LncRNA SEMA3B-AS1 suppresses the tumor-initiating characteristics of triple negative breast cancer via engaging in MLL4-mediated H3K4 trimethylation.

Long noncoding RNAs (lncRNAs) are crucial regulators of tumor-initiating cells (TICs) and hold particular importance in triple negative breast cancer (TNBC). Yet, the precise mechanisms by which TIC-associated lncRNAs influence TNBC remain unclear. Our research utilized The Cancer Genome Atlas Breast Cancer (BC) data set to identify prognostic lncRNAs. We then conducted extensive assays to explore their impact on the tumor-initiating phenotype of TNBC cells and the underlying mechanisms. Notably, we found that low expression of lncRNA SEMA3B-AS1 correlated with unfavorable survival in BC patients. SEMA3B-AS1 was also downregulated in TNBC and linked to advanced tumor stage. Functional experiments confirmed its role as a TIC-suppressing lncRNA, curtailing mammosphere formation, ALDH + TIC cell proportion, and impairing clonogenicity, migration, and invasion. Mechanistic insights unveiled SEMA3B-AS1's nuclear localization and interaction with MLL4 (mixed-lineage leukemia 4), triggering H3K4 methylation-associated transcript activation and thus elevating the expression of SEMA3B, a recognized tumor suppressor gene. Our findings emphasize SEMA3B-AS1's significance as a TNBC-suppressing lncRNA that modulates TIC behavior. This study advances our comprehension of lncRNA's role in TNBC progression, advocating for their potential as therapeutic targets in this aggressive BC subtype.

Evaluation of brain nerve function in ICU patients with Delirium by deep learning algorithm-based resting state MRI.

The purpose of this study was to explore the value of resting-state magnetic resonance imaging (MRI) based on the brain extraction tool (BET) algorithm in evaluating the cranial nerve function of patients with delirium in intensive care unit (ICU). A total of 100 patients with delirium in hospital were studied, and 20 healthy volunteers were used as control. All the subjects were examined by MRI, and the images were analyzed by the BET algorithm, and the convolution neural network (CNN) algorithm was introduced for comparison. The application effects of the two algorithms were analyzed, and the differences of brain nerve function between delirium patients and normal people were explored. The results showed that the root mean square error, high frequency error norm, and structural similarity of the BET algorithm were 70.4%, 71.5%, and 0.92, respectively, which were significantly higher than those of the CNN algorithm (P < 0.05). Compared with normal people, the ReHo values of pontine, hippocampus (right), cerebellum (left), midbrain, and basal ganglia in delirium patients were significantly higher. ReHo values of frontal gyrus, middle frontal gyrus, left inferior frontal gyrus, parietal lobe, and temporal lobe and anisotropy scores (FA) of cerebellums (left), frontal lobe, temporal lobe (left), corpus callosum, and hippocampus (left) decreased significantly. The average diffusivity (MD) of medial frontal lobe, superior temporal gyrus (right), the first half of cingulate gyrus, bilateral insula, and caudate nucleus (left) increased significantly (P < 0.05). MRI based on the deep learning algorithm can effectively improve the image quality, which is valuable in evaluating the brain nerve function of delirium patients. Abnormal brain structure damage and abnormal function can be used to help diagnose delirium.

A novel disulfidptosis-associated expression pattern in breast cancer based on machine learning.

Background: Breast cancer (BC), the leading cause of cancer-related deaths among women, remains a serious threat to human health worldwide. The biological function and prognostic value of disulfidptosis as a novel strategy for BC treatment via induction of cell death remain unknown. Methods: Gene mutations and copy number variations (CNVs) in 10 disulfidptosis genes were evaluated. Differential expression, prognostic, and univariate Cox analyses were then performed for 10 genes, and BC-specific disulfidptosis-related genes (DRGs) were screened. Unsupervised consensus clustering was used to identify different expression clusters. In addition, we screened the differentially expressed genes (DEGs) among different expression clusters and identified hub genes. Moreover, the expression level of DEGs was detected by RT-qPCR in cellular level. Finally, we used the least absolute shrinkage and selection operator (LASSO) regression algorithm to establish a prognostic feature based on DEGs, and verified the accuracy and sensitivity of its prediction through prognostic analysis and subject operating characteristic curve analysis. The correlation of the signature with the tumor immune microenvironment and tumor stemness was analyzed. Results: Disulfidptosis genes showed significant CNVs. Two clusters were identified based on three DRGs (DNUFS1, LRPPRC, SLC7A11). Cluster A was found to be associated with better survival outcomes(p < 0.05) and higher levels of immune cell infiltration(p < 0.05). A prognostic signature of four disulfidptosis-related DEGs (KIF21A, APOD, ALOX15B, ELOVL2) was developed by LASSO regression analysis. The signature showed a good prediction ability. In addition, the prognostic signature in this study were strongly related to the tumor microenvironment (TME), tumor immune cell infiltration, tumor mutation burden (TMB), tumor stemness, and drug sensitivity. Conclusion: The prognostic signature we constructed based on disulfidptosis-DEGs is a good predictor of prognosis in patients with BC. This prognostic signature is closely related to TME, and its potential correlation provides clues for further studies.

