A nationwide registry-based cohort study of the MammaPrint genomic risk classifier in invasive breast cancer

Comparison of Genomic Profiling Data with Clinical Parameters: Implications for Breast Cancer Prognosis

Simple Summary

Around 20 years ago, genomic profiling of breast carcinomas identified tumor subtypes with clinical implications and opened the door for a better understanding of breast cancer biology. The commercialization of multigene tests had a significant impact on clinical practice, and yet, controversy exists as to which methodology is best to inform the choice of therapy and existing recommendations are inconsistent and often driven by cost-effectiveness. Here we report data from a cohort of breast cancer patients in which pathological and molecular subtyping are directly compared in a clinical setting. The findings show that some patients with genomic low-risk tumors could receive unnecessary systemic therapy if only following the classical clinical parameters, while others could remain under-treated. This study suggests that to design precise treatment regimens for patients with early breast cancer, the conventional clinicopathological classification should be complemented with the robust prognostic information provided by molecular subtyping.

Abstract

Precise prognosis is crucial for selection of adjuvant therapy in breast cancer. Molecular subtyping is increasingly used to complement immunohistochemical and pathological classification and to predict recurrence. This study compares both outcomes in a clinical setting. Molecular subtyping (MammaPrint^®, TargetPrint^®, and BluePrint^®) and pathological classification data were compared in a cohort of 143 breast cancer patients. High risk clinical factors were defined by a value of the proliferation factor Ki67 equal or higher than 14% and/or high histological grade. The results from molecular classification were considered as reference. Core needle biopsies were found to be comparable to surgery samples for molecular classification. Discrepancies were found between molecular and pathological subtyping of the samples, including misclassification of HER2-positive tumors and the identification of a significant percentage of genomic high risk T1N0 tumors. In addition, 20% of clinical low-risk tumors showed genomic high risk, while clinical high-risk samples included 42% of cases with genomic low risk. According to pathological subtyping, a considerable number of breast cancer patients would not receive the appropriate systemic therapy. Our findings support the need to determine the molecular subtype of invasive breast tumors to improve breast cancer management.

Prediction of Late Recurrence and Distant Metastasis in Early-stage Breast Cancer: Overview of Current and Emerging Biomarkers

Recently, a significant number of breast cancer (BC) patients have been diagnosed at an early stage. It is therefore critical to accurately predict the risk of recurrence and distant metastasis for better management of BC in this setting. Clinicopathologic patterns, particularly lymph node status, tumor size, and hormonal receptor status are routinely used to identify women at increased risk of recurrence. However, these factors have limitations regarding their predictive ability for late metastasis risk in patients with early BC. Emerging molecular signatures using gene expression-based approaches have improved the prognostic and predictive accuracy for this indication. However, the use of their based-scores for risk assessment has provided contradictory findings. Therefore, developing and using newly emerged alternative predictive and prognostic biomarkers for identifying patients at high- and low-risk is of great importance. The present review discusses some serum biomarkers and multigene profiling scores for predicting late recurrence and distant metastasis in early-stage BC based on recently published studies and clinical trials.

Grading of invasive breast carcinoma: the way forward

Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histologic grading needs to be performed accurately, on properly fixed specimens, and by adequately trained dedicated pathologists that take the time to diligently follow the protocol methodology. In this paper, we review the history of histologic grading, describe the basics of grading, review prognostic value and reproducibility issues, compare performance of grading to gene expression profiles, and discuss how to move forward to improve reproducibility of grading by training, feedback and artificial intelligence algorithms, and special stains to better recognize mitoses. We conclude that histologic grading, when adequately carried out, remains to be of important prognostic value in breast cancer patients.

