Distinct profiles of proliferating CD8+/TCF1+ T cells and CD163+/PD-L1+ macrophages predict risk of relapse differently among treatment-naïve breast cancer subtypes

Immunophenotypic analysis of breast cancer microenvironment is gaining attraction as a clinical tool improving breast cancer patient stratification. The aim of this study is to evaluate proliferating CD8 + including CD8 + TCF1 + Τ cells along with PD-L1 expressing tissue-associated macrophages among different breast cancer subtypes. A well-characterized cohort of 791 treatment-naïve breast cancer patients was included. The analysis demonstrated a distinct expression pattern among breast cancer subtypes characterized by increased CD8 + , CD163 + and CD163 + PD-L1 + cells along with high PD-L1 status and decreased fraction of CD8 + Ki67 + T cells in triple negative (TNBC) and HER2 + compared to luminal tumors. Kaplan-Meier and Cox univariate survival analysis revealed that breast cancer patients with high CD8 + , CD8 + Ki67 + , CD8 + TCF1 + cells, PD-L1 score and CD163 + PD-L1 + cells are likely to have a prolonged relapse free survival, while patients with high CD163 + cells have a worse prognosis. A differential impact of high CD8 + , CD8 + Ki67 + , CD8 + TCF1 + T cells, CD163 + PD-L1 + macrophages and PD-L1 status on prognosis was identified among the various breast cancer subtypes since only TNBC patients experience an improved prognosis compared to patients with luminal A tumors. Conversely, high infiltration by CD163 + cells is associated with worse prognosis only in patients with luminal A but not in TNBC tumors. Multivariate Cox regression analysis in TNBC patients revealed that increased CD8 + [hazard ratio (HR) = 0.542; 95% confidence interval (CI) 0.309-0.950; p = 0.032), CD8 + TCF1 + (HR = 0.280; 95% CI 0.101-0.779; p = 0.015), CD163 + PD-L1 + (HR: 0.312; 95% CI 0.112-0.870; p = 0.026) cells along with PD-L1 status employing two different scoring methods (HR: 0.362; 95% CI 0.162-0.812; p = 0.014 and HR: 0.395; 95% CI 0.176-0.884; p = 0.024) were independently linked with a lower relapse rate. Multivariate analysis in Luminal type A patients revealed that increased CD163 + was independently associated with a higher relapse rate (HR = 2.360; 95% CI 1.077-5.170; p = 0.032). This study demonstrates that the evaluation of the functional status of CD8 + T cells in combination with the analysis of immunosuppressive elements could provide clinically relevant information in different breast cancer subtypes.

Noninvasive Assessment of Tumor Histological Grade in Invasive Breast Carcinoma Based on Ultrasound Radiomics and Clinical Characteristics: A Multicenter Study

Rationale and Objectives: We aimed to develop and validate prediction models for histological grade of invasive breast carcinoma (BC) based on ultrasound radiomics features and clinical characteristics. Materials and Methods: A number of 383 patients with invasive BC were retrospectively enrolled and divided into a training set (207 patients), internal validation set (90 patients), and external validation set (86 patients). Ultrasound radiomics features were extracted from all the eligible patients. The Boruta method was used to identify the most useful features. Seven classifiers were adopted to developed prediction models. The output of the classifier with best performance was labeled as the radiomics score (Rad-score) and the classifier was selected as the Rad-score model. A combined model combining clinical factors and Rad-score was developed. The performance of the models was evaluated using receiver operating characteristic curve. Results: Seven radiomics features were selected from 788 candidate features. The logistic regression model performing best among the 7 classifiers in the internal and external validation sets was considered as Rad-score model, with areas under the receiver operating characteristic curve (AUC) values of 0.731 and 0.738. The tumor size was screened out as the risk factor and the combined model was developed, with AUC values of 0.721 and 0.737 in the internal and external validation sets. Furthermore, the 10-fold cross-validation demonstrated that the 2 models above were reliable and stable. Conclusion: The Rad-score model and combined model were able to predict histological grade of invasive BC, which may enable tailored therapeutic strategies for patients with BC in routine clinical use.

Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer

This study aimed to identify microRNAs associated with histological grade using comprehensive microRNA analysis data obtained by next-generation sequencing from early-stage invasive breast cancer. RNA-seq data from normal breast and breast cancer samples were compared to identify candidate microRNAs with differential expression using bioinformatics. A total of 108 microRNAs were significantly differentially expressed in normal breast and breast cancer tissues. Using clinicopathological information and microRNA sequencing data of 430 patients with breast cancer from The Cancer Genome Atlas (TCGA), the differences in candidate microRNAs between low- and high-grade tumors were identified. Comparing the expression of the 108 microRNAs between low- and high-grade cases, 25 and 18 microRNAs were significantly upregulated and downregulated, respectively, in high-grade cases. Clustering analysis of the TCGA cohort using these 43 microRNAs identified two groups strongly predictive of histological grade. miR-3677 is a microRNA upregulated in high-grade breast cancer. The outcome analysis revealed that patients with high miR-3677 expression had significantly worse prognosis than those with low miR-3677 expression. This study shows that microRNAs are associated with histological grade in early-stage invasive breast cancer. These findings contribute to the elucidation of a new mechanism of breast cancer growth regulated by specific microRNAs.

Evaluating the effectiveness of stain normalization techniques in automated grading of invasive ductal carcinoma histopathological images

Debates persist regarding the impact of Stain Normalization (SN) on recent breast cancer histopathological studies. While some studies propose no influence on classification outcomes, others argue for improvement. This study aims to assess the efficacy of SN in breast cancer histopathological classification, specifically focusing on Invasive Ductal Carcinoma (IDC) grading using Convolutional Neural Networks (CNNs). The null hypothesis asserts that SN has no effect on the accuracy of CNN-based IDC grading, while the alternative hypothesis suggests the contrary. We evaluated six SN techniques, with five templates selected as target images for the conventional SN techniques. We also utilized seven ImageNet pre-trained CNNs for IDC grading. The performance of models trained with and without SN was compared to discern the influence of SN on classification outcomes. The analysis unveiled a p-value of 0.11, indicating no statistically significant difference in Balanced Accuracy Scores between models trained with StainGAN-normalized images, achieving a score of 0.9196 (the best-performing SN technique), and models trained with non-normalized images, which scored 0.9308. As a result, we did not reject the null hypothesis, indicating that we found no evidence to support a significant discrepancy in effectiveness between stain-normalized and non-normalized datasets for IDC grading tasks. This study demonstrates that SN has a limited impact on IDC grading, challenging the assumption of performance enhancement through SN.

Lymphovascular invasion is an independent prognostic factor in breast cancer irrespective of axillary node metastasis and molecular subtypes

Purpose

Lymphovascular invasion (LVI) is a well-known poor prognostic factor for early breast cancer. However, the effect of LVI on breast cancer subtype and node status remains unknown. In this study, we aimed to evaluate the clinical significance of LVI on the recurrence and long-term survival of patients with early breast cancer by comparing groups according to the subtype and node status.

Methods

We retrospectively reviewed the medical records of 4554 patients with breast cancer who underwent breast cancer surgery between January 2010 and December 2017. The primary endpoints were disease-free survival (DFS) and overall survival (OS). Univariate and multivariate analyses were performed to identify prognostic factors related to the DFS and OS according to the nodal status and breast cancer subtype.

Results

During a follow-up period of 94 months, the median OS and DFS were 92 and 90 months, respectively. The LVI expression rate was 8.4%. LVI had a negative impact on the DFS and OS, regardless of the lymph node status. LVI was associated with higher recurrence and lower survival in the luminal A, human epidermal growth factor receptor 2-positive, and triple-negative breast cancer subtypes. The Cox proportional hazards model showed that LVI was a significant prognostic factor for both DFS and OS. No correlation has been observed between LVI and the Oncotype Dx results in terms of prognostic value in early breast cancer.

Conclusion

LVI is an independent poor prognostic factor in patients with early breast cancer, regardless of the node status and molecular subtype. Therefore, the LVI status should be considered when making treatment decisions for patients with early stage breast cancer; however, further prospective studies are warranted.

Is Immediate Lymphatic Reconstruction on Breast Cancer Patients Oncologically Safe? A Preliminary Study

Background

In breast cancer patients receiving axillary lymph node dissection (ALND), immediate lymphatic reconstruction (ILR) with lymphovenous anastomosis is an emerging technique for reducing the risk of arm lymphedema. However, the oncologic safety of surgically diverting lymphatic ducts directly into venules in a node-positive axilla is still a concern of inadvertently inducing metastasis of remaining cancer cells. This study aimed to assess the oncologic safety of ILR.

