Systematic review of the clinical and economic value of gene expression profiles for invasive early breast cancer available in Europe

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.

In ER-Positive, HER2-Negative Breast Cancers, HER2 mRNA Levels Correlate Better with Clinicopathologic Features and Oncotype DX Recurrence Score than HER2 Immunohistochemistry

With the approval of trastuzumab deruxtecan for treating advanced human epidermal growth factor receptor-2 (HER2) low breast cancer (BC), it has become increasingly important to develop more accurate and reliable methods to identify HER2-low BC. In addition, HER2 immunohistochemistry (IHC) has limitations for quantification of HER2. We explored the relationship between HER2 IHC and mRNA levels and evaluated whether HER2 IHC scores and mRNA levels are associated with clinicopathologic features and Oncotype DX Recurrence Score (RS) in estrogen receptor (ER)-positive, HER2-negative BCs. A total of 750 BCs sent for Oncotype DX (ODX) testing were included in this study, and 559 with HER2 mRNA levels were available. There were no statistically significant differences between HER2 0 and HER2-low BC in clinicopathologic variables or ODX RS using HER2 IHC. There was a significant difference in median HER2 mRNA values between HER2 0 and HER2-low (8.7 vs 9.3, P < .001); however, the HER2 mRNA distribution had substantial overlap between these 2 groups with a suboptimal area under the receiver operating characteristic curve (area under the receiver operating characteristic curve = 0.68). A HER2 mRNA value of 9.2 was generated as the optimal cutoff for distinguishing HER2 0 and HER2-low BC. Comparing ER+ BCs with HER2 mRNA high (>9.2) and low (≤9.2) revealed a statistically significant difference in most clinicopathologic variables and ODX RS. From this large cohort of ER-positive, HER2-negative BC, our results demonstrated that HER2 mRNA levels correlated better with clinicopathologic features and recurrence risk as assessed by ODX RS than HER2 IHC scores. Our findings suggest that HER2 mRNA-detecting methods could potentially serve as a quantitative and reliable method for identifying a biologically meaningful group of HER2-low BC. Further study is needed to determine whether HER2 mRNA levels could be more reliable than IHC for identifying which patients will be most likely to benefit from trastuzumab deruxtecan.

A novel machine learning prediction model for metastasis in breast cancer

BACKGROUND

Breast cancer (BC) metastasis is the common cause of high mortality. Conventional prognostic criteria cannot accurately predict the BC metastasis risk. The machine learning technologies can overcome the disadvantage of conventional models.

AIM

We developed a model to predict BC metastasis using the random survival forest (RSF) method.

METHODS

Based on demographic data and routine clinical data, we used RSF-recursive feature elimination to identify the predictive variables and developed a model to predict metastasis using RSF method. The area under the receiver operating characteristic curve (AUROC) and Kaplan-Meier survival (KM) analyses were plotted to validate the predictive effect when C-index was plotted to assess the discrimination and Brier scores was plotted to assess the calibration of the predictive model.

RESULTS

We developed a metastasis prediction model comprising three variables (pathological stage, aspartate aminotransferase, and neutrophil count) selected by RSF-recursive feature elimination. The model was reliable and stable when assessed by the AUROC (0.932 in training set and 0.905 in validation set) and KM survival analyses (p < .0001). The C-indexes (0.959) and Brier score (0.097) also validated the good predictive ability of this model.

CONCLUSIONS

This model relies on routine data and examination indicators in real-time clinical practice and exhibits an accurate prediction performance without increasing the cost for patients. Using this model, clinicians can facilitate risk communication and provide precise and efficient individualized therapy to patients with breast cancer.

Targeting the Oxytocin Receptor for Breast Cancer Management: A Niche for Peptide Tracers

Breast cancer is a leading cause of death in women, and its management highly depends on early disease diagnosis and monitoring. This remains challenging due to breast cancer's heterogeneity and a scarcity of specific biomarkers that could predict responses to therapy and enable personalized treatment. This Perspective describes the diagnostic landscape for breast cancer management, molecular strategies targeting receptors overexpressed in tumors, the theranostic potential of the oxytocin receptor (OTR) as an emerging breast cancer target, and the development of OTR-specific optical and nuclear tracers to study, visualize, and treat tumors. A special focus is on the chemistry and pharmacology underpinning OTR tracer development, preclinical in vitro and in vivo studies, challenges, and future directions. The use of peptide-based tracers targeting upregulated receptors in cancer is a highly promising strategy complementing current diagnostics and therapies and providing new opportunities to improve cancer management and patient survival.

Biomarkers predictive of a response to extended endocrine therapy in breast cancer: a systematic review and meta-analysis

PURPOSE

Extension of adjuvant endocrine therapy beyond five years confers only modest survival benefit in breast cancer patients and carries risk of toxicities. This systematic review investigates the role of biomarker tests in predicting the clinical response to an extension of endocrine therapy.

METHODS

We searched Ovid MEDLINE, Ovid Embase, Global Index Medicus, and the Cochrane Central Register of Controlled Trials using an iterative approach to identify full-text articles related to breast cancer, endocrine therapy, and biomarkers.

RESULTS

Of the 1,217 unique reports identified, five studies were deemed eligible. Four investigated the Breast Cancer Index (BCI) assay in three distinct study populations. These studies consistently showed that BCI score was predictive of response to extended endocrine therapy among 1,946 combined patients, who were predominately non-Hispanic white and postmenopausal.

CONCLUSIONS

Evidence in the setting of predictive tests for extended endocrine therapy is sparse. Most relevant studies investigated the use of BCI, but these study populations were largely restricted to a single age, race, and ethnicity group. Future studies should evaluate a variety of biomarkers in diverse populations. Without sufficient evidence, physicians and patients face a difficult decision in balancing the benefits and risks of endocrine therapy extension.

American Radium Society Appropriate Use Criteria Postmastectomy Radiation Therapy: Executive Summary of Clinical Topics

PURPOSE

To conduct an appropriate use criteria expert panel update on clinical topics relevant to current clinical practice regarding postmastectomy radiation therapy (PMRT).

METHODS AND MATERIALS

An analysis of the medical literature from peer-reviewed journals was conducted from May 4, 2010 to May 4, 2022 using the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines to search the PubMed database to retrieve a comprehensive set of relevant articles. A well-established methodology (modified Delphi) was used by the expert panel to rate the appropriate use of procedures.

RESULTS

Evidence for key questions in PMRT regarding benefit in special populations and technical considerations for delivery was examined and described. Risk factors for local-regional recurrence in patients with intermediate-risk disease that indicate benefit of PMRT include molecular subtype, age, clinical stage, and pathologic response to neoadjuvant chemotherapy. Use of hypofractionated radiation in PMRT has been examined in several recent randomized trials and is under investigation for patients with breast reconstruction. The use of bolus varies significantly by practice region and has limited evidence for routine use. Adverse effects occurred with both PMRT preimplant and postimplant exchange in 2-staged breast reconstruction.

CONCLUSIONS

Most patients with even limited nodal involvement will likely benefit from PMRT with significant reduction in local-regional recurrence and potential survival. Patients with initial clinical stage III disease and/or any residual disease after neoadjuvant chemotherapy should be strongly considered for PMRT. Growing evidence supports the use of hypofractionated radiation for PMRT with equivalent efficacy and decreased acute side effects, but additional evidence is needed for special populations. There is limited evidence to support routine use of bolus in all patients. Timing of PMRT regarding completion of 2-staged breast reconstruction requires a discussion of increased risks with radiation postimplant exchange compared with increased risk of failure of reconstruction or surgical complications with radiation preimplant exchange.

