
Shuang Zhang,1,* Jing Zhao,2,* Yuzhe Zhao,3 Zheng Zhi,1,4 Huanfang Fan,1 Na Li,2 Jiankang Liu,2,5 Qingxia Li21Department of Oncology, Hebei Province Traditional Chinese Medicine Hospital, Shijiazhuang, Hebei, People’s Republic of China; 2Department of Oncology, Hebei General Hospital, Shijiazhuang, Hebei, People’s Republic of China; 3Department of Gland Surgery, Hebei General Hospital, Shijiazhuang, Hebei, People’s Republic of China; 4College of Traditional Chinese Medicine, Hebei University of Chinese Medicine, Shijiazhuang, Hebei, People’s Republic of China; 5Graduate School, Hebei Medical University, Shijiazhuang, Hebei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jing Zhao, Department of Oncology, Hebei General Hospital, No. 348 Heping West Road, Xinhua District, Shijiazhuang, Hebei, 050051, People’s Republic of China, Email zzzjmail@163.comObjective: This study investigates the prognostic utility of lipid biomarkers in breast cancer (BC) and constructs nomograms incorporating the triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio to facilitate individualized outcome prediction.Methods: A total of 563 patients with stage I–III breast cancer who underwent mastectomy at Hebei General Hospital between July 2017 and July 2020 were retrospectively analyzed in this single-centre study. Patients were randomly allocated into a training cohort (N=394) and a validation cohort (N=169). Associations between lipid biomarkers, clinicopathological factors, and patient outcomes—overall survival (OS) and disease-free survival (DFS)—were evaluated using Cox proportional hazards models. Nomograms were subsequently constructed from variables identified in multivariate analyses. Predictive performance was assessed via Akaike Information Criterion (AIC), time-dependent ROC curves, calibration plots, decision curve analysis (DCA), concordance index (C-index), and risk group stratification.Results: Preoperative TG/HDL-C, TNM stage, and molecular subtype emerged as significant predictors of OS in BC patients, whereas TG/HDL-C and TNM stage demonstrated prognostic value for DFS. The derived and internally validated nomograms displayed robust predictive performance. For OS prediction, the 1-, 3-, and 5-year time-dependent AUCs reached 0.868, 0.913, 0.966 in the training cohort and 0.877, 0.921, 0.933 in the validation cohort, with corresponding C-indexes of 0.892 (95% CI: 0.868– 0.916) and 0.907 (95% CI: 0.874– 0.939), respectively. For DFS prediction, the 1-, 3-, and 5-year time-dependent AUCs were 0.797, 0.760, 0.788 for the training cohort and 0.644, 0.700, 0.755 for the validation cohort, accompanied by C-indexes of 0.737 (95% CI: 0.682– 0.792) and 0.664 (95% CI: 0.544– 0.784). The nomograms had better discrimination, calibration and clinical utility than TNM staging, with stable performance in the validation cohort. A user-friendly web calculator was built for clinical use.Conclusion: This study performed the development and internal validation of prognostic nomograms. The preoperative TG/HDL-C ratio serves as a potential prognostic indicator for OS and DFS in stage I–III BC. The nomogram integrating this ratio, TNM stage and molecular subtype represents an exploratory tool for personalized risk stratification. These findings warrant further validation in independent prospective multicenter cohorts before any clinical application.Keywords: breast cancer, blood lipid, TG/HDL-C, nomogram, prognosis
The presence of bone metastasis represents one of the common and toughest complications of breast cancer that significantly increases the morbidity rate. Currently available therapies for treating breast cancer have been able to ameliorate symptoms, but still suffer from insufficient accumulation of the drugs in bone metastatic sites and severe side effects on the whole body. The use of drug delivery systems based on nanomedicine has been demonstrated to be a promising approach in improving drug accumulation and pharmacodynamics of drugs in pre-clinical models. Engineered nanoparticles could be tailored in order to improve accumulation in the tumor environment and provide the delivery of drugs to bone metastatic regions. Moreover, recent advances in nanotechnology have provided many new options for imaging and therapeutic experiments in metastatic cancers. Modulation of tumor‑associated macrophage (TAM) polarization represents one of the recently described strategies since M2-like phenotype contributes to tumor growth, immunosuppression and metastasis development, while induction of M1-like phenotype has been proven to be effective in enhancing anti-tumor immune response in pre-clinical models. In this review, we discuss recent advances in the nanomedicine approach that targets TAM polarization in breast cancer bone metastasis, the rationale of the proposed strategies, therapeutic potential and limitations.