Methods

From January 2020 to January 2022, 95 breast cancer patients received ALND, and 45 of them also received ILR. Patients with recurrent cancer, with follow-up less than 12 months, and with missed data were excluded. Variables were compared between ILR and non-ILR groups, and the outcome of interest was the rate of distant recurrence after follow-up for at least 1 year.

Results

Thirty-four patients in the ILR group and 32 patients in the non-ILR group fulfilled the inclusion criteria for analysis. No statistically significant difference was noted between groups in terms of age, body mass index, type of breast surgery, pathologic cancer staging, histologic type and grade of breast cancer, molecular subtypes, frequency of axillary lymph node metastasis, or adjuvant therapy. For the patients receiving follow-up for at least 1 year, no statistically significant difference was found in terms of distant recurrence rates between ILR and non-ILR groups (P = 0.44).

Conclusion

For breast cancer patients receiving ALND, ILR with lymphovenous anastomosis is oncologically safe, within an average follow-up period of 21 months.

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.

Clinicopathological Factors Affecting Breast Cancer Survival in Jamaican Women: A Retrospective Review

OBJECTIVE

Breast cancer is the leading cause of cancer affecting women worldwide. The survival rate is primarily affected by the stage of the disease and several other demographic and clinicopathological factors.

METHODS

This study is a retrospective cohort study of female patients of the University Hospital of the West Indies diagnosed with breast cancer between 2011 and 2016. The age, tumor size, SBR/Nottingham grade, tumor histologic subtype, tumor molecular subtype, and survival status of the cohort on November 1, 2019, were determined. The data were summarized. Survival across each variable was compared using univariate log-rank tests, Cox proportional hazard models, and crude and adjusted models. A second wave analysis was performed excluding patients whose survival status was presumed.

RESULTS

A total of 503 patients were analyzed. The overall survival rate at 1, 3, and 5 years were 96.4%, 84.9%, and 79.0%, respectively, for the entire cohort. The molecular subtype was the most significant clinicopathological factor affecting overall survival. A younger age < 40 years, higher histologic grade, estrogen receptor-negative breast cancers, invasive ductal type breast cancers, and T1 lesions were associated with poorer survival outcomes at 5 years. The findings were reproduced after a second wave analysis excluding patients who were presumed alive was applied.

CONCLUSIONS

Breast cancer overall survival in Jamaica is consistent with that of other developing countries in the literature. This study is an important contribution to the growing body of literature available and aids to the overall understanding of the behavior of breast cancer locally.

DLA-H: A Deep Learning Accelerator for Histopathologic Image Classification

It is more than a decade since machine learning and especially its leading subtype deep learning have become one of the most interesting topics in almost all areas of science and industry. In numerous contexts, at least one of the applications of deep learning is utilized or is going to be utilized. Using deep learning for image classification is now very popular and widely used in various use cases. Many types of research in medical sciences have been focused on the advantages of deep learning for image classification problems. Some recent researches show more than 90% accuracy for breast tissue classification which is a breakthrough. A huge number of computations in deep neural networks are considered a big challenge both from software and hardware point of view. From the architectural perspective, this big amount of computing operations will result in high power consumption and computation runtime. This led to the emersion of deep learning accelerators which are designed mainly for improving performance and energy efficiency. Data reuse and localization are two great opportunities for achieving energy-efficient computations with lower runtime. Data flows are mainly designed based on these important parameters. In this paper, DLA-H and BJS, a deep learning accelerator, and its data flow for histopathologic image classification are proposed. The simulation results with the MAESTRO tool showed 756 cycles for total runtime and [Formula: see text] GFLOPS roofline throughput that is an extreme performance improvement in comparison to current general-purpose deep learning accelerators and data flows.

Circadian rhythm disrupting behaviours and cancer outcomes in breast cancer survivors: a systematic review

PURPOSE

Circadian rhythm disruptors (e.g., night-shift work) are risk factors for breast cancer, however studies on their association with prognosis is limited. A small but growing body of research suggests that altered sleep patterns and eating behaviours are potential mechanistic links between circadian rhythm disruptors and breast cancer. We therefore systematically summarised literature examining the influence of circadian rhythm disrupting behaviours on cancer outcomes in women with breast cancer.

METHODS

A systematic search of five databases from inception to January 2021 was conducted. Original research published in English, assessing the relationship between post-diagnosis sleep patters and eating behaviours, and breast cancer outcomes were considered. Risk of bias was assessed using the Newcastle-Ottawa Assessment Scale for Cohort Studies.

RESULTS

Eight studies published original evidence addressing sleep duration and/or quality (k = 7) and, eating time and frequency (k = 1). Longer sleep duration (≥ 9 h versus [referent range] 6-8 h) was consistently associated with increased risk of all outcomes of interest (HR range: 1.37-2.33). There was limited evidence to suggest that measures of better sleep quality are associated with lower risk of all-cause mortality (HR range: 0.29-0.97). Shorter nightly fasting duration (< 13 h versus ≥ 13 h) was associated with higher risk of all breast cancer outcomes (HR range: 1.21-1.36).

CONCLUSION

Our review suggests that circadian rhythm disrupting behaviours may influence cancer outcomes in women with breast cancer. While causality remains unclear, to further understand these associations future research directions have been identified. Additional well-designed studies, examining other exposures (e.g., light exposure, temporal eating patterns), biomarkers, and patient-reported outcomes, in diverse populations (e.g., breast cancer subtype-specific, socio-demographic diversity) are warranted.

Breast Amide Proton Transfer Imaging at 3 T: Diagnostic Performance and Association With Pathologic Characteristics

BACKGROUND

Amide proton transfer (APT) imaging has been increasingly applied in tumor characterization. However, its value in evaluating breast cancer remains undetermined.

PURPOSE

To assess the diagnostic performance of APT imaging in breast cancer and its association with prognostic histopathologic characteristics.

STUDY TYPE

Prospective.

SUBJECTS

Eighty-four patients with breast lesions.

FIELD STRENGTH/SEQUENCE

A 3.0 T/single-shot fast spin echo APT imaging.

ASSESSMENT

APTw signal in breast lesion was quantified. Lesion malignancy, T stage, grades, Ki-67 index, molecular biomarkers (estrogen receptor [ER] expression, progesterone receptor [PR] expression, human epidermal growth factor receptor [HER-2] expression), molecular subtypes (luminal A, luminal B, triple negative, and HER-2 enriched) were determined.

STATISTICAL TESTS

Student t-test, one-way analysis of variance, receiver operating characteristic analysis, and Pearson's correlation with P < 0.05 as statistical significance.

RESULTS

APTw signal was significantly higher in malignant lesions (1.55% ± 1.24%) than in benign lesions (0.54% ± 1.13%), and in grade III lesions than in grade II lesions (1.65% ± 0.84% vs. 0.96% ± 0.96%), and in T2- (1.57% ± 0.64%) and T3-stage lesions (1.54% ± 0.63%) than in T1-stage lesions (0.81% ± 0.64%) for invasive breast carcinoma of no special type. APTw signal significantly correlated with Ki-67 index (r = 0.364) but showed no significant difference in groups of ER (P = 0.069), PR (P = 0.069), HER-2 (P = 0.961), and among molecular subtypes (P = 0.073).

DATA CONCLUSION

APT imaging shows potential in differentiating breast lesion malignancy and associates with prognosis-related tumor grade, T stage, and proliferative activity.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Mortality rate and predictors among patients with breast cancer at a referral hospital in northwest Ethiopia: A retrospective follow-up study

BACKGROUND

Breast cancer is one of the common global health concerns that affects2.1 million women each year and causes the highest number of cancer-related morbidity and mortality among women. The objective of this study was to determine the mortality rate and its predictors among breast cancer patients at the referral hospitals, in northwest Ethiopia.

METHODS

A retrospective follow-up study was conducted on breast cancer patients registered between February 01, 2015 and February 28, 2018. They were selected by simple random sampling using computer-generated method and followed until February 29, 2020, in Amhara region referral hospital. A pre-tested data extraction checklist was used to collect data from the registration book and patient medical records. The collected data were entered into Epi-Data version 3.1 and exported to STATA version 14 for analysis. The mortality rate by person-year observation was computed. The Kaplan-Meier survival curve with the log-rank test was used to estimate the survival probabilities of the patients. Bivariate and multivariate Cox regression model was used to identify predictors of mortality.

