Use of Biomarkers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline

Prognostic Value of Plasma HER2 Gene Copy Number in HER2-Positive Metastatic Breast Cancer Treated with First-Line Trastuzumab

Objective

Patients with HER2-positive metastatic breast cancer (MBC) benefit from trastuzumab-based therapy but eventually develop intrinsic or acquired resistance. Whether plasma HER2 gene copy number (GCN) could predict survival after trastuzumab treatment remained controversial. We evaluated the prognostic value of plasma HER2 GCN using low-coverage whole-genome sequencing (LC-WGS).

Methods

The plasma was collected from HER2-positive MBC patients whose pre-therapeutic samples were available before first-line trastuzumab-based treatment. Plasma DNA was extracted and assessed by LC-WGS for HER2 GCN. The optimal cut-off point for HER2 GCN to shorter survival was determined by receiver operating characteristic (ROC) curve analysis.

Results

A total of 49 patients were retrieved from 2013 to 2017, among whom 21 had multiple organ involvement (≥3 sites). Variations of HER2 GCN in pre-therapeutic plasma ranged from 1.89 to 23.86 (median = 2.59). ROC analysis identified the optimal cut-off point for HER2 GCN as 2.82 (P = 0.005), with 23 patients had high-level HER2 GCN and 26 in the low-level group. Both progression-free survival (PFS, P = 0.032) and overall survival (OS, P = 0.006) were adversely associated with high-level HER2 GCN. In multivariate analyses, high HER2 GCN was independently associated with shorter PFS [hazard ratio (HR) = 2.042, P = 0.037], while both high HER2 GCN (HR = 4.909, P = 0.004) and more metastatic organs (HR = 4.019, P = 0.011) were negative prognostic factors for OS.

Conclusion

In this population of patients with HER2-positive MBC, individuals with high HER2 GCNs in plasma had worse prognosis after trastuzumab-based therapy. Plasma HER2 GCN may be a prognostic marker in these patients.

Albumin Nanoparticle of Paclitaxel (Abraxane) Decreases while Taxol Increases Breast Cancer Stem Cells in Treatment of Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) has a high rate of metastasis, which is associated with breast cancer stem-like cells (CSCs). Although Taxol (micelle formulation of paclitaxel) is the first line chemotherapy to treat TNBC, it increases CSCs in residual tumors. Abraxane, albumin nanoparticle of paclitaxel, showed lower plasma concentration compared to Taxol in both human and animal models, but it is not clear why Abraxane showed superior efficacy to Taxol in treatment of metastatic breast cancer in humans. In this study, we intend to investigate if Abraxane eliminates CSCs for its better efficacy. The results showed that Abraxane showed similar cytotoxicity in SUM149 cells in comparison with Taxol. Although Abraxane showed 3- to 5-fold lower blood drug concentration compared to Taxol, it achieved similar tumor drug concentration and 10-fold higher tumor/plasma ratio in SUM149 xenograft NOD/SCID mouse model. In addition, Abraxane and Taxol showed similar efficacy to shrink the tumor size in orthotopic breast cancer NOD/SCID mouse model. However, Abraxane decreased breast CSCs frequency by 3- to 9-fold, while Taxol increased breast CSCs frequency in an orthotopic breast cancer NOD/SCID mouse model. Furthermore, Abraxane increased 3- to 15-fold intracellular uptake in both ALDH+ CSCs and differentiated ALDH- cells in comparison with Taxol, which provides a mechanism for Abraxane's superior efficacy to eliminate CSCs in comparison with Taxol. Our data suggest albumin nanoparticle Abraxane may have a broad implication to enhance drug's efficacy by eliminating breast cancer stem cells for treatment of metastatic diseases.

Correlation between salivary and serum CA15-3 concentrations in patients with breast cancer

The early detection of breast cancer enables the use of less aggressive treatment and increases patient survival. The transmembrane glycoprotein mucin 1, which is also known as cancer antigen 15-3 (CA15-3), is aberrantly glycosylated and overexpressed in a variety of epithelial cancers, and serves a crucial role in the progression of the disease. CA15-3 is currently used as a marker of breast cancer. In the present study, CA15-3 concentrations in saliva and blood of patients with breast cancer were evaluated to test new assays to detect salivary CA15-3 in addition to ELISA and its diagnostic value. To the best of our knowledge, there are no previous reports of the use of chemiluminescence assay (CLIA) and electrochemiluminescence assay (ECLIA) in saliva. Saliva and blood were collected on the same day from patients with breast cancer (n=26) and healthy controls (n=28). For each subject, the level of serum CA15-3 was measured using ECLIA, and the level of salivary CA15-3 was measured using ECLIA, CLIA and enzyme-linked immunosorbent assay (ELISA). ELISA and CLIA were able to detect CA15-3 in saliva; however, ECLIA could not detect salivary CA15-3. There was no significant difference between the mean serum and salivary CA15-3 levels in patients with breast cancer or healthy controls. The levels of CA15-3 were highest for luminal breast cancer subtypes and stage IV cases. A moderate correlation was observed between salivary and serum CA15-3 levels as measured by ELISA in breast cancer patients (r=0.56; P=0.0047). The results demonstrated that ECLIA was not a good method to detect salivary CA15-3, although it is the gold standard for detecting serum CA15-3. The presence of CA15-3 in saliva was confirmed, and this will be useful in future research. Further investigations are necessary to confirm the ability to detect salivary CA15-3 and its correlation with serum CA15-3.

Do 21-Gene Recurrence Score Influence Chemotherapy Decisions in T1bN0 Breast Cancer Patients?

Purpose: Hormone receptor (HR)-positive breast cancer patients with tumor size ≤1.0 cm and negative node have favorable outcomes. The 21-gene Recurrence Score (RS) could predict response to chemotherapy for HR+ breast cancer, but its role in T1bN0 disease is challenging.

Methods: T1bN0 breast cancer patients diagnosed between January 2014 and June 2019 with RS results were included and categorized as Low- (RS < 18), Intermediate- (RS 18–30), or High-risk (RS > 30) groups. Univariate and multivariate analysis were used to assess factors associated with RS distribution and chemotherapy recommendation. Chemotherapy decisions change and patient adherence after 21-gene RS testing were also evaluated.

Results: Among 237 patients with T1bN0 tumors, proportions of Low-, Intermediate-, and High-risk RS were 19.8, 63.3, and 16.9%, respectively. Multivariate analysis found that ER expression (P = 0.011), PR expression (P < 0.001), and Ki-67 index (P = 0.001) were independently associated with RS distribution. Adjuvant chemotherapy was recommended for 31.6% of patients, which was more frequently given to patients with higher tumor grade [Odds ratio (OR) = 2.99 for grade II, OR = 59.19 for grade III, P = 0.006], lymph vascular invasion (OR = 8.22, P = 0.032), Luminal-B subtype (OR = 5.68, P < 0.001), and Intermediate-to High-risk RS (OR = 10.01 for Intermediate-risk, OR = 192.42 for High-risk, P < 0.001). Chemotherapy decision change was found in 18.6% of patients, mainly in those with Intermediate- to High-risk RS tumor with the majority from no-chemotherapy to chemotherapy. The treatment compliance rate after the 21-gene RS testing with MDT was 95.4%.

Conclusion: RS category was related to ER, PR, and Ki-67 expression, which was recognized as an independent factor of chemotherapy recommendation in T1bN0 breast cancer. The 21-gene RS testing would lead to a chemotherapy decision change rate of 18.6% as well as a high treatment adherence, which can be applied in T1bN0 patients.

Overview of Breast Cancer and Implications of Overtreatment of Early-Stage Breast Cancer: An Indian Perspective

The prevalence and mortality of breast cancer is increasing in Asian countries, including India. With advances in medical technology leading to better detection and characterization of the disease, it has been possible to classify breast cancer into various subtypes using markers, which helps predict the risk of distant recurrence, response to therapy, and prognosis using a combination of molecular and clinical parameters. Breast cancer and its therapy, mainly surgery, systemic therapy (anticancer chemotherapy, hormonal therapy, targeted therapy, and immunotherapy), and radiation therapy, are associated with significant adverse influences on physical and mental health, quality of life, and the economic status of the patient and her family. The fear of recurrence and its devastating effects often leads to overtreatment, with a toxic cost to the patient financially and physically in cases in which this is not required. This article discusses some aspects of a breast cancer diagnosis and its impact on the various facets of the life of the patient and her family. It further elucidates the role of prognostic factors, the currently available biomarkers and prognostic signatures, and the importance of ethnically validating biomarkers and prognostic signatures.

Multigene testing in breast cancer: What have we learned from the 21-gene recurrence score assay?

