Management of locally advanced breast cancer-perspectives and future directions

Value of CDR1-AS as a predictive and prognostic biomarker for patients with breast cancer receiving neoadjuvant chemotherapy in a prospective Chinese cohort

BACKGROUND

Neoadjuvant chemotherapy (NAC) is an effective treatment for locally advanced breast cancer (BC). However, there are no effective biomarkers for evaluating its efficacy. CDR1-AS, well known for its important role in tumorigenesis, is a famous circular RNA involved in the chemosensitivity of cancers other than BC. However, the predictive role of CDR1-AS in the efficacy and prognosis of NAC for BC has not been fully elucidated. We herein aimed to clarify this role.

METHODS

The present study included patients treated with paclitaxel-cisplatin-based NAC. The expression of CDR1-AS was detected by real-time quantitative reverse transcription polymerase chain reaction testing. The predictive value of CDR1-AS expression was examined in pathological complete response (pCR) after NAC using logistic regression analysis. The relationship between CDR1-AS expression and survival was demonstrated using the Kaplan-Meier method, and tested by log-rank test and Cox proportional hazards regression model.

RESULTS

The present study enrolled 106 patients with BC. Multivariate logistic regression analysis revealed that CDR1-AS expression was an independent predictive factor for pCR (odds ratio [OR] = 0.244; 95% confidence interval [CI] 0.081-0.732; p = 0.012). Furthermore, pCR benefits with low CDR1-AS expression were observed across all subgroups. The Kaplan-Meier curves and log-rank test suggested that the CDR1-AS high-expression group showed significantly better disease-free survival (DFS; log-rank p = 0.022) and relapse-free survival (RFS; log-rank p = 0.012) than the CDR1-AS low-expression group. Multivariate analysis revealed that CDR1-AS expression was an independent prognostic factor for DFS (adjusted HR = 0.177; 95% CI 0.034-0.928, p = 0.041), RFS (adjusted HR = 0.061; 95% CI 0.006-0.643, p = 0.020), and distant disease-free survival (adjusted HR = 0.061; 95% CI 0.006-0.972, p = 0.047).

CONCLUSIONS

CDR1-AS may be a potential novel predictive biomarker of pCR and survival benefit in patients with locally advanced BC receiving NAC. This may help identify specific chemosensitive individuals and build personalized treatment strategies.

ER-Targeted PET for Initial Staging and Suspected Recurrence in ER-Positive Breast Cancer

Importance

There are insufficient data comparing 16α-18F-fluoro-17β-estradiol (FES) positron emission tomography (PET) computed tomography (CT) with standard-of-care imaging (SOC) for staging locally advanced breast cancer (LABC) or evaluating suspected recurrence.

Objective

To determine the detection rate of FES PET/CT and SOC for distant metastases in patients with estrogen receptor (ER)-positive LABC and recurrences in patients with ER-positive BC and suspected recurrence.

Design, Setting, and Participants

This diagnostic study was conducted as a single-center phase 2 trial, from January 2021 to September 2023. The study design provided 80% power to find a 20% detection rate difference. Participants included patients with ER-positive LABC (cohort 1) or suspected recurrence (cohort 2). Data were analyzed from September 2023 to February 2024.

Exposure

Participants underwent both SOC imaging and experimental FES PET/CT. When there were suspicious lesions on imaging, 1 was biopsied for histopathological reference standard to confirm presence (true positive) or absence (false positive) of malignant neoplasm.

Main Outcomes and Measures

The outcome of interest was the detection rate of FES PET CT vs SOC for distant metastases and recurrences.

Results

A total of 124 patients were accrued, with 62 in cohort 1 (median [IQR] age, 52 [32-84] years) and 62 in cohort 2 (median [IQR] age, 66 [30-93] years). In cohort 1, of 14 true-positive findings, SOC imaging detected 12 and FES detected 11 (P > .99). In cohort 2, of 23 true-positive findings, SOC detected 16 and FES detected 18 (P = .77). In 30 patients with lobular histology, of 11 true-positive findings, SOC detected 5 and FES detected 9 (P = .29). There were 6 false-positive findings on SOC and 1 false-positive finding on FES PET/CT (P = .13).

Conclusions and Relevance

In this diagnostic study with pathological findings as the reference standard, no difference was found between FES PET/CT and current SOC imaging for detecting distant metastases in patients with ER-positive LABC or recurrences in patients with ER-positive tumors and suspected recurrence. FES PET/CT could be considered for both clinical indications, which are not part of current Appropriate Use Criteria for FES PET. The findings regarding FES PET/CT in patients with lobular tumors, and for lower false positives than current SOC imaging, warrant further investigation.

Diagnosis and treatment status of inoperable locally advanced breast cancer and the application value of inorganic nanomaterials

Locally advanced breast cancer (LABC) is a heterogeneous group of breast cancer that accounts for 10-30% of breast cancer cases. Despite the ongoing development of current treatment methods, LABC remains a severe and complex public health concern around the world, thus prompting the urgent requirement for innovative diagnosis and treatment strategies. The primary treatment challenges are inoperable clinical status and ineffective local control methods. With the rapid advancement of nanotechnology, inorganic nanoparticles (INPs) exhibit a potential application prospect in diagnosing and treating breast cancer. Due to the unique inherent characteristics of INPs, different functions can be performed via appropriate modifications and constructions, thus making them suitable for different imaging technology strategies and treatment schemes. INPs can improve the efficacy of conventional local radiotherapy treatment. In the face of inoperable LABC, INPs have proposed new local therapeutic methods and fostered the evolution of novel strategies such as photothermal and photodynamic therapy, magnetothermal therapy, sonodynamic therapy, and multifunctional inorganic nanoplatform. This article reviews the advances of INPs in local accurate imaging and breast cancer treatment and offers insights to overcome the existing clinical difficulties in LABC management.

Multidisciplinary and Tailored Treatment of Locally Advanced Breast Cancer in Progression during Neoadjuvant Chemotherapy: Case Report

Locally advanced breast cancer (LABC) is a complex disease that requires a multidisciplinary approach. Neoadjuvant chemotherapy (NAC) is usually performed in order to achieve loco-regional radical resection; although its importance in the multidisciplinary approach to LABC is well recognized, a small number of patients show Progressive Disease (PD). No standard salvage treatment (ST) has been defined and different strategies can be adopted, such as second-line systemic therapies, radiation therapy, and surgery. Herein, a case of LABC in PD during NAC is reported with a literature review, with the aim of highlighting the importance of a tailored multidisciplinary treatment for each patient.

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning

Objective

Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT).

Materials and methods

Several deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes.

Results

Amongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network.

Conclusion

Deep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism.

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies

BACKGROUND

Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) has demonstrated a strong correlation to improved survival in breast cancer (BC) patients. However, pCR rates to NAC are less than 30%, depending on the BC subtype. Early prediction of NAC response would facilitate therapeutic modifications for individual patients, potentially improving overall treatment outcomes and patient survival.

PURPOSE

This study, for the first time, proposes a hierarchical self-attention-guided deep learning framework to predict NAC response in breast cancer patients using digital histopathological images of pre-treatment biopsy specimens.

METHODS

Digitized hematoxylin and eosin-stained slides of BC core needle biopsies were obtained from 207 patients treated with NAC, followed by surgery. The response to NAC for each patient was determined using the standard clinical and pathological criteria after surgery. The digital pathology images were processed through the proposed hierarchical framework consisting of patch-level and tumor-level processing modules followed by a patient-level response prediction component. A combination of convolutional layers and transformer self-attention blocks were utilized in the patch-level processing architecture to generate optimized feature maps. The feature maps were analyzed through two vision transformer architectures adapted for the tumor-level processing and the patient-level response prediction components. The feature map sequences for these transformer architectures were defined based on the patch positions within the tumor beds and the bed positions within the biopsy slide, respectively. A five-fold cross-validation at the patient level was applied on the training set (144 patients with 9430 annotated tumor beds and 1,559,784 patches) to train the models and optimize the hyperparameters. An unseen independent test set (63 patients with 3574 annotated tumor beds and 173,637 patches) was used to evaluate the framework.

RESULTS

The obtained results on the test set showed an AUC of 0.89 and an F1-score of 90% for predicting pCR to NAC a priori by the proposed hierarchical framework. Similar frameworks with the patch-level, patch-level + tumor-level, and patch-level + patient-level processing components resulted in AUCs of 0.79, 0.81, and 0.84 and F1-scores of 86%, 87%, and 89%, respectively.

CONCLUSIONS

The results demonstrate a high potential of the proposed hierarchical deep-learning methodology for analyzing digital pathology images of pre-treatment tumor biopsies to predict the pathological response of breast cancer to NAC.

The management of locally advanced, ulcerated breast cancer in a menopausal woman: a case report

Introduction and importance

This case report presents the clinical details of a 46-year-old postmenopausal woman who was diagnosed with a locally advanced, ulcerated, hormone receptor-positive, HER2-negative stage 2B lobular carcinoma of the breast. The complexity of the case necessitated a multidisciplinary, personalized approach.

Case presentation

The patient, a postmenopausal woman, presented with locally advanced lobular carcinoma of the breast. The tumor was of significant size and exhibited ulceration. Given the hormone receptor-positive status of the tumor, a comprehensive treatment plan was formulated, taking into account the patient's overall health and potential tolerance to treatment. Surgical removal of the tumor was performed, followed by adjuvant therapy with aromatase inhibitors.

Clinical discussion

The complexity of this case highlights the importance of a personalized and patient-centered strategy in managing breast cancer. The patient's menopausal status, tumor characteristics, and potential tolerance to treatment were crucial factors that influenced the treatment plan. The successful outcome of the treatment and the patient's ability to tolerate the therapy underscores the significance of individualized treatment planning.

