Prognosis Of Breast Cancer Patients Research Articles

Pretreatment plasma vitamin D and response to neoadjuvant chemotherapy in breast cancer: evidence from pooled analysis of cohort studies

Background: Biological evidence has revealed anti-tumor effect of vitamin D, but whether it could predict the response to neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients remains inconclusive. The aim was to investigate the association between pretreatment vitamin D level and response to NAC and subsequent survival outcomes in BC patients. Materials and Methods: We systematically searched the Medline, Embase, Cochrane Library and Web of Science databases and clinical trial registries to identify relevant articles from inception to October 8, 2024. Eligible studies investigating the associations between pretreatment plasma vitamin D and response to NAC in BC patients were selected according to the predefined criteria, with the study characteristics extracted by two reviewers. The primary outcome was pathological complete response (pCR), while overall pathological response and event-free survival (EFS) were adopted as secondary outcomes. Summary effect estimates of odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled using a random-effects model. Subgroup and sensitivity analyses were performed based on study characteristics and methodological quality. Results: Six retrospective cohort studies involving 1,291 BC patients were included. We observed a significant association between pretreatment vitamin D deficiency and 50% increased odds of non-pCR after NAC (OR=1.50, 95%CI 1.11-2.03, P=0.008) with no heterogeneity (I2=0%). We also identified a significant association of vitamin D with overall pathological response (OR=1.33, 95%CI 1.01-1.75, P=0.046). A similar association with EFS (HR=1.27, 95%CI 0.92-1.75, P=0.139) was also noted although the effect estimate was not statistically significant. Sensitivity analyses based on methodological quality showed consistent findings. Conclusion: Pretreatment vitamin D deficiency is associated with an inferior response to NAC in BC patients. Our meta-analysis advocates further prospective studies with large sample sizes before vitamin D supplementation could be administered to improve NAC response and subsequent prognosis of BC patients.

Micro-computed Tomography in the Evaluation of Eosin-stained Axillary Lymph Node Biopsies of Females Diagnosed with Breast Cancer.

Histopathological investigation of metastasis in core needle axillary lymph node (ALN) biopsies is crucial for the prognosis and treatment planning of breast cancer patients. Biopsies are typically sliced and evaluated as two-dimensional (2D) images. Biopsy sampling errors and the limited view provided by 2D histology are leading factors contributing to false-negative results in the preoperative detection of metastatic lymph nodes and underestimation of metastatic foci.In this proof-of-concept study, we aim to explore the technical feasibility and the potential capacities of tridimensional (3D) X-ray micro-computed tomography imaging to expedite error detection, enhancement of histopathological accuracy, and precise measurement of metastatic lesion on ALN core needle biopsies of two breast cancer patients. Our self-developed micro-CT protocol uses eosin for the first time, a common histological dye, to enhance 3D architecture of ALNs. Performed analysis on the images of the ALN biopsies involves cancer tissue segmentation, swift biopsy evaluation, and measurement of the metastatic longest diameter and deposit volume.The eosin micro-CT protocol shows potential for an improved tumor deposit estimates, offering additional clinical value compared to standard 2D histology, however, further studies for validating this method are needed.

Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response

Background/Objectives: Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. Methods: The anoikis-related prognostic signature (ANRS) was generated using a variety of machine learning methods, and the correlation between the ANRS and the tumor microenvironment (TME), drug sensitivity, and immunotherapy was investigated. Moreover, single-cell analysis and spatial transcriptome studies were conducted to investigate the expression of prognostic ANRGs across various cell types. Finally, the expression of ANRGs was verified by RT-PCR and Western blot analysis (WB), and the expression level of PLK1 in the blood was measured by the enzyme-linked immunosorbent assay (ELISA). Results: The ANRS, consisting of five ANRGs, was established. BC patients within the high-ANRS group exhibited poorer prognoses, characterized by elevated levels of immune suppression and stromal scores. The low-ANRS group had a better response to chemotherapy and immunotherapy. Single-cell analysis and spatial transcriptomics revealed variations in ANRGs across cells. The results of RT-PCR and WB were consistent with the differential expression analyses from databases. NU.1025 and imatinib were identified as potential inhibitors for SPIB and PLK1, respectively. Additionally, findings from ELISA demonstrated increased expression levels of PLK1 in the blood of BC patients. Conclusions: The ANRS can act as an independent prognostic indicator for BC patients, providing significant guidance for the implementation of chemotherapy and immunotherapy in these patients. Additionally, PLK1 has emerged as a potential blood-based diagnostic marker for breast cancer patients.

