra multispectral optoacoustic tomography (eMSOT) imaging over a period of 41 days. Tumor vascular function was assessed by dynamic oxygen-enhanced eMSOT (OE-eMSOT). The obtained in vivo optoacoustic data were thoroughly validated by ex vivo cryoimaging and immunohistochemical staining against markers of vascularity and hypoxia.

Results: We provide the first preclinical evidence that prolonged treatment with Taxotere causes a significant drop in mean whole tumor oxygenation. Furthermore, application of OE-eMSOT showed a diminished vascular response in Taxotere-treated tumors and revealed the presence of static blood pools, indicating increased vascular permeability.

Conclusion: Our work has important translational implications and supports the feasibility of eMSOT imaging for non-invasive assessment of tumor microenvironmental responses to chemotherapy.

A Novel Three-Gene Score as a Predictive Biomarker for Pathologically Complete Response after Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Although triple-negative breast cancer (TNBC) typically responds better to neoadjuvant chemotherapy (NAC) compared to the other subtypes, a pathological complete response (pCR) is achieved in less than half of the cases. We established a novel three-gene score using genes based on the E2F target gene set that identified pCR after NAC, which showed robust performance in both training and validation cohorts (total of n = 3862 breast cancer patients). We found that the three-gene score was elevated in TNBC compared to the other subtypes. A high score was associated with Nottingham histological grade 3 in TNBC. Across multiple cohorts, high-score TNBC enriched not only E2F targets but also G2M checkpoint and mitotic spindle, which are all cell proliferation-related gene sets. High-score TNBC was associated with homologous recombination deficiency, high mutation load, and high infiltration of Th1, Th2, and gamma-delta T cells. However, the score did not correlate with drug sensitivity for paclitaxel, 5-fluorouracil, cyclophosphamide, and doxorubicin in TNBC human cell lines. High-score TNBC was significantly associated with a high rate of pCR not only in the training cohort but also in the validation cohorts. High-score TNBC was significantly associated with better survival in patients who received chemotherapy but not in patients who did not receive chemotherapy. The three-gene score is associated with a high mutation rate, immune cell infiltration, and predicts response to NAC in TNBC.

Impact of sequence order of anthracyclines and taxanes in neoadjuvant chemotherapy on pathologic complete response rate in HER2-negative breast cancer patients

PURPOSE

Data exploring optimal sequencing of anthracyclines and taxanes as neoadjuvant chemotherapy (NACT) for breast cancer are limited and inconsistent. The objective of this study was to assess the real-world impact of sequence order on pathologic complete response (pCR) and clinical outcomes from NACT.

METHODS

Patients with HER2-negative breast cancer treated with NACT from May 2012 to April 2020 were identified from a prospectively collected institutional database. The primary endpoint was to compare rates of pCR (ypT0/isN0) between patients who received anthracyclines followed by taxanes (AC-T) to those who received taxanes followed by anthracyclines (T-AC). Additional endpoints of interest included clinical complete response, downstaging, Neo-Bioscore, conversion to breast-conserving surgery eligibility, relapse-free survival, and overall survival between groups.

RESULTS

Of the 283 patients who met eligibility criteria, 187 (66%) received AC-T and 96 (34%) received T-AC. Sequence order did not influence the primary endpoint of pCR rate (19% for AC-T vs. 21% for T-AC, p = 0.752). There were also no significant differences in secondary NACT efficacy outcomes between groups. In the overall cohort, pCR rate was higher in patients with triple-negative breast cancer (TNBC) (32% vs. 13% in hormone-positive cancer, p < 0.001) and grade 3 tumors (31% vs. 12% for grade 1-2 tumors, p < 0.001).

CONCLUSIONS

In this real-world analysis of HER2-negative breast cancer patients, there was no differential impact on pCR rate or clinical outcomes from NACT with sequence order of anthracyclines and taxanes. This supports the current variation in prescribing practice.

