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.

RxPONDER showed that in postmenopausal women with early-stage hormone receptor + /HER2- breast cancer (BC) with 1-3 positive axillary lymph nodes (LN) and a recurrence score ≤ 25, the addition of chemotherapy to endocrine therapy did not improve distant recurrence-free survival. We sought to evaluate Oncotype DX recurrence score (ODX RS) distribution in LN negative and LN positive patients aged ≥ 50 years (y) and to determine clinicopathologic factors associated with RS.

ODX RS, demographic, and pathologic information was collected for patients with ER + /HER2- BC with 0 (patients < 50y) or 0-3 positive (patients ≥ 50y) LN treated at our institution between January 2021 and December 2022. Statistical analyses were conducted using Pearson chi-square and two-tailed t tests.

The study cohort included 2378 BC from 2285 women. Among women ≥ 50y, there was no significant difference in RS distribution between pN0, pN1mi, and pN1a patients; with 85.4%, 86.5%, and 81% having a RS ≤ 25, respectively. Among LN + women ≥ 50y, RS > 25 was significantly associated with higher grade (P = .001), lower ER (P = .007), and lower PR (P < .001). Among LN- women ≥ 50y, RS > 25 was significantly associated with higher grade (P < .001), lower ER (P < .001), and lower PR (P < .001).

ODX RS distribution among LN + and LN- women aged ≥ 50y was similar. In this population, RS is significantly associated with tumor grade, ER, and PR, regardless of LN status. In our post-RxPONDER era cohort, over 80% of women aged ≥ 50y with early-stage ER + /HER2- BC with ≤ 3 positive axillary LN would be spared chemotherapy based on RS, regardless of nodal status.

This study evaluates the reproducibility of the IRSN-23 model, which classifies patients into highly chemotherapy-sensitive (Gp-R) or less-sensitive (Gp-NR) groups based on immune-related gene expression using DNA microarray analysis, and its impact on breast cancer subtype classification.

Tumor tissues from 146 breast cancer patients receiving neoadjuvant chemotherapy (paclitaxel-FEC) ± trastuzumab at Osaka University Hospital (OUH) were used to classify patients into Gp-R or Gp-NR using IRSN-23. The ability to predict a pathological complete response (pCR) was assessed and the results were validated with independent public datasets (N = 1282).

In the OUH dataset, the pCR rate was significantly higher in the Gp-R group than in the Gp-NR group without trastuzumab (29 versus 1%, P = 1.70E-5). In all validation sets without anti-HER2 therapy, the pCR rate in the Gp-R group was significantly higher than that in the Gp-NR group. The pooled analysis of the validation set showed higher pCR rates in the Gp-R group than in the Gp-NR group, both without (N = 1103, 40 versus 12%, P = 2.02E-26) and with (N = 304, 49 versus 35%, P = 0.017) anti-HER2 therapy. Collaboration analyses of IRSN-23 and Oncotype Dx or PAM50 could identify highly chemotherapy-sensitive groups and refine breast cancer subtype classification based on the tumor microenvironment (offensive factor-PAM50 and defensive factor-IRSN-23), and the immune subtype was correlated with a better prognosis after NAC.

This study offers new validation analyses of IRSN-23 in predicting chemotherapy efficacy, showing high reproducibility. The findings indicate the clinical value of using IRSN-23 for refining breast cancer subtype classification, with implications for personalized treatment strategies and improved patient outcomes.

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.

Medical advancements in breast cancer are truly remarkable. Especially in recent years, numerous new therapeutics have been approved and surgical strategies have been de-escalated for specific patient groups. In the therapeutic setting, CDK4/6 inhibitors as oral maintenance therapy in early breast cancer and immune checkpoint inhibitors (Pembrolizumab) for triple-negative breast cancer (BC) are noteworthy. In the surgical field, prospective randomized controlled trials have currently explored the possibility to deescalate axillary surgery by omitting sentinel lymph node excision (INSEMA, SOUND). As a result, there have been significant improvements in prognosis and a reduction in surgical morbidity for patients. Many exciting trials are underway, and it remains to be seen whether antibody-drug conjugates beyond trastuzumab emtansine, will find their way into the treatment lines for early-stage BC. Furthermore, the integration of artificial intelligence in both diagnostics and treatment recommendation evaluation is a promising area with great potential.

The Oncotype DX (ODX) recurrence score (RS) is prognostic and predictive of chemotherapy benefit in patients with hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer. Data on the distribution of germline BRCA1 and/or BRCA2 pathogenic variants (gBRCA PV) by RS are limited. This retrospective, real-world study explored demographics, clinical characteristics, gBRCA testing rates, and gBRCA PV prevalence in HR-positive/HER2-negative stage I-III breast cancer, stratified by RS.

Deidentified patient data (from 1 January 2011 to 30 September 2022) from US electronic health records in a nationwide database were used. Patients aged ≥ 18 years with HR-positive/HER2-negative breast cancer and a known ODX RS were included. Demographics, clinical characteristics, and genetic testing rates were compared in patients with low, intermediate, and high tumor RS. gBRCA PV prevalence was compared across categories in patients who underwent genetic testing.