Bilateral primary breast cancer (BPBC) accounts for 2-12% of all breast cancers, with an increasing incidence trend. However, its clinical management remains challenged by the absence of unified diagnostic criteria, lack of evidence-based therapeutic guidelines, incomplete prognostic assessment frameworks, and a paucity of data from Asian populations. This narrative review critically synthesizes literature from PubMed, Web of Science, and CNKI databases (2020-2025) across seven dimensions: diagnosis and differential diagnosis, clinicopathological features, risk factors, imaging, genetics, treatment, and prognosis. Current evidence demonstrates that SBBC and MBBC exhibit significant heterogeneity in age at onset, molecular subtype distribution, and prognosis, with bilateral receptor discordance rates of 11-23%, mandating separate evaluation of each side; all current treatment recommendations are extrapolated from unilateral breast cancer evidence, leaving decisions in cases of subtype discordance without evidence-based support; and existing genetic risk models and clinical evidence are predominantly derived from Western populations, with only limited single-center retrospective data available from Asian populations but systematic, high-quality evidence remaining insufficient, such that direct application carries a risk of systematic bias. This review aims to provide an evidence-based reference for standardized clinical practice, emphasizing the urgent need to establish unified diagnostic criteria, develop population-specific risk models for Asian populations, and conduct dedicated prospective trials.
Background:Reliable biomarkers for predicting response to neoadjuvant chemotherapy (NAC) in breast cancer remain limited. This study evaluated the association of pretreatment Albumin-to-Neutrophil Ratio (ANR) and IronMLR with pathological response following NAC. Methods:This retrospective study included 71 patients with breast cancer treated with NAC. Pretreatment inflammatory indices were calculated from routine blood samples obtained before treatment initiation. ANR and IronMLR were compared across pathological response groups. Receiver operating characteristic (ROC) analysis was performed to evaluate predictive performance. Results:The mean age was 53.9±10.6 years, and pathological complete response (pCR) was achieved in 30 patients (42.3%). ANR was not significantly associated with pathological response (p=0.121). In contrast, IronMLR levels differed significantly among complete responders, partial responders, and non-responders (p<0.001). ROC analysis demonstrated favorable discriminatory performance of IronMLR for predicting treatment response, with an area under the curve of 0.909 (95% CI, 0.832-0.986; p<0.001). An IronMLR cut-off value of 175.40 yielded 77.4% sensitivity and 77.8% specificity. Patients with IronMLR ≥175.40 exhibited significantly higher response rates than those with lower values (96.0% vs 66.7%, p=0.001). Conclusion:Pretreatment IronMLR was significantly associated with pathological response following NAC in patients with breast cancer, whereas ANR showed no significant association. Given its simplicity and accessibility, IronMLR may represent a potentially useful biomarker for treatment stratification. Further prospective multicenter studies are warranted to validate these findings.
Background:Breast cancer remains a leading cause of female mortality worldwide, with therapeutic benefit limited by tumor heterogeneity and drug resistance. Identification of novel therapeutic targets through integration of genetic causality inference and functional validation is urgently needed. Methods:Plasma protein quantitative trait loci (pQTL) from the Fenland cohort (~10,700 individuals) and the FinnGen R10 SomaScan subset (n = 828) were integrated with breast cancer genome-wide association study data from the Breast Cancer Association Consortium (122,977 cases and 105,974 controls). Causal protein-disease relationships were inferred using summary-data-based Mendelian randomization (SMR), with colocalization and HEIDI tests. Multi-level validation was performed using TCGA-BRCA transcriptomic data. Functional validation included CCK-8, EdU, wound healing, Transwell invasion, and flow cytometry apoptosis analysis evaluated CPNE1 knocdown and/or overexpression of the MST1 gene which encodes macrophage-simulating protein (MSP). Results:SMR identified 23 proteins in Fenland and 10 in FinnGen at FDR < 0.05. MST1/MSP and CPNE1 were supported in both datasets with PP.H4 ≥ 0.80 and non-significant HEIDI tests. Genetically predicted circulating MSP was positively associated with breast cancer risk, whereas circulating CPNE1 showed an inverse association. TCGA-BRCA showed higher CPNE1 mRNA in tumors (P = 2.57×10⁻25) and lower MST1 mRNA (P = 3.04×10⁻23). CPNE1 expression was highest in triple-negative breast cancer and correlated positively with clinical stage (ρ = 0.211), whereas MST1 expression was lowest in triple-negative breast cancer and correlated inversely with stage (ρ = -0.164). In T47D and MDA-MB-231 cells, CPNE1 knockdown and MST1 overexpression each reduced proliferation, migration, and invasion and increased apoptosis; the combined group showed greater changes than either single intervention. Conclusion:This study prioritizes the MST1 gene, which encodes MSP, and CPNE1 as candidate proteins for further investigation in breast cancer. However, the circulating-protein associations, tumor-mRNA patterns, and cell-autonomous perturbations represent distinct and directionally discordant biological contexts. The findings therefore support context-dependent candidate roles and justify mechanistic, in vivo, and formal interaction studies, but do not yet establish therapeutic efficacy or synergy.