Conclusion

This case report emphasizes the necessity for a comprehensive and patient-centered approach to managing complex cases of breast cancer. The findings support the development of personalized therapeutic strategies aimed at improving patient outcomes and quality of life. The successful treatment of the locally advanced, ulcerated lobular carcinoma of the breast in this postmenopausal patient further highlights the importance of considering individual factors and tailoring treatment plans accordingly.

An in-silico investigation and network pharmacology based approach to explore the anti-breast-cancer potential of Tecteria coadunata (Wall.) C. Chr

Uncontrolled cell proliferation is a common definition of cancer. After lung carcinoma, breast neoplasm is the second-most prevalent kind of cancer. The majority of breast cancer cells and healthy breast cells both have receptors for circulating oestrogen and progesterone. In order to promote the development and division of cancer cells, oestrogen and progesterone bind to the receptors and may collaborate with growth factors (such as oncogenes and mutant tumour suppressor genes). As per the literature, Tecteria coadunata (Wall.) C. Chr. has anticancer, antioxidant and anti-inflammatory potential. After the hydroalcoholic extraction of this rhizome, total of 200 phytochemicals were retrieved from HR-LCMS analysis. In this current study, Network pharmacology was carried out to explore the rationale of Tecteria coadunata (Wall.) C. Chr. by using different database using Cytoscape software. The network depicted the interaction of Bioactives with their targets and their association with several disease, especially breast cancer. Tecteria coadunata (Wall.) C. Chr. has offered new relationship with variety of genes and its applications in different types of breast cancers. Further Gene Ontology was carried out and it showed key targets were TP53, BRCA2, PGR and CHEK 2. Further Signalling pathways were also enriched. Flex-X software was used for molecular docking studies, and it verified that Dopaxanthin, Dantrolene and Orotidin shows the highest binding affinities with key targets. Additionally, Pharmacokinetic analysis revealed that all top three lead compounds which follows the Lipinski Rule (Rule of three) without interrupting the conditions of bioavailability with minimal toxicity.Communicated by Ramaswamy H. Sarma.

Impact of 18F-Labeled Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography Versus Conventional Staging in Patients With Locally Advanced Breast Cancer

PURPOSE

Patients with locally advanced breast cancer (LABC) typically undergo staging tests at presentation. If staging does not detect metastases, treatment consists of curative intent combined modality therapy (neoadjuvant chemotherapy, surgery, and regional radiation). Positron emission tomography-computed tomography (PET-CT) may detect more asymptomatic distant metastases, but the evidence is based on uncontrolled studies.

METHODS

For inclusion, patients had histological evidence of invasive ductal carcinoma of the breast and TNM stage III or IIb (T3N0, but not T2N1). Consenting patients from six regional cancer centers in Ontario were randomly assigned to 18F-labeled fluorodeoxyglucose PET-CT or conventional staging (bone scan, CT of the chest/abdomen and pelvis). The primary end point was upstaging to stage IV. A key secondary outcome was receiving curative intent combined modality therapy (ClinicalTrials.gov identifier: NCT02751710).

RESULTS

Between December 2016 and April 2022, 184 patients were randomly assigned to whole-body PET-CT and 185 patients to conventional staging. Forty-three (23%) PET-CT patients were upstaged to stage IV compared with 21 (11%) conventional staged patients (absolute difference, 12.3% [95% CI, 3.9 to 19.9]; P = .002). Consequently, treatment was changed in 35 (81.3%) of 43 upstaged PET-CT patients and 20 (95.2%) of the 21 upstaged conventional patients. Subsequently, 149 (81%) patients in the PET-CT group received combined modality treatment versus 165 (89.2%) patients in the conventional staging group (absolute difference, 8.2% [95% CI, 0.1 to 15.4]; P = .03).

CONCLUSION

In patients with LABC, PET-CT detected more distant metastases than conventional staging, and fewer PET-CT patients received combined modality therapy. Our randomized trial demonstrates the utility of the PET-CT staging strategy.

Radiomic signatures based on pretreatment 18F-FDG PET/CT, combined with clinicopathological characteristics, as early prognostic biomarkers among patients with invasive breast cancer

Purpose

The aim of this study was to investigate the predictive role of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the prognostic risk stratification of patients with invasive breast cancer (IBC). To achieve this, we developed a clinicopathologic-radiomic-based model (C-R model) and established a nomogram that could be utilized in clinical practice.

Methods

We retrospectively enrolled a total of 91 patients who underwent preoperative 18F-FDG PET/CT and randomly divided them into training (n=63) and testing cohorts (n=28). Radiomic signatures (RSs) were identified using the least absolute shrinkage and selection operator (LASSO) regression algorithm and used to compute the radiomic score (Rad-score). Patients were assigned to high- and low-risk groups based on the optimal cut-off value of the receiver operating characteristic (ROC) curve analysis for both Rad-score and clinicopathological risk factors. Univariate and multivariate Cox regression analyses were performed to determine the association between these variables and progression-free survival (PFS) or overall survival (OS). We then plotted a nomogram integrating all these factors to validate the predictive performance of survival status.

Results

The Rad-score, age, clinical M stage, and minimum standardized uptake value (SUVmin) were identified as independent prognostic factors for predicting PFS, while only Rad-score, age, and clinical M stage were found to be prognostic factors for OS in the training cohort. In the testing cohort, the C-R model showed superior performance compared to single clinical or radiomic models. The concordance index (C-index) values for the C-R model, clinical model, and radiomic model were 0.816, 0.772, and 0.647 for predicting PFS, and 0.882, 0.824, and 0.754 for OS, respectively. Furthermore, decision curve analysis (DCA) and calibration curves demonstrated that the C-R model had a good ability for both clinical net benefit and application.

Conclusion

The combination of clinicopathological risks and baseline PET/CT-derived Rad-score could be used to evaluate the prognosis in patients with IBC. The predictive nomogram based on the C-R model further enhanced individualized estimation and allowed for more accurate prediction of patient outcomes.

18F-FDG PET-Derived Volume-Based Parameters to Predict Disease-Free Survival in Patients with Grade III Breast Cancer of Different Molecular Subtypes Candidates to Neoadjuvant Chemotherapy

We investigated whether baseline [¹⁸F] Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)-derived semiquantitative parameters could predict disease-free survival (DFS) in patients with grade III breast cancer (BC) of different molecular subtypes candidate to neoadjuvant chemotherapy (NAC). For each ¹⁸F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used to determine the capability to predict DFS and find the optimal threshold for each parameter. Ninety-five grade III breast cancer patients with different molecular types were retrieved from the databases of the University Hospital of Padua and the University Hospital of Ferrara (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In luminal B patients, WB_MTV (AUC: 0.75; best cut-off: WB_MTV > 195.33; SS: 55.56%, SP: 100%; p = 0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG > 1066.21; SS: 55.56%, SP: 100%; p = 0.05) were the best predictors of DFS. In luminal B-HER2 patients, WB_SUVmax was the only predictor of DFS (AUC: 0.857; best cut-off: WB_SUVmax > 13.12; SS: 100%; SP: 71.43%; p < 0.001). No parameter significantly affected the prediction of DFS in patients with grade III triple-negative BC. Volume-based parameters, extracted from baseline ¹⁸F-FDG PET, seem promising in predicting recurrence in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC.

Fungating and Ulcerating Breast Cancer: Wound Closure Algorithm, Complications, and Survival Trends

Fungating breast cancer severely affects patients' daily lives, and patient management poses major oncology challenges. To present 10-year outcomes of unique tumor presentation, suggesting a focused algorithm for surgical management and providing deep analysis for factors affecting survival and surgical outcomes. Eighty-two patients with fungating breast cancer were enrolled in the period from January 2010 to February 2020 in the Mansoura University Oncology Center database. Epidemiological and pathological characteristics, risk factors, different surgical treatment techniques, and surgical and oncological outcomes were reviewed. Preoperative systemic therapy was used in 41 patients, with the majority (77.8%) showing progressive response. Mastectomy was performed in 81 (98.8%) patients, with primary wound closure in 71 (86.6%), and wide local excision in a single patient (1.2%). Different reconstructive techniques in non-primary closure operations were used. Complications were reported in 33 (40.7%) patients, of which 16 (48.5%) were of Clavien-Dindo grade II category. Loco-regional recurrence occurred in 20.7% of patients. The mortality rate during follow-up was 31.7% (n = 26). Estimated mean overall survival (with 95% CI) was 55.96 (41.98-69.9) months; estimated mean loco-regional recurrence-free survival (with 95% CI) was 38.01 (24.6-51.4) months. Surgery is a cornerstone fungating breast cancer treatment option, but at the expense of high morbidity. Sophisticated reconstructive procedures may be indicated for wound closure. A suggested algorithm based on the center's experience of wound management in difficult mastectomy cases is displayed.

The Role of Radiotherapy for Patients with Unresectable Locally Advanced Breast Cancer following Neoadjuvant Systemic Therapy

Background

For locally advanced breast cancer (LABC) patients who remained unresectable after neoadjuvant systemic therapy (NST), radiotherapy (RT) is considered as an approach for tumor downstaging. In this study, we attempted to discuss the value of RT for patients with unresectable or progressive disease in the breast and/or regional nodes following NST.

Methods

Between January 2013 and November 2020, the data for 71 patients with chemo-refractory LABC or de novo bone-only metastasis stage IV BC who received locoregional RT with or without surgical resection were retrospectively analyzed. Factors associated with tumor complete response (CR) were recognized using logistic regression. Locoregional progression-free survival (LRPFS) and progression-free survival (PFS) were calculated using the Kaplan-Meier method. The Cox regression model was applied to recognize the recurrence risk factors.