FABP4-mediated lipid accumulation and lipolysis in tumor-associated macrophages promote breast cancer metastasis.

A high density of tumor-associated macrophages (TAMs) is associated with poorer prognosis and survival in breast cancer patients. Recent studies have shown that lipid accumulation in TAMs can promote tumor growth and metastasis in various models. However, the specific molecular mechanisms that drive lipid accumulation and tumor progression in TAMs remain largely unknown. Herein, we demonstrated that unsaturated fatty acids (FAs), unlike saturated ones, are more likely to form lipid droplets in murine macrophages. Specifically, unsaturated FAs, including linoleic acids (LA), activate the FABP4/CEBPα pathway, leading to triglyceride synthesis and lipid droplet formation. Furthermore, FABP4 enhances lipolysis and FA utilization by breast cancer cell lines, which promotes cancer cell migration in vitro and metastasis in vivo. Notably, a deficiency of FABP4 in murine macrophages significantly reduces LA-induced lipid metabolism. Therefore, our findings suggest FABP4 as a crucial lipid messenger that facilitates unsaturated FA-mediated lipid accumulation and lipolysis in TAMs, thus contributing to the metastasis of breast cancer.

FABP4-mediated lipid accumulation and lipolysis in tumor-associated macrophages promote breast cancer metastasis

A high density of tumor-associated macrophages (TAMs) is associated with poorer prognosis and survival in breast cancer patients. Recent studies have shown that lipid accumulation in TAMs can promote tumor growth and metastasis in various models. However, the specific molecular mechanisms that drive lipid accumulation and tumor progression in TAMs remain largely unknown. Herein, we demonstrated that unsaturated fatty acids (FAs), unlike saturated ones, are more likely to form lipid droplets in murine macrophages. Specifically, unsaturated FAs, including linoleic acids (LA), activate the FABP4/CEBPα pathway, leading to triglyceride synthesis and lipid droplet formation. Furthermore, FABP4 enhances lipolysis and FA utilization by breast cancer cell lines, which promotes cancer cell migration in vitro and metastasis in vivo. Notably, a deficiency of FABP4 in murine macrophages significantly reduces LA-induced lipid metabolism. Therefore, our findings suggest FABP4 as a crucial lipid messenger that facilitates unsaturated FA-mediated lipid accumulation and lipolysis in TAMs, thus contributing to the metastasis of breast cancer.

The correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis.

This study aimed to explore the correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis. A total of 196 patients with surgically confirmed breast cancer between September 2019 and December 2023 were included. Data on preoperative B-mode ultrasound (US), color Doppler, and shear wave elastography (SWE) features of breast cancer masses were collected and analyzed to determine their correlation with axillary lymph node metastasis. The area under the receiver operating characteristic curve (AUC) of B-mode US, color Doppler, SWE, and the multi-mode predictive model for evaluating axillary lymph node metastasis were compared. Among the 196 patients, 70 had positive axillary lymph nodes, while 126 had negative axillary lymph nodes. There was no significant difference in the color features between the negative and positive axillary lymph node groups. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were identified as independent risk factors to predict axillary lymph node metastasis according to binary logistic regression analysis. The AUC of the predictive model based on these independent risk factors was 0.803 (95% CI: 0.739-0.867), which was significantly higher than that of B-mode US or SWE alone. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were found to be valuable for predicting axillary lymph node metastasis in patients with breast cancer. The predictive model developed in this study, combining the multi-mode ultrasonographic features of breast cancer masses, could serve as a noninvasive and convenient method to predict axillary lymph node status. This approach could aid in clinical decision-making and individualized treatment to improve the prognosis of breast cancer patients.