A ceRNA network-mediated over-expression of cuproptosis-related gene SLC31A1 correlates with poor prognosis and positive immune infiltration in breast cancer.

Introduction: Solute carrier family 31 member 1(SLC31A1) has been reported as the copper importer, and was identified to be involved in the process of "cuproptosis". However, the mechanism of SLC31A1 in breast cancer remains unclear. Methods: We examined the expression of SLC31A1 mRNA in breast cancer tissues and cell lines using Real-time PCR. The data for this study were obtained from The Cancer Genome Atlas (TCGA) database and analyzed via R 3.6.3. TIMER, UALCAN, GEPIA2, STRING, Metascape, Kaplan-Meier Plotter, starBase and miRNet websites were used for a comprehensive analysis of SLC31A1. Results: Our study suggested that SLC31A1 mRNA was over-expressed in breast tumor tissue and breast cancer cell lines, and which was closely related to poor relapse-free survival (RFS) and distant metastasis-free survival (DMFS). In addition, we constructed a co-expression network of SLC31A1. Functional enrichment analysis indicated that they were mainly involved in copper ion transport. Interestingly, SLC31A1 expression was positively associated with all m6A-related genes, especially with YTHDF3 (r = 0.479). Importantly, the LINC00511/miR-29c-3p/SLC31A1 axis was identified as the most potential pathway promoting breast cancer progress by affecting copper transport. Furthermore, the expression level of SLC31A1 in breast cancer was positively correlated with tumor immune cell infiltration, immune cell biomarkers and cancer-associated fibroblast (CAF). Conclusion: Up-regulation of SLC31A1 expression and regulation of copper ion transport mediated by LINC00511-miR-29-3p axis is related to poor prognosis and positively correlated with tumor immune infiltration in breast cancer.

Validation of the Eighth American Joint Committee on Cancer Anatomic and Prognostic Staging System for Breast Cancer.

BACKGROUND: The eighth edition of new staging systems for breast cancer incorporated four biological factors and the anatomic staging system. Validating analysis on Chinese patients has been limited. Our study performed analysis comparing the prognostic value of the staging system based on Chinese data. METHODS AND MATERIALS: All patients were classified according to the eighth edition and compared between anatomic and prognostic staging systems. The Kaplan-Meier test was used to calculate the overall survival (OS) and disease-free survival (DFS). We performed Harrell concordance index (C-index) analyses to quantify a models' predictive performance. Akaike information criterion (AIC) via Cox regression analysis was used to conduct bootstrap-based goodness-of-fit comparisons of the competing staging systems. RESULTS: A total of 1556 patients were enrolled in the cohort. The median follow-up time was 76 mo (range, 4-146 mo), the median age was 48 y old (range, 21-87 y). The ratio of movement between anatomic stage (AS) and prognostic stage (PS) was 50.9%. Of these, 691 (44.5%) AS patients were down staged and 100 (6.4%) patients were upstaged when reclassified based on PS. Significant differences between two stages were achieved for stage IIIC in 5-y OS rates and for IIIB in 5-y DFS rates (63.5% versus 50.0% and 58.0% versus44.0%). The value of the C-index for PS and AS were 0.711 and 0.687 (P = 0.04). The AIC reaches a value of 3452.9 for the PS and a value of 3476.4 for the AS. CONCLUSIONS: The PS might provide better accuracy than the AS in predicting the prognosis of Chinese female breast cancer patients. It also provides a strong basis for the utility of clinical biomarkers to evaluate the prognosis of patients.

Comparison of the Gut Microbiota in Patients with Benign and Malignant Breast Tumors: A Pilot Study.

The microbiome plays diverse roles in many diseases and can potentially contribute to cancer development. Breast cancer is the most commonly diagnosed cancer in women worldwide. Thus, we investigated whether the gut microbiota differs between patients with breast carcinoma and those with benign tumors. The DNA of the fecal microbiota community was detected by Illumina sequencing and the taxonomy of 16S rRNA genes. The α-diversity and ß-diversity analyses were used to determine richness and evenness of the gut microbiota. Gene function prediction of the microbiota in patients with benign and malignant carcinoma was performed using PICRUSt. There was no significant difference in the α-diversity between patients with benign and malignant tumors (P = 3.15e-1 for the Chao index and P = 3.1e-1 for the ACE index). The microbiota composition was different between the 2 groups, although no statistical difference was observed in ß-diversity. Of the 31 different genera compared between the 2 groups, level of only Citrobacter was significantly higher in the malignant tumor group than that in benign tumor group. The metabolic pathways of the gut microbiome in the malignant tumor group were significantly different from those in benign tumor group. Furthermore, the study establishes the distinct richness of the gut microbiome in patients with breast cancer with different clinicopathological factors, including ER, PR, Ki-67 level, Her2 status, and tumor grade. These findings suggest that the gut microbiome may be useful for the diagnosis and treatment of malignant breast carcinoma.