Of 3637 patients (median age: 62 years), 950 (26.1%) had low, 2155 (59.3%) had intermediate, and 532 (14.6%) had high tumor RS. Despite increases in genetic testing over time, gBRCA status was determined in only 31.5% (n = 1147/3637) of patients. Among tested patients, 37/1147 (3.2%) had gBRCA PV; median age was lower in gBRCA PV carriers than in noncarriers (52 versus 56 years; p = 0.034); tumors from gBRCA PV carriers had significantly higher grade (p = 0.002) and median RS (p = 0.001) than tumors from noncarriers; prevalence of gBRCA PV was highest among tested patients with high tumor RS (n = 14/185; 7.6%), but gBRCA PVs were identified among patients with intermediate (n = 19/674; 2.8%) and low (n = 4/288; 1.4%) tumor RS.

Prevalence of gBRCA PV was highest among patients with high tumor RS, but not negligible in patients with intermediate and low tumor RS. Wider implementation of genetic testing, irrespective of ODX RS, could help optimize the management of patients with HR-positive/HER2-negative early breast cancer.

To update the ASCO evidence-based recommendations on the use of sentinel lymph node biopsy (SLNB) in patients with early-stage breast cancer treated with initial surgery.

ASCO convened an Expert Panel to develop updated recommendations based on a systematic literature review (January 2016-May 2024).

Eleven randomized clinical trials (14 publications), eight meta-analyses and/or systematic reviews, and one prospective cohort study met the inclusion criteria for this systematic review. Expert Panel members used available evidence and informal consensus to develop practice recommendations.

Clinicians should not recommend routine SLNB in select patients who are postmenopausal and ≥50 years of age and with negative findings on preoperative axillary ultrasound for grade 1-2, small (≤2 cm), hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer and who undergo breast-conserving therapy. Clinicians may offer postmastectomy radiation (RT) with regional nodal irradiation (RNI) and omit axillary lymph node dissection (ALND) in patients with clinically node-negative invasive breast cancer ≤5 cm who receive mastectomy and have one to two positive sentinel nodes. Clinicians may offer SLNB in patients who have cT3-T4c or multicentric tumors (clinically node-negative) or ductal carcinoma in situ treated with mastectomy, and in patients who are obese, male, or pregnant, or who have had prior breast or axillary surgery. Clinicians should not recommend ALND for patients with early-stage breast cancer who do not have nodal metastases, and clinicians should not recommend ALND for patients with early-stage breast cancer who have one or two sentinel lymph node metastases and will receive breast-conserving surgery and whole-breast RT with or without RNI.Additional information is available at www.asco.org/breast-cancer-guidelines.This guideline has been endorsed by the American Society for Radiation Oncology (ASTRO).

Breast cancer remains a major global health challenge. While advances in precision oncology have contributed to improvements in patient outcomes and provided a deeper understanding of the biological mechanisms that drive the disease, historically, research and patients' allocation to treatment have heavily relied on single-omic approaches, analyzing individual molecular dimensions such as genomics, transcriptomics, or proteomics. While these have provided deep insights into breast cancer biology, they often fail to offer a complete understanding of the disease's complex molecular landscape.

In this review, the authors explore the recent advancements in multi-omic research in the realm of breast cancer and use clinical data to show how multi-omic integration can offer a more holistic understanding of the molecular alterations and their functional consequences underlying breast cancer.

The overall developments in multi-omic research and AI are expected to complement precision diagnostics through potentially refining prognostic models, and treatment selection. Overcoming challenges such as cost, data complexity, and lack of standardization is crucial for unlocking the full potential of multi-omics and AI in breast cancer patient care to enable the advancement of personalized treatments and improve patient outcomes.

Hormone receptor-positive (HR+)/HER2-negative (HER2-) early-stage breast cancers (EBC) are treated with adjuvant endocrine therapy (ET), with chemotherapy (CT) reserved for high-risk cases. Obesity is linked to increased recurrence risk. The Oncotype DX® assay predicts prognosis and CT benefit. The PRO BONO study evaluated Oncotype DX test's impact on treatment decisions and explored associations between genomic risk, tumor features, and patient metabolic profiles.

Patients with HR+ /HER2-EBC undergoing Oncotype DX testing were enrolled. Body mass index (BMI), tumor characteristics (ER, PR, Ki67, grading, size, nodal status), a large panel of metabolic analytes, and Oncotype DX Recurrence Score® (RS) results were collected. Treatment recommendations (ET vs CT-ET) were recorded pre- and post-Oncotype DX, and concordance was determined using Cohen's Kappa. Associations were tested using Chi-Square test and Spearman Correlation.

Of the 248 EBC patients (2019-2021), Oncotype DX testing reduced CT use by 47.7 %. Higher RS positively correlated with serum triglycerides and inversely with GIP (all p < 0.05). No significant association was found between patient BMI and RS result. Conversely, tumor size positively correlated with BMI (p = 0.0286) and with serum levels of leptin (p = 0.0079), PAI-1 (p = 0.0083), C-peptide (p = 0.0124), GIP (p = 0.0036), GLP-1 (p = 0.0476), glucagon (p = 0.0224), and insulin (p = 0.0327). A BMI≥ 30 and higher GLP-1 levels (>148.85pg/ml) were independently associated with increased odds of having larger tumor size (>2 cm).

Recurrence Score result significantly impacts treatment decisions in HR+ /HER2-EBC. RS result was not associated with BMI, although unfavorable metabolic profiles and obesity-related markers correlated with larger tumors. These findings highlight the need to further investigate the link between metabolic profiles and breast cancer biology.

Neoadjuvant chemotherapy (NAC) is now frequently utilized for earlier stage breast cancer. Historically, removing axillary lymph nodes (LN) has guided treatment decisions and reduced regional recurrence, yet its utility in clinically node-negative (cN0) patients following NAC has yet to be elucidated. This study evaluated the incidence of residual occult pathologic nodal disease after NAC in cN0 breast cancer and associated clinicopathologic risk factors.