RESULTS

The overall mortality rate of breast cancer was 16.9 per 100 person-years observation. The median survival time was 38.3 (IQR: 26.23, 49.4) months. Independent predictors of breast cancer mortality was; Clinical stage IV and stage III (aHR:10.44,95% CI: 8.02,11.93 and aHR: 9.43, 95% CI: 6.29,11.03respectively), number of positive lymph node in the category of 10 and more and number of positive lymph node within the category of 4-9 (aHR:12.58, 95%CI: 5.2, 30.46 and aHR: 4.78, 95% CI: 2.19, 10.43respectively), co-morbidities (aHR:1.5, 95%CI: 1.01,2.21), Postmenopausal (aHR:2.03,95% CI: 1.37, 3), histologic grade III (aHR:2.12, 95% CI: 1.26,3.55) and not received hormonal therapy (aHR: 2.19, 95%CI: 1.52,3.15) were independent predictors of mortality.

CONCLUSION

The overall mortality rate was 16.9 per 100 person-years. The finding was higher compared to high-income countries. Advanced clinical stage, co-morbidities, menopausal status, and hormonal therapy are the significant predictors of mortality. Early detection and treatment of breast cancer is needed to reduce the mortality rate.

DDX43 mRNA expression and protein levels in relation to clinicopathological profile of breast cancer

BACKGROUND

Breast cancer (BC) is the most often diagnosed cancer in women globally. Cancer cells appear to rely heavily on RNA helicases. DDX43 is one of DEAD- box RNA helicase family members. But, the relationship between clinicopathological, prognostic significance in different BC subtypes and DDX43 expression remains unclear. Therefore, the purpose of this study was to assess the clinicopathological significance of DDX43 protein and mRNA expression in different BC subtypes.

MATERIALS AND METHODS

A total of 80 females newly diagnosed with BC and 20 control females that were age-matched were recruited for this study. DDX43 protein levels were measured by ELISA technique. We used a real-time polymerase chain reaction quantification (real-time PCR) to measure the levels of DDX43 mRNA expression. Levels of DDX43 protein and mRNA expression within BC patients had been compared to those of control subjects and correlated with clinicopathological data.

RESULTS

The mean normalized serum levels of DDX43 protein were slightly higher in control than in both benign and malignant groups, but this result was non-significant. The mean normalized level of DDX43 mRNA expression was higher in the control than in both benign and malignant cases, although the results were not statistically significant and marginally significant, respectively. Moreover, the mean normalized level of DDX43 mRNA expression was significantly higher in benign than in malignant cases. In malignant cases, low DDX43 protein expression was linked to higher nuclear grade and invasive duct carcinoma (IDC), whereas high mRNA expression was linked to the aggressive types of breast cancer such as TNBC, higher tumor and nuclear grades.

CONCLUSION

This study explored the potential of using blood DDX43 mRNA expression or protein levels, or both in clinical settings as a marker of disease progression in human breast cancer. DDX43 mRNA expression proposes a less invasive method for discriminating benign from malignant BC.

Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological images

Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems based on deep learning have shown that deep learning may achieve reliable accuracy in IDC grade classification using histopathology images. However, there is a dearth of comprehensive performance comparisons of Convolutional Neural Network (CNN) designs on IDC in the literature. As such, we would like to conduct a comparison analysis of the performance of seven selected CNN models: EfficientNetB0, EfficientNetV2B0, EfficientNetV2B0-21k, ResNetV1-50, ResNetV2-50, MobileNetV1, and MobileNetV2 with transfer learning. To implement each pre-trained CNN architecture, we deployed the corresponded feature vector available from the TensorFlowHub, integrating it with dropout and dense layers to form a complete CNN model. Our findings indicated that the EfficientNetV2B0-21k (0.72B Floating-Point Operations and 7.1 M parameters) outperformed other CNN models in the IDC grading task. Nevertheless, we discovered that practically all selected CNN models perform well in the IDC grading task, with an average balanced accuracy of 0.936 ± 0.0189 on the cross-validation set and 0.9308 ± 0.0211on the test set.

Comparison of the Nottingham Prognostic Index and OncotypeDX© recurrence score in predicting outcome in estrogen receptor positive breast cancer

INTRODUCTION

Traditionally, Nottingham prognostic index (NPI) informed prognosis in patients with estrogen receptor positive, human epidermal growth factor receptor-2 negative, node negative (ER+/HER2-/LN-) breast cancer. At present, OncotypeDX© Recurrence Score (RS) predicts prognosis and response to adjuvant chemotherapy (AC).

AIMS

To compare NPI and RS for estimating prognosis in ER + breast cancer.

METHODS

Consecutive patients with ER+/HER2-/LN- disease were included. Disease-free (DFS) and overall survival (OS) were determined using Kaplan-Meier and Cox regression analyses.

RESULTS

1471 patients met inclusion criteria. The mean follow-up was 110.7months. NPI was calculable for 1382 patients: 19.8% had NPI≤2.4 (291/1471), 33.0% had NPI 2.41-3.4 (486/1471), 30.0% had NPI 3.41-4.4 (441/1471), 10.9% had NPI 4.41-5.4 (160/1471), and 0.3% had NPI>5.4 (4/1471). In total, 329 patients underwent RS (mean RS: 18.7) and 82.1% had RS < 25 (270/329) and 17.9% had RS ≥ 25 (59/329). Using multivariable Cox regression analyses (n = 1382), NPI independently predicted DFS (Hazard ratio (HR): 1.357, 95% confidence interval (CI): 1.140-1.616, P < 0.001) and OS (HR: 1.003, 95% CI: 1.001-1.006, P = 0.024). When performing a focused analysis of those who underwent both NPI and RS (n = 329), neither biomarker predicted DFS or OS. Using Kaplan Meier analyses, NPI category predicted DFS (P = 0.008) and (P = 0.026) OS. Conversely, 21-gene RS group failed to predict DFS (P = 0.187) and OS (P = 0.296).

CONCLUSION

In our focused analysis, neither NPI nor RS predicted survival outcomes. However, in the entire series, NPI independently predicted both DFS and OS. On the 40th anniversary since its derivation, NPI continues to provide accurate prognostication in breast cancer, outperforming RS in the current study.

Cytological Grading of Breast Carcinomas and Its Prognostic Implications

Introduction

Determining the histological grade of breast carcinomas before mastectomy is necessary to decide about neoadjuvant chemotherapy. Core needle biopsies used for this purpose often under-grade the tumour. The grade obtained from fine needle aspiration cytology samples will help in such situations and whenever biopsy is not done, as in a resource-poor setup. Many studies are being done to find out the cytological grading system that correlates well with histological grading.

Methods

This study was done between 2016 and 2019 including the cases in which both modified radical mastectomy and fine needle aspiration of the tumour had been done. Robinson’s cytological grading was done in Papanicolaou and haematoxylin & eosin (H&E) stained cytology smears and correlated with modified Bloom-Richardson histologic grading done in modified radical mastectomy specimens. We also studied the prognostic significance of Robinson’s method by studying the association between cytological grade and lymph node metastasis.

Results

Sixty cases were studied. The two methods had the same grade in 49 (81.7%) cases. They showed a significant positive correlation (Spearman correlation coefficient 0.848, p-0.0001), significant association (Chi-square test, p-0.0001), and substantial agreement (kappa value 0.72). Multiple regression analysis showed chromatin score and nucleoli score as the most influential parameters. Lymph node metastasis showed significant association with cytological grade (p-0.0003), cell dissociation score (p-0.0001), nucleoli score (p-0.01), and chromatin score (p-0.04).

Conclusion

Robinson’s cytological grading is a simple, reliable adjunct/alternative to core needle biopsies for grading breast carcinomas before mastectomy. Hence, it can be made a part of routine cytology reporting of breast carcinomas. Further long-term studies will help in confirming its prognostic significance.

The current staging and classification systems of breast cancer and their pitfalls: Is it possible to integrate the complexity of this neoplasm into a unified staging system?

Breast cancer is one of the leading causes of cancer death in women worldwide due to its variable aggressiveness and high propensity to develop distant metastases. The staging can be performed clinically or pathologically, generating the stage stratification by the TNM (T - tumor size; N- lymph node metastasis; M - distant organ metastasis) system. However, cancers with virtually identical TNM characteristics can present highly contrasting behaviors due to the divergence of molecular profiles. This review focuses on the histopathological nuances and molecular understanding of breast cancer through the profiling of gene and protein expression, culminating in improvements promoted by the integration of this information into the traditional staging system. As a culminating point, it will highlight predictive statistical tools for genomic risks and decision algorithms as a possible solution to integrate the various systems because they have the potential to reduce the indications for such tests, serving as a funnel in association with staging and previous classification.