Meng Jiang,1,* Qilong Wang,2,* Hong Xu11Department of Oncology, First Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, 215000, People’s Republic of China; 2Department of Neurosurgery, Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, 215000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hong Xu, Department of Oncology, First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Gusu District, Suzhou City, Jiangsu Province, 215000, People’s Republic of China, Email xuhong1234521@163.comBackground: Breast cancer remains a leading cause of female mortality worldwide, with therapeutic benefit limited by tumor heterogeneity and drug resistance. Identification of novel therapeutic targets through integration of genetic causality inference and functional validation is urgently needed.Methods: Plasma protein quantitative trait loci (pQTL) from the Fenland cohort (~10,700 individuals) and the FinnGen R10 SomaScan subset (n = 828) were integrated with breast cancer genome-wide association study data from the Breast Cancer Association Consortium (122,977 cases and 105,974 controls). Causal protein-disease relationships were inferred using summary-data-based Mendelian randomization (SMR), with colocalization and HEIDI tests. Multi-level validation was performed using TCGA-BRCA transcriptomic data. Functional validation included CCK-8, EdU, wound healing, Transwell invasion, and flow cytometry apoptosis analysis evaluated CPNE1 knocdown and/or overexpression of the MST1 gene which encodes macrophage-simulating protein (MSP).Results: SMR identified 23 proteins in Fenland and 10 in FinnGen at FDR < 0.05. MST1/MSP and CPNE1 were supported in both datasets with PP.H4 ≥ 0.80 and non-significant HEIDI tests. Genetically predicted circulating MSP was positively associated with breast cancer risk, whereas circulating CPNE1 showed an inverse association. TCGA-BRCA showed higher CPNE1 mRNA in tumors (P = 2.57× 10⁻25) and lower MST1 mRNA (P = 3.04× 10⁻23). CPNE1 expression was highest in triple-negative breast cancer and correlated positively with clinical stage (ρ = 0.211), whereas MST1 expression was lowest in triple-negative breast cancer and correlated inversely with stage (ρ = − 0.164). In T47D and MDA-MB-231 cells, CPNE1 knockdown and MST1 overexpression each reduced proliferation, migration, and invasion and increased apoptosis; the combined group showed greater changes than either single intervention.Conclusion: This study prioritizes the MST1 gene, which encodes MSP, and CPNE1 as candidate proteins for further investigation in breast cancer. However, the circulating-protein associations, tumor-mRNA patterns, and cell-autonomous perturbations represent distinct and directionally discordant biological contexts. The findings therefore support context-dependent candidate roles and justify mechanistic, in vivo, and formal interaction studies, but do not yet establish therapeutic efficacy or synergy.Keywords: breast cancer, CPNE1, MST1, Mendelian randomization, therapeutic target, SMR
Huixi Zhong,1,2 Di Lu,1,2 Yaling Zeng,1,2 Xihui Tu,3 Purong Zhang,2 Tengfei Xing21School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, People’s Republic of China; 2Department of Breast, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610041, People’s Republic of China; 3College of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of ChinaCorrespondence: Purong Zhang, Email zprrong123321@163.com Tengfei Xing, Email xingtengfei@scszlyy.org.cnAbstract: Bilateral primary breast cancer (BPBC) accounts for 2– 12% of all breast cancers, with an increasing incidence trend. However, its clinical management remains challenged by the absence of unified diagnostic criteria, lack of evidence-based therapeutic guidelines, incomplete prognostic assessment frameworks, and a paucity of data from Asian populations. This narrative review critically synthesizes literature from PubMed, Web of Science, and CNKI databases (2020– 2025) across seven dimensions: diagnosis and differential diagnosis, clinicopathological features, risk factors, imaging, genetics, treatment, and prognosis. Current evidence demonstrates that SBBC and MBBC exhibit significant heterogeneity in age at onset, molecular subtype distribution, and prognosis, with bilateral receptor discordance rates of 11– 23%, mandating separate evaluation of each side; all current treatment recommendations are extrapolated from unilateral breast cancer evidence, leaving decisions in cases of subtype discordance without evidence-based support; and existing genetic risk models and clinical evidence are predominantly derived from Western populations, with only limited single-center retrospective data available from Asian populations but systematic, high-quality evidence remaining insufficient, such that direct application carries a risk of systematic bias. This review aims to provide an evidence-based reference for standardized clinical practice, emphasizing the urgent need to establish unified diagnostic criteria, develop population-specific risk models for Asian populations, and conduct dedicated prospective trials.Keywords: bilateral primary breast cancer, synchronous bilateral breast cancer, metachronous bilateral breast cancer, clinicopathological features, risk factors, prognosis
