Estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status in invasive breast cancer: a 3,198 cases study at National Cancer Center, China

External Quality Assurance Helps Improve Infrastructure for Testing Breast Biomarkers Across a Lower- and Middle-Income Country: Our Experience With Breast Biomarker Testing in the National Cancer Grid External Quality Assurance System in India

CONTEXT.—

Biomarkers in breast cancer need strict monitoring given their role in patient management.

OBJECTIVE.—

To study the impact that regular participation in the National Cancer Grid (NCG) external quality assurance (EQA) system has on concordance rates for biomarkers in breast carcinoma.

DESIGN.—

Tissue microarrays (TMAs) containing breast carcinomas were circulated to participating laboratories that performed immunohistochemistry for breast biomarkers. The returned TMAs were then assessed for test concordance.

RESULTS.—

A total of 105 laboratories participated in the estrogen receptor (ER) and progesterone receptor (PR) EQA system cycles, and 99 centers participated in the human epidermal growth factor 2 (HER2) EQA system. In the ER EQA in the first cycle only 1 laboratory had a 100% concordance rate, which improved to 59 of 77 (76.6%) and 85 of 97 (87.6%) in the fourth and fifth cycles, respectively. In the PR EQA the 100% pass rate jumped from zero to 52 of 76 (68.4%) in the fourth cycle and 86 of 97 (88.6%) in the last cycle. For HER2 EQA, the 100% pass rates were seen in 7 of 23 laboratories (30.4%) in the first cycle, 49 of 78 laboratories (62.8%) in the fourth cycle, and 48 of 94 laboratories (51.1%) in fifth cycle of EQA. Centers that participated in the NCG EQA system for a longer period often changed testing methodology, with consequent improvement in their laboratory concordance rates. An increasing trend for the use of automated platforms and of the US Food and Drug Administration-approved antibody for HER2 testing was observed.

CONCLUSIONS.—

Our experience demonstrates that laboratory performance improves with participation in an EQA system even in less perfect settings, and this drives the placement of more proficient practices across the country.

The diagnostic performance of dual-layer spectral detector CT for distinguishing breast cancer biomarker expression and molecular subtypes

To evaluate the diagnostic performance of dual-layer spectral detector CT for differentiation of breast cancer molecular subtypes. This study was done in a retrospective approach including 104 female patients histopathologically proven to have breast cancer. These patients underwent chest arterial and venous phase dual-layer SDCT. CT values, iodine concentrations (IC)s, and Z-effective (Zeff) values of the lesions and arteries in the same layer were determined for both arterial and venous phases. Parameter values were normalized, and slopes of the spectral curves (λHu) were calculated. Breast cancer biomarkers were also analyzed. Afterward, correlations between the obtained parameters and biomarkers were analyzed. Eventually, the diagnostic performance was assessed using ROC curves. ER or PR-negative patients generally showed significantly higher mean iodine concentrations, CT, and Z-effective values. HER2-positive patients showed significantly higher CTVE, ZeffVE, N-ZeffVE, ICART, ICVE, NICART, NICVE, and λVE. Only ICVE and ZeffVE differed significantly between Ki67-positive and negative patients. All parameters showed significant diagnostic value for subtypes except N-ZeffART. Luminal and non-luminal types differed significantly and ROC curves indicated that multi-factors had the best diagnostic efficacy. The dual-layer SDCT distinguishes breast cancer biomarker expression and molecular subtypes. Thus, it can be used for preoperative assessment of breast cancer.

Multidimensional analysis to elucidate the possible mechanism of bone metastasis in breast cancer

BACKGROUND

Breast cancer (BC) patients tend to suffer from distant metastasis, especially bone metastasis.

METHODS

All the analysis based on open-accessed data was performed in R software, dependent on multiple algorithms and packages. The RNA levels of specific genes were detected using quantitative Real-time PCR as a method of detecting the RNA levels. To assess the ability of BC cells to proliferate, we utilized the CCK8 test, colony formation, and the 5-Ethynyl-20-deoxyuridine assay. BC cells were evaluated for invasion and migration by using Transwell assays and wound healing assays.

RESULTS

In our study, we identified the molecules involved in BC bone metastasis based on the data from multiple BC cohorts. Then, we comprehensively investigated the effect pattern and underlying biological role of these molecules. We found that in the identified molecules, the EMP1, ACKR3, ITGA10, MMP13, COL11A1, and THY1 were significantly correlated with patient prognosis and mainly expressed in CAFs. Therefore, we explored the CAFs in the BC microenvironment. Results showed that CAFs could activate multiple carcinogenic pathways and most of these pathways play an important role in cancer metastasis. Meanwhile, we noticed the interaction between CAFs and malignant, endothelial, and M2 macrophage cells. Moreover, we found that CAFs could induce the remodeling of the BC microenvironment and promote the malignant behavior of BC cells. Then, we identified MMP13 for further analysis. It was found that MMP13 can enhance the malignant phenotype of BC cells. Meanwhile, biological enrichment and immune infiltration analysis were conducted to present the effect pattern of MMP13 in BC.

CONCLUSIONS

Our result can improve the understanding of researchers on the underlying mechanisms of BC bone metastasis.

A Comprehensive Model Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Better Predict the Preoperative Histological Grade of Breast Cancer Than a Radiomics Model

Background

Histological grade is an important prognostic factor for patients with breast cancer and can affect clinical decision-making. From a clinical perspective, developing an efficient and non-invasive method for evaluating histological grading is desirable, facilitating improved clinical decision-making by physicians. This study aimed to develop an integrated model based on radiomics and clinical imaging features for preoperative prediction of histological grade invasive breast cancer.

