Utility of PHH3 in Evaluation of Mitotic Index in Breast Carcinoma and Impact on Tumor Grade

Background:

Mitotic activity index is considered as the most important grading component to predict prognosis in invasive breast carcinoma. But it is believed that it is also the cause of discordance in grade estimation based on Bloom-Richardson system. Thus, reproducible methods such as immunohistochemistry (IHC) based analysis methods appears to be of great value in facilitating mitotic count.

Materials and Methods:

In the present study, we examined the utility of Phosphohistone H3 by IHC in various grades of breast carcinoma and compared it with traditional mitotic count by hematoxylin and eosin (H and E) staining and probable changes in tumor grading.

Results:

Total 90 cases of invasive breast carcinoma were evaluated. Mean mitotic count were 8.6 and 6.4/10HPF in IHC and HandE groups, respectively. Although , mean average count was higher by IHC method , good correlation was observed(R=0.914). Using PHH3 IHC, two out of 33 cases of grade I tumors were upgraded in to grade II and three cases of grade II were upgraded in to grade III. None of the tumors were down graded.

Conclusion:

Similar to some other previous studies, we found PHH3 a robust sensitive and practical marker for mitotic count in breast carcinoma. Especially it is helpful to identify the most proliferating area. However, further studies are required to confirm the superiority of this biomarker for including in grading system.

Membranous overexpression of S100A10 is associated with a high-grade cellular status of breast carcinoma

S100A10 promotes tumor invasion in various cancers. Although genetic studies on S100A10 in breast carcinoma (BC) have been used for molecular biological classification, immunohistochemical studies are lacking. We aimed to identify the correlation between S100A10 expression in BC and various pathological parameters, including morphological features to determine histological grade (HG). Immunostained serial paraffin-embedded tissue sections from 176 cases of resected BC or normal mammary ducts (controls) were assessed for the membrane expression of S100A10. Of the 176 cases, 125 conventional infiltrating ductal carcinomas were chosen, comprising 67 (53.6%) S100A10-positive tumors, whereas normal mammary ducts were S100A10-negative. S100A10 immunoreactivity in ductal carcinoma in situ (n = 51) was similar to that of invasive carcinoma. The distinct membrane-immunopositivity was correlated with high HG, severe nuclear pleomorphism, frequent mitotic counts, high Ki-67 labeling index, HER2/neu overexpression, and low estrogen receptor status (P < 0.05), but not with tubular formation, pT categories, node metastasis, vessel permeation, and pStage. Membrane overexpression of S100A10 in BC correlates with the high-grade morphological and molecular status of the carcinoma cell rather than stromal invasion and architectural deviation. Evidence points to the use of S100A10 as a biomarker representing a high-grade cellular status of BC.

Does chemotherapy improve survival in patients with nodal positive luminal A breast cancer? A retrospective Multicenter Study

Background

In this study based on the BRENDA data, we investigated the impact of endocrine ± chemotherapy for luminal A, nodal positive breast cancer on recurrence free (RFS) and overall survival (OS). In addition, we analysed if tumor size of luminal A breast cancer influences survival in patients with the same number of positive lymph nodes.

Methods

In this retrospective multi-centre cohort study data of 1376 nodal-positive patients with primary diagnosis of luminal A breast cancer during 2001–2008 were analysed. The results were stratified by therapy and adjusted by age, tumor size and number of affected lymph nodes.

Results

In our study population, patients had a good to excellent prognosis (5-year RFS: 91% and tumorspecific 5-year OS 96.5%). There was no significant difference in RFS stratified by patients with only endocrine therapy and with endocrine plus chemo-therapy. Patients with 1–3 affected lymph nodes had no significant differences in OS treated only with endocrine therapy or with endocrine plus chemotherapy, independent of tumor size. Patients with large tumors and more than 3 affected lymph nodes had a significant worse survival as compared to the small tumors. However, despite the worse prognosis of those, adjuvant chemotherapy failed in order to improve RFS.

Conclusions

According to our data, nodal positive patients with luminal A breast cancer have, if any, a limited benefit of adjuvant chemotherapy. Tumor size and nodal status seem to be of prognostic value in terms of survival, however both tumor size as well as nodal status were not predictive for a benefit of adjuvant chemotherapy.

Predicting factors for survival of breast cancer patients using machine learning techniques

BACKGROUND

Breast cancer is one of the most common diseases in women worldwide. Many studies have been conducted to predict the survival indicators, however most of these analyses were predominantly performed using basic statistical methods. As an alternative, this study used machine learning techniques to build models for detecting and visualising significant prognostic indicators of breast cancer survival rate.

METHODS

A large hospital-based breast cancer dataset retrieved from the University Malaya Medical Centre, Kuala Lumpur, Malaysia (n = 8066) with diagnosis information between 1993 and 2016 was used in this study. The dataset contained 23 predictor variables and one dependent variable, which referred to the survival status of the patients (alive or dead). In determining the significant prognostic factors of breast cancer survival rate, prediction models were built using decision tree, random forest, neural networks, extreme boost, logistic regression, and support vector machine. Next, the dataset was clustered based on the receptor status of breast cancer patients identified via immunohistochemistry to perform advanced modelling using random forest. Subsequently, the important variables were ranked via variable selection methods in random forest. Finally, decision trees were built and validation was performed using survival analysis.

RESULTS

In terms of both model accuracy and calibration measure, all algorithms produced close outcomes, with the lowest obtained from decision tree (accuracy = 79.8%) and the highest from random forest (accuracy = 82.7%). The important variables identified in this study were cancer stage classification, tumour size, number of total axillary lymph nodes removed, number of positive lymph nodes, types of primary treatment, and methods of diagnosis.

CONCLUSION

Interestingly the various machine learning algorithms used in this study yielded close accuracy hence these methods could be used as alternative predictive tools in the breast cancer survival studies, particularly in the Asian region. The important prognostic factors influencing survival rate of breast cancer identified in this study, which were validated by survival curves, are useful and could be translated into decision support tools in the medical domain.