A retrospective study of 249 cN0 patients who received NAC at our institution from 2010-2021 was performed. Clinical and pathologic tumor features were compared between 2 groups: persistent LN- versus LN+ after NAC.

The study group comprised 166 patients: 19 (11.4%) had pathologic LNs positive following NAC. Patients with LN+ (n = 19) versus LN- (n = 147) had greater mean clinical tumor size (P < .01), higher clinical T stage (P < .001), invasive lobular cancer (P < .01), lymphovascular invasion (P 0.01), and ER+ HER2- phenotype (P < .01). Conversely, LN- patients more likely had HER2+ tumors (P < .01) and in-breast pathologic complete response (P < .05). Sentinel LN biopsy (SLNB) obtained a mean of 3.8 LNs with 2 (1.2%) patients having ≥ypN2. At 46 months median follow-up, 1 (0.6%) axillary recurrence occurred.

There is a low incidence of both residual occult disease in the axilla and axillary recurrence in cN0 breast cancer patients following NAC. Many of these patients may avoid axillary surgery, or at a maximum, undergo SLNB alone with low concern for axillary recurrence.

This work was conducted in order to validate a pre-treatment quantitative ultrasound (QUS) and texture derivative analyses-based prediction model proposed in our previous study to identify responders and non-responders to neoadjuvant chemotherapy in patients with breast cancer. The validation cohort consisted of 56 breast cancer patients diagnosed between the years 2018 and 2021. Among all patients, 53 were treated with neoadjuvant chemotherapy and three had unplanned changes in their chemotherapy cycles. Radio Frequency (RF) data were collected volumetrically prior to the start of chemotherapy. In addition to tumour region (core), a 5 mm tumour-margin was also chosen for parameters estimation. The prediction model, which was developed previously based on quantitative ultrasound, texture derivative, and tumour molecular subtypes, was used to identify responders and non-responders. The actual response, which was determined by clinical and pathological assessment after lumpectomy or mastectomy, was then compared to the predicted response. The sensitivity, specificity, positive predictive value, negative predictive value, and F1 score for determining chemotherapy response of all patients in the validation cohort were 94%, 67%, 96%, 57%, and 95%, respectively. Removing patients who had unplanned changes in their chemotherapy resulted in a sensitivity, specificity, positive predictive value, negative predictive value, and F1 score of all patients in the validation cohort of 94%, 100%, 100%, 50%, and 97%, respectively. Explanations for the misclassified cases included unplanned modifications made to the type of chemotherapy during treatment, inherent limitations of the predictive model, presence of DCIS in tumour structure, and an ill-defined tumour border in a minority of cases. Validation of a model was conducted in an independent cohort of patient for the first time to predict the tumour response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivate, and molecular features in patients with breast cancer. Further research is needed to improve the positive predictive value and evaluate whether the treatment outcome can be improved in predicted non-responders by switching to other treatment options.

Guidelines recommend neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) for muscle-invasive bladder cancer (MIBC). Current recommendations do not consider genomic profiles, although the Basal/Squamous (Ba/Sq) subtype is less likely to respond to NAC compared to Urothelial-like (Uro) and Genomically Unstable (GU) subtypes. The aim of this study is to perform cost-effectiveness analyses of a de-escalated use of NAC in patients with Ba/Sq tumors and MIBC.

A cost-effectiveness analysis was performed using a decision analytic Markov model using a healthcare provider perspective. Treatment and prognosis probabilities originated from the Bladder Cancer Data Base, Sweden (BladderBaSe) 2.0. Information on molecular subtype and outcomes was retrieved from published studies, and quality-adjusted life year (QALY) data were obtained from the iROC trial. Costs were collected from the regional healthcare registers in Sweden, utility values were obtained from the literature, and outcomes are presented as incremental cost-effectiveness ratio (ICER). Scenario analyses, along with several one-way and probabilistic sensitivity analyses were performed to capture uncertainties.

At a 5-year time horizon, the model predicts that molecular subtype-based treatment has an ICER of 4,964 Euro/QALY (66,766 Swedish Krona/QALY), which is deemed cost-effective in the Swedish setting. At €7,427 (100,000 SEK) willingness-to-pay threshold, the molecular subtype-based treatment has a 65% probability of being cost-effective. The results were not sensitive to uncertainty analyses.

Molecular subtype-based treatment of MIBC, i.e., refraining from administering NAC to patients with Ba/Sq tumors, is cost-effective compared to the current treatment practices in Sweden.

Age stratification influences the clinicopathological features and survival outcomes of breast cancer. We aimed to understand the effect of age on gene variants in young Chinese women with breast cancer compared with those from The Cancer Genome Atlas (TCGA).

Enrolled patients ≤ 40 years old (N = 370) underwent germline or somatic genetic testing using a 32-gene hereditary cancer panel at Fujian Union Hospital. Significant alterations of germline and somatic genes were analyzed. The frequency of somatic variants was compared between enrolled patients and patients from TCGA who were divided into two groups (≤ 40 years and > 40 years).

Among the enrolled patients (median age 36; range 25-40), 335 underwent germline genetic testing and 174 underwent simultaneous somatic genetic testing. We detected 44 germline pathogenic/likely pathogenic variants in 42 (12.5%) patients, where BRCA1/2 was the most common gene (29.8.5%). Family history of first-degree relatives was significantly associated with pathogenic variants (p < 0.001). Somatic Tier I/II mutation frequency was like that of patients ≤ 40 from TCGA (N = 97). More PIK3CA and TP53 mutations in luminal A and basal-like tumors, respectively, were detected in young patients than in patients > 40 from TCGA (N = 975). No significant differences were observed in other breast cancer subtypes.