Ten-year update: NRG Oncology/National Surgical Adjuvant Breast and Bowel Project B-42 randomized trial: extended letrozole therapy in early-stage breast cancer

BACKGROUND

The National Surgical Adjuvant Breast and Bowel Project B-42 trial evaluated extended letrozole therapy (ELT) in postmenopausal breast cancer patients who were disease free after 5 years of aromatase inhibitor (AI)-based therapy. Seven-year results demonstrated a nonstatistically significant trend in disease-free survival (DFS) in favor of ELT. We present 10-year outcome results.

METHODS

In this double-blind, phase III trial, patients with stage I-IIIA hormone receptor-positive breast cancer, disease free after 5 years of an AI or tamoxifen followed by an AI, were randomly assigned to 5 years of letrozole or placebo. Primary endpoint was DFS, defined as time from random assignment to breast cancer recurrence, second primary malignancy, or death. All statistical tests are 2-sided.

RESULTS

Between September 2006 and January 2010, 3966 patients were randomly assigned (letrozole: 1983; placebo: 1983). Median follow-up time for 3923 patients included in efficacy analyses was 10.3 years. There was statistically significant improvement in DFS in favor of letrozole compared with placebo (hazard ratio [HR] = 0.85, 95% confidence interval [CI] = 0.74 to 0.96; P  = .01; 10-year DFS: placebo = 72.6%, letrozole = 75.9%, absolute difference = 3.3%). There was no difference in the effect of letrozole on overall survival (HR = 0.97, 95% CI = 0.82 to 1.15; P  = .74). Letrozole statistically significantly reduced breast cancer-free interval events (HR = 0.75, 95% CI = 0.62 to 0.91; P = .003; absolute difference in cumulative incidence = 2.7%) and distant recurrences (HR = 0.72, 95% CI = 0.55 to 0.92; P = .01; absolute difference = 1.8%). The rates of osteoporotic fractures and arterial thrombotic events did not differ between treatment groups.

CONCLUSIONS

The beneficial effect of ELT on DFS persisted at 10 years. Letrozole also improved breast cancer-free interval and distant recurrences without improving overall survival. Careful assessment of potential risks and benefits is necessary for selecting appropriate candidates for ELT.

The mutational landscape of a US Midwestern breast cancer cohort reveals subtype-specific cancer drivers and prognostic markers

BACKGROUND

Female breast cancer remains the second leading cause of cancer-related death in the USA. The heterogeneity in the tumor morphology across the cohort and within patients can lead to unpredictable therapy resistance, metastasis, and clinical outcome. Hence, supplementing classic pathological markers with intrinsic tumor molecular markers can help identify novel molecular subtypes and the discovery of actionable biomarkers.

METHODS

We conducted a large multi-institutional genomic analysis of paired normal and tumor samples from breast cancer patients to profile the complex genomic architecture of breast tumors. Long-term patient follow-up, therapeutic regimens, and treatment response for this cohort are documented using the Breast Cancer Collaborative Registry. The majority of the patients in this study were at tumor stage 1 (51.4%) and stage 2 (36.3%) at the time of diagnosis. Whole-exome sequencing data from 554 patients were used for mutational profiling and identifying cancer drivers.

RESULTS

We identified 54 tumors having at least 1000 mutations and 185 tumors with less than 100 mutations. Tumor mutational burden varied across the classified subtypes, and the top ten mutated genes include MUC4, MUC16, PIK3CA, TTN, TP53, NBPF10, NBPF1, CDC27, AHNAK2, and MUC2. Patients were classified based on seven biological and tumor-specific parameters, including grade, stage, hormone receptor status, histological subtype, Ki67 expression, lymph node status, race, and mutational profiles compared across different subtypes. Mutual exclusion of mutations in PIK3CA and TP53 was pronounced across different tumor grades. Cancer drivers specific to each subtype include TP53, PIK3CA, CDC27, CDH1, STK39, CBFB, MAP3K1, and GATA3, and mutations associated with patient survival were identified in our cohort.

CONCLUSIONS

This extensive study has revealed tumor burden, driver genes, co-occurrence, mutual exclusivity, and survival effects of mutations on a US Midwestern breast cancer cohort, paving the way for developing personalized therapeutic strategies.

PROCURE European consensus on breast cancer multigene signatures in early breast cancer management

Breast cancer multigene signatures (BCMS) have changed how patients with early-stage breast cancer (eBC) are managed, as they provide prognostic information and can be used to select patients who may avoid adjuvant chemotherapy. Clinical guidelines make recommendations on the use of BCMS; however, little is known on the current use of BCMS in clinical practice. We conduct a two-round Delphi survey to enquire about current use and perceived utility for specific patient profiles, and unmet needs of BCMS. Overall, 133 panellists experienced in breast cancer across 11 European countries have participated, most using BCMS either routinely (66.2%) or in selected cases (27.1%). Our results show that BCMS are mainly used to assess the risk of recurrence and to select patients for adjuvant chemotherapy; notably, no consensus has been reached on the lack of utility of BCMS for selecting the type of chemotherapy to administer. Also, there are discrepancies between the recommended and current use of BCMS in clinical practice, with use in certain patient profiles for which there is no supporting evidence. Our study suggests that physician education initiatives are needed to ensure the correct use and interpretation of BCMS to, ultimately, improve management of patients with eBC.

The Rochester Modified Magee Algorithm (RoMMa): An Outcomes Based Strategy for Clinical Risk-Assessment and Risk-Stratification in ER Positive, HER2 Negative Breast Cancer Patients Being Considered for Oncotype DX® Testing

INTRODUCTION

Multigene genomic profiling has become the standard of care in the clinical risk-assessment and risk-stratification of ER⁺, HER2^- breast cancer (BC) patients, with Oncotype DX^® (ODX) emerging as the genomic profile test with the most support from the international community. The current state of the health care economy demands that cost-efficiency and access to testing must be considered when evaluating the clinical utility of multigene profile tests such as ODX. Several studies have suggested that certain lower risk patients can be identified more cost-efficiently than simply reflexing all ER⁺, HER2^- BC patients to ODX testing. The Magee equations^TM use standard histopathologic data in a set of multivariable models to estimate the ODX recurrence score. Our group published the first outcome data in 2019 on the Magee equations^TM, using a modification of the Magee equations^TM combined with an algorithmic approach-the Rochester Modified Magee algorithm (RoMMa). There has since been limited published outcome data on the Magee equations^TM. We present additional outcome data, with considerations of the TAILORx risk-stratification recommendations.

METHODS

355 patients with an ODX recurrence score, and at least five years of follow-up or a BC recurrence were included in the study. All patients received either Tamoxifen or an aromatase inhibitor. None of the patients received adjuvant systemic chemotherapy.

RESULTS

There was no significant difference in the risk of recurrence in similar risk categories (very low risk, low risk, and high risk) between the average Modified Magee score and ODX recurrence score with the chi-square test of independence (p > 0.05) or log-rank test (p > 0.05). Using the RoMMa, we estimate that at least 17% of individuals can safely avoid ODX testing.

CONCLUSION

Our study further reinforces that BC patients can be confidently stratified into lower and higher-risk recurrence groups using the Magee equations^TM. The RoMMa can be helpful in the initial clinical risk-assessment and risk-stratification of BC patients, providing increased opportunities for cost savings in the health care system, and for clinical risk-assessment and risk-stratification in less-developed geographies where multigene testing might not be available.