Exposure to radiofrequency radiation increases the risk of breast cancer: A systematic review and meta-analysis

The present systematic review and meta-analysis investigated the association between exposure to radiofrequency radiation and the risk of breast cancer. The published studies that were available in PubMed, Embase, Cochrane Library, Ovid MEDLINE, CINAHL Plus, Web of Science, Airiti Library, Networked Digital Library of Theses and Dissertations and ProQuest until May 2020 were investigated. A total of eight studies (four case-control and four cohort studies) were eligible for quantitative analysis. A significant association between radiofrequency radiation exposure and breast cancer risk was detected [pooled relative risk (RR)=1.189; 95% confidence interval (CI), 1.056-1.339]. Subgroup analyses indicated that radiofrequency radiation exposure significantly increased the risk of breast cancer susceptibility among subjects aged ≥50 years (RR=2.179; 95% CI, 1.260-3.770). Pooled estimates revealed that the use of electrical appliances, which emit radiofrequency radiation, such as mobile phones and computers, significantly increased breast cancer development (RR=2.057; 95% CI, 1.272-3.327), while occupational radiofrequency exposure and transmitters did not increase breast cancer development (RR=1.274; 95% CI, 0.956-1.697; RR=1.133; 95% CI, 0.987-1.300, respectively). It was concluded that radiofrequency radiation exposure significantly increased the risk of breast cancer, especially in women aged ≥50 years and in individuals who used electric appliances, such as mobile phones and computers. In accordance with Preferred Reporting Items for Systematic Reviews and Meta-analysis, an evaluation protocol was prepared and registered with the PROSPERO database (registration no. CRD42018087283).

RDGN-based predictive model for the prognosis of breast cancer

Background

Breast cancer is the most diagnosed malignancy in females in the United States. The members of retinal determination gene network (RDGN) including DACH, EYA, as well as SIX families participate in the proliferation, apoptosis, and metastasis of multiple tumors including breast cancer. A comprehensive predictive model of RDGN might be helpful to herald the prognosis of breast cancer patients.

Methods

In this study, the Gene Expression Ominibus (GEO) and Gene Set Expression Analysis (GSEA) algorithm were used to investigate the effect of RDGN members on downstream signaling pathways. Besides, based on The Cancer Genome Atlas (TCGA) database, we explored the expression patterns of RDGN members in tumors, normal tissues, and different breast cancer subtypes. Moreover, we estimated the relationship between RDGN members and the outcomes of breast cancer patients. Lastly, we constructed a RDGN-based predictive model by Cox proportional hazard regression and verified the model in two separate GEO datasets.

Results

The results of GSEA showed that the expression of DACH1 was negatively correlated with cell cycle and DNA replication pathways. On the contrary, the levels of EYA2 and SIX1 were significantly positively correlated with DNA replication, mTOR, and Wnt pathways. Further investigation in TCGA database indicated that DACH1 expression was lower in breast cancers especially basal-like subtype. In the meanwhile, SIX1 was remarkably upregulated in breast cancers while EYA2 level was increased in Basal-like and Her-2 enriched subtypes. Survival analyses demonstrated that DACH1 was a favorable factor while EYA2 and SIX1 were risk factors for breast cancer patients. Given the results of Cox proportional hazard regression analysis, two members of RDGN were involved in the present predictive model and patients with high model index had poorer outcomes.

Conclusion

This study showed that aberrant RDGN expression was an unfavorable factor for breast cancer. This RDGN-based comprehensively framework was meaningful for predicting the prognosis of breast cancer patients.

Mitotic score and pleomorphic histology in invasive lobular carcinoma of the breast: impact on disease-free survival

PURPOSE

Pleomorphic invasive lobular carcinoma (ILC) has long been thought to have worse outcomes than classic ILC and is therefore often treated with chemotherapy. However, recent data question the utility of the pleomorphic designation, as the poor outcomes seen may be related to other associated high-risk features. Importantly, mitotic count may better define a subset of ILC with high risk of recurrence. We sought to determine the impact of pleomorphic histology versus mitotic count on disease-free survival (DFS) in pure ILC. Additionally, we evaluated whether pleomorphic histology was associated with receipt of chemotherapy when adjusting for other factors.

METHODS

We analyzed a cohort of 475 patients with stage I-III pure ILC. We used Kaplan-Meier estimates, and Cox proportional hazards and logistic regression for multivariate analyses. Pleomorphic histology was confirmed by central pathology review.

