Effect of Ki-67 Expression Levels and Histological Grade on Breast Cancer Early Relapse in Patients with Different Immunohistochemical-based Subtypes

Development of a Nomogram-Integrated Model Incorporating Intra-tumoral and Peri-tumoral Ultrasound Radiomics Alongside Clinical Parameters for the Prediction of Histological Grading in Invasive Breast Cancer

OBJECTIVE

To develop a comprehensive nomogram to predict the histological grading of breast cancer and further examine its clinical significance by integrating both intra-tumoral and peri-tumoral ultrasound radiomics features.

METHODS

In a retrospective study 468 female breast cancer patients were analyzed from 2017 to 2020 at the Second Affiliated Hospital of Harbin Medical University. Patients were grouped into high-grade (n = 215) and low-grade (n = 253) categories based on pathological evaluation. Tumor regions of interest were defined and expanded automatically to peri-tumor regions of interest. Ultrasound radiomics features were extracted independently. To ensure rigor, cases were randomly divided into 80% training and 20% test sets. Optimal features were selected using statistical and machine learning methods. Intra-tumor, peri-tumor, and combined radiomics models were constructed. To determine the best predictors of breast cancer histological grading, we screened the features using single- and multi-factor logistic regression analyses. Finally, a nomogram was developed and evaluated for its predictive value in this context.

RESULTS

By applying logistic regression, we integrated ultrasound, clinicopathologic, and radiomics features to generate a nomogram. The combined model outperformed others, achieving areas under the curve of 0.934 and 0.812 in training and test sets. Calibration curves also showed high accuracy and reliability.

CONCLUSION

A nomogram constructed through the integration of combined intra-tumor-peri-tumor ultrasound radiomics features along with clinicopathologic characteristics exhibited remarkable performance in distinguishing the histologic grades of invasive breast cancer.

Preoperative Prediction of Breast Cancer Histological Grade Using Intratumoral and Peritumoral Radiomics Features from T2WI and DWI MR Sequences

Background

Histological grade is an acknowledged prognostic factor for breast cancer, essential for determining clinical treatment strategies and prognosis assessment. Our study aims to establish intra- and peritumoral radiomics models using T2WI and DWI MR sequences for predicting the histological grade of breast cancer.

Methods

700 breast cancer cases who had MRI scans before surgery were included. The intratumoral region (ITR) of interest was manually delineated, while the peritumoral region (PTR-3 mm) was automatically obtained by expanding the ITR by 3 mm. Radiomics features were extracted using the intra- and peritumoral images from T2WI and DWI sequences on breast MRI. Then, the key features with the strongest predictivity of histological grade were selected. Finally, 9 predictive radiomics models were established based on T2WI-ITR, T2WI-3mmPTR, DWI-ITR, DWI-3mmPTR, T2WI-ITR + 3mmPTR, DWI-ITR + 3mmPTR, (T2WI + DWI)-ITR, (T2WI + DWI)-3mmPTR and (T2WI + DWI)-ITR + 3mmPTR.

Results

The (T2WI + DWI)-ITR + 3mmPTR contained 13 DWI features which included a shape feature, a texture feature, and 11 filtered features, as well as 10 T2WI features, all of which were filtered features. Among the 9 models, the combined models showed better performance than the single models in both the training and test sets, especially for the (T2WI + DWI)-ITR + 3mmPTR radiomics model. The (T2WI + DWI)-ITR + 3mmPTR radiomics model achieved a sensitivity, specificity, accuracy, and AUC of 80.4%, 72.4%, 75.0%, and 0.860 in the training set, and 68.9%, 70.5%, 70.0%, and 0.781 in the test set. Decision curve analysis (DCA) showed that the (T2WI + DWI)-ITR + 3mmPTR model had the greatest net clinical benefit compared to the other models.

Conclusion

The intra- and peritumoral radiomics methodologies using T2WI and DWI MR sequences could be utilized to assess histological grade for breast cancer, particularly with the (T2WI + DWI)-ITR + 3mmPTR radiomics model demonstrating significant potential for clinical application.

Patterns in use and tolerance of adjuvant neratinib in patients with hormone receptor (HR)-positive, HER2-positive early-stage breast cancer

PURPOSE

One year of neratinib therapy is known to derive a significant invasive disease-free survival (iDFS) benefit in early-stage, hormone receptor-positive (HR +), HER2 + , node-positive breast cancer after trastuzumab-based adjuvant therapy. Limitations to neratinib use include significant gastrointestinal side effects, which often result in treatment discontinuation. In this study, we aimed to identify clinicopathologic features associated with adjuvant neratinib use and factors impacting treatment completion.

METHODS

We performed a retrospective review of patients with early-stage HR + HER2 + breast cancer who were prescribed neratinib from 2017 to 2023 at our institution. We used the electronic medical record to extract information on patient characteristics, clinical features, and treatment information. Patients were identified as high risk based on definitions adapted from the standard high-risk definition in HR + HER2- breast cancer combined with studies correlating high Ki67 or high tumor grade with lower recurrence-free survival. Statistical analysis was performed using two-sided T-tests and chi-square tests.

RESULTS

We identified 62 eligible patients of whom 55% completed 1 year of neratinib and 45% did not. Sixty percent (N = 37) of patients offered neratinib were considered high risk at diagnosis. The most common reason for neratinib discontinuation was inability to tolerate side effects (54%) followed by pill burden (18%). The most common side effect experienced by patients was diarrhea despite anti-diarrheal prophylaxis (56%), followed by rash (8%). Patients who received an up-titration of neratinib were more likely to complete the full course of neratinib when compared to those who did not (76% vs. 40.5% p = 0.013). The median starting dose of those who completed neratinib treatment was 140 vs. 240 mg in those who did not (p = 0.016). Neither group experienced a statistically significant greater likelihood of treatment holds or dose reductions. In terms of outcomes, 10 patients had progression of disease of whom 7 did not complete neratinib treatment (p = 0.169). Interestingly, those 7 patients developed metastatic disease and 57% (N = 4) had central nervous system metastases.

CONCLUSION

Patients are more likely to complete 1 year of adjuvant neratinib with dose up-titration. Dose reductions and interruptions did not affect neratinib adherence in our patient population. Seven patients (11%) in our study developed metastatic disease, all of whom did not complete adjuvant neratinib treatment.