Cost-effectiveness analysis of Oncotype DX from a Brazilian private medicine perspective: a GBECAM multicenter retrospective study

Background

Oncotype DX (ODX) is a validated assay for the prediction of risk of recurrence and benefit of chemotherapy (CT) in both node negative (N0) and 1-3 positive nodes (N1), hormone receptor positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) early breast cancer (eBC). Due to limited access to genomic assays in Brazil, treatment decisions remain largely driven by traditional clinicopathologic risk factors. ODX has been reported to be cost-effective in different health system, but limited data are available considering the reality of middle-income countries such as Brazil. We aim to evaluate the cost-effectiveness of ODX across strata of clinical risk groups using data from a dataset of patients from Brazilian institutions.

Methods

Clinicopathologic and ODX information were analyzed for patients with T1-T3, N0-N1, HR+/HER2- eBC who had an ODX performed between 2005 and 2020. Projections of CT indication by clinicopathologic criteria were based on binary clinical risk categorization based on the Adjuvant! Algorithm. The ODX score was correlated with the indication of CT according to TAILORx and RxPONDER data. Two decision-tree models were developed. In the first model, low and high clinical risk patients were included while in the second, only high clinical risk patients were included. The cost for ODX and CT was based on the Brazilian private medicine perspective.

Results

In all, 645 patients were analyzed; 411 patients (63.7%) had low clinical risk and 234 patients (36.3%) had high clinical risk disease. The ODX indicated low (<11), intermediate (11-25), and high (>25) risk in 119 (18.4%), 415 (64.3%), and 111 (17.2%) patients, respectively. Among 645 patients analyzed in the first model, ODX was effective (5.6% reduction in CT indication) though with an incremental cost of United States Dollar (US$) 2288.87 per patient. Among 234 patients analyzed in the second model (high clinical risk only), ODX led to a 57.7% reduction in CT indication and reduced costs by US$ 4350.66 per patient.

Conclusions

Our study suggests that ODX is cost-saving for patients with high clinical risk HR+/HER2- eBC and cost-attractive for the overall population in the Brazilian private medicine perspective. Its incorporation into routine practice should be strongly considered by healthcare providers.

Improved NSGA-II algorithms for multi-objective biomarker discovery

MOTIVATION

In modern translational research, the development of biomarkers heavily relies on use of omics technologies, but implementations with basic data mining algorithms frequently lead to false positives. Non-dominated Sorting Genetic Algorithm II (NSGA2) is an extremely effective algorithm for biomarker discovery but has been rarely evaluated against large-scale datasets. The exploration of the feature search space is the key to NSGA2 success but in specific cases NSGA2 expresses a shallow exploration of the space of possible feature combinations, possibly leading to models with low predictive performances.

RESULTS

We propose two improved NSGA2 algorithms for finding subsets of biomarkers exhibiting different trade-offs between accuracy and feature number. The performances are investigated on gene expression data of breast cancer patients. The results are compared with NSGA2 and LASSO. The benchmarking dataset includes internal and external validation sets. The results show that the proposed algorithms generate a better approximation of the optimal trade-offs between accuracy and set size. Moreover, validation and test accuracies are better than those provided by NSGA2 and LASSO. Remarkably, the GA-based methods provide biomarkers that achieve a very high prediction accuracy (>80%) with a small number of features (<10), representing a valid alternative to known biomarker models, such as Pam50 and MammaPrint.

AVAILABILITY AND IMPLEMENTATION

The software is publicly available on GitHub at github.com/UEFBiomedicalInformaticsLab/BIODAI/tree/main/MOO.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of "Chuanxiong Rhizoma: Radix Salviae miltiorrhizae" Herb Couples in the Treatment of Preeclampsia

Objective

The aim of the study is to explore the molecular mechanism of activating blood circulation and dispersing stasis herbs in the treatment of pre-eclampsia with Chuanxiong Rhizoma-Radix Salvia miltiorrhiza.

Methods

The chemical composition and targets of Chuanxiong Rhizoma-Radix Salvia miltiorrhiza were retrieved from the TCMSP database, and a PPI network was constructed for common genes. Subsequently, a graph of the "active component-target-action pathway" was plotted by Cytoscape 3.7.2 and a KEGG pathway enrichment was performed using the R language cluster profiler package. Molecular docking was conducted between the top five PPI targets of Chuanxiong Rhizoma-Radix Salvia miltiorrhiza.

Results

According to network pharmacology, there were 32 target genes, 60 active components, and 59 pathways in Chuanxiong Rhizoma-Radix Salvia miltiorrhiza, and its most evident effects were exerted on G-protein-coupled amine receptors and the neuroactive ligand-receptor interaction signaling pathway. Molecular docking indicated that the target protein had a good binding ability with the drugs.

Conclusion

Chuanxiong Rhizoma-Radix Salvia miltiorrhiza have therapeutic effects in pre-eclampsia, as confirmed by the results of molecular biology analysis. Thus, the Chuanxiong Rhizoma-Radix Salvia miltiorrhiza regimen provides a basis for the treatment of pre-eclampsia using traditional Chinese medicine.

Hospital Rurality and Gene Expression Profiling for Early-Stage Breast Cancer among Iowa Residents (2010-2018)

Objective

Given the challenges rural cancer patients face in accessing cancer care as well as the slower diffusion and adoption of new medical technologies among rural providers, the aim of our study was to examine trends in gene expression profiling (GEP) testing and evaluate the association between hospital rurality and receipt of GEP testing.

Methods

Data from the Iowa Cancer Registry (ICR) were used to identify women with newly diagnosed, histologically confirmed breast cancer from 2010 through 2018 who met eligibility criteria for GEP testing. Patients were allocated to the hospitals where their most definitive surgical treatment was received, and Rural-Urban Commuting Area codes were used to categorize hospitals into urban (N = 43), large rural (N = 16), and small rural (N = 48). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression to evaluate the association between hospital rurality and GEP test use, adjusting for demographic and clinical characteristics. The association between test result and treatment received was assessed among patients who received Oncotype DX (ODX) testing.

Results

Of 6,726 patients eligible for GEP test use, 46% (N = 3,069) underwent testing with 95% receiving ODX. While overall GEP testing rates increased over time from 42% between 2010 and 2012 to 51% between 2016 and 2018 (P _trend < 0.0001), use continued to be the lowest among patients treated at hospitals in small rural areas. The odds of GEP testing remained significantly lower among patients treated at hospitals located in small rural areas (aOR 0.55; 95% CI 0.43-0.71), after adjusting for demographic and clinical characteristics. ODX recurrence scores were highly correlated with chemotherapy use across all strata of hospital rurality.

Conclusions

GEP testing continues to be underutilized, especially among those treated at small rural hospitals. Targeted interventions aimed at increasing rates of GEP testing to ensure the appropriate use of adjuvant chemotherapy may improve health outcomes and lower treatment-related costs.

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.

Potential of chimeric antigen receptor (CAR)-redirected immune cells in breast cancer therapies: Recent advances

Despite substantial developments in conventional treatments such as surgery, chemotherapy, radiotherapy, endocrine therapy, and molecular-targeted therapy, breast cancer remains the leading cause of cancer mortality in women. Currently, chimeric antigen receptor (CAR)-redirected immune cell therapy has emerged as an innovative immunotherapeutic approach to ameliorate survival rates of breast cancer patients by eliciting cytotoxic activity against cognate tumour-associated antigens expressing tumour cells. As a crucial component of adaptive immunity, T cells and NK cells, as the central innate immune cells, are two types of pivotal candidates for CAR engineering in treating solid malignancies. However, the biological distinctions between NK cells- and T cells lead to differences in cancer immunotherapy outcomes. Likewise, optimal breast cancer removal via CAR-redirected immune cells requires detecting safe target antigens, improving CAR structure for ideal immune cell functions, promoting CAR-redirected immune cells filtration to the tumour microenvironment (TME), and increasing the ability of these engineered cells to persist and retain within the immunosuppressive TME. This review provides a concise overview of breast cancer pathogenesis and its hostile TME. We focus on the CAR-T and CAR-NK cells and discuss their significant differences. Finally, we deliver a summary based on recent advancements in the therapeutic capability of CAR-T and CAR-NK cells in treating breast cancer.