The Chaperone System in Breast Cancer: Roles and Therapeutic Prospects of the Molecular Chaperones Hsp27, Hsp60, Hsp70, and Hsp90

Breast cancer (BC) is a major public health problem, with key pieces of information needed for developing preventive and curative measures still missing. For example, the participation of the chaperone system (CS) in carcinogenesis and anti-cancer responses is poorly understood, although it can be predicted to be a crucial factor in these mechanisms. The chief components of the CS are the molecular chaperones, and here we discuss four of them, Hsp27, Hsp60, Hsp70, and Hsp90, focusing on their pro-carcinogenic roles in BC and potential for developing anti-BC therapies. These chaperones can be targets of negative chaperonotherapy, namely the elimination/blocking/inhibition of the chaperone(s) functioning in favor of BC, using, for instance, Hsp inhibitors. The chaperones can also be employed in immunotherapy against BC as adjuvants, together with BC antigens. Extracellular vesicles (EVs) in BC diagnosis and management are also briefly discussed, considering their potential as easily accessible carriers of biomarkers and as shippers of anti-cancer agents amenable to manipulation and controlled delivery. The data surveyed from many laboratories reveal that, to enhance the understanding of the role of the CS in BS pathogenesis, one must consider the CS as a physiological system, encompassing diverse members throughout the body and interacting with the ubiquitin–proteasome system, the chaperone-mediated autophagy machinery, and the immune system (IS). An integrated view of the CS, including its functional partners and considering its highly dynamic nature with EVs transporting CS components to reach all the cell compartments in which they are needed, opens as yet unexplored pathways leading to carcinogenesis that are amenable to interference by anti-cancer treatments centered on CS components, such as the molecular chaperones.

Contralateral Breast Screening with Preoperative MRI: Long-Term Outcomes for Newly Diagnosed Breast Cancer

Background The diagnostic value of screening the contralateral breast with MRI in patients with newly diagnosed breast cancer is poorly understood. Purpose To assess the impact of MRI for screening the contralateral breast on long-term outcomes in patients with newly diagnosed breast cancer and to determine whether subgroups with unfavorable prognoses would benefit from MRI in terms of survival. Materials and Methods Data on consecutive patients with newly diagnosed breast cancer seen from January 2008 to December 2010 were reviewed retrospectively. Patients with neoadjuvant chemotherapy, previous breast cancer, distant metastasis, absence of contralateral mammography at diagnosis, and no planned surgical treatment were excluded. Groups that did and did not undergo preoperative MRI were compared. Survival analysis was performed using the Kaplan-Meier method for propensity score-matched groups to estimate cause-specific survival (CSS) and overall survival (OS). A marginal Cox proportional hazards model was used to evaluate association of MRI and clinicopathologic variables with OS. Results Of 1846 patients, 1199 fulfilled the inclusion criteria. Median follow-up time was 10 years (range, 0-14 years). The 2:1 matched sample comprised 705 patients (470 in the MRI group and 235 in the no-MRI group); median ages at surgery were 59 years (range, 31-87 years) and 64 years (range, 37-92 years), respectively. MRI depicted contralateral synchronous disease more frequently (27 of 470 patients [5.7%] vs five of 235 patients [2.1%]; P = .047) and was associated with a higher OS (hazard ratio [HR], 2.51; 95% CI: 1.25, 5.06; P = .01). No differences were observed between groups in metachronous disease rate (MRI group: 21 of 470 patients [4.5%]; no-MRI group: 10 of 235 patients [4.3%]; P > .99) or CSS (HR, 1.34; 95% CI: 0.56, 3.21; P = .51). MRI benefit was greater in patients with larger tumor sizes (>2 cm) (HR, 2.58; 95% CI: 1.11, 5.99; P = .03) and histologic grade III tumors (HR, 2.94; 95% CI: 1.18, 7.32; P = .02). Conclusion Routine MRI screening of the contralateral breast after first diagnosis of breast cancer improved overall survival; the most pronounced benefit was found in patients with larger primary tumor size and primary tumors of histologic grade III. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Taourel in this issue.

Definition of High-Risk Early Hormone-Positive HER2−Negative Breast Cancer: A Consensus Review

Breast cancer is one of the major causes of cancer-related morbidity and mortality in women worldwide. During the past three decades, several improvements in the adjuvant treatment of hormone receptor-positive/HER2−negative breast cancer have been achieved with the introduction of optimized adjuvant chemotherapy and endocrine treatment. However, estimating the risk of relapse of breast cancer on an individual basis is still challenging. The IRIDE (hIGh Risk DEfinition in breast cancer) working group was established with the aim of reviewing evidence from the literature to synthesize the current relevant features that predict hormone-positive/HER2−negative early breast cancer relapse. A panel of experts in breast cancer was involved in identifying clinical, pathological, morphological, and genetic factors. A RAND consensus method was used to define the relevance of each risk factor. Among the 21 features included, 12 were considered relevant risk factors for relapse. For each of these, we provided a consensus statement and relevant comments on the supporting scientific evidence. This work may guide clinicians in the practical management of hormone-positive/HER2−negative early breast cancers.

Chick Chorioallantoic Membrane (CAM) Assays as a Model of Patient-Derived Xenografts from Circulating Cancer Stem Cells (cCSCs) in Breast Cancer Patients

Simple Summary

Circulating cancer cells—and in particular their very rare subpopulation, circulating cancer stem cells (cCSCs)—are responsible for recurrence and metastasis. In this study, we present a novel process in which patient-derived xenograft (PDX) can be harvested on chorioallantoic membrane (CAM) from circulating cancer stem cells. In our opinion, the CAM-based PDX model using circulating cancer stem cells can provide a fast, low-cost, easy-to-use, and efficient preclinical platform for drug screening, therapy optimization, and biomarker discovery.

Abstract

Background: cCSCs are a small subset of circulating tumor cells with cancer stem cell features: resistance to cancer treatments and the capacity for generating metastases. PDX are an appreciated tool in oncology, providing biologically meaningful models of many cancer types, and potential platforms for the development of precision oncology approaches. Commonly, mouse models are used for the in vivo assessment of potential new therapeutic targets in cancers. However, animal models are costly and time consuming. An attractive alternative to such animal experiments is the chicken chorioallantoic membrane assay. Methods: In this study, primary cultures from cCSCs were established using the sphere-forming assay. Subsequently, tumorspheres were transplanted onto the CAM membrane of fertilized chicken eggs to form secondary microtumors. Results: We have developed an innovative in vitro platform for cultivation of cCSCs from peripheral blood of cancer patients. The number of tumorspheres increased significantly with tumor progression and aggressiveness of primary tumor. The number of tumorspheres was positively correlated with Ki-67, Her2 status, and grade score in primary breast tumors. The grafting of tumorspheres onto the CAM was successful and positively correlated with aggressiveness and proliferation capacity of the primary tumor. These tumors pathologically closely resembled the primary tumor. Conclusions: The number of tumorspheres cultured from peripheral blood and the success rate of establishing PDX directly reflect the aggressiveness and proliferation capacity of the primary tumor. A CAM-based PDX model using cCSC provides a fast, low-cost, easy to handle, and powerful preclinical platform for drug screening, therapy optimization, and biomarker discovery.

Lymphovascular invasion has a significant prognostic impact in patients with early breast cancer, results from a large, national, multicenter, retrospective cohort study

Background

We determined the prognostic impact of lymphovascular invasion (LVI) in a large, national, multicenter, retrospective cohort of patients with early breast cancer (BC) according to numerous factors.

Patients and methods

We collected data on 17 322 early BC patients treated in 13 French cancer centers from 1991 to 2013. Survival functions were calculated using the Kaplan–Meier method and multivariate survival analyses were carried out using the Cox proportional hazards regression model adjusted for significant variables associated with LVI or not. Two propensity score-based matching approaches were used to balance differences in known prognostic variables associated with LVI status and to assess the impact of adjuvant chemotherapy (AC) in LVI-positive luminal A-like patients.

Results

LVI was present in 24.3% (4205) of patients. LVI was significantly and independently associated with all clinical and pathological characteristics analyzed in the entire population and according to endocrine receptor (ER) status except for the time period in binary logistic regression. According to multivariate analyses including ER status, AC, grade, and tumor subtypes, the presence of LVI was significantly associated with a negative prognostic impact on overall (OS), disease-free (DFS), and metastasis-free survival (MFS) in all patients [hazard ratio (HR) = 1.345, HR = 1.312, and HR = 1.415, respectively; P < 0.0001], which was also observed in the propensity score-based analysis in addition to the association of AC with a significant increase in both OS and DFS in LVI-positive luminal A-like patients. LVI did not have a significant impact in either patients with ER-positive grade 3 tumors or those with AC-treated luminal A-like tumors.

Conclusion

The presence of LVI has an independent negative prognostic impact on OS, DFS, and MFS in early BC patients, except in ER-positive grade 3 tumors and in those with luminal A-like tumors treated with AC. Therefore, LVI may indicate the existence of a subset of luminal A-like patients who may still benefit from adjuvant therapy.