Emre Özge,1 Rıza Umar Gürsu,1 Bünyamin Güney,1 Özgür Han,1 Çiğdem Yıldırım,1 İlkay Gültürk,1 Servet Emir,2 Hülya Nur Özge31Department of Medical Oncology, University of Health Sciences Türkiye, İstanbul Training and Research Hospital, İstanbul, Türkiye; 2Department of İnternal Medicine, Ümraniye Training and Research Hospital, İstanbul, Türkiye; 3Department of Medical Oncology, Institute of Oncology, Istanbul University, İstanbul, TürkiyeCorrespondence: Emre Özge, Department of Medical Oncology, University of Health Sciences Türkiye, İstanbul Training and Research Hospital, İstanbul, Türkiye, Email emre_ozge89@hotmail.comBackground: Reliable biomarkers for predicting response to neoadjuvant chemotherapy (NAC) in breast cancer remain limited. This study evaluated the association of pretreatment Albumin-to-Neutrophil Ratio (ANR) and IronMLR with pathological response following NAC.Methods: This retrospective study included 71 patients with breast cancer treated with NAC. Pretreatment inflammatory indices were calculated from routine blood samples obtained before treatment initiation. ANR and IronMLR were compared across pathological response groups. Receiver operating characteristic (ROC) analysis was performed to evaluate predictive performance.Results: The mean age was 53.9± 10.6 years, and pathological complete response (pCR) was achieved in 30 patients (42.3%). ANR was not significantly associated with pathological response (p=0.121). In contrast, IronMLR levels differed significantly among complete responders, partial responders, and non-responders (p< 0.001). ROC analysis demonstrated favorable discriminatory performance of IronMLR for predicting treatment response, with an area under the curve of 0.909 (95% CI, 0.832– 0.986; p< 0.001). An IronMLR cut-off value of 175.40 yielded 77.4% sensitivity and 77.8% specificity. Patients with IronMLR ≥ 175.40 exhibited significantly higher response rates than those with lower values (96.0% vs 66.7%, p=0.001).Conclusion: Pretreatment IronMLR was significantly associated with pathological response following NAC in patients with breast cancer, whereas ANR showed no significant association. Given its simplicity and accessibility, IronMLR may represent a potentially useful biomarker for treatment stratification. Further prospective multicenter studies are warranted to validate these findings.Keywords: breast cancer, neoadjuvant chemotherapy, pathological response, pathological complete response, IronMLR, albumin-to-neutrophil ratio, systemic inflammation
Introduction:The SWI/SNF (SWItch/Sucrose Non - Fermentable) complex is a multi - subunit, ATPase - dependent chromatin - remodeling complex involved in regulating key cellular processes. Tumors with SWI/SNF loss tend to be poorly differentiated and aggressive. Triple - negative breast cancer (TNBC) typically has a high histological grade and a poor prognosis. Given the limited reports on the SWI/SNF complex in breast cancer, we focused on its role in TNBC. Methods:Using tissue microarray and immunohistochemistry (IHC), we evaluated the expression of four important subunits of the SWI/SNF complex (SMARCB1, SMARCA2, ARID1A, and SMARCA4) in 104 TNBC tissues, which included 96 cases of conventional TNBC and 8 cases of low - grade TNBC. Additionally, we evaluated the endogenous expression of the four subunits in five breast cancer cell lines by real - time quantitative PCR (RT - qPCR). These cell lines consisted of two TNBC cell lines (MDA - MB - 231, MDA - MB - 468) and three non - TNBC cell lines (MCF - 7, T47D, and MDA - MB - 453). Results:The IHC results indicated that the deletion rate of SMARCA2 was the highest in TNBC compared with other subunits (91/104, 87.5%) (p < 0.0001), and SMARCA4 had the highest retention rate (98/104, 94.2%). Whether low - grade TNBC was excluded or not, there was no significant difference between the deletion rate and various clinicopathological parameters. Consistently, we found that SMARCA2 exhibited the lowest expression level across all five cell lines (p < 0.01). SMARCA4 showed the highest expression in all cell lines except MDA - MB - 453, in which ARID1A expression was the highest. Conclusion:These results indicate that TNBC is characterized by a high proportion of SMARCA2 deletion and positive expression of SMARCA4, which are significant molecular features. The roles and potential mechanisms of these two factors in TNBC require further investigation.