Research on the Economics of Cancer-Related Health Care: An Overview of the Review Literature

We reviewed current literature reviews regarding economics of cancer-related health care to identify focus areas and gaps. We searched PubMed for systematic and other reviews with the Medical Subject Headings "neoplasms" and "economics" published between January 1, 2010, and April 1, 2020, identifying 164 reviews. Review characteristics were abstracted and described. The majority (70.7%) of reviews focused on cost-effectiveness or cost-utility analyses. Few reviews addressed other types of cancer health economic studies. More than two-thirds of the reviews examined cancer treatments, followed by screening (15.9%) and survivorship or end-of-life (13.4%). The plurality of reviews (28.7%) cut across cancer site, followed by breast (20.7%), colorectal (11.6%), and gynecologic (8.5%) cancers. Specific topics addressed cancer screening modalities, novel therapies, pain management, or exercise interventions during survivorship. The results indicate that reviews do not regularly cover other phases of care or topics including financial hardship, policy, and measurement and methods.

Biomarkers for Adjuvant Endocrine and Chemotherapy in Early-Stage Breast Cancer: ASCO Guideline Update

PURPOSE

To update recommendations on appropriate use of breast cancer biomarker assay results to guide adjuvant endocrine and chemotherapy decisions in early-stage breast cancer.

METHODS

An updated literature search identified randomized clinical trials and prospective-retrospective studies published from January 2016 to October 2021. Outcomes of interest included overall survival and disease-free or recurrence-free survival. Expert Panel members used informal consensus to develop evidence-based recommendations.

RESULTS

The search identified 24 studies informing the evidence base.

RECOMMENDATIONS

Clinicians may use Oncotype DX, MammaPrint, Breast Cancer Index (BCI), and EndoPredict to guide adjuvant endocrine and chemotherapy in patients who are postmenopausal or age > 50 years with early-stage estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative (ER+ and HER2-) breast cancer that is node-negative or with 1-3 positive nodes. Prosigna and BCI may be used in postmenopausal patients with node-negative ER+ and HER2- breast cancer. In premenopausal patients, clinicians may use Oncotype in patients with node-negative ER+ and HER2- breast cancer. Current data suggest that premenopausal patients with 1-3 positive nodes benefit from chemotherapy regardless of genomic assay result. There are no data on use of genomic tests to guide adjuvant chemotherapy in patients with ≥ 4 positive nodes. Ki67 combined with other parameters or immunohistochemistry 4 score may be used in postmenopausal patients without access to genomic tests to guide adjuvant therapy decisions. BCI may be offered to patients with 0-3 positive nodes who received 5 years of endocrine therapy without evidence of recurrence to guide decisions about extended endocrine therapy. None of the assays are recommended for treatment guidance in individuals with HER2-positive or triple-negative breast cancer. Treatment decisions should also consider disease stage, comorbidities, and patient preferences.Additional information is available at www.asco.org/breast-cancer-guidelines.

Cost-Effectiveness Analysis from a Societal Perspective of Recurrence Index for Distant Recurrence (RecurIndex) in Women with Hormone Receptor-Positive and HER2-Negative Early-Stage Breast Cancer

Purpose

A clinical-genomic prognostic multigene panel (RI-DR assay, RecurIndex^®), predicting the risk level of distant recurrence (DR) in early-stage breast cancer (EBC) patients with an Asian background, has been validated as a valuable tool for identifying high-risk patients to develop distant recurrence (metastasis). Although the clinical benefit of adjuvant chemotherapy from the assay’s prediction is already proved, its affordability remains uncertain. This study is the first time in which the long-term cost-effectiveness of the RI-DR assay is evaluated.

Patients and Methods

A lifetime Markov decision-analytic model was developed from a societal perspective to estimate the life-years gained (LYGs), quality-adjusted life-years (QALYs), medical costs, and incremental cost-effectiveness ratios (ICERs), comparing EBC women with and without RI-DR genomic testing. A decision tree was used to classify patients in one of the fifteen end nodes (by order, each arm was stratified by a patient being tested or not with the RI-DR assay, being treated or not with adjuvant chemotherapy and had no, minor, major, or fatal toxicity after adjuvant chemotherapy). Health utilities, costs, transition probabilities, and survival data were extracted from the scientific literature. Deterministic sensitivity analysis (DSA) and probabilistic sensitivity analysis (PSA) were performed on variables to assess the robustness of the model. A willingness-to-pay (WTP) threshold of 790,000 NT$ per QALY gained was considered as a cost-effectiveness criterion.

Results

The incremental cost per QALY gained under base-case assumptions of the model was 173,842 NT$. Findings on the variation in model input parameters were robust and confirmed that every key variable was cost-effective for the benefit of RI-DR testing.

Conclusion

The clinical-genomic RI-DR assay is cost-effective in guiding adjuvant chemotherapy decisions compared to current clinical practice guidelines.

What genes are differentially expressed in individuals with schizophrenia? A systematic review

Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.

The clinician's perspective on the 21-gene assay in early breast cancer

Most patients with early HR+ and HER2- breast cancer receive a hormone therapy; the clinical question still open is how to identify patients who can really benefit from adjuvant chemotherapy. The accurate identification of these patients is essential to avoid an over-treatment, increasing the risk of an unnecessary toxicity; on the contrary, the omission of chemotherapy can deprive high risk patients of a potential life-saving treatment (under-treatment). Several multigene assays (MGAs), assessing the risk of relapse according to the biological characteristics of the tumor, have been developed. To date, the 21-gene assay (Oncotype DX Breast Recurrence Score^®) is the only test developed and validated to be actionable, i.e., able to predict the benefit of adjuvant chemotherapy. The different available tests can be classified according to their clinical utility based on their prognostic and predictive value. A prognostic test gives information about the outcome of the disease, regardless of the administered therapy. When the aim of the test is to drive the treatment decisions, the predictive component, and therefore the ability to accurately identify which patients could benefit from chemotherapy, is essential. This review summarizes the clinical evidences of the Oncotype DX^® test supporting its clinical utility.

The value of prognostic ultrasound features of breast cancer in different molecular subtypes with a focus on triple negative disease

The ultrasound (US) features of breast cancer have recently been shown to have prognostic significance. We aim to assess these features according to molecular subtype. 1140 consecutive US visible invasive breast cancers had US size and mean stiffness by shearwave elastography (SWE) recorded prospectively. Skin thickening (> 2.5 mm) overlying the cancer on US and the presence of posterior echo enhancement were assessed retrospectively while blinded to outcomes. Cancers were classified as luminal, triple negative (TN) or HER2 + ve based on immunohistochemistry and florescent in-situ hybridization. The relationship between US parameters and breast cancer specific survival (BCSS) was ascertained using Kaplan–Meier survival curves and ROC analysis. At median follow-up 6.3 year, there were 117 breast cancer (10%) and 132 non-breast deaths (12%). US size was significantly associated with BCSS all groups (area under the curve (AUC) 0.74 in luminal cancers, 0.64 for TN and 0.65 for HER2 + ve cancers). US skin thickening was associated most strongly with poor prognosis in TN cancers (53% vs. 80% 6 year survival, p = 0.0004). Posterior echo enhancement was associated with a poor BCSS in TN cancers (63% vs. 82% 6 year survival, p = 0.02). Mean stiffness at SWE was prognostic in the luminal and HER2 positive groups (AUC 0.69 and 0.63, respectively). In the subgroup of patients with TN cancers receiving neo-adjuvant chemotherapy posterior enhancement and skin thickening were not associated with response. US skin thickening is a poor prognostic indicator is all 3 subtypes studied, while posterior enhancement was associated with poor outcome in TN cancers

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.