Results

After RT, 11 patients (15.5%) achieved total cCR. Triple-negative subtype (TNBC) was associated with a lower total cCR rate compared with other subtypes (p = 0.033). 26 patients proceeded to surgery, and the operability rate was 36.6%. 1-year LRPFS and PFS were 79.0% and 58.0%, respectively, for the entire cohort. Surgical cases had an improved 1-year LRPFS (p = 0.015), but not 1-year PFS (p = 0.057), compared with definitive RT cases. Non-any cCR was the most prominent predictor of a shorter LRPFS (p < 0.001) and PFS (p = 0.002) in the multivariate analysis. Higher TNM stage showed a trend toward a shorter LRPFS time (p = 0.058), and TNBC (p = 0.061) showed a trend toward a shorter PFS interval.

Conclusions

This study demonstrated that RT was an effective tumor downstaging option for chemo-refractory LABC. For patients with favorable tumor regression, surgery following RT might bring survival benefits.

Palliative Radiotherapy for Symptomatic Locally Advanced Breast Cancer

Objective: Women with locally advanced breast cancer (LABC) or inoperable local recurrence often suffer from a significantly reduced quality of life (QOL) due to local tumor-associated pain, bleeding, exulceration, or malodorous discharge. We aimed to further investigate the benefit of radiotherapy (RT) for symptom relief while weighing the side-effects. Materials and methods: Patients who received symptom-oriented RT for palliative therapy of their LABC or local recurrence in the Department of Radiation Oncology at Heidelberg University Hospital between 2012 and 2021 were recorded. Clinical, pathological, and therapeutic data were collected and the oncological and symptomatic responses as well as therapy-associated toxicities were analyzed. Results: We retrospectively identified 26 consecutive women who received palliative RT with a median total dose of 39 Gy or single dose of 3 Gy in 13 fractions due to (impending) exulceration, pain, local hemorrhage, and/or vascular or plexus compression. With a median follow-up of 6.5 months after initiation of RT, overall survival at 6 and 12 months was 60.0% and 31.7%, and local control was 75.0% and 47.6%, respectively. Radiation had to be discontinued in 4 patients due to oncological clinical deterioration or death. When completed as initially planned, symptom improvement was achieved in 95% and WHO level reduction of analgesics in 28.6% of patients. In 36% (16%) of patients, local RT had already been indicated >3 months (>6 months) before the actual start of RT, but was delayed or not initiated among others in favor of drug alternatives or systemic therapies. RT-associated toxicities included only low-grade side-effects (CTCAE I°-II°) with predominantly skin erythema and fatigue even in the context of re-RT. Conclusion: Palliative RT in symptomatic LABC or locoregional recurrence is an effective treatment option for controlling local symptoms with only mild toxicity. It may thus improve QOL and should be considered early in palliative patient care management.

The Value of Semiquantitative Parameters Derived from 18F-FDG PET/CT for Predicting Response to Neoadjuvant Chemotherapy in a Cohort of Patients with Different Molecular Subtypes of Breast Cancer

Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is a strong prognostic factor in breast cancer (BC). The aim of this study was to investigate whether semiquantitative parameters derived from baseline [¹⁸F]Fluorodeoxyglucose ([¹⁸F]FDG) positron emission computed tomography/computed tomography (PET/CT) could predict pCR after NAC and survival outcomes in patients affected by different molecular subtypes of BC. We retrospectively retrieved patients from the databases of two Italian hospitals (Centre A: University Hospital of Ferrara; Centre B: University of Padua) meeting the following inclusion criteria: (1) diagnosis of BC; (2) history of NAC; (3) baseline [¹⁸F]FDG PET/CT performed before the first cycle of NAC; (4) available follow-up data (response after NAC and survival information). For each [¹⁸F]FDG PET/CT scan, semiquantitative parameters (SUVmax, SUVmean, MTV and TLG) related to the primary tumor (B), to the reference lesion for both axillary (N) and distant lymph node (DN), and to the whole-body burden of disease (WB) were evaluated. Patients enrolled were 133: 34 from centre A and 99 from centre B. Patients' molecular subtypes were: 9 luminal A, 49 luminal B, 33 luminal B + HER-2, 10 HER-2 enriched, and 32 triple negative (TNBC). Luminal A and HER-2 enriched BC patients were excluded from the analysis due to the small sample size. pCR after NAC was achieved in 47 patients (41.2%). [¹⁸F]FDG PET/CT detected the primary tumor in 98.3% of patients and lymph node metastases were more frequently detected in Luminal B subgroup. Among Luminal B patients, median SUVmean_B values were significantly higher (p = 0.027) in responders (7.06 ± 5.9) vs. non-responders (4.4 ± 2.1) to NAC. Luminal B + HER-2 non-responders showed a statistically significantly higher median MTV_B (7.3 ± 4.2 cm³ vs. 3.5 ± 2.5 cm³; p = 0.003) and TLG_B (36.5 ± 24.9 vs. 18.9 ± 17.7; p = 0.025) than responders at baseline [¹⁸F]FDG PET/CT. None of the semiquantitative parameters predicted pCR after NAC in TNBC patients. However, among TNBC patients who achieved pCR after NAC, 4 volumetric parameters (MTV_B, TLG_B, MTV_WB and TLG_WB) were significantly higher in patients dead at follow-up. If confirmed in further studies, these results could open up a widespread use of [¹⁸F]FDG PET/CT as a baseline predictor of response to NAC in luminal B and luminal B + HER-2 patients and as a prognostic tool in TNBC.

Development and validation of nomograms for predicting overall survival and cancer specific survival in locally advanced breast cancer patients: A SEER population-based study

Background

For patients with locally advanced breast cancer (LABC), conventional TNM staging is not accurate in predicting survival outcomes. The aim of this study was to develop two accurate survival prediction models to guide clinical decision making.

Methods

A retrospective analysis of 22,842 LABC patients was performed from 2010 to 2015 using the Surveillance, Epidemiology and End Results (SEER) database. An additional cohort of 200 patients from the Binzhou Medical University Hospital (BMUH) was analyzed. The least absolute shrinkage and selection operator (LASSO) regression was used to screen for variables. The identified variables were used to build a survival prediction model. The performance of the nomogram models was assessed based on the concordance index (C-index), calibration plot, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA).

Results

The LASSO analysis identified 9 variables in patients with LABC, including age, marital status, Grade, histological type, T-stage, N-stage, surgery, radiotherapy, and chemotherapy. In the training cohort, the C-index of the nomogram in predicting the overall survival (OS) was 0.767 [95% confidence intervals (95% CI): 0.751-0.775], cancer specific survival (CSS) was 0.765 (95% CI: 0.756-0.774). In the external validation cohort, the C-index of the nomogram in predicting the OS was 0.858 (95% CI: 0.812-0.904), the CSS was 0.866 (95% CI: 0.817-0.915). In the training cohort, the area under the receiver operator characteristics curve (AUC) values of the nomogram in prediction of the 1, 3, and 5-year OS were 0.836 (95% CI: 0.821-0.851), 0.769 (95% CI: 0.759-0.780), and 0.750 (95% CI: 0.738-0.762), respectively. The AUC values for prediction of the 1, 3, and 5-year CSS were 0.829 (95% CI: 0.811-0.847), 0.769 (95% CI: 0.757-0.780), and 0.745 (95% CI: 0.732-0.758), respectively. Results of the C-index, ROC curve, and DCA demonstrated that the nomogram was more accurate in predicting the OS and CSS of patients compared with conventional TNM staging.

Conclusion

Two prediction models were developed and validated in this study which provided more accurate prediction of the OS and CSS in LABC patients than the TNM staging. The constructed models can be used for predicting survival outcomes and guide treatment plans for LABC patients.

Characterization of glucose metabolism in breast cancer to guide clinical therapy

Background

Breast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.

Materials and methods

The mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of “rms”.

Results

We constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10⁻⁷). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8⁺ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.

Conclusions

We identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.

Locally advanced breast cancer arising in the axilla

Locally advanced breast cancer arising from ectopic axillary breast tissue is an unusual presentation of this malignancy. The work-up and treatment approach pose some unique challenges. We present the case of a 37-year-old female presenting with a left axillary lesion with skin involvement. Radiological studies and biopsy demonstrated an underlying axillary mass compatible with a triple-positive invasive ductal carcinoma of the breast. Following neoadjuvant therapy, the patient underwent nipple-sparing mastectomy with wide local excision of the involved axillary skin and axillary lymph node dissection. Ectopic locally advanced breast cancer can be treated similarly to its orthotopic counterpart, favoring a neoadjuvant therapy approach followed by surgical excision. Special considerations include the local anatomy of the tumor, the extent of surgery and reconstructive options.

Survival comparison between postoperative and preoperative radiotherapy for stage I-III non-inflammatory breast cancer

To compare the survival benefit between preoperative and postoperative radiotherapy for stage I-III non-inflammatory breast cancer patients, we conducted a retrospective cohort study using surveillance, epidemiology and end results databases. Our study recruited patients who had been diagnosed with stage I-III breast cancer and underwent surgery and radiotherapy. The overall survival was calculated by Kaplan-Meier method. Cox risk model was used to determine the impact of radiotherapy according to stage, molecular subtype and other risk factors. Propensity score matching was used to balance measurable confounding factors. Of all the 411,279 enrolled patients varying from 1975 to 2016, 1712 patients received preoperative radiotherapy, and 409,567 patients received postoperative radiotherapy. Compared with the postoperative radiotherapy group, the preoperative radiotherapy group showed significantly higher risks of overall mortality and breast cancer-specific mortality. Survival differences in treatment sequences were correlated with stage, molecular subtypes and other risk factors. According to the results of this study, preoperative radiotherapy did not show a survival advantage, and postoperative radiotherapy is still the primary treatment. However, preoperative radiotherapy also has some theoretical advantages, such as phase reduction and recurrence reduction. Therefore, it is still worthy of further exploration.