The Influence of treatment intervals on prognosis in young breast cancer patients: Insights from the French national cohort

BackgroundSuboptimal treatment delays is known to impact prognosis of patients with cancer but optimal timing in specific subgroups remains poorly studied. This study aimed to analyze treatment delays in young women treated for a breast cancer (BC) on and its impact on their prognosis using French Nationwide Data. MethodsUsing the CAREPAT-YBC Cohort based on the French National Healthcare System Database, we analyzed disease-free survival (DFS) in 22,093 young women (18-45 years) who underwent either surgery-chemotherapy-radiotherapy pathway (adjuvant setting, 15,433 patients) or chemotherapy-surgery-radiotherapy pathway (neoadjuvant setting, 6,660 patients), according to delays between the different pathways. ResultsFor the adjuvant chemotherapy-radiotherapy interval, the best timing was 17-31 days with increased risk above this delay. For the neoadjuvant setting, the optimal neoadjuvant chemotherapy-surgery interval was 17-31 days, while ≤15 days (HR 1.44, 95%CI 1.21-1.71) or ≥62 days (HR 2.07, 95%CI 1.36-3.15) showed poorer prognosis. Combining best timing into an "optimal pathway" was associated with respectively a 1.2-fold decreased risk for recurrence or mortality. ConclusionOptimizing treatment intervals enhance BC survival in younger age.

CLDN11 deficiency upregulates FOXM1 to facilitate breast tumor progression through hedgehog signaling pathway.

Claudins (CLDNs) play a crucial role in regulating the permeability of epithelial barriers and can impact tumor behavior through alterations in their expression. However, the precise mechanisms underlying the involvement of CLDNs in breast cancer progression remain unclear. This study aimed to investigate the role of CLDN11 in breast cancer progression. Utilizing the TCGA database and clinical specimens from breast cancer patients, we observed reduced expression of CLDN11 in tumor tissues, which correlated with poor prognosis in breast cancer patients. In vitro, silencing of CLDN11 enhanced the proliferative and migratory characteristics of breast cancer cell lines MCF-7 and MDA-MB-231. Mechanistically, CLDN11 deficiency promoted the upregulation of Forkhead Box M1 (FOXM1) by activating the hedgehog signaling pathway, thereby sustaining tumor progression in breast cancer. In vivo, blockade of hedgehog signaling suppressed the tumor progression induced by CLDN11 silencing. Our study highlights the significance of the CLDN11/FOXM1 axis in breast cancer progression, suggesting CLDN11 as a potential diagnostic indicator and therapeutic target for clinical therapy.

The dyslipidemic effect of cytostatics in the treatment of early breast cancer as a serious risk factor of cardiovascular diseases.

The development of highly effective anti-cancer therapies over the past several decades has dramatically changed the situation of patients with malignant tumor disease, who currently achieve a high rate of cure in the early stages of the disease. Despite tremendous progress, chemotherapy remains the primary treatment modality for early breast cancer. However, chemotherapy-related complications have a major impact on cardiovascular morbidity and mortality in this group of patients. Almost 80% of women diagnosed with breast cancer are over 50 years of age and already have risk factors for cardiovascular disease, such as age, family history, hypertension, elevated cholesterol, smoking, diabetes, and elevated body mass index. Most breast cancer patients do not die and, in line with the general population, cardiovascular disease remains the most common cause of death. Clinical research, extensive retrospective analyzes and prospective works describe the dyslipidemic effect of cytostatics, which may predispose to the development of atherosclerotic cardiovascular diseases. The administration of neoadjuvant or adjuvant chemotherapy based on anthracyclines and taxanes can lead to an increase in total cholesterol, triacylglycerides, LDL cholesterol and a decrease in HDL cholesterol. Abnormally high concentrations of lipids in the blood represent one of the main risk factors for the development and progression of cardiovascular diseases. The works also indicate a correlation between serum lipid levels and the rate of achieving pathological complete remission after the administration of neoadjuvant chemotherapy. Dyslipidemia is associated with a worse prognosis in breast cancer patients treated with neoadjuvant chemotherapy. The aim of the thesis is to point out the dyslipidemic effects of cytostatics and the risks of atherosclerotic cardiovascular diseases in breast cancer patients who have undergone adjuvant or neoadjuvant chemotherapy for early breast cancer. The identification of cardiovascular risk factors at the beginning of oncological treatment, the monitoring of the lipid spectrum during the treatment and the timely intervention of dyslipidemia treatment escape attention at present.