Standardized pathology report for breast cancer

Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of 'standard data elements,' 'conditional data elements,' and a biomarker report form. The 'standard data elements' consist of the basic pathologic features used for prognostication, while other factors related to prognosis or diagnosis are described in the 'conditional data elements.' In addition to standard data elements, all recommended issues are also presented. We expect that this standardized pathology report for breast cancer will improve diagnostic concordance and communication between pathologists and clinicians, as well as between pathologists inter-institutionally.

Standardized Pathology Report for Breast Cancer

Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of ‘standard data elements,’ ‘conditional data elements,’ and a biomarker report form. The ‘standard data elements’ consist of the basic pathologic features used for prognostication, while other factors related to prognosis or diagnosis are described in the ‘conditional data elements.’ In addition to standard data elements, all recommended issues are also presented. We expect that this standardized pathology report for breast cancer will improve diagnostic concordance and communication between pathologists and clinicians, as well as between pathologists inter-institutionally.

Defining radiologic complete response using a correlation of presurgical ultrasound and mammographic localization findings with pathological complete response following neoadjuvant chemotherapy in breast cancer

PURPOSE

Breast cancer affects a significant number of patients younger than 40 years in the Gulf and breast conservative treatment is highly preferred. Pathological complete response (pCR) following neoadjuvant chemotherapy is increasingly being observed with the new chemotherapy agents. Although MRI is more accurate in such evaluations, digital mammography and high-resolution ultrasound (US) which are less expensive may accurately predict pCR which is the focus of this study.

METHODS

A 6-year retrospective study of 93 breast cancer cases who had neoadjuvant chemotherapy and had presurgical radiological localization was carried out. Forty-five had US localization while 48 underwent mammographic localization when US failed to define any residual mass. Radiologic complete response (rCR) was defined as absence of mass with only postbiopsy clip overlying normal breast parenchyma pattern in US and in mammography (clip sign). Mass or abnormal parenchymal pattern was considered as residual tumor. The pathology reports of pCR or not with background changes were recorded.

RESULTS

Ultrasound localization correctly predicted 42 out of 43 pathologic masses with 98 % accuracy. Mammographic localization correctly predicted 40 out of 43 pCR with 93 % accuracy. The best responders were triple negative and HER2 positive hormone negative breast cancer.

CONCLUSION

The study defines radiologic complete response (rCR) as absence of a mass with the postbiopsy tissue marker overlying a normal-looking breast parenchyma in both ultrasound and mammographic evaluation. A correlation of 93 % was found with pCR. The few false negative cases were associated with overlying dense breast and possibly post treatment reaction. Allocation of a BI-RADS category for rCR is suggested.

Lactate concentration in breast cancer using advanced magnetic resonance spectroscopy

BACKGROUND

Precision medicine in breast cancer demands markers sensitive to early treatment response. Aerobic glycolysis (AG) upregulates lactate dehydrogenase A (LDH-A) with elevated lactate production; however, existing approaches for lactate quantification are either invasive or impractical clinically.

METHODS

Thirty female patients (age 39-78 years, 15 grade II and 15 grade III) with invasive ductal carcinoma were enrolled. Lactate concentration was quantified from freshly excised whole tumours with double quantum filtered (DQF) magnetic resonance spectroscopy (MRS), and Nottingham Prognostic Index (NPI), LDH-A and proliferative marker Ki-67 were assessed histologically.

RESULTS

There was a significantly higher lactate concentration (t = 2.2224, p = 0.0349) in grade III (7.7 ± 2.9 mM) than in grade II (5.5 ± 2.4 mM). Lactate concentration was correlated with NPI (ρ = 0.3618, p = 0.0495), but not with Ki-67 (ρ = 0.3041, p = 0.1023) or tumour size (r = 0.1716, p = 0.3645). Lactate concentration was negatively correlated with LDH-A (ρ = -0.3734, p = 0.0421).

CONCLUSION

Our results showed that lactate concentration in whole breast tumour from DQF MRS is sensitive to tumour grades and patient prognosis.

Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

Background

After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favorable prognosis. Among non-selected patients, pCR is, however, achieved in only 10–30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives.

Objective

To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml^− 1) and tumour volume, can be used for early prediction of pathologic response.

Methods

One hunred four women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3–6. The cell-loss metric was established at baseline (n = 104), 48 h after cycle 2 (n = 104) and prior to cycle 2 (n = 57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months later.

Results

Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdivided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48 h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11, 11, 23 and 46%) differed significantly (p = 0.01). In 80 patients with remaining tumour, tumour size was inversely related to the metric (p = 0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8 and 83.3%, compared to 40.5 and 88.7% 48 h after treatment 2.

Conclusion

A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

Trial registration

PROMIX (Clinical Trials.govNCT000957125).

Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

BACKGROUND

After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favorable prognosis. Among non-selected patients, pCR is, however, achieved in only 10-30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives.

OBJECTIVE

To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml^- 1) and tumour volume, can be used for early prediction of pathologic response.

METHODS

One hunred four women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3-6. The cell-loss metric was established at baseline (n = 104), 48 h after cycle 2 (n = 104) and prior to cycle 2 (n = 57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months later.

RESULTS

Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdivided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48 h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11, 11, 23 and 46%) differed significantly (p = 0.01). In 80 patients with remaining tumour, tumour size was inversely related to the metric (p = 0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8 and 83.3%, compared to 40.5 and 88.7% 48 h after treatment 2.

CONCLUSION

A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

TRIAL REGISTRATION

PROMIX (Clinical Trials.govNCT000957125).

The treatment option of progressive disease in breast cancer during neoadjuvant chemotherapy: a single-center experience

Patients' responses to breast cancer neoadjuvant chemotherapy (NACT) differ because of heterogeneous tumor characteristics. Reports about NACT progression are sporadic. Here we enrolled 1187 patients who received NACT in our cancer center between January 1, 2007, and December 31, 2016. We analyzed the characteristics and treatments of patients with progressive disease (PD) or non-PD or pathological complete response (pCR). In total, 45 (3.8%) patients had PD. PD patients were associated with a significantly worse disease-free survival (DFS) (hazard ratio (HR) = 3.77; 95% CI, 1.77 to 8.00; P =.001) and overall survival (OS) (HR = 3.85; 95% CI, 1.77 to 8.35; P =.001). For the PD patients, 28 (62.2%) patients received mastectomy immediately after PD, and 17 (37.8%) changed to chemotherapy. DFS and OS exhibited no significant differences between these two salvage therapies. After a change to second chemotherapy, 58.8% (10/17) patients had PD or SD. With the exception of tumor size, pretreatment T stage, and histology type, no other significant differences were noted between PD and pCR patients. Our results demonstrated that PD patients were associated with a significantly worse prognosis. Based on these results, we suggest to give the addition of trastuzumab to HER-2 positive patients instead of changing the chemotherapy regimen and proceeding to surgery instead of further chemotherapy once patients have PD during NACT. Given that some similar characteristics exist between PD and pCR patients, more studies to identify novel molecular markers to predict disease response to NACT should be performed.

Capecitabine + Epirubicin + Cyclophosphamide Combination Therapy (CEX Therapy) as Neoadjuvant Chemotherapy for HER-2-Negative Breast Cancer: A Retrospective, Single-Center Study

BACKGROUND

We modified and administered capecitabine + epirubicin + cyclophosphamide combination therapy (CEX) as neoadjuvant chemotherapy (NAC) for HER-2-negative breast cancer and retrospectively analyzed its effectiveness and tolerability at our center.

METHODS

The inclusion criteria were presence of breast cancer negative for HER-2 and positive lymph node metastasis, or negative lymph node metastasis when tumor diameter was 20 mm or greater without distant metastasis. Additional inclusion criteria were a performance status of 0 or 1, an EF >60%, and an age of 75 years or less. Clinical outcomes were evaluated after 4 courses of epirubicin 80 mg/m2, cyclophosphamide 500 mg/m2 (administered every 3 weeks), and capecitabine 1,500 mg/m2 (administered for 2 weeks and withdrawn for 1 week).