Expression of Ki-67 in Invasive Breast Carcinoma and Its Correlation With Different Clinicopathological Features

Introduction Worldwide, breast cancer is still the most common cancer that affects women. Breast cancer prognosis is based on a number of clinical and pathological indicators. Further features are needed to predict early metastasis and prognosis of patients with breast carcinoma, as the current pathological characteristics, such as tumor differentiation, vascular infiltration, and TNM (tumor, node, and metastasis) staging, cannot fully describe the early metastatic biological behavior in breast carcinoma. High Ki-67 expression is seen to be associated with worse survival in cancer patients. Hence, this study was conducted to study the utility of Ki-67 as a prognostic marker in invasive breast carcinoma and its association with known clinicopathological factors. Methodology The study was a hospital-based cross-sectional study carried out in the Histopathology Section of the Department of Pathology, Shri BM Patil Medical College Hospital and Research Centre, Bijapur Lingayat District Education (BLDE) (Deemed to be University), Vijayapura. The study was conducted between September 1, 2022, and April 30, 2024. The study population consisted of 55 cases of mastectomy specimens of primary breast cancer admitted to our hospital. Data regarding the patient's age, tumor size, histological type, histological grade, lymph node status, and vascular invasion were noted from medical records. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2/neu (HER2/neu) proto-oncogene, and Ki-67 markers was performed according to standard protocol. The relationship of Ki-67 with these clinicopathological parameters was analyzed statistically. Results In the current study, high-grade Ki-67 nuclear positivity was seen in 30 cases out of 55 cases, and low-grade Ki-67 was seen in the remaining 25 cases. The association of Ki-67 with tumor size and histological grade showed statistical significance with a p-value of less than 0.05 and 0.001, respectively. However, no statistical significance was seen with lymph node status, vascular invasion, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2/neu (HER2/neu) proto-oncogene status with p-values greater than 0.05. Conclusion The expression of Ki-67 was statistically significant with histological grading and tumor size in our study. Immunohistochemical determination of the Ki-67 proliferation index should be performed in routine cases of breast cancer to obtain clinically useful information on tumor aggressiveness as reflected in their proliferative rate. Hence, Ki-67 can be used as a predictive and prognostic marker in managing breast cancer patients.

Efficacy and prognosis of HER2-Low and HER2-Zero in triple-negative breast cancer after neoadjuvant chemotherapy

Mounting evidence showed that HER2-Low breast cancer patients could benefit from the novel anti-HER2 antibody-drug conjugates (ADCs) treatment, which pointed the way towards better therapy for HER2-Low patients. The purpose of this study was to describe the clinicopathological features, along with chemotherapeutic effects and survival outcomes of HER2-Low and HER2-Zero in TNBC who received neoadjuvant chemotherapy (NACT). We retrospectively evaluated 638 triple-negative breast cancer patients who were treated with neoadjuvant chemotherapy between August 2014 and August 2022. Pathologic complete response (pCR) and survival outcomes were analyzed in HER2-Low cohort, HER2-Zero cohort and the overall patients, respectively. In the entire cohort, 342 (53.6%) patients were HER2-Low and 296 (46.4%) patients were HER2-Zero. No significant difference was found between HER2-Low and HER2-Zero patients based on all the clinical-pathological characteristics. 143 cases (22.4%) achieved pCR after NACT in the overall TNBC patients. The pCR rate of the HER2-Low patients and the HER2-Zero patients was 21.3% and 23.6%, respectively, exhibiting no statistical difference (p = 0.487). The survival of pCR group after NACT significantly improved compared to non-pCR group either in HER2-Low patients or in HER2-Zero patients. Although we found that patients with HER2-Low had longer DFS than patients with HER2-Zero, there was no considerable difference (p = 0.068). However, HER2-Low patients had a dramatically longer OS than HER2-Zero patients (p = 0.012). The data from present study confirmed the clinical importance of HER2-Low expression in TNBC. Further effort is needed to determine whether HER2-Low could be a more favorable prognostic marker for individual treatment.

Exploratory pilot study to characterize the immune landscapes of malignant pleural effusions and their corresponding primary tumors from patients with breast carcinoma and lung adenocarcinoma

INTRODUCTION

Malignant pleural effusion (MPE) is a frequent complication of advanced malignancies. In this pilot study, we characterized the immune landscapes of MPEs, compared them to their primary tumor (PT) samples from breast carcinoma (BC) and lung adenocarcinoma (LADC), and tested the utility of multiplexed image technology in cytological samples.

MATERIALS AND METHODS

We evaluated the immune contexture of 6 BC and 5 LADC MPEs and their PTs using 3 multiplex immunofluorescence panels. We explored the associations between sample characteristics and pleural effusion-free survival.

RESULTS

No MPE samples had positive programmed death-ligand 1 expression in malignant cells, although 3 of 11 PTs has positive programmed death-ligand 1 expression (more than 1% expression in malignant cells). Overall, in LADC samples, cluster of differentiation 3 (CD3)+ T cells and CD3+CD8+ cytotoxic T cells predominated (median percentages for MPEs versus PTs: 45.6% versus 40.7% and 4.7% versus 6.6%, respectively) compared with BC. CD68+ macrophages predominated in the BC samples (medians for MPEs 61.2% versus PTs for 57.1%) but not in the LADC samples. Generally in PTs, CD3+CD8+ forkhead box P3+ T cells and the median distances from the malignant cells to CD3+CD8+Ki67+ and CD3+ programmed cell death protein 1 + T cells correlated to earlier MPE after PT diagnosis.

CONCLUSIONS

The immune cell phenotypes in the MPEs and PTs were similar within each cancer type but different between BC versus LADC. An MPE analysis can potentially be used as a substitute for a PT analysis, but an expanded study of this topic is essential.

Differentiating Primary and Recurrent Lesions in Patients with a History of Breast Cancer: A Comprehensive Review

Breast cancer (BC) recurrence remains a concerning issue, requiring accurate identification and differentiation from primary lesions for optimal patient management. This comprehensive review aims to summarize and evaluate the current evidence on methods to distinguish primary breast tumors from recurrent lesions in patients with a history of BC. Also, we provide a comprehensive understanding of the different imaging techniques, including mammography, ultrasound, magnetic resonance imaging, and positron emission tomography, highlighting their diagnostic accuracy, limitations, and potential integration. In addition, the role of various biopsy modalities and molecular markers was explored. Furthermore, the potential role of liquid biopsy, circulating tumor cells, and circulating tumor DNA in differentiating between primary and recurrent BC was emphasized. Finally, it addresses emerging diagnostic modalities, such as radiomic analysis and artificial intelligence, which show promising potential in enhancing diagnostic accuracy. Through comprehensive analysis and review of the available literature, the current study provides an up-to-date understanding of the current state of knowledge, challenges, and future directions in accurately distinguishing between primary and recurrent breast lesions in patients with a history of BC.

The Role of Ki-67 in HR+/HER2- Breast Cancer: A Real-World Study of 956 Patients

Objective

This study determined the cut-off value of Ki-67 expression and discussed the interaction between Ki-67 and histological grade, further explored the prognostic role of Ki-67 in hormone receptor-positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer;.

Materials and Methods

We assessed the Ki-67 expression of 956 patients with HR+/HER2 breast cancer diagnosed in the General Hospital of Ningxia Medical University from 2015 to 2019 by immunohistochemistry (IHC), The disease-free survival (DFS) was defined as the time from postoperative to the first local recurrence, distant metastasis or death of the disease. The follow-up by means of inpatient or outpatient medical records and telephone.