Upregulated Long Non-Coding RNA LL22NC03-N64E9.1 Promotes the Proliferation and Migration of Human Breast Cancer Cells by Silencing Kruppel-Like Factor 2 Expression.

INTRODUCTION: Recently, the significant regulatory effects of lncRNAs on the oncogenesis and growth of tumor have been demonstrated by an increasing number of research projects. A previous study showed that LL22NC03-N64E9.1 could promote the development of colorectal cancer, especially via enhanced cell proliferation. Similarly, this lncRNA should have comparable functions in breast cancer (BC), which requires in-depth investigation. Therefore, this study was designed to explore the correlation of LL22NC03-N64E9.1 with BC. METHODS: qRT-PCR was used to assess the relative expression of LL22NC03-N64E9.1 in BC tissues. Cell viability examination and colony formation experiments were performed to investigate the role of LL22NC03-N64E9.1 in BC cell's proliferation. Transwell assays were used to explore the effects of LL22NC03-N64E9.1 on BC cell's migration. RNA immunoprecipitation, chromosome immunoprecipitation assay and rescue experiments were performed to analyze the association of LL22NC03-N64E9.1 with target proteins and genes in BC cells. RESULTS: We identified that LL22NC03-N64E9.1 is an oncogene, upregulated in BC, which was verified in a cohort of 48 pairs of BC tissues. Based on the loss-of-function experiments, silencing LL22NC03-N64E9.1 expression significantly inhibited malignancy progression. In terms of the mechanism, LL22NC03-N64E9.1 acted on the enhancer of zeste homolog 2 (EZH2) by direct binding, which promoted BC cell growth. Furthermore, in the promoters of KLF2, the trimethylation of H3K27 could be regulated by LL22NC03-N64E9.1 as the mediator. CONCLUSION: Relying on the LL22NC03-N64E9.1/EZH2/KLF2 pathway, the lncRNA LL22NC03-N64E9.1 was significantly associated with BC development and could, therefore, be a potential therapeutic target to block BC growth.

Long intergenic non-protein-coding RNA 01446 facilitates the proliferation and metastasis of gastric cancer cells through interacting with the histone lysine-specific demethylase LSD1.

Growing evidences illustrated that long non-coding RNAs (lncRNAs) exhibited widespread effects on the progression of human cancers via various mechanisms. Long intergenic non-protein-coding RNA 01446 (LINC01446), a 3484-bp ncRNA, is known to locate at chromosome 7p12.1. However, its biological functions and specific action mechanism in gastric cancer (GC) are still unclear. In our study, LINC01446 was proved to be markedly upregulated in GC tissues relative to the normal tissues, and positively correlated with the poor survival of GC patients. The multivariate Cox regression model showed that LINC01446 functioned as an independent prognostic factor for the survival of GC patients. Functionally, LINC01446 facilitated the proliferation and metastasis of GC cells. Moreover, RNA-seq analysis demonstrated that LINC01446 knockdown primarily regulated the genes relating to the growth and migration of GC. Mechanistically, LINC01446 could widely interact with histone lysine-specific demethylase LSD1 and recruit LSD1 to the Ras-related dexamethasone-induced 1 (RASD1) promoter, thereby suppressing RASD1 transcription. Overall, these findings suggest that LINC01446/LSD1/RASD1 regulatory axis may provide bona fide targets for anti-GC therapies.

Effect of node status on breast cancer survival by subtype: a single-center retrospective cohort study.

BACKGROUND: Nodal involvement and molecular subtypes were used as independent prognostic indicators in women with breast cancer. However, they did not adequately address the effect of node status by subtype in outcomes. METHODS: We performed a retrospective review of data from 2004 to 2011 from the Affiliated Union Hospital of Fujian Medical University with newly diagnosed stage I to III breast cancer to investigate the relationship between node status and 5-year disease-free survival (DFS) and breast cancer-specific survival (BCSS) by molecular subtype. The Cox proportional hazards model was used for multivariate analysis. RESULTS: Median follow-up time was 6.4 years. Luminal HER2 and luminal B were the subtypes with a higher percentage of nodal involvement and high-volume nodal involvement (≥4 positive lymph node) than luminal A. The effect of node status on the prognosis varied with molecular subtype. There was no difference in 5-year DFS and BCSS between stage N1 or N2 and N0 groups in patients with luminal A disease. Nodal involvement in women with the luminal B, luminal HER2, and triple-negative subtypes showed significant difference for 5-year DFS and BCSS compared to the node negative group. CONCLUSIONS: Nodal involvement seems to be associated with worse survival in women with the luminal B, luminal HER2, and triple-negative subtypes, but not with the luminal A subtype.