Bovine leukemia virus DNA associated with breast cancer in women from South Brazil

Breast cancer is a neoplastic condition with a high morbidity and mortality amongst women worldwide. Recent data linking bovine leukemia virus (BLV) with breast cancer has been contested already. Our study investigated the presence of BLV genome in healthy (n = 72) and cancerous (n = 72) paraffin-embedded samples of breast tissues from women in south Brazil. BLV DNA was found most frequently (30.5%) in breast cancer tissue than in healthy breast (13.9%) (Odds ratio = 2.73; confidence interval = 1.18-6.29; p = 0.027). In contrast, antibodies to BLV were found in a very small percentage of healthy blood donors. There was no association between BLV DNA and other tumor prognostic biological markers such as hormonal receptors, HER2 oncoprotein, proliferation index, metastasis in sentinels lymph nodes, and tumor grade and size. Our findings suggest that BLV should be considered a potential predisposing factor to breast cancer in women.

The predictive value of the prognostic staging system in the 8th edition of the American Joint Committee on Cancer for triple-negative breast cancer: a SEER population-based analysis

Aim: To examine the stage changes and survival differences among triple-negative breast cancer (TNBC) patients based on the prognostic staging system. Methods: We used the SEER database to identify eligible patients with TNBC diagnosed between 2010 and 2014. Kaplan–Meier curves were drawn for comparison. The primary end point was breast cancer-specific survival. Results: The median follow-up time was 26 months for 19,608 patients. The stages of all TNBC patients increased or remained unchanged during rearrangement from anatomic staging to prognostic staging. Stage IIA, IIIA and IIIC comprised the majority of patients. Several patients did not have prognostic staging. Stage IIIC incorporated six substages that contributed to high heterogeneity. Overall, the Kaplan–Meier curves still showed the favorable differentiation among stages and substages, with the exception of stage IIB and substage IIIA (T2N0, grade 2–3) patients. Conclusion: The prognostic information for breast cancer patients provided by the novel prognostic staging system may be less accurate for TNBC patients in our independent analysis. Moreover, stage IIB and substage IIIA (T2N0, grade 2–3) should possibly undergo further evaluation.

Introduction of a New Staging System of Breast Cancer for Radiologists: An Emphasis on the Prognostic Stage

In 2017, the American Joint Committee on Cancer announced the 8th edition of its cancer staging system. For breast cancer, the most significant change in the staging system is the incorporation of biomarkers into the anatomic staging to create prognostic stages. Different prognostic stages are assigned to tumors with the same anatomic stages according to the tumor grade, hormone receptor (estrogen receptor; progesterone receptor) status, and HER2 status. A Clinical Prognostic Stage is assigned to all patients regardless of the type of therapy used; in contrast, a Pathologic Prognosis Stage is assigned to patients in whom surgery is the initial treatment. In a few situations, low Oncotype DX recurrence scores can change the prognostic stage. The radiologists need to understand the importance of the biologic factors that can influence cancer staging.

BCL-2 expression aids in the immunohistochemical prediction of the Oncotype DX breast cancer recurrence score

Background

The development of molecular techniques to estimate the risk of breast cancer recurrence has been a significant addition to the suite of tools available to pathologists and breast oncologists. It has previously been shown that immunohistochemistry can provide a surrogate measure of tumor recurrence risk, effectively providing a less expensive and more rapid estimate of risk without the need for send-out. However, concordance between gene expression-based and immunohistochemistry-based approaches has been modest, making it difficult to determine when one approach can serve as an adequate substitute for the other. We investigated whether immunohistochemistry-based methods can be augmented to provide a useful therapeutic indicator of risk.

Methods

We studied whether the Oncotype DX breast cancer recurrence score can be predicted from routinely acquired immunohistochemistry of breast tumor histology. We examined the effects of two modifications to conventional scoring measures based on ER, PR, Ki-67, and Her2 expression. First, we tested a mathematical transformation that produces a more diagnostic-relevant representation of the staining attributes of these markers. Second, we considered the expression of BCL-2, a complex involved in regulating apoptosis, as an additional prognostic marker.

Results

We found that the mathematical transformation improved concordance rates over the conventional scoring model. By establishing a measure of prediction certainty, we discovered that the difference in concordance between methods was even greater among the most certain cases in the sample, demonstrating the utility of an accompanying measure of prediction certainty. Including BCL-2 expression in the scoring model increased the number of breast cancer cases in the cohort that were considered high certainty, effectively expanding the applicability of this technique to a greater proportion of patients.

Conclusions

Our results demonstrate an improvement in concordance between immunohistochemistry-based and gene expression-based methods to predict breast cancer recurrence risk following two simple modifications to the conventional scoring model.

American Joint Committee on Cancer's Staging System for Breast Cancer, Eighth Edition: What the Radiologist Needs to Know

The TNM staging system for cancer was developed by Pierre Denoix in France in the 1940s and 1950s. The North American effort to standardize the TNM system for cancer staging was first organized in 1959 as the American Joint Committee for Cancer Staging and End-Results Reporting, which is now the American Joint Committee on Cancer (AJCC). The most recent edition of the AJCC Cancer Staging Manual, the eighth edition, was globally adopted on January 1, 2018. Previous editions of the manual have relied on anatomic methods of staging alone, which used population-based survival data to predict clinical outcomes. In the era of precision medicine, the major change in the eighth edition is the incorporation of prognostic biomarkers to more accurately predict clinical outcomes and treatment response on an individual basis, without relying solely on the anatomic extent of disease. Factors such as tumor grade, hormone receptor and oncogene expression, and multigene panel recurrence scores are now integrated with anatomic information to yield a final prognostic stage group, which will provide better stratification of patient prognosis. The purpose of this article is to review the major changes in the AJCC eighth edition for breast cancer staging, review anatomic TNM staging, familiarize the radiologist with prognostic biomarkers and prognostic staging, and identify key sites of disease that may alter clinical management. ^©RSNA, 2018.

