Discovery of a novel hybrid coumarin-hydroxamate conjugate targeting the HDAC1-Sp1-FOSL2 signaling axis for breast cancer therapy.

BACKGROUND: Breast cancer is one of the most lethal cancers in women. Despite significant advances in the diagnosis and treatment of breast cancer, many patients still succumb to this disease, and thus, novel effective treatments are urgently needed. Natural product coumarin has been broadly investigated since it reveals various biological properties in the medicinal field. Accumulating evidence indicates that histone deacetylase inhibitors (HDACIs) are promising novel anti-breast cancer agents. However, most current HDACIs exhibit only moderate effects against solid tumors and are associated with severe side effects. Thus, to develop more effective HDACIs for breast cancer therapy, hydroxamate of HDACIs was linked to coumarin core, and coumarin-hydroxamate hybrids were designed and synthesized. METHODS: A substituted coumarin moiety was incorporated into the classic hydroxamate HDACIs by the pharmacophore fusion strategy. ZN444B was identified by using the HDACI screening kit and cell viability assay. Molecular docking was performed to explore the binding mode of ZN444B with HDAC1. Western blot, immunofluorescent staining, cell viability, colony formation and cell migration and flow cytometry assays were used to analyze the anti-breast cancer effects of ZN444B in vitro. Orthotopic studies in mouse models were applied for preclinical evaluation of efficacy and toxicity in vivo. Proteomic analysis, dual-luciferase reporter assay, chromatin immunoprecipitation, co-immunoprecipitation, immunofluorescent staining assays along with immunohistochemical (IHC) analysis were used to elucidate the molecular basis of the actions of ZN444B. RESULTS: We synthesized and identified a novel coumarin-hydroxamate conjugate, ZN444B which possesses promising anti-breast cancer activity both in vitro and in vivo. A molecular docking model showed that ZN444B binds to HDAC1 with high affinity. Further mechanistic studies revealed that ZN444B specifically decreases FOS-like antigen 2 (FOSL2) mRNA levels by inhibiting the deacetylase activity of HDAC1 on Sp1 at K703 and abrogates the binding ability of Sp1 to the FOSL2 promoter. Furthermore, FOSL2 expression positively correlates with breast cancer progression and metastasis. Silencing FOSL2 expression decreases the sensitivity of breast cancer cells to ZN444B treatment. In addition, ZN444B shows no systemic toxicity in mice. CONCLUSIONS: Our findings highlight the potential of FOSL2 as a new biomarker and therapeutic target for breast cancer and that targeting the HDAC1-Sp1-FOSL2 signaling axis with ZN444B may be a promising therapeutic strategy for breast cancer.

Prevalence of BRCA mutation in breast and ovarian cancer among women in India: A systematic review and meta-analysis protocol.

PURPOSE: We present a methodically devised protocol for conducting a systematic review and meta-analysis aimed at ascertaining the prevalence of BReast CAncer gene (BRCA) mutations in breast and ovarian cancer (BOC) among women in India. The review will include cross-sectional, cohort, case-series, and registry-based studies focusing on females clinically diagnosed with any stage of BOC, tested for BRCA germline mutation and undergone any form of treatment. METHODS: A Cochrane literature search will be carried out to identify all the published and unpublished articles available in English from 2010 till date across various electronic databases including PubMed, Psych Info, SCI, Cochrane Central, Embase, Scopus, IND Med and Google Scholar. A step-by-step process will be followed to select all the relevant studies for final inclusion using Rayyan software. The selection process of the review will be reported based on Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA) checklist. The protocol has been registered in PROSPERO (ID: CRD42023463452). Joanna Briggs Institute Critical Appraisal Checklist will be used to evaluate the methodological quality of the included studies. The outcome measure will be the prevalence of BRCA1/2 gene mutation in this population. Meta-analysis will be performed to report the pooled prevalence along with 95% confidence interval. DISCUSSION: The results of this review study will provide valuable insights for clinicians, and policy makers, enabling them to formulate guidelines that underscore the importance of screening for BRCA mutations in cases of BOC.

Gene expression profile of immune-check point in response to Trastuzumab therapy in patients with HER-2 positive breast cancer.

