Strategy For Treatment Of Breast Cancer Research Articles

Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis

BackgroundBreast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratification particularly challenging. Emerging evidence suggests that lactylation, a novel post-translational modification, plays a crucial role in tumor progression and immune modulation.MethodsTo address breast cancer heterogeneity, we developed a machine learning-derived lactylation signature (MLLS) using lactylation-related genes selected through random survival forest (RSF) and univariate Cox regression analyses. A total of 108 algorithmic combinations were applied across multiple datasets to construct and validate the model. Immune microenvironment characteristics were analyzed using multiple immune infiltration algorithms. Computational drug-repurposing analyses were conducted to identify potential therapeutic agents for high-risk patients.ResultsThe MLLS effectively stratified patients into low- and high-risk groups with significantly different prognoses. The model demonstrated robust predictive power across multiple cohorts. Immune infiltration analysis revealed that the low-risk group exhibited higher levels of immune checkpoints (e.g., PD-1, PD-L1) and greater infiltration of B cells, CD4+ T cells, and CD8+ T cells, suggesting better responsiveness to immunotherapy. In contrast, the high-risk group showed immune suppression features associated with poor prognosis. Methotrexate was computationally predicted as a potential therapeutic candidate for high-risk patients, although experimental validation remains necessary.ConclusionThe MLLS represents a promising prognostic biomarker and may support personalized treatment strategies in breast cancer, particularly for identifying candidates who may benefit from immunotherapy.

Designing pegylated dextran sheathed doxorubicin loaded iron nanoparticles against premenopausal breast cancer.

Designing pegylated dextran sheathed doxorubicin loaded iron nanoparticles against premenopausal breast cancer.

Harnessing sulfur-doped carbon nanodots conjugated with IDO inhibitors act as a dual-mode breast cancer immunotherapy.

Harnessing sulfur-doped carbon nanodots conjugated with IDO inhibitors act as a dual-mode breast cancer immunotherapy.

Navigating antibody‒drug conjugates (ADCs): from metastatic to early breast cancer treatment strategies.

We are currently living in the era of precision medicine, and antibody‒drug conjugates (ADCs) represent promising advancements in targeted cancer therapy. While several ADCs have been investigated over the years, only three have gained FDA approval for breast cancer (BC): ado-trastuzumab emtansine (T-DM1/Kadcyla), trastuzumab deruxtecan (T-DXd/Enhertu), and sacituzumab govitecan (SG/Trodelvy). This review focuses on the three approved ADCs for BC, reviewing the trials that led to their approval and detailing the ongoing trials testing their clinical efficacy and safety profiles. We examine ongoing trials targeting both metastatic and early-stage patients. Notably, we explore trials incorporating investigational ADCs into early management strategies, addressing the unique challenges of biomarker identification, target toxicity, and cost-effectiveness. By summarizing the current landscape of FDA-approved and investigational ADCs, this study highlights the evolving nature of BC treatment. Preliminary findings from ongoing trials suggest that early integration of ADCs can lead to significant improvements in disease-free survival, reinforcing their role in personalized medicine. As research advances, ADCs are likely to become a cornerstone of breast cancer treatment, providing new hope for better patient outcomes.

High Expression of Complement 3 Enhances the Efficacy of Neoadjuvant Chemotherapy Prior to Oncoplastic Surgery for HER2-Positive Breast Cancer.

Background: Neoadjuvant chemotherapy for breast cancer (BC) improves patient prognosis, but its efficacy is hindered by the disease's high heterogeneity. This study enhances effectiveness of targeted therapy to improve clinical outcomes. Methods: This study enrolled 335 patients from three centers. Differentially expressed genes were identified using DESeq2, and Venn analysis was applied to identify hub Complement genes. Hub gene expression was validated through public databases and IHC in real-world samples. In addition, associations between these genes and clinical factors were evaluated. Survival analysis, using the log-rank test, assessed overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) as end points. The authors also locate hub Complement 3 gene position by immunofluorescence. Results: The study identified C3 as a hub Complement gene associated with trastuzumab sensitivity. C3 shows higher expression in normal than tumor tissues. C3 was highly expressed in HER2-negative and early-stage BC, but showed no differences in lymph node or metastasis subgroups. High C3 expression correlated with better OS, DSS, and PFI, particularly in HER2+ patients. IHC analysis confirmed higher C3 expression in normal tissues with the lowest in triple-negative BC. Immunofluorescence findings suggest that C3 recruits complement receptor 2 to enhance trastuzumab efficacy in HER2+ patients. Conclusions: This finding highlights the potential of complement 3 to improve therapeutic outcomes and pave the way for more personalized treatment strategies in BC.

