Estrogen receptor (ER)-positive breast cancer is the most common subtype, accounting for approximately 80% of cases, with endocrine therapy as the standard postoperative treatment. However, despite risk-reducing therapies, the risk of recurrence remains substantial. Studies, including the POETIC trial, have demonstrated that low Ki67 levels following short-term neoadjuvant endocrine therapy (sNAET) are associated with a favorable prognosis. The objective of this study is to identify genes associated with the suppression of cell cycle progression by sNAET in postmenopausal patients with ER-positive/human epidermal growth factor receptor 2-negative breast cancer.

Ninety-seven tissue samples were collected and classified into groups based on Ki67 expression levels before and after treatment. RNA sequencing and real-time quantitative reverse transcription PCR were performed to analyze gene expression in tumor samples from patients stratified into High-High (H-H) or High-Low (H-L) groups based on Ki67 levels before and after sNAET.

Among the differentially expressed genes identified, CXCL9 and ABCA12 were significantly upregulated in the H-H group and were associated with a poor response to endocrine therapy. Conversely, NPY1R was significantly upregulated in the H-L group, suggesting greater responsiveness. In multivariate logistic regression analysis, CXCL9 (OR: 0.65, p = 0.024) and NPY1R (OR: 1.61, p = 0.048) were significant predictors of Ki67 reduction.

These findings suggest that CXCL9 and NPY1R could serve as predictive biomarkers for endocrine therapy response. Identifying these biomarkers may facilitate personalized treatment strategies, including the addition of therapies such as chemotherapy for resistant cases.

Breast cancer is the most common malignancy affecting women, marked by significant complexity and heterogeneity. This disease includes multiple subtypes, each with unique biological features and treatment responses. Despite significant advancements in detection and therapy, challenges remain, particularly in managing aggressive forms like triple-negative breast cancer and overcoming drug resistance. Breast cancer classification and subtype determination are typically performed by immunohistochemistry (IHC) method, which assesses four key markers (ER, PR, HER2, KI67); however, due to the recognized issues with this approach-especially regarding the evaluation of Ki67-there is a risk of misclassification. Patients who may be suitable for chemotherapy could miss possible advantages and only experience needless toxicity as a result of improper treatment decisions. Molecular profiling has improved breast cancer management, enabling the creation of multigene prognostic tests (MPTs) like Oncotype Dx, MammaPrint, Prosigna, Endopredict, and Breast Cancer Index which assess gene expression profiles to more accurately predict recurrence risks. These tools help personalize treatment, identifying patients who can avoid chemotherapy and/or extended endocrine therapy. While many MPTs are available, only Oncotype Dx and MammaPrint have prospective validation, with Prosigna providing additional prognostic insights by incorporating clinical variables. Molecular tests are especially usefull in the "gray zone," which includes tumors measuring between 1 and 3 cm with 0-3 positive lymph nodes and an intermediate proliferation index. However, their clinical utility has not been definitively established, and significant differences exist between them. This article provides an in-depth analysis of established genomic assays, including testing procedures, clinical validity, utility, diagnostic frameworks, and methodologies. Our comparison aims to improve early breast cancer management by guiding pathologists and oncologists in optimizing the use of genomic assays in clinical practice. By presenting this information, we aim to enhance understanding of the clinical utility and effectiveness of these assays, supporting the development of personalized treatment strategies for early breast cancer patients. Genomic assays offer important insights that can support treatment decisions in early-stage breast cancer, especially when used alongside other clinical evaluations, predictive tools, and management guidelines. While multiple gene expression profiling tests are available, they classify patients differently and are not interchangeable; therefore, their application should be at the clinician's discretion during the decision-making process. It is essential that these tests are not the sole factor in determining the best treatment plan: other clinical considerations and patient preferences should also play a significant role in guiding treatment decisions.

Endocrine therapy (ET) is a cornerstone in the management of patients with hormone receptor-positive early breast cancer, which accounts for over 70% of cases worldwide. The efficacy of adjuvant ET for 5 years in reducing the risk of recurrence and improving survival outcomes is well documented. However, the risk for late relapses, occurring >5 years after initial treatment, has prompted exploration of longer treatment durations. Extending ET beyond the traditional 5-year period offers additional benefit in reducing the risk of recurrence and improving long-term outcomes. Nevertheless, determining the optimal duration and identifying suitable candidates for extended therapy is often nuanced. This review aims to comprehensively evaluate the current landscape of extended ET in breast cancer management. It provides an overview of the rationale behind extending endocrine treatment in both premenopausal and postmenopausal women, with a focus on clinical trials and observational studies supporting extended therapy. Furthermore, it emphasizes the significance of considering associated toxicities in patient management. It also explores novel strategies involving the combination of ET with new drugs, leading to an evolution of treatment paradigms that may make the need for extended therapy obsolete.

While existing multi-gene assays aid adjuvant treatment decisions, no gene signature has identified HR+/HER2- early breast cancer (EBC) patients at high recurrence risk post-chemo-endocrine therapy (C-ET).

Clinical data and RNA sequencing information from 1457 HR+/HER2- breast cancer patients were collected from West China Hospital, the GEO database, and the TCGA database. Using univariate Cox regression, gene set enrichment analysis, and LASSO regression, ten key genes associated with recurrence were identified. A comprehensive prognostic model was developed by combining the 10-gene risk score with clinicopathological features, and a nomogram was created to predict 3-, 5-, and 7-year recurrence-free survival (RFS). The model's performance was evaluated using AUC and decision curve analysis (DCA).