OBJECTIVE: Aim: To clarify the association between response to Trastuzumab and molecular expression of TIM-3 and FOXP-3 immune checkpoints. PATIENTS AND METHODS: Materials and Methods: FOXP-3 and TIM-3 expression in peripheral blood was analyzed using qPCR, and the serum level of Trastuzumab was estimated using an immune sorbent enzyme assay. RESULTS: Results: During treatment with Trastuzumab, the FOXP-3 gene expression showed a significant decline throughout one year of treatment, going from 0.85 at cycle 9 to 0.75 at cycle 17. While the TIM-3 gene expression showed a significant up regulation at cycle 9 to 2.8 fold, followed by a reduction in the fold change from 2.8 to 1.7 in the font of reference gene expression. CONCLUSION: Conclusions:FOXP-3 and TIM-3 have the potential to be suggestive markers that can anticipate the response to Trastuzumab, but they are not capable of predicting the likelihood of recurrence.

AKT-dependent nuclear localization of EPRS1 activates PARP1 in breast cancer cells.

Glutamyl-prolyl-tRNA synthetase (EPRS1) is a bifunctional aminoacyl-tRNA-synthetase (aaRS) essential for decoding the genetic code. EPRS1 resides, with seven other aaRSs and three noncatalytic proteins, in the cytoplasmic multi-tRNA synthetase complex (MSC). Multiple MSC-resident aaRSs, including EPRS1, exhibit stimulus-dependent release from the MSC to perform noncanonical activities distinct from their primary function in protein synthesis. Here, we show EPRS1 is present in both cytoplasm and nucleus of breast cancer cells with constitutively low phosphatase and tensin homolog (PTEN) expression. EPRS1 is primarily cytosolic in PTEN-expressing cells, but chemical or genetic inhibition of PTEN, or chemical or stress-mediated activation of its target, AKT, induces EPRS1 nuclear localization. Likewise, preferential nuclear localization of EPRS1 was observed in invasive ductal carcinoma that were also P-Ser473-AKT+. EPRS1 nuclear transport requires a nuclear localization signal (NLS) within the linker region that joins the catalytic glutamyl-tRNA synthetase and prolyl-tRNA synthetase domains. Nuclear EPRS1 interacts with poly(ADP-ribose) polymerase 1 (PARP1), a DNA-damage sensor that directs poly(ADP-ribosyl)ation (PARylation) of proteins. EPRS1 is a critical regulator of PARP1 activity as shown by markedly reduced ADP-ribosylation in EPRS1 knockdown cells. Moreover, EPRS1 and PARP1 knockdown comparably alter the expression of multiple tumor-related genes, inhibit DNA-damage repair, reduce tumor cell survival, and diminish tumor sphere formation by breast cancer cells. EPRS1-mediated regulation of PARP1 activity provides a mechanistic link between PTEN loss in breast cancer cells, PARP1 activation, and cell survival and tumor growth. Targeting the noncanonical activity of EPRS1, without inhibiting canonical tRNA ligase activity, provides a therapeutic approach potentially supplementing existing PARP1 inhibitors.

[Examination of breast density in breast cancer discordant twin pairs]. / Emlodenzitás vizsgálata emlorákdiszkordáns ikerpárok esetében.

Previous twin studies show that genetic factors are responsible for 63% of the variability in breast density. We analyzed the mammographic images of 9 discordant twin pairs for breast cancer from the population-based Hungarian Twin Registry. We measured breast density using 3D Slicer software. Genetic variants predisposing to breast cancer were also examined. One of the examined twin pairs had a BRCA2 mutation in both members. There was no significant difference between the mean values of breast density in the tumor and non-tumor groups (p=0.323). In terms of parity and the presence of menopause, we found mostly no significant difference between the members of the twin pair. In our cohort of identical twins discordant for breast cancer, the average breast density showed no significant difference, which can be explained by the common genetic basis of breast cancer and breast density.

Differences in 21-Gene and PAM50 Recurrence Scores in Younger and Black Women With Breast Cancer.

