Molecular classification of geriatric breast cancer displays distinct senescent subgroups of prognostic significance.

Breast cancer in the elderly presents distinct biological characteristics and clinical treatment responses compared with cancer in younger patients. Comprehensive Geriatric Assessment is recommended for evaluating treatment efficacy in elderly cancer patients based on physiological classification. However, research on molecular classification in older cancer patients remains insufficient. In this study, we identified two subgroups with distinct senescent clusters among geriatric breast cancer patients through multi-omics analysis. Using various machine learning algorithms, we developed a comprehensive scoring model called "Sene_Signature," which more accurately distinguished elderly breast cancer patients compared with existing methods and better predicted their prognosis. The Sene_Signature was correlated with tumor immune cell infiltration, as supported by single-cell transcriptomics, RNA sequencing, and pathological data. Furthermore, we observed increased drug responsiveness in patients with a high Sene_Signature to treatments targeting the epidermal growth factor receptor and cell-cycle pathways. We also established a user-friendly web platform to assist investigators in assessing Sene_Signature scores and predicting treatment responses for elderly breast cancer patients. In conclusion, we developed a novel model for evaluating prognosis and therapeutic responses, providing a potential molecular classification that assists in the pre-treatment assessment of geriatric breast cancer.

ZC3H12A inhibits tumor growth and metastasis of breast cancer under hypoxic condition via the inactivation of IL-17 signaling pathway.

Hypoxia is a major contributor to tumor microenvironment (TME) and metastasis in most solid tumors. We seek to screen hypoxia-related genes affecting metastasis in breast cancer and to reveal relative potential regulatory pathway. Based on gene expression profiling of GSE17188 dataset, differential expressed genes (DEGs) were identified between highly metastatic breast cancer cells under hypoxia and samples under normoxia. The protein-protein interaction (PPI) network was utilized to determine hub genes. The gene expression profiling interactive analysis database (GEPIA2) and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) were employed to quantify hub genes. Moreover, overexpression of zinc finger CCCH-type containing 12A (ZC3H12A) was performed both in breast cancer cells and xenograft mouse model to determine the role of ZC3H12A. We identified 134 DEGs between hypoxic and normoxic samples. Based on PPI analysis, 5 hub genes interleukin (IL)-6, GALN (GAL), CD22 molecule (CD22), ZC3H12A and TNF receptor associated factor 1 (TRAF1) were determined; the expression levels of TRAF1, IL-6, ZC3H12A and GAL were remarkably downregulated while CD22 was upregulated in breast cancer cells. Besides, patients with higher expression of ZC3H12A had favorable prognosis. Overexpression of ZC3H12A could inhibit metastasis and tumor growth of breast cancer; overexpression of ZC3H12A downregulated the expression of IL-17 signaling pathway-related proteins such as IL-17 receptor A (IL-17RA), IL-17A and nuclear factor κB activator 1 (Act1). This study reveals ZC3H12A and IL-17 signaling pathway as potential therapeutic targets for hypoxic breast cancer.

LOC102724163 promotes breast cancer cell proliferation and invasion by stimulating MUC19 expression.

Breast cancer (BC) is a malignant disease and the most commonly diagnosed cancer in women. Numerous studies have previously verified the important role of long non-coding RNAs in a number of biological processes in BC. In the present study, analysis of The Cancer Genome Atlas database and reverse transcription-quantitative PCR demonstrated that LOC102724163 expression levels were significantly upregulated in BC tissues compared to matched adjacent normal tissues and were associated with an unfavorable prognosis in patients with BC. Gain or loss of function assays indicated that overexpression of LOC102724163 significantly increased tumorgenicity in vivo and cell migration, proliferation and invasion in vitro. In the mechanistical aspect, LOC102724163 sponged microRNA (miR)-508-5p to elevate MUC19 expression. Additionally, rescue assays ascertained the function of the LOC102724163/miR-508-5p/MUC19 axis in the proliferation and invasion of BC cells. To the best of our knowledge, this is the first study to have demonstrated that LOC102724163 may act as a competing endogenous RNA to control MUC19 expression levels by competitively sponging miR-508-5p to modulate BC progression. Therefore, the present study has provided new insights into BC diagnosis and treatment.

A Competing Endogenous RNA Network Reveals Novel lncRNA, miRNA and mRNA Biomarkers With Diagnostic and Prognostic Value for Early Breast Cancer.

