Search Results (1,156)

Cyclin-dependent kinase (CDK)4/6 inhibitors have become a key component of adjuvant treatment for patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2−) early breast cancer who are at high risk of recurrence. The addition of abemaciclib and ribociclib to standard endocrine therapy has demonstrated clinically meaningful improvements in invasive disease-free survival, supported by the monarchE and NATALEE trials, respectively. With expansion of patient eligibility for CDK4/6 inhibitors, multidisciplinary coordination among medical oncologists, surgeons, nurses, pharmacists, and other health care providers is critical to optimizing patient identification, monitoring, and management of adverse events. This expert guidance document provides practical recommendations for implementing adjuvant CDK4/6 inhibitor therapy in routine clinical practice, incorporating insights from multiple specialties and with patient advocacy representation. Key considerations include patient selection based on clinical trial data, treatment duration, dosing schedules, adverse event profiles, monitoring requirements, drug–drug interactions, and patient-specific factors such as tolerability, cost, and quality of life. This guidance aims to support Canadian clinicians in effectively integrating CDK4/6 inhibitors into clinical practice, ensuring optimal patient outcomes through a multidisciplinary and patient-centric approach. Full article

Background/Objectives: Cancer suffers from unresolved therapeutic challenges owing to the lack of targeted therapies and heightened recurrence risk. This study aimed to investigate the new series of hydroxamate by structurally modifying the pharmacophore of vorinostat. Methods: The present work involves the synthesis of 15 differently substituted 2H-1,2,3-triazole-based hydroxamide analogs by employing triazole ring as a cap with varied linker fragments. The compounds were evaluated for their anticancer effect, especially their anti-breast cancer response. Molecular docking and molecular dynamics simulations were conducted to examine binding interactions. Results: Results indicated that among all synthesized hybrids, the molecule VI(i) inhibits the growth of MCF-7 and A-549 cells (GI₅₀ < 10 μg/mL) in an antiproliferative assay. Compound VI(i) was also tested for cytotoxic activity by employing an MTT assay against A549, MCF-7, and MDA-MB-231 cell lines, and the findings indicate its potent anticancer response, especially against MCF-7 cells with IC₅₀ of 60 µg/mL. However, it experiences minimal toxicity towards the normal cell line (HEK-293). Mechanistic studies revealed a dual-pathway activation: first, apoptosis (17.18% of early and 10.22% of late apoptotic cells by annexin V/PI analysis); second, cell cycle arrest at the S and G2/M phases. It also promotes ROS generation in a concentration-dependent manner. The HDAC–inhibitory assay, extended in silico molecular docking, and MD simulation experiments further validated its significant binding affinity towards HDAC 1 and 6 isoforms. DFT and ADMET screening further support the biological proclivity of the title compounds. The notable biological contribution of VI(i) highlights it as a potential candidate, especially against breast cancer cells. Full article

Background: Unlike most cancers, breast cancer poses a persistent risk of distant recurrence—often years after initial treatment—making long-term risk stratification uniquely challenging. Current tools fall short in predicting late metastatic events, particularly for early-stage patients. Methods: We present an interpretable machine learning (ML) pipeline to predict distant recurrence-free survival at 5, 10, and 15 years, integrating Bayesian network-based causal feature selection, deep feed-forward neural network models (DNMs), and SHAP-based interpretation. Using electronic health record (EHR)-based clinical data from over 6000 patients, we first applied the Markov blanket and interactive risk factor learner (MBIL) to identify minimally sufficient predictor subsets. These were then used to train optimized DNM classifiers, with hyperparameters tuned via grid search and benchmarked against models from 10 traditional ML methods and models trained using all predictors. Results: Our best models achieved area under the curve (AUC) scores of 0.79, 0.83, and 0.89 for 5-, 10-, and 15-year predictions, respectively—substantially outperforming baselines. MBIL reduced input dimensionality by over 80% without sacrificing accuracy. Importantly, MBIL-selected features (e.g., nodal status, hormone receptor expression, tumor size) overlapped strongly with top SHAP contributors, reinforcing interpretability. Calibration plots further demonstrated close agreement between predicted probabilities and observed recurrence rates. The percentage performance improvement due to grid search ranged from 25.3% to 60%. Conclusions: This study demonstrates that combining causal selection, deep learning, and grid search improves prediction accuracy, transparency, and calibration for long-horizon breast cancer recurrence risk. The proposed framework is well-positioned for clinical use, especially to guide long-term follow-up and therapy decisions in early-stage patients. Full article