Most invasive breast cancers express hormone receptors (HR) and typically have a favorable prognosis following endocrine therapy. Patients at a higher risk of recurrence can be identified by multigene prognostic classifiers such as the 21-gene recurrence score (RS) assay, 70-gene prognostic signature, PAM-50, 12-gene molecular score, and others. The 21-gene RS assay (Oncotype Dx™, Genomic Health, Redwood City, CA) has level I clinical evidence and is the most widely used multigene assay in North America. The RS assay is based on reverse transcriptase polymerase chain reaction that can be performed on the RNA isolated from formalin-fixed paraffin-embedded tissue. It evaluates the expression of 16 cancer-related genes developed based on a multi-step approach. Due to its ability to assess recurrence risk and predict potential benefit from chemotherapy, the assay is recommended for patients with node-negative, HR-positive, and human epidermal growth factor receptor 2 (HER2)-negative breast cancer by the American Society of Clinical Oncology, National Comprehensive Cancer Network clinical practice guidelines in oncology, European Society for Medical Oncology clinical practice guidelines, and St. Gallen consensus panel guidelines. The RS assay has also been incorporated in the prognostic stage groups in the 8th edition of the American Joint Commission of Cancer staging manual in order to provide essential genomic information for optimal treatment decisions. This review will focus on the utility of the RS assay in HR-positive and HER2-negative breast cancer patients, including risk of distant and locoregional recurrence in node-negative and node-positive tumors, association with radiotherapy, special subtypes of breast cancer, practical issues related to selecting tumors for testing, and overview of the recently published TailorX (Trial Assigning IndividuaLized Options for treatment [Rx]) results.

EndoPredict® in early hormone receptor-positive, HER2-negative breast cancer

Purpose

Evaluating consecutive early breast cancer patients, we analyzed both the impact of EndoPredict^® on clinical decisions as well as clinico-pathological factors influencing the decision to perform this gene expression test.

Methods

Hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients treated between 2011 and 2016 were included in this study to investigate the role of EndoPredict^® (EPclin) in the treatment of early breast cancer. A main study aim was to analyze the changes in therapy recommendations with and without EPclin. In addition, the impact of clinico-pathological parameters for the decision to perform EPclin was examined by Pearson's chi-squared test (χ²-test) and Fisher's exact test as well as univariate and multivariate logistic regressions.

Results

In a cohort of 869 consecutive early HR-positive, HER-negative breast cancer patients, EPclin was utilized in 156 (18.0%) patients. EPclin led to changes in therapy recommendations in 33.3% (n = 52), with both therapy escalation in 19.2% (n = 30) and de-escalation in 14.1% (n = 22). The clinico-pathological factors influencing the use of EPclin were age (P < 0.001, odds ratio [OR] 0.498), tumor size (P = 0.011, OR 0.071), nodal status (P = 0.021, OR 1.674), histological grade (P = 0.043, OR 0.432), and Ki-67 (P < 0.001, OR 3.599).

Conclusions

EPclin led to a change in therapy recommendations in one third of the patients. Clinico-pathological parameters such as younger age, smaller tumor size, positive nodal status, intermediate histological grade and intermediate Ki-67 had a significant influence on the use of EndoPredict^®.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05688-1) contains supplementary material, which is available to authorized users.

Cancer genomics predicts disease relapse and therapeutic response to neoadjuvant chemotherapy of hormone sensitive breast cancers

Several studies provide insight into the landscape of breast cancer genomics with the genomic characterization of tumors offering exceptional opportunities in defining therapies tailored to the patient's specific need. However, translating genomic data into personalized treatment regimens has been hampered partly due to uncertainties in deviating from guideline based clinical protocols. Here we report a genomic approach to predict favorable outcome to treatment responses thus enabling personalized medicine in the selection of specific treatment regimens. The genomic data were divided into a training set of N = 835 cases and a validation set consisting of 1315 hormone sensitive, 634 triple negative breast cancer (TNBC) and 1365 breast cancer patients with information on neoadjuvant chemotherapy responses. Patients were selected by the following criteria: estrogen receptor (ER) status, lymph node invasion, recurrence free survival. The k-means classification algorithm delineated clusters with low- and high- expression of genes related to recurrence of disease; a multivariate Cox's proportional hazard model defined recurrence risk for disease. Classifier genes were validated by Immunohistochemistry (IHC) using tissue microarray sections containing both normal and cancerous tissues and by evaluating findings deposited in the human protein atlas repository. Based on the leave-on-out cross validation procedure of 4 independent data sets we identified 51-genes associated with disease relapse and selected 10, i.e. TOP2A, AURKA, CKS2, CCNB2, CDK1 SLC19A1, E2F8, E2F1, PRC1, KIF11 for in depth validation. Expression of the mechanistically linked disease regulated genes significantly correlated with recurrence free survival among ER-positive and triple negative breast cancer patients and was independent of age, tumor size, histological grade and node status. Importantly, the classifier genes predicted pathological complete responses to neoadjuvant chemotherapy (P < 0.001) with high expression of these genes being associated with an improved therapeutic response toward two different anthracycline-taxane regimens; thus, highlighting the prospective for precision medicine. Our study demonstrates the potential of classifier genes to predict risk for disease relapse and treatment response to chemotherapies. The classifier genes enable rational selection of patients who benefit best from a given chemotherapy thus providing the best possible care. The findings encourage independent clinical validation.

p53 and BLC2 Immunohistochemical Expression Across Molecular Subtypes in 1099 Early Breast Cancer Patients With Long-Term Follow-up: An Observational Study

INTRODUCTION

p53 and antiapoptotic B-cell leukemia/lymphoma 2 (BLC2) have been proposed as prognostic markers for early breast cancer (BC), although their relationship with conventional parameters and patient prognosis, as well as their distribution within the molecular BC subtypes remains uncertain.

PATIENTS AND METHODS

In this observational study, we analyzed the immunohistochemical expression of p53 and BLC2 in 1099 early BC patients surgically treated between 2000 and 2006 and followed for at least 5 years, also considering their association with pathologic factors and molecular subtypes, as well as their influence on disease-free survival.

RESULTS

p53 and BLC2 are distributed differently across molecular subtypes (P < .0001); in particular, p53 positivity and BLC2 negativity seems to be associated with more aggressive conventional tumor phenotypes. Moreover, BLC2 negativity seems to be a significant discriminating factor for disease-free survival (P = .003) according to Kaplan-Meier analysis, while p53 seems to have no discriminating effect. Among patients with discordant p53/BLC2 phenotype, the combination p53⁺BLC2^- seems to be associated with the worst outcomes (P = .007) and significantly influenced the clinical course of node-negative patients treated only with hormone therapy (P = .004).

CONCLUSION

These two biomarkers, in addition to conventional pathologic factors and molecular subtype, could help define the risk and outcome of BC.

Prediction of Oncotype DX recurrence score using deep multi-layer perceptrons in estrogen receptor-positive, HER2-negative breast cancer

Oncotype DX (ODX) is a multi-gene expression signature designed for estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients to predict the recurrence score (RS) and chemotherapy (CT) benefit. The aim of our study is to develop a prediction tool for the three RS's categories based on deep multi-layer perceptrons (DMLP) and using only the morphoimmunohistological variables. We performed a retrospective cohort of 320 patients who underwent ODX testing from three French hospitals. Clinico-pathological characteristics were recorded. We built a supervised machine learning classification model using Matlab software with 152 cases for the training and 168 cases for the testing. Three classifiers were used to learn the three risk categories of the ODX, namely the low, intermediate, and high risk. Experimental results provide the area under the curve (AUC), respectively, for the three risk categories: 0.63 [95% confidence interval: (0.5446, 0.7154), p < 0.001], 0.59 [95% confidence interval: (0.5031, 0.6769), p < 0.001], 0.75 [95% confidence interval: (0.6184, 0.8816), p < 0.001]. Concordance rate between actual RS and predicted RS ranged from 53 to 56% for each class between DMLP and ODX. The concordance rate of low and intermediate combined risk group was 85%.We developed a predictive machine learning model that could help to define patient's RS. Moreover, we integrated histopathological data and DMLP results to select tumor for ODX testing. Thus, this process allows more relevant use of histopathological data, and optimizes and enhances this information.

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

OBJECTIVE

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The RNA binding protein CPEB2 regulates hormone sensing in mammary gland development and luminal breast cancer

Organogenesis is directed by coordinated cell proliferation and differentiation programs. The hierarchical networks of transcription factors driving mammary gland development and function have been widely studied. However, the contribution of posttranscriptional gene expression reprogramming remains largely unexplored. The 3' untranslated regions of messenger RNAs (mRNAs) contain combinatorial ensembles of cis-regulatory elements that define transcript-specific regulation of protein synthesis through their cognate RNA binding proteins. We analyze the contribution of the RNA binding cytoplasmic polyadenylation element-binding (CPEB) protein family, which collectively regulate mRNA translation for about 30% of the genome. We find that CPEB2 is required for the integration of hormonal signaling by controlling the protein expression from a subset of ER/PR- regulated transcripts. Furthermore, CPEB2 is critical for the development of ER-positive breast tumors. This work uncovers a previously unknown gene expression regulation level in breast morphogenesis and tumorigenesis, coordinating sequential transcriptional and posttranscriptional layers of gene expression regulation.

Estrogen and Progesterone Receptor Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Guideline Update

PURPOSE.—

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen receptor (ER) and progesterone receptor (PgR) testing in breast cancer guideline.