BACKGROUND: This study aims to reveal early breast cancer (BC) specific competing endogenous RNA (ceRNA) network through the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and mRNAs. METHODS: Based on The Cancer Genome Atlas (TCGA), we obtained the differentially expressed mRNAs, miRNAs, and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) between early BC and normal samples. The lncRNA-miRNA-mRNA interaction network was constructed using Cytoscape. Functional enrichment were performed using GeneCoDis3. The expression of selected genes were validated by qRT-PCR. Based on the published dataset, we validated the result of TCGA integration analysis. The diagnostic and prognostic value of candidate genes was evaluated by ROC curve analysis and survival analysis, respectively. RESULTS: Totally, 1207 DEmRNAs, 194 DElncRNAs and 37 DEmiRNAs were obtained. Functional enrichment analysis results showed that all of DEmRNAs were enriched in pathway of cytokine-cytokine receptor interaction, PPAR signaling pathway and pathways in cancer. The DEmRNA-DEmiRNA-DElncRNA interaction network in early BC was consisted of 23 DEmiRNAs, 95 DElncRNAs and 309 DEmRNAs. Among ceRNA network, IL-6-hsa-miR-182-5p-ADAMTS9-AS1 interactions, LIFR-hsa-miR-21-5p-ADAMTS9-AS1 interactions and MMP1/MMP11-hsa-miR-145-5p-CDKN2B-AS1 interactions were speculated to involve in the development of early BC. The qRT-PCR results were consistent with our integrated analysis. Except for ADAMTS9-AS1 and CDKN2B-AS1, expression of the others results in the Gene Expression Omnibus (GEO) dataset were generally consistent with TCGA integrated analysis. The area under curve (AUC) of the ADAMTS9-AS1, CDKN2B-AS1, IL-6, MMP11, hsa-miR-145-5p and hsa-miR-182-5p were 0.947, 0.862, 0.842, 0.993, 0.960 and 0.944, and the specificity and sensitivity of the 6 biomarkers were 83.4% and 95.6%, 72.2% and 90.3%, 80.1% and 74.3%, 96.2% and 96.5%, 90.1% and 92.3%, and 88.7% and 90.4%, respectively. In addition, IL-6 had potential prognostic value for early BC. CONCLUSION: These findings may provide novel insights into the lncRNA-miRNA-mRNA network and uncover potential therapeutic targets in early BC.

Identification and validation of a combined hypoxia and immune index for triple-negative breast cancer.

The interaction between hypoxia and immune status has been confirmed in various cancer settings, and corresponding treatments have been investigated. However, reliable biomarkers are needed for individual treatment, so we sought to develop a novel scoring system based on hypoxia and immune status. Prognostic hypoxia-immune status-related signatures of patients with triple-negative breast cancer (TNBC) were identified in The Cancer Genome Atlas (TCGA) (N = 158), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (N = 297), and GSE58812 (N = 107). LASSO Cox regression was used for model construction. Hypoxia and immune status expression profiles were analyzed, and infiltrating immune cells were compared. Quantitative real-time PCR (qRT-PCR) was used for validation in the Sun Yat-sen University Cancer Center (SYSUCC) cohort, and immunofluorescence was applied for the detection of hypoxia and immune markers in cancer tissues. Ten cross-cohort prognostic hypoxia-immune signatures were included to construct the comprehensive index of hypoxia and immune (CIHI) in the METABRIC cohort. Two subgroups of patients with distinct hypoxia-immune status conditions were identified using CIHI: hypoxiahigh /immunelow and hypoxialow /immunehigh , with a significantly better overall survival (OS) rate in the latter (P < 0.01). The prognostic value of CIHI was further validated in the TCGA, GSE58812, and SYSUCC cohorts (P < 0.01). Hypoxia-immune signatures were significantly differentially expressed between the two groups, and more active immune responses were observed in the hypoxialow /immunehigh group. Cytotoxic lymphocytes were inversely correlated with CIHI in silico. Differentially expressed CA-IX and stromal PD-L1 were detected between subgroups of the SYSUCC cohort. A hypoxia-immune-based cross-cohort classifier for predicting prognosis was developed and validated, which may guide hypoxia modifier treatment and immunotherapy for TNBC.

Combined quantitative evaluation on early-stage fatigue damage of coarse-grained austenite stainless steel based on EBSD and ultrasonic technique.

The elastic anisotropy and heterogeneity effects of coarse-grained austenite on ultrasonic propagation significantly undermine the effectiveness of ultrasonic property-based fatigue damage evaluation. A discrete method based on electron backscatter diffraction (EBSD) was proposed to decouple the effects between coarse-grained structure and fatigue damage. An orientation-based damage index, local misorientation (ML), was extracted and macroscopic and microscopic plastic deformations were characterized. The evolution of ultrasonic attenuation coefficient Δα was established with ΔML in grain scale. Approximate downward parabolas was observed, and the peak value of Δα in 〈1 1 1〉 orientation was found to be larger and more sensitive to the cyclic damage than that of 〈0 0 1〉 and 〈0 1 1〉. The influences of the heterogeneous substructure and surface roughness were discussed respectively.

Ultrasonic characterization of thermal barrier coatings porosity through BP neural network optimizing Gaussian process regression algorithm.