Cost-utility analysis of olaparib assisted targeted therapy for BRCA mutation HER2-negative early breast cancer in China and in the United States

BackgroundOlaparib, an inhibitor of poly (ADP-ribose) polymerase (PARP), has demonstrated promising outcomes in treating HER2-negative early-stage breast cancer with BRCA mutations. However, a comprehensive evaluation of its cost-effectiveness in the context of the United States and China has yet to be undertaken. This study seeks to fill this research void by performing a thorough cost-utility analysis.MethodsThis investigation takes as its foundation the findings from the OlympiA trial. We obtained survival curves from this trial and used the Weibull distribution function to calculate transition probabilities. Relevant literature provided the necessary data on costs, utility values, and discount rates applicable to both the United States and China. We utilized TreeAge software to construct Markov models for each country, simulating the progression of early-stage breast cancer. These models underwent extensive examination through multi-way analysis, cost-utility analysis, Monte Carlo simulations, one-way and two-way sensitivity analyses, as well as probabilistic sensitivity analysis.ResultsThe cost-utility analysis of the Chinese Markov model revealed that the total expenditure for the Olaparib cohort amounted to 384,274.75 RMB, generating 6.41 QALYs. Conversely, the placebo group incurred a total cost of 60,264.10 RMB, resulting in 6.34 QALYs. The Incremental Cost-Utility Ratio (ICUR) between the two cohorts stood at 5,007,332.36 RMB/QALY, which is significantly higher than thrice the Gross Domestic Product (GDP) per capita of China in 2022, set at 257,094 RMB. As for the U.S. model, the Olaparib group had a total expenditure of 245,604.01 USD, yielding 7.53 QALYs, while the placebo cohort had a total cost of 93,019.92 USD, generating 7.45 QALYs. The ICUR for the two groups was calculated at 1,891,974.19 USD/QALY, substantially surpassing the U.S. Willingness-To-Pay (WTP) threshold of 150,000 USD/QALY.ConclusionsWhen evaluated in the context of healthcare economics in both China and the United States, the implementation of an Olaparib-based treatment strategy for early-stage HER2-negative breast cancer with BRCA mutations does not present a cost-effective solution in either nation.

The transcriptional regulators GATA6 and TET1 regulate the TGF-β pathway in cancer-associated fibroblasts to promote breast cancer progression

Cancer-associated fibroblasts (CAFs) are pivotal drivers of tumor progression, yet the molecular mechanisms underlying their activation remain incompletely understood. Here, we identified the TET1/SMAD4/GATA6 regulatory axis as a central mechanism governing CAF transformation and function in breast cancer. Through integrative in vitro and in vivo models, we demonstrated that TET1, an epigenetic modulator, demethylates the SMAD4 promoter, enhancing SMAD4 expression. SMAD4 transcriptionally upregulates GATA6, which amplifies TGF-β signaling by directly activating the TGF-β promoter, establishing a self-reinforcing feedforward loop critical for CAF identity and stromal-tumor crosstalk. GATA6 and TET1 were significantly upregulated in breast CAFs compared to normal fibroblasts (NFs) and TGF-β-induced CAFs. Loss- or gain-of-function experiments revealed that these regulators control CAF survival, marker expression, and secretion of pro-tumorigenic factors. Knockdown of GATA6 or TET1 reduced CAF-mediated migration and invasion of breast cancer cells in vitro, while their overexpression enhanced cancer cell aggressiveness. Mechanistically, TET1-mediated epigenetic remodeling and GATA6-driven transcriptional activation converge on the TGF-β/SMAD pathway, sustaining CAF activation. In vivo, tumors derived from GATA6- or TET1-depleted CAFs exhibited reduced growth, proliferation, and CAF engraftment, underscoring their role in tumor progression. These findings position GATA6 and TET1 as promising targets to disrupt CAF-driven tumorigenesis, offering novel strategies for breast cancer treatment. By unraveling the epigenetic-transcriptional interplay within the tumor microenvironment, this study advances our understanding of stromal reprogramming and its implications for precision oncology.