METHODS.—

A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature.

RECOMMENDATIONS.—

The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines .

Breast cancer: Biology, biomarkers, and treatments

During the past recent years, various therapies emerged in the era of breast cancer. Breast cancer is a heterogeneous disease in which genetic and environmental factors are involved. Breast cancer stem cells (BCSCs) are the main player in the aggressiveness of different tumors and also, these cells are the main challenge in cancer treatment. Moreover, the major obstacle to achieve an effective treatment is resistance to therapies. There are various types of treatment for breast cancer (BC) patients. Therefore, in this review, we present the current treatments, novel approaches such as antibody-drug conjugation systems (ADCs), nanoparticles (albumin-, metal-, lipid-, polymer-, micelle-based nanoparticles), and BCSCs-based therapies. Furthermore, prognostic and predictive biomarkers will be discussed also biomarkers that have been applied by some tests such as Oncotype DX, Mamm αPrint, and uPA/PAI-1 are regarded as suitable prognostic and predictive factors in breast cancer.

Application of magnetic nanoparticles in nucleic acid detection

Nucleic acid is the main material for storing, copying, and transmitting genetic information. Gene sequencing is of great significance in DNA damage research, gene therapy, mutation analysis, bacterial infection, drug development, and clinical diagnosis. Gene detection has a wide range of applications, such as environmental, biomedical, pharmaceutical, agriculture and forensic medicine to name a few. Compared with Sanger sequencing, high-throughput sequencing technology has the advantages of larger output, high resolution, and low cost which greatly promotes the application of sequencing technology in life science research. Magnetic nanoparticles, as an important part of nanomaterials, have been widely used in various applications because of their good dispersion, high surface area, low cost, easy separation in buffer systems and signal detection. Based on the above, the application of magnetic nanoparticles in nucleic acid detection was reviewed.

Harmonizing gene signatures to predict benefit from adjuvant chemotherapy in early breast cancer

PURPOSE OF REVIEW

Breast cancer is a heterogeneous disease, including different subtypes with their own biology, prognosis, clinical characteristics and treatment. To date, traditional clinical and pathological determinants remain the main factors guiding treatment decision-making; however, the development of multigene assays improved the ability to predict the risk of recurrence in patients with early-stage breast cancer. These tools underwent an extensive independent validation and have already been partly incorporated into clinical practice.

RECENT FINDINGS

The current article summarizes current evidence for the use of the different genomic assays in clinical practice, their characteristics and validation studies. A few studies comparing available genomic assays revealed that they provide different information with a modest correlation and that they are not interchangeable; other trials are currently ongoing in this setting.

SUMMARY

Variability across different gene signatures may be a challenge for the optimal management of the individual patient, hence each assay should be used for the clinical setting in which it has been validated.

Absolute Improvements in Freedom From Distant Recurrence to Tailor Adjuvant Endocrine Therapies for Premenopausal Women: Results From TEXT and SOFT

PURPOSE

The Tamoxifen and Exemestane Trial (TEXT)/Suppression of Ovarian Function Trial (SOFT) showed superior outcomes for premenopausal women with hormone receptor (HR)-positive breast cancer treated with adjuvant exemestane plus ovarian function suppression (OFS) or tamoxifen plus OFS versus tamoxifen alone. We previously reported the magnitude of absolute improvements in freedom from any recurrence across a continuous, composite measure of recurrence risk to tailor decision making. With longer follow-up, we now focus on distant recurrence.

METHODS

The TEXT/SOFT HR-positive/human epidermal growth factor receptor 2 (HER2)-negative analysis population included 4,891 women stratified by predetermined chemotherapy use. Kaplan-Meier estimates of 8-year freedom from distant recurrence were analyzed using subpopulation treatment effect pattern plot (STEPP) methodology across subpopulations defined by the continuous composite measure of recurrence risk. For each patient, the composite risk value was obtained from a Cox model that incorporated age; nodal status; tumor size; grade; and estrogen receptor, progesterone receptor, and Ki-67 labeling index expression levels.

RESULTS

The overall rate of 8-year freedom from distant recurrence was 91.1% and ranged from approximately 100% to 63% across lowest to highest composite risks. TEXT patients who received chemotherapy had an average absolute improvement with exemestane plus OFS versus tamoxifen plus OFS of 5.1%, and STEPP analysis showed improvements from less than 1% to more than 15% from lowest to highest composite risks. SOFT patients who remained premenopausal after chemotherapy had an average 5.2% absolute improvement with exemestane plus OFS versus tamoxifen and reached 10% across composite risks; for tamoxifen plus OFS versus tamoxifen, the maximum improvement was approximately 3.5%. Women who did not receive chemotherapy had a more than 97% rate of 8-year freedom from distant recurrence, and improvements with exemestane plus OFS ranged from 1% to 4%.

CONCLUSION

Premenopausal women with HR-positive/HER2-negative breast cancer and high recurrence risk, as defined by clinicopathologic characteristics, may experience a 10% to 15% absolute improvement in 8-year freedom from distant recurrence with exemestane plus OFS versus tamoxifen plus OFS or tamoxifen alone. The potential benefit of escalating endocrine therapy versus tamoxifen alone is minimal for those at low recurrence risk.

Estrogen and Progesterone Receptor Testing in Breast Cancer: ASCO/CAP Guideline Update

PURPOSE

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen (ER) and progesterone receptor (PgR) testing in breast cancer guideline.

METHODS

A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature.

RECOMMENDATIONS

The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines.

Evaluating overall survival and competing risks of survival in patients with early-stage breast cancer using a comprehensive nomogram

BACKGROUND

Patients with early-stage breast cancer (BC) live long but have competing comorbidities. This study aimed to estimate the effect of cancer and other causes of death in patients with early-stage BC and further quantify the survival differences.

MATERIALS AND METHODS

Data of patients diagnosed with BC between 2010 and 2016 were collected from the Surveillance, Epidemiology, and End Results database. The cumulative incidence function for breast cancer-specific mortality (BCSM) and other cause-specific mortality (OCSM) was estimated, and the differences were tested using the Gray test. The nomogram for estimating 3-, 4-, and 5-year overall survival (OS), breast cancer-specific survival, and other cause-specific survival was established based on Cox regression analysis and Fine and Gray competing risk analysis. The discriminative ability, calibration, and precision of the nomogram were evaluated and compared using C statistics, calibration plots, and area under the receiver operating characteristic curve.

RESULTS

A total of 196 304 eligible patients with early-stage BC were identified in this study. Of these, 12 417 (6.3%) patients died: 5628 (45.3%) due to BC and 6789 (54.7%) due to other causes. Five validated variables were incorporated to develop the prognostic nomogram: age, grade, tumor size, subtype, and surgery of primary site (Figure 3). Age was a strong predictive factor, which was more obvious in OCSM. The effect of surgery was more prominent in BCSM. Increased tumor size was correlated with OS and BCSM and slightly correlated with OCSM. Grade and subtype differences were more predominant in BCSM than in OCSM. The established nomogram was well calibrated and displayed good discrimination.

CONCLUSIONS

We evaluate OS and competing risks of death in patients with early-stage BC, establishing the first comprehensive prognostic nomogram.

Prospective observational study on the impact of the 21-gene assay on treatment decisions and resources optimization in breast cancer patients in Lombardy: The BONDX study

PURPOSE

Adjuvant treatment decisions in early breast cancer (eBC) have traditionally been driven by risk stratification based on clinical and pathological risk factors. The 21-gene Oncotype DX® assay has been validated as a predictive test for benefit from adjuvant chemotherapy (CT), hence assessing its impact in clinical decisions is of high interest. The objective of this study was to estimate the rate of adjuvant treatment decision modification impacted by the Recurrence Score® result, and the consequent budget impact.

METHODS

The study was a multicentre, prospective, real-life experience in Lombardy (Italy) including consecutive patients with T1-T3, N0-N1a, and ER+/HER2-eBC with clinical-pathologic "intermediate risk" of relapse. The change in treatment recommendations was assessed before and after availability of Recurrence Score result. A budget model evaluated the implications of 21-gene testing in the study population.

RESULTS

The overall proportion of CT recommendations was reduced from 24.6% to 15.2% after 21-gene testing, with a major impact in patients initially considered for CT plus hormone therapy (CHT). In these patients, the total budget was reduced, leading to a net saving of -€81,017. The greater the physician propensity to prescribe CHT, the higher the potential savings for the health system from sparing CT in most tested patients.

CONCLUSIONS

Our real-life experience suggests that all intermediate-risk ER+/HER2-eBC patients who are initially deemed candidates for CHT should be tested with the 21-gene test. The potential to spare CT in at least half of them offers relevant advantages for patients and national health services.

Pharmacogenomics of breast cancer: highlighting CYP2D6 and tamoxifen

PURPOSE

To review recent pharmacogenomics studies on breast cancer patients undergoing tamoxifen therapy, highlighting how our knowledge on cytochrome P450 2D6 (CYP2D6) can help to guide the development of adjuvant therapies for these patients.

