Overexpressing S100A9 ameliorates NK cell dysfunction in estrogen receptor-positive breast cancer.

BACKGROUND: Estrogen receptor (ER) positive human epidermal growth factor receptor 2 (HER2) negative breast cancer (ER+/HER2-BC) and triple-negative breast cancer (TNBC) are two distinct breast cancer molecular subtypes, especially in tumor immune microenvironment (TIME). The TIME of TNBC is considered to be more inflammatory than that of ER+/HER2-BC. Natural killer (NK) cells are innate lymphocytes that play an important role of tumor eradication in TME. However, studies focusing on the different cell states of NK cells in breast cancer subtypes are still inadequate. METHODS: In this study, single-cell mRNA sequencing (scRNA-seq) and bulk mRNA sequencing data from ER+/HER2-BC and TNBC were analyzed. Key regulator of NK cell suppression in ER+/HER2-BC, S100A9, was quantified by qPCR and ELISA in MCF-7, T47D, MDA-MB-468 and MDA-MB-231 cell lines. The prognosis predictability of S100A9 and NK activation markers was evaluated by Kaplan-Meier analyses using TCGA-BRAC data. The phenotype changes of NK cells in ER+/HER2-BC after overexpressing S100A9 in cancer cells were evaluated by the production levels of IFN-gamma, perforin and granzyme B and cytotoxicity assay. RESULTS: By analyzing scRNA-seq data, we found that multiple genes involved in cellular stress response were upregulated in ER+/HER2-BC compared with TNBC. Moreover, TLR regulation pathway was significantly enriched using differentially expressed genes (DEGs) from comparing the transcriptome data of ER+/HER2-BC and TNBC cancer cells, and NK cell infiltration high/low groups. Among the DEGs, S100A9 was identified as a key regulator. Patients with higher expression levels of S100A9 and NK cell activation markers had better overall survival. Furthermore, we proved that overexpression of S100A9 in ER+/HER2-cells could improve cocultured NK cell function. CONCLUSION: In conclusion, the study we presented demonstrated that NK cells in ER+/HER2-BC were hypofunctional, and S100A9 was an important regulator of NK cell function in ER+BC. Our work contributes to elucidate the regulatory networks between cancer cells and NK cells and may provide theoretical basis for novel drug development.

Comparing survival outcomes between neoadjuvant and adjuvant chemotherapy within T2N1M0 stage hormone receptor-positive, HER2-negative breast cancer: a retrospective cohort study based on SEER database.

BACKGROUND: Guideline recommendations for the application of neoadjuvant chemotherapy (NACT) in T2N1M0 stage hormone receptor-positive, HER2-negative (HR + /HER2-) breast cancer are ambiguous. The debate continues regarding whether NACT or adjuvant chemotherapy (ACT) offers superior survival outcomes for these patients. MATERIALS AND METHODS: Female patients diagnosed with HR + /HER2- breast cancer at T2N1M0 stage between 2010 and 2020, were identified from the Surveillance, Epidemiology, and End Results database and divided into two groups, the NACT group and the ACT group. Propensity score matching (PSM) was utilized to establish balanced cohorts between groups, considering baseline features. Kaplan-Meier (K-M) analysis and the Cox proportional hazards model were executed to assess the efficacy of both NACT and ACT in terms of overall survival (OS) and breast cancer-specific survival (BCSS). A logistic regression model was employed to examine the association between predictive variables and response to NACT. RESULTS: After PSM, 4,682 patients were finally included. K-M curves showed that patients receiving NACT exhibited significantly worse OS and BCSS when compared with patients undergoing ACT. Multivariable Cox analysis indicated that not achieving pathologic complete response (non-pCR) after NACT (versus ACT), was identified as an adverse prognostic factor for OS (HR 1.58, 95% CI 1.36-1.83) and BCSS (HR 1.70, 95% CI 1.44-2. 02). The logistic regression model revealed that low tumor grade independently predicted non-pCR. CONCLUSION: Among T2N1M0 stage HR + /HER2- patients, OS and BCSS of NACT were inferior to ACT. Patients who attained non-pCR after NACT demonstrated significantly worse survival outcomes compared with those who received ACT.

Identification of a PANoptosis-related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer.

Breast cancer (BC) is the most prevalent malignancy among women worldwide. Mounting evidence suggests that PANoptosis participates in cancer development and therapy. However, the role of PANoptosis in BC remains unclear. In this study, we identified ten PANoptosis-related genes using Cox regression analysis, random forest (RF) algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. A PANoptosis-related score (PRS) was calculated based on the coefficient of LASSO. Notably, we divided the patients into high- and low-risk groups according to the PRS and revealed a negative correlation between PRS and overall survival. Next, a nomogram model was constructed and validated to improve the clinical application of PRS. Functional enrichment analyses and the Bayesian network demonstrated that differentially expressed genes between high- and low-risk groups were mainly enriched in immune-related pathways. Besides, we found significant differences in tumor mutation burden and tumor immune microenvironment between patients in these two groups using bulk-RNA and single-cell RNA sequencing data. Furthermore, charged multivesicular body protein 2B (CHMP2B) was identified as the hub gene by combining LASSO, weighted gene co-expression network analysis, RF and eXtreme Gradient Boosting. Importantly, using immunohistochemistry analysis based on our tissue microarray, we found that CHMP2B was highly expressed in tumor tissue, and CD4 and CD8 were more likely to be positive in the CHMP2B-negative group. Survival analyses revealed that CHMP2B adversely impacted the survival of BC patients. In conclusion, we not only constructed a highly accurate predictive model based on PRS, but also revealed the importance of PANoptosis-related gene signature in the modulation of the tumor microenvironment and drug sensitivity in BC.