The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa

Background

MammaPrint (MP) has been applied in South Africa (SA) for decision-making in early-stage hormone receptor-positive breast cancer since 2006. The cost-impact of MP in SA has not been assessed.

Aim

To assess different MP testing strategies for cost-minimization in early-stage breast carcinoma using a funder perspective.

Methods

Clinico-pathologic information was extracted from a prospectively collected database. Clinical risk stratification was done using Adjuvant Online! (AOL) and the Predict V2.1 algorithm (www.predict.nhs.uk). An unselected MP testing strategy was compared to a selective strategy, testing only clinically high risk (cHigh) patients. Excluding human epidermal growth factor receptor-2 positive tumours, the costs for chemotherapy treatment and MP using funding data were used to evaluate the financial impact of these strategies.

Results

In 583 patients with 601 tumours, 52% were clinically low risk (cLow) (AOL) while the average Predict 10-year survival with chemotherapy was 2.9%. MP correlated strongly with Predict and 318 (60%) patients were MP low risk. Unselective testing allowed omission of chemotherapy in 44 (8.4%) patients but escalated cost by 57.7%. Using a selective testing strategy, only 251 would be tested, de-escalating treatment in 138 (55%) and reducing cost by 19.5%. Considering a Predict value up to 3.2% as cHigh, cost would be up to 7.3% (p = 0.0467) lower with a selective testing strategy.

Conclusion

MP allowed reduction in the use of adjuvant chemotherapy. Unselective use of MP increases overall costs. A selective testing strategy through clinical risk stratification using AOL/Predict results in substantial cost saving.

•

Current clinical application of MammaPrint in early breast cancer in South Africa results in the testing of a large percentage of clinically low risk patients.

•

When expensive assays, is used in this (unselected) manner, it results in reduced use of chemotherapy, but the total direct cost is increased.

•

A selective testing strategy could result in substantial cost savings.

Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).

Multigene tests for breast cancer: the physician's perspective

Breast cancer is the most common tumour in women and the first cause of death for cancer in the female population. Preserving the quality of life has therefore become an important objective in the management of the disease. The benefits of adjuvant chemotherapy in patients with HR+ HER2- early breast cancer should always be balanced against its potential short and long-term adverse effects, and identifying the appropriate patients for whom chemotherapy can offer the highest clinical benefit is critical. Besides clinical and pathological factors, today four multigene tests able to guide the choice of the adjuvant therapy early breast cancer are available in Italy: Oncotype DX®, EndoPredict®, MammaPrint® e Prosigna®. This review evaluates the main characteristics of these diagnostic tests, the studies on clinical utility, their economic impact and their inclusion in international and national guidelines. The Oncotype DX Breast Recurrence Score® test is the only multigene test validated, with level IA evidence, to guide the adjuvant therapy decisions: hormone therapy alone for most patients with RS results 0-25, and chemotherapy for patients with RS results 26-100. Clinical data demonstrate that the Oncotype DX test is able to significantly impact therapeutic decisions, reducing chemotherapy use up to 49% and supporting the use of chemotherapy (up to 12%) in potentially under-treated patients. Based on the level of clinical evidence and established clinical utility, several multigene tests have been included in the main international guidelines, with recommendations ranging from "strong" to "moderate".

Recommendations from the European Commission Initiative on Breast Cancer for multigene testing to guide the use of adjuvant chemotherapy in patients with early breast cancer, hormone receptor positive, HER-2 negative

Background

Predicting the risk of recurrence and response to chemotherapy in women with early breast cancer is crucial to optimise adjuvant treatment. Despite the common practice of using multigene tests to predict recurrence, existing recommendations are inconsistent. Our aim was to formulate healthcare recommendations for the question “Should multigene tests be used in women who have early invasive breast cancer, hormone receptor-positive, HER2-negative, to guide the use of adjuvant chemotherapy?”

Methods

The European Commission Initiative on Breast Cancer (ECIBC) Guidelines Development Group (GDG), a multidisciplinary guideline panel including experts and three patients, developed recommendations informed by systematic reviews of the evidence. Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision frameworks were used. Four multigene tests were evaluated: the 21-gene recurrence score (21-RS), the 70-gene signature (70-GS), the PAM50 risk of recurrence score (PAM50-RORS), and the 12-gene molecular score (12-MS).

Results

Five studies (2 marker-based design RCTs, two treatment interaction design RCTs and 1 pooled individual data analysis from observational studies) were included; no eligible studies on PAM50-RORS or 12-MS were identified and the GDG did not formulate recommendations for these tests.

Conclusions

The ECIBC GDG suggests the use of the 21-RS for lymph node-negative women (conditional recommendation, very low certainty of evidence), recognising that benefits are probably larger in women at high risk of recurrence based on clinical characteristics. The ECIBC GDG suggests the use of the 70-GS for women at high clinical risk (conditional recommendation, low certainty of evidence), and recommends not using 70-GS in women at low clinical risk (strong recommendation, low certainty of evidence).

Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer

Although research into immunotherapy is growing, its use in the treatment of breast cancer remains limited. Thus, identification and evaluation of prognostic biomarkers of tissue microenvironments will reveal new immune-based therapeutic strategies for breast cancer. Using an in silico bioinformatic approach, we investigated the tumor microenvironmental and genetic factors related to breast cancer. We calculated the Immune score, Stromal score, Estimate score, Tumor purity, TMB (Tumor mutation burden), and MATH (Mutant-allele tumor heterogeneity) of Breast cancer patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and Maftools. Significant correlations between Immune/Stromal scores with breast cancer subtypes and tumor stages were established. Importantly, we found that the Immune score, but not the Stromal score, was significantly related to the patient's prognosis. Weighted correlation network analysis (WGCNA) identified a pattern of gene function associated with Immune score, and that almost all of these genes (388 genes) are significantly upregulated in the higher Immune score group. Protein-protein interaction (PPI) network analysis revealed the enrichment of immune checkpoint genes, predicting a good prognosis for breast cancer. Among all the upregulated genes, FPR3, a G protein-coupled receptor essential for neutrophil activation, is the sole factor that predicts poor prognosis. Gene set enrichment analysis analysis showed FRP3 upregulation synergizes with the activation of many pathways involved in carcinogenesis. In summary, this study identified FPR3 as a key immune-related biomarker predicting a poor prognosis for breast cancer, revealing it as a promising intervention target for immunotherapy.

Why is appropriate healthcare inaccessible for many European breast cancer patients? - The EBCC 12 manifesto

In Europe, inappropriate reimbursement and funding rules and regulations act as disincentives to best breast cancer care or, at worst, hinder best care. This problem was the focus of the 12th European Breast Cancer Conference (EBCC) manifesto, discussed during the virtual conference. As patient involvement is indispensable in driving changes to clinical practice, Europa Donna the European patient advocacy group was closely involved in the 12th manifesto. Reimbursement policies have rarely evolved with advances in breast cancer care such as outpatient (ambulatory) care rather than inpatient admission, use of oral or subcutaneous anti-cancer drugs rather than day-hospital intravenous administration, oncoplastic surgery techniques to minimize mastectomy rates, breast reconstructive surgery, risk-reducing surgery for BRCA mutation carriers, or use of hypo-fractionated breast radiation therapy. Although each European country, region and centre will have to understand how their reimbursement policies may hinder best care and find their own solutions, the problems are similar throughout Europe and some solutions can be broadly applied. This manifesto is not calling for more funding or demanding changes that will result in more expensive care. Reimbursement, if better aligned with guidelines and optimal clinical practice, will deliver more cost-effective healthcare. This will release resources, support more equitable use of finite funding and resources, so allowing more European breast cancer patients to benefit from evidence-based treatment recommended by national and international guidelines.