These results provide a spectrum of genomic alterations in young Chinese women and highlight different frequencies of gene variants in young Asian patients versus Western patients with breast cancer. Further research should explore the biological mechanism to provide more treatment strategies for young Asian women.

The past decade has seen the introduction of artificial intelligence (AI)-based approaches aimed at optimizing several workflows across many medical specialties. In clinical oncology, the most promising applications include those involving image analysis, such as digital pathology. In this Perspective, we provide a comprehensive examination of the developments in AI in digital pathology between 2019 and 2024. We evaluate the current landscape from the lens of technological innovations, regulatory trends, deployment and implementation, reimbursement and commercial implications. We assess the technological advances that have driven improvements in AI, enabling more robust and scalable solutions for digital pathology. We also examine regulatory developments, in particular those affecting in-house devices and laboratory-developed tests, which are shaping the landscape of AI-based tools in digital pathology. Finally, we discuss the role of reimbursement frameworks and commercial investment in the clinical adoption of AI-based technologies. In this Perspective, we highlight both the progress and challenges in AI-driven digital pathology over the past 5 years, outlining the path forward for its adoption into routine practice in clinical oncology.

Gene expression signatures (GES) are a powerful tool in oncology used for classification, prognostication, and therapeutic response prediction of malignancies. In this article, we review the disease site guidelines by the National Comprehensive Cancer Network that use GES for treatment planning and clinical use. We identified 4 cancer types for which treatment decisions are frequently influenced by GES. Future developments in the field of GES are likely to include expanded data sources to personalize radiation therapy dosing and predict response to immunotherapy. Ongoing challenges in GES may be addressed to ensure that all patients with cancer benefit from precision oncology.

Multigene prognostic genomic assays have become essential tools in the management of early breast cancer (BC), providing information that help in risk-stratification, to provide risk-adapted decision-making of adjuvant treatments. Clinical practice guidelines recommend refining the prognostic information provided by clinical and pathology features with the use of genomic tests, such as Oncotype DX®, to classify cancers into risk groups and inform adjuvant treatment strategies. However, the clinical value (i.e., prognostic and/or predictive) and applicability of these assays vary due to differences in the clinical setting, especially in those populations that were underrepresented in pivotal clinical trials. Oncotype DX® is a broadly utilized genomic test for breast cancer, having the highest level of supporting evidence to inform clinical practice. Our manuscript provides a comprehensive overview on this recurrence score assay, evaluates supporting evidence across patient populations, and discusses their impact on treatment decisions in those groups of patients underrepresented in pivotal clinical trials, where evidence is limited with the use of Oncotype DX.

The cure for early breast cancer (EBC) is increasing over the last decades due to the improvement of diagnosis and therapy. Individualization of cancer treatment in EBC requires constant optimization by implementing current guidelines. The AGO (working group gynecologic oncology) QS-Mamma initiative, a quality assurance program (QS) of the AGO Breast Committee, was introduced to provide insight in guideline adherence in real-world practice in Germany. We evaluated 10 years of QS-Mamma data to identify gaps and trends implementing those guidelines.

QS-Mamma is a retrospective sample survey providing a representative overview of the treatment landscape of breast cancer in Germany. The last six cohorts were analyzed over a period of 10 years. Across all cohorts, an average of 264 centers documented a total of n = 4,577 patients with EBC.

Testing for BRCA mutations in triple-negative patients increased significantly. Breast conserving surgery has been standard of care since the start of data collection; choice of surgical procedure depends primarily on tumor size and nodal status according to the patient's preference, if possible. Axillary intervention has shifted toward SLNE or targeted axillary procedures in patients with negative preoperative nodal staging. Neoadjuvant systemic therapy in operable EBC is established. Anthracycline administration in the adjuvant setting decreases. We noted an uptake on using platinum-containing CTx in TNBC, corresponding to AGO recommendations. Dual HER2 blockade is established in HER2-positive EBC with increased risk of relapse. Changes in guidelines are reflected in real-world data.

Guideline adherence in breast cancer care is high and new treatments and diagnostic options are implemented promptly. Finally, escalation and de-escalation of treatment depend on individual tumor characteristics resulting in the individual risk of recurrence. Guidelines should be flanked by real-world evidence to ensure and survey their impact.

The results of the TAILORx trial have shown that premenopausal patients with intermediate Oncotype Dx (ODx) recurrence score of 16-25 may benefit from adjuvant chemotherapy. In addition, the clinicopathological features showed the information complementary to ODx results. However, the characteristics may vary depending on menopausal status even in the same score. This study aimed to analyze the differences in the clinical characteristics by menopausal status.

This study conducted a retrospective analysis of 756 patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and node-negative breast cancer who underwent the ODx test from July 2013 to December 2020 at the Severance Hospital.

Of the 756 patients, 261 patients were postmenopausal, and 495 were premenopausal. The premenopausal patients with a midrange ODx had similar clinicopathological features as compared to those with a high ODx. Conversely, the postmenopausal patients with a midrange ODx did not show significantly different clinicopathological features from those with a low ODx, whereas a difference was seen as compared to those with a high ODx.