PURPOSE: Genomic tests, such as the Oncotype Dx 21-gene and Prosigna risk of recurrence (ROR-P) assay, are commonly used for breast cancer prognostication. Emerging data suggest variability between assays, but this has not been compared in diverse populations. MATERIALS AND METHODS: RNA sequencing was performed on 647 previously untreated stage I-III estrogen receptor-positive/human epidermal growth factor receptor 2-negative tumors in the Carolina Breast Cancer Study, which oversampled Black and younger women (age <50 years at diagnosis), using research versions of two common RNA-based prognostic assays: ROR-PR and the 21-gene recurrence score (RSR). Relative frequency differences and 95% CIs were estimated for associations with race and age, and hazards of 5-year local or distant recurrence were modeled with Cox regression. Proliferation and estrogen module scores from each assay, representing broad activity of genes in those pathways, were examined to guide interpretation of differences between tests. RESULTS: Among both younger and older individuals, Black women had higher frequency of intermediate and high ROR-PR scores than non-Black women. Race was not significantly associated with RSR in either age group. High (hazard ratio [HR], 4.67 [95% CI, 1.73 to 12.70]) and intermediate (HR, 2.12 [95% CI, 0.98 to 4.62]) ROR-PR scores were associated with greater risk of recurrence, but RSR did not predict recurrence. RSR emphasized estrogen over proliferation modules, whereas ROR-PR emphasized proliferation. Higher proliferation scores were associated with younger age and Black race in both assays. Modifications to the RSR algorithm that increased emphasis on proliferation improved prognostication in this diverse population. CONCLUSION: ROR-PR and the 21-gene RSR differentially emphasize estrogen-related and proliferative biology. The emphasis of 21-gene RS on estrogen-related biology and lower endocrine therapy initiation among Black women may contribute to poorer prognostic ability in heterogeneously treated populations.

Screening Nonlinear miRNA Features of Breast Cancer by Using Ensemble Regularized Polynomial Logistic Regression.

Differentiating breast cancer subtypes based on miRNA data helps doctors provide more personalized treatment plans for patients. This paper explored the interaction between miRNA pairs and developed a novel ensemble regularized polynomial logistic regression method for screening nonlinear features of breast cancer. Three different types of second-order polynomial logistic regression with elastic network penalty (SOPLR-EN) in which each type contains 10 identical models were integrated to determine the most suitable sample set for feature screening by using bootstrap sampling strategy. A single feature and 39 nonlinear features were obtained by screening features that appeared at least 15 times in 30 integrations and were involved in the classification of at least 4 subtypes. The second-order polynomial logistic regression with ridge penalty (SOPLR-R) built on screened feature set achieved 82.30% classification accuracy for distinguishing breast cancer subtypes, surpassing the performance of other six methods. Further, 11 nonlinear miRNA biomarkers were identified, and their significant relevance to breast cancer was illustrated through six types of biological analysis.

Construction of a Spatial-Confined Self-Stacking Catalytic Circuit for Rapid and Sensitive Imaging of Piwi-Interacting RNA in Living Cells.

Piwi-interacting RNAs (piRNAs) are small noncoding RNAs that repress transposable elements to maintain genome integrity. The canonical catalytic hairpin assembly (CHA) circuit relies on random collisions of free-diffused reactant probes, which substantially slow down reaction efficiency and kinetics. Herein, we demonstrate the construction of a spatial-confined self-stacking catalytic circuit for rapid and sensitive imaging of piRNA in living cells based on intramolecular and intermolecular hybridization-accelerated CHA. We rationally design a 3WJ probe that not only accelerates the reaction kinetics by increasing the local concentration of reactant probes but also eliminates background signal leakage caused by cross-entanglement of preassembled probes. This strategy achieves high sensitivity and good specificity with shortened assay time. It can quantify intracellular piRNA expression at a single-cell level, discriminate piRNA expression in tissues of breast cancer patients and healthy persons, and in situ image piRNA in living cells, offering a new approach for early diagnosis and postoperative monitoring.

The CRL3KCTD10 ubiquitin ligase-USP18 axis coordinately regulates cystine uptake and ferroptosis by modulating SLC7A11.