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In a study of 17 322 early BC patients, LVI had a significant independent negative prognostic impact on survival.

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LVI negatively impacted survival in almost every patient category and cancer subtype, with and without AC.

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LVI did not have a negative survival impact in patients with ER+ grade 3 or with luminal A-like tumors with chemotherapy.

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Results suggest a possible benefit of AC in LVI-positive luminal A-like patients.

Sentinel node involvement with or without completion axillary lymph node dissection: treatment and pathologic results of randomized SERC trial

Based on results of clinical trials, completion ALND (cALND) is frequently not performed for patients with breast conservation therapy and one or two involved sentinel nodes (SN) by micro- or macro-metastases. However, there were limitations despite a conclusion of non-inferiority for cALND omission. No trial had included patients with SN macro-metastases and total mastectomy or with >2 SN macro-metastases. The aim of the study was too analyze treatment delivered and pathologic results of patients included in SERC trial. SERC trial is a multicenter randomized non-inferiority phase-3 trial comparing no cALND with cALND in cT0-1-2, cN0 patients with SN ITC (isolated tumor cells) or micro-metastases or macro-metastases, mastectomy or breast conservative surgery. We randomized 1855 patients, 929 to receive cALND and 926 SLNB alone. No significant differences in patient’s and tumor characteristics, type of surgery, and adjuvant chemotherapy (AC) were observed between the two arms. Rates of involved SN nodes by ITC, micro-metastases, and macro-metastases were 5.91%, 28.12%, and 65.97%, respectively, without significant difference between two arms for all criteria. In multivariate analysis, two factors were associated with higher positive non-SN rate: no AC versus AC administered after ALND (OR = 3.32, p < 0.0001) and >2 involved SN versus ≤2 (OR = 3.45, p = 0.0258). Crude rates of positive NSN were 17.62% (74/420) and 26.45% (73/276) for patient’s eligible and non-eligible to ACOSOG-Z0011 trial. No significant differences in patient’s and tumor characteristics and treatment delivered were observed between the two arms. Higher positive-NSN rate was observed for patients with AC performed after ALND (17.65% for SN micro-metastases, 35.22% for SN macro-metastases) in comparison with AC administered before ALND.

Type 2 Diabetes Mellitus and Clinicopathological Tumor Characteristics in Women Diagnosed with Breast Cancer: A Systematic Review and Meta-Analysis

Poor prognosis caused by type 2 diabetes mellitus (T2DM) in women with breast cancer is conferred, while the association between T2DM and breast tumor aggressiveness is still a matter of debate. This study aimed to clarify the differences in breast cancer characteristics, including stage, size, lymph node status, grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (Her2), between patients with and without pre-existing T2DM. PubMed, Embase, and Web of Science were searched for studies from 1 January 2010 to 2 July 2021. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were pooled by using a random effects model. T2DM was significantly associated with tumor stages III/IV versus cancers in situ and stages I/II (pooled ORs (pOR), 95% CI: 1.19; 1.04-1.36, p = 0.012), tumor size >20 versus ≤20 mm (pOR, 95% CI: 1.18; 1.04-1.35, p = 0.013), and lymph node invasion versus no involvement (pOR, 95% CI: 1.26; 1.05-1.51, p = 0.013). These findings suggest that women with T2DM are at a higher risk of late-stage tumors, large tumor sizes, and invasive lymph nodes at breast cancer diagnosis.

Breast Cancer in Jamaica: Stage, Grade and Molecular Subtype Distributions Across Age Blocks, the Implications for Screening and Treatment

Background

Breast cancer is the most commonly diagnosed and leading cause of cancer-related morbidity and mortality in females worldwide. Significant disparities exist in breast cancer incidence and mortalities between low- to middle- and high-income countries. The purpose of this study was to analyze the distribution of prognostic and predictive clinicopathological features of invasive breast cancer at a single institution in Jamaica across three age groups.

Methods

Data from patients diagnosed with invasive breast cancer who underwent definitive surgery between August 2017 and September 2018 were identified. The patients were divided into three age groups (< 50, 50 - 59 and > 59 years) and the distribution of tumor size, grade, molecular subtype, nodal status and anatomic stage were determined and compared with the US population registry. Comparisons of the various characteristics were performed using the Fisher’s exact test.

Results

Ninety-nine definitive operations were performed and met the criteria for analysis. Average age at the time of diagnosis was 54 years compared to 62 years reported in the US databases. Thirty-six percent of the patients presented below age 50 years, which was twice the corresponding rate reported for Caucasian females (18%) in the USA. Fifty percent of patients in our registry had axillary lymph node metastases at presentation and they were younger than patients with negative axillary nodes (95% confidence interval (CI) -12.06 to -1.93, P = 0.007). Patients in the age group less than age 50 years were more likely to have advanced stage, high histological grade cancers compared to the older age blocks (95% CI 0.039 - 0.902, P = 0.033).

Conclusion

Invasive breast cancer presents at an earlier age in Jamaican women and is associated with poor prognostic features such as high rates of axillary lymph node metastases, high histological grade, advanced stage, triple-negative subtypes and low luminal A subtypes.

American Joint Committee on Cancer's Staging System for Breast Cancer, Eighth Edition: Summary for Clinicians

Breast cancer is commonly staged using the American Joint Committee on Cancer (AJCC) staging system. The 7^th edition of the AJCC Staging Manual, was a purely anatomic staging method, which uses primary tumor size (T), nodal involvement (N), and metastasis (M) based on clinical and pathological evaluations. Advancements in tumor biology and prognostic biological markers, such as estrogen receptor (ER)/progesterone receptor (PR), HER2/neu, and Ki-67, have allowed clinicians to understand why similarly staged patients had significantly different outcomes. The most recent update to the staging system integrates molecular markers with disease extent for more optimal estimation of prognosis. This change improves the prognosis of breast cancer patients and better informs physicians in the planning of treatments. This review summarizes the changes in the AJCC Staging Manual, 8^th edition and their impact on practicing radiologists in breast cancer management.

Expanding Criteria for Prognostic Stage IA in Hormone Receptor-Positive Breast Cancer

BACKGROUND

The prognostic significance of patients with low-risk recurrence score (RS) results in the context of the American Joint Committee on Cancer (AJCC) eighth edition pathologic prognostic staging has not been investigated. We evaluated if expanded RS criteria can be considered for downstaging in AJCC pathologic prognostic staging.

METHODS

Using Surveillance, Epidemiology, and End Results data, we identified patients with T1-3N0-3M0 hormone receptor-positive, HER2-negative breast cancer treated from 2010 to 2015 with follow-up data through 2016. We evaluated TNM categories, grade, and RS result. The primary outcome measured was 5-year disease-specific survival (DSS) of patients with low-risk RS results not already pathologic prognostic stage IA, determined by T and N categories per AJCC eighth edition. All statistical tests were 2-sided.

RESULTS

Of 154 050 patients with median follow-up of 49 months (range = 0-83), RS results were obtained in 60 886 (39.5%): RS was less than 11 in 13 570 (22.3%); 11-17 in 22 719 (37.3%); 18-25 in 16 521 (27.1%); and 26 or higher in 8076 (13.3%). Five-year DSS for pathologic prognostic stage IA patients (n = 114 910, 74.6%) was 98.8%. Among N0-1 patients with a RS less than 18 not staged as pathologic prognostic stage IA by current criteria, 5-year DSS was excellent and not statistically significantly different than for pathologic prognostic stage IA patients (97.2%-99.7%; P > .05). For those with a RS of 18-25, there was a small decrease in DSS for T2N0 (2.3%) and modest decrease for T1-2N1 (4.2%-6.4%) compared with pathologic prognostic stage IA patients (P < .001).

CONCLUSION

Patients with a RS less than 18 have excellent 5-year DSS regardless of T category for N0-1 disease suggesting further modification of the AJCC staging system using this cutoff.

Lack of prognostic impact of sentinel node micro-metastases in endocrine receptor-positive early breast cancer: results from a large multicenter cohort☆

Background

Prognostic impact of lymph node micro-metastases (pN1mi) has been discordantly reported in the literature. The need to clarify this point for decision-making regarding adjuvant therapy, particularly for patients with endocrine receptor (ER)-positive status and HER2-negative tumors, is further reinforced by the generalization of gene expression signatures using pN status in their recommendation algorithm.