Breast cancer (BC) is the most prevalent malignancy in women worldwide. Despite most cases being diagnosed in the early stages, patients typically require a multimodal treatment approach. This typically involves a combination of surgery, radiotherapy, systemic treatments (including chemotherapy or immunotherapy), targeted therapy, and endocrine therapy, depending on the disease subtype and the risk of recurrence. Moreover, patients with BC and germline mutations in the breast cancer genes 1 or 2 (BRCA1/BRCA2), (gBRCAm), who are typically young women, often require more aggressive therapeutic interventions. These mutations present unique characteristics that necessitate a distinct treatment approach, potentially influencing the side effect profiles of patients with BC. Regardless of the clear benefit observed with these treatments in terms of reduced recurrence and mortality rates, long-term, treatment-related adverse events occur that negatively affect the health-related quality of life (HRQoL) of BC survivors. Thus, long-term adverse events need to be factored into the treatment decision algorithm of patients with early BC (eBC). Physical, functional, emotional, and psychosocial adverse events can occur and represent a significant concern and a challenge for clinicians, patients, and their families. This review article provides an overview of the various long-term adverse events that patients with eBC may experience, including their associated risk factors, as well as management and prevention strategies. We also explore the evidence of the long-term impact of treatment on the HRQoL of patients with gBRCAm. By providing a comprehensive overview of current evidence and recommendations regarding patients’ HRQoL, we aim to equip clinicians with scientific and clinical knowledge and provide guidance to optimize care and improve long-term outcomes. Full article

Background/Objectives: To develop a DL-based model predicting recurrence risk in HER2-low breast cancer patients and to compare performance of the MRI-alone, clinicopathologic-alone, and combined models. Methods: We analyzed 453 patients with HER2-low breast cancer who underwent surgery and preoperative breast MRI between May 2018 and April 2022. Patients were randomly assigned to either a training cohort (n = 331) or a test cohort (n = 122). Imaging features were extracted from DCE-MRI and ADC maps, with regions of interest manually annotated by radiologists. Clinicopathological features included tumor size, nodal status, histological grade, and hormone receptor status. Three DL prediction models were developed: a CNN-based MRI-alone model, a clinicopathologic-alone model based on a multi-layer perceptron (MLP) and a combined model integrating CNN-extracted MRI features with clinicopathological data via MLP. Model performance was evaluated using AUC, sensitivity, specificity, and F1-score. Results: The MRI-alone model achieved an AUC of 0.69 (95% CI, 0.68–0.69), with a sensitivity of 37.6% (95% CI, 35.7–39.4), specificity of 87.5% (95% CI, 86.9–88.2), and F1-score of 0.34 (95% CI, 0.33–0.35). The clinicopathologic-alone model yielded the highest AUC of 0.92 (95% CI, 0.92–0.92) and sensitivity of 93.6% (95% CI, 93.4–93.8), but showed the lowest specificity (72.3%, 95% CI, 71.8–72.8) and F1-score of 0.50 (95% CI, 0.49–0.50). The combined model demonstrated the most balanced performance, achieving an AUC of 0.90 (95% CI, 0.89–0.91), sensitivity of 80.0% (95% CI, 78.7–81.3), specificity of 83.2% (95% CI: 82.7–83.6), and the highest F1-score of 0.55 (95% CI, 0.54–0.57). Conclusions: The DL-based model combining MRI and clinicopathological features showed superior performance in predicting recurrence in HER2-low breast cancer. This multimodal approach offers a framework for individualized risk assessment and may aid in refining follow-up strategies. Full article