Ppm1b Negatively Regulates 3-Bromopyruvate Induced Necroptosis in Breast Cancer Cells

Up to 30% of breast cancer mortality is caused by cancer relapse despite primary clinical treatments due to distant metastases. Further research focusing on breast cancer mechanisms are needed for deeper understanding of disease prognosis. 3-bromopyruvate (3-BP), a glycolysis inhibitor, has been studied as one of the antitumor agents in recent years. In this report, we want to investigate the form of cell death induced by 3-BP and demonstrate the inhibitory effect of 3-BP on breast cancer cell proliferation and its mechanism in vivo and in vitro. We found that 3-BP could inhibit MDA-MB-231 and MCF-7 breast cancer cell proliferation, through energy metabolism inhibition. Further, necroptosis characters in MDA-MB-231 cells after 3-BP treatment were observed, which could be negatively regulated through Ppm1b by dephosphorylation of RIP3. In addition, 3-BP treatment in an MDA-MB-231 cell-transplanted mouse model showed a significant antitumor effect, which correlated with necroptosis-related protein Ppm1b. The findings demonstrate the potential for 3-BP in the treatment of breast cancer, providing impetus for further clinical studies.

Efficient gene expression signature for a breast cancer immuno-subtype

MOTIVATION AND BACKGROUND

The patient's immune system plays an important role in cancer pathogenesis, prognosis and susceptibility to treatment. Recent work introduced an immune related breast cancer. This subtyping is based on the expression profiles of the tumor samples. Specifically, one study showed that analyzing 658 genes can lead to a signature for subtyping tumors. Furthermore, this classification is independent of other known molecular and clinical breast cancer subtyping. Finally, that study shows that the suggested subtyping has significant prognostic implications.

RESULTS

In this work we develop an efficient signature associated with survival in breast cancer. We begin by developing a more efficient signature for the above-mentioned breast cancer immune-based subtyping. This signature represents better performance with a set of 579 genes that obtains an improved Area Under Curve (AUC). We then determine a set of 193 genes and an associated classification rule that yield subtypes with a much stronger statistically significant (log rank p-value < 2 × 10-4 in a test cohort) difference in survival. To obtain these improved results we develop a feature selection process that matches the high-dimensionality character of the data and the dual performance objectives, driven by survival and anchored by the literature subtyping.

Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer

IMPORTANCE

Axillary lymph node metastasis (ALNM) status, typically estimated using an invasive procedure with a high false-negative rate, strongly affects the prognosis of recurrence in breast cancer. However, preoperative noninvasive tools to accurately predict ALNM status and disease-free survival (DFS) are lacking.

OBJECTIVE

To develop and validate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic signatures for preoperative identification of ALNM and to assess individual DFS in patients with early-stage breast cancer.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective prognostic study included patients with histologically confirmed early-stage breast cancer diagnosed at 4 hospitals in China from July 3, 2007, to September 21, 2019, randomly divided (7:3) into development and vaidation cohorts. All patients underwent preoperative MRI scans, were treated with surgery and sentinel lymph node biopsy or ALN dissection, and were pathologically examined to determine the ALNM status. Data analysis was conducted from February 15, 2019, to March 20, 2020.

EXPOSURE

Clinical and DCE-MRI radiomic signatures.

MAIN OUTCOMES AND MEASURES

The primary end points were ALNM and DFS.

RESULTS

This study included 1214 women (median [IQR] age, 47 [42-55] years), split into development (849 [69.9%]) and validation (365 [30.1%]) cohorts. The radiomic signature identified ALNM in the development and validation cohorts with areas under the curve (AUCs) of 0.88 and 0.85, respectively, and the clinical-radiomic nomogram accurately predicted ALNM in the development and validation cohorts (AUC, 0.92 and 0.90, respectively) based on a least absolute shrinkage and selection operator (LASSO)-logistic regression model. The radiomic signature predicted 3-year DFS in the development and validation cohorts (AUC, 0.81 and 0.73, respectively), and the clinical-radiomic nomogram could discriminate high-risk from low-risk patients in the development cohort (hazard ratio [HR], 0.04; 95% CI, 0.01-0.11; P < .001) and the validation cohort (HR, 0.04; 95% CI, 0.004-0.32; P < .001) based on a random forest-Cox regression model. The clinical-radiomic nomogram was associated with 3-year DFS in the development and validation cohorts (AUC, 0.89 and 0.90, respectively). The decision curve analysis demonstrated that the clinical-radiomic nomogram displayed better clinical predictive usefulness than the clinical or radiomic signature alone.

CONCLUSIONS AND RELEVANCE

This study described the application of MRI-based machine learning in patients with breast cancer, presenting novel individualized clinical decision nomograms that could be used to predict ALNM status and DFS. The clinical-radiomic nomograms were useful in clinical decision-making associated with personalized selection of surgical interventions and therapeutic regimens for patients with early-stage breast cancer.

The Potential Use of Tumour-Based Prognostic and Predictive Tools in Older Women with Primary Breast Cancer: A Narrative Review

A move is under way towards personalised cancer treatment, where tumour biology of an individual patient is examined to give unique predictive and prognostic information. This is extremely important in the setting of older women, who have treatment-specific goals which may differ from their younger counterparts, and may include conservation of quality of life rather than curative intent of treatment. One method employed to assist with this is the use of tumour-based prognostic and predictive tools. This article explores six of the most common tumour-based tools currently available on the market: MammaPrint, Oncotype DX, Mammostrat, Prosigna, EndoPredict, IHC4. The article discusses the creation and validation of these tools, their use and validation in older women, and future directions in the field. With the exception of Oncotype Dx, which has also been licensed for prediction of response from adjuvant chemotherapy, these tools have been licensed for use as prognostic tools only, mainly in the setting of adjuvant therapy following surgery. The evidence base for use in older women is strongest for Mammostrat and PAM50, although overall the evidence is much weaker than that in younger women. Where older women have been included in validation studies, this is often in small numbers, or the exact proportion of older women is unknown. In practice, all six of the tools are recommended to be utilised on surgical excision specimens, as well as in core needle biopsy (CNB) specimens in all of the tools except Mammostrat. This is extremely important in the setting of older women, of whom a large proportion do not undergo surgery. The suggested nature of the sample is formalin-fixed paraffin-embedded in all the tools except MammaPrint, which can also be performed on fresh-frozen samples. Future development of prognostic tools in older women with breast cancer should focus on treatment dilemmas specific to this population. This includes the decision of primary treatment between surgery or endocrine therapy and decisions regarding adjuvant therapy, in particular, chemotherapy.

Next-generation diagnostics for precision oncology: Preanalytical considerations, technical challenges, and available technologies

Molecular diagnostics as the centrepiece of precision oncology has gone through revolutionary developments over the last decade, becoming tremendously broad, deep and precise with still ongoing advancements. In the majority of scenarios, treatment selection for cancer patients without any type of molecular characterization is no longer conceivable. Considering the impact of sample quality on the reliability of molecular analyses and the importance of the results for the fate of an individual patient, it is surprising how sparsely preanalytical and analytical requirements are addressed scientifically. Standardization and rigorous quality assessment continue to play only a marginal role in the field. Within this review, we will systematically discuss influencing preanalytic parameters and technology setups affecting molecular test results. We will shed light on the specifics of different analytes, technical modalities, and analysis pipelines. The review will have a certain focus on broad molecular genetic tumour testing with next generation sequencing but will go beyond that including other molecular diagnostic modalities and will give a glimpse into the future of molecular testing.