The 10-gene risk score was significantly associated with recurrence risk of HR+/HER2- EBC after C-ET and effectively distinguished between high-risk and low-risk patients (training: HR: 6.37, P < 0.001; validation: HR: 4.51, P < 0.001). It maintained consistent stratification efficacy across different treatment regimens, clinical stages, and grades. Compared to existing multi-gene signatures (21-gene, 70-gene, EndoPredict, PAM50, GGI), HR+/HER2- EBC patients identified as high-risk by the 10-gene risk score exhibited a higher 10-year cumulative recurrence rate following C-ET. In multivariate Cox regression analysis, the 10-gene risk score remained an independent prognostic factor in both the training and validation sets. The comprehensive model, integrating the 10-gene score and clinicopathological features, showed high predictive accuracy (AUC: 0.734, 0.778, 0.792 for 3, 5, 7 years in training; 0.691, 0.715, 0.709 in validation).

The 10-gene risk score can serve as a tool to predict recurrence risk in HR+/HER2- EBC patients following C-ET, assisting clinicians in developing personalized treatment plans for high-risk patients and ultimately improving patient prognosis.

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) have revolutionized the treatment of hormone-receptor positive (HR+), HER2 negative (HER2-) metastatic breast cancer, and are now also established agents in the treatment of high-risk and intermediate-risk HR+ early breast cancer. Several strategies regarding CDK4/6i combinations or continuation beyond progression have been successfully evaluated in the metastatic setting, and are considered a standard of care. Mechanism of action of and resistance mechanisms against CDK4/6i in addition to endocrine resistance represent an important research topic, important for the treatment of HR+ breast cancer. Clinically, CDK4/6i are efficient substances that are usually well tolerated. However, side effects differing between the substances have been reported, and might lead to treatment discontinuation, including in the early disease setting. In the adjuvant setting, the addition of palbociclib to standard endocrine treatment has not improved outcomes, whereas large randomized phase III trials have demonstrated significant disease-free survival benefit for the addition of ribociclib (NATALEE trial) and abemaciclib (monarchE trial). Patient selection, treatment duration, endocrine backbone therapy, and other study details differ between these pivotal trials. This review focuses on both the scientific background as well as all available clinical data of CDK4/6i, with particular emphasis on their use in early breast cancer.

Triple-negative breast cancer (TNBC) is a diverse category with a subset that displays particularly aggressive characteristics, referred to in this study as "rapid relapse" TNBC (rrTNBC). This term is defined as the occurrence of distant metastasis or death within 24 months post-diagnosis. The paper mainly studies the clinicopathologic traits of TNBC patients experiencing rapid disease progression and chemotherapy resistance and identify predictive markers for this outcome. A retrospective evaluation was conducted on 2294 TNBC patients who underwent surgery at Tianjin Medical University Cancer Hospital. Of these, 369 were categorized as experiencing rapid relapse, while 1925 did not relapse rapidly. Logistic regression analysis was applied to determine potential markers predictive of rapid relapse post-chemotherapy. Both univariate and multivariate logistic regression analyses pinpointed several predictors of rapid relapse in TNBC patients post-chemotherapy. These include age at diagnosis (≥ 50 years, OR = 0.413, 95% CI: 0.289-0.590), postoperative pathological T staging (T2, OR = 2.557, 95% CI: 1.766-3.703; T3 + T4, OR = 3.725, 95% CI: 1.355-10.454), and N staging (N1, OR = 3.056, 95% CI: 2.021-4.619; N2, OR = 6.917, 95% CI: 3.920-12.206; N3, OR = 24.597, 95% CI: 11.875-50.948). Additionally, sTIL expression (intermediate, OR = 0.204, 95% CI: 0.139-0.300; high, OR = 0.020, 95% CI: 0.011-0.035) and Her2 expression (Her2 1+, OR = 0.470, 95% CI: 0.321-0.688) were identified as protective indicators against rapid relapse. A predictive model incorporating these predictors yielded a C-index of 0.898 in the training set and 0.938 in the validation set, with respective Brier scores of 0.079 and 0.073. The study successfully established and validated a predictive model for rapid disease progression and chemotherapy resistance in TNBC patients post-chemotherapy, demonstrating robust discrimination and accuracy.

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common subtype, representing over two-thirds of new diagnoses. Adjuvant therapy, which encompasses various medications and treatment durations, is the standard approach for managing early stage HR+ HER2- breast cancer. Optimizing treatment is essential to minimize unnecessary side effects while addressing the biological variability inherent in HR+/HER2- breast cancers. Incorporating biological biomarkers into treatment decisions, alongside traditional clinical factors, is vital. Gene expression assays can identify patients unlikely to benefit from adjuvant chemotherapy, thereby refining treatment strategies and improving risk assessment. This paper reviews evidence for several genomic tests, including Oncotype DX, MammaPrint, Breast Cancer Index, RucurIndex, and EndoPredict, which assist in tailoring adjuvant therapy. Additionally, we explore the role of liquid biopsies in personalizing treatment, emphasizing the importance of considering late relapse risks and potential benefits of extended systemic therapy for HR+/HER2- breast cancer patients.