Results

22.5% was used as the cut-off for low/high Ki-67 expression in HR+/HER2- breast cancer. Compared with the value of 14%, which is commonly used in clinic at present, the consistency of the two values is moderate (Kappa = 0.484, P<0.001). The expression of Ki-67 was increased with the grade. (Median: G1:10%; G2:20%; G3:40%. Mean: G1:13%; G2:23%; G3:39%, P <0.001). Survival analysis was based on all patients for a median of 51 months (24-89 months), 63 cases had recurrence or metastasis during the follow-up, which 21 cases had low expression of Ki-67 and 42 cases had high expression. The patients with Ki-67 ≥ 22.5% had a 2.969 higher risk of early recurrence and metastasis than the patients with Ki-67 < 22.5%. There were 4 cases of local recurrence, 7 cases of regional lymph node metastasis, and 52 cases of distant metastasis in all patients, the common distant metastases were bone, liver, and lung, and rare metastases were adrenal gland, bone marrow, and pericardium.

Conclusion

In HR+/HER2- breast cancer, patients with Ki-67 > 22.5% have a worse prognosis and are more likely to have early recurrence and metastasis.

Tumor circadian clock strength influences metastatic potential and predicts patient prognosis in luminal A breast cancer

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular circadian rhythms in noncancerous and cancerous human breast tissues and their clinical relevance are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time-stamped biopsies with public datasets. For noncancerous breast tissue, inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype-specific changes in circadian organization. Luminal A organoids and informatic ordering of luminal A samples exhibit continued, albeit dampened and reprogrammed rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among luminal A samples. Cycling of EMT pathway genes was markedly increased in high-magnitude luminal A tumors. Surprisingly, patients with high-magnitude tumors had reduced 5-y survival. Correspondingly, 3D luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype-specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis.

Environmental pressures, tumor characteristics, and death rate in a female breast cancer cohort: a seven-years Bayesian survival analysis using cancer registry data from a contaminated area in Italy

Introduction

In Taranto, Southern Italy, adverse impacts on the environment and human health due to industrial installations have been studied. In the literature, few associations have been reported between environmental factors and breast cancer mortality in women. The aim of this study was to investigate the relationships between residence in areas with high environmental pressures, female breast cancer characteristics, and death rate.

Methods

Data from the Taranto Cancer Registry were used, including all women with invasive breast cancer diagnosed between 01 January 2015 and 31 December 2020 and with follow-up to 31 December 2021. Bayesian mixed effects logistic and Cox regression models were fitted with the approach of integrated nested Laplace approximation, adjusting for patients and disease characteristics.

Results

A total of 10,445 person-years were observed. Variables associated with higher death rate were residence in the contaminated site of national interest (SIN) (HR 1.22, 95% CrI 1.01-1.48), pathological/clinical stage III (HR 2.77, 95% CrI 1.93-3.97) and IV (HR 17.05, 95% CrI 11.94-24.34), histological grade 3 (HR 2.50, 95% CrI 1.20-5.23), Ki-67 proliferation index of 21-50% (HR 1.42, 95% CrI 1.10-1.83) and > 50% (HR 1.81, 95% CrI 1.29-2.55), and bilateral localization (HR 1.65, 95% CrI 1.01-2.68). Variables associated with lower death rate were estrogen and/or progesterone receptor positivity (HR 0.61, 95% CrI 0.45-0.81) and HER2/neu oncogene positivity (HR 0.59, 95% CrI 0.44-0.79).

Discussion

The findings confirmed the independent prognostic values of different female breast cancer characteristics. Even after adjusting for patients and disease characteristics, residence in the SIN of Taranto appeared to be associated with an increased death rate.

Tumour circular RNAs elicit anti-tumour immunity by encoding cryptic peptides

Emerging data have shown that previously defined noncoding genomes might encode peptides that bind human leukocyte antigen (HLA) as cryptic antigens to stimulate adaptive immunity1,2. However, the significance and mechanisms of action of cryptic antigens in anti-tumour immunity remain unclear. Here mass spectrometry of the HLA class I (HLA-I) peptidome coupled with ribosome sequencing of human breast cancer samples identified HLA-I-binding cryptic antigenic peptides that were noncanonically translated by a tumour-specific circular RNA (circRNA): circFAM53B. The cryptic peptides efficiently primed naive CD4+ and CD8+ T cells in an antigen-specific manner and induced anti-tumour immunity. Clinically, the expression of circFAM53B and its encoded peptides was associated with substantial infiltration of antigen-specific CD8+ T cells and better survival in patients with breast cancer and patients with melanoma. Mechanistically, circFAM53B-encoded peptides had strong binding affinity to both HLA-I and HLA-II molecules. In vivo, administration of vaccines consisting of tumour-specific circRNA or its encoded peptides in mice bearing breast cancer tumours or melanoma induced enhanced infiltration of tumour-antigen-specific cytotoxic T cells, which led to effective tumour control. Overall, our findings reveal that noncanonical translation of circRNAs can drive efficient anti-tumour immunity, which suggests that vaccination exploiting tumour-specific circRNAs may serve as an immunotherapeutic strategy against malignant tumours.

Infliximab, a Monoclonal Antibody against TNF-α, Inhibits NF-κB Activation, Autotaxin Expression and Breast Cancer Metastasis to Lungs

An inflammatory milieu in the tumor microenvironment leads to immune evasion, resistance to cell death, metastasis and poor prognosis in breast cancer patients. TNF-α is a proinflammatory cytokine that regulates multiple aspects of tumor biology from initiation to progression. TNF-α-induced NF-κB activation initiates inflammatory pathways, which determine cell survival, death and tumor progression. One candidate pathway involves the increased secretion of autotaxin, which produces lysophosphatidate that signals through six G-protein-coupled receptors. Significantly, autotaxin is one of the 40-50 most upregulated genes in metastatic tumors. In this study, we investigated the effects of TNF-α by blocking its action with a monoclonal antibody, Infliximab, and studied the effects on autotaxin secretion and tumor progression. Infliximab had little effect on tumor growth, but it decreased lung metastasis by 60% in a syngeneic BALB/c mouse model using 4T1 breast cancer cells. Infliximab-treated mice also showed a decrease in proliferation and metastatic markers like Ki-67 and vimentin in tumors. This was accompanied by decreases in NF-κB activation, autotaxin expression and the concentrations of plasma and tumor cytokines/chemokines which are involved in metastasis. We also demonstrated a positive correlation of TNF-α -NF-κB and ATX expression in breast cancer patients using cancer databases. Studies in vitro showed that TNF-α-induced NF-κB activation increases autotaxin expression and the clone forming ability of 4T1 breast cancer cells. This report highlights the potential role of Infliximab as an additional approach to attenuate signaling through the autotaxin-lysophosphatidate-inflammatory cycle and decrease mortality from metastatic cancer.