Clonal evolution in primary breast cancers under sequential epirubicin and docetaxel monotherapy

Background

Subclonal evolution during primary breast cancer treatment is largely unexplored. We aimed to assess the dynamic changes in subclonal composition of treatment-naïve breast cancers during neoadjuvant chemotherapy.

Methods

We performed whole exome sequencing of tumor biopsies collected before, at therapy switch, and after treatment with sequential epirubicin and docetaxel monotherapy in 51 out of 109 patients with primary breast cancer, who were included in a prospectively registered, neoadjuvant single-arm phase II trial.

Results

There was a profound and differential redistribution of subclones during epirubicin and docetaxel treatment, regardless of therapy response. While truncal mutations and main subclones persisted, smaller subclones frequently appeared or disappeared. Reassessment of raw data, beyond formal mutation calling, indicated that the majority of subclones seemingly appearing during treatment were in fact present in pretreatment breast cancers, below conventional detection limits. Likewise, subclones which seemingly disappeared were still present, below detection limits, in most cases where tumor tissue remained. Tumor mutational burden (TMB) dropped during neoadjuvant therapy, and copy number analysis demonstrated specific genomic regions to be systematically lost or gained for each of the two chemotherapeutics.

Conclusions

Sequential epirubicin and docetaxel monotherapy caused profound redistribution of smaller subclones in primary breast cancer, while early truncal mutations and major subclones generally persisted through treatment.

Trial registration

ClinicalTrials.gov, NCT00496795, registered on July 4, 2007.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01090-2.

High AUF1 level in stromal fibroblasts promotes carcinogenesis and chemoresistance and predicts unfavorable prognosis among locally advanced breast cancer patients

Background

Locally advanced breast cancer (LABC), the most aggressive form of the disease, is a serious threat for women's health worldwide. The AU-rich RNA-binding factor 1 (AUF1) promotes the formation of chemo-resistant breast cancer stem cells. Thereby, we investigated the power of AUF1 expression, in both cancer cells and their stromal fibroblasts, as predictive biomarker for LABC patients’ clinical outcome following neoadjuvant treatment.

Methods

We have used immunohistochemistry to assess the level of AUF1 on formalin-fixed paraffin-embedded tissues. Immunoblotting was utilized to show the effect of AUF1 ectopic expression in breast stromal fibroblasts on the expression of various genes both in vitro and in orthotopic tumor xenografts. Cytotoxicity was evaluated using the WST1 assay, while a label-free real-time setting using the xCELLigence RTCA technology was utilized to assess the proliferative, migratory and invasive abilities of cells.

Results

We have shown that high AUF1 immunostaining (≥ 10%) in both cancer cells and their adjacent cancer-associated fibroblasts (CAFs) was significantly associated with higher tumor grade. Kaplan–Meier univariate analysis revealed a strong correlation between high AUF1 level in CAFs and poor patient’s survival. This correlation was highly significant in patients with triple negative breast cancer, who showed poor disease-free survival (DFS) and overall survival (OS). High expression of AUF1 in CAFs was also associated with poor OS of ER+/Her2− patients. Similarly, AUF1-positive malignant cells tended to be associated with shorter DFS and OS of ER+/Her2+ patients. Interestingly, neoadjuvant therapy downregulated AUF1 to a level lower than 10% in malignant cells in a significant number of patients, which improved both DFS and OS. In addition, ectopic expression of AUF1 in breast fibroblasts activated these cells and enhanced their capacity to promote, in an IL-6-dependent manner, the epithelial-to-mesenchymal transition and stemness processes. Furthermore, these AUF1-expressing cells enhanced the chemoresistance of breast cancer cells and their growth in orthotopic tumor xenografts.

Conclusions

The present findings show that the CAF-activating factor AUF1 has prognostic/predictive value for breast cancer patients and could represent a great therapeutic target in order to improve the precision of cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01543-x.

Smart Nanoparticles for Breast Cancer Treatment Based on the Tumor Microenvironment

Breast cancer (BC) is the most common malignant tumor in women. There are different risk characteristics and treatment strategies for different subtypes of BC. The tumor microenvironment (TME) is of great significance for understanding the occurrence, development, and metastasis of tumors. The TME plays an important role in all stages of BC metastasis, immune monitoring, immune response avoidance, and drug resistance, and also plays an important role in the diagnosis, prevention, and prognosis of BC. Smart nanosystems have broad development prospect in the regulation of the BC drug delivery based on the response of the TME. In particular, TME-responsive nanoparticles cleverly utilize the abnormal features of BC tissues and cells to achieve targeted transport, stable release, and improved efficacy. We here present a review of the mechanisms underlying the response of the TME to BC to provide potential nanostrategies for future BC treatment.

High DNMT1 Expression in Stromal Fibroblasts Promotes Angiogenesis and Unfavorable Outcome in Locally Advanced Breast Cancer Patients

Background

Active breast cancer-associated fibroblasts (CAFs) play a leading role in breast carcinogenesis through promoting angiogenesis and resistance to therapy. Consequently, these active stromal cells have significant influence on patient outcome. Therefore, we explored here the role of the DNA methyltransferase 1 (DNMT1) protein in CAF-dependent promotion of angiogenesis as well as the prognostic power of DNMT1 level in both cancer cells and their adjacent CAFs in locally advanced breast cancer patients.

Methods

We applied immunohistochemistry to evaluate the level of DNMT1 in breast cancer tissues and their adjacent normal counterparts. Quantitative RT-PCR and immunoblotting were performed to investigate the role of DNMT1 in regulating the expression of pro-angiogenic genes in active CAFs and also their response to the DNMT1 inhibitors decitabine (DAC) as well as eugenol.

Results

We have shown that DNMT1 controls the pro-angiogenic potential of CAFs both in vitro and in vivo through positive regulation of the expression/secretion of 2 important pro-angiogenic factors VEGF-A and IL-8 as well as their upstream effectors mTOR and HIF-1α. To confirm this, we have shown that these DNMT1-related pro-angiogenic effects were suppressed by 2 DNMT1 inhibitors decitabine and eugenol. Interestingly, in a cohort of 100 tumors from locally advanced breast cancer patients (LABC), we have shown that high expression of DNMT1 in tumor cells and their adjacent stromal fibroblasts is correlated with poor survival of these patients.

Conclusion

DNMT1 upregulation in breast stromal fibroblasts promotes angiogenesis via IL-8/VEGF-A upregulation, and correlates well with poor survival of LABC patients.

Radiomics predicts the prognosis of patients with locally advanced breast cancer by reflecting the heterogeneity of tumor cells and the tumor microenvironment

Background

This study investigated the efficacy of radiomics to predict survival outcome for locally advanced breast cancer (LABC) patients and the association of radiomics with tumor heterogeneity and microenvironment.

Methods

Patients with LABC from 2010 to 2015 were retrospectively reviewed. Radiomics features were extracted from enhanced MRI. We constructed the radiomics score using lasso and assessed its prognostic value. An external validation cohort from The Cancer Imaging Archive was used to assess phenotype reproducibility. Sequencing data from TCGA and our center were applied to reveal genomic landscape of different radiomics score groups. Tumor infiltrating lymphocytes map and bioinformatics methods were applied to evaluate the heterogeneity of tumor microenvironment. Computational histopathology was also applied.

Results

A total of 278 patients were divided into training cohort and validation cohort. Radiomics score was constructed and significantly associated with disease-free survival (DFS) of the patients in training cohort, validation cohort and external validation cohort (p < 0.001, p = 0.014 and p = 0.041, respectively). The radiomics-based nomogram showed better predictive performance of DFS compared with TNM model. Distinct gene expression patterns were identified. Immunophenotype and immune cell composition was different in each radiomics score group. The link between radiomics and computational histopathology was revealed.

Conclusions

The radiomics score could effectively predict prognosis of LABC after neoadjuvant chemotherapy and radiotherapy. Radiomics revealed heterogeneity of tumor cell and tumor microenvironment and holds great potential to facilitate individualized DFS estimation and guide personalized care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01516-0.

Early Changes in Quantitative Ultrasound Imaging Parameters during Neoadjuvant Chemotherapy to Predict Recurrence in Patients with Locally Advanced Breast Cancer

BACKGROUND

This study was conducted to explore the use of quantitative ultrasound (QUS) in predicting recurrence for patients with locally advanced breast cancer (LABC) early during neoadjuvant chemotherapy (NAC).

METHODS

Eighty-three patients with LABC were scanned with 7 MHz ultrasound before starting NAC (week 0) and during treatment (week 4). Spectral parametric maps were generated corresponding to tumor volume. Twenty-four textural features (QUS-Tex¹) were determined from parametric maps acquired using grey-level co-occurrence matrices (GLCM) for each patient, which were further processed to generate 64 texture derivatives (QUS-Tex¹-Tex²), leading to a total of 95 features from each time point. Analysis was carried out on week 4 data and compared to baseline (week 0) data. ∆Week 4 data was obtained from the difference in QUS parameters, texture features (QUS-Tex¹), and texture derivatives (QUS-Tex¹-Tex²) of week 4 data and week 0 data. Patients were divided into two groups: recurrence and non-recurrence. Machine learning algorithms using k-nearest neighbor (k-NN) and support vector machines (SVMs) were used to generate radiomic models. Internal validation was undertaken using leave-one patient out cross-validation method.

RESULTS

With a median follow up of 69 months (range 7-118 months), 28 patients had disease recurrence. The k-NN classifier was the best performing algorithm at week 4 with sensitivity, specificity, accuracy, and area under curve (AUC) of 87%, 75%, 81%, and 0.83, respectively. The inclusion of texture derivatives (QUS-Tex¹-Tex²) in week 4 QUS data analysis led to the improvement of the classifier performances. The AUC increased from 0.70 (0.59 to 0.79, 95% confidence interval) without texture derivatives to 0.83 (0.73 to 0.92) with texture derivatives. The most relevant features separating the two groups were higher-order texture derivatives obtained from scatterer diameter and acoustic concentration-related parametric images.