In this study, unlike the postmenopausal patients, some of the clinicopathological characteristics of the premenopausal patients with a midrange ODx were closer to those with a high ODx than those with a low ODx. In the premenopausal patients with a midrange ODx, considering the baseline characteristic itself, there was a significant difference between those with a low ODx when compared with postmenopausal patients. Therefore, more aggressive treatment decisions may be helpful in premenopausal patients with a midrange ODx.

Climate change is the greatest threat to human existence. Currently it impacts breast cancer care by disrupting treatment, by food poverty and economic hardship and through fossil fuel pollution which increases breast cancer incidence. These impacts are greatest in those already experiencing deprivation. However, healthcare (including breast cancer care) is not an innocent bystander in climate change. The carbon emissions of healthcare are equivalent to the continent of Africa with 1.5 billion people. Like all other enterprises healthcare has an obligation to move to net zero carbon emissions. Previously conducted studies of healthcare professionals have highlighted the role of guidance documents to facilitate climate engagement by them. This prompted the formation of an interdisciplinary group to review the intersection points between breast cancer care and planetary health. A solution tree of sustainable solutions for practicing clinicians is proposed which can be integrated into daily clinical practice and into their personal lives.

By analyzing the existing data of this study, a prediction tool for the overall breast cancer survival and disease-free survival (DFS) of elderly women was established.

Clinicopathologic data were collected from elderly women with BC who were admitted to the Tianjin Medical University Cancer Institute and Hospital from August 2014 to December 2017. Independent prognostic factors for BC in elderly patients were confirmed using the Cox proportional hazards model. Nomograms were developed with these factors for predicting the 3- and 5-year overall survival (OS) as well as DFS. The nomograms' discrimination ability and calibration were assessed through the area under the curve (AUC), concordance index (C-index), decision curve analysis (DCA), and calibration plots.

We enroled 889 elderly patients with BC, and the results showed that the 3-year OS rate was 93.4% (95%CI = 91.8%-95.1%), the 3-year DFS rate was 87.8% (95%CI = 85.7%-90.0%), the 5-year OS rate was 85.6% (95%CI = 83.3%-87.9%), and the 5-year DFS rate was 80.1%(95%CI = 77.5%-82.8%). The corrected C-indices of the OS and DFS nomograms were 0.799 and 0.667, respectively (95%CI = 0.767-0.830 and 0.632-0.702, respectively). Relatively high AUC values were shown by the nomograms for estimating OS and DFS. The DCA revealed that the constructed nomograms had net benefits for clinical application. The calibration curves demonstrated an excellent correspondence between the data predicted by the nomograms and the actual survival data. Survival curves indicated that risk stratification could differentiate OS and DFS.

This study developed novel and practical nomograms for individual prediction of DFS and OS in elderly BC patients. These nomograms can predict 3- and 5-year OS as well as DFS in the elderly BC patient population, thereby enabling personalized risk assessment and risk-based therapy.

In light of evolving evidence that some patients with node-positive estrogen receptor-positive (ER+) disease may receive less benefit from chemotherapy, this study reports 12-year outcomes of the C9741 trial overall, and by the sensitivity to endocrine therapy (SET2,3) test index, a biomarker measuring endocrine transcriptional activity, to identify patients most likely to benefit from dose-dense chemotherapy.

In all, 1,973 patients were randomly assigned to dose-dense versus conventional chemotherapy. Hazard ratios (HRs) for prognosis and for predictive interaction with chemotherapy schedule were estimated from Cox models of long-term disease-free survival (DFS) and overall survival (OS). SET2,3 was tested on the 682 banked RNA samples from ER+ cancers.

Dose-dense chemotherapy improved DFS in the overall study population by 23% (HR, 0.77 [95% CI, 0.66 to 0.90]) and OS by 20% (HR, 0.80 [95% CI, 0.67 to 0.95]); the benefits of dose-dense therapy were seen for ER+ and ER-negative subsets, without significant interaction between treatment arm and ER status. Low SET2,3 status was highly prognostic, but also predicted improved outcomes from dose-dense chemotherapy (interaction P = .0998 for DFS; 0.027 for OS), independent of menopausal status. Specifically, low endocrine transcriptional activity predicted benefit from dose-dense chemotherapy, whereas tumor burden and proliferation-driven signatures for molecular subtype classification did not.

At 12-year follow-up, C9741 confirmed the sustained long-term benefit of adjuvant dose-dense chemotherapy for node-positive breast cancer. SET2,3 identified patients with ER+ breast cancer who benefited from dose-dense chemotherapy, and specifically, this benefit was predicted by low endocrine activity in the cancer, rather than tumor burden, molecular subtype, or menopausal status.

Hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) tumors represent the most common types of early-stage breast cancer. However, their response to adjuvant systemic treatments varies widely due to tumor heterogeneity. Current decisions for adjuvant treatment rely heavily on clinical and pathological characteristics, which can sometimes lead to overtreatment. Accurately identifying patients who will benefit from adjuvant chemotherapy at an individual level remains a challenge. Multigene profiling assays are now widely used in clinics to better assess recurrence risk and chemotherapy response for HR+ disease. In this report, we examine the advantages and limitations of two widely used molecular profiling tests-Oncotype DX and Prosigna. Both Oncotype DX and Prosigna have been demonstrated to be effective prognostic tools in early breast cancer, with Oncotype DX also being validated as a predictive tool to guide chemotherapy decisions. We focus on studies that directly compare these molecular tests and discuss how their strengths can be leveraged to improve clinical decision-making for early-stage HR+ breast cancers. Finally, we highlight remaining knowledge gaps and propose directions for future research.

