Identification of therapeutic targets for osteosarcoma by integrating single-cell RNA sequencing and network pharmacology

Background: Osteosarcoma (OS) is a common primary tumor with extensive heterogeneity. In this study, we used single-cell RNA sequencing (scRNA-seq) and network pharmacology to analyze effective targets for Osteosarcoma treatment.Methods: The cell heterogeneity of the Osteosarcoma single-cell dataset GSE162454 was analyzed using the Seurat package. The bulk-RNA transcriptome dataset GSE36001 was downloaded and analyzed using the CIBERSORT algorithm. The key targets for OS therapy were determined using Pearson’s correlation analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on key targets. The DeepDR algorithm was used to predict potential drugs for Osteosarcoma treatment. Molecular docking analysis was performed to verify the binding abilities of the predicted drugs and key targets. qRT-PCR assay was used to detect the expression of key targets in osteoblasts and OS cells.Results: A total of 21 cell clusters were obtained based on the GSE162454 dataset, which were labeled as eight cell types by marker gene tagging. Four cell types (B cells, cancer-associated fibroblasts (CAFs), endothelial cells, and plasmocytes) were identified in Osteosarcoma and normal tissues, based on differences in cell abundance. In total, 17 key targets were identified by Pearson’s correlation analysis. GO and KEGG analysis showed that these 17 genes were associated with immune regulation pathways. Molecular docking analysis showed that RUNX2, OMD, and CD4 all bound well to vincristine, dexamethasone, and vinblastine. The expression of CD4, OMD, and JUN was decreased in Osteosarcoma cells compared with osteoblasts, whereas RUNX2 and COL9A3 expression was increased.Conclusion: We identified five key targets (CD4, RUNX2, OMD, COL9A3, and JUN) that are associated with Osteosarcoma progression. Vincristine, dexamethasone, and vinblastine may form a promising drug–target pair with RUNX2, OMD, and CD4 for Osteosarcoma treatment

A Mendelian analysis of the relationships between immune cells and breast cancer

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ %CD4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives

Health risks and respiratory intake of submicron particles in the working environment: A case study

Background: Powder-coating processes have been extensively used in various industries. The submicron particles generated during the powder-coating process in the workplace have complex compositions and can cause serious diseases. The purpose of this study was to better understand the health risks and respiratory intake of submicron particles during the powder coating process.Methods: The concentrations of and variations in submicron particles were measured using real-time instruments. The health risks of submicron particles were analyzed using the Stoffenmanager Nano model. A new computational fluid dynamics model was used to assess the respiratory intake of ultrafine particles (UFPs), which was indicated by the deposited dosage of UFPs in the olfactory area, nasal cavity, and lungs. The deposited doses of UFPs were used to calculate the average daily doses (ADDs) of workers, according to the method described by the Environmental Protection Agency.Results: The number concentration (NC), mass concentration, surface area concentration, personal NC, and lung-deposited surface area concentration of submicron particles were >105 pt/cm3, 0.2–0.4 mg/m3, 600–1,200 μm2/cm3, 0.7–1.4 pt/cm3, and 100–700 μm2/cm3, respectively. The size distribution showed that the submicron particles mainly gathered between 30 and 200 nm. The health risk of submicron particles was high. Upon respiratory intake, most UFPs (111.5 mg) were inhaled into the lungs, a few UFPs (0.272 mg) were trapped in the nasal cavity, and a small minority of UFPs (0.292 mg) were deposited in the olfactory area. The ADD of male workers with 10 years of exposure in the olfactory area, nasal cavity, and lung were 1.192 × 10–3 mg/kg·d−1, 1.11 × 10–3 mg/kg·d−1, and 0.455 mg/kg·d−1, respectively.Conclusion: Owing to the high concentrations of submicron particles, the workers involved in the powder-coating process are at a high health risk. Moreover, the respiratory intake of UFPs by workers is high, which is suggested by the highly deposited dosage of UFPs in the lungs and the corresponding high ADD in workers. Control measures, including engineering control, management control, and personal protective equipment, must be improved for the protection of workers

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Change Detection for High-Resolution Remote Sensing Images Based on a Multi-Scale Attention Siamese Network

To address the problems in remote sensing image change detection such as missed detection of features at different scales and incomplete region detection, this paper proposes a high-resolution remote sensing image change detection model (Multi-scale Attention Siamese Network, MASNet) based on a Siamese network and multi-scale attention mechanism. The MASNet model took the Siamese structure of the ResNet-50 network to extract features of different simultaneous images and then applied the attention module to feature maps of different scales to generate multi-scale feature representations. Meanwhile, an improved contrastive loss function was adopted to enhance the learning of change features and improving the imbalance problem between unchanged and changed samples. Furthermore, to address the current time-consuming and laborious phenomenon of manually annotating datasets, we provided a change detection dataset from Yunnan Province in China (YNCD) that contains 1540 pairs of 256 × 256 bi-temporal images with a spatial resolution of 1 m. Then, model training and change detection applications were studied by expanding a small number of experimental area samples into the existing public datasets. The results showed that the overall accuracy of the MASNet model for change detection in the experimental area is 95.34%, precision rate is 79.78%, recall rate is 81.52%, and F1 score is 80.64%, which are better than those of six comparative models (FC-EF, FC-Siam-Diff, FC-Siam-Conc, PAN, MANet, and STANet). This verifies the effectiveness of the MASNet model as well as the feasibility of change detection by expanding existing public datasets

DataSheet_3_A Mendelian analysis of the relationships between immune cells and breast cancer.pdf

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

DataSheet_2_A Mendelian analysis of the relationships between immune cells and breast cancer.pdf

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

DataSheet_1_A Mendelian analysis of the relationships between immune cells and breast cancer.pdf

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

Table_1_A Mendelian analysis of the relationships between immune cells and breast cancer.xlsx

BackgroundEmerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.MethodsA two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.ResultsAccording to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ �4+ (p-value:1.37×10−6), CD8dim %T cell (p-value:4.62×10−43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10−5), CD27 on PB/PC (p-value:2.72×10−18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10−6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10−166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms’ p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.ConclusionThrough genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.</p

Anticancer activity and mechanisms of action of Taisui fermentation broth in human colorectal cancer HCT116 cells in vitro and in vivo

Taisui, an unclassified biological object, is considered as a functional food with rich medicinal value in ancient Chinese books. However, there are few studies on Taisui, particularly on its anticancer activity and underlying mechanisms. Herein, we evaluated the anticancer potential of Taisui fermentation broth using HCT116 cells and nude mice xenografts in vitro and in vivo. Taisui fermentation broth inhibited HCT116 cells proliferation by inducing S-phase arrest, apoptosis, and autophagy, by regulating related proteins. Taisui fermentation broth-induced HCT116 cells death was reversed by inhibiting apoptosis and autophagy. Autophagy inhibition suppressed Taisui fermentation broth-induced apoptosis, whereas apoptosis inhibition attenuated Taisui fermentation broth-induced autophagy. Taisui fermentation broth induced apoptosis and autophagy by regulating reactive oxygen species-mediated c-Jun NH2-terminal kinase/p38 signaling in HCT116 cells. Additionally, Taisui fermentation broth inhibited tumor growth in a mouse xenograft model. Taisui fermentation broth may be a promising anticancer agent for the treatment of colorectal cancer