METHODS

A comprehensive literature search was conducted. Articles reporting findings pertaining to the effect of CYP2D6 on the therapeutic efficacy of tamoxifen, those reporting how targeting CYP2D6 could inform tamoxifen-based therapy development, and those on the tamoxifen effects on cell lines and animal models were included in the review.

RESULTS

With CYP2D6 being the primary enzyme for tamoxifen metabolism, single-nucleotide polymorphisms (SNPs) in this gene were one of the determinants in the rate of tamoxifen metabolism, thereby potentially having an effect on the efficacy of tamoxifen-based therapies. Our review indicates the potential effectiveness of targeting these SNPs, including those for the CYP2D6*10 allele (c. 100C > T), in modifying the level of tamoxifen metabolism. These findings suggest the importance of pharmacogenomics research in our understanding of the efficacy of adjuvant therapies. However, the involvement of multiple enzymes in tamoxifen metabolism, dietary factors, ethnic differences in gene frequencies, and patients' compliance to tamoxifen therapies in studies do present challenges in pharmacogenomics research.

CONCLUSIONS

Pharmacogenomics could play important roles in mediating the advancement of tamoxifen-based adjuvant therapies. Research efforts should be directed towards the exploration of further SNPs of CYP2D6 that affect tamoxifen metabolism, as well as epigenetic changes in CYP2D6, enabling the design of precision medicine and confirming clinical validity in the use of pharmacogenomics for tamoxifen.

Correlation Between Oncotype DX, PREDICT and the Nottingham Prognostic Index: Implications for the Management of Early Breast Cancer

Introduction Breast cancer remains the most common cancer diagnosis in the UK. The current clinical practice utilises two different types of modalities to estimate the prognosis, risk of recurrence and benefit from adjuvant chemotherapy treatment in patients with early breast cancer. The first set of modalities includes risk calculators based on clinicopathological features, e.g. PREDICT or the Nottingham Prognostic Index (NPI); the second includes genetic profiling of tumour tissue using Oncotype DX (ODX; Genomic Health, Redwood City, CA) testing. PREDICT, NPI and ODX stratify breast cancers into high-, intermediate- and low-risk categories to help guide adjuvant chemotherapy treatment decisions. This study compares PREDICT, NPI and ODX Recurrence Scores (RS), with the aim of assessing 1) the correlation between the RS for PREDICT, NPI and ODX and 2) whether early breast cancer patients are stratified into similar risk categories by all three modalities. Methods This retrospective study included early breast cancer patients treated at a National Health Service (NHS) hospital over a 12-month period (October 1, 2017 to September 30, 2018). Inclusion criteria: consecutive patients with estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative and lymph node-negative breast cancer. All patients were discussed at the local multidisciplinary team (MDT) meeting and underwent ODX testing. Exclusion criteria: patients without ODX test scores; patients with an in-breast recurrence; patients who did not undergo a sentinel lymph node biopsy (SLNB); and patients with ductal carcinoma in situ (DCIS) only. NPI and PREDICT scores were calculated for each patient using online tools, and ODX data was obtained through Genomic Health and MDT records. Patients were risk-stratified into high, intermediate and low risk of recurrence groups based on their PREDICT, NPI and ODX scores. The thresholds for risk stratification were based on current practice, which is evidence-based. Correlations between PREDICT, NPI and ODX scores were analysed using Spearman's correlation coefficient. Results Forty-six patients (mean age: 56 years), with a total of 57 early breast cancers, underwent ODX testing. Risk categories generated by PREDICT very strongly correlated with NPI for all patients (r=0.92; P<0.0001). However, the RS generated by ODX testing only strongly correlated for patients with low-risk PREDICT scores (r=0.51; P=0.0134), while no correlation between RS and PREDICT was observed for patients with intermediate- or high-risk PREDICT scores (r=-0.0064; P=0.9767). Similar results were seen between NPI and RS. Overall, only 19/46 (41.3%) patients had an RS which corresponded to PREDICT risk category, while 18/46 (39.1%) patients had an RS that indicated a higher risk of recurrence than PREDICT, and 9/46 (19.6%) patients had an RS indicating a lower risk of recurrence than PREDICT. Similar results were found when comparing RS and NPI. Conclusion The risk of recurrence estimated by ODX in patients deemed low risk by PREDICT or NPI highly correlated, while no such correlation existed in patients with an estimated intermediate- or high-risk breast cancer. In PREDICT- or NPI-estimated intermediate- and high-risk patients, ODX provided valuable additional prognostic information to guide adjuvant treatment, while the potential avoidance of ODX testing in low-risk patients presents significant cost-savings.

New Advances in Molecular Breast Cancer Pathology

Breast cancer (BC) comprises a diverse spectrum of diseases featuring distinct presentation, morphological, biological, and clinical phenotypes. BC behaviour and response to therapy also vary widely. Current evidence indicates that traditional prognostic and predictive classification systems are insufficient to reflect the biological and clinical heterogeneity of BC. Advancements in high-throughput molecular techniques and bioinformatics have contributed to the improved understanding of BC biology, refinement of molecular taxonomies and the development of novel prognostic and predictive molecular assays. Molecular testing has also become increasingly important in the diagnosis and treatment of BC in the era of precision medicine. Despite the enormous amount of research work to develop and refine BC molecular prognostic and predictive assays, it is still in evolution and proper incorporation of these molecular tests into clinical practice to guide patient's management remains a challenge. With the increasing use of more sophisticated high throughput molecular techniques, large amounts of data will continue to emerge, which could potentially lead to identification of novel therapeutic targets and allow more precise classification systems that can accurately predict outcome and response to therapy. In this review, we provide an update on the molecular classification of BC and molecular prognostic assays. Companion diagnostics, contribution of massive parallel sequencing and the use of liquid biopsy are also highlighted.

The Correlation of Magee EquationsTM and Oncotype DX® Recurrence Score From Core Needle Biopsy Tissues in Predicting Response to Neoadjuvant Chemotherapy in ER+ and HER2- Breast Cancer

Objective

Oncotype DX^® recurrence score (RS) can be predicted from Magee Equations^TM (MS) postoperatively. The aim of this study is to investigate correlation of MS with RS from pretreatment core needle biopsy (CNB) tissues, and their clinical usefulness in prediction of response to neoadjuvant chemotherapy (NCT) in estrogen receptor-positive and human epidermal growth factor receptor 2-negative (ER+/HER2-) breast cancer (BC).

Materials and Methods

Pretreatment CNB tissue samples from 60 patients with ER+/HER2- invasive BC were analyzed for MS and RS correlation. MS and RS were categorized as follows: low (<18), intermediate (18-30), and high (≥ 31). Percentage Tumor size Reduction (%TR) was used to assess tumor response to NCT, and substantial %TR was defined as at least 50% reduction (≥50%TR). Correlation between MS and RS, and predictive factors for the ≥50%TR achievement were assessed.

Results

MS and RS represented a strong correlation (Spearman's correlation; r=0.58, p<0.0001) as a continuous variable. As a categorical variable, the concordance between MS and RS was 43.3%, and it increased to 80% (r=0.61, p=0.003) with the exclusion of the intermediate risk categories. Although, there was pathologic complete response (pCR), MS showed the highest predictive power for the ≥50% TR achievement, none of the factors were statistically significant (p≥0.07).

Conclusion

Our study demonstrated that there was a strong correlation between MS and RS from pretreatment biopsy tissue samples in ER+ and HER2- invasive BC.

Incorporation of clinical and biological factors improves prognostication and reflects contemporary clinical practice

We developed prognostic models for breast cancer-specific survival (BCSS) that consider anatomic stage and other important determinants of prognosis and survival in breast cancer, such as age, grade, and receptor-based subtypes with the intention to demonstrate that these factors, conditional on stage, improve prediction of BCSS. A total of 20,928 patients with stage I–III invasive primary breast cancer treated at The University of Texas MD Anderson Cancer Center between 1990 and 2016, who received surgery as an initial treatment were identified to generate prognostic models by Fine-Gray competing risk regression model. Model predictive accuracy was assessed using Harrell’s C-index. The Aalen–Johansen estimator and a selected Fine–Gray model were used to estimate the 5-year and 10-year BCSS probabilities. The performance of the selected model was evaluated by assessing discrimination and prediction calibration in an external validation dataset of 29,727 patients from the National Comprehensive Cancer Network (NCCN). The inclusion of age, grade, and receptor-based subtype in addition to stage significantly improved the model predictive accuracy (C-index: 0.774 (95% CI 0.755–0.794) vs. 0.692 for stage alone, p < 0.0001). Young age (<40), higher grade, and TNBC subtype were significantly associated with worse BCSS. The selected model showed good discriminative ability but poor calibration when applied to the validation data. After recalibration, the predictions showed good calibration in the training and validation data. More refined BCSS prediction is possible through a model that has been externally validated and includes clinical and biological factors.