Introduction:Proteome-guided liquid biopsy tests hold immense promise for the future of early cancer detection. Here, we analyzed the plasma proteome of 1,259 biobanked samples consisting of healthy women and women with breast cancer. The Astrin Biosciences' breast cancer early detection test is a laboratory developed test (LDT) that uses a protein-based machine learning classifier to identify breast cancer with high accuracy. Methods:The classifier was trained on 845 women (466 healthy and 379 with newly diagnosed, treatment naïve breast cancer) and validated on 397 women (195 healthy and 202 breast cancer) from the same collection cohort (held-out validation). All plasma samples were processed in an automated, blinded manner coupled with semi-quantitative, label-free mass spectrometry (MS)-based analysis. Results:The held-out validation performance achieved 92.3% specificity (180/195; 95% Wilson CI: 87.7-95.3%), 92.6% sensitivity (187/202; 95% Wilson CI: 88.1-95.4%) and an AUC of 0.975 (95% Bootstrap CI: 0.961-0.987). Observed sensitivity remained high across all breast cancer stages and pathological and molecular subtypes, albeit with small sample sizes for some subtypes. Gene set enrichment analyses (GSEA) identified epithelial-to-mesenchymal transition (EMT) and PI3K-AKT signaling as enriched in the breast cancer samples, highlighting that our test may possibly identify cancer-related proteins in early-stage patients. A simulated population demonstrates the utility of our test as a supplement to mammography, detecting nearly all (93%) breast cancers missed by mammography and reducing the number of false positives relative to MRI and Contrast-Enhanced Mammography (CEM) alone by >10-fold. Discussion:Overall, our proteomic data demonstrates high sensitivity and specificity in women with breast cancer, especially at early stages, and is a favorable supplemental test post mammogram.
Objective:To investigate whether exosomes derived from paclitaxel (PTX)-resistant breast cancer cells confer chemoresistance to parental cells and to explore the involvement of the p53/PI3K/AKT/mTOR signaling pathway in this process. Methods:Exosomes were isolated from PTX-sensitive and PTX-resistant breast cancer cells (MCF-7 and MDA-MB-231) and characterized by transmission electron microscopy, nanoparticle tracking analysis, and detection of exosomal markers. Bioinformatics analyses were performed to predict microRNAs potentially targeting TP53. Functional assays, including Cell Counting Kit-8 (CCK-8), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), quantitative real-time PCR (qRT-PCR), and Western blotting, were used to assess drug sensitivity, apoptosis, and pathway-related molecular changes in recipient cells. MicroRNA inhibition and p53 overexpression approaches were applied for mechanistic validation, and key experiments were conducted in multiple breast cancer cell models. Results:Exosomes derived from PTX-resistant cells significantly enhanced PTX resistance and attenuated apoptosis-related changes in recipient cells. Inhibition of exosomal miR-21 or restoration of p53 expression reversed these effects. Similar results were observed across different breast cancer subtypes. Conclusion:These findings indicate that exosomal miR-21 derived from PTX-resistant breast cancer cells may contribute to chemoresistance, at least in part, by suppressing p53 and modulating PI3K/AKT/mTOR pathway activation.
Purpose:To explore the value of combined quantitative shear wave elastography (SWE) parameters and breast cancer molecular markers for the differential diagnosis of benign and malignant breast masses. Methods:This study retrospectively analyzed the clinical data of 225 patients who underwent conventional ultrasound, SWE examinations, immunohistochemical analysis, and measurement of serum tumor markers CA15-3 and CA125. Based on the pathological diagnoses, the patients were categorized into malignant (n=107) and benign (n=118) mass groups. Results:The malignant mass group exhibited significantly higher values of quantitative SWE parameters, including maximum elasticity (E max), Shell1 E max, Shell2 E max, and Shell3 E max, than the benign mass group (P<0.05). Hemodynamic indicators, including the maximum blood flow velocity, resistance index, and pulsatility index, were also markedly elevated in the malignant mass group (P<0.05). Regarding the SWE imaging classification, the malignant mass group primarily corresponded to Types IV and V, whereas the benign mass group was mainly classified as Types I and II (P<0.001). Serum tumor markers CA15-3 and CA125 were significantly elevated in the malignant mass group. The combined detection of quantitative SWE parameters, CA15-3, and CA125 demonstrated higher AUC values than single detection, suggesting that the integration of SWE parameters with CA15-3 and CA125 significantly enhances diagnostic efficacy in differentiating benign from malignant breast masses (P<0.01). Conclusion:The combined detection of quantitative SWE parameters and breast cancer molecular markers significantly enhances the accuracy of differentiating benign from malignant breast masses.