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Adjuvant endocrine therapy (ET) represents the standard of care for almost all hormone receptor (HR)+/HER2- breast cancers, and different agents and durations are currently available. In this context, the tailoring and optimization of adjuvant endocrine treatment by reducing unnecessary toxic treatment while taking into account the biological heterogeneity of HR+/HER2- breast cancer represents a clinical priority. There is therefore a significant need for the integration of biological biomarkers in the choice of adjuvant ET beyond currently used clinicopathological characteristics. Several gene expression assays have been developed to identify patients with HR+/HER2- breast cancer who will not derive benefit from the addition of adjuvant chemotherapy. By enhancing risk stratification and predicting therapeutic response, genomic assays have also shown to be a promising tool for optimizing endocrine treatment decisions. In this study, we review evidence supporting the use of most common commercially available gene expression assays [Oncotype DX, MammaPrint, Breast Cancer Index (BCI), Prosigna, and EndoPredict] in tailoring adjuvant ET. Available data on the use of genomic tests to inform extended adjuvant treatment choice based on the risk of late relapse and on the estimated benefit of a prolonged ET are discussed. Moreover, preliminary evidence regarding the use of genomic assays to inform de-escalation of endocrine treatment, such as shorter durations or omission, for low-risk patients is reviewed. Overall, gene expression assays are emerging as potential tools to further personalize adjuvant treatment for patients with HR+/HER2- breast cancers.

EndoPredict® (EP) is a multigene assay to predict distant recurrence risk in luminal breast cancer. EP measures the expression of 12 genes in primary tumor by qRT-PCR from formalin-fixed paraffin-embedded (FFPE) tissues and calculates EP risk score that indicates the risk of distant recurrence. We evaluated the performance of EP in predicting distant recurrence risk using microarray data from fresh frozen (FF) tissues. We also examined the applicability of EP to microarray data from FFPE tissues.

We analyzed the publicly available data of 431 node-negative and 270 node-positive patients with luminal breast cancer who received endocrine therapy alone. We evaluated the prognostic value of EP using microarray data from FF tissues. Next, we created an algorithm to calculate EP risk score using microarray data from FFPE tissues. We examined the correlation coefficient of EP risk score and concordance rate of EP risk high/low using microarray data from FFPE/FF tissue pairs in a validation set of 39 patients.

In 431 node-negative patients, the distant recurrence-free survival (DRFS) rate was significantly worse in those with high EP risk scores (P = 3.68 × 10-6, log-rank). The 5-year DRFS was 95.2% in those with low EP risk score. In the validation set, the correlation coefficient of EP risk score was 0.93 and the concordance rate of EP risk high/low was 91.7%.

EP using microarray data from FF tissues was useful in predicting distant recurrence risk in luminal breast cancer, and EP might be utilized in microarray data from FFPE tissues.

Risk of recurrence from primary ER+ breast cancer continues for at least 20 years. We aimed to identify clinical and molecular features associated with risk of recurrence after 10 years.

ER+ breast cancers from patients with and without recurrence were analysed with the BC360 NanoString Panel and an 87 gene targeted-exome panel. Frequency of clinical, pathologic and molecular characteristics was compared between cases (recurred between 10 and 20 years) and controls (no recurrence by 20 years) in the Very Late Recurrence (VLR) cohort. Analogous data from METABRIC were examined to confirm or refute findings.

VLR cases had larger tumours and higher node positivity. Both VLR and METABRIC cases had higher clinical treatment score at 5 years (CTS5). There was a trend for fewer GATA3 mutations in cases in both VLR and METABRIC but no statistically significant differences in mutation frequency. Cell cycle and proliferation genes were strongly expressed in VLR cases. Immune-related genes and cell cycle inhibitors were highly expressed in controls. Neither of these changes were significant after correction for multiple testing.

Clinicopathologic features are prognostic beyond 10 years. Conversely, molecular features, such as copy number alterations, TP53 mutations and intrinsic subtype which have early prognostic significance, have little prognostic value after 10 years.

The Clinical Treatment Score post-5 years (CTS5) is an easy-to-use tool estimating the late distant recurrence (LDR) risk in patients with hormone receptor-positive breast cancer after 5 years of endocrine therapy (ET). Apart from evaluating the prognostic value and calibration accuracy of CTS5, the aim of this study is to clarify if this score is able to identify patients at higher risk for LDR who will benefit from extended ET.

Prognostic power, calibration, and predictive value of the CTS5 was tested in patients of the prospective ABCSG-06 and -06a trials (n = 1254 and 860 patients, respectively). Time to LDR was analyzed with Cox regression models.

Higher rates of LDR in the years five to ten were observed in high- and intermediate-risk patients compared to low-risk patients (HR 4.02, 95%CI 2.26-7.15, p < 0.001 and HR 1.93, 95%CI 1.05-3.56, p = 0.035). An increasing continuous CTS5 was associated with increasing LDR risk (HR 2.23, 95% CI 1.74-2.85, p < 0.001). Miscalibration of CTS5 in high-risk patients could be observed. Although not reaching significance, high-risk patients benefitted the most from prolonged ET with an absolute reduction of the estimated 5-year LDR of - 6.1% (95%CI - 14.4 to 2.3).

The CTS5 is a reliable prognostic tool that is well calibrated in the lower and intermediate risk groups with a substantial difference of expected versus observed LDR rates in high-risk patients. While a numerical trend in favoring prolonged ET for patients with a higher CTS5 was found, a significantly predictive value for the score could not be confirmed.

ABCSG-06 trial (NCT00309491), ABCSG-06A7 1033AU/0001 (NCT00300508).

EMIT-1 is a national, observational, single-arm trial designed to assess the value of the Prosigna, Prediction Analysis of Microarray using the 50 gene classifier (PAM50)/Risk of Recurrence (ROR), test as a routine diagnostic tool, examining its impact on adjuvant treatment decisions, clinical outcomes, side-effects and cost-effectiveness. Here we present the impact on treatment decisions.

Patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative pT1-pT2 lymph node-negative early breast cancer (EBC) were included. The Prosigna test and standard histopathology assessments were carried out. Clinicians' treatment decisions were recorded before (pre-Prosigna) and after (post-Prosigna) the Prosigna test results were disclosed.

Of 2217 patients included, 2178 had conclusive Prosigna results. The pre-Prosigna treatment decisions were: no systemic treatment (NT) in 27% of patients, endocrine treatment alone (ET) in 38% and chemotherapy (CT) followed by ET (CT + ET) in 35%. Post-Prosigna treatment decisions were 25% NT, 51% ET and 24% CT + ET, respectively. Adjuvant treatment changed in 28% of patients, including 21% change in CT use. Among patients assigned to CT + ET pre-Prosigna, 45% were de-escalated to ET post-Prosigna. Of patients assigned to ET, 12% were escalated to CT + ET and 8% were de-escalated to NT; of those assigned to NT, 18% were escalated to ET/CT + ET. CT was more frequently recommended for patients aged ≤50 years. In the subgroup with pT1c-pT2 G2 and intermediate Ki67 (0.5-1.5× local laboratory median Ki67 score), the pre-Prosigna CT treatment decision varied widely across hospitals (3%-51%). Post-Prosigna, the variability of CT use was markedly reduced (8%-24%). The correlation between Ki67 and ROR score within this subgroup was poor (r = 0.25-0.39). The median ROR score increased by increasing histological grade, but the ROR score ranges were wide (for G1 0-79, G2 0-90, G3 16-94).

The Prosigna test result changed adjuvant treatment decisions in all EBC clinical risk groups, markedly decreased the CT use for patients categorized as higher clinical risk pre-Prosigna and reduced treatment decision discrepancies between hospitals.

The Oncotype DX Breast RS test has been adopted in Scotland and has been the subject of a large population-based study by a Scottish Consensus Group to assess the uptake of the recurrence score (RS), evaluate co-variates associated with the RS and to analyse the effect it may have had on clinical practice.

Pan-Scotland study between August 2018-August 2021 evaluating 833 patients who had a RS test performed as part of their diagnostic pathway. Data was extracted retrospectively from electronic records and analysis conducted to describe change in chemotherapy administration (by direct comparison with conventional risk assessment tools), and univariate/multivariate analysis to assess relationship between covariates and the RS.

Chemotherapy treatment was strongly influenced by the RS (p < 0.001). Only 30 % of patients received chemotherapy treatment in the intermediate and high risk PREDICT groups, where chemotherapy is considered. Additionally, 55.5 % of patients with a high risk PREDICT had a low RS and did not receive chemotherapy. There were 17 % of patients with a low risk PREDICT but high RS who received chemotherapy. Multivariate regression analysis showed the progesterone receptor Allred score (PR score) to be a strong independent predictor of the RS, with a negative PR score being associated with high RS (OR 4.49, p < 0.001). Increasing grade was also associated with high RS (OR 3.81, p < 0.001). Classic lobular pathology was associated with a low RS in comparison to other tumour pathology (p < 0.01). Nodal disease was associated with a lower RS (p = 0.012) on univariate analysis, with menopausal status (p = 0.43) not influencing the RS on univariate or multivariate analysis.

Genomic assays offer the potential for risk-stratified decision making regarding the use of chemotherapy. They can help reduce unnecessary chemotherapy treatment and identify a subgroup of patients with more adverse genomic tumour biology. A recent publication by Health Improvement Scotland (HIS) has updated guidance on use of the RS test for NHS Scotland. It suggests to limit its use to the intermediate risk PREDICT group. Our study shows the impact of the RS test in the low and high risk PREDICT groups. The implementation across Scotland has resulted in a notable shift in practice, leading to a significant reduction in chemotherapy administration in the setting of high risk PREDICT scores returning low risk RS. There has also been utility for the test in the low risk PREDICT group to detect a small subgroup with a high RS. We have found the PR score to have a strong independent association with high risk RS. This finding was not evaluated by the key RS test papers, and the potential prognostic information provided by the PR score as a surrogate biomarker is an outstanding question that requires more research to validate.

BCI (H/I) has been shown to predict extended endocrine therapy (EET) benefit. We examined BCI (H/I) for EET benefit prediction in NSABP B-42, which evaluated extended letrozole therapy (ELT) in patients with hormone receptor-positive breast cancer after 5 years of ET.

A stratified Cox model was used to analyze RFI as the primary endpoint, with DR, BCFI, and DFS as secondary endpoints. Because of a nonproportional effect of ELT on DR, time-dependent analyses were performed.

The translational cohort included 2,178 patients (45% BCI (H/I)-High, 55% BCI (H/I)-Low). ELT showed an absolute 10-year RFI benefit of 1.6% (P = 0.10), resulting in an underpowered primary analysis (50% power). ELT benefit and BCI (H/I) did not show a significant interaction for RFI (BCI (H/I)-Low: 10 years absolute benefit 1.1% [HR, 0.70; 95% confidence interval (CI), 0.43-1.12; P = 0.13]; BCI (H/I)-High: 2.4% [HR, 0.83; 95% CI, 0.55-1.26; P = 0.38]; Pinteraction = 0.56). Time-dependent DR analysis showed that after 4 years, BCI (H/I)-High patients had significant ELT benefit (HR = 0.29; 95% CI, 0.12-0.69; P < 0.01), whereas BCI (H/I)-Low patients were less likely to benefit (HR, 0.68; 95% CI, 0.33-1.39; P = 0.29; Pinteraction = 0.14). Prediction of ELT benefit by BCI (H/I) was more apparent in the HER2- subset after 4 years (ELT-by-BCI (H/I) Pinteraction = 0.04).