Luminal A versus luminal B breast cancer: MammaTyper mRNA versus immunohistochemical subtyping with an emphasis on standardised Ki67 labelling-based or mitotic activity index-based proliferation assessment

AIMS

Proliferation assessment by the use of Ki67 is a crucial component in intrinsic subtyping of luminal breast cancers (BCs), but suffers from variability between laboratories, observers, and methods. MammaTyper is a quantitative molecular tool that measures mRNA levels of ERBB2, ESR1, PGR and MKI67 in BC, and interprets the results according to the St Gallen 2013 consensus recommendations. We compared MammaTyper with immunohistochemistry (IHC)-based subtypes, with a focus on standardised proliferation assessment.

METHODS AND RESULTS

We analysed the agreement in assigning subtypes between MammaTyper and receptor IHC in 101 unifocal luminal HER2-negative early BCs of no special type. Two Ki67 counting protocols, Ki67-Global (Ki67-G) and Ki67-HotSpot (Ki67-H), recommended by the International Ki67 in BC Working Group, and the mitotic activity index (MAI) were used for proliferation assessment. The proportions of BCs identified as luminal A and as luminal B were 55% and 45% for MammaTyper, 55% and 45% for IHC + Ki67-G, 36% and 64% for IHC + Ki67-H, and 56% and 44% for IHC + MAI. The levels of agreement between MammaTyper-based and IHC-based subtyping were 84% (κ = 0.679) for IHC + Ki67-G, 72% (κ = 0.462) for IHC + Ki67-H, and 89% (κ = 0.779) for IHC + MAI.

CONCLUSIONS

High rates of agreement between mRNA-based and IHC-based intrinsic subtyping of luminal HER2-negative BC can be achieved. However, the agreement between IHC-based and MammaTyper-based luminal subtypes depends on the proliferation assessment method, and was highest when the MAI was used. Further comparative clinical studies are needed to determine which method is to be preferred, including analysis of cost-effectiveness.

Programmed death-ligand 1 gene expression is a prognostic marker in early breast cancer and provides additional prognostic value to 21-gene and 70-gene signatures in estrogen receptor-positive disease

Gene and protein expression of programmed death‐ligand 1 (PD‐L1) are prognostic in early breast cancer (BC), but their prognostic information is inconsistent at least in some biological subgroups. The validated prognostic gene signatures (GS) in BC are mainly based on proliferation and estrogen receptor (ER)‐related genes. Here, we aimed to explore the prognostic capacity of PD‐L1 expression at the protein vs mRNA levels and to investigate the prognostic information that PD‐L1 can potentially add to routinely used GS. Gene expression data were derived from two early BC cohorts (cohort 1: 562 patients; cohort 2: 1081 patients). Tissue microarrays from cohort 1 were immunohistochemically (IHC) stained for PD‐L1 using the SP263 clone. GS scores (21‐gene, 70‐gene) were calculated, and likelihood‐ratio (LR) tests and concordance indices were used to evaluate the additional prognostic information for each signature. The immune cell composition was also evaluated using the CIBERSORT in silico tool. PD‐L1 gene and protein expressions were independently associated with better prognosis. In ER+/HER2− patients, PD‐L1 gene expression provided significant additional prognostic information beyond that of both 21‐GS [LR‐Δχ² = 15.289 and LR‐Δχ² = 8.812, P < 0.01 for distant metastasis‐free interval (DMFI) in cohorts 1 and 2, respectively] and 70‐GS score alone (LR‐Δχ² = 18.198 and LR‐Δχ² = 8.467, P < 0.01 for DMFI in cohorts 1 and 2, respectively). PD‐L1 expression was correlated with IHC‐determined CD3+ cells (r = 0.41, P < 0.001) and with CD8+ (r = 0.62, P < 0.001) and CD4+ memory activated (r = 0.66, P < 0.001) but not with memory resting (r = −0.063, P = 0.14) or regulatory (r = −0.12, P < 0.01) T cells in silico. PD‐L1 gene expression represents a promising favorable prognostic marker and can provide additional prognostic value to 21‐ and 70‐gene scores in ER+/HER2− BC.

A 3-gene biomarker signature to predict response to taxane-based neoadjuvant chemotherapy in breast cancer

Breast cancer is the most common cancer in women worldwide, affecting one in eight women in their lifetime. Taxane-based chemotherapy is routinely used in the treatment of breast cancer. The purpose of this study was to develop and validate a predictive biomarker to improve the benefit/risk ratio for that cytotoxic chemotherapy. We explicitly strived for a biomarker that enables secure translation into clinical practice. We used genome-wide gene expression data of the Hatzis et al. discovery cohort of 310 patients for biomarker development and three independent cohorts with a total of 567 breast cancer patients for validation. We were able to develop a biomarker signature that consists of just the three gene products ELF5, SCUBE2 and NFIB, measured on RNA level. Compared to Hatzis et al., we achieved a significant improvement in predicting responders and non-responders in the Hatzis et al. validation cohort with an area under the receiver operating characteristics curve of 0.73 [95% CI, 69%—77%]. Moreover, we could confirm the performance of our biomarker on two further independent validation cohorts. The overall performance on all three validation cohorts expressed as area under the receiver operating characteristics curve was 0.75 [95% CI, 70%—80%]. At the clinically relevant classifier’s operation point to optimize the exclusion of non-responders, the biomarker correctly predicts three out of four patients not responding to neoadjuvant taxane-based chemotherapy, independent of the breast cancer subtype. At the same time, the response rate in the group of predicted responders increased to 42% compared to 23% response rate in all patients of the validation cohorts.

The Utility of Oncotype DX for Adjuvant Chemotherapy Treatment Decisions in Estrogen Receptor-positive, Human Epidermal Growth Factor Receptor 2-negative, Node-negative Breast Cancer

Introduction Breast cancer is the most common cancer diagnosis in the UK. Recently, there has been a reduction in breast cancer-specific mortality and recurrence attributed, in part, to the delivery of adjuvant chemotherapy. The National Institute for Health and Care Excellence (NICE) recommends the use of genetic profiling with Oncotype DX (ODX) to guide decisions to offer adjuvant chemotherapy after surgery in intermediate-risk early breast cancer patients. This study aimed to evaluate the utility of ODX testing in routine clinical practice in a National Health Service (NHS) hospital.  Methods Consecutive early breast cancer patients, identified through the multidisciplinary team (MDT) records, treated in our institution over 12 months (October 2017-September 2018) were included. PREDICT and Nottingham prognostic index (NPI) scores (from online clinicopathological recurrence risk tools) were calculated for each patient, and ODX data obtained through Genomic Health, Inc. (Redwood City, California). Patients were divided into two groups, those that underwent ODX testing (ODX group) and those that did not (non-ODX group). Descriptive statistics were used to analyse patient and tumour characteristics. The Gaussian distribution of each data set was assessed using the Anderson-Darling test. For comparisons between patient groups, the non-parametric equivalent of the two-tailed t-test (Mann-Whitney) was used. Dichotomous variables (e.g. chemotherapy decisions) were compared using chi-squared tests. Results One-hundred thirty-three patients (mean age 62 years) treated for 152 early breast cancers, were included in the final analysis. Breast cancers in the ODX group were of greater median tumour size (24 vs 16 mm; P<0.0001) and higher median tumour grade (3 vs 2; P<0.0001). PREDICT scores (3 vs 1, P<0.0001) and NPI scores (3.40 vs 2.30, P<0.0001) for the ODX group were also significantly higher than the non-ODX group. A greater proportion of patients were offered chemotherapy in the ODX group (39.9% vs 6.9%, P<0.001). However, for the PREDICT-calculated intermediate-risk patients, ODX testing resulted in a lower proportion of patients being offered chemotherapy compared to the intermediate-risk patients who were not genetically profiled (54.5% vs 83.3%, P=0.3547), although this result was not statistically significant. Conclusions Patients selected for ODX testing were younger, with significantly higher-grade and larger-sized tumours compared to patients not selected for genetic profiling. ODX testing significantly impacted the delivery of chemotherapy, as the recurrence score generated through ODX testing guided the final decision.

The impact of Oncotype DX breast cancer assay results on clinical practice: a UK experience

BACKGROUND

Genomic tests are increasingly being used by clinicians when considering adjuvant chemotherapy for patients with oestrogen receptor-positive (ER+), human epidermal growth factor 2-negative (HER2-) breast cancer. The Oncotype DX breast recurrence score assay was the first test available in the UK National Health Service. This study looked at how UK clinicians were interpreting Recurrence Scores (RS) in everyday practice.

METHODS

RS, patient and tumour characteristics and adjuvant therapy details were retrospectively collected for 713 patients from 14 UK cancer centres. Risk by RS-pathology-clinical (RSPC) was calculated and compared to the low/intermediate/risk categories, both as originally defined (RS < 18, 18-30 and > 30) and also using redefined boundaries (RS < 11, 11-25 and > 25).

RESULTS

49.8%, 36.2% and 14% of patients were at low (RS < 18), intermediate (RS 18-30) and high (RS > 30) risk of recurrence, respectively. Overall 26.7% received adjuvant chemotherapy. 49.2% of those were RS > 30; 93.3% of patients were RS > 25. Concordance between RS and RSPC improved when intermediate risk was defined as RS 11-25.