Breast cancer (BC) continues to pose a global health threat and presents challenges for treatment due to its high heterogeneity. Recent advancements in the understanding of mitochondrial permeability transition (MPT) and the regulatory roles of long non-coding RNAs (lncRNAs) offer potential insights for the stratification and personalized treatment of BC. Although the association between MPT and lncRNAs has not been widely studied, a few research studies have indicated a regulatory impact of lncRNAs on MPT, further deepening the understanding of the tumor. To identify reliable biomarkers associated with MPT for managing BC, bulk RNA-seq data of MPT-related lncRNAs acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project were utilized to assess BC patients. A scoring system, termed the MPT-related score (MPTRscore), was developed using LASSO-Cox regression on data from 1,029 BC patients from TCGA-BRCA. Meanwhile, the superior prognostic accuracy of the MPTRscore was demonstrated by comparing it with biomarkers, including PAM50 subtyping for standardization. Subsequently, a clinical prediction model was created by incorporating the MPTRscore and clinical variables. This analysis revealed two distinct MPTRscore groups characterized by different biomolecular processes, tumor microenvironment (TME) patterns, and clinical outcomes. The MPTRscore was further investigated through unsupervised consensus clustering of TCGA-BRCA based on MPTRscore-related prognostic genes. Additionally, the MPTRscore was identified as an independent prognostic factor for BC and showed guiding utility in immunotherapy and chemotherapy response. Specifically, patients with a low MPTRscore exhibited better prognosis and treatment responses compared to those with a high MPTRscore. Significantly, the relevance of clustering results and MPTRscore was found to be mediated by lncRNA transcript RP11-573D15.8-018. In conclusion, MPTRscore-related clusters were identified in BC, and an integrative score was developed as a biomarker for predicting BC prognosis and therapeutic response. Additionally, molecular interactions underlying the relationship between MPTRscore-related clusters and MPTRscore were uncovered, proving insights for BC stratification. These findings may aid in prognosis determination and therapeutic decision-making for BC patients.

The optimal adjuvant endocrine treatment in premenopausal patients with hormone receptor-positive, HER2-negative (HRpos/HER2neg) early breast cancer (eBC) remains debated, particularly the choice between aromatase inhibitors plus ovarian function suppression (AI + OFS) or tamoxifen (TAM) with or without additional OFS. This study assessed the use of adjuvant endocrine therapies for premenopausal patients with intermediate/high-risk HRpos/HER2neg eBC.

CLEAR-B (AGO-B-059; NCT05870813) was a retrospective study analyzing data, collected from January 2016 to June 2019 and from January 2022 to December 2023 during the certification process of breast centers in Germany. Premenopausal patients with HRpos/HER2neg intermediate/high-risk eBC were eligible. Patient and disease characteristics, in addition to recommended and received adjuvant treatments, were evaluated.

The number of registered patients was 3137, of whom 2789 had complete information on endocrine treatments (1717 for 2016-2019 and 1072 for 2022-2023). In 2016-2019, 8.4 % of the patients were recommended to be treated with AI + OFS, whereas in 2022-2023, the proportion of patients with a treatment recommendation for AI + OFS rose to 42.1 %. In 2016-2019, TAM monotherapy was most frequently recommended (80.8 %). Conversely, TAM + OFS was not commonly recommended (9.3 % in 2016-2019 and 16.5 % in 2022-2023). While no clear association between tumor stage and chosen endocrine therapy was found in 2016-2019, most patients with ≥stage IIA were recommended to be treated with AI + OFS in 2022-2023.

This analysis shows that treatment recommendation for AI + OFS in premenopausal patients with HRpos/HER2neg eBC increased relevantly in the past years, reflecting latest guideline recommendations.

Explaining gene expression profiling (GEP) test results to patients can be challenging. We examined the utility of two 8 min films about Oncotype DX and Prosigna to aid the knowledge and decision-making of women with early-stage oestrogen receptor positive (ER+) breast cancer.

Patients awaiting GEP test results completed an anxiety questionnaire and the intolerance of uncertainty scale (IUS) before randomisation and divided into Group A (standard verbal and/or written hospital information) or Group B (standard information plus GEP film). Prior to results, they were interviewed about their GEP test knowledge and how the recurrence risk helps determine treatment options. After the results consultation, participants answered two further questionnaires. Participating clinicians completed IUS scales and reported their satisfaction with the results discussions.

230/251 patients completed the study (Group A (n=106) and Group B (n=124)). The total knowledge score was higher in Group B (estimated between groups mean difference of 2.5 (95% CI:1.7 to 3.4) p<0.001). Most treatment decisions adhered to recommended risk of recurrence thresholds, although patients with higher trait anxiety were more likely to make less apparently rational decisions OR=0.93 (95%CI 0.88 to 0.97) p=0.002 (163/230; 70.8% received ET alone; 65/230; 28% ET plus chemotherapy, and two sought second opinions). Clinicians reported slightly longer consultations for Group A participants who tended to ask more difficult and unexpected questions.

Patients who received standard verbal and written information plus film had increased knowledge about GEP tests compared with standard information alone.

ISRCTN28497350.