BCI (H/I)-High versus BCI (H/I)-Low did not show a statistically significant difference in ELT benefit for the primary endpoint (RFI). However, in time-dependent DR analysis, BCI (H/I)-High patients experienced statistically significant benefit from ELT after 4 years, whereas (H/I)-Low patients did not. Because BCI (H/I) has been validated as a predictive marker of EET benefit in other trials, additional follow-up may enable further characterization of BCI's predictive ability.

Distant metastasis is the leading cause of death in breast cancer (BC). The timing of distant metastasis differs according to subtypes of BCs and there is a need for identification of biomarkers for the prediction of early and late metastasis. To identify biomarker candidates whose abundance level can discriminate metastasis types, we performed a high-throughput proteomics assay using tissue samples from BCs with no metastasis, late metastasis, and early metastasis, processed data with machine learning-based feature selection, and found that low VWA5A could be responsible for shorter duration of metastasis-free interval. Low expression of VWA5A gene in METABRIC cohort was associated with poor survival in BCs, especially in hormone receptor (HR)-positive BCs. In-vitro experiments confirmed tumor suppressive effect of VWA5A on BCs in HR+ and triple-negative BC cell lines. We found that expression of VWA5A can be assessed by immunohistochemistry (IHC) on archival tissue samples. Decreasing nuclear expression of VWA5A was significantly associated with advanced T stage and lymphatic invasion in consecutive BCs of all subtypes. We discovered lower expression of VWA5A as the potential biomarker for metastasis-prone BCs, and our results support the clinical utility of VWA5A IHC, as an adjunctive tools for prognostication of BCs.

Breast cancer is heterogeneous and differs substantially across different tumors (intertumor heterogeneity) and even within an individual tumor (intratumor heterogeneity). Gene-expression profiling has considerably impacted our understanding of breast cancer biology. Four main "intrinsic subtypes" of breast cancer (i.e., luminal A, luminal B, HER2-enriched, and basal-like) have been consistently identified by gene expression, showing significant prognostic and predictive value in multiple clinical scenarios. Thanks to the molecular profiling of breast tumors, breast cancer is a paradigm of treatment personalization. Several standardized prognostic gene-expression assays are presently being used in the clinic to guide treatment decisions. Moreover, the development of single-cell-level resolution molecular profiling has allowed us to appreciate that breast cancer is also heterogeneous within a single tumor. There is an evident functional heterogeneity within the neoplastic and tumor microenvironment cells. Finally, emerging insights from these studies suggest a substantial cellular organization of neoplastic and tumor microenvironment cells, thus defining breast cancer ecosystems and highlighting the importance of spatial localizations.

Accurate prediction of the risk of recurrence is crucial for optimal treatment decisions in hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer. The GenesWell BCT is a molecular assay to predict the 10-year risk of distant metastasis. In this study, we evaluated the long-term prognostic value of the GenesWell BCT assay.

The BCT score was assessed in patients with HR-positive/HER2-negative early breast cancer who did not receive chemotherapy. We compared the 15-year distant metastasis-free survival (DMFS) between risk groups classified based on the BCT score. The risk of early (0-5 years) and late (5-15 years) recurrence was evaluated based on the BCT score classification.

According to the BCT score, 366 patients from Japan and Korea were categorized as BCT low risk (83.6%) and high risk (16.4%) for distant metastasis. Median follow-up time was 17.4 years. The 15-year DMFS rate was significantly lower in the BCT high-risk group (63.3%) than in the BCT low-risk group (93.6%) (P < 0.001). The BCT risk group was an independent prognostic factor for 15-year DMFS (hazard ratio, 4.59; 95% confidence interval 2.13-9.88; P < 0.001). Furthermore, the BCT score was a significant predictor of late recurrence (5-15 years) in patients aged ≤ 50 years and those aged > 50 years, and added prognostic information to traditional clinical prognostic factors.

The BCT score can identify patients at low risk for recurrence who may not require adjuvant chemotherapy or extended endocrine therapy, regardless of age.

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.

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.

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.

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.

In this review, the evolving role of currently available genomic assays for hormone receptor-positive, early-stage breast cancer in the selection of patients for extended adjuvant endocrine therapy will be discussed.

Several studies have investigated the prognostic performance of the Oncotype DX, Breast Cancer Index (BCI), Prosigna, and EndoPredict genomic assays in the late recurrence setting (>5 years after diagnosis), beyond standardly used clinicopathologic parameters, with mixed results. Recently, BCI has also been validated to predict the likelihood of benefit from extended endocrine therapy, though certain data limitations may need to be addressed to justify routine use in clinical practice.

Even after 5 years of adjuvant endocrine therapy, patients with hormone receptor-positive breast cancer have a significant risk for late recurrence, including distant metastases, that might be prevented with longer durations of endocrine therapy. However, the added toxicity and variable benefit derived from extended endocrine therapy make optimal patient selection crucial. Genomic assays are in development to risk-stratify patients for late recurrence and determine efficacy of extended endocrine therapy, with the aim to help guide extended endocrine therapy decisions for clinicians and individualize treatment strategies for patients.