CONCLUSIONS

This real-world data demonstrate the value of genomic tests in reducing the use of adjuvant chemotherapy in breast cancer. Incorporating clinical characteristics or RSPC scores gives additional prognostic information which may also aid clinicians' decision making.

Change in therapeutic management after the EndoPredict assay in a prospective decision impact study of Mexican premenopausal breast cancer patients

Objective

To evaluate the change in adjuvant therapeutic decision in a cohort of young women with breast cancer discussed by a multidisciplinary team, before and after EndoPredict testing.

Patients and methods

99 premenopausal women with hormone receptor-positive, HER2-negative, T1-T2, and N0-N1 breast cancer were included. Clinicopathological characteristics were recorded and cases were presented in a multidisciplinary tumor board. Consensual therapeutic decisions before and after EndoPredict results were registered. Medical records were reviewed at six-month follow-up to determine physicians’ adherence to therapeutic recommendations. Pearson chi-square and McNemar’s tests were used to analyze differences between groups and changes in treatment recommendations, respectively.

Results

Median age at diagnosis was 43 years. The most frequent tumor size was pT2 (53.5%) and 27% of patients had 1–3 positive lymph nodes. 46% of patients had a low-risk EPclin result. Nodal status and tumor grade were significantly associated with EPclin result (p < .00001 and p = .0110, respectively), while Ki67 levels and age ≤40 years were not. A change in chemotherapy decision was registered in 19.2% of patients (p = .066), with the greatest impact in de-escalation (9% net reduction). A change in chemotherapy or endocrine therapy regimen was suggested in 19% and 20% of cases, respectively, after EPclin results were available. A significant difference was found in the median EPclin score between patients with a low- vs. high-intensity chemotherapy and endocrine therapy regimen recommendation (p = 0.049 and p = 0.0001, respectively). Tumor board treatment recommendation adherence with the EndoPredict result was 95% and final treatment adherence to EPclin result was 93%.

Conclusions

The EndoPredict test successfully assisted the clinical decision-making process in premenopausal patients, with a clinically significant change in overall decision-making, with the greatest impact seen in chemotherapy reduction, and a high rate of therapeutic adherence.

Prognostic Significance of Tumor Subtypes in Women With Breast Cancer According to Stage: A Population-based Study

OBJECTIVES

The contribution of tumor subtypes (TS) in each stage of breast cancer with the use of contemporary therapies is unclear. The aim of this study was to analyze differences in overall survival (OS) by TS according to stage compared with other factors.

MATERIALS AND METHODS

We evaluated women with breast cancer diagnosed between 2010 and 2013 with known estrogen receptor and progesterone receptor (together hormone receptor [HR]) status and human epidermal growth factor receptor 2 (HER2) status reported to the SEER program. Patient characteristics were compared between TS. Univariate and multivariate analyses were performed to determine the effect of each variable on OS. Breast cancer-specific survival was a secondary endpoint.

RESULTS

We included 166,054 patients. TS distribution was: 72.5% HR-positive/HER2-negative, 10.8% HR-positive/HER2-positive, 4.8% HR-negative/HER2-positive, and 12% triple-negative (TN). Patients with HR-positive/HER2-negative tumors were older, had a lower grade and presented with the earlier stage (all P<0.0001). OS was significantly different according to TS in each stage (Pinteraction<0.0001). HR-positive/HER2-negative had the best OS in stage I (3-year OS, 97.2%). In contrast, HR-positive/HER2-positive had the best 3-year OS in stage II (94.5%), stage III (87.8%), and stage IV (54.8%). There was a 40.1% difference in OS at 3 years in stage IV between TN and HR-positive/HER2-positive. Multivariate analysis adjusted for age, race, grade, histology, and marital status confirmed these results.

CONCLUSIONS

Although HR-positive/HER2-negative tumors had better clinicopathologic features, the HR-positive/HER2-positive group had the best OS in most stages. OS was significantly different by TS in each of the 4 stages and these results remained significant in the multivariate model.

Implications of the 21-gene recurrence score assay (Oncotype DX) on adjuvant treatment decisions in ER-positive early-stage breast cancer patients: experience of Kuwait Cancer Control Center

BACKGROUND

The Oncotype DX is a quantitative assay of the expression of 16 tumor-related genes and 5 reference genes that predicts the potential of adjuvant chemotherapy benefit in estrogen receptor (ER)-positive early breast cancer patients. The study aims to evaluate the impact of Oncotype DX as a tool for adjuvant treatment decision of ER-positive, HER2-negative, N0/N1 early-stage breast cancer patients and to determine which clinicopathological criteria derived the greatest advantage.

RESULTS

A hundred patients at a median age of 50 years were included. TNM stage distribution was 34, 63, and 3 patients for stages I, II, and IIIA respectively. Fifty-four patients had luminal A and 46 had luminal B tumors. The recurrence score (RS) results were low, intermediate, and high risk in 54, 34, and 12 patients respectively. Before the test results, adjuvant chemoendocrine therapy (CET) was recommended for 46 patients while 54 were advised for endocrine therapy (ET). After getting the test results, 25 patients received CET (1, 12, and12 patients in the low-, intermediate-, and high-risk groups respectively) and 75 received ET. Treatment change was documented in 37 patients (8 patients from ET to CET and 29 from CET to ET; p = 0.001, McNemar test). Treatment change was significant among patients ≤ 50 years, luminal B tumors, stage II and IIIA disease, and node-positive disease.

CONCLUSION

Oncotype DX testing resulted in significant changes in the adjuvant treatment decisions in ER-positive, HER2-negative early breast cancer particularly in the case of young, luminal B, N1, and stage II-IIIA disease.

A preliminary report of head-to-head comparison of 18-gene-based clinical-genomic model and oncotype DX 21-gene assay for predicting recurrence of early-stage breast cancer

Background

The information of Oncotype DX applied in Asian breast cancer patients is limited. A recurrence index for distant recurrence (RI-DR) has been developed for early-stage breast cancer (EBC) from tumor samples in Chinese patients. In this study, we compared the prognostic performance of the Oncotype DX (ODx) recurrence score (RS) with the RI-DR for any recurrence risk type.

Materials and methods

One hundred thirty-eight (138) patients with hormone receptor-positive and human epidermal growth factor receptor 2-negative EBC who were previously tested with ODx were included for testing with the RI-DR. The cutoff score to partition the low- and high-risk patients was 26 for RS and 36 for RI-DR. The primary endpoint was recurrence-free survival (RFS).

Results

The concordance between the RI-DR and RS was 83% in N0 patients and 81% in node-positive patients when the RS score cutoff was set at 26. With a median follow-up interval of 36.8 months, the 4-year RFS for the high- and low-risk groups categorized by the RS were 61.9% and 95.0%, respectively (hazard ratio: 10.6, 95.0% confidence interval [CI]: 1.8–62.9). The 4-year RFS in the high- and low-risk groups categorized by the RI-DR were 72.6% and 98.5%, respectively (hazard ratio: 18.9, 95% CI: 1.8–138.8).

Conclusion

This paper illustrated the performance of RI-DR and ODx RS in breast cancer women in Taiwan. There was high concordance between the RI-DR and RS. The RI-DR is not inferior to the RS in predicting RFS in EBC patients. This study will fill the gap between the current and best practice in Chinese patients.

Trend and survival benefit of Oncotype DX use among female hormone receptor-positive breast cancer patients in 17 SEER registries, 2004-2015

PURPOSE

To examine (1) the trend and associated factors of Oncotype DX (ODX) use among hormone receptor-positive (HR+) breast cancer (BC) patients in 2004-2015; (2) the trend of reported chemotherapy by Recurrence Score (RS); and (3) the survival differences associated with ODX use.

METHODS

ODX data from Genomic Health Inc. were linked with 17 SEER registries data. HR + BC cases with lymph node negative (N0) or 1-3 positive LNs (N1) from 2004-2015 were analyzed. The Cochrane-Armitage trend test, logistic regression, Kaplan-Meier survival curve, and stratified Cox model were performed. Survival analysis was restricted to HR+/HER2- patients from 2010 to 2014, matched on propensity score.

RESULTS

ODX use increased substantially from 2004 to 2015 (N0: 2.0% to 42.7%; N1: 0.3% to 27.9%). Non-Hispanic black and Medicaid insured patients had lower odds of receiving ODX. N0 patients with moderately differentiated or 2.1-5.0 cm tumor and N1 patients with well-differentiated or < 2.0 cm tumor had higher odds of using ODX. The reported chemotherapy use decreased significantly with low and intermediate RS, and increased for high RS among N0 patients. ODX use was associated with better breast cancer-specific survival [hazard ratio (95% CI) N0 1.96 (1.60-2.41), N1 1.90 (1.42-2.54)] and overall survival [N0 2.06 (1.83-2.31), N1 1.72 (1.42-2.09)], especially in the first 36 months.