Methods

In this retrospective study, we recruited 211 patients with invasive breast cancer and randomly assigned them to either a training group (n=147) or a validation group (n=64) with a 7:3 ratio. Patients were classified as having low-grade tumors, which included grade I and II tumors, or high-grade tumors, which included grade III tumors. Three models were constructed based on basic clinical features, radiomics features, and the sum of the two. To assess diagnostic performance of the radiomics models, we employed measures such as receiver operating characteristic (ROC) curve, decision curve analysis (DCA), accuracy, sensitivity, and specificity, and the predictive performance of the three models was compared using the DeLong test and net reclassification improvement (NRI).

Results

The area under the curve (AUC) of the clinical model, radiomics model, and comprehensive model was 0.682, 0.833, and 0.882 in the training set and 0.741, 0.751, and 0.836 in the validation set, respectively. NRI analysis confirmed that the combined model was better than the other two models in predicting the histological grade of breast cancer (NRI=21.4% in the testing cohort).

Conclusion

Compared with the other models, the comprehensive model based on the combination of basic clinical features and radiomics features exhibits more significant potential for predicting histological grade and can better assist clinicians in optimal decision-making.

Breast cancer molecular subtype and relationship with clinicopathological profiles among Vietnamese women: A retrospective study

BACKGROUND

Molecular subtypes play an important role in predicting prognosis and guiding treatment for breast cancer. Having a better knowledge of ethnic molecular features is essential.

OBJECTIVES

Determining the distribution of various breast cancer molecular subtypes and investigating the relationship between these subtypes and clinicopathological features.

METHODS

Retrospective data was collected from Hanoi National Cancer Hospital and Bach Mai Hospital that included 274 women diagnosed with invasive breast cancer between January 2017 and June 2019. Patients were categorized into five subtypes according to the 2015 St. Gallen molecular classification. The variables analyzed were molecular subtypes and tumor-related characteristics. To evaluate the relationship between these subtypes and clinicopathological features, a Chi-squared test and Fisher exact test were performed.

RESULTS

The most prominent subtype was Luminal A (33.2%), followed by Luminal B/Her2- (19.7%) and Luminal B/Her2 + (17.5%), then HER2 overexpression (16.4%), whereas triple negative was the least popular subtype (13.1%). Particularly, 33.9% of all patients, including the Luminal B/Her2 + and the HER2 overexpressing groups, were Her2 positive. There was a statistically significant difference between molecular subtypes and histological type (p = 0.01), tumor grade (p < 0.001), but it was independent of age, tumor size, lymph node metastasis, and lymphovascular invasion.

CONCLUSIONS

In contrast to the triple negative variant, the Luminal A variant is the most common among Vietnamese women. The rate of positive tests for HER2 was rather high. These subtypes were closely related to tumor grade and histopathological type. Understanding the molecular subtypes and their relation to clinicopathological features helps clinicians with patient treatment, and prognosis. The application of the 2015 St. Gallen molecular classification should be recommended for use in clinical practice.

The correlation between imaging findings and breast cancer cell receptors status

INTRODUCTION

Breast cancer is the most common malignancy among women, and subtypes are mainly defined based on hormone receptors such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). The relationship between breast cancer subtypes and imaging features in mammography and sonography has been studied but the results are controversial. The purpose of this study was to determine the relationship between the hormonal receptor status of breast tumors and the radiologic feature of the tumors on mammography and sonography.

METHODS

Eighty patients with breast cancer enrolled in this cross-sectional study. ER, PR, and HER2 determined by immunohistochemistry. Every patient underwent mammography and sonography before the biopsy. We evaluated the relationship between the hormonal receptor status and radiographic features of tumors on breast sonography and mammography.

RESULTS

The majority of the patients (n=75 (93.8%)) were diagnosed with invasive ductal carcinoma (IDC). The mean and standard deviation of the age was 49 ± 9 years. There was no significant relationship between the hormonal receptor status and the sonographic margin and shape (P>0.05). However, PR (P=0.002) and ER (P=0.001) status were significantly correlated with posterior features on sonography. ER-positive patients were more likely to have indistinct or speculated masses on mammography (P=0.017). Irregular or oval masses on mammography were higher in patients with ER (p=0.032).

CONCLUSION

There was a significant correlation between PR and ER status and posterior features on sonography. Positive ER was associated with indistinct or speculated masses on mammography, as well as irregular or oval masses.

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer

To investigate the correlations between ultrasonographic morphological characteristics quantitatively assessed using a deep learning-based computer-aided diagnostic system (DL-CAD) and histopathologic features of breast cancer.This retrospective study included 282 women with invasive breast cancer (<5 cm; mean age, 54.4 [range, 29-85] years) who underwent surgery between February 2016 and April 2017. The morphological characteristics of breast cancer on B-mode ultrasonography were analyzed using DL-CAD, and quantitative scores (0-1) were obtained. Associations between quantitative scores and tumor histologic type, grade, size, subtype, and lymph node status were compared.Two-hundred and thirty-six (83.7%) tumors were invasive ductal carcinoma, 18 (6.4%) invasive lobular carcinoma, and 28 (9.9%) micropapillary, apocrine, and mucinous. The mean size was 1.8 ± 1.0 (standard deviation) cm, and 108 (38.3%) cases were node positive. Irregular shape score was associated with tumor size (P < .001), lymph nodes status (P = .001), and estrogen receptor status (P = .016). Not-circumscribed margin (P < .001) and hypoechogenicity (P = .003) scores correlated with tumor size, and non-parallel orientation score correlated with histologic grade (P = .024). Luminal A tumors exhibited more irregular features (P = .048) with no parallel orientation (P = .002), whereas triple-negative breast cancer showed a rounder/more oval and parallel orientation.Quantitative morphological characteristics of breast cancers determined using DL-CAD correlated with histopathologic features and could provide useful information about breast cancer phenotypes.

Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer

BACKGROUND

Human epidermal growth factor receptor2+ subtype breast cancer has a high degree of malignancy and a poor prognosis. The aim of this study is to develop a prediction model for the human epidermal growth factor receptor2+ subtype (non-luminal) of breast cancer based on the clinical and ultrasound features related with estrogen receptor, progesterone receptor, and human epidermal growth factor receptor2.

METHODS

We collected clinical data and reviewed preoperative ultrasound images of enrolled breast cancers from September 2017 to August 2020. We divided the data into in three groups as follows. Group I: estrogen receptor ± , Group II: progesterone receptor ± and Group III: human epidermal growth factor receptor2 ± . Univariate and multivariate logistic regression analyses were used to analyze the clinical and ultrasound features related with biomarkers among these groups. A model to predict human epidermal growth factor receptor2+ subtype was then developed based on the results of multivariate regression analyses, and the efficacy was evaluated using the area under receiver operating characteristic curve, accuracy, sensitivity, specificity.

RESULTS

The human epidermal growth factor receptor2+ subtype accounted for 138 cases (11.8%) in the training set and 51 cases (10.1%) in the test set. In the multivariate regression analysis, age ≤ 50 years was an independent predictor of progesterone receptor + (p = 0.007), and posterior enhancement was a negative predictor of progesterone receptor + (p = 0.013) in Group II; palpable axillary lymph node, round, irregular shape and calcifications were independent predictors of the positivity for human epidermal growth factor receptor-2 in Group III (p = 0.001, p = 0.007, p = 0.010, p < 0.001, respectively). In Group I, shape was the only factor related to estrogen receptor status in the univariate analysis (p < 0.05). The area under receiver operating characteristic curve, accuracy, sensitivity, specificity of the model to predict human epidermal growth factor receptor2+ subtype breast cancer was 0.697, 60.14%, 72.46%, 58.49% and 0.725, 72.06%, 64.71%, 72.89% in the training and test sets, respectively.

CONCLUSIONS

Our study established a model to predict the human epidermal growth factor receptor2-positive subtype with moderate performance. And the results demonstrated that clinical and ultrasound features were significantly associated with biomarkers.

Development and external validation of a breast cancer absolute risk prediction model in Chinese population

BACKGROUNDS

In contrast to developed countries, breast cancer in China is characterized by a rapidly escalating incidence rate in the past two decades, lower survival rate, and vast geographic variation. However, there is no validated risk prediction model in China to aid early detection yet.

METHODS

A large nationwide prospective cohort, China Kadoorie Biobank (CKB), was used to evaluate relative and attributable risks of invasive breast cancer. A total of 300,824 women free of any prior cancer were recruited during 2004-2008 and followed up to Dec 31, 2016. Cox models were used to identify breast cancer risk factors and build a relative risk model. Absolute risks were calculated by incorporating national age- and residence-specific breast cancer incidence and non-breast cancer mortality rates. We used an independent large prospective cohort, Shanghai Women's Health Study (SWHS), with 73,203 women to externally validate the calibration and discriminating accuracy.

RESULTS

During a median of 10.2 years of follow-up in the CKB, 2287 cases were observed. The final model included age, residence area, education, BMI, height, family history of overall cancer, parity, and age at menarche. The model was well-calibrated in both the CKB and the SWHS, yielding expected/observed (E/O) ratios of 1.01 (95% confidence interval (CI), 0.94-1.09) and 0.94 (95% CI, 0.89-0.99), respectively. After eliminating the effect of age and residence, the model maintained moderate but comparable discriminating accuracy compared with those of some previous externally validated models. The adjusted areas under the receiver operating curve (AUC) were 0.634 (95% CI, 0.608-0.661) and 0.585 (95% CI, 0.564-0.605) in the CKB and the SWHS, respectively.

CONCLUSIONS

Based only on non-laboratory predictors, our model has a good calibration and moderate discriminating capacity. The model may serve as a useful tool to raise individuals' awareness and aid risk-stratified screening and prevention strategies.

Prevalence of Molecular Subtypes of Breast Cancer: A Single Institutional Experience of 2062 Patients

Objective

The aim of the study was to analyze the prevalence of molecular subtypes of all breast cancer patients treated at tertiary cancer centre in West India in 12 years.

Materials and Methods

A retrospective observational study carried out in Tertiary Cancer Care Centre in Western India. Electronic medical records of all breast cancer patients were retrieved from the hospital database between March 2007 to March 2019. Patient's characteristic, histological features and molecular subtypes were collected and analyzed.