Purpose:Breast cancer (BC) is a highly heterogeneous malignancy, and current treatments often suffer from toxicity, limited selectivity, and high cost. This study aimed to integrate transcriptome-level data, multi-layered network analysis, and drug repositioning strategies to identify candidate diagnostic and prognostic biomarkers for BC and propose potential repositioned drug candidates. Methods:Differentially expressed genes (DEGs) were identified from the GSE42568 dataset (|log2FC| > 1 and p < 0.05). Functional enrichment analyses were conducted using GO and KEGG. Three biological interaction layers - protein-protein interactions, transcription factors, and miRNA-mRNA interactions were constructed, and hub nodes were identified using topological metrics. Kaplan-Meier analyses assessed survival associations. PCA evaluated sample separation across datasets in GSE42568, GSE113865, and GSE22820. Drug repositioning was performed using L1000CDS2, and in vitro validation of a top drug candidate (niclosamide) and an exploratory comparative compound (amitriptyline) was performed using MCF-7 cells, including viability and combination assays. Results:A total of 4266 DEGs were identified. Network analyses revealed 37 hub signatures, 11 of which-ESR1, RECQL4, FOS, BCL2, CXCL8, TRIM25, EGR1, CDH1, KRAS, PTGS2, and IL6 were associated with survival outcomes. PCA demonstrated clear separation between healthy and BC samples. Drug repositioning identified eight candidates, with niclosamide as the top hit. In vitro assays showed marked reduction in cell viability at 5 µM niclosamide and 25 µM amitriptyline after 24 h treatment. No significant additive effect was observed in the combination treatment. Conclusion:This integrative approach revealed candidate BC-specific biomarkers and identified niclosamide as a potential repositioned therapeutic. These findings remain exploratory and do not provide definitive clinical evidence. Further validation across additional models and clinical settings is required.
Background:There is growing evidence that long non-coding RNAs (lncRNAs) play crucial roles in cancer progression and therapy. Our previous study showed that the lncRNA plasmacytoma variant translocation 1 (PVT1) regulates tumor growth and metastasis in breast cancer (BC). As a conventional chemotherapeutic drug, doxorubicin (DOX) resistance continues to be a major challenge in BC treatment. This study aimed to explore the role and underlying mechanism of PVT1 in doxorubicin-resistant BC. Methods:Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting (WB) were carried out to detect gene and protein expression levels. The extent of ferroptosis was measured based on the cellular glutathione (GSH) levels and total or lipid reactive oxygen species (ROS) levels. An in-situ tumor implantation model in nude mice was employed to validate the mechanism in vivo. Transcriptome analysis was conducted to identify downstream target genes. Results:This study found that PVT1 was highly expressed in the plasma of drug-resistant patients and drug-resistant cell lines. Silencing PVT1 reduced cellular glutathione level, increased reactive oxygen species (ROS) and lipid peroxidation (LPO), while ferroptosis inhibition in rescue experiments partially reversed the oxidative stress. In-vivo study confirmed that silencing PVT1 increased the sensitivity of BC cells to doxorubicin treatment. Transcriptomic sequencing revealed that solute carrier family 3 member 2 (SLC3A2) was the most potential target gene of PVT1, which was confirmed in PVT1-silenced cell models. Conclusion:Mechanistically, PVT1 increased SLC3A2 expression, thus inhibiting ferroptosis and promoting doxorubicin resistance in BC, indicating that PVT1 could be a promising therapeutic target for doxorubicin-resistant BC patients.
Background:Despite significant progress in treating estrogen receptor (ER)-positive breast cancer (BC), the recurrence risk remains high and mechanisms driving initial ductal tumorigenesis is unclear. Given an emerging role of LINE-1 (L1), HERV-K and other endogenous retroviral elements (EREs) in cancer, we tested the hypothesis that their expression can be induced by estrogen and blocked by treatment with lamivudine (3TC), an HIV-1 drug that can also inhibit L1 and HERV-K encoded reverse transcriptases (RTs) and ERE propagation. Methods:This is a preclinical study using the well-established ACI rat model of spontaneous estrogen-driven BC to examine the earliest stages of cancer development and the effects of 3TC. Rat mammary glands and peripheral blood mononuclear cells (PBMCs) were analyzed by immunohistochemistry (IHC) and RNA sequencing (RNAseq). A panel of human BC cell lines and tissue microarrays (TMAs) were assessed by RT-qPCR, immunoblotting and IHC to evaluate ERE RNA and protein expression and a potential association with the ER- and FOXA1- positive BC. Results:Development of estrogen-induced ER+ and FOXA1+ pre-invasive ductal tumors in rat mammary glands was accompanied by systemic inflammation and upregulation of ERE RNAs in mammary glands and PBMCs; these effects were attenuated by oral administration of 3TC. L1 and HERV RNAs and proteins were also detected in human BC cell lines and in tumor tissues with high ER and FOXA1 protein levels, suggesting that their expression is an intrinsic part of the ER- and FOXA1- driven oncogenic programs. Conclusion:Using a rat model, our study demonstrates estrogen dependent ERE expression in pre-invasive ER+FOXA1+ mammary tumor cells and in circulating immune cells, activation of innate immune responses, and the inhibitory effects of 3TC. ERE RNAs and proteins are also highly expressed in human ER+FOXA1+ breast cancers, warranting further investigation into their functions and a potential use of 3TC as a preventive strategy for reducing a risk of cancer progression, especially in woman with ER+FOXA1+ tumors.