Challenges in Preventing Bone Loss Induced by Aromatase Inhibitors

CONTEXT

Aromatase inhibitors have become a mainstay in the adjuvant treatment regimen in postmenopausal women with hormone receptor-positive breast cancer. While many of these patients have an excellent long-term prognosis, adverse effects on bone represent an emerging complication of aromatase inhibitor treatment, resulting in substantial bone loss and fragility fractures. Treatment approaches to prevent aromatase inhibitor-induced bone loss typically consist of an antiresorptive approach with bisphosphonates or the RANKL antibody denosumab. However, different guidelines vary with respect to treatment thresholds, duration, and dosing. The choice of antiresorptive regime is further complicated by comorbidities and potential disease-modifying effects of individual agents.

OBJECTIVE

This review summarizes the evidence of how aromatase inhibitors affect bone health and provides an update of clinical approaches to preserve bone strength in affected women. (J Clin Endocrinol Metab XX: 0-0, 2020).

Bringing Greater Accuracy to Europe's Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. This paper sets out the potential of biomarker testing, the unfolding precision and range of possible diagnosis and prediction, and the many obstacles to adoption. It offers case studies of biomarker testing in breast, ovarian, prostate, lung, thyroid and colon cancers, and derives specific lessons as to the potential and actual use of each of them. It also draws lessons about how to improve access and alignment, and to remedy the data deficiencies that impede development. And it suggests solutions to outstanding issues - notably including funding and the tangled web of obtaining reimbursement or equivalent coverage that Europe's fragmented health system implies. It urges a European evolution towards an initial minimum testing scenario, which would guarantee universal access to a suite of biomarker tests for the currently most common conditions, and, further into the future, to an optimum testing scenario in which a much wider range of biomarker tests would be introduced and become part of a more sophisticated health system articulated around personalised medicine. For exploiting genomics to the full, it argues the need for a new policy framework for Europe. Biomarker testing is not an issue that can be treated in isolation, since the purpose of testing is to improve health. Its use is therefore always closely linked to specific health challenges and needs to be viewed in the broader policy context in the EU and more widely. The paper is the result of extensive engagement with experts and decision makers to develop the framework, and consequently represents a wide consensus of views on how healthcare systems should respond from push and pull factors at local, national and cross-border and EU level. It contains strong views and clear recommendations springing from the convictions of patients, clinicians, academics, medicines authorities, HTA bodies, payers, the diagnostic, pharmaceutical and ICT industries, and national policy makers.

Personalised medicine and the decision to withhold chemotherapy in early breast cancer with intermediate risk of recurrence - a systematic review and meta-analysis

PURPOSE

To assess the evidence for decision making, at the health care and the patient levels, regarding the use of gene expression assays to inform chemotherapy decisions in breast cancer patients with intermediate clinical risk of recurrence.

METHODS

Systematic literature searches were performed (January 2002-April 2020) in Medline, Embase, PubMed, Cochrane Library, PsycINFO and HTA databases.

INCLUSION CRITERIA

patients (P) were individuals with post-surgical breast cancer at intermediate clinical risk of recurrence; intervention (I)/comparison (C) was (i) use of, versus no use of, a gene expression assay and (ii) withholding versus providing chemotherapy; outcomes (O) were overall survival (OS), health-related quality of life (HRQL), and recurrence. Randomised controlled trials (RCTs) and non-RCTs were included. Random-effects meta-analyses were performed where possible.

RESULTS

Three inconclusive non-RCTs, respectively, compared OS and recurrence with and without a gene expression assay. No studies investigated HRQL. Regarding the comparison withholding versus providing chemotherapy based on a gene expression assay, one RCT and four non-RCTs evaluated OS. In the RCT, 93.9% (I) versus 93.8% (C) were alive at 9 years. Three RCTs and seven non-RCTs evaluated recurrence. Three RCTs could be pooled regarding distant recurrence; 4.29% versus 3.88% had such an event (risk ratio: 1.12 (95% confidence interval: 0.90 to 1.39).

CONCLUSION

Regarding the use of gene expression assays in breast cancer, evidence on patient effects, informing patient-level chemotherapy decision making, is available. However, evidence for prioritisation at the overall health care level, i.e. use of, versus no use of, such assays, is largely lacking.

Cost-effectiveness analysis of the 70-gene signature compared with clinical assessment in breast cancer based on a randomised controlled trial

BACKGROUND

The clinical utility of the 70-gene signature (MammaPrint®) to guide chemotherapy use in T1-3N0-1M0 breast cancer was demonstrated in the Microarray in Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy (MINDACT) study. One thousand four ninety seven of 3356 (46.2%) enrolled patients with high clinical risk (in accordance with the modified Adjuvant! Online clinical-pathological assessment) had a low-risk 70-gene signature. Using patient-level data from the MINDACT trial, the cost-effectiveness of using the 70-gene signature to guide adjuvant chemotherapy selection for clinical high risk, estrogen receptor positive (ER+), human epidermal growth factor 2 negative (HER2-) patients was analysed.

PATIENTS AND METHODS

A hybrid decision tree-Markov model simulated treatment strategies in accordance with the 70-gene signature with clinical assessment versus clinical assessment alone, over a 10-year time horizon. Primary outcomes were quality-adjusted life years (QALYs), country-specific costs and incremental cost-effectiveness ratios (ICERs) for six countries: Belgium, France, Germany, Netherlands, UK and the US.

RESULTS

Treatment strategies guided by the 70-gene signature result in more QALYs compared with clinical assessment alone. Costs of the 70-gene signature strategy were lower in five of six countries. This led to dominance of the 70-gene signature in Belgium, France, Germany, Netherlands and the US and to a cost-effective situation in the UK (ICER £22,910/QALY). Annual national cost savings were €4.2M (Belgium), €24.7M (France), €45.1M (Germany), €12.7M (Netherlands) and $244M (US). UK budget increase was £8.4M.

CONCLUSION

Using the 70-gene signature to safely guide chemotherapy de-escalation in clinical high risk patients with ER+/HER2- tumours is cost-effective compared with using clinical assessment alone. Long-term follow-up and outcomes from the MINDACT trial are necessary to address uncertainties in model inputs.

The use of genomic tests in patients with breast cancer in Lombardy: a successful healthcare model

BACKGROUND

The accurate identification of patients with early breast cancer (eBC) suitable for adjuvant chemotherapy is essential in order to avoid overtreatment or undertreatment. For eBC patients with luminal (HR+/HER2-) intermediate risk disease, multigene assays (MGAs) have been convincingly reported to be useful in guiding treatment decisions. The most recently published data and recommendations from main International Guidelines and Heath Technology Assessment reports confirmed the benefit of MGAs in guiding treatment decisions for clinically intermediate risk patients, and led several countries to test reimbursement.

PURPOSE

This article describes the process followed by the Lombardy region in Italy regarding the reimbursement of MGAs for patients with eBC, based on the results of a prospective clinical trial.

RESULTS

The study shows that the use of Oncotype DX allowed avoiding the use of unnecessary adjuvant chemotherapy in 50% of patients for whom chemotherapy was initially recommended according to traditional clinical practice. On the basis of these data, a group of oncologists in collaboration with a pathologist regional board formally requested authorization for MGA reimbursement in Lombardy. Acknowledging the strategic importance of the proposal, the Lombardy region approved the reimbursement of MGAs for resident patients with luminal eBC at intermediate clinical risk. It can be assumed that about 1500 patients will be tested in Lombardy per year and this should allow the Regional Health Service to save more than 750 chemotherapies/year.

CONCLUSION

The introduction of MGAs in the clinical evaluation of patients with luminal eBC with intermediate risk is economically sustainable and contributes towards preserving quality of life of eligible women.