The POWER-PAK Score Characterizes Tumor Response to 3 Months of Preoperative Endocrine Therapy

BACKGROUND

The Pre-Operative Window of Endocrine Therapy to Inform Radiation Therapy Decisions (POWER, NCT04272801) trial aims to determine whether 3 months of preoperative endocrine therapy (pre-ET) informs adjuvant radiation therapy decisions among older women with early stage, ER-positive breast cancer. We propose the POWER Pathologic Assessment and Ki-67 (POWER-PAK) scoring system to characterize the histologic effects of pre-ET.

METHODS

Histologic evaluation was performed on core biopsy and lumpectomy specimens from 37 POWER trial participants who completed pre-ET and surgery. The POWER-PAK score consists of tumor regression, decrease in Ki-67 expression, and ER expression, each ranging from 0 to 2. Scores were aggregated to create the POWER-PAK score with a range from 0 to 6. Participants with no residual tumor were labelled 6-NRT.

RESULTS

ER expression did not decrease after pre-ET. Ki-67 decreased from 13% in biopsy specimens to 5% in the lumpectomy specimens (p < 0.001). Cellularity decreased from 40% to 23% (p < 0.001). There was heterogeneity of POWER-PAK scores ranging from 2 to 6-NRT: score of 2, n = 2 (5.4%); 4, n = 8 (21.6%); 5, n = 4 (10.8%); 6, n = 16 (43.2%); and 6-NRT, n = 7 (18.9%). Participants with a score ≥ 5 were more likely to have smaller tumors after pre-ET compared with those with a score < 5 (p = 0.04).

CONCLUSIONS

The tumor responses following treatment with pre-ET are heterogenous. We propose that the POWER-PAK scoring system can be used to quantify response to pre-ET. Future studies will explore the use of POWER-PAK to support informed decision-making for adjuvant therapy options for older women with early stage breast cancer.

Predictive value of radiomics-based machine learning for the disease-free survival in breast cancer: a systematic review and meta-analysis

Purpose

This study summarized the previously-published studies regarding the use of radiomics-based predictive models for the identification of breast cancer-associated prognostic factors, which can help clinical decision-making and follow-up strategy.

Materials and methods

This study has been pre-registered on PROSPERO. PubMed, Embase, Cochrane Library, and Web of Science were searched, from inception to April 23, 2022, for studies that used radiomics for prognostic prediction of breast cancer patients. Then the search was updated on July 18, 2023. Quality assessment was conducted using the Radiomics Quality Score, and meta-analysis was performed using R software.

Results

A total of 975 articles were retrieved, and 13 studies were included, involving 5014 participants and 35 prognostic models. Among the models, 20 models were radiomics-based and the other 15 were based on clinical or pathological information. The primary outcome was Disease-free Survival (DFS). The retrieved studies were screened using LASSO, and Cox Regression was applied for modeling. The mean RQS was 18. The c-index of radiomics-based models for DFS prediction was 0.763 (95%CI 0.718-0.810) in the training set and 0.702 (95%CI 0.637-0.774) in the validation set. The c-index of combination models was 0.807 (95%CI0.736-0.885) in the training set and 0.840 (95%CI 0.794-0.888) in the validation set. There was no significant change in the c-index of DFS at 1, 2, 3, and over 5 years of follow-up.

Conclusion

This study has proved that radiomics-based prognostic models are of great predictive performance for the prognosis of breast cancer patients. combination model shows significantly enhanced predictive performance.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022332392.

A nomogram for predicting the risk of male breast cancer for overall survival

Background

Male breast cancer (MBC) is a rare disease, accounting for <1% of all male carcinomas. Lack of prospective data, the current therapy for MBC is based on retrospective analysis or information that is extrapolated from studies of female patients. We constructed a nomogram model for predicting the overall survival (OS) of MBC patients and verify its feasibility using data from China.

Methods

Constructed a predictive model using 1224 MBC patients from the Surveillance, Epidemiology and End Results (SEER) registry between 2010 and 2015. The performance of the model was externally validated between 2002 to 2021 using 44 MBC patients from the Fujian Medical University Union Hospital. The independent prognostic factors were selected by univariate and multivariate Cox regression analyses. The nomogram was constructed to predict individual survival outcomes for MBC patients. The discriminative power, calibration, and clinical effectiveness of the nomogram were evaluated by the receiver operating characteristic (ROC) curve, and the decision curve analysis (DCA).

Results

A total of 1224 male breast cancer patients were in the training cohort and 44 in the validation cohort. T status (p<0.001), age at diagnosis (p<0.001), histologic grade (p=0.008), M status (p<0.001), ER status (p=0.001), Her2 status (p=0.019), chemotherapy (p=0.015) were independently associated with OS. The diagnostic performance of this model was evaluated and validated using ROC curves on the training and validation datasets. In the training cohort, the nomogram-predicted AUC value was 0.786 for 3-year OS and 0.767 for 5-year OS. In the validation cohort, the nomogram-predicted AUC value was 0.893 for 3-year OS and 0.895 for 5-year OS. Decision curve analysis demonstrated that the nomogram was more benefit than the AJCC stage.

Conclusions

We developed a nomogram that predicts 3-year and 5-year survival in MBC patients. Validation using bootstrap sampling revealed optimal discrimination and calibration, suggesting that the nomogram may have clinical utility. The results remain reproducible in the validation cohort which included Chinese data. The model was superior to the AJCC stage system as shown in the decision curve analysis (DCA).

A Comprehensive Review on Electrochemical Nano Biosensors for Precise Detection of Blood-Based Oncomarkers in Breast Cancer

Breast cancer (BC), one of the most common and life-threatening cancers, has the highest incidence rate among women. Early diagnosis of BC oncomarkers is considered the most effective strategy for detecting and treating BC. Finding the type and stage of BC in women as soon as possible is one of the greatest ways to stop its incidence and negative effects on medical treatment. The development of biosensors for early, sensitive, and selective detection of oncomarkers has recently attracted much attention. An electrochemical nano biosensor (EN) is a very suitable option for a powerful tool for cancer diagnosis. This comprehensive review provides information about the prevalence and pathobiology of BC, recent advances in clinically available BC oncomarkers, and the most common electrochemical nano biosensors for point-of-care (POC) detection of various BC oncomarkers using nanomaterial-based signal amplification techniques.

Machine Learning Approach for the Determination of the Best Cut-off Points for Ki67 Proliferation Index in Adjuvant and Neo-adjuvant Therapy Breast Cancer Patients

BACKGROUND

This study aims to evaluate Ki67 cut-off points for differentiating low and high-risk patients based on survival and recurrence and find the best Ki67 cut-off points in breast cancer patients undergoing adjuvant and neoadjuvant therapy using machine learning methods.