Predictive value of methylene blue combined with indocyanine green in sentinel lymph node metastasis in breast cancer: a prospective pilot cohort study.

The status of sentinel lymph nodes is crucial for prognosis and treatment decisions in breast cancer patients. This study aimed to evaluate the predictive value of combined methylene blue and indocyanine green for sentinel lymph node metastasis in breast cancer. This prospective cohort study enrolled 90 clinically node-negative breast cancer patients. Methylene blue and indocyanine green were injected locally before surgery. Sentinel lymph nodes were grouped based on fluorescence intensity and methylene blue staining. A binary logistic regression model was established using 285 lymph node groups to predict metastatic risk. A total of 475 lymph nodes were identified, with 33 being metastatic. The metastatic risk reached 70% for partially blue-stained and weakly fluorescent lymph nodes between 1-2 cm. The model revealed associations between lymph node size, dye staining patterns, and metastatic risks (P<0.05). The AUC of the ROC curve was 0.855. The staining pattern of combined methylene blue and indocyanine green could predict risks of sentinel lymph node metastasis and facilitate rapid intraoperative identification of high-risk lymph nodes.

The prognostic value of skeletal muscle mass and density in breast cancer: a systematic review and meta-analysis.

Aim: The effect of skeletal muscle mass and density on the long-term survival outcome of breast cancer patients is unclear.Materials & methods: Systematically searched all articles in PubMed, Web of science, Springerlink, EMBASEand Wiley databases that studied the association between skeletal muscle and survival outcomes of breast cancer by 25September 2023. The hazard ratios and confidence intervals of the multiple factor analysis results controlling for confounding variables in the study were collected and analyzed using STATA 14.0 software.Results: This meta-analysis included a total of 13 studies, with a median age of 48.2years. Meta results showed that the survival (hazard ratio [HR]: 0.98, 95% CI: 0.89-1.08) and recurrence (HR: 0.96, 95% CI: 0.92-1.00) outcomes of breast cancer patients with sarcopenia were not significantly affected compared with those without sarcopenia. No significant heterogeneity or publication bias was observed in the study.Conclusion: The conclusion that skeletal muscle is regarded as a useful factor that can guide and optimize the prognosis of breast cancer patients is uncertain, or the result is very weak. Considering the impact of research quality and confounding factors, prospective studies are needed in the future to further demonstrate.PROSPERO identifier: CRD42023463480 (www.crd.york.ac.uk/prospero).

7615 Genomic Consequences of GRHL2 Overexpression in ER+ Breast Cancer Cells

Abstract Disclosure: K.O. Allen: None. C. Zheng: None. N. Solodin: None. M.S. Ozers: Owner/Co-Owner; Self; Proteovista, LLC. C.L. Warren: None. P.E. Messa: None. D.T. Vogt: None. E.T. Alarid: None. Breast cancer progression is characterized by the presence and prevalence of metastatic disease. At a genomic level, metastasis can be facilitated via rearrangement of the chromatin landscape to expose oncogenic genes for transcription. Grainyhead like protein 2 (GRHL2) is a nuclear transcription factor implicated in epithelial cell differentiation. The GRHL2 motif has been found near activated estrogen receptor (ER) binding sites, and elevated levels of GRHL2 have been linked to worse prognosis in hormone receptor positive breast cancer patients. In its capacity to contribute to a more severe disease state when overexpressed, GRHL2 may function as either a transcription or pioneer factor to aid in the expression of metastasis-associated genes. Our lab previously showed that GRHL2 genomic binding precedes ER binding at co-regulated binding sites. Also, overexpression of GRHL2 in MCF7 cells for 24 hours did not appreciably alter gene expression by RNA-Seq. These data taken together indicate that GRHL2 may be exhibiting pioneer factor activity. However, the specific role of GRHL2 overexpression in hormone positive breast cancer progression remains unknown. In order to examine the mechanism of GRHL2 action, GRHL2 genomic binding was investigated using a tetracycline-inducible MCF7 model that allows controlled overexpression of GRHL2. ChIP studies were performed to determine GRHL2 binding intensity at specific and genome wide GRHL2 binding sites. Specific focus was given to established GRHL2 binding sites near oncogenic genes responsible for epithelial to mesenchymal transition (EMT), dormancy, and proto-oncogenic behavior. A similar analysis examined H3K27 acetylation to validate active gene transcription. An orthogonal technology, Specificity and Affinity for Protein (SNAP) microarrays, which characterizes direct GRHL2 binding to tiled genomic regions identified in ChIP-Seq analyses from multiple labs, was utilized to discriminate direct and indirect GRHL2 binding sites. The requirement for GRHL2 transactivation function in regulation of EMT related genes was further interrogated using transactivation GRHL2 dominant negative mutants. This work aims to distinguish the transcriptional and non-transcriptional activities of GRHL2 in breast cancer cells on a genome wide level and thereby, provide a deeper understanding of how overexpressed GRHL2 contributes to hormone positive breast cancer. Presentation: 6/3/2024