The majority of breast cancers are oestrogen receptor-positive (ER+). In ER+ cancers, oestrogen acts as a disease driver, so these tumours are likely to be susceptible to endocrine therapy (ET). ET works by blocking the hormone's synthesis or effect. A significant number of patients diagnosed with breast cancer will have the spread of tumour cells into regional lymph nodes either at the time of diagnosis, or as a recurrence some years later. Patients with node-positive disease have a poorer prognosis and can respond less well to ET. The nodal metastases may be genomically similar or, as is becoming more evident, may differ from the primary tumour. However, nodal metastatic disease is often not assessed, and treatment decisions are almost always based on biomarkers evaluated in the primary tumour. This review will summarise the evidence in the field on ER+, node-positive breast cancer, including diagnosis, treatment, prognosis and predictive tools.

Breast cancer is the leading cause of cancer in women in Spain and its annual incidence is rapidly increasing. Thanks to the screening programs in place, nearly 90% of breast cancer cases are detected in early and potentially curable stages, despite the COVID-19 pandemic possibly having impacted these numbers (not yet quantified). In recent years, locoregional and systemic therapies are increasingly being directed by new diagnostic tools that have improved the balance between toxicity and clinical benefit. New therapeutic strategies, such as immunotherapy, targeted drugs, and antibody-drug conjugates have also improved outcomes in some patient subgroups. This clinical practice guideline is based on a systematic review of relevant studies and on the consensus of experts from GEICAM, SOLTI, and SEOM.

The risk of late distant recurrence (LDR) of estrogen receptor (ER)-positive breast cancer continues even after 5 years of endocrine treatment. Clinical Treatment Score after 5 years (CTS5) was developed and validated as a tool to assess the risk of LDR using data from Tamoxifen, Arimidex Alone or in Combinations (ATAC) and Breast International Group 1-98 (BIG1-98) trials. This study aimed to externally validate CTS5 in a real-world cohort of patients treated at an academic center in Thailand.

The study was a retrospective analytical research study of early-stage, ER-positive breast cancer patients. The primary endpoint was LDR. The risk of LDR was determined using the CTS5 calculator. Cox regression model and Kaplan-Meier survival analysis were applied for prognostic validation of CTS5. Calibration was performed by comparing observed LDR to expected LDR using the Hosmer-Lemeshow (H-L) test.

A total of 323 women were included with a median follow-up period of 11.6 years. The rate of LDR was 10.8%. The CTS5 was prognostic for LDR. C-index of the area under the ROC curve was 0.672. There was no significant difference between actual and expected numbers of LDR with an observed (O) LDR events to expected (E) number of LDR events ratio of 0.99 (0.86-1.12) (H-L P = .79) indicating a proper calibration in this cohort.

Our study validated that CTS5 is accurate in predicting the risk of LDR in ER-positive breast cancer cases in Thai patients. Its performance seemed to be better in postmenopausal patients. CTS5 could be applied in routine clinical practice to improve decisions regarding prolonged endocrine therapy, particularly in resource-limited countries where molecular profiling are inaccessible.

Luminal breast cancers are hormone receptor (estrogen and/or progesterone) positive that are further divided into HER2-negative luminal A and HER2-positive luminal B subtypes. According to currently accepted convention, they represent the most common subtypes of breast cancer, accounting for approximately 70% of cases. Biomarkers play a critical role in the functional characterization, prognostication, and therapeutic prediction, rendering them indispensable for the clinical management of invasive breast cancer. Traditional biomarkers include clinicopathological parameters, which are increasingly extended by genetic and other molecular markers, enabling the comprehensive characterization of patients with luminal breast cancer. Liquid biopsies capturing and analyzing circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are emerging technologies that envision personalized management through precision oncology. This article reviews key biomarkers in luminal breast cancer and ongoing developments.

Stratification of recurrence risk is a cornerstone of early breast cancer diagnosis that informs a patient's optimal treatment pathway. Several tools exist that combine clinicopathological and molecular information, including multigene assays, which can estimate risk of recurrence and quantify the potential benefit of different adjuvant treatment modalities. While the tools endorsed by treatment guidelines are supported by level I and II evidence and provide similar prognostic accuracy at the population level, they can yield discordant risk prediction at the individual patient level. This review examines the evidence for these tools in clinical practice and offers a perspective of potential future risk stratification strategies. Experience from clinical trials with cyclin D kinase 4/6 (CDK4/6) inhibitors in the setting of hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) early breast cancer is provided as an illustrative example of risk stratification.

Breast cancer is the second most frequent cancer in the world. It is a heterogeneous disease and the leading cause of cancer mortality in women. Advances in molecular technologies allowed for the identification of new and more specifics biomarkers for breast cancer diagnosis, prognosis, and risk prediction, enabling personalized treatments, improving therapy, and preventing overtreatment, undertreatment, and incorrect treatment. Several breast cancer biomarkers have been identified and, along with traditional biomarkers, they can assist physicians throughout treatment plan and increase therapy success. Despite the need of more data to improve specificity and determine the real clinical utility of some biomarkers, others are already established and can be used as a guide to make treatment decisions. In this review, we summarize the available traditional, novel, and potential biomarkers while also including gene expression profiles, breast cancer single-cell and polyploid giant cancer cells. We hope to help physicians understand tumor specific characteristics and support decision-making in patient-personalized clinical management, consequently improving treatment outcome.