Decreased methylation in the SNAI2 and ADAM23 genes associated with de-differentiation and haematogenous dissemination in breast cancers

BACKGROUND

In breast cancer (BC), deregulation of DNA methylation leads to aberrant expressions and functions of key regulatory genes. In our study, we investigated the relationship between the methylation profiles of genes associated with cancer invasivity and clinico-pathological parameters. In detail, we studied differences in the methylation levels between BC patients with haematogenous and lymphogenous cancer dissemination.

METHODS

We analysed samples of primary tumours (PTs), lymph node metastases (LNMs) and peripheral blood cells (PBCs) from 59 patients with sporadic disseminated BC. Evaluation of the DNA methylation levels of six genes related to invasivity, ADAM23, uPA, CXCL12, TWIST1, SNAI1 and SNAI2, was performed by pyrosequencing.

RESULTS

Among the cancer-specific methylated genes, we found lower methylation levels of the SNAI2 gene in histologic grade 3 tumours (OR = 0.61; 95% CI, 0.39-0.97; P = 0.038) than in fully or moderately differentiated cancers. We also evaluated the methylation profiles in patients with different cancer cell dissemination statuses (positivity for circulating tumour cells (CTCs) and/or LNMs). We detected the significant association between reduced DNA methylation of ADAM23 in PTs and presence of CTCs in the peripheral blood of patients (OR = 0.45; 95% CI, 0.23-0.90; P = 0.023).

CONCLUSION

The relationships between the decreased methylation levels of the SNAI2 and ADAM23 genes and cancer de-differentiation and haematogenous dissemination, respectively, indicate novel functions of those genes in the invasive processes. After experimental validation of the association between the lower values of SNAI2 and ADAM23 methylation and clinical features of aggressive BCs, these methylation profiles could improve the management of metastatic disease.

miRNA in a multiomic context for diagnosis, treatment monitoring and personalized management of metastatic breast cancer

Metastatic breast cancer is characterized by aggressive spreading to distant organs. Despite huge multilevel research, there are still several important challenges that have to be clarified in the management of this disease. Therefore, recent investigations have implemented a modern, multiomic approach with the aim of identifying specific biomarkers for not only early detection but also to predict treatment responses and metastatic spread. Specific attention is paid to short miRNAs, which regulate gene expression at the post-transcriptional level. Aberrant miRNA expression could initiate cancer development, cell proliferation, invasion, migration, metastatic spread or drug resistance. An miRNA signature is, therefore, believed to be a promising biomarker and prediction tool that could be utilized in all phases of carcinogenesis. This article offers comprehensive information about miRNA profiles useful for diagnostic and treatment purposes that may sufficiently advance breast cancer management and improve individual outcomes in the near future.

Biomarkers in breast cancer: A consensus statement by the Spanish Society of Medical Oncology and the Spanish Society of Pathology

This consensus statement revises and updates the recommendations for biomarkers use in the diagnosis and treatment of breast cancer, and is a joint initiative of the Spanish Society of Medical Oncology and the Spanish Society of Pathology. This expert group recommends determining in all cases of breast cancer the histologic grade and the alpha-estrogen receptor (ER), progesterone receptor, Ki-67 and HER2 status, in order to assist prognosis and establish therapeutic options, including hormone therapy, chemotherapy and anti-HER2 therapy. One of the four available genetic prognostic platforms (MammaPrint^®, Oncotype DX^®, Prosigna^® or EndoPredict^®) may be used in node-negative ER-positive patients to establish a prognostic category and decide with the patient whether adjuvant treatment may be limited to hormonal therapy. Newer technologies including next-generation sequencing, liquid biopsy, tumour-infiltrating lymphocytes or PD-1 determination are at this point investigational.

Lymphovascular invasion can be better than pathologic complete response to predict prognosis in breast cancer treated with neoadjuvant chemotherapy

Lymphovascular invasion (LVI) has been a predictor of worse survival outcomes in breast cancer. However, the role of LVI compared than pathologic complete response (pCR) following neoadjuvant chemotherapy (NAC) remains unclear. The aim of this study was to examine the association between LVI and survival outcomes and clinicopathological features in patients with breast cancer treated with NAC. We retrospectively analyzed 187 patients with breast cancer treated with NAC and surgery between 2005 and 2013 in our institution. Kaplan-Meier analyses were used to assess recurrence-free survival (RFS) and overall survival (OS). Median follow-up was 57.9 months. Mastectomy (vs breast conserving surgery [BCS]; hazard ratio [HR], 1.791; 95% confidence interval [CI], 1.022-3.139; P = .042), ypN1-3 stage (vs ypN0 stage; HR, 2.561; 95% CI, 1.247-5.261; P = .010), and LVI (vs no LVI; HR, 2.041; 95% CI, 1.170-3.562; P = .012) were associated with worse RFS. Mastectomy (vs BCS; HR, 2.768; 95% CI, 1.173-6.535; P = .020), LVI (vs no LVI; HR, 3.474; 95% CI, 1.646-7.332, P = .001), and human epidermal growth factor receptor 2 overexpression type (vs luminal A type; HR, 11.360; 95% CI, 1.501-85.972; P = .019) were associated with worse OS. Patients with LVI and hormone receptor-negative cancer had the worst RFS (P < .001) and OS (P < .001). LVI more than pCR in surgical breast cancer specimens obtained after NAC was a significant independent prognostic factor. Patients with hormonal receptor-negative cancer and LVI had unfavorable survival outcomes. We suggest that patients with hormone receptor-negative cancer and LVI should receive short-term follow-up and appropriate management.

Anatomy and Breast Cancer Staging: Is It Still Relevant?

Breast cancer staging concisely summarizes disease status, creating a framework for assessing and relaying prognostic information. The fundamental concepts and components of breast cancer staging are reviewed. The AJCC Cancer Staging Manual, which includes traditional anatomic factors, now includes additional tumor characteristics: tumor grade, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor 2 status, and (when available) multigene panel testing from the primary tumor. With these updates, staging provides the most reliable system for accurately predicting patient outcome. When the AJCC 8th edition guidelines are adopted, they will more closely reflect tumor biology.