RESULTS

A clinical benefit was noted in all 18 patients who received CEX as neoadjuvant chemotherapy during the period from 2009 through 2013. The clinical response rate was 83.3% (15/18), and the clinical complete response rate was 50%. Aesthetic outcomes of breast-conserving surgery were positive in all patients. Among patients with satisfactory outcomes, 33.3% had a pathologic complete response (triple-negative: 6, luminal: 0) and 68.8% were n0 (triple-negative: 8, luminal: 3). All patients with a pathologic complete response are presently alive, free of recurrence, and currently undergoing follow-up. Adverse events were classified as grade 2 or lower in all patients.

CONCLUSIONS

CEX therapy administered as neoadjuvant chemotherapy could be useful for individualized treatment. In particular, this regimen was effective for triple-negative breast cancer.

GRP78 expression in peripheral blood mononuclear cells is a new predictive marker for the benefit of taxanes in breast cancer neoadjuvant treatment

BACKGROUND

Breast cancer treatment is tailored to the specific cancer subtype. Often, systemic treatment is given prior to surgery. Chemotherapy induces significant endoplasmic reticulum (ER) stress-mediated cell death and upregulation of 78-kDa glucose-regulated protein (GRP78). We hypothesized that chemotherapy induces ER stress not only in the tumor tissue but also in immune cells, which may affect the response to anti-cancer treatment.

METHODS

We determined the surface expression of GRP78 on 15 different peripheral blood mononuclear cell (PBMC) subpopulations in 20 breast cancer patients at three time points of the neoadjuvant treatment, i.e., at baseline, after anthracycline treatment, and after taxanes treatment. For this purpose, we performed flow cytometric analyses and analyzed the data using ANOVA and the Tukey test. Serum cytokine levels were also evaluated, and their levels were correlated with response to treatment using the t-test after log transformation and Mann-Whitney U Wilcoxon W test.

RESULTS

A significant increase in GRP78 expression in PBMCs was documented during the taxane phase, only in patients who achieved pathological complete response (pCR). GRP78-positive clones correlated with increased serum levels of interferon gamma (IFNγ).

CONCLUSIONS

The presence of GRP78-positive clones in certain PBMC subpopulations in pCR patients suggests a dynamic interaction between ER stress and immune responsiveness. The correlation of GRP78-positive clones with increased levels of IFNγ supports the idea that GRP78 expression in PBMCs might serve as a new predictive marker to identify the possible benefits of taxanes in the neoadjuvant setting.

Ki-67 response-guided preoperative chemotherapy for HER2-positive breast cancer: results of a randomised Phase 2 study

BACKGROUND

The effectiveness of a therapeutic strategy that switches chemotherapy, based on Ki-67 tumour expression after initial therapy, relative to that of standard chemotherapy, has not been evaluated.

METHODS

Patients were randomly assigned to the control arm or the Ki-67 response-guided arm (Ki-67 arm). Primary tumour biopsies were obtained before treatment, and after three once-weekly doses of paclitaxel and trastuzumab to assess the interim Ki-67 index. In the control arm, paclitaxel and trastuzumab were continued for a total of 12 doses, regardless of the interim Ki-67 index. In the Ki-67 arm, subsequent treatment was based on the interim Ki-67 index. Ki-67 early responder is defined as the absolute Ki-67 value that was <10%, and the percentage of Ki-67-positive tumour cells was reduced by >30% compared with before treatment. Early Ki-67 responders continued to receive the same treatment, while early Ki-67 non-responders were switched to epirubicin plus cyclophosphamide. The primary endpoint was the pathological complete response (pCR) rate.

RESULTS

A total of 237 patients were randomised. There was almost linear correlation between the Ki-67 reduction rate at interim assessment and the pCR rate. The pCR rate in Ki-67 early non-responders in the Ki-67 arm was inferior to that in the control arm (44.1%; 31.4-56.7; P = 0.025).