RESULTS

In a multivariate model, pleomorphic histology was not associated with reduced DFS. Only mitotic score, receptor subtype, and pathologic stage were independently and significantly associated with DFS. Patients with pleomorphic ILC were significantly more likely to receive chemotherapy than patients with classic ILC (adjusted odds ratio 2.96, p = 0.026).

CONCLUSIONS

The pleomorphic designation in ILC does not have clinical utility and should not be used to determine therapy. Rather, mitotic count identified clear prognostic groups in this cohort of pure ILC.

Significant inter- and intra-laboratory variation in grading of invasive breast cancer: A nationwide study of 33,043 patients in the Netherlands

Accurate, consistent and reproducible grading by pathologists is of key-importance for identification of individual patients with invasive breast cancer (IBC) that will or will not benefit from adjuvant systemic treatment. We studied the laboratory-specific grading variation using nationwide real-life data to create insight and awareness in grading variation. Synoptic pathology reports of all IBC resection-specimens, obtained between 2013 and 2016, were retrieved from the nationwide Dutch Pathology Registry (PALGA). Absolute differences in laboratory-proportions of Grades I-III were compared to the national reference. Multivariable logistic regression provided laboratory-specific odds ratios (ORs) for high- vs. low-grade IBC. 33,792 IBC pathology reports of 33,043 patients from 39 laboratories were included, of which 28.1% were reported as Grade I (range between laboratories 16.3-43.3%), 47.6% as Grade II (38.4-57.8%), and 24.3% as Grade III (15.5-34.3%). Based on national guidelines, the indication for adjuvant chemotherapy was dependent on histologic grade in 29.9% of patients. After case-mix correction, 20 laboratories (51.3%) showed a significantly deviant OR. Significant grading differences were also observed among pathologists within laboratories. In this cohort of 33,043 breast cancer patients, we observed substantial inter- and intra-laboratory variation in histologic grading. It can be anticipated that this has influenced outcome including exposure to unnecessary toxicity, since choice of adjuvant chemotherapy was dependent on grade in nearly a third of patients. Better standardization and training seems warranted.

Hormone- and HER2-receptor assessment in 33,046 breast cancer patients: a nationwide comparison of positivity rates between pathology laboratories in the Netherlands

Purpose

Patient management of invasive breast cancer (IBC) is to a large extent based on hormone- and HER2-receptor assessment. High-quality, reliable receptor assessment is of key importance as false results may lead to under- or overtreatment of patients. Surveillance of case-mix adjusted positivity rates has been suggested as a tool to identify laboratories with insufficient testing assays, as this covers the whole process of receptor assessment and enables laboratories to benchmark their positivity rates against other laboratories. We studied laboratory-specific variation in hormone- and HER2 positivity rates of 33,046 breast cancer patients using real-life nationwide data.

Methods

All synoptic pathology reports of IBC resection-specimens, obtained between 2013 and 2016, were retrieved from the nationwide Dutch pathology registry (PALGA). Absolute and case-mix adjusted receptor positivity rates were compared to the mean national proportion and presented in funnel plots in separate analyses for estrogen (ER), progesterone (PR) and HER2. Case-mix adjustment was performed by multivariable logistic regression.

Results

33,794 IBC lesions from 33,046 patients of 39 pathology laboratories were included. After case-mix adjustment, mean positivity rates were 87.2% for ER (range 80.4–94.3), 71.3% for PR (62.5–77.5%), and 9.9% for HER2 (5.5–12.7%). Overall, 14 (35.9%), 17 (43.6%) and 11 (28.2%) laboratories showed positivity rates outside the 95% confidence interval for ER, PR and HER2, respectively.

Conclusion

This nationwide study shows that absolute variation in hormone- and HER2-receptor positivity rates between Dutch pathology laboratories is limited. Yet, the considerable number of outlying laboratories shows that there is still need for improvement. Continuous monitoring and benchmarking of positivity rates may help to realize this.