The Association between Molecular Subtypes of Breast Cancer with Histological Grade and Lymph Node Metastases in Indonesian Woman

Objective: Breast carcinoma is a heterogeneous disease which is rich in diversity. Molecular subtypes of breast cancer, histological grade and lymph node metastases are strong prognostic and predictive factors. In Indonesia, only a limited number of studies have investigated the correlation between molecular subtypes with histological grade and lymph node metastases. Methods: We analyzed 247 invasive breast carcinoma cases from the Anatomic Pathology Installation of Dr. Sardjito General Hospital Yogyakarta between 2012-2015. The slides were stained for estrogen receptors (ER), progesterone receptors (PR), HER2, Ki-67 and CK5/6 for classification into breast cancer subtypes (BCS). Histological grade using the Nottingham system and lymph node status were obtained from anatomic pathology records. The association between histological grade and lymph node status with BCS was examined with Chi-square tests. Results: The immunohistochemical features of 247 cases of women with invasive breast carcinoma were examined. There were 102 (41.3%) patients with Luminal A, 34 (13.8%) patients with Luminal B, 48 (19.4%) patients with HER2-positive, and 63 (25.5%) patients with triple negative breast cancer (TNBC). There were 148 (59.9%) patients with negative lymph node status and 99 (40.1%) with positive status. Among 63 TNBC cases, 37 (58.7%) patients were positive for CK5/6 staining (basal-like). Statistically, there were significant differences between histological grade and subtypes (p=0.013). However, no significant differences were found for lymph node metastases (p=0.540). Conclusion: Among subtypes, Luminal A has the highest frequency, followed by TNBC, HER2-positive and Luminal B. Histological grade was associated with molecular subtypes of breast carcinoma in Yogyakarta. Grade I was associated with Luminal A, while Grade III was associated with Luminal B, HER2 and TNBC subtypes.

[Consensus statement on biomarkers in breast cancer by the Spanish Society of Pathology and the Spanish Society of Medical Oncology]

This consensus statement is a joint initiative of the Spanish Society of Pathology (SEAP) and the Spanish Society of Medical Oncology (SEOM). It revises and updates the recommendations for the use of biomarkers in the diagnosis and treatment of breast cancer. The group of experts recommends that, in all cases of breast cancer, the histologic grade and the alpha-estrogen receptor (ER), progesterone receptor, Ki-67 and HER2 status should be determined, in order to assist prognosis and establish therapeutic options, including hormone therapy, chemotherapy and anti-HER2 therapy. One of the four available genetic prognostic platforms (MammaPrint^®, Oncotype DX^®, Prosigna^® or EndoPredict^®) may be used in node-negative ER-positive patients to establish a prognostic category and decide, together with the patient, whether adjuvant treatment be limited to hormonal therapy. Newer technologies, including next generation sequencing, liquid biopsy, tumour infiltrating lymphocytes or PD-1 determination, are still investigational.

Breast Cancer in Low- and Middle-Income Countries: Why We Need Pathology Capability to Solve This Challenge

Breast cancer is the leading cause of cancer mortality among women in developing countries. Timely and accurate histopathological diagnosis of breast cancer is critical to delivering high-quality breast cancer care to patients in low- and middle-income countries (LMIC). The most important prognostic factors in breast cancer along with tumor size and nodal status are tumor grade, estrogen receptor status, as well as HER2 status in countries where specific targeted therapies are available. In addition, detailed and complete cancer registry data are needed to assess a country's disease burden and guide disease prioritization and allocation of resources for breast cancer treatment. Innovations in leapfrog technology and low-cost point-of-care tests for molecular evaluations are needed to provide accurate and timely pathology, with the ultimate goal of improving survival outcomes for patients with breast cancer in LMIC.

Does tumor size improve the accuracy of prognostic prediction in patients with esophageal squamous cell carcinoma after surgical resection?

This study aimed to investigate whether the inclusion of tumor size could improve the prognostic accuracy in patients with esophageal squamous cell cancer (ESCC). A total of 387 patients with ESCC who underwent curative resection were enrolled in this analysis. The patients were categorized into small-sized tumors (SSTs) and large-sized tumors (LSTs) using an appropriate cut-off point for tumor size. Kaplan–Meier survival curve and log–rank test were used to evaluate the prognostic value of tumor size. A Cox regression model was adopted for multivariate analysis. Their accuracy was compared based on the presence or absence of tumor size. Using 3.5 cm as the optimal cut-off point, 228 and 159 patients presented with LSTs (≥ 3.5 cm) and SSTs (< 3.5 cm), respectively. The patients with LSTs had significantly worse prognoses than patients with SSTs (23.9% vs. 43.2%, P < 0.001). Multivariate analysis revealed that tumor size, histological type, invasion depth, and lymph node metastasis were independent predictors of overall survival. The addition of tumor size to the AJCC TNM staging improved the predictive accuracy of the 5-year survival rate by 3.9%. Further study showed that tumor size and T stage were independent predictors of the prognosis of node-negative patients, and the combination of tumor size and T stage improved the predictive accuracy by 3.7%. In conclusion, tumor size is indeed a simple and practical prognostic factor in patients with ESCC. It can be used to improve the prognostic accuracy of the current TNM staging, especially for patients with node-negative disease.

The transition module: a method for preventing overfitting in convolutional neural networks

Digital pathology has advanced substantially over the last decade with the adoption of slide scanners in pathology labs. The use of digital slides to analyse diseases at the microscopic level is both cost-effective and efficient. Identifying complex tumour patterns in digital slides is a challenging problem but holds significant importance for tumour burden assessment, grading and many other pathological assessments in cancer research. The use of convolutional neural networks (CNNs) to analyse such complex images has been well adopted in digital pathology. However, in recent years, the architecture of CNNs has altered with the introduction of inception modules which have shown great promise for classification tasks. In this paper, we propose a modified 'transition' module which encourages generalisation in a deep learning framework with few training samples. In the transition module, filters of varying sizes are used to encourage class-specific filters at multiple spatial resolutions followed by global average pooling. We demonstrate the performance of the transition module in AlexNet and ZFNet, for classifying breast tumours in two independent data-sets of scanned histology sections; the inclusion of the transition module in these CNNs improved performance.