Results

A total of 2062 women fulfilled the criteria for this study and were analyzed. The median age of study population was 51 years (range 22-100 years). Among these, 1357 (65.8%) were of ≤55 years and 705 (34.2%) were over 55 years. The overall incidence of Hormonal Receptor-positive patients (either estrogen-receptor (ER) or progesterone-receptor (PR) or both) was 1162 (56.4%). The Mean tumor size was 3.8cm (range 0-18cm). The most common histology was IDC (96%). Axillary nodes were positive in 62.5%. Luminal type A was positive in 762 (37%) patients while Luminal type B was present in 157 (7.6%) patients. Basal-like subtype was observed in 537 (26%) patients while HER2 rich subtype was seen in 229 (11.1%). The incidence of Luminal A subtype increased with age. The highest observed among patients (72%) aged 70 years or more. Incidence of Basal like subtype was highest in patients less than 30 years (52%).

Conclusion

Luminal-like disease is the most common molecular subtype in India. Identification of Basal like breast cancer, a highly aggressive, biologically and clinically distinct subtype different than its non-basal variant, is important for treatment planning and target therapy.

Luminal B is the Most Common Intrinsic Molecular Subtypes of Invasive Ductal Breast Carcinoma Patients in East Kalimantan, Indonesia

Objective: Breast carcinoma has no longer been considered as a single and standalone disease. Its subtypes have been known to vary in terms of risk factors, natural histories, and responses to therapies. In particular, intrinsic molecular subtypes based on St. Gallen International Expert Consensus 2013 have classified breast carcinoma into luminal A, luminal B, HER2+, and triple-negative, depending on the expression of ER, PgR, HER2, and Ki-67. Research on intrinsic molecular subtypes of breast carcinoma in Indonesia, however, are rarely conducted, which then triggers the intention to conduct this study. Methods: In this work, a retrospective study was conducted on 92 formalin-fixed paraffin-embedded samples of invasive ductal breast carcinoma patients. These samples were from patients at Abdul Wahab Sjahranie County General Hospital Samarinda, East Kalimantan, Indonesia, in 2016. Next, immunohistochemical staining using anti-ER, PgR, HER2, and Ki-67 antibodies was applied to classify intrinsic molecular subtypes. Then, an association between clinical and immunohistochemical factors with intrinsic molecular subtypes of breast carcinoma were analyzed using Chi-square test. Results: Looking at results of the retrospective study, luminal B was discovered as the most common intrinsic molecular subtypes of breast carcinoma (42.39%) in East Kalimantan, Indonesia. The next ranks of breast carcinoma subtypes in the region included HER2+ (39.13%), triple-negative (10.87%), and luminal A (7.61%). In fact, there was a significant association between age (p = 0.019) with intrinsic molecular subtypes of breast carcinoma. Conclusion: The study found luminal B as the most common intrinsic molecular subtypes of Indonesian breast carcinoma in the region under investigation. In the future, the higher positivity rate of luminal B in breast carcinoma patients compared to prior studies would require further investigations.

Increased systemic immune-inflammation index independently predicts poor survival for hormone receptor-negative, HER2-positive breast cancer patients

Purpose: We sought to examine the role of pretreatment systemic immune-inflammation index (SII) in hormone receptor-negative, human epidermal growth factor receptor 2+ (HER2+) breast cancer patients.

Patients and methods: 155 HER2+ patients treated in our hospital from September 3, 2002, to September 21, 2012, were retrospectively enrolled. SII was established as neutrophil x platelet/lymphocyte counts. The median value of SII was used as cut-off value. We used the Kaplan-Meier method to evaluate the overall survival (OS), disease-free survival (DFS), distant metastasis-free survival (DMFS). To comparatively evaluate the survival rates between patients from two groups, we used the log-rank test. For identifying independent factors of prognosis, we used the Cox regression model, applying multivariate statistics.

Results: Analyses show that HER2+ patients with high and low SII had median DFS of 15.1 and 31.5 months, respectively (P<0.001), while the median DMFS in HER2+ patients with high SII was 18.4 and in patients with low SII was 33.0 months (P=0.001), and the median OS were 54.5 and 71.1 months respectively in high and low SII patients, respectively (P=0.002). Multivariate analysis had revealed increased SII independently linked to poor DFS (HR =1.46, 95% CI: 1.01–2.11, P=0.045). The difference between SII and DMFS bore no statistical significance. (HR =1.40, 95% CI: 0.96–2.03, P=0.078), while high SII independently predicted short OS (HR =1.51, 95% CI: 1.02–2.25, P=0.038).

Conclusion: Our findings suggest that increased SII independently predicts poor survival for hormone receptor-negative, HER2+ breast cancer patients. Prospective studies are, however, required to confirm the role of SII in the prognosis of patients with HER2+ before clinical use.

Breast cancer primary tumor ER expression pattern predicts its expression concordance in matched synchronous lymph node metastases

Background

Estrogen receptor (ER) expression is important for treatment selection and prognostication of breast cancer patients. Although the metastases are the main targets of endocrine therapy, ER status is often based on the primary tumor. However, ER expression in breast cancer primary lesion may not match with its synchronous metastatic lesions in some cases. In this study, we analyzed ER expression concordance between breast cancer primary tumor and metastatic lesions.

Methods

Paraffin blocks of 100 primary breast invasive ductal carcinoma cases with axillary lymph node metastases were collected. Five tissue cores were punched out from individual primary breast cancer, and one tissue core from each lymph node metastases to assemble tissue microarrays for ER staining. Samples were then scored as 0, 1+, 2+, and 3+ according to the number and intensity of ER stained tumor cells.