Formulation optimization and characterization of Central composite design optimized LAP-loaded calcium pectinate nanoparticles: anticancer activity against MCF-7 cells

Objective The study aimed to formulate and optimize Lapatinib-loaded calcium pectinate nanoparticles (LAP-PEC-NPs) using central composite design (CCD), evaluate their physicochemical properties, and compare their anticancer efficacy with raw LAP on MCF7 breast cancer cell lines. Significance of review The study is significant as it successfully developed LAP-PEC-NPs through systematic optimization. These nanoparticles exhibited favorable physicochemical properties, high drug entrapment, and sustained release. The effective inhibition of MCF7 breast cancer cell growth by LAP-PEC-NPs underscores their potential as a promising cancer treatment strategy, enhancing LAP’s therapeutic efficacy and bioavailability. Key findings LAP-PEC-NPs were successfully developed using an ionic gelation process. The optimization resulted in an ideal formulation with a polydispersity index (PDI) of 0.289, a droplet size of 93.65 nm, and a zeta potential of −17.32 mV. LAP’s amorphous nature within the nanoparticles’ porous matrix was confirmed through characterization techniques. Dissolution studies showed sustained drug release, with LAP-PEC-NPs releasing approximately 75% of LAP over 72 h, significantly higher than raw LAP. Evaluation of MCF7 breast cancer cell lines revealed that LAP-PEC-NPs effectively inhibited cell growth. Conclusions The study successfully developed and optimized LAP-PEC-NPs, yielding nanoparticles with desirable characteristics. The sustained drug release kinetics and promising anticancer efficacy of LAP-PEC-NPs suggest their potential as a therapeutic strategy for breast cancer treatment. These findings pave the way for further preclinical and clinical studies to validate the efficacy and safety of LAP-PEC-NPs for clinical translation.

CircSCD1 inhibits ferroptosis in breast Cancer through stabilizing SCD1 protein via deubiquitinase OTUB1

Breast cancer is the leading cause of cancer-related death in women worldwide, and its developmental mechanisms involve complex factors. Recent studies have shown that ferroptosis is closely related to the occurrence and progression of breast cancer. However, the role of circular RNAs (circRNAs) in regulating ferroptosis in breast cancer remains unclear. In this study, we investigated the regulatory role of circSCD1 (hsa_circ_0019512) in breast cancer. We examined the expression of circSCD1 in breast cancer cell lines and explored its impact on cell viability and colony formation. We also evaluated the involvement of circSCD1 in ferroptosis by measuring the levels of malondialdehyde (MDA), glutathione (GSH), reactive oxygen species (ROS), and intracellular iron. In vivo xenograft experiments were performed to confirm the role of circSCD1 in promoting tumor growth and inhibiting ferroptosis.Furthermore, we investigated the mechanism by which circSCD1 regulates SCD1 protein stability through ubiquitination and identified the interaction between circSCD1 and the deubiquitinase OTUB1. Our results showed that circSCD1 was upregulated in breast cancer cell lines and promoted cell viability and colony formation. Knockdown of circSCD1 increased MDA and ROS levels, decreased GSH levels, and enhanced ferroptosis in breast cancer cells. In vivo, circSCD1 knockdown significantly reduced tumor size and weight, while its overexpression enhanced tumor growth. Mechanistically, circSCD1 interacted with OTUB1 to inhibit the ubiquitination and degradation of SCD1 protein, thereby stabilizing its expression. Rescue experiments demonstrated that SCD1 overexpression partially reversed the effects of circSCD1 knockdown on cell proliferation and ferroptosis. Our findings suggest that circSCD1 plays a crucial role in promoting breast cancer cell growth and inhibiting ferroptosis by regulating SCD1 protein stability. Targeting the circSCD1/OTUB1/SCD1 axis may provide a potential therapeutic strategy for breast cancer treatment.

