Long non‑coding RNA‑DUXAP8 regulates TOP2A in the growth and metastasis of osteosarcoma via microRNA‑635

A 5-lncRNA signature predicts clinical prognosis and demonstrates a different mRNA expression in adult soft tissue sarcoma

Background

Adult soft tissue sarcoma (SARC) is a highly aggressive malignancy. A growing number of long non-coding RNAs (lncRNAs) have been linked to malignancies, and many researchers consider lncRNAs potential biomarkers for prognosis. However, there is limited evidence available to determine the role of lncRNAs in the prognosis of SARC. In this study, we collected The Cancer Genome Atlas (TCGA) data to identify prognosis-related lncRNAs for SARC and explore the relationship between lncRNAs and gene expression.

Methods

TCGA datasets, which included 259 samples, served as data sources in this study. Univariable Cox regression analysis, robust analysis, and multivariable Cox regression analysis were used to construct a 5-lncRNA signature Cox regression model. Then, based on the median risk score, high- and low-risk groups were identified. The Kaplan-Meier method was applied to survival analysis in the training set, testing set, complete set, and different pathological type sets. To explore the relationship between lncRNAs and messenger RNAs (mRNAs), differentially expressed mRNAs (DEmRNAs) between the high- and low-risk groups were identified. The function of DEmRNAs was predicted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The relationships between the 5 lncRNAs and DEmRNAs were calculated using the Spearman correlation coefficient. A total of 18 DEmRNAs that showed a strong correlation with risk score (|Spearman's r|>0.6) in leiomyosarcoma (LMS) samples were identified, and a protein-protein interaction (PPI) network was built using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database.

Results

A Cox regression model was built in this study with the risk score= (-0.5698*AC018645.2) + 0.1732*LINC02454 + 0.387*ERICD + 0.6262*DSCR9 + 0.9781*AL031770.1. The study found that this 5-lncRNA signature could predict prognosis well, especially in LMS, a subtype of SARC, with P value =1.19e-06 [hazard ratio (HR) 6.134, 95% confidence interval (CI): 2.951-12.752]. Additionally, 44 DEmRNAs were observed between the high- and low-risk groups, and the expression levels of DEmRNAs in LMS samples differed from other pathology types. The PPI network analysis revealed that MYH11, MYLK, and CNN1 were the most important hub genes among the 18 DEmRNAs, all of which are essential for muscle function.

Conclusions

In this study, a predictive clinical model for SARC was successfully established, showing better prediction accuracy in patients with LMS. Importantly, we identified MYH11, MYLK, and CNN1 as potential therapeutic targets for SARC.

Osteosarcoma in a ceRNET perspective

Osteosarcoma (OS) is the most prevalent and fatal type of bone tumor. It is characterized by great heterogeneity of genomic aberrations, mutated genes, and cell types contribution, making therapy and patients management particularly challenging. A unifying picture of molecular mechanisms underlying the disease could help to transform those challenges into opportunities.This review deeply explores the occurrence in OS of large-scale RNA regulatory networks, denominated "competing endogenous RNA network" (ceRNET), wherein different RNA biotypes, such as long non-coding RNAs, circular RNAs and mRNAs can functionally interact each other by competitively binding to shared microRNAs. Here, we discuss how the unbalancing of any network component can derail the entire circuit, driving OS onset and progression by impacting on cell proliferation, migration, invasion, tumor growth and metastasis, and even chemotherapeutic resistance, as distilled from many studies. Intriguingly, the aberrant expression of the networks components in OS cells can be triggered also by the surroundings, through cytokines and vesicles, with their bioactive cargo of proteins and non-coding RNAs, highlighting the relevance of tumor microenvironment. A comprehensive picture of RNA regulatory networks underlying OS could pave the way for the development of innovative RNA-targeted and RNA-based therapies and new diagnostic tools, also in the perspective of precision oncology.