The prognostic role of survivin expression in breast cancer: A systematic review and meta-analysis.

Breast cancer is a heterogeneous condition with variations in histopathological, genomic, and biological characteristics. Although clinicopathological prognostic factors and gene expression profiles are commonly used to guide treatment decisions in patients with breast cancer, there is still a need for new prognostic markers. One potential marker is survivin, a protein belonging to the apoptosis inhibitor family. However, studies examining the relationship between survivin and prognosis in breast cancer have yielded inconsistent results. This study aimed to evaluate the impact of survivin expression on the prognosis of breast cancer patients through a meta-analysis. Studies evaluating survivin expression were sourced from the PubMed, Embase, and Cochrane databases. We conducted a meta-analysis based on full-text articles that evaluated the relationship between survivin expression and survival by immunochemistry or polymerase chain reaction. The studies were initially divided into 2 groups based on the evaluation of overall survival (OS) and disease-free survival (DFS). Subsequently, each group was further categorized according to the method used to detect survivin expression. Statistical analyses for this study were conducted using Stata and JAMOVI. After screening with keywords, we identified 24 retrospective studies evaluating OS and 15 retrospective studies evaluating DFS, which were included in the analysis. We found that the studies in the meta-analysis were not heterogeneous, and this remained consistent when categorizing the groups by survivin expression detection. Survivin expression was associated with OS (HR 1.23, 95% CI 0.81-1.65) and DFS (HR 0.89, CI 0.42-1.36), indicating poor prognosis. This significant relationship between survivin expression and survival persisted when the studies were categorized by the detection method, either immunohistochemistry or polymerase chain reaction. In this study, we evaluated the prognostic significance of survivin expression in patients with breast cancer through a meta-analysis. These results support the use of survivin expression as a prognostic marker in breast cancer, potentially guiding treatment decisions.

Withaferin A decreases glycolytic reprogramming in breast cancer

Reprogrammed glucose metabolism is considered as the hallmark of cancer with therapeutic implications. Phytocompounds have potential to inhibit cancer metabolism. Here, we tested the ability of Withaferin A (WA), a withanolide derived from Withania somnifera, in modulating cancer metabolism. The assessed effect of WA on aerobic glycolysis in breast cancer cell lines showed that WA decreases the glucose uptake, lactate production and ATP generation by inhibiting the expression of key glycolytic enzymes i.e., GLUT1, HK2 and PKM2. We also identified that WA induced inhibition of cancer glycolysis by targeting c-myc as validated by silencing experiments followed by metabolic readouts. Decreased glycolysis resulted in reduced cell viability, biomass and colony forming ability of breast cancer cells. To further validate our in vitro findings in breast cancer patients, we analyzed 90 metabolic pathways in ~ 2000 breast tumors and observed that glycolysis is the most deregulated pathway in breast tumors. Deregulated glycolysis also predicted poor prognosis in breast cancer patients. In addition, patient data showed correlation between c-myc expression and glycolytic deregulation in breast cancer. Taken together, our results highlight the role of WA in inhibiting breast cancer metabolism via c-myc/glycolysis axis.