Fertility preservation methods in the context of breast cancer treatment: real-life experience and prospects

The article discusses current methods for preserving fertility in women undergoing breast cancer (BC) treatment. It provides a detailed overview of contemporary breast cancer treatments and their impact on fertility. To prevent fertility loss, there are described key strategies such as oocyte, embryo, and ovarian tissue cryopreservation, as well as temporary suppression of ovarian function using gonadotropin-releasing hormone agonists. In addition, it analyzes factors such as lack of information, limited medical resources, and the need for immediate anticancer therapy initiation that hinder access to such methods. The importance of comprehensive patient support systems involving coordination among oncologists, reproductive specialists, and psychologists is emphasized. Special attention is paid to further development and improvement of existing methods aimed at reducing gonadotoxicity, as well as ongoing research to identify new safe and effective strategies. It is specifically stressed about importance of long-term monitoring of children born from preserved gametes and tissues to assess the safety and efficacy of such approaches. Integrating fertility preservation into the overall BC treatment strategy can markedly improve women's quality of life by increasing their chances of regaining reproductive function after completing primary treatment.

IL-7R Expression Correlates with Prognosis in Breast Cancer.

The tumor microenvironment (TME) exerts a significant influence on the development, invasion, metastasis, and drug resistance of breast cancer. Therefore, this study sought to investigate potential prognostic factors and markers indicative of TME remodeling in breast cancer, utilizing data from the TCGA database. In this study, transcriptome RNA-seq data from 1222 breast cancer samples were processed using CIBERSORT and ESTIMATE algorithms. We conducted a differential gene expression analysis utilizing COX regression analysis and constructed protein-protein interaction (PPI) networks for enhanced visualization. Through univariate COX analysis and cross-analysis within PPI networks, the Interleukin-7 receptor (IL-7R) emerged as a potential predictor. Subsequently, we performed a comprehensive investigation encompassing single-gene survival analysis, clinical correlation assessment, and GSEA enrichment analysis targeting IL-7R as a core gene associated with prognosis. We examined the expression of IL-7R in human breast cancer and normal breast tissue through clinical studies and cytology experiments, followed by an indepth analysis of the relationship between IL-7R and breast cancer. The survival analysis revealed that breast cancer patients with elevated IL-7R expression experienced prolonged survival compared to those with lower IL-7R levels. Results obtained from the Wilcoxon rank-sum test, along with clinical and cellular experiments, indicated higher IL-7R expression in tumor samples compared to normal samples. Correlation tests conducted between IL-7R expression and clinicopathological stage characteristics highlighted statistically significant associations between IL-7R expression and the T and M stages. Additionally, cell classification analysis of tumor-infiltrating immune cells (TIC) proportion showed that activated CD4+ T cells and CD8 T cells of memory B cells were positively correlated with IL-7R expression. These findings further underscored the impact of IL-7R levels on the tumor microenvironment (TME). IL-7R emerges as a potential prognostic indicator for breast cancer patients, particularly in sustaining the immunoactive status of the tumor microenvironment (TME) and contributing to immune reconstitution. These findings offer novel insights into breast cancer treatment strategies.

Evaluating Diagnostic Technologies for Breast Lesions: A Focused Review of Breast-Specific Gamma Imaging, Magnetic Resonance Imaging, Mammography, and Ultrasound with Molecular Subtype Insights

This systematic review evaluates the diagnostic effectiveness of breast-specific gamma imaging (BSGI), MRI, mammography, and ultrasound in detecting breast lesions and their associations with molecular subtypes. Following PRISMA guidelines, a comprehensive search of PubMed, Embase, and Cochrane databases was conducted for studies published between January 2014 and October 2024. Nine studies met the inclusion criteria, encompassing clinical trials and observational studies that provided data on sensitivity, specificity, and diagnostic accuracy. Methodological quality was assessed using the QUADAS-2 tool, and pooled diagnostic measures were calculated with STATA V.14.0. BSGI demonstrated high diagnostic performance, with a sensitivity of 91.7% and specificity of 80.7%, surpassing mammography (77.3% sensitivity, 74.5% specificity) and ultrasound (82.1% sensitivity, 70.8% specificity). MRI exhibited the highest sensitivity at 92.5% but lower specificity at 69.7%. The diagnostic odds ratio for BSGI was 4.90 (95% CI: 3.12–7.68), emphasizing its role as a valuable adjunct to mammography and MRI, particularly in dense breast tissues and cases of inconclusive findings. The findings highlight the potential of BSGI to improve diagnostic accuracy and assist in identifying molecular subtypes, such as HER2-positive and triple-negative cancers, facilitating more personalized breast cancer treatment strategies. BSGI’s integration into diagnostic workflows offers promising advancements for breast cancer management.