Results

For cases with ER 3+ (strong expression) in all cores of primary lesions (n = 38), ER expression in metastatic lymph node was found in 94.7% of the patients. 91.0% of the metastatic lymph nodes were ER positive, and 84.3% of them to be 3+. Among the 46 cases of ER negative expression in all cores of primary lesions, 39 of them had all the metastatic nodes being ER negative, and ER negative nodes were seen in 95.7% of the metastases. As for 16 cases of ER inconsistent expression in primary lesions, 4 cases showed negative ER expression in all metastatic nodes, 2 cases displayed diffuse consistent ER 3+ expression, and 10 cases displayed variant ER expression.

Conclusions

The findings suggest that ER expression concordance between breast cancer primary lesion and its matched metastatic lesions could be estimated by primary tumor ER expression pattern.

Characteristics and prognostic values of traditional pathological parameters and advanced molecular subtypes in women in Beijing with operable breast cancer: a retrospective analysis

OBJECTIVES

This study investigated the characteristics and prognostic values of traditional pathological parameters and advanced molecular subtypes in women with operable breast cancer in Beijing.

DESIGN

A retrospective study through case information enquiry or telephonic follow-up.

SETTING

Beijing Friendship Hospital.

PARTICIPANTS

1042 patients with primary operable breast cancer between 2008 and 2012 were enrolled in the study.

MEASURES

The characteristics and 5-year relapse rates according to the Nottingham Prognosis Index (NPI) and molecular subtypes were analysed.

RESULTS

In 1042 patients, the percentages of high histological grade, N1+N2, T2+T4 were 7.3%, 24.2%, 46.9%, respectively. In patients with invasive breast cancer, the percentages of auxiliary staging, positive margins, vascular invasion and nerve infiltration were 65.0%, 2.8%, 10.5% and 1.1%, respectively. The missing percentages of auxiliary staging, margins, vascular tumour invasion and nerve infiltration were 14.2%, 31.4%, 46.5% and 97.4%, respectively. The percentages of ER-positive, PR-positive, HER2-positive and Ki-67 high expression were 64.3%, 43.8%, 18.8% and 62.7%, respectively. The percentages of luminal A, luminal B, HER2-overexpression and basal-like breast cancers were 10.5%, 54.2%, 8.2% and 11.2%, respectively. Luminal A, luminal B and basal-like breast cancer subtypes were more common in the >60 years group, the 41-60 years group and the 20-40 years group, respectively. The 5-year relapse rates according to NPI were as follows: 6.2% in the low recurrence risk group, 10.4% in the moderate recurrence risk group and 12.9% in the high recurrence risk group. The 5-year relapse rates according to molecular subtypes were as follows: luminal A 4.0%, luminal B 7.0%, HER2-overexpression14.2%, basal-like 15.6%.

CONCLUSIONS

Reasonable analysis of traditional pathological parameters and advanced molecular subtypes in women with operable breast cancer in Beijing may be useful to guide precise treatment and predict prognosis.

Increased derived neutrophil-to-lymphocyte ratio and Breast Imaging-Reporting and Data System classification predict poor survival in patients with non-distant metastatic HER2+ breast cancer treated with neoadjuvant chemotherapy

Introduction

The prognostic role of the derived neutrophil-to-lymphocyte ratio (dNLR) in human patients with HER2+ breast cancer is not well understood. Here, we aimed to investigate the prognostic significance of dNLR in patients with HER2+ breast cancer undergoing neoadjuvant chemotherapy.

Methods

A total of 310 patients with non-distant metastatic HER2+ breast cancer who had received neoadjuvant chemotherapy in our hospital from May 2006 to November 2013 were retrospectively included in this study. Kaplan–Meier curves were used to assess overall survival (OS) and disease-free survival (DFS). The Cox regression model was used to evaluate the prognostic value of dNLR and Breast Imaging-Reporting and Data System (BI-RADS) classification, as well as other clinicopathological parameters in patients with HER2+ breast cancer treated with neoadjuvant chemotherapy.

Results

We found that dNLR prior to treatment was positively correlated with tumor size, tumor stage, lymphovascular invasion, and histological grade (P<0.05). The median OS of patients with high dNLR and low dNLR were 44.2 and 69.9, respectively (P<0.001), and the median DFS of patients with high dNLR and low dNLR were 15.3 and 22.1 months, respectively (P<0.001). Multivariate analysis showed that dNLR was an independent risk factor for OS (HR =1.726; 95% CI: 1.072–2.662; P=0.009) and DFS (HR =1.658; 95% CI: 1.125–2.426; P=0.026). Moreover, increased BI-RADS classification independently predicted short OS (HR =1.609; 95% CI: 1.216–2.351; P=0.015) and DFS (HR =1.925; 95% CI: 1.526–2.635; P=0.021).

Conclusion

dNLR prior to treatment and BI-RADS classification are independent prognostic factors in patients with HER2+ breast cancer receiving neoadjuvant chemotherapy.

Presentation of the Molecular Subtypes of Breast Cancer Detected By Immunohistochemistry in Surgically Treated Patients

INTRODUCTION

The detection of estrogen, progesterone and HER-2 neu receptors on the surface of the tumour cell is a significant prognostic factor, alone or in combination. The presence or absence of receptors on the surface of the tumour cell is associated with the conditional gene expression in the tumour cell itself. Based on these genetically determined expressions of the tumour cell, five molecular subtypes of breast cancer have been classified on the St. Gallen International Expert Consensus in 2011 that can be immunohistochemically detected, with each subtype manifesting certain prognosis and aggression.