Overestimation of Late Distant Recurrences in High-Risk Patients With ER-Positive Breast Cancer: Validity and Accuracy of the CTS5 Risk Score in the TEAM and IDEAL Trials

PURPOSE

Most distant recurrences (DRs) in women with hormone receptor-positive breast cancer occur after 5 years from diagnosis. The Clinical Treatment Score post-5 years (CTS5) estimates DRs after 5 years of adjuvant endocrine therapy (AET). The aim of this study was to externally validate the CTS5 as a prognostic/predictive tool.

METHODS

The CTS5 categorizes patients who have been disease free for 5 years into low, intermediate, and high risk and calculates an absolute risk for developing DRs between 5 and 10 years. Discrimination and calibration were assessed using data from the TEAM and IDEAL trials. The predictive value of the CTS5 was tested with data from the IDEAL trial.

RESULTS

A total of 5,895 patients from the TEAM trial and 1,591 patients from the IDEAL trial were included. When assessing the CTS5 discrimination, significantly more DRs were found at 10 years after diagnosis in the CTS5 high- and intermediate-risk groups than in the low-risk group (hazard ratio, 5.7 [95% CI, 3.6 to 8.8] and 2.8 [95% CI, 1.7 to 4.4], respectively). In low- and intermediate-risk patients, the CTS5-predicted DR rates were higher, although not statistically significantly so, than observed rates. However, in high-risk patients, the CTS5-predicted DR rates were significantly higher than observed rates (29% v 19%, respectively; P < .001). The CTS5 was not predictive for extended AET duration.

CONCLUSION

The CTS5 score as applied to patients treated in the TEAM and IDEAL cohorts discriminates between risk categories but overestimates the risk of late DRs in high-risk patients. Therefore, the numerical risk assessment from the CTS5 calculator in its current form should be interpreted with caution when used in daily clinical practice, particularly in high-risk patients.

An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture.

In breast cancer, the immune infiltration of the tumour associates with clinical outcome. Here, the authors infer immune context based on gene expression data and identify a new independent subtype linked to pro-tumorigenic immune infiltration.

External validation of the PREDICT tool in Spanish women with breast cancer participating in population-based screening programmes

RATIONALE, AIMS, AND OBJECTIVES

To externally validate the PREDICT tool in a cohort of women participating in a population-based breast cancer screening programme who were diagnosed with breast cancer between 2000 and 2008 in Spain.

METHODS

A total of 535 women were included in the validation study. We calculated predicted 5-year survival using the beta values from the development of the PREDICT model and predicted and observed events for a given risk groups. Model fit, discrimination, and calibration were evaluated. Seeking to improve the model, we also explored the impact on discrimination of the inclusion of additional variables, not in the PREDICT algorithm.

RESULTS

In patients who were oestrogen receptor (ER) positive (negative), PREDICT overestimated (underestimated) the 5-year overall survival in all the subgroups studied. Analysis of model performance showed good calibration but modest discrimination (C-index, 0.697 [ER negative] and 0.768 [ER positive]). When updating the model, no additional variables were found to be significant in ER-negative patients, but for ER-positive patients, concurrent liver disease was a significant factor, its inclusion improving model discrimination (C-index, 0.817).

CONCLUSIONS

The PREDICT tool does not discriminate well in our population considering only the variables of the original algorithm. More accurate tools are needed to obtain a better discrimination.

Oncotype DX recurrence score implications for disparities in chemotherapy and breast cancer mortality in Georgia

Among women diagnosed with stage I-IIIa, node-negative, hormone receptor (HR)-positive breast cancer (BC), Oncotype DX recurrence scores (ODX RS) inform chemotherapy treatment decisions. Differences in recurrence scores or testing may contribute to racial disparities in BC mortality among women with HR+ tumors. We identified 12,081 non-Hispanic White (NHW) and non-Hispanic Black (NHB) BC patients in Georgia (2010-2014), eligible to receive an ODX RS. Logistic regression was used to estimate the odds of chemotherapy receipt by race and ODX RS. Cox proportional hazard regression was used to calculate the hazard ratios (HRs) comparing BC mortality rates by race and recurrence score. Receipt of Oncotype testing was consistent between NHB and NHW women. Receipt of chemotherapy was generally comparable within strata of ODX RS-although NHB women with low scores were slightly more likely to receive chemotherapy (OR = 1.16, 95% CI 0.77, 1.75), and NHB women with high scores less likely to receive chemotherapy (OR = 0.77, 95% CI 0.48, 1.24), than NHW counterparts. NHB women with a low recurrence score had the largest hazard of BC mortality (HR = 2.47 95% CI 1.22, 4.99) compared to NHW women. Our data suggest that additional tumor heterogeneity, or other downstream treatment factors, not captured by ODX, may be drivers of racial disparities in HR+ BC.

Multigene expression signatures in early hormone receptor positive HER 2 negative breast cancer

Background The standard treatment of hormone receptor positive, HER2 negative early breast cancer (BC) is surgery followed by adjuvant systemic therapy either with endocrine therapy alone or with the addition of chemotherapy followed by endocrine therapy. Adjuvant systemic therapy reduces the risk of recurrence and death from BC. Whether an individual patient will benefit from adjuvant chemotherapy is an important clinical decision. Decisions that rely solely on clinical-pathological factors can often lead to overtreatment. Multigene signatures represent an important progress in optimal selection of high risk patients that might benefit from the addition of chemotherapy to adjuvant endocrine therapy. Conclusions Several signatures are already commercially available and also accepted by international guidelines. Oncotype DX and MammaPrint have been most extensively validated and supported by level IA evidence.

Genomics applied to the treatment of breast cancer

Breast cancer remains a major health issue in the world with 1.7 million new cases in 2012 worldwide. It is the second cause of death from cancer in western countries. Genomics have started to modify the treatment of breast cancer, and the developments should become more and more significant, especially in the present era of treatment personalization and with the implementation of new technologies. With molecular signatures, genomics enabled a de-escalation of chemotherapy and personalized treatments of localized forms of estrogen-dependent breast cancers. Genomics can also make a real contribution to constitutional genetics, so as to identify mutations in a panel of candidate genes. In this review, we will discuss the contributions of genomics applied to the treatment of breast cancer, whether already validated contributions or possible future applications linked to research data.

Higher ER load is not associated with better outcome in stage 1-3 breast cancer: a descriptive overview of quantitative HR analysis in operable breast cancer

PURPOSE

In breast cancer, hormone receptor (HR) status is generally a qualitative measure; positive or negative. Quantitatively measured oestrogen and progesterone receptors (ER and PR) are frequently proposed prognostic and predictive markers, some guidelines even provide different treatment options for patients with strong versus weak expression.

AIM

To evaluate quantitative HR load assessed by immunohistochemistry as a prognostic and predictive measure in stage 1-3 breast cancer.

METHODS

We reviewed all the available literature on quantitatively measured HRs using immunohistochemistry.

RESULTS

All included studies (n = 19) comprised a cohort of 30,754 patients. Only 2 out of 17 studies found a clear correlation between higher quantitative ER and better disease outcome. Only one trial examined quantitative ER both as prognostic and predictive marker and found no association between ER% and survival. Ten studies examined quantitative PR load, only two of those found a significant correlation between higher PR load and better disease outcome. Two trials examined quantitative PR both as prognostic and predictive marker, neither found any association between PR% and disease outcome.

CONCLUSIONS

There is no clear evidence for using quantitatively assessed ER and PR as prognostic nor predictive marker in patients with stage 1-3 breast cancer. We recommend only using a qualitative HR status in future guidelines and treatment considerations.