FMRP protects breast cancer cells from ferroptosis by promoting SLC7A11 alternative splicing through interacting with hnRNPM

Ferroptosis is a unique modality of regulated cell death that is driven by iron-dependent phospholipid peroxidation. N6-methyladenosine (m6A) RNA modification participates in varieties of cellular processes. However, it remains elusive whether m6A reader Fragile X Mental Retardation Protein (FMRP) are involved in the modulation of ferroptosis in breast cancer (BC). In this study, we found that FMRP expression was elevated and associated with poor prognosis and pathological stage in BC patients. Overexpression of FMRP induced ferroptosis resistance and exerted oncogenic roles by positively regulating a critical ferroptosis defense gene SLC7A11. Mechanistically, upregulated FMRP catalyzes m6A modification of SLC7A11 mRNA and further influences the SLC7A11 translation through METTL3-dependent manner. Further studies revealed that FMRP interacts with splicing factor hnRNPM to recognize the splice site and then modulated the exon skip splicing event of SLC7A11 transcript. Interestingly, SLC7A11-S splicing variant can effectively promote FMRP overexpression-induced ferroptosis resistance in BC cells. Moreover, our clinical data suggested that FMRP/hnRNPM/SLC7A11 expression were significantly increased in the tumor tissues, and this signal axis was important evaluation factors closely related to the worse survival and prognosis of BC patients. Overall, our results uncovered a novel regulatory mechanism by which high FMRP expression protects BC cells from undergoing ferroptosis. Targeting the FMRP–SLC7A11 axis has a dual effect of inhibiting ferroptosis resistance and tumor growth, which could be a promising therapeutic target for treating BC.

A novel arginine methylation-associated lncRNA signature effectively predicts prognosis in breast cancer patients.

Breast cancer (BC) is a disease highly associated with epigenetic modification, and arginine methylation is particularly important in its genetic regulation. However, the role of arginine methylation related lncRNAs in breast cancer has not been studied. First, we identified the related lncRNAs (from TCGA database) according to the differentially expressed genes related to arginine methylation in breast cancer. Then the lncRNAs related to protein arginine methylation were obtained by regression analysis, and the risk score model was constructed. Finally, the cell experiment and subcutaneous tumor model verified that the arginine methylation related lncRNA z68871.1 in the model had a significant effect on the proliferation and invasion of breast cancer cells. In conclusion, we successfully constructed an arginine methylation related lncRNA model, which has strong predictive ability. At the same time, this study provides an experimental basis for exploring the mechanism of arginine methylation in BC and helps to find new biomarkers of BC.

TMCO1 is upregulated in breast cancer and regulates the response to pro-apoptotic agents in breast cancer cells

AbstractThe release of Ca2+ ions from endoplasmic reticulum calcium stores is a key event in a variety of cellular processes, including gene transcription, migration and proliferation. This release of Ca2+ often occurs through inositol 1,4,5-triphosphate receptors and the activity of these channels and the levels of stored Ca2+ in the endoplasmic reticulum are important regulators of cell death in cancer cells. A recently identified Ca2+ channel of the endoplasmic reticulum is transmembrane and coiled-coil domains 1 (TMCO1). In this study, we link the overexpression of TMCO1 with prognosis in node-positive basal breast cancer patients. We also identify interacting proteins of TMCO1, which include endoplasmic reticulum-resident proteins involved in Ca2+ regulation and proteins directly involved in nucleocytoplasmic transport. Interacting proteins included nuclear transport proteins and TMCO1 was shown to have both nuclear and endoplasmic reticulum localisation in MDA-MB-231 basal breast cancer cells. These studies also define a role for TMCO1 in the regulation of breast cancer cells in their sensitivity to BCL-2/MCL-1 inhibitors, analogous to the role of inositol 1,4,5-triphosphate receptors in the regulation of cell death pathways activated by these agents.

Honokiol Exhibits Anti-Tumor Effects in Breast Cancer by Modulating the miR-148a-5p-CYP1B1 Axis.