AIM

Analyzing the presentation of molecular subtypes of breast cancer that are immunohistochemically detected in surgically treated patients at the Clinic for Thoracic and Vascular Surgery.

MATERIAL AND METHODS

We used the international classification on molecular subtypes of breast cancer which divides them into: Luminal A (ER+ and/or PR+, HER-2 negative, Ki-67 < 14%), Luminal B with HER-2 negative (ER+ and/or PR+, HER-2 negative, Ki-67 ≥ 14%), Luminal B with HER-2 positive (ER+ and/or PR+, HER-2+, any Ki-67), HER-2 enriched (ER-, PR-, HER-2+), and basal-like (triple negative) (ER-, PR-, HER-2 negative, CK5/6+ and/or EGFR+). A total of 290 patients, surgically treated for breast cancer, were analysed during 2014.

RESULTS

In our analysis, we found that Luminal A was present in 77 (26.55%) patients, Luminal B HER-2 negative was present in 91 (31.38%) patients, Luminal B HER-2 positive was present in 70 (24.14%) patients, HER-2 enriched was present in 25 (8.62%) patients and basal-like (or triple negative) was present in 27 (9.31%) patients.

CONCLUSION

Detecting the subtype of breast cancer is important for evaluating the prognosis of the disease, but also for determining and providing an adequate therapy. Therefore, determining the subtype of breast cancer is necessary for the routine histopathological assay.

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

Improving accuracy of breast cancer biomarker testing in India

There is a global mandate even in countries with low resources to improve the accuracy of testing biomarkers in breast cancer viz. oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2neu) given their critical impact in the management of patients. The steps taken include compulsory participation in an external quality assurance (EQA) programme, centralized testing, and regular performance audits for laboratories. This review addresses the status of ER/PR and HER2neu testing in India and possible reasons for the delay in development of guidelines and mandate for testing in the country. The chief cause of erroneous ER and PR testing in India continues to be easily correctable issues such as fixation and antigen retrieval, while for HER2neu testing, it is the use of low-cost non-validated antibodies and interpretative errors. These deficiencies can however, be rectified by (i) distributing the accountability and responsibility to surgeons and oncologist, (ii) certification of centres for testing in oncology, and (iii) initiation of a national EQA system (EQAS) programme that will help with economical solutions and identifying the centres of excellence and instill a system for reprimand of poorly performing laboratories.

Validity of St Gallen risk categories in prognostication of breast cancer patients in Southern Sri Lanka

Background

Although, there are many developments in the field of management, breast cancer is still the commonest cause of cancer related deaths in women in Sri Lanka. This emphasizes the need for validation of treatment protocols that are used in Sri Lanka for managing breast cancers. There are no published papers on treatment and survival of breast cancer patients in Sri Lanka. Hence this study was designed to determine the validity of St Gallen risk categories based on the survival outcomes of breast cancer patients in Southern Sri Lanka.

Method

This retro-prospective study included all female breast cancer patients who had sought the immunohistochemistry services of our unit from May 2006 to December 2012. Patients who had neo-adjuvant chemotherapy were excluded. Patients were stratified according to the St Gallen risk categories; low-risk (LR), intermediate-risk (IR) and high-risk (HR), which is used in deciding on the adjuvant treatment. IR category was subdivided based on presence/absence of 1–3 positive-nodes (absent-IR1, present-IR2) and HR on the number of positive-nodes(1–3 lymph nodes;HR1,> 3 lymph nodes;HR2). Kaplan-Meier and Cox-regression models were used in the survival analysis.

Results

This study included 713breast cancer patients (LR-2%, IR1–45%, IR2–10%, HR1–13%, HR2–30%). Five year breast cancer specific survival (BCSS)wasLR-100%, IR-91%, HR-66% and the recurrence free survival (RFS) was LR-85%, IR-84%, HR-65%. BCSS and RFS curves were significantly different between the three risk categories (p < 0.001).

No survival difference was evident between the IR1 and IR2 (BCSS-p = 0.232, RFS-p = 0.118). HR1 and HR2 had a distinctly different BCSS (p = 0.033) with no difference in RFS (p = 0.190).

Conclusion

This study validates the St Gallen risk categorization of female breast cancer patients in our setting. However, the HR includes two subsets of patients with a distinct difference in BCSS.

Prognostic parameters of luminal A and luminal B intrinsic breast cancer subtypes of Pakistani patients

Background

Prognosis of breast cancer and success of therapeutic interventions largely rely on the clinico-pathologic and biological characteristics of the tumor and vary due to the heterogeneous nature of breast cancers. The aim of this study was to determine the frequency and prognostic parameters of luminal breast cancers in our population to devise targeted and personalized therapeutic regimens tailored to the needs of the loco-regional population.

Methods

A retrospective cross-sectional study including 1951 cases of primary breast cancer treated at Liaquat National Hospital Karachi was conducted during the year 2011–2016. The clinico-pathologic characteristics were observed and semiquantitative immunohistochemical analysis was performed to study the luminal subtypes A and B. The cross-tabulated statistics of the observed characteristics were performed between the two subtypes. The significance level of each characteristic was estimated utilizing the chi-square test.