The introduction of the cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors abemaciclib and ribociclib to the adjuvant setting marks a significant advancement in the treatment of hormone-receptor-positive, human epidermal growth factor receptor 2-negative early breast cancer (HR+, HER2- EBC). Despite significant strides in early detection and treatment, many patients continue to face the risk of disease recurrence, highlighting the need for more effective adjuvant therapies. These CDK4/6 inhibitors, combined with adjuvant endocrine therapy, have shown promising efficacy in reducing recurrence rates while maintaining a manageable safety profile, as evidenced by the monarchE and NATALEE trials. This paper explores the integration of adjuvant CDK4/6 inhibitors into clinical practice, focusing on disease-free survival and safety outcomes. Key considerations in selecting between abemaciclib and ribociclib are discussed, including patient risk profiles, efficacy and safety profiles, treatment duration, and individual patient preferences. In addition, we discuss managing adverse events to prevent premature discontinuation, with strategies that include dose holds, dose reductions, proactive symptom management, and patient education. The paper also highlights strategies to enhance patient medication adherence and the involvement of multidisciplinary care teams to support treatment delivery. As research continues to evolve, additional follow-ups of the monarchE and NATALEE trials and future trials will further refine patient selection and treatment sequencing, ultimately improving outcomes and enhancing the quality of life for patients with HR+, HER2- EBC.

Chemotherapy clearly adversely affects fertility in women of childbearing age. But it is not yet clear whether chemotherapy at the expense of fertility can benefit younger patients with early-stage breast cancer. We conducted a retrospective cohort study utilizing the Surveillance, Epidemiology, and End Results database and the Shanghai Jiao Tong University Breast Cancer Data Base spanning from 2010 to 2020 to investigate early-stage breast malignant carcinoma in patients aged between 20 and 39 years. To address covariate imbalance, propensity score matching (PSM) was employed with a ratio of 1:1 and caliper set at 0.02 standard deviation of propensity score. Univariate and multivariate analyses were performed to evaluate the impact of chemotherapy on both breast cancer-specific survival (BCSS) and overall survival (OS). We identified a total of 6265 patients with complete information about breast cancer. Among them, 3855 patients received chemotherapy. Following successful PSM, we obtained a matched cohort comprising 3038 patients where the characteristics between the two groups were balanced except for race. Kaplan-Meier survival analysis revealed no significant differences in BCSS (P = 0.183) and OS (P = 0.295) between the chemotherapy group and no-chemotherapy group. Similarly, in matched dataset. multivariate COX analysis revealed that chemotherapy did not significantly reduce the risk of BCSS (HR 1.332; 95% CI [0.865-2.051], P = 0.193) and OS (HR 1.225; 95% CI [0.818-1.833], P = 0.324). The chemotherapy group did not demonstrate a superior benefit in any of the subgroups when stratified analyses were conducted based on molecular subtype, tumor size, age, and ethnicity. Chemotherapy fails to significantly improve prognostic outcomes in young patients diagnosed with early-stage breast cancer. With the help of genetic testing, these patients can expect further step-down therapy in the future.

Although numerous technical advances have been made in cancer treatment, chemotherapy is still a viable treatment option. However, it is more effective when used in combination with photothermal therapy for resistant breast cancer cells. This study introduces a smart drug delivery system, (DOX-OA+VERA+AuNRs)@NLC, which is designed for dual chemo/photothermal therapy of multiple-drug-resistant breast cancer. Type-III nanostructured lipid carriers (NLCs) were used as drug delivery systems, where nano-in-nano structures offer several advantages. Doxorubicin (DOX) was used as the antitumor agent by ion-pairing it with oleic acid (OA) to increase the DOX loading capacity, as well as to reduce the burst release of the drug. Verapamil (VERA), which was used as a chemosensitizer to overcome the multiple-drug resistance, was co-loaded with DOX-OA. Gold nanorods (AuNRs) were exploited as the photothermal therapy agent in photothermal therapy (PTT) application, which would have a synergistic relation with chemotherapy. The release of DOX-OA and VERA from NLCs was studied in vitro by triggering with NIR laser irradiation. Thus, an all-in-one drug delivery system was designed to release the active pharmaceutical ingredients (APIs) at higher concentrations in the desired region and provide both chemo/PTT. Besides, the application of a folic acid-chitosan (FA-CS) coating to NLCs has facilitated the development of systems capable of targeting and specifically releasing their cargo within cancerous tissues while preserving their surrounding environment.

Breast cancer is a significant health issue for women worldwide and poses unique challenges for all ages. Older women face many concerns about breast cancer treatment and outcomes. This study aims to compare breast cancer management and outcomes across various age groups within a single-center experience in a region with an aging population, focusing specifically on women aged 70 and older to identify potential disparities in treatment and prognosis.

We conducted a retrospective analysis of all female patients diagnosed with breast cancer at our local reference Breast Unit in northeastern Italy between January 2002 and July 2023. The primary outcome measures in this study were overall survival (OS), disease-free survival (DFS), cumulative loco-regional recurrences, and cumulative distant recurrences.

The study included 2478 women over 70 (31.12%), 4690 women aged between 45 and 69 (58.90%), and 795 women under 45 (9.98%). According to the study, older women were more likely to have advanced-stage cancer, whereas they received less aggressive treatment, including fewer adjuvant therapies and surgical interventions. We also observed worse prognoses in this group of patients if compared with women aged 45 to 69 years. Moreover, data showed that the incidence of breast cancer among older women has increased over time.

Our findings highlight the need for tailored treatment strategies for older breast cancer patients to balance treatment efficacy with quality-of-life considerations. These findings call for a strategic reevaluation of treatment protocols and emphasize the importance of personalized care, particularly for older women, to improve outcomes without sacrificing the quality of life while maintaining maximum survival potential.

The Rx for positive node endocrine-responsive breast cancer trial highlighted that premenopausal (PRE) women who underwent chemotherapy exhibited superior survival rates compared to postmenopausal (POST) counterparts, but showed worse survival without chemotherapy. This raises the question whether application of ovarian function suppression (OFS) in PRE women aligns with their cancer biology, treatment response, and outcomes observed in POST women.