SLC7A11 is a cystine transporter and ferroptosis inhibitor. How the stability of SLC7A11 is coordinately regulated in response to environmental cystine by which E3 ligase and deubiquitylase (DUB) remains elusive. Here, we report that neddylation inhibitor MLN4924 increases cystine uptake by causing SLC7A11 accumulation, via inactivating Cullin-RING ligase-3 (CRL-3). We identified KCTD10 as the substrate-recognizing subunit of CRL-3 for SLC7A11 ubiquitylation, and USP18 as SLC7A11 deubiquitylase. Upon cystine deprivation, the protein levels of KCTD10 or USP18 are decreased or increased, respectively, contributing to SLC7A11 accumulation. By destabilizing or stabilizing SLC7A11, KCTD10, or USP18 inversely regulates the cystine uptake and ferroptosis. Biologically, MLN4924 combination with SLC7A11 inhibitor Imidazole Ketone Erastin (IKE) enhanced suppression of tumor growth. In human breast tumor tissues, SLC7A11 levels were negatively or positively correlated with KCTD10 or USP18, respectively. Collectively, our study defines how SLC7A11 and ferroptosis is coordinately regulated by the CRL3KCTD10/E3-USP18/DUB axis, and provides a sound rationale of drug combination to enhance anticancer efficacy.

Clinical Response to Olaparib in a Patient With Leptomeningeal Carcinomatosis in Newly Diagnosed Breast Cancer With Germline BRCA2 Mutation.

Case of LMC in a BRCA2-mutated breast cancer patient shows clinical improvement with Olaparib therapy.

ctGAN: combined transformation of gene expression and survival data with generative adversarial network.

Recent studies have extensively used deep learning algorithms to analyze gene expression to predict disease diagnosis, treatment effectiveness, and survival outcomes. Survival analysis studies on diseases with high mortality rates, such as cancer, are indispensable. However, deep learning models are plagued by overfitting owing to the limited sample size relative to the large number of genes. Consequently, the latest style-transfer deep generative models have been implemented to generate gene expression data. However, these models are limited in their applicability for clinical purposes because they generate only transcriptomic data. Therefore, this study proposes ctGAN, which enables the combined transformation of gene expression and survival data using a generative adversarial network (GAN). ctGAN improves survival analysis by augmenting data through style transformations between breast cancer and 11 other cancer types. We evaluated the concordance index (C-index) enhancements compared with previous models to demonstrate its superiority. Performance improvements were observed in nine of the 11 cancer types. Moreover, ctGAN outperformed previous models in seven out of the 11 cancer types, with colon adenocarcinoma (COAD) exhibiting the most significant improvement (median C-index increase of ~15.70%). Furthermore, integrating the generated COAD enhanced the log-rank p-value (0.041) compared with using only the real COAD (p-value = 0.797). Based on the data distribution, we demonstrated that the model generated highly plausible data. In clustering evaluation, ctGAN exhibited the highest performance in most cases (89.62%). These findings suggest that ctGAN can be meaningfully utilized to predict disease progression and select personalized treatments in the medical field.

A High Immune-Related Index with the Suppression of cGAS-STING Pathway is a Key Determinant to Herceptin Resistance in HER2+ Breast Cancer.

Resistance to HER2-targeted therapy is the major cause of treatment failure in patients with HER2+ breast cancer (BC). Given the key role of immune microenvironment in tumor development, there is a lack of an ideal prognostic model that fully accounts for immune infiltration. In this study, WGCNA analysis was performed to discover the relationship between immune-related signaling and prognosis of HER2+ BC. After Herceptin-resistant BC cell lines established, transcriptional profiles of resistant cell line and RNA-sequencing data from GSE76360 cohort were analyzed for candidate genes. 85 samples of HER2+ BC from TCGA database were analyzed by the Cox regression, XGBoost and Lasso algorithm to generalize a credible immune-related prognostic index (IRPI). Correlations between the IRPI signature and tumor microenvironment were further analyzed by multiple algorithms, including single-cell RNA sequencing data analysis. Patients with high IRPI had suppressive tumor immune microenvironment and worse prognosis. The suppression of type I interferon signaling indicated by the IRPI in Herceptin-resistant HER2+ BC was validated. And we elucidated that the suppression of cGAS-STING pathway is the key determinant underlying immune escape in Herceptin-resistant BC with high IRPI. A combination of STING agonist and DS-8201 could serve as a new strategy for Herceptin-resistant HER2+ BC.