Background:Triple-negative breast cancer (TNBC) is an aggressive subtype with poor prognosis, closely associated with an imbalanced tumor immune microenvironment. Tumor-associated macrophages (TAMs) play a crucial role in tumor progression. Purpose:This study aimed to investigate whether glycine combined with β-elemene inhibits TNBC progression by suppressing M2 macrophage polarization through the IL-6/JAK2/STAT3 pathway. Methods:UPLC-Q-Exactive HRMS was used to identify glycine and β-elemene. In vitro, 4T1 cell viability was determined by CCK-8 assay. RAW264.7 cells were polarized to M2 macrophages and co-cultured with 4T1 cells. Colony formation, wound healing, and Transwell assays were performed. Western blot and immunohistochemistry were used to detect protein expression. In vitro experiments were performed with at least three independent biological replicates. In vivo, 4T1 xenograft mouse models were established (n=10 per group) to evaluate anti-tumor efficacy. Results:Glycine combined with β-elemene significantly suppressed proliferation, colony formation, and migration of 4T1 cells. Mechanistically, the combination inhibited M2 macrophage polarization by downregulating IL-6, p-JAK2, and p-STAT3. In vivo, the combination with paclitaxel showed the strongest anti-tumor effect, with reduced tumor volume and weight, decreased Ki-67 expression, and suppressed M2 polarization. Conclusion:Glycine combined with β-elemene inhibits M2 macrophage polarization by suppressing the IL-6/JAK2/STAT3 pathway, thereby exerting anti-TNBC effects. Its combination with paclitaxel demonstrates synergistic anti-tumor efficacy.
Shang Wang,1 Chen Gao,2 Qi Wang,2 Jing Xu21Department of Pathology, School of Basic Medicine, Qingdao University, Qingdao, People’s Republic of China; 2Department of Pathology, Qingdao Central Hospital, University of Health and Rehabilitation Sciences (Qingdao Central Medical Group), Qingdao, People’s Republic of ChinaCorrespondence: Jing Xu, Department of Pathology, Qingdao Central Hospital, University of Health and Rehabilitation Sciences (Qingdao Central Medical Group), Num. 127, Siliunan Road, Qingdao, Shandong, 266042, People’s Republic of China, Tel +86-0532-84851283, Email xujing@uhrs.edu.cnIntroduction: The SWI/SNF (SWItch/Sucrose Non - Fermentable) complex is a multi - subunit, ATPase - dependent chromatin - remodeling complex involved in regulating key cellular processes. Tumors with SWI/SNF loss tend to be poorly differentiated and aggressive. Triple - negative breast cancer (TNBC) typically has a high histological grade and a poor prognosis. Given the limited reports on the SWI/SNF complex in breast cancer, we focused on its role in TNBC.Methods: Using tissue microarray and immunohistochemistry (IHC), we evaluated the expression of four important subunits of the SWI/SNF complex (SMARCB1, SMARCA2, ARID1A, and SMARCA4) in 104 TNBC tissues, which included 96 cases of conventional TNBC and 8 cases of low - grade TNBC. Additionally, we evaluated the endogenous expression of the four subunits in five breast cancer cell lines by real - time quantitative PCR (RT - qPCR). These cell lines consisted of two TNBC cell lines (MDA - MB - 231, MDA - MB - 468) and three non - TNBC cell lines (MCF - 7, T47D, and MDA - MB - 453).Results: The IHC results indicated that the deletion rate of SMARCA2 was the highest in TNBC compared with other subunits (91/104, 87.5%) (p < 0.0001), and SMARCA4 had the highest retention rate (98/104, 94.2%). Whether low - grade TNBC was excluded or not, there was no significant difference between the deletion rate and various clinicopathological parameters. Consistently, we found that SMARCA2 exhibited the lowest expression level across all five cell lines (p < 0.01). SMARCA4 showed the highest expression in all cell lines except MDA - MB - 453, in which ARID1A expression was the highest.Conclusion: These results indicate that TNBC is characterized by a high proportion of SMARCA2 deletion and positive expression of SMARCA4, which are significant molecular features. The roles and potential mechanisms of these two factors in TNBC require further investigation.Keywords: triple-negative breast cancer, SWI-SNF complex, SMARCA2, SMARCA4, chromatin remodelling, immunohistochemistry