CONCLUSION

ODX use has increased significantly since 2004, nonetheless disparities remain, especially for racial/ethnic minorities and Medicaid insured patients. Administering chemotherapy based on ODX results has been improved among N0 patients. Patients receiving ODX had better survival than those not.

Decision-making of Adjuvant Chemotherapy for Breast Cancer Patients with Discordant Risk Classifications between Clinical-Pathological Factors and 21-gene Recurrence Score

Background: Clinical-pathological factors and 21-gene recurrence score (RS) influence adjuvant chemotherapy (ACT) decision for early breast cancer patients. We investigated the decision-making of ACT in patients with discordant risk classifications of clinical-pathological factors and RS.

Methods: Patients with hormonal receptor (HR)+/ human epidermal growth factor receptor 2 (HER2)-, early breast cancer, who underwent 21-gene RS testing were identified from Ruijin Hospital (RJBC) and the Surveillance, Epidemiology, and End Results (SEER) database. According to Adjuvant! Online and RS (≤25 or >25), discordant risk classifications were defined as: clinical low-risk/ RS high-risk (C-low/ RS-high) and clinical high-risk/ RS low-risk (C-high/RS-low). McNemar's test was used to assess the changes between pre- and post-RS recommendations. Breast cancer-specific survival (BCSS) was estimated using the Kaplan-Meier methods.

Results: Among 727 RJBC patients, the C-low/RS-high group and the C-high/RS-low group represented 19.7% and 21.3% of the cohort. After receiving 21-gene RS results, treatment recommendations were changed for 22.1% patients with discordant risk classifications: ACT rate increased from 41.9% to 75.5% in the C-low/RS-high group and decreased from 63.9% to 60.0% in the C-high/RS-low group. Among 2958 patients from the SEER cohort, 18.4% of the C-high/RS-low group and 59.2% of the C-low/RS-high group received ACT. There was no significant difference in the estimated 3-year BCSS between ACT or not among the C-low/RS-high group (p=0.708) and the C-high/RS-low groups (p=0.391).

Conclusion: For patients with discordant risk classifications, physicians were apt to adopt the 21-gene RS rather than routine clinical-pathological factors to guide ACT selection.

Multicentric breast cancer with heterogeneous histopathology: a multidisciplinary review

Multiple synchronous (multifocal or multicentric) ipsilateral breast cancers with heterogeneous histopathology are a rare clinical occurrence, however, their incidence is increasing due to the use of MRI for breast cancer screening and staging. Some studies have demonstrated poorer clinical outcomes for this pattern of breast cancer, but there is no evidence to guide clinical practice. In this multidisciplinary review, we reflect on pathology and molecular characteristics, imaging findings, surgical management including conservation and reconstructive options and approach to the axilla, and the role of chemotherapy and radiotherapy. Multidisciplinary discussions appear decisive in planning an appropriate surgical choice and defining the correct systemic treatment tailored to each clinical condition.

Metastatic Conditioning of Myeloid Cells at a Subcutaneous Synthetic Niche Reflects Disease Progression and Predicts Therapeutic Outcomes

Monitoring metastatic events in distal tissues is challenged by their sporadic occurrence in obscure and inaccessible locations within these vital organs. A synthetic biomaterial scaffold can function as a synthetic metastatic niche to reveal the nature of these distal sites. These implanted scaffolds promote tissue ingrowth, which upon cancer initiation is transformed into a metastatic niche that captures aggressive circulating tumor cells. We hypothesized that immune cell phenotypes at synthetic niches reflect the immunosuppressive conditioning within a host that contributes to metastatic cell recruitment and can identify disease progression and response to therapy. We analyzed the expression of 632 immune-centric genes in tissue biopsied from implants at weekly intervals following inoculation. Specific immune populations within implants were then analyzed by single-cell RNA-seq. Dynamic gene expression profiles in innate cells, such as myeloid-derived suppressor cells, macrophages, and dendritic cells, suggest the development of an immunosuppressive microenvironment. These dynamics in immune phenotypes at implants was analogous to that in the diseased lung and had distinct dynamics compared with blood leukocytes. Following a therapeutic excision of the primary tumor, longitudinal tracking of immune phenotypes at the implant in individual mice showed an initial response to therapy, which over time differentiated recurrence versus survival. Collectively, the microenvironment at the synthetic niche acts as a sentinel by reflecting both progression and regression of disease. SIGNIFICANCE: Immune dynamics at biomaterial implants, functioning as a synthetic metastatic niche, provides unique information that correlates with disease progression. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/3/602/F1.large.jpg.See related commentary by Wolf and Elisseeff, p. 377.

Expected Monetary Impact of Oncotype DX Score-Concordant Systemic Breast Cancer Therapy Based on the TAILORx Trial

BACKGROUND

TAILORx demonstrated that women with node-negative, hormone receptor-positive, HER2-negative breast cancers and Oncotype DX recurrence scores (RS) of 0-25 had similar 9-year outcomes with endocrine vs chemo-endocrine therapy; evidence for women aged 50 years and younger and RS 16-25 was less clear. We estimated how expected changes in practice following the trial might affect US costs in the initial 12 months of care (initial costs).

METHODS

Data from Surveillance, Epidemiology, and End Results (SEER), SEER-Medicare, and SEER-Genomic Health Inc datasets were used to estimate Oncotype DX testing and chemotherapy rates and mean initial costs pre- and post-TAILORx (in 2018 dollars), assuming all women received Oncotype DX testing and score-suggested therapy posttrial. Sensitivity analyses tested the impact on costs of assumptions about compliance with testing and score-suggested treatment and estimation methods.

RESULTS

Pretrial mean initial costs were $2.816 billion. Posttrial, Oncotype DX testing costs were projected to increase from $115 to $231 million and chemotherapy use to decrease from 25% to 17%, resulting in initial care costs of $2.766 billion, or a net savings of $49 million (1.8% decrease). A small net savings was seen under most assumptions. The one exception was if all women aged 50 years and younger with tumors with RS 16-25 elected to receive chemotherapy, initial care costs could increase by $105 million (4% increase).

CONCLUSIONS

Personalizing breast cancer treatment based on tumor genetic profiles could result in small cost decreases in the initial 12 months of care. Studies are needed to evaluate the long-term costs and nonmonetary benefits of personalized cancer care.

Current immunoassay methods and their applications to clinically used biomarkers of breast cancer

Breast cancer is the leading cause of cancer-related mortality worldwide, with a higher incidence in developed countries. The biomarkers for breast cancer such as estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, CA (cancer antigen) 15-3, CA 27.29, and carcinoembryonic antigen have been recommended for use in the laboratory based on the guidelines of American and European societies. Immunoassays have been frequently and consistently used to detect these clinically established biomarkers of breast cancer. Despite the higher accessibility of serum biomarkers, including CA 15-3, CA 27.29, and CEA, compared to tissue markers, variations in immunoassays affect their standardization and clinical utility. When reviewing the immunoassays used to detect these serum markers, we found that the most frequently used immunoassay was enzyme-linked immunosorbent assay, followed by electrochemiluminescent immunoassay, and then chemiluminescence immunoassay for CA 15-3 and CEA. Meanwhile, the chemiluminescence immunoassay was the most common technique for CA27.29. The electrochemiluminescent immunoassay and monoclonal fluorometric assay have become the preferred methods in 2010-2019 compared to 2000-2009. Analytical and clinical performance factors such as sensitivity, specificity, detection limit, hazard risk to laboratory personnel, speed, and economic feasibility influenced these changes in user preference. When using the immunoassays, there should be a comprehensive understanding of the principles, advantages, vulnerability, and precautions for interpretation. In the future, a combination of immunological biomarkers and genetic platforms will benefit patients with breast cancer by facilitating prognosis prediction and guiding therapeutic intervention.

Genomic profiling in oncology clinical practice

The development of high-throughput technologies such as next-generation sequencing for DNA sequencing together with the decrease in their cost has led to the progressive introduction of genomic profiling in our daily practice in oncology. Nowadays, genomic profiling is part of genetic counseling, cancer diagnosis, molecular characterization, and as a biomarker of prognosis and response to treatment. Furthermore, germline or somatic genomic characterization of the tumor may provide new treatment opportunities for patients with cancer. In this review, we will summarize the clinical applications and limitations of genomic profiling in oncology clinical practice, focusing on next-generation sequencing.

miRNAs as Biomarkers in Disease: Latest Findings Regarding Their Role in Diagnosis and Prognosis

MicroRNAs (miRNAs) represent a class of small, non-coding RNAs with the main roles of regulating mRNA through its degradation and adjusting protein levels. In recent years, extraordinary progress has been made in terms of identifying the origin and exact functions of miRNA, focusing on their potential use in both the research and the clinical field. This review aims at improving the current understanding of these molecules and their applicability in the medical field. A thorough analysis of the literature consulting resources available in online databases such as NCBI, PubMed, Medline, ScienceDirect, and UpToDate was performed. There is promising evidence that in spite of the lack of standardized protocols regarding the use of miRNAs in current clinical practice, they constitute a reliable tool for future use. These molecules meet most of the required criteria for being an ideal biomarker, such as accessibility, high specificity, and sensitivity. Despite present limitations, miRNAs as biomarkers for various conditions remain an impressive research field. As current techniques evolve, we anticipate that miRNAs will become a routine approach in the development of personalized patient profiles, thus permitting more specific therapeutic interventions.