Incorporating Tumor Characteristics to the American Joint Committee on Cancer Breast Cancer Staging System

BACKGROUND

The American Joint Committee on Cancer (AJCC) breast cancer staging system provides important prognostic information. The recently published eighth edition incorporates biological markers and recommends the use of a complex "prognostic stage." In this study, we assessed the relationship between stage, breast cancer subtype, grade, and outcome in a large population-based cohort and evaluated a risk score system incorporating tumor characteristic to the AJCC anatomic staging system.

MATERIALS AND METHODS

Patients diagnosed with primary breast cancer stage I-IV between 2005-2008 were identified in the California Cancer Registry. For patients with stage I-III disease, pathologic stage was recorded. For patients with stage IV disease, clinical stage was utilized. Five-year breast cancer specific survival (BCSS) and overall survival (OS) rates were determined for each potential tumor size-node involvement-metastases (TNM) combination according to breast cancer subtype. A risk score point-based system using grade, estrogen receptor, and human epidermal growth factor receptor 2 (HER2) status was designed to complement the anatomic AJCC staging system. Survival probabilities between groups were compared using log-rank test. Cox proportional hazards models were used.

RESULTS

Among 43,938 patients, we observed differences in 5-year BCSS and OS for each TNM combination according to breast cancer subtype. The most favorable outcomes were seen for hormone receptor-positive tumors followed closely by HER2-positive tumors, with the worst outcomes observed for triple negative breast cancer. Our risk score system separated patients into four risk groups within each stage category (all p < .05).

CONCLUSION

Our simple risk score system incorporates biological factors into the AJCC anatomic staging system, providing accurate prognostic information.

IMPLICATIONS FOR PRACTICE

This study demonstrates that stage, but also breast cancer subtype and grade, define prognosis in a large population of breast cancer patients. It shows that a point-based risk score system that incorporates these biological factors provides refined stratification and information on prognosis, improving the anatomic American Joint Committee on Cancer (AJCC) staging system. In addition, the overall mortality and breast cancer specific mortality rates detailed here provide much-needed information about prognosis in the current era, refining the current AJCC staging.

Evaluation of the prognostic stage in the 8th edition of the American Joint Committee on Cancer in locally advanced breast cancer: An analysis based on SEER 18 database

BACKGROUND

The new "prognostic stage" in the 8th edition of the American Joint Committee on Cancer (AJCC) incorporated important biologic factors such as estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), histologic grade and TNM stage into one system. The objective of this study was to evaluate the "prognostic stage" in locally advanced breast cancer (LABC) based on the Surveillance, Epidemiology, and End Results (SEER) 18 database.

METHODS

10053 LABCs diagnosed between 2010 and 2013 were enrolled. TNM stage was based on AJCC 7th edition. Comparisons of biologic factor proportions among stage changes were performed using Pearson's chi-square test. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated using the Kaplan-Meier method and log rank testing with pairwise comparisons between different stages was conducted. Cox models were fitted to assess the independent prognostic factors.

RESULTS

The prognostic stage grouped LABC into six stages: IB-IIIC among which IB-IIIA had a relatively better survival. It reassigned 74% LABCs to a different tumor stage. 60.4% cases in grade III and 68.3% cases with triple negative breast cancer were upstaged while 57.1% cases with ER/PR dual positivity were down staged. It was an independent prognostic factor of LABC. There were statistically significant survival differences among stage IB-IIIA, IIIB and IIIC. Among each TNM stage, there were statistically significant survival differences among stage changes.

CONCLUSIONS

The prognostic stage provided accurate prognostic information for LABC compared with anatomic TNM stage. It will lead to accuracy in prognosis prediction and optimal treatment selection, and therefore, better outcomes.

Separase is a marker for prognosis and mitotic activity in breast cancer

Background:

Cancer cell proliferation is a critical feature in classifying and predicting the outcome of breast carcinoma. Separase has a central role in cell cycle progression in unleashing sister-chromatids at anaphase onset. Abnormally functioning separase is known to lead to chromosomal instability.

Methods:

The study comprises 349 breast carcinoma patients treated in Central Hospital of Central Finland. The prognostic value, role as a proliferation marker and regulatory interactions of separase are evaluated by immunohistochemical and double- and triple-immunofluorescence (IF) detections based on complete clinical data and >22-year follow-up of the patient material.

Results:

In our material, abnormal separase expression predicted doubled risk of breast cancer death (P<0.001). Up to 11.3-year survival difference was observed when comparing patients with and without separase expressing cancer cell mitoses. Particularly, abnormal separase expression predicted impaired survival for luminal breast carcinoma (P<0.001, respectively). In multivariate analyses, abnormal separase expression showed independent prognostic value. The complex inhibitory interactions involving securin and cyclin B1 were investigated in double- and triple-IFs and revealed patient subgroups with aberrant regulation and expression patterns of separase.

Conclusions:

In our experience, separase is a promising and clinically applicable proliferation marker. Separase expression shows strong and independent prognostic value and could be developed into a biomarker for treatment decisions in breast carcinoma, particularly defining prognostic subgroups among luminal carcinomas.

Better survival after breast-conserving therapy compared to mastectomy when axillary node status is positive in early-stage breast cancer: a registry-based follow-up study of 6387 Norwegian women participating in screening, primarily operated between 1998 and 2009

Background

Recent registry studies on early-stage breast cancer have shown better survival rates when women underwent breast-conserving therapy (BCT) compared with mastectomy (MTX). The aim of this study is to investigate women participating in screening, in all four stages of early breast cancer (T1N0M0, T2N0M0, T1N1M0, and T2N1M0), as to whether there is a survival benefit when women undergo BCT compared to MTX.