Background/Objectives: Erysipelas is an acute bacterial skin infection, particularly affecting the lower limbs, with a tendency to recur. Despite its clinical importance, data on demographic and epidemiological risk factors, as well as factors influencing hospitalization, remain limited. This study aimed to analyze the epidemiological and clinical characteristics of patients hospitalized with primary and recurrent erysipelas, focusing on risk factors contributing to disease onset, recurrence, and prolonged hospitalization. Methods: A retrospective single-center analysis was conducted on 239 patients hospitalized for erysipelas at the Department of Dermatology, Pediatric Dermatology, and Oncology at the Medical University of Lodz. Data collected included demographics, lesion location, laboratory markers, comorbidities, and hospitalization outcomes. Statistical analyses were performed to assess associations between risk factors, disease recurrence, and hospitalization duration. Results: The majority of erysipelas cases (85.4%) involved the lower limbs, with a higher prevalence in men. Upper extremities were mostly affected in women, especially those who had undergone breast cancer surgery. Recurrent erysipelas accounted for 75.7% of cases. Most patients (89.1%) had at least one comorbidity, with hypertension, diabetes type 2 (DM2), and obesity being the most common. Higher white blood cell (WBC) count, obesity, atrial fibrillation (AF), and the need for enoxaparin administration were independently associated with prolonged hospitalization. Dyslipidemia was significantly associated with erysipelas recurrence (p < 0.05). Conclusions: Both primary and recurrent erysipelas are associated with specific risk factors. Recurrent erysipelas may be linked to components of metabolic syndrome, particularly obesity and dyslipidemia, which emerged as a significant risk factor in this study. Hospitalization length may be prolonged by inflammation markers (WBC and CRP) and comorbidities such as AF, obesity, or the need for enoxaparin in patients with elevated thrombosis risk. Further multicenter studies with larger cohorts are needed to assess the impact of demographics, biomarkers, metabolic disorders, and treatment strategies on erysipelas recurrence and outcomes. Awareness of these risk factors is essential for effective prevention, management, and recurrence reduction. Full article

Adjuvant endocrine therapy for early breast cancer significantly reduces recurrence but increases bone fragility. Given limited data on denosumab (60 mg every 6 months) in premenopausal patients receiving endocrine therapy for early breast cancer, we conducted a retrospective real-world study at the Gemelli Hospital (September 2018–January 2025). A descriptive analysis was performed. The primary endpoint was to assess efficacy, evaluated by changes in bone mineral density via dual-energy X-ray absorptiometry and by monitoring bone turnover markers, particularly serum C-terminal telopeptide of type I collagen. Safety was evaluated based on adverse endocrine therapy events (osteoporotic fractures) and adverse denosumab events (osteonecrosis of the jaw). Sixty-nine patients were eligible for the study. Endocrine therapy included ovarian function suppression with exemestane (89.8%) or tamoxifen (10.1%). Baseline spinal osteoporosis decreased from 20.3% to 5.8%, osteopenia from 39.1% to 34.8%, with normal T-scores rising from 17.4% to 34.8%. Femoral improvements were similar. Serum C-terminal telopeptide of type I collagen levels (evaluated in 35.8%) showed stable reduction in 97%. Denosumab adherence was 89.9%. One osteonecrosis of the jaw case occurred (1.4%); no fractures were reported. Denosumab demonstrated efficacy in improving bone density and reducing bone turnover, with excellent adherence and favorable safety. Longer follow-up is needed to assess post-discontinuation effects. Full article

