Verification of TREX1 as a promising indicator of judging the prognosis of osteosarcoma

TREX1 cytosolic DNA degradation correlates with autoimmune disease and cancer immunity

The N-terminal domain of Three Prime Repair Exonuclease 1 (TREX1) is catalytically active and can degrade dsDNA or ssDNA in the cytosol, whereas the C-terminal domain is primarily involved in protein localization. TREX1 deficiency induces cytosolic DNA accumulation as well as activation of the cGAS-STING-IFN signaling pathway, which results in tissue inflammation and autoimmune diseases. Furthermore, TREX1 expression in cancer immunity can be adaptively regulated to promote tumor proliferation, making it a promising therapeutic target.

MetastaSite: Predicting metastasis to different sites using deep learning with gene expression data

Deep learning has massive potential in predicting phenotype from different omics profiles. However, deep neural networks are viewed as black boxes, providing predictions without explanation. Therefore, the requirements for these models to become interpretable are increasing, especially in the medical field. Here we propose a computational framework that takes the gene expression profile of any primary cancer sample and predicts whether patients' samples are primary (localized) or metastasized to the brain, bone, lung, or liver based on deep learning architecture. Specifically, we first constructed an AutoEncoder framework to learn the non-linear relationship between genes, and then DeepLIFT was applied to calculate genes' importance scores. Next, to mine the top essential genes that can distinguish the primary and metastasized tumors, we iteratively added ten top-ranked genes based upon their importance score to train a DNN model. Then we trained a final multi-class DNN that uses the output from the previous part as an input and predicts whether samples are primary or metastasized to the brain, bone, lung, or liver. The prediction performances ranged from AUC of 0.93-0.82. We further designed the model's workflow to provide a second functionality beyond metastasis site prediction, i.e., to identify the biological functions that the DL model uses to perform the prediction. To our knowledge, this is the first multi-class DNN model developed for the generic prediction of metastasis to various sites.

TREX1 suppression imparts cancer-stem-cell-like characteristics to CD133- osteosarcoma cells through the activation of E2F4 signaling

There is ongoing debate whether cancer stem cells (CSCs) could arise from the transformation of non-CSCs under specific conditions. In the present study, the role of the three prime repair exonuclease 1 (TREX1) in regulating CSC generation form human osteosarcoma cells was investigated. High, intermediate and low levels of TREX1 expression were respectively observed in low-grade, high-grade and metastatic human osteosarcoma samples, while the opposite tendency was observed for E2F4, a transcription factor associated with G2 arrest. Luciferase assay proved that TREX1 had a negative impact on the activity of E2F4 promoter. TREX1 was highly expressed in CD133^- HOS cells (non-CSC osteosarcoma cells) compared to CD133⁺ ones; whereas TREX1 knockdown endowed the CD133^- non-CSCs with CSC-like characteristics in vitro relying on E2F4 activation, as demonstrated by enlarged proportion of the subset expressing CSC markers in flow cytometry analysis, enhanced self-renewal ability in osteosphere formation assay, increased metastasis capacity in migration and invasion assays, together with improved chemoresistance to cisplatin. Furthermore, TREX1 knockdown and subsequent E2F4 activation could promote the tumorigenicity of CD133^- non-CSCs in vivo. With respect to underlying mechanisms, it was found that in CD133^- HOS cells, TREX1 suppression would allow the activation of β-catenin signaling in the dependence of E2F4, thus possibly leading to the up-regulation of the transcription factor OCT4. These findings suggested that TREX1 was probably a negative regulator of CSC formation and hence worth to be further studied for developing new treatments in cancer therapies targeting CSCs.

The expressions of CD133, ALDH1, and vasculogenic mimicry in osteosarcoma and their clinical significance

BACKGROUND AND PURPOSE

Osteosarcoma is an aggressive malignant bone tumor in children and adolescents, which is more likely to recur and metastasize at the early stages. Cancer stem cells (CSC, CD133 is a biomarker of cancer stem cells), angiogenesis, and vasculogenic mimicry (VM) are closely related to tumor metastasis and recurrence. In this study, we investigated the associations among CD133, aldehyde dehydrogenase 1 (ALDH1), and VM in osteosarcoma, and their associations with clinical characteristics.

METHODS

Positive rates of CD133, ALDH1, and VM in 96 whole osteosarcoma tissue samples were detected by immunohistochemistry (IHC) and histochemistry staining. Patients' clinical data were also collected.

RESULTS

Positive rates of CD133, ALDH1, and VM were significantly higher in osteosarcoma tissues compared with the control tissues. Positive rates of CD133, ALDH1, and VM were positively associated with lymph node metastasis, distant metastasis, Enneking stages, and patients' overall survival (OS). A multivariate analysis indicated that the positive rates of CD133, ALDH1, and VM, as well as the Enneking stages were independent prognostic factors of osteosarcoma.

CONCLUSION

The positive rates of CD133, ALDH1, and VM could represent potential biomarkers for metastasis and prognosis, which suggests these molecules might be promising therapeutic targets for osteosarcoma.

Exploring the key genes and pathways of side population cells in human osteosarcoma using gene expression array analysis

BACKGROUND

Human osteosarcoma (OS) is one of the most common primary bone sarcoma, because of early metastasis and few treatment strategies. It has been reported that the tumorigenicity and self-renewal capacity of side population (SP) cells play roles in human OS via regulating of target genes. This study aims to complement the differentially expressed genes (DEGs) that regulated between the SP cells and the non-SP cells from primary human OS and identify their functions and molecular pathways associated with OS.

METHODS

The gene expression profile GSE63390 was downloaded, and bioinformatics analysis was made.

RESULTS

One hundred forty-one DEGs totally were identified. Among them, 72 DEGs (51.06%) were overexpressed, and the remaining 69 DEGs (48.94%) were underexpressed. Gene ontology (GO) and pathway enrichment analysis of target genes were performed. We furthermore identified some relevant core genes using gene-gene interaction network analysis such as EIF4E, FAU, HSPD1, IL-6, and KISS1, which may have a relationship with the development process of OS. We also discovered that EIF4E/mTOR signaling pathway could be a potential research target for therapy and tumorigenesis of OS.

CONCLUSION

This analysis provides a comprehensive understanding of the roles of DEGs coming from SP cells in the development of OS. However, these predictions need further experimental validation in future studies.