CONCLUSIONS

The standard chemotherapy protocol remains as the recommended strategy for patients with HER2-positive breast cancer.

CLINICAL TRIAL REGISTRATION

Clinical Trial Registration: UMIN-CTR as UMIN000007074.

Neoadjuvant or adjuvant chemotherapy in early breast cancer?

INTRODUCTION

The administration of chemotherapy before (neoadjuvant), rather than after surgery (adjuvant) in early breast cancer has been considered an optional strategy for patients with operable breast cancer. We reviewed this concept considering recent results in the field.

AREAS COVERED

Herein, the authors cover neoadjuvant chemotherapy with or without biologics in triple-negative and HER2-positive operable breast cancer with a focus on rates of complete pathological remission (pCR) in the breast and axilla. The impact of the CREATE X and KATERINE randomized clinical trials of post-surgical treatments in patients with residual disease after neoadjuvant chemotherapy is also discussed.

EXPERT OPINION

The CREATE X and KATERINE clinical trials show for the first time and with methodological strengths that, in TNBC and HER2-positive breast cancer patients, post-surgical capecitabine and T-DM1, respectively, can improve prognosis when the disease persists after neoadjuvant chemotherapy. Therefore, the role of pCR as a treatment endpoint and a guide for further treatment decisions is now demonstrated. On account of these results, neoadjuvant chemotherapy becomes not an option, but rather the preferred treatment strategy for more and more TNBC and HER2-positive breast cancer patients in clinical practice.

Prediction model of the response to neoadjuvant chemotherapy in breast cancers by a Naive Bayes algorithm

BACKGROUND AND OBJECTIVE

Chemotherapy is useful to many breast cancer patients, however, it is not therapeutic for some patients. Pathologic complete response (pCR) is an indicator to good response in Neoadjuvant chemotherapy (NAC). In this study, we aimed to develop a way to predict pCR before NAC.

METHODS

We retrospectively collected 287 stage II-III breast cancer cases either to a training set (N = 197) or to a test set (N = 90). Fourteen candidate genes were selected from four public microarray data sets. A prediction model was built, by using these fourteen candidate genes and three reference genes expression which were tested by TaqMan probe-based quantitative polymerase chain reaction, after selecting a better algorithm.

RESULTS

The Naive Bayes algorithm had a relatively higher predictive value, compared with random forest, support vector machine (SVM), and k-nearest neighbor (knn) algorithms (P < 0.05). This 17-gene prediction model showed a high positive correlation with pCR (odds ratio, 8.914, 95% confidence interval, 4.430-17.934, P < 0.001). By using this model, the enrolled patients were classified into sensitive (SE) and insensitive (INS) groups. The pCR rates between the SE and INS groups were highly different (42.3% vs.7.6%, P < 0.001). The sensitivity and specificity of this prediction model were 84.5% and 62.0%.

CONCLUSIONS

Instead of whole transcriptome-based technologies, panel gene expression with tens of essential genes implemented in a machine learning model has predictive potential for chemosensitivity in breast cancers.

A randomized study comparing docetaxel/cyclophosphamide (TC), 5-fluorouracil/epirubicin/cyclophosphamide (FEC) followed by TC, and TC followed by FEC for patients with hormone receptor-positive HER2-negative primary breast cancer

Purpose

Our primary objective was to determine the benefit/risk of anthracycline-free regimens by comparing docetaxel + cyclophosphamide (TC) alone, fluorouracil + epirubicin + cyclophosphamide (FEC) followed by TC, or TC followed by FEC as a primary treatment for patients with HR-positive, HER2-negative BC.