Of breast cancers, the triple-negative subtype (TNBC) is characterized by aggressive behavior, poor prognosis and limited treatment options due to its high molecular heterogeneity. Since insufficient programmed cell death response is a major hallmark of cancer, here we searched for apoptosis-related biomarkers of prognostic potential in TNBC. The expression of the pro-apoptotic caspase 8, cytochrome c, caspase 3, the anti-apoptotic BCL2 and the caspase-independent mediator, apoptosis-inducing factor-1 (AIF1; gene AIFM1) was tested in TNBC both in silico at transcript and protein level using KM-Plotter, and in situ in our clinical TNBC cohort of 103 cases using immunohistochemistry. Expression data were correlated with overall survival (OS), recurrence-free survival (RFS) and distant metastasis-free survival (DMFS). We found that elevated expression of the executioner apoptotic factors AIF1 and caspase 3, and of BCL2, grants significant OS advantage within TNBC, both at the mRNA and protein level, particularly for chemotherapy-treated vs untreated patients. The dominantly cytoplasmic localization of AIF1 and cleaved-caspase 3 proteins in primary TNBC suggests that chemotherapy may recruit them from the cytoplasmic/mitochondrial stocks to contribute to improved patient survival in proportion to their expression. Our results suggest that testing for the expression of AIF1, caspase 3 and BCL2 may identify partly overlapping TNBC subgroups with favorable prognosis, warranting further research into the potential relevance of apoptosis-targeting treatment strategies. Full article

Background: Pathological complete response (pCR) serves as a prognostic surrogate endpoint for long-term clinical outcomes in breast cancer patients receiving neoadjuvant systemic therapy (NAST). This study aims to develop and evaluate machine learning-based biomarkers for predicting pCR and recurrence-free survival (RFS). Methods: This retrospective monocentric study included 235 women (mean age 46 ± 11 years) with non-metastatic breast cancer treated with NAST. We developed various machine learning models using clinical features (age, genetic mutations, TNM stage, hormonal receptor expression, HER2 status, and histological grade), along with morphological features (size, T2 signal, and surrounding edema) and radiomics data extracted from pre-treatment MRI. Patients were divided into training and test groups with different MRI models. A customized machine learning pipeline was implemented to handle these diverse data types, consisting of feature selection and classification components. Results: The models demonstrated superior prediction ability using radiomics features, with the best model achieving an AUC of 0.72. Subgroup analysis revealed optimal performance in triple-negative breast cancer (AUC of 0.80) and HER2-positive subgroups (AUC of 0.65). Conclusion: Machine learning models incorporating clinical, qualitative, and radiomics data from pre-treatment MRI can effectively predict pCR in breast cancer patients receiving NAST, particularly among triple-negative and HER2-positive breast cancer subgroups. Full article

Background/Objectives: Adherence to oral endocrine therapy (OET) is essential to reduce recurrence but is predominantly lower among underserved patients, leading to worse health outcomes. We aimed to depict longitudinal patterns of OET adherence using group-based trajectory modeling (GBTM) and identify predictors associated with each adherence trajectory. Methods: A single-center, retrospective study was conducted to analyze data from women 18 years or older with metastatic breast cancer who initiated with an OET and were treated from January to December 2022. Adherence was measured using a proportion of days covered (PDC > 80%) for 12 months. Binary monthly indicator of PDC was incorporated into GBTM. Four models were generated by changing the number of groups from 2 to 5, using a 2nd-order polynomial function of time. A multinomial logistic regression model was run to evaluate the predictors of non-adherence trajectories, and “adherence” was considered the reference group. Results: A total of 346 women had a (mean age of 60) years; 93% were Hispanic or of Mexican origin; 90% were taking aromatase inhibitors (AIs), with an endocrine therapy of 1.05 years. Three trajectories of adherence to GBTM were identified: a gradual decline in adherence (n = 88, 25.5%), improving suboptimal adherence (n = 106, 30.6%), and adherent (n = 152, 43.9%). Multinomial logistic regression analysis showed that significant predictors are diabetes (odds ratio (OR), 2.96; 95% confidence interval (CI), 1.57–5.57) and fewer years of therapy (OR, 2.96; 95% CI, 1.57–5.57). Suboptimal adherence among RGV patients receiving OET, with approximately 56% following a non-adherent trajectory. Conclusions: Suboptimal adherence among RGV patients receiving OET, with approximately 56% following a non-adherent trajectory. Significant predictors should be considered when designing targeted interventions. Full article