Method

A cohort of 6387 women aged 50–69, with primary-operated breast cancer from January 1998 to December 2009, participating in screening and followed-up until the end of 2010. Life tables were calculated by stages (pT1N0M0, pT2N0M0, pT1N1M0, and pT2N1M0), surgery groups (BCT and MTX), and screening detection (first screening, later screening, or interval cancer). Cox regression was used to calculate hazard ratios (HR) between BCT and MTX in crude and adjusted analyses.

Results

In stage T1N1M0, women who underwent MTX had an HR of 2.91 (95% CI 1.30–6.48) for breast cancer death compared to women who underwent BCT, after adjusting for screening detection, years of diagnosis, age at diagnosis, histology, grade, and hormone receptor status. For all other TNM categories of early breast cancer, there was no difference in survival.

10-year breast cancer-specific survival (BCSS) in T1N0M0 was 98% for women undergoing BCT and 96% for women undergoing MTX. 10-year BCSS in T1N1M0 was 97% for women undergoing BCT and 89% for women undergoing MTX.

Conclusions

For women participating in screening, there is a benefit of BCT over MTX in stage T1N1M0. No such effects were observed in the other early stages of breast cancer.

Molecular genetics complexity impeding research progress in breast and ovarian cancers

Breast and ovarian cancer are heterogeneous diseases. While breast cancer accounts for 25% of cancers worldwide, ovarian cancer accounts for 3.5% of all cancers and it is considered to be the most lethal type of cancer among women. In Oman, breast cancer accounts for 25% and ovarian cancer for 4.5% of all cancer cases. Various risk factors, including variable biological and clinical traits, are involved in the onset of breast and ovarian cancer. Although highly developed diagnostic and therapeutic methods have paved the way for better management, targeted therapy against specific biomarkers has not yet shown any significant improvement, particularly in triple-negative breast cancer and epithelial ovarian cancer, which are associated with high mortality rates. Thus, elucidating the mechanisms underlying the pathology of these diseases is expected to improve their prevention, prognosis and management. The aim of the present study was to provide a comprehensive review and updated information on genomics and proteomics alterations associated with cancer pathogenesis, as reported by several research groups worldwide. Furthermore, molecular research in our laboratory, aimed at identifying new pathways involved in the pathogenesis of breast and ovarian cancer using microarray and chromatin immunoprecipitation (ChIP), is discussed. Relevant candidate genes were found to be either up- or downregulated in a cohort of breast cancer cases. Similarly, ChIP analysis revealed that relevant candidate genes were regulated by the E2F5 transcription factor in ovarian cancer tissue. An ongoing study aims to validate these genes with a putative role as biological markers that may contribute to the development of targeted therapies for breast and ovarian cancer.

Sleep quality, duration, and breast cancer aggressiveness

PURPOSE

Epidemiological studies suggest that short sleep duration and poor sleep quality may increase breast cancer risk. However, whether sleep is associated with breast tumor aggressiveness characteristics has largely been unexplored.

METHODS

The study included 4171 non-Hispanic whites (NHW) and 235 African Americans (AA) diagnosed with incident, primary, invasive breast cancer in the Women's Health Initiative (WHI) Observational Study (1994-2013). We used logistic regression to examine the association of baseline sleep (sleep duration, sleep quality, WHI Insomnia Rating Scale) with tumor grade, stage, hormone receptor status, HER2 status.

RESULTS

In NHW, women who reported 6 h of sleep/night were more likely to have tumors classified as regional/distant stage at diagnosis compared to women who slept 7-8 h/night (adjusted odds ratio (OR): 1.25, 95% confidence interval (CI): 1.05-1.48). AA women who reported their typical night's sleep as 'average quality' or 'restless or very restless sleep' were more likely to be diagnosed with triple-negative tumors than those who reported 'sound or restful' sleep (adjusted ORs: 2.91 (1.11, 7.63) and 3.74 (1.10, 12.77), respectively).

CONCLUSIONS

Our findings provide indications that aspects of sleep (sleep duration and quality), partially modifiable health behaviors, may be associated with development of aggressive tumor characteristics in postmenopausal women. The role of these sleep attributes may differ for NHW and AA women; however, further study in robust, racial diverse samples is needed. This study provides evidence that facets of sleep behavior are associated with the development of aggressive tumor features and these associations differ by race.

Histological grade provides significant prognostic information in addition to breast cancer subtypes defined according to St Gallen 2013

BACKGROUND

The St Gallen surrogate definition of the intrinsic subtypes of breast cancer consist of five subgroups based on estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor type 2 (HER2), and Ki-67. PgR and Ki-67 are used for discriminating between the 'Luminal A-like' and 'Luminal B-like (HER2-negative)' subtypes. Histological grade (G) has prognostic value in breast cancer; however, its relationship to the St Gallen subtypes is not clear. Based on a previous pilot study, we hypothesized that G could be a primary discriminator for ER-positive/HER2-negative breast cancers that were G1 or G3, whereas Ki-67 and PgR could provide additional prognostic information specifically for patients with G2 tumors. To test this hypothesis, a larger patient cohort was examined.

PATIENTS AND METHODS

Six hundred seventy-one patients (≥35 years of age, pT1-2, pN0-1) with ER-positive/HER2-negative breast cancer and complete data for PgR, Ki-67, G, lymph node status, tumor size, age, and distant disease-free survival (DDFS; median follow-up 9.2 years) were included.

RESULTS

'Luminal A-like' tumors were mostly G1 or G2 (90%) whereas 'Luminal B-like' tumors were mostly G2 or G3 (87%) and corresponded with good and poor DDFS, respectively. In 'Luminal B-like' tumors that were G1 (n = 23), no metastasis occurred, whereas 14 of 40 'Luminal A-like' tumors that were G3 metastasized. In the G2 subgroup, low PgR and high Ki-67 were associated with an increased risk of distant metastases, hazard ratio (HR) and 95% confidence interval (CI) 1.8 (0.95-3.4) and 1.5 (0.80-2.8), respectively.