Methods

We randomized patients with stage I–III HR-positive HER2-negative, operable BC to receive either six cycles of TC (TC6), three cycles of FEC followed by three cycles of TC (FEC-TC), or three cycles of TC followed by three cycles of FEC (TC-FEC). The primary endpoint was the pathological response. Secondary endpoints included clinical response, type of surgical procedure, recurrence, death, and adverse events (by NCI-Common Terminology Criteria for Adverse Events v.3.0). We conducted all statistical analyses using SAS Version 9.2.

Results

We enrolled 195 patients and analyzed data from 193 as the intention-to-treat population. Pathological complete response rates were numerically higher in the TC6 group than in the other groups (p = 0.321). The breast conservation rate was significantly higher in the TC6 group (73%) than in the other groups (FEC-TC 51%, TC-FEC 45%, p = 0.007). Adverse events with grade > 3 were not common in the treatment groups (p = 0.569). The overall and distant disease-free survivals were similar among the groups with median follow-up of 5.80 years.

Conclusions

Despite similar long-term efficacy and safety profile, the higher breast conservation rate in the TC6 group suggests that preoperative chemotherapy without an anthracycline may benefit patients with HR-positive HER2-negative BC.

Trial registration

UMIN000003283 https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000003873.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05590-w) contains supplementary material, which is available to authorized users.

Antitumor Efficacy of Focused Ultrasound-MFL Nanoparticles Combination Therapy in Mouse Breast Cancer Xenografts

High doses of chemotherapy agents can cause adverse effects. To address this issue, drug-loaded vesicles with minimum drug loss, guided by an external element for precise delivery, are desired. Combinational therapy of both a focused ultrasound-induced drug delivery method and membrane fusogenic liposomes (MFLs) as drug delivery vehicles can satisfy such premises. In this study, we confirmed that the use of a small quantity of docetaxel-loaded membrane fusogenic liposomes (DTX-MFL) with focused ultrasound can induce better antitumor response in a xenograft mouse model compared to conventional docetaxel monotherapy and DTX-MFL only.

Pathologic Response After Weekly Paclitaxel versus Docetaxel in Operable Breast Cancer

Introduction

Weekly paclitaxel (Ptx) and q3w docetaxel (Dtx) are equivalent in adjuvant breast cancer treatment. Weekly Ptx is better tolerated than q3w Dtx and became the first choice in daily practice, even preoperatively.

Methods

To compare the efficacy and safety of the two regimens, a retrospective analysis was performed in breast cancer patients (pts) referred for neoadjuvant, sequential, taxane-containing chemotherapy to the Institute of Oncology and Oncofort Clinic, Bucharest, between 2008 and 2017.

Results

Forty-seven cases were eligible, median age was 56 years (34–73 years), mainly stage IIIA–B (53.2%, 25 pts) and ductal invasive (70.2%, 33 pts) of which 24 pts (51%) received q3w Dtx and 23 pts (48.9%) weekly Ptx. The histological response rates were 62.5% (15 pts) and 73.7% (17 pts) (p=0.47), average dose-intensity was 87.7% and 96.7% (p=0.002) and grade III–IV toxicity rate was 12.5% and 13% (p=0.64), respectively. Pathologic response was correlated with immunophenotype, PgR expression, tumor size and backbone chemotherapy (p<0.05).

Discussion

Our study showed an improved efficacy of taxane’s weekly administration, probably due to a better tolerance and a lower rate of dose-impairing toxicities.

MicroRNA-423 Drug Resistance and Proliferation of Breast Cancer Cells by Targeting ZFP36

BACKGROUND/AIMS

The effects of microRNA-423 on proliferation and drug resistance of breast cancer cells were explored, the downstream target genes of miR-423 and the targeted regulatory relationship between them were studied.

METHODS

RT-qPCR was used to detect the expression of miR-423 in breast cancer tissues and cell lines, and the transfection efficiency of miR-423 inhibitory vector miR-423-inhibitor was constructed and verified. CCK-8 and colony formation assays were used to examine the effect of miR-423 on tumor cell proliferation. Target gene prediction and screening and luciferase reporter assay were used to verify downstream target genes of miR-432. The mRNA and protein expression of miR-423target gene ZFP36 was detected by RT-qPCR and Western blotting.