Targeted delivery of anti-miRNA21 sensitizes PD-L1high tumor to immunotherapy by promoting immunogenic cell death.

Rationale: Growing evidence has demonstrated that miRNA-21 (miR-21) upregulation is closely associated with tumor pathogenesis. However, the mechanisms by which miR-21 inhibition modulates the immunosuppressive tumor microenvironment (TME) and improves tumor sensitivity to immune checkpoint blockade therapies remain largely unexplored. In this study, we demonstrate the precise delivery of anti-miR-21 using a PD-L1-targeting peptide conjugate (P21) to the PD-L1high TME. Methods: Investigating miR-21 inhibition mechanisms involved conducting quantitative real-time PCR, western blot, flow cytometry, and confocal microscopy analyses. The antitumor efficacy and immune profile of P21 monotherapy, or combined with anti-PD-L1 immune checkpoint inhibitors, were assessed in mouse models bearing CT26.CL25 tumors and 4T1 breast cancer. Results Inhibition of oncogenic miR-21 in cancer cells by P21 efficiently activates tumor suppressor genes, inducing autophagy and endoplasmic reticulum stress. Subsequent cell-death-associated immune activation (immunogenic cell death) is initiated via the release of damage-associated molecular patterns. The in vivo results also illustrated that the immunogenic cell death triggered by P21 could effectively sensitize the immunosuppressive TME. That is, P21 enhances CD8+ T cell infiltration in tumor tissues by conferring immunogenicity to dying cancer cells and promoting dendritic cell maturation. Meanwhile, combining P21 with an anti-PD-L1 immune checkpoint inhibitor elicits a highly potent antitumor effect in a CT26.CL25 tumor-bearing mouse model and 4T1 metastatic tumor model. Conclusions: Collectively, we have clarified a miR-21-related immunogenic cell death mechanism through the precise delivery of anti-miR-21 to the PD-L1high TME. These findings highlight the potential of miR-21 as a target for immunotherapeutic interventions.

A Novel Class I HDAC Inhibitor, AW01178, Inhibits Epithelial-Mesenchymal Transition and Metastasis of Breast Cancer.

Epithelial-mesenchymal transition (EMT) refers to the transformation of polar epithelial cells into motile mesenchymal cells under specific physiological or pathological conditions, thus promoting the metastasis of cancer cells. Epithelial cadherin (E-cadherin) is a protein that plays an important role in the acquisition of tumor cell motility and serves as a key EMT epithelial marker. In the present study, AW01178, a small-molecule compound with potential therapeutic efficacy, was identified via in-cell Western high-throughput screening technology using E-cadherin as the target. The compound induced the upregulation of E-cadherin at both mRNA and protein levels and inhibited the EMT of breast cancer cells in vitro as well as metastasis in vivo. Mechanistically, AW01178 is a novel benzacetamide histone deacetylase inhibitor (HDACi) mainly targeting class I histone deacetylases. AW01178 promoted the transcription and expression of E-cadherin through enhancing the acetylation level of histone H3 in the E-cadherin promoter region, thereby inhibiting the metastasis of breast cancer cells. The collective findings support the potential utility of the novel HDACi compound identified in this study, AW01178, as a therapeutic drug for breast cancer and highlight its value for the future development of HDACi structures as anticancer drugs.

Identifying Key Genes Involved in Axillary Lymph Node Metastasis in Breast Cancer Using Advanced RNA-Seq Analysis: A Methodological Approach with GLMQL and MAS.