PATIENTS AND METHODS

Patients with breast cancer treated at 2 referral hospitals between December 2000 and March 2021 who had invasive breast cancer entered this study. There were 257 patients in the neoadjuvant group and 2139 in the adjuvant group. A decision tree method was used to predict the likelihood of survival and recurrence. The 2-ensemble technique of RUSboost and bagged tree were imposed on the decision tree method to increase the accuracy of the determination. 80 percent of the data was used to train and validate the model, and 20% was used as a test.

RESULTS

In adjuvant therapy breast cancer patients with Invasive ductal carcinoma (IDC) and Invasive lobular carcinoma (ILC) the cutoff points for survival were 20 and 10, respectively. For luminal A, luminal B, Her2 neu, and triple-negative adjuvant therapy patients' the cutoff points for survival were 25, 15, 20, and 20, respectively. For neoadjuvant therapy luminal A and luminal B group, survival cutoff points were 25 and 20, respectively.

CONCLUSION

Despite variability in measurement and cut-off points, the Ki-67 proliferation index is still helpful in the clinic. Further investigation is needed to determine the best cut-off points for different patients. The sensitivity and specificity of Ki-67 cutoff point prediction models in this study could further prove its significance as a prognostic factor.

Ki 67: a Promising Prognostic Marker in Early Breast Cancer-a Review Article

Ki67 index is considered to be a reliable indicator of the proliferative activity of breast cancer. Additionally, the Ki67 proliferative marker may play a role in assessing response to systemic therapeutic strategies and can act as a prognostic biomarker. But its limited reproducibility which stems from a lack of standardization of procedures, inter-observer variability, and preanalytical and analytical variabilities all have hampered the use of the Ki67 index in clinical practice. Currently, clinical trials have been evaluating Ki67 as a predictive marker for needing adjuvant chemotherapy in luminal early breast cancer patients receiving neoadjuvant endocrine therapy. But the inconsistencies existing in the estimation of the Ki67 index limit the utility of Ki67 in standard clinical practice. The purpose of this review is to evaluate the benefits and drawbacks of utilizing Ki-67 in early-stage breast cancer to prognosticate the disease and predict the risk of recurrence.

Prediction of Ki-67 of Invasive Ductal Breast Cancer Based on Ultrasound Radiomics Nomogram

PURPOSE

The objective of this research was to develop and validate an ultrasound-based radiomics nomogram for the pre-operative assessment of Ki-67 in breast cancer (BC).

MATERIALS AND METHODS

From December 2016 to December 2018, 515 patients with invasive ductal breast cancer who received two-dimensional (2D) ultrasound and Ki-67 examination were studied and analyzed retrospectively. The dataset was distributed at random into a training cohort (n = 360) and a test cohort (n = 155) in the ratio of 7:3. Each tumor region of interest was defined based on 2D ultrasound images and radiomics features were extracted. ANOVA, maximum correlation minimum redundancy (mRMR) algorithm, and minimum absolute shrinkage and selection operator (LASSO) were performed to pick features, and independent clinical predictors were integrated with radscore to construct the nomogram for predicting Ki-67 index by univariate and multivariate logistic regression analysis. The performance and utility of the models were evaluated by plotting receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves.

RESULTS

In the testing cohort, the area under the receiver characteristic curve (AUC) of the nomogram was 0.770 (95% confidence interval, 0.690-0.860). In both cohorts, the nomogram outperformed both the clinical model and the radiomics model (P < .05 according to the DeLong test). The analysis of DCA proved that the model has clinical utility.

CONCLUSIONS

The nomogram based on 2D ultrasound images offered an approach for predicting Ki-67 in BC.

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.

Validation of a Disease-Free Survival Prediction Model Using UBE2C and Clinical Indicators in Breast Cancer Patients

Objective

To explore the validation of a disease-free survival (DFS) model for predicting disease progression based on the combination of ubiquitin-conjugating enzyme E2 C (UBE2C) levels and clinical indicators in breast cancer patients.

Methods

We enrolled 121 patients with breast cancer, collected their baseline characteristics and follow-up data, and analyzed the UBE2C levels in tumor tissues. We studied the relationship between UBE2C expression in tumor tissues and disease progression events of patients. We used the Kaplan-Meier method for identifying the disease-free survival rate of patients, and the multivariate Cox regression analysis to study the risk factors affecting the prognosis of patients. We sought to develop and validate a model for predicting disease progression.

Results

We found that the level of expression of UBE2C could effectively distinguish the prognosis of patients. In the Receiver Operating Characteristic (ROC) curve analysis, the Area under the ROC Curve (AUC) = 0.826 (0.714-0.938) indicating that high levels of UBE2C was a high-risk factor for poor prognosis. After evaluating different models using the ROC curve, Concordance index (C-index), calibration curve, Net Reclassification Index (NRI), Integrated Discrimination Improvement Index (IDI), and other methods, we finally developed a model for the expression of Tumor-Node (TN) staging using Ki-67 and UBE2C, which had an AUC=0.870, 95% CI of 0.786-0.953. The traditional TN model had an AUC=0.717, and 95% CI of 0.581-0.853. Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) analysis indicated that the model had good clinical benefits and it was relatively simple to use.

Conclusion

We found that high levels of UBE2C was a high-risk factor for poor prognosis. The use of UBE2C in addition to other breast cancer-related indicators effectively predicted the possible disease progression, thus providing a reliable basis for clinical decision-making.

Comparison Between Manual and Automated Assessment of Ki-67 in Breast Carcinoma: Test of a Simple Method in Daily Practice

BACKGROUND

In the era of "precision medicine," the availability of high-quality tumor biomarker tests is critical and tumor proliferation evaluated by Ki-67 antibody is one of the most important prognostic factors in breast cancer. But the evaluation of Ki-67 index has been shown to suffer from some interobserver variability. The goal of the study is to develop an easy, automated, and reliable Ki-67 assessment approach for invasive breast carcinoma in routine practice.

PATIENTS AND METHODS

A total of 151 biopsies of invasive breast carcinoma were analyzed. The Ki-67 index was evaluated by 2 pathologists with MIB-1 antibody as a global tumor index and also in a hotspot. These 2 areas were also analyzed by digital image analysis (DIA).

RESULTS

For Ki-67 index assessment, in the global and hotspot tumor area, the concordances were very good between DIA and pathologists when DIA focused on the annotations made by pathologist (0.73 and 0.83, respectively). However, this was definitely not the case when DIA was not constrained within the pathologist's annotations and automatically established its global or hotspot area in the whole tissue sample (concordance correlation coefficients between 0.28 and 0.58).

CONCLUSIONS

The DIA technique demonstrated a meaningful concordance with the indices evaluated by pathologists when the tumor area is previously identified by a pathologist. In contrast, basing Ki-67 assessment on automatic tissue detection was not satisfactory and provided bad concordance results. A representative tumoral zone must therefore be manually selected prior to the measurement made by the DIA.

