135 research outputs found

    MAGEA1 inhibits the expression of BORIS via increased promoter methylation

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    Melanoma-associated antigen A1 (MAGEA1) and BORIS (also known as CTCFL) are members of the cancer testis antigen (CTA) family. Their functions and expression-regulation mechanisms are not fully understood. In this study, we reveal new functions and regulatory mechanisms of MAGEA1 and BORIS in breast cancer cells, which we investigated in parental and genetically manipulated breast cancer cells via gene overexpression or siRNA-mediated downregulation. We identified the interaction between MAGEA1 and CTCF, which is required for the binding of MAGEA1 to the BORIS promoter and is critical for the recruitment of DNMT3a. A protein complex containing MAGEA1, CTCF and DNMT3a was formed before or after conjunction with the BORIS promoter. The binding of this complex to the BORIS promoter accounts for the hypermethylation and repression of BORIS expression, which results in cell death in the breast cancer cell lines tested. Multiple approaches were employed, including co-immunoprecipitation, glutathione S-transferase pull-down assay, co-localization and cell death analyses using annexin V-FITC/propidium iodide double-staining and caspase 3 activation assays, chromatin immunoprecipitation and bisulfite sequencing PCR assays for methylation. Our results have implications for the development of strategies in CTA-based immune therapeutics

    A multi-stage semi-supervised learning for ankle fracture classification on CT images

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    Because of the complicated mechanism of ankle injury, it is very difficult to diagnose ankle fracture in clinic. In order to simplify the process of fracture diagnosis, an automatic diagnosis model of ankle fracture was proposed. Firstly, a tibia-fibula segmentation network is proposed for the joint tibiofibular region of the ankle joint, and the corresponding segmentation dataset is established on the basis of fracture data. Secondly, the image registration method is used to register the bone segmentation mask with the normal bone mask. Finally, a semi-supervised classifier is constructed to make full use of a large number of unlabeled data to classify ankle fractures. Experiments show that the proposed method can segment fractures with fracture lines accurately and has better performance than the general method. At the same time, this method is superior to classification network in several indexes

    Effect of dietary Ginkgo biloba leaf on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii

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    This trial investigated the effect of dietary Ginkgo biloba leaf (GBL) on the growth performance and nonspecific immunity of red swamp crayfish Procambarus clarkii. 180 Crayfishes were randomly divided into three groups. One group was fed with basic diet, whereas the other two groups were fed with diets containing 1% and 3% GBL. After 32 days of feeding, GBL addition tended to increase the body weight gain rate compared with control. In 3% GBL group, the bodyweight gain rate of male crayfish was higher than that of female crayfish. While female crayfish were advantageous in terms of meat yield. Liver-related indexes were influenced by GBL addition and 3% GBL could reduce glutamic pyruvic transaminase and glutamic oxaloacetic transaminase as well as total cholesterol in male crayfish, showing its function in liver protection. Moreover, GBL addition effects on liver protection was better in male crayfish than female crayfish

    Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data

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    Purpose: Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers. However, fully automatic assessment of TILs on WSIs currently remains a great challenge because of the heterogeneity and large size of WSIs. We present an automatic pipeline based on a cascade-training U-net to generate high-resolution TIL maps on WSIs. Methods: We present global cell-level TIL maps and 43 quantitative TIL spatial image features for 1,000 WSIs of The Cancer Genome Atlas patients with breast cancer. For more specific analysis, all the patients were divided into three subtypes, namely, estrogen receptor (ER)-positive, ER-negative, and triple-negative groups. The associations between TIL scores and gene expression and somatic mutation were examined separately in three breast cancer subtypes. Both univariate and multivariate survival analyses were performed on 43 TIL image features to examine the prognostic value of TIL spatial patterns in different breast cancer subtypes. Results: The TIL score was in strong association with immune response pathway and genes (eg, programmed death-1 and CLTA4). Different breast cancer subtypes showed TIL score in association with mutations from different genes suggesting that different genetic alterations may lead to similar phenotypes. Spatial TIL features that represent density and distribution of TIL clusters were important indicators of the patient outcomes. Conclusion: Our pipeline can facilitate computational pathology-based discovery in cancer immunology and research on immunotherapy. Our analysis results are available for the research community to generate new hypotheses and insights on breast cancer immunology and development

    Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer

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    Background: Existing studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer. Methods: An established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis. Results: Using canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR < 0.05). We then found that these 436 regulatory regions were associated with 74 potential target genes. After functional enrichment analysis, we observed that these potential target genes were enriched in cancer-associated pathways. We further demonstrated that using the gene expression signals and the epithelial tissue proportion extracted from this integration framework could stratify patient prognoses more accurately, outperforming predictions based on only omics or image features. Conclusion: This integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets

    Automatic coronary artery segmentation of CCTA images using UNet with a local contextual transformer