Our study aims to address the methodological challenges frequently encountered in RNA-Seq data analysis within cancer studies. Specifically, it enhances the identification of key genes involved in axillary lymph node metastasis (ALNM) in breast cancer. We employ Generalized Linear Models with Quasi-Likelihood (GLMQLs) to manage the inherently discrete and overdispersed nature of RNA-Seq data, marking a significant improvement over conventional methods such as the t-test, which assumes a normal distribution and equal variances across samples. We utilize the Trimmed Mean of M-values (TMMs) method for normalization to address library-specific compositional differences effectively. Our study focuses on a distinct cohort of 104 untreated patients from the TCGA Breast Invasive Carcinoma (BRCA) dataset to maintain an untainted genetic profile, thereby providing more accurate insights into the genetic underpinnings of lymph node metastasis. This strategic selection paves the way for developing early intervention strategies and targeted therapies. Our analysis is exclusively dedicated to protein-coding genes, enriched by the Magnitude Altitude Scoring (MAS) system, which rigorously identifies key genes that could serve as predictors in developing an ALNM predictive model. Our novel approach has pinpointed several genes significantly linked to ALNM in breast cancer, offering vital insights into the molecular dynamics of cancer development and metastasis. These genes, including ERBB2, CCNA1, FOXC2, LEFTY2, VTN, ACKR3, and PTGS2, are involved in key processes like apoptosis, epithelial-mesenchymal transition, angiogenesis, response to hypoxia, and KRAS signaling pathways, which are crucial for tumor virulence and the spread of metastases. Moreover, the approach has also emphasized the importance of the small proline-rich protein family (SPRR), including SPRR2B, SPRR2E, and SPRR2D, recognized for their significant involvement in cancer-related pathways and their potential as therapeutic targets. Important transcripts such as H3C10, H1-2, PADI4, and others have been highlighted as critical in modulating the chromatin structure and gene expression, fundamental for the progression and spread of cancer.

ADAR-Mediated A>I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer.

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.

HER4 Affects Sensitivity to Tamoxifen and Abemaciclib in Luminal Breast Cancer Cells and Restricts Tumor Growth in MCF-7-Based Humanized Tumor Mice.

The impact of the HER4 receptor on the growth and treatment of estrogen receptor-positive breast cancer is widely uncertain. Using CRISPR/Cas9 technology, we generated stable HER4 knockout variants derived from the HER4-positive MCF-7, T-47D, and ZR-75-1 breast cancer cell lines. We investigated tumor cell proliferation as well as the cellular and molecular mechanisms of tamoxifen, abemaciclib, AMG232, and NRG1 treatments as a function of HER4 in vitro. HER4 differentially affects the cellular response to tamoxifen and abemaciclib treatment. Most conspicuous is the increased sensitivity of MCF-7 in vitro upon HER4 knockout and the inhibition of cell proliferation by NRG1. Additionally, we assessed tumor growth and immunological effects as responses to tamoxifen and abemaciclib therapy in humanized tumor mice (HTM) based on MCF-7 HER4-wildtype and the corresponding HER4-knockout cells. Without any treatment, the enhanced MCF-7 tumor growth in HTM upon HER4 knockout suggests a tumor-suppressive effect of HER4 under preclinical but human-like conditions. This phenomenon is associated with an increased HER2 expression in MCF-7 in vivo. Independent of HER4, abemaciclib and tamoxifen treatment considerably inhibited tumor growth in these mice. However, abemaciclib-treated hormone receptor-positive breast cancer patients with tumor-associated mdm2 gene copy gains or pronounced HER4 expression showed a reduced event-free survival. Evidently, the presence of HER4 affects the efficacy of tamoxifen and abemaciclib treatment in different estrogen receptor-positive breast cancer cells, even to different extents, and is associated with unfavorable outcomes in abemaciclib-treated patients.

Metformin Prevents Tumor Cell Growth and Invasion of Human Hormone Receptor-Positive Breast Cancer (HR+ BC) Cells via FOXA1 Inhibition.

Women with type 2 diabetes (T2D) have a higher risk of being diagnosed with breast cancer and have worse survival than non-diabetic women if they do develop breast cancer. However, more research is needed to elucidate the biological underpinnings of these relationships. Here, we found that forkhead box A1 (FOXA1), a forkhead family transcription factor, and metformin (1,1-dimethylbiguanide hydrochloride), a medication used to treat T2D, may impact hormone-receptor-positive (HR+) breast cancer (BC) tumor cell growth and metastasis. Indeed, fourteen diabetes-associated genes are highly expressed in only three HR+ breast cancer cell lines but not the other subtypes utilizing a 53,805 gene database obtained from NCBI GEO. Among the diabetes-related genes, FOXA1, MTA3, PAK4, FGFR3, and KIF22 were highly expressed in HR+ breast cancer from 4032 breast cancer patient tissue samples using the Breast Cancer Gene Expression Omnibus. Notably, elevated FOXA1 expression correlated with poorer overall survival in patients with estrogen-receptor-positive/progesterone-receptor-positive (ER+/PR+) breast cancer. Furthermore, experiments demonstrated that loss of the FOXA1 gene inhibited tumor proliferation and invasion in vitro using MCF-7 and T47D HR+ breast cancer cell lines. Metformin, an anti-diabetic medication, significantly suppressed tumor cell growth in MCF-7 cells. Additionally, either metformin treatment or FOXA1 gene deletion enhanced tamoxifen-induced tumor growth inhibition in HR+ breast cancer cell lines within an ex vivo three-dimensional (3D) organoid model. Therefore, the diabetes-related medicine metformin and FOXA1 gene inhibition might be a new treatment for patients with HR+ breast cancer when combined with tamoxifen, an endocrine therapy.