Correlative studies of the Breast Cancer Index (HOXB13/IL17BR) and ER, PR, AR, AR/ER ratio and Ki67 for prediction of extended endocrine therapy benefit: a Trans-aTTom study

BACKGROUND

Multiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit.

METHODS

Node-positive (N+) patients from the Trans-aTTom study with available tissue specimen and BCI results (N = 789) were included. Expression of ER, PR, AR, and Ki67 was assessed by quantitative immunohistochemistry. BCI (H/I) gene expression analysis was conducted by quantitative RT-PCR. Statistical significance of the treatment by biomarker interaction was evaluated by likelihood ratio tests based on multivariate Cox proportional models, adjusting for age, tumor size, grade, and HER2 status. Pearson's correlation coefficients were calculated to evaluate correlations between BCI (H/I) versus ER, PR, AR, Ki67 and AR/ER ratio.

RESULTS

EET benefit, measured by the difference in risk of recurrence between patients treated with tamoxifen for 10 versus 5 years, is significantly associated with increasing values of BCI (H/I) (interaction P = 0.01). In contrast, expression of ER (P = 0.83), PR (P = 0.66), AR (P = 0.78), Ki67 (P = 0.87) and AR/ER ratio (P = 0.84) exhibited no significant relationship with EET benefit. BCI (H/I) showed a very weak negative correlation with ER (r = - 0.18), PR (r = - 0.25), and AR (r = - 0.14) expression, but no correlation with either Ki67 (r = 0.04) or AR/ER ratio (r = 0.02).

CONCLUSION

These findings are consistent with the growing body of evidence that BCI (H/I) is significantly predictive of response to EET and outcome. Results from this direct comparison demonstrate that expression of ER, PR, AR, Ki67 or AR/ER ratio are not predictive of benefit from EET. BCI (H/I) is the only clinically validated biomarker that predicts EET benefit.

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.

Distinct clinicopathological and genomic features in solid and basaloid adenoid cystic carcinoma of the breast

Adenoid cystic carcinoma (AdCC) of the breast is a rare indolent carcinoma of salivary gland-type tumors, frequently associated with MYB genetic alteration. Solid and basaloid adenoid cystic carcinoma (SB-AdCC) is considered a sparse variant of AdCC. This study sought to search for clinicopathological and genomic features in SB-AdCC. Registered clinicopathological data on a cohort of 13 AdCC of the breast cases, including six conventional adenoid cystic carcinoma (C-AdCC) cases and seven SB-AdCC cases, were collected. MYB gene rearrangement via fluorescent in situ hybridization was investigated and MYB protein expression was evaluated by immunohistochemistry. Compared with C-AdCC, we found that the distribution of SB-AdCC cases were shifted to older age and were more frequently distant metastasis. Moreover, metastasis cases also showed a high (exceed 30%) Ki-67 index. Both groups showed MYB rearrangements and MYB protein expression, but they were less frequent in SB-AdCC than C-AdCC. To conclude, our results suggest that SB-AdCC is an aggressive variant of mammary AdCC with a higher incidence of distant metastases compared with C-AdCC, though they share common molecular features. A high Ki-67 index may be an adverse prognostic factor for metastasis.

An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients' Age: A Retrospective Cohort Study

Characterization of breast cancer into intrinsic molecular profiles has allowed women to live longer, undergoing personalized treatments. With the aim of investigating the relation between different values of ki67 and the predisposition to develop a breast cancer-related IDE at different ages, we enrolled 900 patients with a first diagnosis of invasive breast cancer, and we partitioned the dataset into two sub-samples with respect to an age value equal to 50 years. For each sample, we performed a Kaplan−Meier analysis to compare the IDE-free survival curves obtained with reference to different ki67 values. The analysis on patients under 50 years old resulted in a p-value < 0.001, highlighting how the behaviors of patients characterized by a ki67 ranging from 10% to 20% and greater than 20% were statistically significantly similar. Conversely, patients over 50 years old characterized by a ki67 ranging from 10% to 20% showed an IDE-free survival probability significantly greater than patients with a ki67 greater than 20%, with a p-value of 0.01. Our work shows that the adoption of two different ki67 values, namely, 10% and 20%, might be discriminant in designing personalized treatments for patients under 50 years old and over 50 years old, respectively.

Histological and Immunohistochemical Characteristics for Hereditary Breast Cancer Risk in a Cohort of Brazilian Women

OBJECTIVE

 The study aimed to characterize the clinical, histological, and immunohistochemical profile of women with invasive breast cancer, according to the risk for Hereditary Predisposition Breast and Ovarian Cancer Syndrome in a Brazilian population.

METHODS

 This is a retrospective study performed from a hospital-based cohort of 522 women, diagnosed with breast cancer treated at an oncology referral center in the Southeast region of Brazil, between 2014 and 2016.

RESULTS

 Among the 430 women diagnosed with invasive breast cancer who composed the study population, 127 (29.5%) were classified as at increased risk for hereditary predisposition to breast and ovarian cancer syndrome. There was a lower level of education in patients at increased risk (34.6%) when compared with those at usual risk (46.0%). Regarding tumor characteristics, women at increased risk had higher percentages of the disease diagnosed at an advanced stage (32.3%), and with tumors > 2cm (63.0%), with increased prevalence for both characteristics, when compared with those at usual risk. Furthermore, we found higher percentages of HG3 (43.3%) and K_i-67 ≥ 25% (64.6%) in women at increased risk, with prevalence being about twice as high in this group. The presence of triple-negative tumors was observed as 25.2% in women at increased risk and 6.0% in women at usual risk, with the prevalence of absence of biomarkers being 2.5 times higher among women in the increased risk group.

CONCLUSION

 From the clinical criteria routinely used in the diagnosis of breast cancer, the care practice of genetic counseling for patients at increased risk of hereditary breast cancer in contexts such as Brazil is still scarce.

Correlation of prognostic factors of carcinoma breast with Ki 67 proliferation assay

Prognostic factors are important for the diagnosis of breast cancer as it helps in identification of high risk patients.  The objective of the study is to assess the proliferation index, Ki-67 and correlate it with other markers. The present study was a cohort study conducted in the Department of General Surgery at Tertiary Care Teaching Hospital over a period of 1 year with a sample size of 98. All the patients meeting the inclusion and exclusion criteria are recruited sequentially by convenient sampling until the sample size is attained, with the agreement of the institutional ethics committee. A total of 98 patients with a mean age of 53.61 ± 12.48 years were studied in the final analysis. The mean duration of lump was 4.62 ± 2.18 months and only 6.12% had the complaint of pain.  Majority of them had stage IIIB carcinoma at 43.88%, followed by stage IIA at 27.55%, 15.31% stage IIB, 13.27% stage IIIA.  At cut off 20, 69(70.40%) had ki67 proliferation index ≥20 and 29(29.59%) had<20. Correlation of Ki-67 Index with expression of estrogen receptor status had a p value of 0.019 and with progesterone receptor status, p 0.003 which was significant. 