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    Coronary artery segmentation is an essential procedure in the computer-aided diagnosis of coronary artery disease. It aims to identify and segment the regions of interest in the coronary circulation for further processing and diagnosis. Currently, automatic segmentation of coronary arteries is often unreliable because of their small size and poor distribution of contrast medium, as well as the problems that lead to over-segmentation or omission. To improve the performance of convolutional-neural-network (CNN) based coronary artery segmentation, we propose a novel automatic method, DR-LCT-UNet, with two innovative components: the Dense Residual (DR) module and the Local Contextual Transformer (LCT) module. The DR module aims to preserve unobtrusive features through dense residual connections, while the LCT module is an improved Transformer that focuses on local contextual information, so that coronary artery-related information can be better exploited. The LCT and DR modules are effectively integrated into the skip connections and encoder-decoder of the 3D segmentation network, respectively. Experiments on our CorArtTS2020 dataset show that the dice similarity coefficient (DSC), Recall, and Precision of the proposed method reached 85.8%, 86.3% and 85.8%, respectively, outperforming 3D-UNet (taken as the reference among the 6 other chosen comparison methods), by 2.1%, 1.9%, and 2.1%

    Long noncoding RNA AFAP1-AS1 acts as a competing endogenous RNA of miR-423-5p to facilitate nasopharyngeal carcinoma metastasis through regulating the Rho/Rac pathway

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    Background: Actin filament-associated protein 1 antisense RNA 1 (AFAP1-AS1), a long noncoding RNA, is significantly highly expressed and associated with metastasis and poor prognosis in many cancers, including nasopharyngeal carcinoma (NPC). In this study, we aim to identify the role of AFAP1-AS1 acting as an oncogenic lncRNA to promote NPC metastasis. Methods: The role of AFAP1-AS1, miR-423-5p, and FOSL2 in NPC metastasis was investigated in vitro and in vivo. Bioinformatics analysis and luciferase activity assays were used to identify the interaction between AFAP1-AS1, miR-423- 5p, and FOSL2. Additionally, real-time PCR and western blotting were used to assess the function of AFAP1-AS1 acting as an oncogenic lncRNA to promote NPC progression by regulating miR-423-5p and the downstream Rho/Rac pathway. Results: In this study, we determined that AFAP1-AS1 functions as a competing endogenous RNA in NPC to regulate the Rho/Rac pathway through miR-423-5p. These interactions can mediate the expression of RAB11B, LASP1, and FOSL2 and accelerate cell migration and invasion via the Rho/Rac signaling pathway or FOSL2. AFAP1-AS1 and FOSL2 could competitively bind with miR-423-5p to regulate several molecules, including RAB11B and LASP1 of the Rho/Rac signaling pathway. AFAP1-AS1 can also regulate the expression of LASP1, which was transcriptionally regulated by FOSL2, resulting in increased migration and invasion of NPC cells via the Rho/Rac signaling pathway. Conclusions: The observations in this study identify an important role for AFAP1-AS1 as a competing endogenous RNA (ceRNA) in NPC pathogenesis and indicate that it may serve as a potential target for cancer diagnosis and treatment

    Embryonic diapause due to high glucose is related to changes in glycolysis and oxidative phosphorylation, as well as abnormalities in the TCA cycle and amino acid metabolism

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    IntroductionThe adverse effects of high glucose on embryos can be traced to the preimplantation stage. This study aimed to observe the effect of high glucose on early-stage embryos. Methods and resultsSeven-week-old ICR female mice were superovulated and mated, and the zygotes were collected. The zygotes were randomly cultured in 5 different glucose concentrations (control, 20mM, 40mM, 60mM and 80mM glucose). The cleavage rate, blastocyst rate and total cell number of blastocyst were used to assess the embryo quality. 40 mM glucose was selected to model high glucose levels in this study. 40mM glucose arrested early embryonic development, and the blastocyst rate and total cell number of the blastocyst decreased significantly as glucose concentration was increased. The reduction in the total cell number of blastocysts in the high glucose group was attributed to decreased proliferation and increased cell apoptosis, which is associated with the diminished expression of GLUTs (GLUT1, GLUT2, GLUT3). Furthermore, the metabolic characterization of blastocyst culture was observed in the high-glucose environment. DiscussionThe balance of glycolysis and oxidative phosphorylation at the blastocyst stage was disrupted. And embryo development arrest due to high glucose is associated with changes in glycolysis and oxidative phosphorylation, as well as abnormalities in the TCA cycle and amino acid metabolism

    The role of tripartite motif-containing 28 in cancer progression and its therapeutic potentials

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    Tripartite motif-containing 28 (TRIM28) belongs to tripartite motif (TRIM) family. TRIM28 not only binds and degrades its downstream target, but also acts as a transcription co-factor to inhibit gene expression. More and more studies have shown that TRIM28 plays a vital role in tumor genesis and progression. Here, we reviewed the role of TRIM28 in tumor proliferation, migration, invasion and cell death. Moreover, we also summarized the important role of TRIM28 in tumor stemness sustainability and immune regulation. Because of the importance of TRIM28 in tumors, TIRM28 may be a candidate target for anti-tumor therapy and play an important role in tumor diagnosis and treatment in the future
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