[Gene-age interaction study of breast cancer prognosis based on epigenomic data].

Objective: Exploring gene-age interactions associated with breast cancer prognosis based on epigenomic data. Methods: Differential expression analysis of DNA methylation was conducted using multiple independent epigenomic datasets of breast cancer from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The false discovery rate (FDR) method was used for multiple corrections, retaining differentially methylated sites with q-FDR≤0.05. A three-stage analytic strategy was implemented, using a multivariable Cox proportional hazards regression model to examine gene-age interactions. In the discovery phase, signals with q-FDR ≤ 0.05 were screened out using TCGA-BRCA database. In validation phaseⅠ, the interaction was validated using GSE72245 data, with criteria of P≤0.05 and consistent effect direction. In validation phaseⅡ, the signals were further validated using GSE37754 and GSE75067 data. A prognostic prediction model was constructed by incorporating clinical indicators and interaction signals. Results: The three-stage analytic strategy identified a methylation site (cg16126280EBF1), which interacted with age to jointly affect the overall survival time of patients (interaction HR= 1.001 1,95%CI:1.000 7-1.001 5,P<0.001). Stratified analysis by age showed that the effect of hypermethylation of cg16126280EBF1 was completely opposite in younger patients (HR=0.550 5, 95%CI: 0.383 8-0.789 6, P=0.001) and older patients (HR=2.166 5, 95%CI: 1.285 2-3.652 2, P=0.004). Conclusions: The DNA methylation site cg16126280EBF1 exhibits an interaction with age, jointly influencing the prognosis of breast cancer in a complex association pattern. This finding contributes new population-based evidence for the development of age-specific targeted drugs.

[Overexpression of CDHR2 inhibits proliferation of breast cancer cells by inhibiting the PI3K/Akt pathway].

OBJECTIVE: To investigate the mechanism by which CDHR2 overexpression inhibits breast cancer cell growth and cell cycle pragression via the PI3K/Akt signaling pathway. METHODS: Bioinformatic analysis was performed to investigate CDHR2 expression in breast cancer and its correlation with survival outcomes of the patients. Immunohistochemistry was used to examine CDHR2 expressions in surgical specimens of tumor and adjacent tissues from 10 patients with breast cancer. CDHR2 expression levels were also detected in 5 breast cancer cell lines and a normal human mammary epithelial cell line using qRT-PCR and Western blotting. Breast cancer cell lines MDA-MB-231 and MCF7 with low CDHR2 expression were transfected with a CDHR2-overexpressing plasmid, and the changes in cell proliferation and cell cycle were evaluated using CCK-8 assay, EdU assay, and cell cycle assay; the changes in expressions of PI3K/Akt signaling pathway and cell cycle pathway proteins were detected with Western blotting. RESULTS: Bioinformatic analysis showed low CDHR2 expression level in both breast cancer and adjacent tissues without significant difference between them (P > 0.05), but breast cancer patients with a high expression of CDHR2 had a more favorable prognosis. Immunohistochemistry, qRT-PCR and Western blotting showed that the expression of CDHR2 was significantly down-regulated in breast cancer tissues and breast cancer cells (P < 0.01), and its overexpression strongly inhibited cell proliferation, caused cell cycle arrest, and significantly inhibited PI3K and Akt phosphorylation and the expression of cyclin D1. CONCLUSION: Overexpression of CDHR2 inhibits proliferation and causes cell cycle arrest in breast cancer cells possibly by inhibiting the PI3K/Akt signaling pathway.