Patients and methods

We retrospectively analyzed 13 773 patients treated for ER-positive breast cancer in 13 French cancer centers from 1999 to 2014. Five categories of axillary lymph node (LN) status were defined: negative LN (pN0i−), isolated tumor cells [pN0(i+)], pN1mi, and pN1 divided into single (pN1 = 1) and multiple (pN1 > 1) macro-metastases (>2 mm). The effect of LN micro-metastases on outcomes was investigated both in the entire cohort of patients and in clinically relevant subgroups according to tumor subtypes. Propensity-score-based matching was used to balance differences in known prognostic variables associated with pN status.

Results

As determined by sentinel LN biopsy, 9427 patients were pN0 (68.4%), 546 pN0(i+) (4.0%), 1446 pN1mi (10.5%) and 2354 pN1 with macro-metastases (17.1%). With a median follow-up of 61.25 months, pN1 status, but not pN1mi, significantly impacted overall survival (OS), disease-free survival (DFS), metastasis-free survival (MFS), and breast-cancer-specific survival. In the subgroup of patients with known tumor subtype, pN1 = 1, as pN1 > 1, but not pN1mi, had a significant prognostic impact on OS. DFS and MFS were only impacted by pN1 > 1. Similar results were observed in the subgroup of patients with luminal A-like tumors (n = 7101). In the matched population analysis, pN1macro, but not pN1mi, had a statistically significant negative impact on MFS and OS.

Conclusion

LN micro-metastases have no detectable prognostic impact and should not be considered as a determining factor in indicating adjuvant chemotherapy. The evaluation of the risk of recurrence using second-generation signatures should be calculated considering micro-metastases as pN0.

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LN micro-metastases have no detectable prognostic impact.

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pN1 status, but not pN1mi, significantly impacted overall survival, disease-free survival, metastasis-free survival.

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In the subgroup of patients with known tumor subtype, pN1=1, as pN1>1, but not pN1mi, had a significant prognostic impact on OS.

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LN micro-metastases should not be considered as a determining factor in indicating adjuvant chemotherapy.

Clinicopathological and prognostic significance of programmed cell death ligand 1 expression in patients diagnosed with breast cancer: meta-analysis

BACKGROUND

Uncertainty exists regarding the clinical relevance of programmed cell death ligand 1 (PD-L1) expression in breast cancer.

METHODS

A systematic review was performed in accordance with PRISMA guidelines. Observational studies that compared high versus low expression of PD-L1 on breast cancer cells were identified. Log hazard ratios (HRs) for disease-free and overall survival and their standard errors were calculated from Kaplan-Meier curves or Cox regression analyses, and pooled using the inverse-variance method. Dichotomous variables were pooled as odds ratios (ORs) using the Mantel-Haenszel method.

RESULTS

Sixty-five studies with 19 870 patients were included; 14 404 patients were classified as having low and 4975 high PD-L1 expression. High PD-L1 was associated with achieving a pathological complete response following neoadjuvant chemotherapy (OR 3.30, 95 per cent confidence interval 1.19 to 9.16; P < 0.01; I2 = 85 per cent). Low PD-L1 expression was associated with human epidermal growth factor receptor 2 (OR 3.98, 1.81 to 8.75; P < 0.001; I2 = 96 per cent) and luminal (OR 14.93, 6.46 to 34.51; P < 0.001; I2 = 99 per cent) breast cancer subtypes. Those with low PD-L1 had favourable overall survival rates (HR 1.30, 1.05 to 1.61; P = 0.02; I2 = 85 per cent).

CONCLUSION

Breast cancers with high PD-L1 expression are associated with aggressive clinicopathological and immunohistochemical characteristics and are more likely to achieve a pathological complete response following neoadjuvant chemotherapy. These breast cancers are, however, associated with worse overall survival outcomes.

Variability in Breast Cancer Biomarker Assessment and the Effect on Oncological Treatment Decisions: A Nationwide 5-Year Population-Based Study

We compared estrogen receptor (ER), progesterone receptor (PR), human epidermal growth-factor receptor 2 (HER2), Ki67, and grade scores among the pathology departments in Sweden. We investigated how ER and HER2 positivity rates affect the distribution of endocrine and HER2-targeted treatments among oncology departments. All breast cancer patients diagnosed between 2013 and 2018 in Sweden were identified in the National Quality Register for Breast Cancer. Cases with data on ER, PR, HER2, Ki67, grade, and treatment were selected (43,261 cases from 29 departments following the guidelines for biomarker testing). The ER positivity rates ranged from 84.2% to 97.6% with 6/29 labs out of the overall confidence intervals (CIs), while PR rates varied between 64.8% and 86.6% with 7/29 labs out of the CIs. HER2 positivity rates ranged from 9.4% to 16.3%, with 3/29 labs out of the overall CIs. Median Ki67 varied between 15% and 30%, where 19/29 labs showed significant intra-laboratory variability. The proportion of grade-II cases varied between 42.9% and 57.1%, and 13/29 labs were outside of the CI. Adjusting for patient characteristics, the proportion of endocrine and anti-HER2 treatments followed the rate of ER and HER2 positivity, illustrating the clinical effect of inter- and intra-laboratory variability. There was limited variability among departments in ER, PR, and HER2 testing. However, even a few outlier pathology labs affected endocrine and HER2-targeted treatment rates in a clinically relevant proportion, suggesting the need for improvement. High variability was found in grading and Ki67 assessment, illustrating the need for the adoption of new technologies in practice.

Adjuvant chemotherapy and survival outcome in node-negative breast cancer with a 21-gene recurrence score of 26-30

Aim: To investigate the benefit of chemotherapy among early-stage breast cancer patients with 21-gene recurrence scores of 26-30. Methods: We identified 3754 patients in the Surveillance, Epidemiology, and End Results database. Results: 57.6% of the patients received adjuvant chemotherapy. Patients with higher tumor grade, larger tumors and younger age were more likely to receive chemotherapy. The receipt of chemotherapy was independently associated with better breast cancer-specific survival than in patients without chemotherapy before (p = 0.016) and after (p = 0.043) propensity score matching. The sensitivity analyses showed that survival gain was pronounced in patients with poorly differentiated or undifferentiated disease. Conclusions: Adjuvant chemotherapy improves the outcome for early-stage breast cancer with 21-gene recurrence score of 26-30, especially for patients with high-grade tumors.

Breast Cancer Staging: Updates in the AJCC Cancer Staging Manual, 8th Edition, and Current Challenges for Radiologists, From the AJR Special Series on Cancer Staging

The standardization of the AJCC TNM staging system for breast cancer allows physicians to evaluate patients with breast cancer using standard language and criteria, assess treatment response, and compare patient outcomes. Previous editions of the AJCC Cancer Staging Manual relied on the anatomic TNM method of staging that incorporates imaging and uses population-level survival data to predict patient outcomes. Recent advances in therapy based on biomarker status and multigene panels have improved treatment strategies. In the newest edition of the AJCC Cancer Staging Manual (8th edition, adopted on January 1, 2018), breast cancer staging integrates anatomic staging with tumor grade, biomarker data regarding hormone receptor status, oncogene expression, and gene expression profiling to assign a prognostic stage. This article reviews the 8th edition of the AJCC breast cancer staging system with a focus on anatomic staging and the challenges that anatomic staging poses for radiologists. We highlight key imaging findings that impact patient treatment and discuss the role of imaging in evaluating response to neoadjuvant therapy. Finally, we discuss biomarkers and multigene panels and how these impact prognostic stage. The review will help radiologists identify critical findings that affect breast cancer staging and understand ongoing limitations of imaging in staging.

Molecular Biomarkers for Contemporary Therapies in Hormone Receptor-Positive Breast Cancer

Systemic treatment of hormone receptor-positive (HR+) breast cancer is undergoing a renaissance, with a number of targeted therapies including CDK4/6, mTOR, and PI3K inhibitors now approved for use in combination with endocrine therapies. The increased use of targeted therapies has changed the natural history of HR+ breast cancers, with the emergence of new escape mechanisms leading to the inevitable progression of disease in patients with advanced cancers. The identification of new predictive and pharmacodynamic biomarkers to current standard-of-care therapies and discovery of new therapies is an evolving and urgent clinical challenge in this setting. While traditional, routinely measured biomarkers such as estrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2) still represent the best prognostic and predictive biomarkers for HR+ breast cancer, a significant proportion of patients either do not respond to endocrine therapy or develop endocrine resistant disease. Genomic tests have emerged as a useful adjunct prognostication tool and guide the addition of chemotherapy to endocrine therapy. In the treatment-resistant setting, mutational profiling has been used to identify ESR1, PIK3CA, and AKT mutations as predictive molecular biomarkers to newer therapies. Additionally, pharmacodynamic biomarkers are being increasingly used and considered in the metastatic setting. In this review, we summarise the current state-of-the-art therapies; prognostic, predictive, and pharmacodynamic molecular biomarkers; and how these are impacted by emerging therapies for HR+ breast cancer.

Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer

One of the most frequently identified tumors and a contributing cause of death in women is breast cancer (BC). Many biomarkers associated with survival and prognosis were identified in previous studies through database mining. Nevertheless, the predictive capabilities of single-gene biomarkers are not accurate enough. Genetic signatures can be an enhanced prediction method. This research analyzed data from The Cancer Genome Atlas (TCGA) for the detection of a new genetic signature to predict BC prognosis. Profiling of mRNA expression was carried out in samples of patients with TCGA BC (n = 1222). Gene set enrichment research has been undertaken to classify gene sets that vary greatly between BC tissues and normal tissues. Cox models for additive hazards regression were used to classify genes that were strongly linked to overall survival. A subsequent Cox regression multivariate analysis was used to construct a predictive risk parameter model. Kaplan–Meier survival predictions and log-rank validation have been used to verify the value of risk prediction parameters. Seven genes (PGK1, CACNA1H, IL13RA1, SDC1, AK3, NUP43, SDC3) correlated with glycolysis were shown to be strongly linked to overall survival. Depending on the 7-gene-signature, 1222 BC patients were classified into subgroups of high/low-risk. Certain variables have not impaired the prognostic potential of the seven-gene signature. A seven-gene signature correlated with cellular glycolysis was developed to predict the survival of BC patients. The results include insight into cellular glycolysis mechanisms and the detection of patients with poor BC prognosis.

Staging for Breast Cancer With Internal Mammary Lymph Nodes Metastasis: Utility of Incorporating Biologic Factors

Purpose

To validate the 8th edition of the American Joint Committee on Cancer (AJCC) pathological prognostic staging system for breast cancer patients with internal mammary lymph nodes (IMN) metastasis (N3b disease, stage IIIC in 7th AJCC anatomical staging).

Methods

Breast cancer patients with IMN metastasis diagnosed between 2010 and 2014 were retrieved from the Surveillance, Epidemiology, and End Results program. Chi-squared test, Log-rank test, Kaplan-Meier method, and Cox proportional hazard analysis were applied to statistical analysis.

Results

We included 678 patients with N3b disease in this study. Overall, 68.4% of patients were downstaged to IIIA and IIIB diseases from the 7th anatomical staging to 8th pathological prognostic staging. The new pathological prognostic staging system had better discriminatory value on prognosis prediction among IMN-metastasized breast cancer patients, with a 5-year breast cancer-specific survival (BCSS) of 92.7, 77.4, and 66.0% in stage IIIA, IIIB, and IIIC diseases, respectively (P<0.0001), and the 5-year overall survival (OS) rates was 85.9, 72.1, and 58.7%, respectively (P<0.0001). The results of the multivariate prognostic analysis showed that the new pathological prognostic staging was the independent prognosis related to BCSS and OS, the 8th AJCC pathological prognostic stages showed worse BCSS and OS with gradually increased hazard ratios.

Conclusion

The 8th AJCC pathological prognostic staging system offers more refined prognostic stratification to IMN-metastasized breast cancer patients and endorses its use in routine clinical practice for this specific subgroup of breast cancer.

Preoperative prediction of histologic grade in invasive breast cancer by using contrast-enhanced spectral mammography-based radiomics

OBJECTIVE

To develop and validate a radiomics model based on contrast-enhanced spectral mammography (CESM), and preoperatively discriminate low-grade (grade I/II) and high-grade (grade III) invasive breast cancer.

METHOD

A total of 205 patients with CESM examination and pathologically confirmed invasive breast cancer were retrospectively enrolled. We randomly divided patients into two independent sets namely, training set (164 patients) and test set (41 patients) with a ratio of 8:2. Radiomics features were extracted from the low-energy and subtracted images. The least absolute shrinkage and selection operator (LASSO) logistic regression were established for feature selection, which were then utilized to construct three classification models namely, low energy, subtracted images and their combined model to discriminate high- and low-grade invasive breast cancer. Receiver operator characteristic (ROC) curves were used to confirm performance of three models in training set. The clinical usefulness was evaluated by using decision curve analysis (DCA). An independent test set was used to confirm the discriminatory power of the models. To test robustness of the result, we used 100 times LGOCV (leave group out cross validation) to validate three models.

RESULTS

From initial radiomics feature pool, 17 and 11 features were selected for low-energy image and subtracted image, respectively. The combined model using 28 features showed the best performance for preoperatively evaluating the histologic grade of invasive breast cancer, with an area under the curve, AUC = 0.88, and 95%confidence interval [CI] 0.85 to 0.92 in the training set and AUC = 0.80 (95%CI 0.67 to 0.92) in the test set. The mean AUC of LGOCV is 0.82.

CONCLUSIONS

CESM-based radiomics model is a non-invasive predictive tool that demonstrates good application prospects in preoperatively predicting histological grade of invasive breast cancer.

Prognostic value of depression and anxiety on breast cancer recurrence and mortality: a systematic review and meta-analysis of 282,203 patients

Depression and anxiety are common comorbidities in breast cancer patients. Whether depression and anxiety are associated with breast cancer progression or mortality is unclear. Herein, based on a systematic literature search, 17 eligible studies involving 282,203 breast cancer patients were included. The results showed that depression was associated with cancer recurrence [1.24 (1.07, 1.43)], all-cause mortality [1.30 (1.23, 1.36)], and cancer-specific mortality [1.29 (1.11, 1.49)]. However, anxiety was associated with recurrence [1.17 (1.02, 1.34)] and all-cause mortality [1.13 (1.07, 1.19)] but not with cancer-specific mortality [1.05 (0.82, 1.35)]. Comorbidity of depression and anxiety is associated with all-cause mortality [1.34 (1.24, 1.45)] and cancer-specific mortality [1.45 (1.11, 1.90)]. Subgroup analyses demonstrated that clinically diagnosed depression and anxiety, being female and of younger age (<60 years), and shorter follow-up duration (≤5 years) were related to a poorer prognosis. Our study highlights the critical role of depression/anxiety as an independent factor in predicting breast cancer recurrence and survival. Further research should focus on a favorable strategy that works best to improve outcomes among breast cancer patients with mental disorders.

Correlation of expression of hormone and HER2 receptors with various clinico-pathological prognostic parameters and with each other in malignant breast lesion

BACKGROUND

Estrogen receptors (ER), progesterone receptors (PR) and the human epidermal growth factor receptor-2 (HER2) are basic breast cancer molecular markers that are also best recognized prognostic factors and predictors of type of targeted therapy to be given. The objectives are to study the correlation of expression of hormone and HER2receptors with various clinico-pathological prognostic parameters like patient's age at diagnosis, menopausal status, tumor size, histological grade and lymph node status of tumor and with each other in malignant breast lesion.

METHODS

For this study histopathology (HP) and immunohistochemistry (IHC) slides of excised specimens of 330 female patients with a palpable breast lump deposited to the pathology department of a hospital as a part of routine diagnostic procedure, were evaluated under the guidance of trained doctors who have minimum 5 years of experience in oncopathology. The author has no direct involvement with patients, informed consent was not necessary and data were collected after getting permission from concerned authority.

RESULTS

This study finds significant relationship between hormone receptors and all clinico-pathological prognostic parameters taken for comparison except age at diagnosis. HER2 status has significant relationship with all clinico-pathological prognostic parameters; hormone and HER2 status suggests an inverse relationship.

CONCLUSIONS

Mien of hormone receptors expression in breast cancer is related with better prognostic factors such as older age, postmenopausal status, smaller tumor size, low histological grade and negative lymph node status, however the opposite is correct for HER2. Hormone receptors and HER2 have an inversely proportionate relationship with each other.

Artificial intelligence as the next step towards precision pathology

Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The appearance of digital image analysis holds promise to improve both the volume and precision of histomorphological evaluation. Recently, machine learning, and particularly deep learning, has enabled rapid advances in computational pathology. The integration of machine learning into routine care will be a milestone for the healthcare sector in the next decade, and histopathology is right at the centre of this revolution. Examples of potential high-value machine learning applications include both model-based assessment of routine diagnostic features in pathology, and the ability to extract and identify novel features that provide insights into a disease. Recent groundbreaking results have demonstrated that applications of machine learning methods in pathology significantly improves metastases detection in lymph nodes, Ki67 scoring in breast cancer, Gleason grading in prostate cancer and tumour-infiltrating lymphocyte (TIL) scoring in melanoma. Furthermore, deep learning models have also been demonstrated to be able to predict status of some molecular markers in lung, prostate, gastric and colorectal cancer based on standard HE slides. Moreover, prognostic (survival outcomes) deep neural network models based on digitized HE slides have been demonstrated in several diseases, including lung cancer, melanoma and glioma. In this review, we aim to present and summarize the latest developments in digital image analysis and in the application of artificial intelligence in diagnostic pathology.