Results

Luminal cancers comprised 62.7% of the total number of cases diagnosed with breast cancers in the study period. Out of these 1224 cases of luminal cancers, 845 cases (69%) were luminal B, while 379 (31%) cases were of luminal A. Luminal B cancers were significantly more common in younger age groups as compared to luminal A cancers. Comparison of the two subtypes of luminal breast cancers revealed significant differences. Luminal B cancers were associated with higher grade (26% grade III in luminal B compared to 8% in luminal A), micropapillary histology, and high frequency of nodal metastasis (54 vs. 43%).

Conclusions

Luminal B comprised the most frequent subtype of breast cancer in our study and they were found more constantly in a younger age group. Moreover, they were associated with adverse clinico-histologic parameters like higher grade and nodal metastasis. Therefore, we suggest that, despite lack of widespread availability of molecular studies in our setup, IHC-based typing should be done in every case of breast cancer to individualize therapy.

A pathways-based prediction model for classifying breast cancer subtypes

Breast cancer is highly heterogeneous and is classified into four subtypes characterized by specific biological traits, treatment responses, and clinical prognoses. We performed a systemic analysis of 698 breast cancer patient samples from The Cancer Genome Atlas project database. We identified 136 breast cancer genes differentially expressed among the four subtypes. Based on unsupervised clustering analysis, these 136 core genes efficiently categorized breast cancer patients into the appropriate subtypes. Functional enrichment based on Kyoto Encyclopedia of Genes and Genomes analysis identified six functional pathways regulated by these genes: JAK-STAT signaling, basal cell carcinoma, inflammatory mediator regulation of TRP channels, non-small cell lung cancer, glutamatergic synapse, and amyotrophic lateral sclerosis. Three support vector machine (SVM) classification models based on the identified pathways effectively classified different breast cancer subtypes, suggesting that breast cancer subtype-specific risk assessment based on disease pathways could be a potentially valuable approach. Our analysis not only provides insight into breast cancer subtype-specific mechanisms, but also may improve the accuracy of SVM classification models.

Molecular Subtypes of Breast Cancers from Myanmar Women: A Study of 91 Cases at Two Pathology Centers

Background: Breast cancer is the most common cancer in Myanmar women. Revealing the hormonal receptor status, human epidermal growth factor receptor 2 (HER2) and Ki-67 expression is useful for estimating patient prognosis as well as determination of treatment strategy. However, immunohistochemical features and classification of molecular subtypes in breast cancers from Myanmar remain unknown. Methods: The clinicopathological features of 91 breast cancers from Myanmar women were examined. Immunohistochemistry was performed on tissue specimens with antibodies to estrogen receptor (ER), progesterone receptor (PgR), HER2, Ki-67, cytokeratin (CK)5/6 and CK14. Immunohistochemistry-based molecular subtyping was conducted. Results: Breast cancers in Myanmar women were relatively large, high grade with frequent metastatic lymph nodes. Of the 91 patients, tumors with ER positive, PgR positive, and HER2 positive were 57.1%, 37.4%, and 28.6%, respectively. The most prevalent subtype was luminal B (HER2-) (39.6%), followed by HER2 (22.0%), triple negative (TN)-basal-like (12.1%), luminal A (11.0%), TN-null (8.8%) and luminal B (HER2+) (6.6%). The mean Ki-67 expression of 91 cases was 33.9% (33.9% ± 19.2%) and the median was 28% (range; 4%-90%). The mean Ki-67 expression of luminal A, luminal B, HER2 and TN-basal-like/ null was 7%, 30%, 40%, and 57%/43%, respectively. A higher Ki-67 expression significantly correlated with a higher grade, larger size and higher stage of malignancy. Conclusions: We, for the first time, investigated the histopathological features of breast cancers from Myanmar women. Myanmar breast cancers appeared to be aggressive in nature, as evidenced by high frequency of poor-prognosis subtypes with high level of Ki-67 expression.

MicroRNA-145 functions as a tumor suppressor by targeting matrix metalloproteinase 11 and Rab GTPase family 27a in triple-negative breast cancer

Although increasing evidence has documented that microRNA-145 (miR-145) acts as a tumor suppressor in breast cancer, its exact role in triple-negative breast cancer (TNBC) remains poorly defined. In this study, the expression of miR-145 in human TNBC cells and samples from 30 patients was analyzed by stem-loop real-time PCR. We found that miR-145 was significantly downregulated in TNBC tissues and cells. Upregulating miR-145 in HCC1937 cells dramatically suppressed cell proliferation and induced G1-phase arrest, whereas MDA-MB-231 cells did not show growth inhibition. MiR-145 exhibited an inhibitory role in cell invasion through the post-transcriptional regulation of the novel targets MMP11 and Rab27a in TNBC cells. Additionally, miR-145 silencing could be reversed by 5-aza-2'-deoxycytidine (DAC). These results demonstrated that miR-145 has an inhibitory role in TNBC malignancy by targeting MMP11 and Rab27a, which might be potential therapeutic and diagnostic targets for TNBC.

Molecular Profiling of Breast Carcinoma in Almadinah, KSA: Immunophenotyping and Clinicopathological Correlation

PURPOSE

To subtype breast cancer (BC) in Saudi women according to the recent molecular classification and to correlate these subtypes with available clinicopathological parameters.

MATERIALS AND METHODS

Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (Her2/neu) immunostaining was semi-quantitatively assessed to define molecular subtypes of luminal A and B, HER-2 and triple negative (basal- like) in BC paraffin embedded sections from 115 Saudi female patients diagnosed between 2005 to 2015 at the Department of Pathology, King Fahd Hospital, Almadinah, Saudi Arabia.