Multimodal diagnostic models and subtype analysis for neoadjuvant therapy in breast cancer.

Breast cancer, a heterogeneous malignancy, comprises multiple subtypes and poses a substantial threat to women's health globally. Neoadjuvant therapy (NAT), administered prior to surgery, is integral to breast cancer treatment strategies. It aims to downsize tumors, optimize surgical outcomes, and evaluate tumor responsiveness to treatment. However, accurately predicting NAT efficacy remains challenging due to the disease's complexity and the diverse responses across different molecular subtypes. In this study, we harnessed multimodal data, including proteomic, genomic, MRI imaging, and clinical information, sourced from multiple cohorts such as I-SPY2, TCGA-BRCA, GSE161529, and METABRIC. Post data preprocessing, Lasso regression was utilized for feature extraction and selection. Five machine learning algorithms were employed to construct diagnostic models, with pathological complete response (pCR) as the predictive endpoint. Our results revealed that the multi-omics Ridge regression model achieved the optimal performance in predicting pCR, with an AUC of 0.917. Through unsupervised clustering using the R package MOVICS and nine clustering algorithms, we identified four distinct multimodal breast cancer subtypes associated with NAT. These subtypes exhibited significant differences in proteomic profiles, hallmark cancer gene sets, pathway activities, tumor immune microenvironments, transcription factor activities, and clinical characteristics. For instance, CS1 subtype, predominantly ER-positive, had a low pCR rate and poor response to chemotherapy drugs, while CS4 subtype, characterized by high immune infiltration, showed a better response to immunotherapy. At the single-cell level, we detected significant heterogeneity in the tumor microenvironment among the four subtypes. Malignant cells in different subtypes displayed distinct copy number variations, differentiation levels, and evolutionary trajectories. Cell-cell communication analysis further highlighted differential interaction patterns among the subtypes, with implications for tumor progression and treatment response. Our multimodal diagnostic model and subtype analysis provide novel insights into predicting NAT efficacy in breast cancer. These findings hold promise for guiding personalized treatment strategies. Future research should focus on experimental validation, in-depth exploration of the underlying mechanisms, and extension of these methods to other cancers and treatment modalities.

Appraising histone H4 lysine 5 lactylation as a novel biomarker in breast cancer

Background Posttranslational modifications of histone lysine (K) have integral connections with cell metabolism, and participate in the carcinogenesis of various cancers. This study focuses on evaluating the expression of histone H4 lys 5 lactylation (H4K5lac) and its clinical role in breast cancer (BC). Methods During this research, immunohistochemistry (IHC) and immunoblotting, utilizing a specific primary anti-L-lactyl-histone H4 (Lys 5) rabbit monoclonal antibody, were employed to assess H4K5lac expression in BC tissue chips. H4K5lac expression in the peripheral blood mononuclear cells (PBMCs) of BC patients was investigated through immunoblotting. Results IHC revealed upregulation of histone H4K5lac in both triple-negative breast cancer (TNBC) and non-TNBC tissues, with positive rate of 91.40% [170/(150 + 19 + 17)] and 93.64% (103/110) in TNBC and non-TNBC tissues, respectively. The expression of H4K5lac demonstrated positive correlations with lymph nodes (%), and Ki-67 expression. Survival analysis indicated a negative correlation between H4K5lac expression and overall survival (OS) time in both TNBC (HR [hazard ratio] = 2.773, 95%CI [confidence interval]: 1.128–6.851, P = 0.0384) and non-TNBC cases (HR = 2.156, 95%CI: 1.011–4.599, P = 0.0275). Furthermore, elevated levels of H4K5lac were observed in the PBMCs of BC cases, and H4K5lac expression is positively correlated with serum lactate and carcinoma embryonic antigen (CEA) levels. Conclusions Histone H4K5lac exhibits increased levels in both BC tissues and PBMCs, suggesting its potential as a promising biomarker for BC. This study might pave the way toward novel lactylation treatment strategies in BC.