BAD sensitizes breast cancer cells to docetaxel with increased mitotic arrest and necroptosis

Breast cancer patients are commonly treated with taxane (e.g. docetaxel) chemotherapy, despite poor outcomes and eventual disease relapse. We previously identified the Bcl-2-associated death promoter (BAD) as a prognostic indicator of good outcome in taxane-treated breast cancer patients. We also demonstrated that BAD expression in human breast carcinoma cells generated larger tumors in mouse xenograft models. These paradoxical results suggest that BAD-expressing tumors are differentially sensitive to taxane treatment. We validated this here and show that docetaxel therapy preferentially reduced growth of BAD-expressing xenograft tumors. We next explored the cellular mechanism whereby BAD sensitizes cells to docetaxel. Taxanes are microtubule inhibiting agents that cause cell cycle arrest in mitosis whereupon the cells either die in mitosis or aberrantly exit (mitotic slippage) and survive as polyploid cells. In response to docetaxel, BAD-expressing cells had lengthened mitotic arrest with a higher proportion of cells undergoing death in mitosis with decreased mitotic slippage. Death in mitosis was non-apoptotic and not dependent on Bcl-XL interaction or caspase activation. Instead, cell death was necroptotic, and dependent on ROS. These results suggest that BAD is prognostic for favourable outcome in response to taxane chemotherapy by enhancing necroptotic cell death and inhibiting the production of potentially chemoresistant polyploid cells.

Assessment of the Prognostic Staging System of American Joint Committee on Cancer 8th Edition for Breast Cancer: Comparisons with the Conventional Anatomic Staging System

Purpose

The 8th edition of the American Joint Committee on Cancer (AJCC) staging manual introduced a new prognostic staging system for breast cancer. This study aimed to evaluate the changes in staging distribution and predictive power of the new staging system.

Methods

Of the 12,275 patients with breast cancer identified from the Severance Breast Cancer Registry who underwent surgery between 1978 and 2016, 12,125 patients met the inclusion criteria.

Results

In both the 7th and 8th staging systems, stage I patients constituted the largest proportion (38.2% and 48.4%). Migration from the 7th to 8th edition of the AJCC manual resulted in a decrease in stage II population and an increase in stage I and III populations. A total of 1,293 (15.4%) patients were upstaged, and 1,201 (14.3%) were downstaged. Downstaged patients had better recurrence-free and overall survival (p < 0.001). Pathologic complete response after neoadjuvant therapy showed good prognosis as p stage 0, and yp stages I and III showed poorer outcomes than the same p stage (p < 0.001).

Conclusions

Staging migrations are common in early breast cancer under the prognostic staging system. The prognostic staging system of the 8th edition of the AJCC manual discriminates survival outcomes better than the anatomical staging system of the 7th edition of the AJCC manual.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Case-Based Review and Clinical Guidance on the Use of Genomic Assays for Early-Stage Breast Cancer: Breast Cancer Therapy Expert Group (BCTEG)

In addition to classical clinicopathologic factors, such as hormone receptor positivity, human epidermal growth factor receptor 2 (HER2) status, and tumor size, grade, and lymph node status, a number of commercially available genomic tests may be used to help inform treatment decisions for early breast cancer patients. Although these tests improve our understanding of breast cancer and help to individualize treatment decisions, clinicians face challenges when deciding on the most appropriate test to order, and the advantages, if any, of one test over another. The Breast Cancer Therapy Expert Group (BCTEG) recently convened a roundtable meeting to discuss issues surrounding the use of genomic testing in early breast cancer, with the goal of providing practical guidance on the use of these tests by the community oncologist, for whom breast cancer may be only one of many tumor types they treat. The group recognizes that genomic testing can provide important prognostic (eg, risk for recurrence), and in some cases predictive, information (eg, benefit of chemotherapy, or extended adjuvant endocrine therapy), which can be used to help guide treatment decisions in breast cancer. The available tests differ in the types of information they provide, and in the patient populations and clinical trials that were conducted to validate them. We summarize the discussion of the BCTEG on this topic, and we also consider several patient cases and clinical scenarios in which genomic testing may, or may not, be useful to guide treatment decisions for the practicing community oncologist.

Circulating Tumor Cells in Breast Cancer

With active screening for early detection and advancements in treatment, there has been a significant decrease in mortality from breast cancer. However, a significant proportion of patients with non-metastatic breast cancer at time of diagnosis will relapse. Therefore, it is suggested that the dissemination of bloodstream tumor cells (circulating tumor cells, CTCs) undetectable by currently available diagnostic tools occurs during the early stages of breast cancer progression, and may be the potential source of micrometastases responsible for treatment failures. Here, we review the clinical significance of CTCs, as detected by the FDA-approved CellSearch^® System, in both metastatic and non-metastatic breast cancer patients. Studies so far suggest that CTCs are prognostic of poorer outcomes in breast cancer patients; however, there is currently insufficient data to support use of CTC data to guide treatment. Therefore, there are ongoing studies to evaluate the utility of assessing CTC phenotypes to develop personalized breast cancer treatment, which will be reviewed in this chapter.

Correlation between MR Image-Based Radiomics Features and Risk Scores Associated with Gene Expression Profiles in Breast Cancer

Purpose

To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores.

Materials and Methods

We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models.

Results

The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008–0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171.

Conclusion

Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

Sex Disparity Observed for Oncotype DX Breast Recurrence Score in Predicting Mortality Among Patients with Early Stage ER-Positive Breast Cancer

PURPOSE

Prognostic value of Oncotype DX Breast Recurrence Score (RS) in male patients with breast cancer is understudied. We evaluated associations of RS with overall mortality in male patients with breast cancer and compared it with female counterparts.

EXPERIMENTAL DESIGN

With a cohort of 848 male and 110,898 female patients with breast cancer identified from the National Cancer Database (2010-2014), we estimated HRs and 95% confidence intervals (CI) for overall mortality associated with RS using Cox regression models. RS was evaluated continuously, as well as by categorization following respective traditional (≤17, 18-30, and ≥31) and TAILORx (≤10, 11-25, and ≥26) cutoffs.

RESULTS

RS was positively associated with mortality in male patients (HR = 1.13; 95% CI, 1.02-1.26 per unit RS increment) up to RS > 21, after which the risk plateaued. Among female patients, mortality began to increase with RS only when RS > 23 (HR = 1.02; 95% CI, 1.01-1.02 per unit of RS increment). The intermediate- (HR = 5.37; 95% CI, 1.79-16.11) and high-risk diseases (HR = 4.28; 95% CI, 1.22-14.97) defined by TAILORx, but not traditional cutoffs established for female patients, were associated with elevated mortality risk in men even after adjustment for demographic, clinical characteristics, and treatments, except chemotherapy.

CONCLUSIONS

RS is associated with mortality in male patients with breast cancer at a much lower threshold than that for female patients. Studies are needed to establish specific guidelines for RS thresholds for male patients with breast cancer.

Hormone receptor and HER2 assessment in breast carcinoma metastatic to bone: A comparison between FNA cell blocks and decalcified core needle biopsies

BACKGROUND

Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) guide the clinical management of breast cancer metastases. Decalcification of bone core needle biopsies (CNBs) can affect IHC. In the current study, the authors sought to define whether fine-needle aspiration (FNA) would be a better alternative to CNB for reliable IHC.

METHODS

Patients with breast cancer metastases to bone that were sampled by both CNB and FNA were selected. ER, PR, and HER2 were performed in FNA cell blocks (FNA-CBs) and concurrent decalcified CNBs. Discrepancies were classified as minor when there was a difference of up to 30% nuclear staining in IHC for ER and PR between paired samples and as major when a clinically relevant change was observed (ie, positive vs negative). Quantitative reverse transcriptase-polymerase chain reaction of ESR1 messenger RNA levels was performed on FNA/CNB pairs with discrepancies for ER IHC. IHC status of the primary breast carcinoma was recorded.

RESULTS

Concordance rates for ER, PR, and HER2 were 89%, 67%, and 93%, respectively, between FNA-CB and CNB pairs from 27 patients. Major discrepancies were noted in approximately 11% of FNA/CNB pairs for ER IHC and in 33% of FNA/CNB pairs for PR. ESR1 messenger RNA levels of FNA/CNB matched samples were similar and did not explain the differences in ER IHC expression in the majority of cases. Two of 27 FNA/CNB pairs had different results for HER2 IHC that changed from negative on CNB to equivocal (2+) on FNA-CB. Both cases had prior HER2 amplification by fluorescence in situ hybridization.

CONCLUSIONS

FNA-CB and CNB appear to constitute acceptable methods for the assessment of ER, PR, and HER2 for clinical decision making.