Tumor necrosis (TN) was associated with poor prognosis. However, the traditional classification of TN ignored spatial intratumor heterogeneity, which may be associated with important prognosis. The purpose of this study was to propose a new method to reveal the hidden prognostic value of spatial heterogeneity of TN in invasive breast cancer (IBC).

Multiphoton microscopy (MPM) was used to obtain multiphoton images from 471 patients. According to the relative spatial positions of TN, tumor cells, collagen fibers and myoepithelium, four spatial heterogeneities of TN (TN1-4) were defined. Based on the frequency of individual TN, TN-score was obtained to investigate the prognostic value of TN.

Patients with high-risk TN had worse 5-year disease-free survival (DFS) than patients with no necrosis (32.5% vs. 64.7%; P < 0.0001 in training set; 45.8% vs. 70.8%; P = 0.017 in validation set), while patients with low-risk TN had a 5-year DFS comparable to patients with no necrosis (60.0% vs. 64.7%; P = 0.497 in training set; 59.8% vs. 70.8%; P = 0.121 in validation set). Furthermore, high-risk TN "up-staged" the patients with IBC. Patients with high-risk TN and stage I tumors had a 5-year DFS comparable to patients with stage II tumors (55.6% vs. 62.0%; P = 0.565 in training set; 62.5% vs. 66.3%; P = 0.856 in validation set), as well as patients with high-risk TN and stage II tumors had a 5-year DFS comparable to patients with stage III tumors (33.3% vs. 24.6%; P = 0.271 in training set; 44.4% vs. 39.3%; P = 0.519 in validation set).

TN-score was an independent prognostic factor for 5-year DFS. Only high-risk TN was associated with poor prognosis. High-risk TN "up-staged" the patients with IBC. Incorporating TN-score into staging category could improve its performance to stratify patients.

We review key topics in the management of estrogen receptor (ER)-positive human epidermal growth factor receptor 2-negative breast cancer. The single biggest challenge in management of this disease is late relapse, and we review new methods for identifying which patients are at risk of late relapse and potential therapeutic approaches in clinical trials. CDK4/6 inhibitors have become a standard treatment option for high-risk patients in both the adjuvant setting and the first-line metastatic setting, and we review data on optimal treatment after progression on CDK4/6 inhibitors. Targeting the estrogen receptor remains the single most effective way of targeting the cancer, and we review the developments in new oral selective ER degraders that are becoming a standard of care in cancers with ESR1 mutations and potential future directions.

Clinical decisions for (neo)adjuvant treatment in early breast cancer (eBC) have been based mostly on clinical factors over the last decades. We have reviewed development and validation of such assays in the HR + /HER2 eBC and discuss possible future directions in this field.

Increasing knowledge about the biology of hormone-sensitive eBC, based on the precise and reproducible multigene expression analysis, has led to a significant change in the treatment pathways and reduction of overtreatment in particular by chemotherapy in HR + /HER2 eBC with up to 3 positive lymph nodes based on results from several retrospective-prospective trials used several genomic assays and in particular prospective trials (TAILORx, RxPonder, MINDACT, and ADAPT used OncotypeDX® and Mammaprint®). Precise evaluation of tumor biology together with endocrine responsiveness assessment appears as promising tools for individualized treatment decisions together with clinical factors and menopausal status in early hormone-sensitive/HER2-negative breast cancer.

Through the understanding of multiple etiologies, pathologies, and disease progression trajectories, breast cancer shifted historically from a singular malignancy of the breast to a complex of molecular/biological entities, translating into individualized disease-modifying treatments. As a result, this led to various de-escalations of treatment compared with the gold standard in the era preceding systems biology: radical mastectomy. Targeted therapies have minimized morbidity from the treatments and mortality from the disease. Biomarkers further individualized tumor genetics and molecular biology to optimize treatments targeting specific cancer cells. Landmark discoveries in breast cancer management have evolved through histology, hormone receptors, human epidermal growth factor, single-gene prognostic markers, and multigene prognostic markers. Relevant to the reliance on histopathology in neurodegenerative disorders, histopathology evaluation in breast cancer can serve as a marker of overall prognosis rather than predict response to therapies. This chapter reviews the successes and failures of breast cancer research through history, with focus on the transition from a universal approach for all patients to divergent biomarker development and individualized targeted therapies, discussing future areas of growth in the field that may apply to neurodegenerative disorders.

Most metastatic recurrences of triple negative breast cancer (TNBC) occur within five years of diagnosis, yet late relapses of TNBC (lrTNBC) do occur. Our objective was to develop a risk prediction model of lrTNBC using readily available clinicopathologic and sociodemographic features.

We included patients diagnosed with stage I-III TNBC between 1998 and 2012 at ten academic cancer centers. lrTNBC was defined as relapse or mortality greater than 5 years from diagnosis. Features associated with lrTNBC were included in a multivariable logistic model using backward elimination with a p < 0.10 criterion, with a final multivariable model applied to training (70%) and independent validation (30%) cohorts.

A total 2210 TNBC patients with at least five years follow-up and no relapse before 5 years were included. In final multivariable model, lrTNBC was significantly associated with higher stage at diagnosis (adjusted Odds Ratio [aOR] for stage III vs I, 10.9; 95% Confidence Interval [CI], 7.5-15.9; p < 0.0001) and BMI (aOR for obese vs normal weight, 1.4; 95% CI, 1.0-1.8; p = 0.03). Final model performance was consistent between training (70%) and validation (30%) cohorts.

A risk prediction model incorporating stage, BMI, and age at diagnosis offers potential utility for identification of patients at risk of development of lrTNBC and warrants further investigation.