Breast cancer (BC) is the most frequently diagnosed malignancy in female patients. There is a significant lack of therapeutic strategies for BC, particularly triple-negative breast cancer (TNBC). Honokiol (HNK), a lignin extracted from the Magnolia genus plant, has demonstrated numerous pharmacological effects. Therefore, this study aims to investigate the antitumor effect of HNK on BC cells and employ high-throughput sequencing to elucidate its potential mechanism. We found that HNK significantly inhibited proliferation and induced apoptosis on BC cell lines in a dose-dependent manner. Moreover, HNK treatment suppressed migration and colony formation and initiated the intrinsic apoptotic pathway specifically in MDA-MB-231 cells. High-throughput sequencing and bioinformatics analysis revealed that miR-148a-5p expression was significantly up-regulated, whereas CYP1B1 expression was down-regulated following HNK treatment. Importantly, survival analysis based on TCGA database showed high miR-148a-5p expression was correlated with a better prognosis for BC patients. Inhibition of miR-148a-5p by inhibitor not only increased cell viability but also attenuated apoptosis induced by HNK.Finally, a strong synergistic effect between HNK and paclitaxel was observed in vitro. In conclusion, our study validated the antitumor efficacy of HNK against human BC cells and elucidated its underlying mechanism through high-throughput sequencing, thereby providing compelling evidence for further exploration of the potential clinical application of HNK towards the treatment of BC.

Prognostic prediction of breast cancer patients using machine learning models: a retrospective analysis.

Breast cancer is a common and complex disease, with various clinical features affecting prognosis. Accurate prediction of prognosis is essential for guiding personalized treatment strategies. This study aimed to develop machine learning models for predicting prognosis in breast cancer patients using retrospective data. A total of 6,477 patients from Affiliated Sir Run Run Shaw Hospital were included, and their electronic medical records (EMRs) were thoroughly examined to identify 15 clinical features significantly associated with breast cancer survival. We employed eight different machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), to develop and evaluate the predictive performance of the models. In addition, to investigate the sensitivity of different training/testing set radio to model performance, we examined five sets of ratios: 50:50, 60:40, 70:30, 80:20, 90:10. Among these models, XGBoost demonstrated the highest performance with receiver operating characteristic (ROC) area under the curve (AUC) of 0.813, accuracy of 0.739, sensitivity of 0.815, and specificity of 0.735. Further statistical analysis identified several significant predictors of prognosis, including age, tumor size, lymph node status, and hormone receptor status. The XGBoost model was found to exhibit superior predictive power compared to established prognostic models such as the Nottingham Prognostic Index (NPI) and Predict Breast. Based on the successful performance of the XGBoost model, we developed a prognosis prediction tool specifically designed for breast cancer, providing valuable insights to clinicians, and aiding them in making informed treatment decisions tailored to individual patients. Our study highlights the potential of machine learning models in accurately predicting prognosis for breast cancer patients, ultimately facilitating personalized treatment strategies. Further research and validation are warranted to fully integrate these models into clinical practice.

Peripheral NK cell count predicts response and prognosis in breast cancer patients underwent neoadjuvant chemotherapy.

The count of lymphocyte subsets in blood can reflect the immune status of the body which is closely related to the tumor immune microenvironment and the efficacy of NAT. This study aims to explore the relationship between peripheral blood lymphocyte subsets and the efficacy and prognosis of NAT in breast cancer. We retrospectively analyzed clinicopathological information and peripheral blood lymphocyte subpopulation counts of patients receiving NAT from January 2015 to November 2021 at Sun Yat-sen University Cancer Center. Kaplan-Meier curves were used to estimate the survival probability. The independent predictors of NAT response and survival prognosis were respectively analyzed by multivariate logistic regression and Cox regression, and nomograms were constructed accordingly. The prediction efficiency of three nomograms was validated separately in the training cohort and the testing cohort. 230 patients were included in the study, consisting of 161 in the training cohort and 69 in the testing cohort. After a median follow-up of 1238 days, patients with higher NK cell value showed higher pCR rates and higher OS and RFS after NAT (all P < 0.001). Multivariate analyses suggested NK cell count was an independent predictor of NAT response, OS and RFS. We then built nomograms accordingly and validated the prediction performance in the testing cohort (C index for NAT response: 0.786; for OS: 0.877, for RFS: 0.794). Peripheral blood NK cell count is a potential predictive marker for BC patients receiving NAT. Nomograms based on it might help predict NAT response and prognosis in BC.