CONCLUSIONS

This is the first study highlighting the utility of QUS radiomics in the prediction of recurrence during the treatment of LABC. It reflects that the ongoing treatment-related changes can predict clinical outcomes with higher accuracy as compared to pretreatment features alone.

Circulating tumor cells may serve as a supplement to RECIST in neoadjuvant chemotherapy of patients with locally advanced breast cancer

BACKGROUND

Circulating tumor cells (CTCs) have been shown to be associated with the response to neoadjuvant chemotherapy (NCT) and the prognosis of locally advanced breast cancer (LABC) patients. Our study aimed to investigate whether the change of CTC status during NCT could serve as a supplement to the Response Evaluation Criteria in Solid Tumors (RECIST) in the treatment and evaluation of LABC patients.

METHODS

6 ml of blood samples were collected before NCT, after the first cycle of NCT and after the completion of NCT, respectively. According to the change of CTC number during NCT, the patients were divided into "CTC low-response (low-R)" group and "CTC high-response (high-R)" group. Survival data of each group of patients were obtained through long-term follow-up.

RESULTS

A total of 35 patients diagnosed with LABC were enrolled. The median follow-up for distant metastasis was 27 months (range 7-36 months). There was no significant difference in distant metastasis-free survival (DMFS) between PR/CR group and PD/SD group (P = 0.0914), while CTC low-R group had a worse DMFS than CTC high-R group (P = 0.0199). In PR/CR subgroup, patients with CTC low-R showed a lower DMFS compared with those with CTC high-R (P = 0.0159). However, in PD/SD subgroup, there was no significant difference in DMFS between CTC low-R and CTC high-R group (P = 0.7521). In terms of assessing response to NCT, CTC change or RECIST classification alone had an AUC of 0.533 (95% CI 0.277-0.790) and 0.700 (95% CI 0.611-0.789), respectively. When combining the two, the AUC slightly increased to 0.713 (95% CI 0.532-0.895).

CONCLUSION

The change of CTC number during NCT has a potential to serve as a supplement to RECIST in the assessment of NCT efficacy and the prognosis of LABC patients.

Circulating Exosomal microRNAs as Predictive Biomarkers of Neoadjuvant Chemotherapy Response in Breast Cancer

Background: Neoadjuvant chemotherapy (NACT) is an increasingly used approach for treatment of breast cancer. The pathological complete response (pCR) is considered a good predictor of disease-specific survival. This study investigated whether circulating exosomal microRNAs could predict pCR in breast cancer patients treated with NACT. Method: Plasma samples of 20 breast cancer patients treated with NACT were collected prior to and after the first cycle. RNA sequencing was used to determine microRNA profiling. The Cancer Genome Atlas (TCGA) was used to explore the expression patterns and survivability of the candidate miRNAs, and their potential targets based on the expression levels and copy number variation (CNV) data. Results: Three miRNAs before that NACT (miR-30b, miR-328 and miR-423) predicted pCR in all of the analyzed samples. Upregulation of miR-127 correlated with pCR in triple-negative breast cancer (TNBC). After the first NACT dose, pCR was predicted by exo-miR-141, while miR-34a, exo-miR182, and exo-miR-183 predicted non-pCR. A significant correlation between the candidate miRNAs and the overall survival, subtype, and metastasis in breast cancer, suggesting their potential role as predictive biomarkers of pCR. Conclusions: If the miRNAs identified in this study are validated in a large cohort of patients, they might serve as predictive non-invasive liquid biopsy biomarkers for monitoring pCR to NACT in breast cancer.

Positive ROS (Reactive Oxygen Species) Modulator Engineered Device Support Skin Treatment in Locally Advanced Breast Cancer (LABC) Enhancing Patient Quality of Life

The development of research in genetic and biochemical fields has made it possible to investigate certain metabolic aspects of the microenvironment of chronic skin lesions, including altered cell signalling, highlighting its importance in determining the blockage of repair processes. The purpose of this prospective observational study is to evaluate the efficacy of a medical device consisting of a polyester scaffold enriched with an oleic matrix with controlled release of ROS in the management of LABC skin lesions. During the period from October 2018 to March 2020, 20 patients with locally advanced breast cancer were enrolled and ten were treated with the devices abovementioned. After 30 days of treatment all patients treated reported a general improvement in local conditions with reduction in ulceration area, exudate and odour. The results suggest that the application of these devices even in particular conditions (healthy and neoplastic tissue) does not lead to the onset of negative effects due to the release of ROS, though their role in tissue repair requires further study to fully understand their potential and increase the fields of application of the device by exploiting its modulation capabilities.

Impact of Preoperative vs Postoperative Radiotherapy on Overall Survival of Locally Advanced Breast Cancer Patients

Background

The treatment for locally advanced breast cancer (LABC) is a severe clinical problem. The postoperative radiotherapy is a conventional treatment method for patients with LABC, whereas the effect of preoperative radiotherapy on outcome of LABC remains controversial. This study aimed to examine and compare the overall survival (OS) in patients with LABC who underwent preoperative radiotherapy or postoperative radiotherapy.

Methods

This retrospective cohort study included 41,618 patients with LABC from the National Cancer Database (NCDB) between 2010 and 2014. We collected patients’ demographic, clinicopathologic, treatment and survival information. Propensity score was used to match patients underwent pre-operative radiotherapy with those who underwent post-operative radiotherapy. Cox proportional hazard regression model was performed to access the association between variables and OS. Log-rank test was conducted to evaluate the difference in OS between groups.

Results

The estimated median follow-up of all included participants was 69.6 months (IQR: 42.84-60.22); 70.1 months (IQR: 46.85-79.97) for postoperative radiotherapy, 68.5 (IQR: 41.13-78.23) for preoperative radiotherapy, and 67.5 (IQR: 25.92-70.99) for no radiotherapy. The 5-year survival rate was 80.01% (79.56-80.47) for LABC patients who received postoperative radiotherapy, 64.08% (57.55-71.34) for preoperative radiotherapy, and 59.67% (58.60-60.77) for no radiotherapy. Compared with no radiation, patients receiving postoperative radiotherapy had a 38% lower risk of mortality (HR=0.62, 95%CI: 0.60-0.65, p<0.001), whereas those who received preoperative radiotherapy had no significant survival benefit (HR=0.88, 95%CI: 0.70-1.11, p=0.282). Propensity score matched analysis indicated that patients treated with preoperative radiotherapy had similar outcomes as those treated with postoperative radiotherapy (AHR=1.23, 95%CI: 0.88-1.72, p=0.218). Further analysis showed that in C0 (HR=1.45, 95%CI: 1.01-2.07, p=0.044) and G1-2 (AHR=1.74, 95%CI: 1.59-5.96, p=0.001) subgroup, patients receiving preoperative radiotherapy showed a worse OS than those who received postoperative radiotherapy.

Conclusions

Patients with LABC underwent postoperative radiotherapy had improved overall survival, whereas no significant survival benefit was observed in patients receiving preoperative radiotherapy. Preoperative radiotherapy did not present a better survival than postoperative radiotherapy for LABC patients.

The management of a breast unit during the COVID-19 emergency: a local experience

Introduction: Since breast imaging requires very close contact with patients, a protocol is needed to perform safe daily screening activities during the COVID-19 pandemic. Materials and methods: Patients were triaged and separated into three different clinical scenarios by performing a telephone questionnaire before each diagnostic exam or a nasopharyngeal swab before every recovery. Specific procedures for each scenario are described. Results: From July to October 2020, 994 exams were performed. A total of 16 cancers and 7 suspected COVID-19 patients were identified. No medical staff were infected. Conclusion: This protocol is an example of the practical use of guidelines applied to a breast unit to assist specialists in preventing COVID-19 infection and optimizing resources for breast cancer diagnosis.

Metastatic Pattern Discriminates Survival Benefit of Type of Surgery in Patients With De Novo Stage IV Breast Cancer Based on SEER Database

Background: The role of surgery and surgery type in de novo stage IV breast cancer (BC) is unclear.

Methods: We carried out a retrospective cohort study that included the data of 4,108 individuals with de novo stage IV BC abstracted from SEER (Surveillance, Epidemiology, and End Results) data resource from 2010 to 2015. The patients were stratified into the non-surgery group, breast-conserving (BCS) surgery group, and mastectomy group. Inverse probability propensity score weighting (IPTW) was then used to balance clinicopathologic factors. Overall survival (OS), as well as the breast cancer-specific survival (BCSS), was assessed in the three groups using Kaplan–Meier analysis and COX model. Subgroups were stratified by metastatic sites for analysis.

Results: Of the 4,108 patients, 48.5% received surgery and were stratified into the BCS group (574 cases) and mastectomy group (1,419 cases). After IPTW balance demographic and clinicopathologic factors, BCS and mastectomy groups had better OS (BCS group: HR, 0.61; 95% CI: 0.49–0.75; mastectomy group: HR, 0.7; 95% CI: 0.63–0.79) and BCSS (BCS group: HR, 0.6; 95% CI, 0.47–0.75; mastectomy group: HR, 0.71; 95% CI, 0.63–0.81) than the non-therapy group. Subgroup analyses revealed that BCS, rather than mastectomy, was linked to better OS (HR, 0.66; 95% CI: 0.48–0.91) and BCSS (HR, 0.63; 95% CI: 0.45–0.89) for patients with bone-only metastasis. For patients with viscera metastasis or bone+viscera metastases, BCS achieved similar OS (viscera metastasis: HR, 1.05; 95% CI: 0.74–1.48; bone+viscera metastases: HR, 1.01; 95% CI: 0.64–1.61) and BCSS (viscera metastasis: HR, 0.94; 95% CI: 0.64–1.38; bone+viscera metastases: HR, 1.06; 95% CI: 0.66–1.73) in contrast with mastectomy.