A novel fault diagnosis strategy for LED lamps via light output time-frequency characteristics analysis and machine learning.

Faulty LED lamps can cause a decrease in light efficiency, lead to flicker, and have a negative impact on creating a reliable, stable, and healthy light environment. However, many LED lamps' faults are difficult to detect by electrical parameter measurements or naked-eye observation. Consequently, in this paper, a novel fault diagnosis strategy is proposed by analyzing light output time-frequency characteristics of LED lamps. The proposed fault diagnosis strategy contains three stages: (1) collecting the light output signal of LED lamps, (2) extracting the light output time-frequency characteristics of LED lamps by VMD and energy entropy calculation, and (3) employing SVM to construct the fault diagnosis model which used to identify the faulty LED lamps. To validate the feasibility and effectiveness of the proposed fault diagnosis strategy, simulation experiments are conducted, and the light output signals of LED lamps are collected as experiment datasets using the 10 kHz sampling frequency. The results demonstrate that the proposed fault diagnosis strategy can identify faults effectively, and average accuracy rate can reach to over 92%. This study can help promote the development of large-scale LED lamp maintenance management technology, and bring great benefits for the reliable and healthy operation of large-scale LED lamps particularly.

BPIFB1 promotes metastasis of hormone receptor-positive breast cancer via inducing macrophage M2-like polarization.

Metastasis is an important factor affecting the prognosis of hormone receptor-positive breast cancer (BC). However, the molecular basis for migration and invasion of tumor cells remains poorly understood. Here, we identify that bactericidal/permeability-increasing-fold-containing family B member 1 (BPIFB1), which plays an important role in innate immunity, is significantly elevated in breast cancer and associated with lymph node metastasis. High expression of BPIFB1 and its coding mRNA are significantly associated with poor prognosis of hormone receptor-positive BC. Using enrichment analysis and constructing immune infiltration evaluation, we predict the potential ability of BPIFB1 to promote macrophage M2 polarization. Finally, we demonstrate that BPIFB1 promotes the metastasis of hormone receptor-positive BC by stimulating the M2-like polarization of macrophages via the establishment of BC tumor cells/THP1 co-culture system, qPCR, Transwell assay, and animal experiments. To our knowledge, this is the first report on the role of BPIFB1 as a tumor promoter by activating the macrophage M2 polarization in hormone receptor-positive breast carcinoma. Together, these results provide novel insights into the mechanism of BPIFB1 in BC.

Synthesis and Hydrogen Production Performance of MoP/a-TiO2/Co-ZnIn2S4 Flower-like Composite Photocatalysts.

Semiconductor photocatalysis is an effective strategy for solving the problems of increasing energy demand and environmental pollution. ZnIn2S4-based semiconductor photocatalyst materials have attracted much attention in the field of photocatalysis due to their suitable energy band structure, stable chemical properties, and good visible light responsiveness. In this study, ZnIn2S4 catalysts were modified by metal ion doping, the construction of heterojunctions, and co-catalyst loading to successfully prepare composite photocatalysts. The Co-ZnIn2S4 catalyst synthesized by Co doping and ultrasonic exfoliation exhibited a broader absorption band edge. Next, an a-TiO2/Co-ZnIn2S4 composite photocatalyst was successfully prepared by coating partly amorphous TiO2 on the surface of Co-ZnIn2S4, and the effect of varying the TiO2 loading time on photocatalytic performance was investigated. Finally, MoP was loaded as a co-catalyst to increase the hydrogen production efficiency and reaction activity of the catalyst. The absorption edge of MoP/a-TiO2/Co-ZnIn2S4 was widened from 480 nm to about 518 nm, and the specific surface area increased from 41.29 m2/g to 53.25 m2/g. The hydrogen production performance of this composite catalyst was investigated using a simulated light photocatalytic hydrogen production test system, and the rate of hydrogen production by MoP/a-TiO2/Co-ZnIn2S4 was found to be 2.96 mmol·h-1·g-1, which was three times that of the pure ZnIn2S4 (0.98 mmol·h-1·g-1). After use in three cycles, the hydrogen production only decreased by 5%, indicating that it has good cycle stability.

Nomogram model combined thrombelastography for venous thromboembolism risk in patients undergoing lung cancer surgery.