Neoadjuvant endocrine treatment (NET) associates to satisfactory rates of breast conservative surgery and conversions from inoperable to operable hormone receptor-positive (HR+)/HER2-negative breast cancer (BC), with less toxicities than neoadjuvant chemotherapy (NACT) and similar outcomes. Hence, it has been proposed as a logical alternative to NACT in patients with HR+/HER2- BC candidate to a neoadjuvant approach. Nevertheless, potential barriers to the widespread use of NET include the heterogeneous nature of patient response coupled with the long duration needed to achieve a clinical response. However, interest in NET has significantly increased in the last decade, owing to more in-depth investigation of several biomarkers for a more adequate patient selection and on-treatment benefit monitoring, such as PEPI score, Ki67 and genomic assays. This review is intended to describe the state-of-the-art regarding NET, its future perspectives and potential integration with molecular biomarkers for the optimal selection of patients, regimen and duration of (neo)adjuvant treatments.

The increasing understanding of breast cancer biology has provided the basis for the development of multigene signatures aimed to improve the capability of clinicians to assess patients' prognostication and risk stratification. Incorporating these tools in clinical practice has profoundly impacted on the decision-making process for the adjuvant therapy of patients with ER+/HER2- early breast cancer and the results from prospective adjuvant trials have strengthened the clinical utility of multigene signatures in this setting. In July 2019, Lombardy was the first Region in Italy to reimburse genomic testing for patients with ER+/HER2- early breast cancer. Three years later, a group of investigators from six referral Cancer Centers in Lombardy convened to debate the use of multigene signatures in clinical practice and share their own experience with the tests after reimbursement. Here, we reviewed relevant data on the role of multigene signatures in tailoring adjuvant chemotherapy for patients with ER+/HER2- early breast cancer and discussed about the optimal use of these assays in current clinical practice. As the treatment landscape of early breast cancer evolves and novel questions about the possible additional applications of multigene assays arise, we also provide our viewpoint on the potential implementation of the assays in the evolving scenario ER+/HER2- early breast cancer treatment.

One of the current challenges in breast cancer is the appropriate treatment of invasive lobular breast cancer (ILC) and defining the high-risk group within ILC. The biological character of ILC typically translates to a good prognosis, however, several studies have indicated that the long-term prognosis is worse than for patients diagnosed with the more commonly invasive ductal carcinoma. Many genomic tests are now available to determine whether those patients are at high risk (HR) and enable tailored treatment. Unfortunately, most of the studies in which these genomic tests have been evaluated entail retrospective analysis of a prospective trial.

This review focuses on the validation of the available genomic assays based on trials performed in ILC patients, where in some instances, the various subtypes of ILC (classical, pleomorphic, and non-classic type) were taken into account.

Using Oncotype DX in retrospective studies, only 1.3%-8% of ILC tumors were categorized as HR tumors. For MammaPrint, 24% of patients were classified as HR, which was associated with poor outcome. In a recent sub-analysis of the MINDACT study comprising 487 ILC patients, 16.2% were high genomic risk. EndoPredict, Prosigna Breast Cancer Prognostic Gene Signature Assay, and the Breast Cancer Index have been validated in patients receiving only endocrine treatment.

Although ILC accounts for the second most common breast cancer subtype in women, none of these tests encompass tumor morphology in their algorithms. Prospective studies on ILC with genomic assays are warranted given the various subtypes of and treatment options for this underestimated, but frequently occurring cancer.

Genomic assays can be employed in ILC patients to predict the risk of recurrence and identify those patients who might benefit from chemotherapy in addition to their standard treatment regimen.

Ovarian function suppression (OFS) is a potentially life-saving treatment for young women diagnosed with high-risk hormonal-receptor (HR)+ early breast cancer (EBC), albeit one associated with significant side effects that may adversely affect quality of life. Of particular concern, this article raises a few borderline indications that were largely unaddressed in pivotal clinical trials but are still commonly encountered in daily practice. These, referred to here as 'borderline indications of OFS' remain a source of uncertainty for patients and physicians and are concisely addressed in this article.

The purpose of this study was to evaluate the treatment outcomes of estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) breast cancer according to the risk group using EndoPredict (EP) score.

Between 2015 and 2019, 207 patients with ER+/HER2- pN0-N1 early breast cancer who underwent surgery, EP test, and adjuvant radiotherapy were accrued. The EPclin score, which combines the molecular EP score with nodal status and tumor size, was calculated, and patients were divided into EPclin low- or high-risk groups by the cutoff value of 3.3.

There were 154 and 53 patients in the EPclin low- and high-risk groups, respectively. Forty-one patients (81.1%) of the high-risk group received adjuvant chemotherapy, while only 1 (0.6%) of the low-risk group did. With a median follow-up of 54.1 months (range 8.2-76.6), the 5-year disease-free survival rates of low- and high-risk groups were 100% and 88.9%, respectively (p < 0.001).

The EPclin score was associated with recurrences in ER+/HER2- early breast cancer.

In patients with early-stage endocrine receptor-positive (ER+) breast cancer (BC), adjuvant endocrine therapy (ET) for 5 years is the standard of care. However, for some patients, the risk of recurrence remain high for up to 15 years after diagnosis and extended ET beyond 5 years may be a reasonable option. Nevertheless, this strategy significantly increases the occurrence of side effects. Here we summarize the available evidence from randomized clinical trials on the efficacy and safety profile of extended ET and discuss available clinical and genomic tools helpful to select eligible patients in daily clinical practice.