Conclusions: Local surgery for patients with distant metastasis (DS) exhibited a remarkable survival advantage in contrast with non-operative management. BCS may have more survival benefits for patients with de novo stage IV BC with bone-only metastasis than other metastatic sites. Decisions on de novo stage IV BC primary surgery should be tailored to the metastatic pattern.

The effect of metformin when combined with neoadjuvant chemotherapy in breast cancer patients

Metformin has been used to treat type 2 Diabetes Mellitus since long time. It has two proposed anti-neoplastic mechanisms, direct (insulin-independent) and indirect (insulin-dependent) actions. To assess the effect of Metformin on pathological response when combined with neoadjuvant chemotherapy in breast cancer. A prospective study included stage II, III non-diabetic breast cancer patients who received neoadjuvant chemotherapy in our center during the period from May 2017 to March 2019. 59 patients met our inclusion criteria and completed the study, 27 patients received 850 mg Metformin every 12 h with chemotherapy (group A), and 32 patients received chemotherapy without Metformin (group B). Pathological response was assessed by Chevallier classification and residual cancer burden score (RCB). Both groups were well balanced regarding baseline characteristics. The results of our study showed that the rate of pathological complete response (pCR) was 14.8% in group (A) vs. 6.3% in group (B) with a P value of 0.39. RCB class 3 was 40.7% in group (A) vs. 68.8% in group (B) which was statistically significant with a (P value of 0.031). Patients with triple-positive histology who had RCB class 3 were only (14.3%) in group (A) versus (60%) in group B. Patients with body mass index (BMI) ≥ 25 who had RCB 3 were 40% and 66.7% in group (A) and (B), respectively. Metformin may increase the pCR especially in patients with BMI ≥ 25 and patients with triple-positive histology, a larger phase III study is needed to confirm this finding.

Metal complexes against breast cancer stem cells

With the highest incidence, breast cancer is the leading cause of cancer deaths among women in the world. Tumor metastasis is the major contributor of high mortality in breast cancer, and the existence of cancer stem cells (CSCs) has been proven to be the cause of tumor metastasis. CSCs are a small proportion of tumor cells, and they are associated with self-renewal and tumorigenic potential. Given the significance of CSCs in tumor initiation, expansion, relapse, resistance, and metastasis, studies should investigate and discover effective anticancer agents that can not only inhibit the proliferation of differentiated tumor cells but also reduce the tumorigenic capability of CSCs. Thus, new therapies must be discovered to treat and prevent this severely hazardous disease of human beings. The success of platinum complexes in cancer treatment has laid the basic foundation for the utilization of metal complexes in the treatment of malignant cancers, in particular the highly aggressive triple-negative breast cancer. Importantly, metal complexes currently have diverse and versatile competences in the therapeutic targeting of CSCs. The anti-CSC properties provide a strong impetus for the development of novel metal-based compounds for the targeting of CSCs and treatment of chemotherapy-resistant and relapsed tumors. In this review, we provide the latest advances in metal complexes including platinum, ruthenium, osmium, iridium, manganese, cobalt, nickel, copper, zinc, palladium, and tin complexes against breast CSCs obtained over the past decade, with pertinent literature including those published until 2021.

Comprehensive Analysis of Metabolic Genes in Breast Cancer Based on Multi-Omics Data

Background: Reprogramming of cell metabolism is one of the most important hallmarks of breast cancer. This study aimed to comprehensively analyze metabolic genes in the initiation, progression, and prognosis of breast cancer.

Materials and Methods: Data from The Cancer Genome Atlas (TCGA) in breast cancer were downloaded including RNA-seq, copy number variation, mutation, and DNA methylation. A gene co-expression network was constructed by the weighted correlation network analysis (WGCNA) package in R. Association of metabolic genes with tumor-related immune cells and clinical parameters were also investigated.

Results: We summarized 3,620 metabolic genes and observed mutations in 2,964 genes, of which the most frequently mutated were PIK3CA (51%), TNN (26%), and KMT2C (15%). Four genes (AKT1, ERBB2, KMT2C, and USP34) were associated with survival of breast cancer. Significant association was detected in the tumor mutation burden (TMB) of metabolic genes with T stage (p = 0.045) and N stage (p = 0.004). Copy number variations were significantly associated with recurrence and prognosis of breast cancer. The co-expression network for differentially expressed metabolic genes by WGCNA suggested that the modules were associated with glycerophospholipid, arachidonic acid, carbon, glycolysis/gluconeogenesis, and pyrimidine/purine metabolism. Glycerophospholipid metabolism correlated with most of the immune cells, while arachidonic acid metabolism demonstrated a significant correlation with endothelial cells. Methylation and miRNA jointly regulated 14 metabolic genes while mutation and methylation jointly regulated PIK3R1.

Conclusion: Based on multi-omics data of somatic mutation, copy number variation, mRNA expression, miRNA expression, and DNA methylation, we identified a series of differentially expressed metabolic genes. Metabolic genes are associated with tumor-related immune cells and clinical parameters, which might be therapy targets in future clinical application.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. The GATA3-AS1 transcript was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by RT-qPCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9%, a specificity of 75.0%, and an area under the curve of approximately 0.90, as measured by receiver operating characteristic curve analysis. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning

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Textural and second derivative textural features of CT images can be used in conjunction with machine learning models to predict breast cancer response to chemotherapy prior to the start of treatment.

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The proposed predictive model separates the patients at pre-treatment into two cohorts (responders/non-responders) with significantly different survival.

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The proposed methodology is a step forward towards the precision oncology paradigm for breast cancer patients.

Although neoadjuvant chemotherapy (NAC) is a crucial component of treatment for locally advanced breast cancer (LABC), only about 70% of patients respond to it. Effective adjustment of NAC for individual patients can significantly improve survival rates of those resistant to standard regimens. Thus, the early prediction of NAC outcome is of great importance in facilitating a personalized paradigm for breast cancer therapeutics. In this study, quantitative computed tomography (qCT) parametric imaging in conjunction with machine learning techniques were investigated to predict LABC tumor response to NAC. Textural and second derivative textural (SDT) features of CT images of 72 patients diagnosed with LABC were analysed before the initiation of NAC to quantify intra-tumor heterogeneity. These quantitative features were processed through a correlation-based feature reduction followed by a sequential feature selection with a bootstrap 0.632+ area under the receiver operating characteristic (ROC) curve (AUC0.632+) criterion. The best feature subset consisted of a combination of one textural and three SDT features. Using these features, an AdaBoost decision tree could predict the patient response with a cross-validated AUC0.632+ accuracy, sensitivity and specificity of 0.88, 85%, 88% and 75%, respectively. This study demonstrates, for the first time, that a combination of textural and SDT features of CT images can be used to predict breast cancer response NAC prior to the start of treatment which can potentially facilitate early therapy adjustments.

Network meta-analysis of eribulin versus other chemotherapies used as second- or later-line treatment in locally advanced or metastatic breast cancer

BACKGROUND

Eribulin mesylate (ERI; Halaven®) is a microtubule inhibitor approved in the United States for metastatic breast cancer patients with at least two prior chemotherapy regimens for metastatic breast cancer, and in the European Union in locally advanced breast cancer or metastatic breast cancer patients who progressed after at least one chemotherapy for advanced disease. This network meta-analysis compared the efficacy and safety of ERI versus other chemotherapies in this setting.

METHODS

Systematic searches conducted in MEDLINE, Embase, and the Cochrane Central Register of Clinical Trials identified randomized controlled trials of locally advanced breast cancer/metastatic breast cancer chemotherapies in second- or later-line settings. Efficacy assessment included pre-specified subgroup analysis of breast cancer subtypes. Included studies were assessed for quality using the Centre for Reviews and Dissemination tool. Bayesian network meta-analysis estimated primary outcomes of overall survival and progression-free survival using fixed-effect models. Comparators included: capecitabine (CAP), gemcitabine (GEM), ixabepilone (IXA), utidelone (UTI), treatment by physician's choice (TPC), and vinorelbine (VIN).

RESULTS

The network meta-analysis included seven trials. Results showed that second- or later-line patients treated with ERI had statistically longer overall survival versus TPC (hazard ratio [HR]: 0.81; credible interval [CrI]: 0.66-0.99) or GEM+VIN (0.62; 0.42-0.90) and statistically longer progression-free survival versus TPC (0.76; 0.64-0.90), but statistically shorter progression-free survival versus CAP+IXA (1.40; 1.17-1.67) and CAP+UTI (1.61; 1.23-2.12). In triple negative breast cancer, ERI had statistically longer overall survival versus CAP (0.70; 0.54-0.90); no statistical differences in progression-free survival were observed in triple negative breast cancer.

CONCLUSIONS

This network meta-analysis suggests that ERI may provide an overall survival benefit in the overall locally advanced breast cancer/metastatic breast cancer populations and triple negative breast cancer subgroup compared to standard treatments. These findings support the use of ERI in second- or later-line treatment of patients with locally advanced breast cancer/metastatic breast cancer.

Association between tumor molecular subtype, clinical stage and axillary pathological response in breast cancer patients undergoing complete pathological remission after neoadjuvant chemotherapy: potential implications for de-escalation of axillary surgery

Background

Axillary node status is used in clinical practice to guide the selection of axillary surgery in breast cancer patients. However, to date, the optimal axillary management following neoadjuvant therapy (NAT) for breast cancer remains controversial. Our study aimed to investigate the association of molecular subtype, clinical stage, and ypN status after NAT in breast cancer patients, especially those achieving breast pathological complete remission (pCR).