Breast Cancer Stem Cell Heterogeneity, Plasticity and Treatment Strategies

Breast Cancer Stem Cell Heterogeneity, Plasticity and Treatment Strategies

Formulation, Characterization, and Potential Therapeutic Implications of Encapsulated Recombinant Alpha-luffin in Niosomes.

The anticancer properties of recombinant α-luffin (LUF) are wellestablished. However, the cytotoxic effects of encapsulating LUF within niosomes on the SKBR3 breast cancer cell line have yet to be explored. Our study aimed to investigate whether this encapsulation strategy could improve cytotoxic effects. Alpha-luffin was expressed, purified, and refolded. Then, this protein was utilized to craft an optimal formulation, guided by experimental design. In this work, we have explored various physicochemical properties, including particle size, polydispersity index, zeta potential, morphology, entrapment efficiency, drug release and kinetics, storage stability, and FTIR spectroscopy. Additionally, we have assessed the cellular uptake and cytotoxic effect of the optimized niosome formulation on the SKBR3 breast cancer cell line. The optimized niosome exhibited a mean diameter of 315±6.4 nm (DLS). Successful encapsulation of LUF into regularly shaped, spherical niosomes was achieved, with an encapsulation efficiency of 73.45±2.4%. Notably, Niosomal LUF (NLUF) exhibited significantly increased cytotoxicity against SKBR3 cells. These findings suggest that niosomes loaded with LUF hold promise as a potential treatment strategy for breast cancer.

Adjuvant endocrine treatment strategies for non-metastatic breast cancer: a network meta-analysis.

Adjuvant endocrine treatment strategies for non-metastatic breast cancer: a network meta-analysis.

Discovery of New 4-Aminoquinoline-Thiazolidinone Hybrid Analogs as Antiproliferative Agents Inhibiting TLR4-LPS-Mediated Migration in Triple-Negative Breast Cancer Cells.

The Toll-like receptor 4 (TLR4) signaling pathway plays a leading role in triggering proinflammatory responses by targeting lipopolysaccharide (LPS) molecules from different bacteria. Meanwhile, it is also expressed at higher levels in breast cancer cells than in normal breast tissue. After LPS binding, it initiates downstream signaling pathways that promote inflammation and cell apoptosis. Thus, targeting TLR4-LPS presents a promising dual therapeutic strategy for breast cancer treatment by not only inhibiting tumor growth but also reducing inflammation within the tumor microenvironment. To achieve this, the discovery of a new antiinflammatory agent is needed to reduce LPS-mediated cancer cell proliferation and migration. In this study, a series of 4-aminoquinoline-thiazolidinone hybrid analogs (4a-m) have been synthesized to explore their antiinflammatory as well as anticancer activity to find a new lead. Among them, 4e revealed the most promising antiinflammatory (IC50 = 2.38 ± 0.77 μM) as well as anticancer activity (IC50 = 3.26 ± 1.06 μM) in RAW 267.7 cell line and triple-negative breast cancer (TNBC) cell line, respectively. Further structure-activity relationship study followed by MD simulation analysis was carried out to identify probable binding residues of TLR4 which may play a significant role in developing antiinflammatory activity for promoting cell apoptosis in cancer cells.

Mast cell activation induced by tamoxifen citrate via MRGPRX2 plays a potential adverse role in breast cancer treatment.

Mast cell activation induced by tamoxifen citrate via MRGPRX2 plays a potential adverse role in breast cancer treatment.

Inhibition of XIST restrains paclitaxel resistance in breast cancer cells by targeting hsa-let-7d-5p/ATG16L1 through regulation of autophagy

Inhibition of XIST restrains paclitaxel resistance in breast cancer cells by targeting hsa-let-7d-5p/ATG16L1 through regulation of autophagy