Background: The aim of this study was to develop a nomogram model in combination with thromboelastography (TEG) to predict the development of venous thromboembolism (VTE) after lung cancer surgery. Methods: The data of 502 patients who underwent surgical treatment for lung cancer from December 2020 to December 2022 were retrospectively analyzed. Patients were then randomized into training and validation groups. Univariate and multivariate logistic regression analyses were carried out in the training group and independent risk factors were included in the nomogram to construct risk prediction models. The predictive capability of the model was assessed by the consistency index (C-index), receiver operating characteristic curves (ROC), the calibration plot and decision curve analysis (DCA). Results: The nomogram risk prediction model comprised of the following five independent risk factors: age, operation time, forced expiratory volume in one second and postoperative TEG parameters k value(K) and reaction time(R). The nomogram model demonstrated better predictive power than the modified Caprini model, with the C-index being greater. The calibration curve verified the consistency of nomogram between the two groups. Furthermore, DCA demonstrated the clinical value and potential for practical application of the nomogram. Conclusion: This study is the first to combine TEG and clinical risk factors to construct a nomogram to predict the occurrence of VTE in patients after lung cancer surgery. This model provides a simple and user-friendly method to assess the probability of VTE in postoperative lung cancer patients, enabling clinicians to develop individualized preventive anticoagulation strategies to reduce the incidence of such complications.

Construction of an immunogenic cell death-based risk score prognosis model in breast cancer.

Immunogenic cell death (ICD) is a form of regulated cell death that elicits immune response. Common inducers of ICD include cancer chemotherapy and radiation therapy. A better understanding of ICD might contribute to modify the current regimens of anti-cancer therapy, especially immunotherapy. This study aimed to identify ICD-related prognostic gene signatures in breast cancer (BC). An ICD-based gene prognostic signature was developed using Lasso-cox regression and Kaplan-Meier survival analysis based on datasets acquired from the Cancer Genome Atlas and Gene Expression Omnibus. A nomogram model was developed to predict the prognosis of BC patients. Gene Set Enrichment Analysis (GESA) and Gene Set Variation Analysis (GSVA) were used to explore the differentially expressed signaling pathways in high and low-risk groups. CIBERSORT and ESTIMATE algorithms were performed to investigate the difference of immune status in tumor microenvironment of different risk groups. Six genes (CALR, CLEC9A, BAX, TLR4, CXCR3, and PIK3CA) were selected for construction and validation of the prognosis model of BC based on public data. GSEA and GSVA analysis found that immune-related gene sets were enriched in low-risk group. Moreover, immune cell infiltration analysis showed that the immune features of the high-risk group were characterized by higher infiltration of tumor-associated macrophages and a lower proportion of CD8+ T cells, suggesting an immune evasive tumor microenvironment. We constructed and validated an ICD-based gene signature for predicting prognosis of breast cancer patients. Our model provides a tool with good discrimination and calibration abilities to predict the prognosis of BC, especially triple-negative breast cancer (TNBC).

Spatiotemporal evolution law and driving force of mining city patterns.

Urban transformation is an inevitable trend for mining cities to achieve sustainable development. Analyzing the spatiotemporal evolution laws and driving mechanisms of mining cities is necessary for providing a scientific basis for their transformation. In this study, Jixi was taken as an example, which is a typical mining city in China. Based on geographic information system, various mathematical statistical analysis methods were used to quantitatively analyze the evolution pattern of mining cities. In addition, the driving mechanisms of land expansion in mining cities were examined further. The results showed that (1) the urban land in the mining city is mainly distributed in low-lying areas, and land expansion mainly occurred in flat areas. (2) Based on the distribution of mineral resources, the land use pattern of mining cities was scattered; with steady economic development, the urban spatial pattern tends to be compact. (3) The spatial pattern of mining cities is affected by natural, economic, and policy factors. The results reveal the spatiotemporal evolution law and driving mechanism of the patterns in mining cities, thereby providing a scientific basis for the sustainable development planning and land management of mining cities.

Induction of protective and therapeutic antitumor immunity by a DNA vaccine with C3d as a molecular adjuvant.

Although the critical role of complement component C3d as a molecular adjuvant in preventing virus infection is well established, its role in cancer therapies is unclear. In this study, we have engineered a DNA vaccine that expresses extracellular region of murine VEGFR-2 (FLK1(265-2493)) and 3 copies of C3d (C3d3), a component of complement as a molecular adjuvant, designed to increase antitumor immunity. VEGFR-2 has a more restricted expression on endothelial cells and is upregulated once these cells proliferate during angiogenesis in the tumor vasculature. Immunization of mice with vector encoding FLK1(265-2493) alone generated only background levels of anti-VEGFR-2 antibodies and slight inhibitory effect on tumor growth. However, the addition of C3d3 to the vaccine construct significantly augmented the anti-VEGFR-2 humoral immune response and inhibited the tumor growth. The antitumor activity induced by vaccination with vector encoding FLK1(265-2493)-C3d3 fusion protein was also demonstrated via growth inhibition of established tumors following passive transfer of immune serum from vaccinated mice. Our results suggest that vaccination with vector encoding FLK1(265-2493) with C3d3 as a molecular adjuvant induces adaptive humoral activity, which is directed against the murine VEGFR-2 and can significantly inhibit tumor growth, and that administration of C3d as a molecular adjuvant to increase antibodies levels to VEGFR-2 may provide an alternative treatment modality for cancer therapies.