Porosity is an integral part of thermal barrier coatings (TBCs) and is required to provide thermal insulation and to accommodate operational thermal stresses. Accurate characterization of the TBCs porosity is difficult due to the complex pore morphology and ultra-thin coating thickness. In this paper, a BP neural network optimizing Gaussian process regression (GPR) algorithm, termed BP-GPR, is presented to characterize the TBCs porosity based on a constructed ultrasonic reflection coefficient amplitude spectrum (URCAS). The characteristic parameters of URCAS are optimized through the BP neural network combined with a high determination coefficient R2 rule. Then the optimized parameters are utilized to train the GPR algorithm for predicting the unknown TBCs porosity. The proposed BP-GPR method was demonstrated through a series of finite element method (FEM) simulations, which were implemented on random pore models (RPMs) of plasma spraying ZrO2 coating with a thickness of 300 µm and porosities of 1%, 3%, 5%, 7%, and 9%. Simulation results indicated the relative errors of the predicted porosity of RPMs were 6.37%, 7.62%, 1.07%, and 1.07%, respectively, which has 32% and 48% accuracy higher than that predicted only by BP neural network or GPR algorithm. It is verified that the proposed BP-GPR method can accurately characterize the porosity of TBCs with complex pore morphology.

Modeling of ultrasonic propagation in heavy-walled centrifugally cast austenitic stainless steel based on EBSD analysis.

The ultrasonic inspection of heavy-walled centrifugally cast austenitic stainless steel (CCASS) is challenging due to the complex metallurgical structure. Numerical modeling could provide quantitative information on ultrasonic propagation and plays an important role in developing advanced and reliable ultrasonic inspection techniques. But the fundamental obstacle is the accurate description of the complex metallurgical structure. To overcome this difficulty, a crystal orientation map of a CCASS specimen in the 96 mm × 12 mm radial-axial cross section was acquired based on the electron backscattered diffraction (EBSD) technique and it was used to describe the coarse-grained structure and grain orientation. A model of ultrasonic propagation for CCASS was built according to the EBSD map. The ultrasonic responses of the CCASS sample were also tested. Some experimental phenomena such as structural noise and signal distortion were reproduced. The simulated results showed a good consistence with the experiments. The modeling method is expected to be effective for the precise interpretation of ultrasonic propagation in the polycrystalline structures of CCASS.

Safflower polysaccharide inhibits the proliferation and metastasis of MCF-7 breast cancer cell.

Breast cancer accounts for 22.9% of all types of cancer in females worldwide. Safflower polysaccharide (SPS) is an active fraction purified from safflower petals (Carthamus tinctorius L). The present study investigated the effects of safflower polysaccharide on the proliferation and metastasis of breast cancer cells. Cell viability was analyzed using an MTT assay following treatment of the MCF­7 cells with increasing concentrations of SPS. The results demonstrated that the SPS compound significantly inhibited the proliferation of the MCF­7 human breast cancer cell line and these inhibitory effects increased in a dose­ and time­dependent manner. The half maximal inhibitory concentration (IC50) value of SPS on breast cancer cells, following treatment for 72 h, was detected using an MTT assay and was calculated as 0.12 mg/ml. The apoptotic rate was detected using flow cytometry in the MCF­7 human breast cancer cell line and the results revealed that SPS induced cell apoptosis. The apoptotic rate of the MCF­7 cells treated with SPS was significantly higher compared with that of the untreated cells and increased in a dose­dependent manner. The expression of B­cell lymphoma 2 (Bcl­2) was downregulated and the expression of Bcl­2­associated X protein was upregulated in the MCF­7 cells treated with SPS in a time­dependent manner. Additionally, the expression of matrix metalloproteinase­9 was significantly reduced and the expression of tissue inhibitor of metalloproteinase­1 was increased in the MCF­7 human breast cancer cell treated with SPS. These results demonstrated that SPS inhibited the metastasis of MCF­7 breast cancer cells and understanding the underlying mechanisms may provide novel strategies in breast cancer therapy.

Ultrasonic characterization of thermally grown oxide in thermal barrier coating by reflection coefficient amplitude spectrum.

The thermally grown oxide (TGO) growth at the interface of ceramic coating/bond coating in thermal barrier coatings (TBCs) was evaluated by ultrasonic reflection coefficient amplitude spectrum (URCAS). A theoretical analysis was performed about the influence of acoustic impedance match relationship between the ceramic coating and its adjacent media on URCAS. The immersion ultrasonic narrow pulse echo method was carried out on the TBC specimen before and after oxidation under 1050°C×1h for 15cycles. The resonant peaks of URCAS obtained before and after oxidation showed that TGO which generated between the ceramic coating and bond coating due to the oxidation, changed the acoustic impedance match between the ceramic coating and its adjacent media. This method is able to nondestructively characterize the generation of TGO in TBCs, and is important to practical engineering application.