Oligometastasis represents a clinically relevant state of limited metastatic disease that could be amenable to selected local therapies in carefully chosen patients. Although initial trials such as SABR-COMET demonstrated a survival benefit with aggressive local treatment, breast cancer was underrepresented. Subsequent breast cancer-specific trials, including NRG-BR002, failed to show a clear survival benefit, highlighting uncertainties and the need for further refinement in patient selection and integration with systemic approaches. The definitions of oligometastasis continue to evolve, incorporating radiological, clinical, and biological features. Advances in imaging and molecular profiling suggest that oligometastatic breast cancer might represent a distinct biological subtype, with potential biomarkers including PIK3CA mutations and YAP/TAZ expression. Organ-specific strategies using stereotactic radiotherapy, surgery, and proton therapy have shown favorable local control in certain settings, though their impact on the overall survival remains under investigation. Emerging techniques, including circulating tumor DNA (ctDNA) analysis, are being explored to improve patient selection and disease monitoring. Ongoing trials may provide further insight into the role of local therapy, particularly in hormone receptor-positive or HER2-positive subtypes. Local and systemic strategies need to be carefully coordinated to optimize the outcomes. This review summarizes the current definitions of and evidence and therapeutic considerations for oligometastatic breast cancer and outlines potential future directions. Full article

Breast cancer is a leading cause of central nervous system (CNS) metastases in women, often associated with poor prognosis and limited therapeutic options. However, molecular differences between primary tumors and CNS metastases remain underexplored. We aimed to characterize transcriptomic differences between primary breast tumors and matched CNS metastases and identify immune-related biomarkers associated with metastatic progression and patient outcomes. Transcriptomic profiling was based on 11 matched FFPE sample pairs (primary tumor and CNS metastasis). Paired formalin-fixed paraffin-embedded (FFPE) samples from primary tumors (T1) and CNS metastases (T2) were analyzed using the NanoString nCounter^® platform and the PanCancer IO 360™ Gene Expression Panel. Differential gene expression, Z-score transformation, and heatmap visualization were performed in R. In silico survival analyses for overall survival (OS) and recurrence-free survival (RFS) were conducted using publicly available TCGA and GEO datasets. Forty-five genes were significantly differentially expressed between the T1 and T2 samples. Immune-related genes such as CXCL9, IL7R, CD79A, and CTSW showed consistent downregulation in CNS metastases. High expression of CXCL9 and CD79A was associated with improved OS and RFS, whereas high IL7R and CTSW expression correlated with worse outcomes. These findings indicate immune suppression as a hallmark of CNS colonization. Comparative transcriptomic analysis further underscored the distinct molecular landscapes between primary and metastatic tumors. This study highlights transcriptional signatures associated with breast cancer CNS metastases, emphasizing the role of immune modulation in metastatic progression. The identified genes have potential as prognostic biomarkers and therapeutic targets, supporting the need for site-specific molecular profiling in metastatic breast cancer management. Full article

Background: Genetic insights from diverse populations are key to advancing cancer detection, treatment, and prevention. Unlike other Latin American countries, Colombia lacks a centralized registry for germline and somatic mutations in breast and ovarian cancer. This study describes the country’s first national variant registry, and the occurrence of recurrent mutations and potential founder effects in Colombia. Methods: To address this gap, we implemented the first capturing protocol using the REDCap system. In a group of 213 breast and/or ovarian cancer patients harboring genetic mutations, we collected genetic, clinical, and demographic data from 13 regional centers across Colombia. Statistical analyses assessed variant distribution and patient demographics. Results: Among 229 identified variants (105 germline, 124 somatic), most were classified as pathogenic or likely pathogenic (72.4% germline, 87% somatic). BRCA1 and BRCA2 accounted for the majority of recurrent mutations. Germline recurrent variants (seen >3 times) were recorded for BRCA1 (77.7%; 21/27) and BRCA2 (22.3%; 6/27). Similarly, recurrent somatic variants were identified for BRCA1 (82.6%; 38/46) and BRCA2 (17.4%; 8/46). Notably, four recurrent variants were previously reported as founder mutations: BRCA1 c.1674del (14.3% germline and 23.7% somatic), BRCA1 c.3331_3334del (33.3% germline and 52.6% somatic), BRCA1 c.5123C>A (52.4% germline and 23.7% somatic), and BRCA2 c.2808_2811del (50% germline and 50% somatic). Most cases originated from the Andean region, highlighting regional disparities. Conclusions: This registry offers the first overview of genetic variants in Colombian breast and ovarian cancer patients. Recurrent and region-specific mutations highlight the need for population-focused data to guide targeted screening and personalized care strategies. Full article