RESULTS

The expression of miR-423 was significantly higher than that in normal tissues. Compared to the non-malignant mammary epithelial cell line MCF-10A, the expression of miR-423 was significantly raised in MCR-7 and MCF-7/ADR cells. ZFP36 was a downstream target gene of miR-423 and negatively correlated with the expression of miR-423 in breast cancer. The knockdown of miR-423 can significantly enhance the cytotoxicity of the drug, increase the apoptotic rate of MCF-7/ADR cells. miR-423 was capable of activating the Wnt/β-catenin signaling pathway leading to chemoresistance and proliferation, whereas overexpression of ZFP36 reduced drug resistance and proliferation.

CONCLUSION

miR-423 acted as an oncogene to promote tumor cell proliferation and migration. ZFP36 was a downstream target gene of miR-423, and miR-423 inhibited the expression of ZFP36 via Wnt/β-catenin signaling pathway of breast cancer cells.

CAIX is a predictor of pathological complete response and is associated with higher survival in locally advanced breast cancer submitted to neoadjuvant chemotherapy

BACKGROUND

Locally advanced breast cancer often undergoes neoadjuvant chemotherapy (NAC), which allows in vivo evaluation of the therapeutic response. The determination of the pathological complete response (pCR) is one way to evaluate the response to neoadjuvant chemotherapy. However, the rate of pCR differs significantly between molecular subtypes and the cause is not yet determined. Recently, the metabolic reprogramming of cancer cells and its implications for tumor growth and dissemination has gained increasing prominence and could contribute to a better understanding of NAC. Thus, this study proposed to evaluate the expression of metabolism-related proteins and its association with pCR and survival rates.

METHODS

The expression of monocarboxylate transporters 1 and 4 (MCT1 and MCT4, respectively), cluster of differentiation 147 (CD147), glucose transporter-1 (GLUT1) and carbonic anhydrase IX (CAIX) was analyzed in 196 locally advanced breast cancer samples prior to NAC. The results were associated with clinical-pathological characteristics, occurrence of pCR, disease-free survival (DFS), disease-specific survival (DSS) and overall survival (OS).

RESULTS

The occurrence of pCR was higher in the group of patients whith tumors expressing GLUT1 and CAIX than in the group without expression (27.8% versus 13.1%, p = 0.030 and 46.2% versus 13.5%, p = 0.007, respectively). Together with regional lymph nodes staging and mitotic staging, CAIX expression was considered an independent predictor of pCR. In addition, CAIX expression was associated with DFS and DSS (p = 0.005 and p = 0.012, respectively).

CONCLUSIONS

CAIX expression was a predictor of pCR and was associated with higher DFS and DSS in locally advanced breast cancer patients subjected to NAC.

Changes in Apparent Diffusion Coefficient as Surrogate Marker for Changes in Ki-67 Index Due to Neoadjuvant Chemotherapy in Patients with Invasive Breast Cancer

RATIONALE AND OBJECTIVES

To evaluate possible correlation between changes in apparent diffusion coefficient (ADC) and Ki-67 index as a result of neoadjuvant chemotherapy (NAC) in patients with invasive breast cancer.

METHODS AND MATERIALS

Between February 2016 and October 2017, 87 patients with breast cancer underwent diffusion-weighted magnetic resonance imaging (b = 0 and 800 sec/mm²) before and after NAC. ADC and tumor diameter before and after NAC were compared to the Ki-67 index determined from biopsy or surgical specimens.

RESULTS

Ki-67 index did not correlate significantly with ADC before NAC (p = 0.862) or afterwards (p = 0.292), nor did it correlate with tumor diameter before (p = 0.545) or afterwards (p = 0.478). However, change in ADC as a result of NAC correlated inversely with change in Ki-67 index (r = -0.326, p = 0.002). The percentage change in Ki-67 index did not correlate with the percentage change in ADC (p = 0.404). Similarly, the change in Ki-67 index or percentage change in that index did not correlate with the change in tumor diameter (p = 0.075) or percentage change in tumor diameter (p = 0.233).