CONCLUSIONS

Patients with ER-positive/HER2-negative/G1 breast cancer have a good prognosis, similar to that of 'Luminal A-like', while those with ER-positive/HER2-negative/G3 breast cancer have a worse prognosis, similar to that of 'Luminal B-like', when assessed independently of PgR and Ki-67. Therapy decisions based on Ki-67 and PgR might thus be restricted to the subgroup G2.

African American Race is an Independent Risk Factor in Survival from Initially Diagnosed Localized Breast Cancer

BACKGROUND: African American race negatively impacts survival from localized breast cancer but co-variable factors confound the impact.

METHODS: Data sets were analyzed from the Surveillance, Epidemiology and End Results (SEER) directories from 1973 to 2011 consisting of patients with designated diagnosis of breast adenocarcinoma, race as White or Caucasian, Black or African American, Asian, American Indian or Alaskan Native, Native Hawaiian or Pacific Islander, age, stage I, II or III, grade 1, 2 or 3, estrogen receptor or progesterone receptor positive or negative, marital status as single, married, separated, divorced or widowed and laterality as right or left. The Cox Proportional Hazards Regression model was used to determine hazard ratios for survival. Chi square test was applied to determine the interdependence of variables found significant in the multivariable Cox Proportional Hazards Regression analysis. Cells with stratified data of patients with identical characteristics except African American or Caucasian race were compared.

RESULTS: Age, stage, grade, ER and PR status and marital status significantly co-varied with race and with each other. Stratifications by single co-variables demonstrated worse hazard ratios for survival for African Americans. Stratification by three and four co-variables demonstrated worse hazard ratios for survival for African Americans in most subgroupings with sufficient numbers of values. Differences in some subgroupings containing poor prognostic co-variables did not reach significance, suggesting that race effects may be partly overcome by additional poor prognostic indicators.

CONCLUSIONS: African American race is a poor prognostic indicator for survival from breast cancer independent of 6 associated co-variables with prognostic significance.

A microscopic landscape of the invasive breast cancer genome

Histologic grade is one of the most important microscopic features used to predict the prognosis of invasive breast cancer and may serve as a marker for studying cancer driving genomic abnormalities in vivo. We analyzed whole genome sequencing data from 680 cases of TCGA invasive ductal carcinomas of the breast and correlated them to corresponding pathology information. Ten genetic abnormalities were found to be statistically associated with histologic grade, including three most prevalent cancer driver events, TP53 and PIK3CA mutations and MYC amplification. A distinct genetic interaction among these genomic abnormalities was revealed as measured by the histologic grading score. While TP53 mutation and MYC amplification were synergistic in promoting tumor progression, PIK3CA mutation was found to have alleviated the oncogenic effect of either the TP53 mutation or MYC amplification, and was associated with a significant reduction in mitotic activity in TP53 mutated and/or MYC amplified breast cancer. Furthermore, we discovered that different types of genetic abnormalities (mutation versus amplification) within the same cancer driver gene (PIK3CA or GATA3) were associated with opposite histologic changes in invasive breast cancer. In conclusion, our study suggests that histologic grade may serve as a biomarker to define cancer driving genetic events in vivo.

Clinicopathological Characteristics and Survival Outcomes in Invasive Papillary Carcinoma of the Breast: A SEER Population-Based Study

To investigate the clinicopathological characteristics and survival outcomes of invasive papillary carcinoma (IPC), we identified 233,171 female patients in the Surveillance, Epidemiology, and End Results (SEER) database who had IPC (n = 524) or infiltrating ductal carcinoma (IDC) (n = 232,647). Generally, IPCs occurred in older women (≥50 years old) and presented with smaller sizes, lower grades, higher rates of oestrogen receptor (ER) and progesterone receptor (PR) positivity, and reduced lymph node (LN) involvement and were less likely to be treated with mastectomy than patients with IDC. The five-year disease-specific survival (DSS) rates were significantly better in IPC than in IDC (97.5% vs. 93%, respectively; P < 0.001). In the multivariate analysis, patients with IPC showed a DSS that was similar to that of IDC (hazard ratio = 0.556, 95% confidence interval 0.289–1.070, P = 0.079). No significant difference was observed in DSS between matched IPC and IDC groups (P = 0.085). Differences in outcomes may be partially explained by differences in tumour grade, LN status, and ER and PR status between the 2 groups. Gaining an improved clinical and biological understanding of IPC might result in more tailored and effective therapies in breast cancer patients.

An algorithm for expanding the TNM staging system

AIM

We describe a new method to expand the tumor, lymph node, metastasis (TNM) staging system using a clustering algorithm. Cases of breast cancer were used for demonstration.

MATERIALS & METHODS

An unsupervised ensemble-learning algorithm was used to create dendrograms. Cutting the dendrograms produced prognostic systems.

RESULTS

Prognostic systems contained groups of patients with similar outcomes. The prognostic systems based on tumor size and lymph node status recapitulated the general structure of the TNM for breast cancer. The prognostic systems based on tumor size, lymph node status, histologic grade and estrogen receptor status revealed a more detailed stratification of patients when grade and estrogen receptor status were added.

CONCLUSION

Prognostic systems from cutting the dendrogram have the potential to improve and expand the TNM.

[Prognostic factors of early breast cancer]

Decision about the administration of adjuvant therapy for early breast cancer depends on the evaluation of prognostic factors. Lymph node status, tumor size and grade of differentiation are classical variables in this regard, and can be complemented by hormonal receptor status and HER2 expression. These factors can be combined into prognostic indexes to better estimate the risk of relapse or death. Other factors are less important. Gene profiles have emerged in recent years to identify low-risk patients who can forgo adjuvant chemotherapy. A number of profiles are available and can be used in selected cases. In the future, gene profiling will be used to select patients for treatment with new targeted therapies.

Correlation between mammograghic findings and clinical/ pathologic features in women with small invasive breast carcinomas

BACKGROUND

To study the relationship between mammographic findings and clinical/pathologic features in women with 1-15mm sized invasive breast cancer.