Patients and methods

Patients receiving ⩾4 cycles of NAT were retrospectively included between January 2009 and January 2020. ypN status was compared among patients with different breast pCR statuses, clinical stages, and molecular subtypes in univariate and multivariate analyses.

Results

A total of 1999 patients were included: 457 (22.86%), 884 (44.22%), and 658 (32.92%) patients with cT1-2N0, cT1-2N1, and locally advanced breast cancer (LABC), respectively. Altogether, 435 (21.8%) patients achieved breast pCR: 331 with ypN- and 104 with ypN+ status. Patients achieving breast pCR had a significantly lower ypN+ rate than those without pCR [23.9% versus 62.5%, odds ratio (OR) = 0.14, 95% confidence interval (CI) = 0.09-0.21]. For patients with breast pCR, the ypN+ rate was 6.4%, 25.7%, and 33.9% in cT1-2N0, cT1-2N1, and LABC patients, respectively (p < 0.001). Furthermore, the ypN+ rate was 30.8%, 16.8%, 17.5%, 29.6%, and 27.6% in breast pCR patients with the Luminal A, Luminal B (HER2+), HER2-amplified, Luminal B (HER2-), and triple-negative subtype, respectively. Luminal B (HER2+) (OR = 0.20, 95% CI = 0.05-0.82) and HER2-amplified (OR = 0.19, 95% CI = 0.05-0.83) tumors were associated with lower ypN+ rates. Moreover, 100% of breast pCR patients with cT1-2N0 and HER2-positive disease achieved pathological pN0.

Conclusion

In breast pCR patients after NAT, clinical stage and molecular subtype were significantly associated with ypN status. Patients with cT1-2N0 and HER2-positive disease who achieved breast pCR had a very low ypN+ rate, possibly indicating the possibility for de-escalation of axillary surgery in this patient subgroup.

Impact of Pathologic Complete Response following Neoadjuvant Chemotherapy ± Trastuzumab in Locally Advanced Breast Cancer

Purpose

This study was designed to examine the relationship between breast cancer molecular subtypes and pathological response to neoadjuvant chemotherapy (NAC) ± trastuzumab, in locally advanced breast cancer (LABC).

Methods

Female patients with LABC (T2–T4, N0–N2, and M0) who received neoadjuvant chemotherapy + trastuzumab if HER2+ subtype, followed by surgery and radiotherapy ± hormonal therapy, were identified. The primary endpoint was pathologic complete response (pCR) in the breast and axilla (ypT0/ypN0), with final analysis on disease-free survival (DFS) and overall survival (OS).

Results

Six hundred eighty-one patients with a median age of 44 years, premenopausal: 70%, median tumour size: 7.0 cm (range 4–11 cm), stage II B: 27% and III A/III B: 73%, ER+/HER2−: 40.8%, ER−/HER2−: 23%, ER+/HER2+: 17.7%, and ER−/HER2+: 18.5%. Overall pCR (ypT0/ypN0) was 23%. The pCR rates based on molecular subtypes were ER+/HER2−: 9%; ER+/HER2+: 29%; ER−/HER2−: 31%; and ER−/HER2+: 37%. At median follow-up of 61 months, ER+/HER2+ and ER+/HER2− subtypes had the best 5-year DFS and OS; meanwhile, ER−/HER2+ and ER−/HER2− subtypes had the worst.

Conclusion

Women with ER+/HER2− disease are the least likely to achieve pCR, with the highest rates in HER2+ and triple-negative subgroups. Degree of response is associated with OS; despite the comparatively higher likelihood of achieving pCR in ER−/HER2+ and triple-negative, these subgroups experience a survival detriment. We are consistent with the published data that patients who attain the pathological complete response defined as ypT0/ypN0 have improved outcomes.

Network Pharmacology-Based Approach to Investigate the Molecular Targets of Sinomenine for Treating Breast Cancer

Purpose

Sinomenine has been known to inhibit the proliferation of breast cancer cells. However, its targets have not been found yet. This study aimed to search for molecular targets of sinomenine for treating breast cancer via network pharmacology.

Methods

Potential targets of sinomenine or breast cancer were separately screened from indicated databases. The common targets of both sinomenine and breast cancer were considered as the targets of sinomenine for treating breast cancer. A sinomenine-target-pathway network was constructed based on the obtained results from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The putative targets of sinomenine were further determined by using protein–protein interaction (PPI) analysis and molecular docking. Finally, the putative targets were verified in vitro and in vivo.

Results

Twenty predicted targets were identified through network pharmacological analysis. Gene Ontology (GO) and KEGG pathway enrichment indicated that these predicted targets enriched in the process of MAP kinase activity, VEGF signaling pathway, Relaxin signaling pathway, Growth hormone synthesis, secretion and action. MAPK1, NOS3, NR3C1, NOS1 and NOS2 were further identified as the putative targets by using PPI and molecular docking analysis. Expression of MAPK1, NR3C1, NOS1, NOS2 and NOS3 genes were significantly regulated by sinomenine in both MCF-7 cells and MDA-MB-231 cells. Furthermore, the expression of NR3C1 in human breast cancer specimens was lower than that in para-tumor normal tissues. Meanwhile, the expression of NR3C1 in xenograft tumors was up-regulated after sinomenine treatment.

Conclusion

MAPK1, NR3C1, NOS1, NOS2 and NOS3 were identified as the putative targets of sinomenine for treating breast cancer. NR3C1 was preliminarily confirmed as a target of sinomenine in two breast cancer cell lines, xenograft tumor models and human breast cancer specimens. These data indicated that the network pharmacology-based prediction of sinomenine targets for treating breast cancer could be reliable.

A priori prediction of response in multicentre locally advanced breast cancer (LABC) patients using quantitative ultrasound and derivative texture methods

PURPOSE

We develop a multi-centric response predictive model using QUS spectral parametric imaging and novel texture-derivate methods for determining tumour responses to neoadjuvant chemotherapy (NAC) prior to therapy initiation.

MATERIALS AND METHODS

QUS Spectroscopy provided parametric images of mid-band-fit (MBF), spectral-slope (SS), spectral-intercept (SI), average-scatterer-diameter (ASD), and average-acoustic-concentration (AAC) in 78 patients with locally advanced breast cancer (LABC) undergoing NAC. Ultrasound radiofrequency data were collected from Sunnybrook Health Sciences Center (SHSC), University of Texas MD Anderson Cancer Center (MD-ACC), and St. Michaels Hospital (SMH) using two different systems. Texture analysis was used to quantify heterogeneities of QUS parametric images. Further, a second-pass texture analysis was applied to obtain texture-derivate features. QUS, texture- and texture-derivate parameters were determined from both tumour core and a 5-mm tumour margin and were used in comparison to histopathological analysis for developing a response predictive model to classify responders versus non-responders. Model performance was assessed using leave-one-out cross-validation. Three standard classification algorithms including a linear discriminant analysis (LDA), k-nearest-neighbors (KNN), and support vector machines-radial basis function (SVM-RBF) were evaluated.

RESULTS

A combination of tumour core and margin classification resulted in a peak response prediction performance of 88% sensitivity, 78% specificity, 84% accuracy, 0.86 AUC, 84% PPV, and 83% NPV, achieved using the SVM-RBF classification algorithm. Other parameters and classifiers performed less well running from 66% to 80% accuracy.

CONCLUSIONS

A QUS-based framework and novel texture-derivative method enabled accurate prediction of responses to NAC. Multi-centric response predictive model provides indications of the robustness of the approach to variations due to different ultrasound systems and acquisition parameters.

MicroRNA-383-5p acts as a potential prognostic biomarker and an inhibitor of tumor cell proliferation, migration, and invasion in breast cancer

BACKGROUND

MicroRNAs (miRNAs) have been reported to serve as potential biomarkers in various cancer and play important roles in tumor progression.

OBJECTIVE

The aim of this study was to investigate the prognostic significance and functional role of miR-383-5p in breast cancer.

METHODS

The expression levels of miR-383-5p in breast cancer tissues and cell lines were measured using quantitative real-time PCR analysis. Kaplan-Meier curve and Cox regression analysis were used to explore the prognostic significance of miR-383-5p in breast cancer. The CCK-8 assay was used to assess cell proliferation ability. Transwell assays were used to assess cell migration and invasion abilities of breast cancer cells.

RESULTS

The expression of miR-383-5p was significantly downregulated in breast cancer tissues and cell lines, compared with that in normal tissues and normal epithelial MCF-10A cells, respectively. The expression of miR-383-5p was associated with differentiation, lymph node metastasis, and TNM stage. Patients with low miR-383-5p expression had shorter overall survival than those with high miR-383-5p expression. Overexpression of miR-383-5p significantly inhibited cell proliferation, migration, and invasion, while downregulation of miR-383-5p promoted cell proliferation, migration, and invasion in vitro. LDHA was a direct target of miR-383-5p.

CONCLUSIONS

Taken together, miR-383-5p was downregulated in breast cancer tissues and cell lines, and overexpression of miR-383-5p inhibited cell proliferation, migration, and invasion in breast cancer cells by targeting LDHA. Based on our findings, miR-383-5p may be a prognostic biomarker and therapeutic target for breast cancer.

Clinical and pathological response to neoadjuvant chemotherapy with different chemotherapy regimens predicts the outcome of locally advanced breast cancer

Background

This retrospective analysis was designed to research whether clinical response partial response (PR)/complete response (CR) and pathological response (PCR) to neoadjuvant chemotherapy can translate into prognosis benefit pathological response in patients with locally advanced breast cancer and whether different chemotherapy regimens will influence the outcomes.