CONCLUSION

Comparison of pre- and post-NAC ADC can be used to estimate the change in Ki-67 index in patients with invasive breast cancer.

Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray

: Breast cancer (BRCA) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers expressed during estradiol and tamoxifen treatment of BRCA. The microarray dataset of E-MTAB-4975 from Array Express database was downloaded, and the differential expressed genes (DEGs) between estradiol-treated BRCA sample and tamoxifen-treated BRCA sample were identified by limma package. The pathway and gene ontology (GO) enrichment analysis, construction of protein-protein interaction (PPI) network, module analysis, construction of target genes-miRNA interaction network and target genes-transcription factor (TF) interaction network were performed using bioinformatics tools. The expression, prognostic values, and mutation of hub genes were validated by SurvExpress database, cBioPortal, and human protein atlas (HPA) database. A total of 856 genes (421 up-regulated genes and 435 down-regulated genes) were identified in T47D (overexpressing Split Ends (SPEN) + estradiol) samples compared to T47D (overexpressing Split Ends (SPEN) + tamoxifen) samples. Pathway and GO enrichment analysis revealed that the DEGs were mainly enriched in response to lysine degradation II (pipecolate pathway), cholesterol biosynthesis pathway, cell cycle pathway, and response to cytokine pathway. DEGs (MCM2, TCF4, OLR1, HSPA5, MAP1LC3B, SQSTM1, NEU1, HIST1H1B, RAD51, RFC3, MCM10, ISG15, TNFRSF10B, GBP2, IGFBP5, SOD2, DHF and MT1H) , which were significantly up- and down-regulated in estradiol and tamoxifen-treated BRCA samples, were selected as hub genes according to the results of protein-protein interaction (PPI) network, module analysis, target genes-miRNA interaction network and target genes-TF interaction network analysis. The SurvExpress database, cBioPortal, and Human Protein Atlas (HPA) database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. A comprehensive bioinformatics analysis was performed, and potential therapeutic applications of estradiol and tamoxifen were predicted in BRCA samples. The data may unravel the future molecular mechanisms of BRCA.

Relationship between 18-FDG-PET/CT and Clinicopathological Features and Pathological Responses in Patients with Locally Advanced Breast Cancers

Objective

We investigated the relationship between the maximum standardized uptake value (SUVmax) of whole-body positron emission tomography/computed tomography (PET/CT) performed before treatment and the demographical and histopathological features in locally advanced breast cancer (LABC), as well as the role of PET/CT in the evaluation of pathological complete response (pCR) after neoadjuvant chemotherapy (NAC).

Materials and Methods

Fifty-one LABC patients who received NAC in our center between 2011 and 2015 were retrospectively analyzed. Basal PET/CT was performed in all the patients before NAC. The SUV_max levels and demographical and histopathological results were compared. The relationship between the SUV_max values after NAC and pathological responses were evaluated.

Results

The mean age of the patients was 49 (32-69) years. PET/CT performed after NAC showed complete response in 20 patients (39.2%), partial response in 28 patients (54.9%), stable disease in 2 patients (3.9%), and progressive disease in 1 patient (2%). There was no significant difference between the mean SUV_max values of the patients according to age (>50 and ≤50 years), menopausal status, tumor localization, clinical stage, and grade. The mean SUV_max value was higher in the triple-negative group than those in the HER2 positive and luminal groups. There was a significant difference in the SUV_max values between the group that achieved pCR after NAC and the group that could not achieve pCR (SUV_max value for breast 2.92 vs. 0.30; p=0.01; SUV_max value for axilla 1.5 vs. 0.0, p=0.02).

Conclusion

The SUV_max values are independent of demographical features. There was a significant relationship between the pCR and SUV_max values after NAC. PET/CT could be useful in the evaluation of patients to predict the biological characteristics of tumors.