Assessment of Pharmacological Interactions between SIRT2 Inhibitor AGK2 and Paclitaxel in Different Molecular Subtypes of Breast Cancer Cells

Breast carcinoma (BC) is the most commonly diagnosed type of cancer in women in the world. Although the advances in the treatment of BC patients are significant, numerous side effects, severe toxicity towards normal cells as well as the multidrug resistance (MDR) phenomenon restrict the effectiveness of the therapies used. Therefore, new active compounds which decrease the MDR, extend disease-free survival, thereby ameliorating the effectiveness of the current treatment regimens, are greatly needed. Histone deacetylase inhibitors (HDIs), including sirtuin inhibitors (SIRTi), are the epigenetic antitumor agents which induce a cytotoxic effect in different types of cancer cells, including BC cells. Currently, combined forms of therapy with two or even more chemotherapeutics are promising antineoplastic tools to obtain a better response to therapy and limit adverse effects. Thus, on the one hand, much more effective chemotherapeutics, e.g., sirtuin inhibitors (SIRTi), are in demand; on the other hand, combinations of accepted cytostatics are trialed. Thus, the aim of our research was to examine the combination effects of a renowned cytotoxic drug paclitaxel (PAX) and SIRT2 inhibitor AGK2 on the proliferation and viability of the T47D, MCF7, MDA-MB-231, MDA-MB-468, BT-549 and HCC1937 BC cells. Moreover, cell cycle arrest and apoptosis induction were explored. The type of pharmacological interactions between AGK2 and PAX in different molecular subtypes of BC cells was assessed using the advanced isobolographic method. Our findings demonstrated that the tested active agents singly inhibited viability and proliferation of BC cells as well as induced cell cycle arrest and apoptosis in the cell-dependent context. Additionally, AGK2 increased the antitumor effect of PAX in most BC cell lines. We observed that, depending on the BC cell lines, the combinations of tested drugs showed synergistic, additive or antagonistic pharmacological interaction. In conclusion, our studies demonstrated that the consolidated therapy with the use of AGK2 and PAX can be considered as a potential therapeutic regimen in the personalized cure of BC patients in the future.

Breast Cancer Subtype-Specific miRNAs: Networks, Impacts, and the Potential for Intervention

The regulatory and functional roles of non-coding RNAs are increasingly demonstrated as critical in cancer. Among non-coding RNAs, microRNAs (miRNAs) are the most well-studied with direct regulation of biological signals through post-transcriptional repression of mRNAs. Like the transcriptome, which varies between tissue type and disease condition, the miRNA landscape is also similarly altered and shows disease-specific changes. The importance of individual tumor-promoting or suppressing miRNAs is well documented in breast cancer; however, the implications of miRNA networks is less defined. Some evidence suggests that breast cancer subtype-specific cellular effects are influenced by distinct miRNAs and a comprehensive network of subtype-specific miRNAs and mRNAs would allow us to better understand breast cancer signaling. In this review, we discuss the altered miRNA landscape in the context of breast cancer and propose that breast cancer subtypes have distinct miRNA dysregulation. Further, given that miRNAs can be used as diagnostic and/or prognostic biomarkers, their impact as novel targets for subtype-specific therapy is also possible and suggest important implications for subtype-specific miRNAs.

Immunoarchitectural patterns as potential prognostic factors for invasive ductal breast cancer

Currently, tumor-infiltrating lymphocytes (TILs) in invasive breast cancers are assessed solely on the basis of their number, whereas their spatial distribution is rarely investigated. Therefore, we evaluated TILs in 579 patients with invasive breast cancer of no special type (IBC-NST) with a focus on their spatial distributions in tumor center (TC) and invasive margin (IM). We also assessed a new factor, namely para-tumor infiltrating lymphocytes (PILs) in the para-tumor lobular area (Para). Five immunoarchitectural patterns (IPs) were observed, which were significantly associated with clinicopathological features, especially molecular subtypes, histological grades, clinical stages, and programmed death-ligand 1 (PD-L1) expression. High-TIL density (IP1/2) correlated with favorable disease-free survival (DFS) in TNBC patients (p = 0.04), but opposite results were observed for luminal B subtype patients (both the lowest TIL and PIL densities (IP5) correlated with good DFS, p = 0.013). Luminal B patients with high TILs in the IM and low TILs in the TC (IP3) exhibited the worst DFS, whereas those with low TILs (similar to IP5) and high PILs (IP4) exhibited poor DFS. We also identified TIL subpopulations with significantly different IPs. Our findings suggest that IP can be a potential prognostic factor for tumor immunity in IBC.

Feasibility of Shear Wave Elastography Imaging for Evaluating the Biological Behavior of Breast Cancer

Objective

To explore the feasibility of shear wave elastography (SWE) parameters for assessing the biological behavior of breast cancer.

Materials and Methods

In this prospective study, 224 breast cancer lesions in 216 female patients were examined by B-mode ultrasound and shear wave elastography in sequence. The maximum size (S_max) of the lesion was measured by B-mode ultrasound, and then shear wave elastography was performed on this section to obtain relevant parameters, including maximum elasticity (E_max), mean elasticity (E_mean), standard deviation of elasticity (SD), and the area ratio of shear wave elastography to B-mode ultrasound (AR). The relationship between SWE parameters and pathological type, histopathological classification, histological grade, lymphovascular invasion status (LVI), axillary lymph node status (ALN), and immunohistochemistry of breast cancer lesions was performed according to postoperative pathology.

Results

In the univariate analysis, the pathological type and histopathological classification of breast cancer were not significantly associated with SWE parameters; with an increase in the histological grade of invasive ductal carcinoma (IDC), SD (p = 0.016) and S_max (p = 0.000) values increased. In the ALN-positive group, S_max (p = 0.004) was significantly greater than in the ALN-negative group; S_max (p = 0.003), E_max (p = 0.034), and SD (p = 0.045) were significantly higher in the LVI-positive group than in the LVI-negative group; SD (p = 0.043, p = 0.047) and S_max (p = 0.000, p = 0.000) were significantly lower in the ER⁺ and PR⁺ groups than in the ER^- and PR^- groups, respectively; AR (p = 0.032) was significantly higher in the ER⁺ groups than in the ER^- groups, and S_max (p = 0.002) of the HER2⁺ group showed higher values than that of the HER2^- group; S_max (p = 0.000), SD (p = 0.006), and E_max (p = 0.004) of the Ki-67 high-expression group showed significantly higher values than those of the Ki-67 low-expression group. In the multivariate analysis, Ki-67 was an independent factor of S_max (p = 0.005), E_max (p = 0.004), and SD (p = 0.006); ER was an independent influencing factor of S_max (p = 0.000) and AR (p = 0.032). LVI independently influences S_max (p = 0.006).