Implications for Breast Cancer Restaging Based on the 8th Edition AJCC Staging Manual

OBJECTIVE

We assessed the changes that have resulted from the latest breast cancer staging guidelines and the potential impact on prognosis.

BACKGROUND

Contemporary data suggest that combining anatomic staging and tumor biology yields a predictive synergy for determining breast cancer prognosis. This forms the basis for the American Joint Committee on Cancer's (AJCC) Staging Manual, 8th edition. We assessed the changes that have resulted from the new staging guidelines and the potential impact on prognosis.

METHODS

Women with stages I to III breast cancer from 2010 to 2014 in the National Cancer Data Base were pathologically staged according to the 7th and 8th editions of the AJCC Staging Manual. Patient characteristics and restaging outcomes were summarized. Unadjusted overall survival (OS) was estimated, and differences were assessed. Cox proportional-hazards models were utilized to estimate the adjusted association of stage with OS.

RESULTS

After restaging the 493,854 women identified, 6.8% were upstaged and 29.7% were downstaged. The stage changes varied by tumor histology, receptor status, tumor grade, and Oncotype DX scores (all P < 0.0001). Applying the 8th edition criteria yielded an incremental reduction in survival for each increase in stage, which was not consistently seen in the 7th edition. In a subgroup analysis based on hormone receptor (HR) status, those with stages II and III, and HR- disease had a worse OS than those with HR+ disease.

CONCLUSIONS

Applying the 8th edition staging criteria resulted in a stage change for >35% of patients diagnosed with invasive breast cancer and refined OS estimates. Overall, the transition to the 8th edition is expected to better drive clinical care, treatment recommendations, and future research.

Comparative evaluation of nuclear and histological grades as prognostic factors for invasive breast cancer

BACKGROUND

Although tumor grade, defined by either the nuclear grade (NG) or the histological grade (HG), is widely accepted as one of the prognostic factors for breast cancer, there is a limited direct comparison between these two grading systems. The object of the current study was to compare their prognostic capabilities on the same specimen in a single institutional cohort.

METHODS

We collected data from 1125 patients with breast cancer who underwent surgery at Kaizuka City Hospital between 2002 and 2016 and analyzed the prognostic capability of NG and HG in comparison with other clinicopathological factors. Pathological diagnoses were performed by a single pathologist throughout the study period.

RESULTS

The median follow-up was 52.9 months. During the follow-up period, 103 distant recurrences were observed. The concordance rate of grades between NG and HG was 72.1%. The 5-year recurrence-free survival (RFS) rates for patients with NG1, NG2, and NG3 were 90.6%, 91.8%, and 82.2%, respectively, and the rates for patients with HG1, HG2, and HG3 were 92.7%, 88.6%, and 82.5%, respectively. Significant differences in RFS were noted among each grade for HG. However, this was not true for NG; a significant difference was not noted between NG1 and NG2. In terms of subtypes, both NG3 and HG3 were significantly associated with worse outcomes in patients with ER-positive/HER2-negative tumors.

CONCLUSIONS

Although not a few patients exhibited discordant results between NG and HG, both NG and HG predict outcomes for breast cancer patients, but the latter might appear to be superior as a three-grade classification scale.

Greater Survival Improvement in African American vs. Caucasian Women with Hormone Negative Breast Cancer

Background: African American women have not benefited equally from recently improved breast cancer survival. We investigated if this was true for all subsets.

Methods: We identified 395,170 patients with breast adenocarcinoma from the SEER database from 1990 to 2011 with designated race, age, stage, grade, ER and PR status, marital status and laterality, as control. We grouped patients into two time periods, 1990-2000 and 2001-2011, three age categories, under 40, 40-69 and ≥ 70 years and two stage categories, I-III and IV. We used the Kaplan-Meier and logrank tests to compare survival curves. We stratified data by patient- and tumor-associated variables to determine co-variation among confounding factors using the Pearson Chi-square test and Cox proportional hazards regression to determine hazard ratios (HR) to compare survival.

Results: Stage I-III patients of both races ≥ 70 years old, African American widowed patients and Caucasians with ER- and PR- tumors had worse improvements in survival in 2001-2011 than younger, married or hormone receptor positive patients, respectively. In contrast, African Americans with ER- (Cox HR 0.70 [95% CI 0.65-0.76]) and PR- (Cox HR 0.67 [95% CI 0.62-0.72]) had greater improvement in survival in 2001-2011 than Caucasians with ER- (Cox HR 0.81 [95% CI 0.78-0.84]) and PR- disease (Cox HR 0.75 [95% CI 0.73-0.78]). This was not associated with changes in distribution of tumor or patient attributes.

Conclusions: African American women with stage I-III ER- and PR- breast cancer had greater improvement in survival than Caucasians in 2001-2011. This is the first report of an improvement in racial disparities in survival from breast cancer in a subset of patients.

Comparative Analysis of Proposed Strategies for Incorporating Biologic Factors into Breast Cancer Staging

BACKGROUND

Tumor biology is an important prognostic factor in breast cancer. This study aimed to compare three staging systems incorporating both biologic factors and anatomic staging (AJCC 8th-edition pathologic prognostic staging, Bioscore, and Risk Score) in a large population-based cohort.

METHODS

The Surveillance, Epidemiology and End Results program was used to select patients with primary stages 1-4 breast cancer diagnosed in 2010. Patients with inflammatory carcinoma, those with missing data for biologic factors, and those with stages 1-3 disease not treated with surgery were excluded from the study. Estimates of 5-year disease-specific survival (DSS) were calculated using the Kaplan-Meier method. The Harrel concordance index (C-index) and the Akaike Information Criterion were used to compare each model in terms of predicting DSS.

RESULTS

The study included 21,901 patients with a median age of 60 years. The median follow-up period was 52 months. All the staging models stratified DSS, with a stepwise decrease in DSS for each increase in risk category or score. The C-index of each model incorporating biologic factors was higher than the C-index for anatomic staging alone (C-index: 0.832 vs. 0.856 for AJCC pathologic prognostic staging, 0.856 for Bioscore, and 0.864 for Risk Score, all p < 0.001). The staging systems incorporating biologic factors did not differ significantly in terms of model fit.

CONCLUSION

Staging systems incorporating biologic factors perform better than anatomic staging alone. Implementation of the AJCC 8th-edition pathologic prognostic staging was an important initial step in the inclusion of tumor biology in staging. Given its simplicity and ease of use, the Risk Score should be given consideration as an alternative staging system.

Histo- and clinico-pathological analysis of a large series of triple-negative breast cancer in a single center in China: Evidences on necessity of histological subtyping and grading

Objective

To investigate histo-pathological distribution and clinico-pathological significance in a large Chinese triple-negative breast cancer (TNBC) patients serials based on the latest understanding of its clinico-pathological diversity, and to provide more information to clinicians to improve precision of individualized treatment of TNBC.

Methods

A retrospective analysis was performed on patients with TNBC at Breast Disease Center, Peking University First Hospital between January 2010 and December 2019. Histo- and clinico-pathological characteristics were analyzed by Chi-square test and Student’s t-test, and prognoses were calculated using Kaplan-Meier method and a Cox proportionate hazards model. Bonferroni correction was used to correct for multiple comparison.

Results

Conventional type of TNBC (cTNBC) were identified in 73.7% of 582 TNBC, while special type of TNBC (sTNBC) were 26.3%, including 71 apocrine carcinoma, 20 medullary carcinoma, 31 metaplastic carcinoma, 18 invasive lobular carcinoma, 7 invasive micropapillary carcinoma, 5 adenoid cystic carcinoma and 1 acinic cell carcinoma. Compared to sTNBC, cTNBC was associated with high histologic grade (P<0.001) and lower androgen receptor (AR) expression (P<0.001). TNM stage of low-grade cTNBC was significantly lower than that of high-grade cTNBC (P=0.002). Although no significant difference, there was a trend that the rate of 5-year disease-free survival (DFS) and 5-year overall survival (OS) were longer in high-grade cTNBC than in high-grade sTNBC (P=0.091 and 0.518), and were longer in low-grade sTNBC than in high-grade sTNBC (P=0.051 and 0.350). Metaplastic carcinomas showed larger tumor size (P=0.008) and higher proliferative Ki67 index (P=0.004) than cTNBCs.

Conclusions

Results from our cohort imply that sub-categorization or subtyping and histological grading could be meaningful in pathological evaluation of TNBC, and need to be clarified in more large collections of TNBC.