Background:Breast cancer is the most prevalent malignancy among womificant advances in systemic therapies, metastatic breast cancer remains largely incurable, highlighting the need for reliable prognostic biomarkers. Mean platelet volume (MPV), a routinely measured hematological parameter reflecting platelet size, has been linked to platelet activation, systemic inflammation, and tumor progression. However, the prognostic significance of MPV in recurrent or de novo metastatic breast cancer is unclear. This study evaluated the association between pretreatment MPV and overall survival in this patient population. Methods:A retrospective analysis was conducted on 200 women with recurrent or de novo metastatic breast cancer. Clinical, pathological, and hematological data were collected from medical records. Pretreatment MPV was measured prior to initiation of systemic therapy. MPV was assessed using both the institutional laboratory upper reference limit of 10.5 fL and an exploratory receiver operating characteristic-derived cutoff of 9.55 fL. Overall survival was defined as the interval from diagnosis of recurrent or de novo metastatic disease to death from any cause or last follow-up. Survival outcomes were compared according to MPV status. Results:Pretreatment MPV was not significantly associated with overall survival in patients with recurrent or de novo metastatic breast cancer. Using the institutional cutoff of 10.5 fL, median overall survival was 48 months for patients with MPV <10.5 fL (95% CI: 38.161-57.839) and 108 months for those with MPV ≥10.5 fL (95% CI: 26.214-189.800), with no statistically significant difference between groups (p = 0.693). No significant differences were observed between MPV groups regarding age, menopausal status, tumor biomarkers, metastatic characteristics, or recurrence timing. In multivariable analysis, central nervous system metastasis was independently associated with increased mortality (HR 2.22, 95% CI: 1.224-4.027; p = 0.009), whereas MPV status was not independently associated with overall survival (HR 0.81, 95% CI: 0.379-1.750; p = 0.601). Conclusion:Pretreatment MPV was not identified as an independent prognostic factor for overall survival in patients with recurrent or de novo metastatic breast cancer. Although MPV is an easily accessible hematological parameter, these findings indicate that MPV alone is unlikely to serve as a reliable prognostic biomarker in this clinical context. Further studies with larger cohorts, standardized MPV measurement methods, and adjustment for potential confounding factors are warranted.
Background:Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited targeted treatment options. Radiotherapy remains an important therapeutic approach for TNBC, but radioresistance markedly limits its efficacy. Absent in melanoma 2 (AIM2) has been increasingly implicated in tumor biology and innate immune signaling; however, its role in TNBC radioresistance and its regulation by the lactate-rich tumor microenvironment remain unclear. Methods:Radiation-resistant TNBC cell models were established from BT-549 and MDA-MB-231 cells by repeated fractional irradiation. AIM2 knockdown and IRF3 overexpression were achieved by lentiviral transduction. Cell proliferation, colony formation, apoptosis, protein expression, AIM2 lactylation, subcellular localization, and AIM2-IRF3 interaction were evaluated using CCK-8 assay, colony formation assay, flow cytometry, RT-qPCR, Western blotting, co-immunoprecipitation, and immunofluorescence. Bioinformatics analyses were performed to assess the potential prognostic relevance of AIM2. In vitro experiments were performed with at least three independent biological replicates. Results:Radiation treatment increased AIM2 expression in TNBC cells. AIM2 knockdown reduced colony formation and promoted apoptosis in radioresistant TNBC cells. High-lactate conditions decreased AIM2 expression, increased AIM2 lactylation, and promoted AIM2 nuclear translocation. IRF3 overexpression partially reversed the effects of AIM2 knockdown on colony formation and apoptosis, whereas lactate treatment weakened the interaction between AIM2 and IRF3. Bioinformatics analyses indicated that elevated AIM2 expression was associated with poorer prognosis. Conclusion:These findings suggest that AIM2 may be involved in the regulation of TNBC radioresistance, potentially through its interaction with IRF3. High-lactate conditions may affect this regulatory axis by enhancing AIM2 lactylation. This study provides preliminary evidence for a potential mechanism linking lactate-mediated post-translational modification with radiosensitivity regulation in TNBC; however, further mechanistic, in vivo, and clinical validation is required.