Methods

One hundred and thirty-five patients with breast cancer patients who received neoadjuvant chemotherapy were included in the retrospective analysis. Patients were followed up strictly. Overall survival (OS) was evaluated by the Kaplan-Meier analysis. The comparison of the clinical and pathological characteristics and recurrence was performed using the carried out by chi-squared and Fisher's exact tests. Univariate and multivariate analyses were performed by the Cox regression analysis.

Results

Clinical response was strongly correlated with lymph nodes status (P=0.032). The OS comparison of pathological response between the pCR group and non-pCR groups did not exhibit statistically significant differences (P=0.400). A similar non-significant response result was observed in the comparison of clinical response between the PR/CR and SD/PD groups group (P=0.108). Univariate and multivariate analyses did not support clinical response (P=0.156 P=0.095 respectively) or pathological response (P=0.600 P=0.144 respectively) as the predictors of prognosis. There were no significant differences in either the comparison of the clinical response group it seems no statistically significance (P=0.496) or the comparison of the pathological response group (P=0.460). OS analyses across different neoadjuvant chemotherapy regimens demonstrated no significant differences (P=0.307). In the PR/CR and PD/SD comparison of every single regimen, there were no significant differences. However, for patients with PR/CR patients from the comparison of five regimens, namely, TAC, FAC, AC-T, AT and TCBP demonstrated a significant difference (P=0.022). In the group of patients with luminal A breast cancer, the result of the Fisher's exact test approached significant (P=0.059).

Conclusions

Neither PR/CR nor pCR can translate into long-term outcome benefit. PR/CR and PCR are not independent predictors in patients with advanced breast cancer. Patients who received a taxane + anthracycline regimen exhibited a higher recurrence rate than any other regimens, especially those patients with luminal A breast cancer.

Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer

Background: To investigate quantitative ultrasound (QUS) based higher-order texture derivatives in predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC).

Materials and Methods: 100 Patients with LABC were scanned before starting NAC. Five QUS parametric image-types were generated from radio-frequency data over the tumor volume. From each QUS parametric-image, 4 grey level co-occurrence matrix-based texture images were derived (20 QUS-Tex¹), which were further processed to create texture derivatives (80 QUS-Tex¹-Tex²). Patients were classified into responders and non-responders based on clinical/pathological responses to treatment. Three machine learning algorithms based on linear discriminant (FLD), k-nearest-neighbors (KNN), and support vector machine (SVM) were used for developing radiomic models of response prediction.

Results: A KNN-model provided the best results with sensitivity, specificity, accuracy, and area under curve (AUC) of 87%, 81%, 82%, and 0.86, respectively. The most helpful features in separating the two response groups were QUS-Tex¹-Tex² features. The 5-year recurrence-free survival (RFS) calculated for KNN predicted responders and non-responders using QUS-Tex¹-Tex² model were comparable to RFS for the actual response groups.

Conclusions: We report the first study demonstrating QUS texture-derivative methods in predicting NAC responses in LABC, which leads to better results compared to using texture features alone.

Neoadjuvant radiotherapy in the approach of locally advanced breast cancer

Background

Approximately 4% of European patients are diagnosed with locally advanced breast cancer (LABC), a clinical condition commonly associated with poorer prognosis. Systemic therapy is the recommended initial treatment and when inoperability criteria prevails, radiotherapy (RT) should be used for tumour downstaging. This study intends to evaluate the impact of neoadjuvant radiotherapy (NART) in the treatment of inoperable LABC.

Methods

A retrospective study of female patients, submitted to the NART between January 2014 and December 2018 at our institution. The evaluation of pathological response (pR) was made based on Pinder criteria. Primary endpoint: pR. Secondary endpoints: overall survival (OS) and progression-free survival (PFS). OS and PFS were calculated using the Kaplan-Meier method. Differences between groups were compared using Student’s t-test, ANOVA (Analysis of variance) and χ² test. The statistical analyses were performed using Stata (V.13).

Results

A total of 76 patients were included, 18% with breast complete response. The 5 years OS was 54% and PFS was 61%. Subgroup analysis showed that pR >90% is correlated with a better OS (p=0.004). Basal-like intrinsic subtype is correlated with worse OS and PFS (p<0.05). No relation was found between response and age, intrinsic subtype, treatment performed and clinical T stage.

Conclusion

Our study confirms that NART is an effective downsizing treatment in inoperable LABC, allowing for a surgical resection regardless of the systemic treatment performed. Response to NART is independent of the intrinsic subtype and pR >90% is correlated with a better OS. Prospective studies to explore predictive response biomarkers are necessary in order to improve patient selection and optimisation of the treatment.

Efficacy and Safety of Capecitabine Alone or in Combination in Advanced Metastatic Breast Cancer Patients Previously Treated with Anthracycline and Taxane: A Systematic Review and Meta-Analysis

BACKGROUND

Capecitabine is frequently used alone or combined with other chemotherapy agents for the treatment of metastatic breast cancer in relapsed patients.

OBJECTIVE

The objective of this meta-analysis is to evaluate the effectiveness and safety of capecitabine monotherapy versus combination in the treatment of metastatic breast cancer patients pretreated with anthracycline and taxane.

METHODS

Eligible randomized controlled trials examining the efficacy and safety of capecitabine alone compared to capecitabine combination were systematically searched. Progression-free survival (PFS), overall survival (OS), overall response rate (ORR), and grades 3-4 drug-related adverse events were the outcomes assessed.

RESULTS

A total of 6,714 patients of 9 trials were involved in the pooled analysis. Our findings demonstrated that capecitabine combination is significantly superior to capecitabine monotherapy in improving PFS (hazard ratio [HR] 1.32, 95% CI 1.13-1.54, p < 0.0001) and ORR (risk ratio [RR] 0.67, 95% CI 0.54-0.83, p < 0.001), but it was insignificant in OS (HR 1.09, 95% CI 0.98-1.22, p = 0.12). On the other hand, the incidence of non-hematological adverse events such as hand-foot syndrome and diarrhea was lower in capecitabine combination compared to capecitabine monotherapy.

CONCLUSION

Capecitabine-based combination chemotherapy showed superiority over capecitabine monotherapy in terms of PFS and ORR, with no significant difference in OS. Non-hematological adverse effects such as hand-foot syndrome were fewer with a combination regimen. However, hematological adverse events were fewer with capecitabine monotherapy regimen.

Comparison of characteristics in Mexican women with breast cancer according to healthcare coverage

Objective:

To compare the sociodemographic, diagnostic, clinical, and treatment-related characteristics and outcomes of patients with breast cancer in two hospitals in Mexico according to type of healthcare coverage.

Methods:

A retrospective cohort study of women with breast cancer according to public or private healthcare coverage in two hospitals was done. Patients were treated by the same group of physicians and healthcare infrastructure. Groups were compared using the chi-square test for categorical variables, Mann–Whitney U-test and Student’s t-test for quantitative variables, and Kaplan–Meier estimator and log-rank test for time dependent outcomes (including recurrence-free and overall survival). A value of p < 0.05 was considered statistically significant.

Results:

A total of 282 women were included. Mean age at diagnosis was 52 years. Women with public healthcare coverage were diagnosed more frequently with self-detected tumors (82.8% vs 47.9%, p < 0.001) and advanced clinical stage (III and IV) (31.1% vs 17.8%, p = 0.014). More women with public healthcare insurance underwent initial systemic treatment (41.1% vs 17.8%, p < 0.001) and mastectomy (70.1% vs 54.9%, p = 0.020), and received more chemotherapy (79.4% vs 43.8%, p < 0.001) and adjuvant radiotherapy (68.9% vs 53.4%, p = 0.017). Overall, no differences were found in survival outcomes according to healthcare coverage. Trends suggesting worse recurrence-free and overall survival were observed in patients with public coverage at 3 years follow-up in stage III (85.7% vs 67.3% and 100% vs 84.6%, respectively) and triple negative disease (83.3% vs 74.5% and 100% vs 74.1%, respectively).

Conclusion:

Strategies to promote preventive medicine, diagnostic mammograms, and prompt diagnosis of breast cancer in Mexican women with public health coverage are needed. Access to the main treatment modalities by Seguro Popular and good quality care by an experienced group of physicians likely explains the similar outcomes between patients with private and public healthcare coverage. However, trends suggesting worse survival for patients with public medical coverage with stage III and triple-negative disease should encourage close follow-up.

Clinical Outcomes of N3 Breast Cancer: A Real-World Study of a Single Institution and the US Surveillance, Epidemiology, and End Results (SEER) Database

Background

Although stage IIIC (any TN3M0) breast cancer is known to have a dismal prognosis, the clinical outcome of current standard management and the prognostic differences between N3a, N3b and N3c remain to be further investigated.

Material and Methods

Data from our center on pathologic N3 (pN3) (n=284) breast cancer and the US Surveillance, Epidemiology, and End Results (SEER) database on clinical N3 (cN3) (n=15,291) and M1 (n=23,623) breast cancer between January 2004 and December 2015 were systematically analyzed for clinicopathological characteristics and survival outcomes.

Results

In our institution, patients with pN3c had the worst survival, with 5-year OS and DFS rates of 52.4% and 41.5%, respectively. Patients with pN3b had a relatively good prognosis, with a 5-year OS rate of 75.3% vs 63.9% for the pN3a group (p=0.045). For DFS, the 5-year survival rate was 63.1% in the pN3b group compared with 40.3% in the pN3a group (p=0.030). In the US SEER database, patients with cN3c had the worst survival in the cN3 group, but the prognosis of cN3c was much better than that of M1. Similarly, patients with cN3b had a better prognosis compared with patients in other groups, with a 5-year OS rate of 68.9% vs 61.9% for the cN3a group (p<0.001) and a 5-year BCSS rate of 73.4% vs 67.1% for the cN3a group (p<0.001).

Conclusion

Breast cancer patients with N3c had the worst clinical outcomes, while the prognosis of N3b patients was better than that of N3a patients.