Different prognosis by subtype in the early mucinous breast cancer: a SEER population-based analysis.

BACKGROUND: Our study aims to investigate the clinicopathological characteristics and survival outcomes of mucinous breast cancer (MBC), and explore the effect of histology type on the breast cancer-specific survival (BCSS) by different subtypes. METHODS: we identified 7,083 patients who were diagnosed with MBC and 248,751 with infiltrating ductal carcinoma (IDC) by using the Surveillance, Epidemiology and End Results (SEER) database. The propensity score matching was used to match baseline characteristics among MBC and IDC, and multivariable cox proportional hazards models were used to analyze the relationship between histology type stratified by subtype and BCSS. RESULTS: MBC patients were associated with a fewer nodal involvement, lower grade, earlier stage, more estrogen receptor (ER) or progesterone receptor (PR) positive, and more favorable prognosis compared to the overall IDC population. After 1:1 matching of MBC with IDC by other factors, we found that MBC patients presented better prognosis than the Matched IDC for BCSS. Analysis among ER+PR+ subgroup revealed that MBC patients was significantly better than that Matched IDC patients for BCSS (HR =0.78, 95% CI, 0.63-0.96). However, the survival analysis in the ER+PR- or ER-PR- subgroups suggested that no significant difference was seen between MBC patients and matched IDC patients for BCSS. CONCLUSIONS: Our findings support that MBC seems to be an independent factor for the better prognosis for breast cancer patients with ER+PR+ breast cancer but not in those with ER+PR- or ER-PR- disease.

An inorganic prodrug, tellurium nanowires with enhanced ROS generation and GSH depletion for selective cancer therapy.

Organic prodrugs have been widely reported to avoid side effects and have been applied for precise tumor therapy in recent years. However, inorganic nano-prodrugs with localized generation of toxic products in the tumor have not been reported. Herein, we report an inorganic nano-prodrug, tellurium nanowires (TeNWs), that generate toxic TeO6 6- triggered by hydrogen peroxide (H2O2) for highly selective cancer chemotherapy. Bovine serum albumin and dextran conjugate coated TeNWs, with a length of ∼82 nm and a width of ∼7 nm, showed high stability in physiological medium. The interaction between TeNWs and intracellular H2O2 produces toxic TeO6 6- molecules greatly enhanced ROS generation, and the reaction product, verified as TeO6 6-, would react with glutathione (GSH) and thus decrease intracellular GSH levels, which greatly increases ROS levels in the tumor. Importantly, TeNWs selectively kill cancer cells by caspase-independent autophagic death and apoptosis, as well as exerting an immune response, while not affecting normal cells due to the high H2O2 levels in cancer cells. Moreover, after the sequential reaction with H2O2 and GSH, TeNWs were dissociated into small molecules and could be rapidly and completely removed from the body. Both in vitro and in vivo experiments indicate that TeNWs are a promising inorganic nano-prodrug that exerts good selective therapeutic effects on tumors.

The Impact of Young Age for Prognosis by Subtype in Women with Early Breast Cancer.

Young age (≤40 years) use to be considered an independent risk factor for the prognosis of women with early-stage breast cancer. We conducted a retrospective analysis to investigate this claim in a population of young patients who were stratified by molecular subtype. We identified 2,125 women with stage I to III breast cancer from the Fujian Medical University Union Hospital. Multivariable Cox proportional hazards models were used to analyze the relationship between age groups stratified by molecular subtype and 5-year disease-free survival (DFS), 5-year distant metastasis-free survival (DMFS), and 5-year breast cancer-specific survival (BCSS). Median follow-up time was 77 months. Patients ≤40 years of age presented with a significantly worse 5-year DFS and 5-year DMFS. In stratified analyses, young women with luminal A subtype disease were associated with a worse 5-year DFS, 5-year DMFS, and 5-year BCSS. Women with luminal B (Her2-) tumors showed a decrease in 5-year DFS and 5-year DMFS. Our findings support the hypothesis that young age seems to be an independent risk factor for the prognosis for breast cancer patients with the luminal A and luminal B (Her2-) subtypes but not in those with luminal B (Her2+), Her2 over-expression, and triple-negative disease.