Aims: To systematically review and synthesize qualitative research exploring the Breast Cancer Survivors (BCSs)’ perception of health promotion interventions and informing strategies to mitigate recurrence risk within five years post-treatment and improve clinical outcomes. Specifically, this study addresses the question: “How do women diagnosed with breast cancer perceive health promotion interventions for recurrence prevention?” Design: A systematic review and qualitative meta-synthesis were performed. Data Sources: A systematic search of scientific databases (CINAHL, MEDLINE, and Scopus) was undertaken in November 2024. The reference list was cross-referenced and hand-searched to identify additional articles. Review Methods: Studies were included if they met the following criteria: they were primary qualitative studies focusing on BCSs within five years post-treatment, involving participants who had completed surgery, radiotherapy, or chemotherapy in the same time frame, as this period is critical for monitoring recurrence and implementing health promotion interventions. Only studies published in peer-reviewed journals and written in Italian, English, French, or Spanish were considered, provided that an abstract and the full text were available. Moreover, eligible studies had to be conducted in high-income or middle-income countries. Studies were excluded if they focused exclusively on advanced or metastatic breast cancer, if they involved mixed cancer populations without reporting separate data for BCSs, or if they were non-qualitative studies or gray literature. The review study protocol was registered in the PROSPERO database (CRD42024626033). Results: The literature search identified 490 records, 13 articles from databases, and 3 articles identified via other methods (web and citation searching) that met inclusion criteria. A narrative synthesis approach allowed the emerging five themes: (I) Challenges, (II) Self-motivation and empowerment, (III) The relationships as a facilitator, (IV) Barriers to change, and (V) Proactive support strategies. Conclusions: Addressing internal and external factors that influence health behaviors is essential to improve adherence, reduce recurrence risk, and enhance quality of life. Tailored interventions, social support, and healthcare engagement are crucial in this effort. Impact: Our meta-synthesis highlighted significant challenges as well as valuable resources for health promotion among BCSs, suggesting practical and tailored approaches to improving the adoption of healthy behaviors, supported by relationships and targeted support strategies. Full article

Background and Objectives: The objective of this review is to evaluate the current evidence regarding hormone treatments for both premenopausal and postmenopausal women with early-stage hormone receptor (HR) positive breast cancer. Materials and Methods: An in-depth exploration of the existing literature was conducted, with landmark clinical trials such as TEXT, SOFT, ATLAS, and aTTom serving as primary references. Results: Through an extensive review of the literature, our findings indicate that for premenopausal women with HR-positive, HER2-negative BC with a low risk of recurrence, standard 5-year monotherapy with tamoxifen represents the optimal therapeutic management, given its favorable clinical outcomes and lower associated toxicity. In contrast, for premenopausal women with an intermediate to high risk of recurrence with the same tumor characteristics, the most effective approach stated in the literature is a combination of ovarian suppression therapy (chemical/surgical) and an aromatase inhibitor/selective estrogen receptor modulator (tamoxifen), with a possible extension of the standard therapeutic period. In postmenopausal patients with HR-positive, HER2-negative breast cancer with a low recurrence risk, the first line of treatment is usually a standard 5-year period of treatment with aromatase inhibitors (AIs)(letrozole, anastrozole, or exemestane). On the other hand, in postmenopausal women with an intermediate to high risk, combination therapy might be needed, as well as an extension of the standard therapeutic time. Conclusions: Treatment consensus depends on pre- vs. postmenopausal status and recurrence risk. Full article