Data from the Seoul National University Hospital breast cancer cohort focusing on patients with stage pT1-3, pN0-1, estrogen receptor-positive (ER+), and HER2-negative breast cancer were analyzed. Survival outcomes, including invasive disease-free survival (iDFS) and distant relapse-free survival (DRFS), were compared between PRE women receiving OFS and POST women, with chemotherapy usage as a stratification factor. Propensity score matching was performed.

We analyzed 3483 patients, comprising 2901 POST and 582 PRE women with OFS. In the cohort without chemotherapy, the 10-year iDFS rates were 90.3 % and 88.3 % (hazard ratio [HR], 1.32; p = 0.16), and 10-year DRFS rates were 94.3 % and 96.1 % (HR, 0.78; p = 0.41) for POST and PRE women with OFS, respectively. Among women treated with chemotherapy, 10-year iDFS rates were 83.0 % and 79.5 % (HR, 1.21; p = 0.37), and DRFS rates were 86.7 % and 85.7 % (HR, 1.14; p = 0.58) for POST and PRE women with OFS, respectively. These results remained consistent after PSM.

Oncological outcomes of PRE women receiving OFS were comparable to those of POST women with ER+ and HER2-early breast cancer, irrespective of chemotherapy administration.

Whether surgical axillary staging as part of breast-conserving therapy can be omitted without compromising survival has remained unclear.

In this prospective, randomized, noninferiority trial, we investigated the omission of axillary surgery as compared with sentinel-lymph-node biopsy in patients with clinically node-negative invasive breast cancer staged as T1 or T2 (tumor size, ≤5 cm) who were scheduled to undergo breast-conserving surgery. We report here the per-protocol analysis of invasive disease-free survival (the primary efficacy outcome). To show the noninferiority of the omission of axillary surgery, the 5-year invasive disease-free survival rate had to be at least 85%, and the upper limit of the confidence interval for the hazard ratio for invasive disease or death had to be below 1.271.

A total of 5502 eligible patients (90% with clinical T1 cancer and 79% with pathological T1 cancer) underwent randomization in a 1:4 ratio. The per-protocol population included 4858 patients; 962 were assigned to undergo treatment without axillary surgery (the surgery-omission group), and 3896 to undergo sentinel-lymph-node biopsy (the surgery group). The median follow-up was 73.6 months. The estimated 5-year invasive disease-free survival rate was 91.9% (95% confidence interval [CI], 89.9 to 93.5) among patients in the surgery-omission group and 91.7% (95% CI, 90.8 to 92.6) among patients in the surgery group, with a hazard ratio of 0.91 (95% CI, 0.73 to 1.14), which was below the prespecified noninferiority margin. The analysis of the first primary-outcome events (occurrence or recurrence of invasive disease or death from any cause), which occurred in a total of 525 patients (10.8%), showed apparent differences between the surgery-omission group and the surgery group in the incidence of axillary recurrence (1.0% vs. 0.3%) and death (1.4% vs. 2.4%). The safety analysis indicates that patients in the surgery-omission group had a lower incidence of lymphedema, greater arm mobility, and less pain with movement of the arm or shoulder than patients who underwent sentinel-lymph-node biopsy.

In this trial involving patients with clinically node-negative, T1 or T2 invasive breast cancer (90% with clinical T1 cancer and 79% with pathological T1 cancer), omission of surgical axillary staging was noninferior to sentinel-lymph-node biopsy after a median follow-up of 6 years. (Funded by the German Cancer Aid; INSEMA ClinicalTrials.gov number, NCT02466737.).

Knowledge-driven prioritization of candidate genes derived from large-scale molecular profiling data for targeted transcriptional profiling assays is challenging due to the vast amount of biomedical literature that needs to be harnessed. We present a workflow leveraging Large Language Models (LLMs) to prioritize candidate genes within module M12.15, a plasma cell-associated module from the BloodGen3 repertoire, by integrating knowledge-driven prioritization with data-driven analysis of transcriptome profiles.

The workflow involves a two-step process: (1) high-throughput screening using LLMs to score and rank the 17 genes of module M12.15 based on six predefined criteria, and (2) prioritization employing high-resolution scoring and fact-checking, with human experts validating and refining AI-generated scores.

The first step identified five candidate genes (CD38, TNFRSF17, IGJ, TOP2A, and TYMS). Following human-augmented LLM scoring and fact checking, as part of the second step, CD38 and TNFRSF17 emerged as the top candidates. Next, transcriptome profiling data from three datasets was incorporated in the workflow to assess expression levels and correlations with the module average across various conditions and cell types. It is on this basis that CD38 was prioritized as the top candidate, with TNFRSF17 and IGJ identified as promising alternatives.

This study introduces a systematic framework that integrates LLMs with human expertise for gene prioritization. Our analysis identified CD38, TNFRSF17, and IGJ as the top candidates within the plasma cell-associated module M12.15 from the BloodGen3 repertoire, with their relative rankings varying systematically based on specific evaluation criteria, from plasma cell biology to therapeutic relevance. This criterion-dependent ranking demonstrates the ability of the framework to perform nuanced, multi-faceted evaluations. By combining knowledge-driven analysis with data-driven metrics, our approach provides a balanced and comprehensive method for biomarker selection. The methodology established here offers a reproducible and scalable approach that can be applied across diverse biological contexts and extended to analyze large module repertoires.