RESULTS

The most common subtypes were luminal A (47%), followed by luminal B (27.8%) and basal like subtypes (18.3%), whereas HER-2 was the least common subtype (6.9%). Luminal A was predominantly found in the old age group, with low tumor grade (p< 0.001) and small tumor size, whereas HER-2 and basal-like subtypes were significantly associated with young age, high tumor grade, lymph node metastasis and lymphovascular invasion (p< 0.03, 0.004, 0.05 and 0.04 respectively). All subtypes showed advanced clinical stage at the time of presentation.

CONCLUSIONS

Molecular subtypes of Saudi BC patients in Almadinah region are consistent with most of the worldwide subtyping. The biological behaviour of each molecular subtype could be expected based on its characteristic clinicopathological features. Along with other prognostic indicators, molecular subtyping would be helpful in predicting prognosis and management of our BC patients. We recommend screening and early diagnosis of BC in our population.

Breast Cancer Subtype is Associated With Axillary Lymph Node Metastasis: A Retrospective Cohort Study

The purpose of this study was to assess whether breast cancer subtype (BCS) as determined by estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 can predict the axillary lymph node metastasis in breast cancer. Patients who received breast conserving surgery or mastectomy and axillary lymph node dissection were identified from 2 cancer centers. The associations between clinicopathological variables and axillary lymph node involvement were evaluated in univariate and multivariate regression analyses. A total of 3471 patients met the inclusion criteria, and 53.0% had axillary lymph node metastases at diagnosis. Patients with hormone receptor (HR)-/human epidermal growth factor receptor 2 (HER2)- subtype had a higher grade disease and the lowest rate of lymphovascular invasion. Univariate and multivariable logistic regression analyses showed that BCS was significantly associated with lymph node involvement. Patients with the HR-/HER2- subtype had the lowest odds of having nodal positivity than those with other BCSs. HR+/HER2- (odds ratio [OR] 1.651, 95% confidence interval [CI]: 1.349-2.021, P < 0.001), HR+/HER2+ (OR 1.958, 95%CI 1.542-2.486, P < 0.001), and HR-/HER2+ (OR 1.525, 95%CI 1.181-1.970, P < 0.001) tumors had higher risk of nodal positivity than the HR-/HER2- subtype. The other independent predictors of nodal metastases included tumor size, tumor grade, and lymphovascular invasion. Breast cancer subtype can predict the presence of axillary lymph node metastasis in breast cancer. HR-/HER2- is associated with a reduced risk of axillary lymph node metastasis compared to other BCSs. Our findings may play an important role in guiding axillary treatment considerations if further confirmed in larger sample size studies.

Identifying ultrasound and clinical features of breast cancer molecular subtypes by ensemble decision

Breast cancer is molecularly heterogeneous and categorized into four molecular subtypes: Luminal-A, Luminal-B, HER2-amplified and Triple-negative. In this study, we aimed to apply an ensemble decision approach to identify the ultrasound and clinical features related to the molecular subtypes. We collected ultrasound and clinical features from 1,000 breast cancer patients and performed immunohistochemistry on these samples. We used the ensemble decision approach to select unique features and to construct decision models. The decision model for Luminal-A subtype was constructed based on the presence of an echogenic halo and post-acoustic shadowing or indifference. The decision model for Luminal-B subtype was constructed based on the absence of an echogenic halo and vascularity. The decision model for HER2-amplified subtype was constructed based on the presence of post-acoustic enhancement, calcification, vascularity and advanced age. The model for Triple-negative subtype followed two rules. One was based on irregular shape, lobulate margin contour, the absence of calcification and hypovascularity, whereas the other was based on oval shape, hypovascularity and micro-lobulate margin contour. The accuracies of the models were 83.8%, 77.4%, 87.9% and 92.7%, respectively. We identified specific features of each molecular subtype and expanded the scope of ultrasound for making diagnoses using these decision models.

p53 expression in breast cancer predicts tumors with low probability of non-sentinel nodes infiltration

AIM

Several predictive tools of non-sentinel lymph nodes neoplastic involvement when a positive sentinel lymph node is found have been described. However, molecular factors have been rarely evaluated to build these tools. The aim of this study was to establish which factors predicted non-sentinel lymph nodes infiltration in our setting, including some molecular factors.

MATERIAL AND METHODS

We carried out a retrospective review of 161 patients with breast cancer and a positive sentinel lymph node who had undergone axillary lymph node dissection, none of whom had received neoadjuvant treatment. Features evaluated as predictive factors for non-sentinel node positivity were: menopausal status, tumor size, histological subtype, histological grade, lymphovascular invasion, extracapsular invasion, Ki67 index, hormonal receptors, CerbB2 and p53 expression, size of sentinel lymph node metastases and number of sentinel lymph nodes affected.

RESULTS

Tumor size (P = 0.001), size of sentinel lymph node metastases (P = 0.001), lobular invasive carcinoma (P = 0.05) and lymphovascular invasion (P = 0.006) were significantly associated with non-sentinel lymph node positivity. Tumor p53 positive expression was strongly associated with non-sentinel lymph node negativity (P = 0.000). In multivariate analysis, all these factors but tumor size maintained their significance. The discrimination power of the model calculated by the area under the receiver-operator curve was 0.811 (95% confidence interval, 0.741-0.880).

CONCLUSION

p53 expression in breast cancer was highly predictive of non-sentinel lymph node negativity in our study. New studies should evaluate if it would be useful to add p53 expression to other existing predictive tools.