Conclusions

The SWE parameters E_max, SD, and AR can be used to evaluate the biological behavior of breast cancer.

Risk for relapse and death after adjuvant chemotherapy associated with SNPs in patients with breast cancer - A retrospective study

For the women breast cancer (BC) patients included in this retrospective study, the first line of systemic treatment in adjuvant modality for breast cancer (BC) after surgery was fluorouracil, epirubicin and cyclophosphamide (FEC). The aim of our investigation was to analyze the prognostic biomarkers for relapse and death of patients eight to ten years after chemotherapy in association with nausea and vomiting.

METHOD

This retrospective study included 114 patients treated between 2010 and 2013. Blood samples for Single Nucleotide Polymorphism (SNP) analysis before the chemotherapy treatment were collected. The medical records were used to determine relapses and death.

RESULTS

Sixteen percent relapsed and 9 % died during the follow-up period. SNPs located in the genes ESR and CASP9 were associated with both relapse and death.

CONCLUSIONS

Relapse and death were at a relative moderate level and consistent with other studies. Two SNPs in the Estrogen hormone receptor gene ESR1 and the apoptosis execution gene Caspases 9 (Casp9) were found to be associated with a higher risk of relapse and death. These findings suggest the possible value of blood biomarkers in the selection of individual treatments in the clinical setting.

3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images

Automated grading systems using deep convolution neural networks (DCNNs) have proven their capability and potential to distinguish between different breast cancer grades using digitized histopathological images. In digital breast pathology, it is vital to measure how confident a DCNN is in grading using a machine-confidence metric, especially with the presence of major computer vision challenging problems such as the high visual variability of the images. Such a quantitative metric can be employed not only to improve the robustness of automated systems, but also to assist medical professionals in identifying complex cases. In this paper, we propose Entropy-based Elastic Ensemble of DCNN models (3E-Net) for grading invasive breast carcinoma microscopy images which provides an initial stage of explainability (using an uncertainty-aware mechanism adopting entropy). Our proposed model has been designed in a way to (1) exclude images that are less sensitive and highly uncertain to our ensemble model and (2) dynamically grade the non-excluded images using the certain models in the ensemble architecture. We evaluated two variations of 3E-Net on an invasive breast carcinoma dataset and we achieved grading accuracy of 96.15% and 99.50%.

Artificial intelligence grading of breast cancer: a promising method to refine prognostic classification for management precision

AIM

Artificial intelligence (AI)-based breast cancer grading may help to overcome perceived limitations of human assessment. Here, the potential value of AI grade was evaluated at the molecular level and in predicting patient outcome.

METHODS AND RESULTS

A supervised convolutional neural network (CNN) model was trained on images of 612 breast cancers from The Cancer Genome Atlas (TCGA). The test set, obtained from the Cooperative Human Tissue Network (CHTN), comprised 1058 cancers with corresponding survival data. Upon reversal, a CNN was trained from images of 1537 CHTN cancers and tested on 397 TCGA cancers. In TCGA, mRNA models were trained using AI grade and Nottingham grade (NG) as labels. Performance of mRNA models in predicting patient outcome was evaluated using data from 1807 cancers from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. In selecting images for training, nucleolar prominence determined high- versus low-grade cancer cells. In CHTN, NG corresponded to significant survival stratification in stages 1, 2 and 3 cancers, while AI grade showed significance in stages 1 and 2 and borderline in stage 3 tumours. In METABRIC, the mRNA model trained from AI grade was not significantly different to the NG-based model. The gene which best described AI grade was TRIP13, a gene involved with mitotic spindle assembly.

CONCLUSION

An AI grade trained from the morphologically distinctive feature of nucleolar prominence could transmit significant patient outcome information across three independent patient cohorts. AI grade shows promise in gene discovery and for second opinions.

The Role of Ki67 in Evaluating Neoadjuvant Endocrine Therapy of Hormone Receptor-Positive Breast Cancer

Ki67 is a proliferation marker. It has been proposed as a useful clinical marker for breast cancer subtype classification, prognosis, and prediction of therapeutic response. But the questionable analytical validity of Ki67 prevents its widespread adoption of these measures for treatment decisions in breast cancer. Currently, Ki67 has been tested as a predictive marker for chemotherapy using clinical and pathological response as endpoints in neoadjuvant endocrine therapy. Ki67 can be used as a predictor to evaluate the recurrence-free survival rate of patients, or its change can be used to predict the preoperative "window of opportunity" in neoadjuvant endocrine therapy. In this review, we will elaborate on the role of Ki67 in neoadjuvant endocrine therapy in breast cancer.

Circulating tumor DNA in neoadjuvant-treated breast cancer reflects response and survival

BACKGROUND

Pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) is strongly associated with favorable outcome. We examined the utility of serial circulating tumor DNA (ctDNA) testing for predicting pCR and risk of metastatic recurrence.

PATIENTS AND METHODS

Cell-free DNA (cfDNA) was isolated from 291 plasma samples of 84 high-risk early breast cancer patients treated in the neoadjuvant I-SPY 2 TRIAL with standard NAC alone or combined with MK-2206 (AKT inhibitor) treatment. Blood was collected at pretreatment (T0), 3 weeks after initiation of paclitaxel (T1), between paclitaxel and anthracycline regimens (T2), or prior to surgery (T3). A personalized ctDNA test was designed to detect up to 16 patient-specific mutations (from whole-exome sequencing of pretreatment tumor) in cfDNA by ultra-deep sequencing. The median follow-up time for survival analysis was 4.8 years.

RESULTS

At T0, 61 of 84 (73%) patients were ctDNA positive, which decreased over time (T1: 35%; T2: 14%; and T3: 9%). Patients who remained ctDNA positive at T1 were significantly more likely to have residual disease after NAC (83% non-pCR) compared with those who cleared ctDNA (52% non-pCR; odds ratio 4.33, P = 0.012). After NAC, all patients who achieved pCR were ctDNA negative (n = 17, 100%). For those who did not achieve pCR (n = 43), ctDNA-positive patients (14%) had a significantly increased risk of metastatic recurrence [hazard ratio (HR) 10.4; 95% confidence interval (CI) 2.3-46.6]; interestingly, patients who did not achieve pCR but were ctDNA negative (86%) had excellent outcome, similar to those who achieved pCR (HR 1.4; 95% CI 0.15-13.5).

CONCLUSIONS

Lack of ctDNA clearance was a significant predictor of poor response and metastatic recurrence, while clearance was associated with improved survival even in patients who did not achieve pCR. Personalized monitoring of ctDNA during NAC of high-risk early breast cancer may aid in real-time assessment of treatment response and help fine-tune pCR as a surrogate endpoint of survival.