MATERIALS AND METHODS

We investigated a consecutive series of 134 cases diagnosed in Tianjin Medical University Cancer Institute and Hospital in 2007. Mammographic findings were classified into five groups as follows :1) stellate mass without calcification; 2) non-stellate mass without calcification; 3) intermediate suspicious calcification with or without associated mass; 4) higher probability malignant calcification with or without associated mass; 5) focal asymmetry/distortion without associated calcification. Associations between mammographic and clinical/pathological features (menopause status/family history/histologic grade/lymph node status and ER/PR/HER2 status) was analyzed through logistic regression and chi square tests.

RESULTS

Compared to the stellate mass without calcification group, higher probability malignant calcification patients were associated significantly with a positive lymph node status, always presenting in patients who were non-menopausal and with a family history of carcinoma.

CONCLUSIONS

Higher probability malignant calcifications with or without associated tumor masses are associated with clinical/pathologic features of poor prognosis.

Influence of Hormone Receptor Status on Spinal Metastatic Lesions in Patients with Breast Cancer

OBJECTIVE

Bony metastasis predominantly affects the spinal column and has been commonly associated in patients with breast cancer. There are two types of lesions that can occur with spine cancer-osteolytic or osteoblastic. Some patients may have mixed lesions, which include lytic and blastic in one vertebra or lytic and blastic in different vertebrae. Previous studies have shown that patients with breast cancer have an increased likelihood for development of lytic spinal metastases.

METHODS

A retrospective chart review was conducted to more closely examine the association between hormone receptor status and spinal lesion type. A total of 195 patients were initially identified through the City of Hope Cancer Registry. Of the 195, only 153 patients had hormone receptor marker status available. Associations between spinal lesion and hormone receptor status were evaluated using χ(2) tests with alpha = 0.05 significance level. In a secondary analysis, the Oncomine Platform was used, which integrated The Cancer Genome Atlas (TCGA) datasets, to identify osteogenic genes that may be relevant to invasive breast cancers.

RESULTS

Contrary to previous studies, our findings revealed progesterone receptor positive (PR+) patients were significantly more likely to present with blastic than lytic or mixed lesions. Furthermore, using TCGA analysis, COL1A1 and COL1A2 were found to be up-regulated, which could provide a molecular explanation for the development of blastic metastases.

CONCLUSIONS

By integrating clinical and bioinformatic techniques, this study provides a novel discovery of the relationship between blastic and PR + breast cancers, which may have important implications for diagnostic strategies concerning vertebral metastases.

Translating the concept of intrinsic subtypes into an oncoplastic cohort of more than 1000 patients - predictors of recurrence and survival

INTRODUCTION

A paradigm shift in breast cancer was introduced by Sørlie's concept of intrinsic subtypes [1]. We validated this concept - which was originally based on 84 individuals - in a large cohort study of 1035 patients with oncoplastic surgery and analyzed if early and late recurrences are linked to a specific intrinsic tumor subtype or resection margins.

MATERIALS AND METHODS

1035 patients with oncoplastic surgery (2004-2009) were analyzed with regard to treatment characteristics and patterns of early (<5 years) and late recurrence (>5 years) and survival related to the intrinsic subtypes. Data was retrieved from patient's charts, customized patients questionnaires and cancer registries.

RESULTS

944 patients with primary, unilateral breast cancer, median age 58 years, were eligible for analysis. At a median FU of 5.2 years, LRR was 4.0%, 5-year-OS 94.5% and DFS 90.9%. Intrinsic subtypes, but not T-size, nodal-status, resections margins nor histopathology, governed local control and survival. There was no signal for prevelance of unclear margins in any of intrinsic subgroups and no preference of any oncoplastic technique attributed to them. TNBC and Her2 non-luminal breast cancer had highest recurrence and lowest survival rates. Although sentinel involvement (SLN+) was prevailing in the Luminal-B-Her 2 negative subtype at 34.3%, this did not translate into a higher axillary dissection rate.

CONCLUSION

This study confirmed the intrinsic subtype concept on a large clinical basis and describes the patterns of early and late recurrence in oncoplastic surgery, concluding that bigger risk may not be overcome by bigger surgery.

A perfect storm: How tumor biology, genomics, and health care delivery patterns collide to create a racial survival disparity in breast cancer and proposed interventions for change

It is well known that there is a significant racial divide in breast cancer incidence and mortality rates. African American women are less likely to be diagnosed with breast cancer than white women but are more likely to die from it. This review explores the factors that may contribute to the racial survival disparity. Consideration is paid to what is known about the role of differences in tumor biology, genomics, cancer screening, and quality of cancer care. It is argued that it is the collision of 2 forces, tumor biology and genomics, with patterns of care that leads to the breast cancer mortality gap. The delays, misuse, and underuse of treatment for African American patients are of increased significance when these patients are presenting with more aggressive forms of breast cancer. In the current climate of health care reform ushered in by the Affordable Care Act, this article also evaluates interventions to close the disparity gap. Prior interventions have been too narrowly focused on the patient rather than addressing the system and improving care across the continuum of breast cancer evaluation and treatment. Lastly, areas of future investigation and policy initiatives aimed at reducing the racial survival disparity in breast cancer are discussed.

Advances in the Molecular Analysis of Breast Cancer: Pathway toward Personalized Medicine

Background

Breast cancer is a heterogeneous disease that encompasses a wide range of clinical behaviors and histological and molecular variants. It is the most common type of cancer affecting women worldwide and is the second leading cause of cancer death.

Methods

A comprehensive literature search was performed to explore the advances in molecular medicine related to the diagnosis and treatment of breast cancer.

Results

During the last few decades, advances in molecular medicine have changed the landscape of cancer treatment as new molecular tests complement and, in many instances, exceed traditional methods for determining patient prognosis and response to treatment options. Personalized medicine is becoming the standard of care around the world. Developments in molecular profiling, genomic analysis, and the discovery of targeted drug therapies have significantly improved patient survival rates and quality of life.

Conclusions

This review highlights what pathologists need to know about current molecular tests for classification and prognostic/predictive assessment of breast carcinoma as well as their role as part of the medical team.