A novel ferroptosis-related microRNA signature with prognostic value in osteosarcoma

The induction of ferroptosis is suggested to be a potential therapeutic strategy for cancers. MicroRNAs (miRNAs) are reported to play an important role in cell death processes. This study aims to construct and validate a risk model based on ferroptosis-related miRNAs (FR_miRNAs) to predict prognosis and identify novel therapeutic targets for osteosarcoma. Data from the Therapeutically Applicable Research to Generate Effective Treatments database are used as the training cohort. A prognostic signature based on two FR_miRNAs (miR-635 and miR-593) is developed using univariate Cox regression, least absolute shrinkage and selection operator regression, and multivariate Cox regression analyses. The area under the curve values of the prognostic signature to predict the 1-year, 2-year, 3-year, and 5-year overall survival rates in patients with osteosarcoma are 0.782, 0.781, 0.722, and 0.777, respectively, indicating a good predictive ability. Based on the risk score, patients are divided into low-risk and high-risk groups. Patients with high-risk scores are associated with poor survival. The risk level is determined to be an independent prognostic factor. A nomogram is established for predicting prognosis. The expression levels of PRNP (miR-635-related ferroptosis-related gene (FRG); P=0.024) and HILPDA (miR-593-related FRG; P=0.025) are significantly different between the low-risk and high-risk groups. All results are validated in an external cohort (GSE39040). The results of the functional assay reveal that miR-635 mimics inhibit osteosarcoma (OS) cell proliferation and migration, whereas miR-593 overexpression exerts the opposite effect. In conclusion, miR-635 and miR-593 exert contrasting regulatory effects on OS cell proliferation and migration.

Exploration of s new biomarker in osteosarcoma and association with clinical outcomes: TOP2A+ cancer associated fibroblasts

BACKGROUND

Osteosarcoma (OS) is the leading malignant primary bone tumor in young adults and children and has a high mortality rate. Cancer-associated fibroblasts (CAFs) are major components of the tumor microenvironment, influencing cancer progression and metastasis. However, there is no systematic study on the role of CAF in OS.

METHODS

We collected six OS patients' single-cell RNA sequencing data from the TISCH database, which was processed using the Seurat package. We selected gene sets from the well-known MSigDB database and resorted to the clusterprofiler package for gene set enrichment analysis (GSEA). The least absolute shrinkage and selection operator (LASSO) regression model was used for identification of the variables. Receiver operating characteristic and decision curve analyses were utilized for determining the efficacy of the monogram model.

RESULTS

TOP2A+ CAFs was recognized as the carcinogenic CAFs subset, given its intense interaction with OS malignant cells and association with the critical cancer driver pathway. We intersected the differentially expressed genes of TOP2A+ CAFs with the prognostic genes selected from 88 OS samples. The acquired gene set was selected using the LASSO regression model and integrated with clinical factors to obtain a monogram model of high prognosis predicting power (area under the curve of 5 year survival at 0.883). Functional enrichment analysis revealed the detailed difference between two risk groups.

CONCLUSION

We identified TOP2A+ CAFs as a subset of oncogenic CAFs in OS. Based on differentially expressed genes derived from TOP2A+ CAFs, combined with bulk transcriptome prognostic genes, we constructed a risk model that can efficiently predict OS prognosis. Collectively, our study may provide new insights for future studies to elucidate the role of CAF in OS.

Targeting long non-coding RNA MALAT1 reverses cancerous phenotypes of breast cancer cells through microRNA-561-3p/TOP2A axis

Non-coding RNAs, including Inc-RNA and miRNA, have been reported to regulate gene expression and are associated with cancer progression. MicroRNA-561-3p (miR-561-3p), as a tumor suppressor, has been reported to play a role in preventing cancer cell progression, and MALAT1 (Lnc-RNA) have also been demonstrated to promote malignancy in various cancers, such as breast cancer (BC). In this study, we aimed to determine the correlation between miR-561-3p and MALAT1 and their roles in breast cancer progression. The expression of MALAT1, mir-561-3p, and topoisomerase alpha 2 (TOP2A) as a target of miR-561-3p was determined in BC clinical samples and cell lines via qRT-PCR. The binding site between MALAT1, miR-561-3p, and TOP2A was investigated by performing the dual luciferase reporter assay. MALAT1 was knocked down by siRNA, and cell proliferation, apoptotic assays, and cell cycle arrest were evaluated. MALAT1 and TOP2A were significantly upregulated, while mir-561-3p expression was downregulated in BC samples and cell lines. MALAT1 knockdown significantly increased miR-561-3p expression, which was meaningfully inverted by co-transfection with the miR 561-3p inhibitor. Furthermore, the knockdown of MALAT1 by siRNA inhibited proliferation, induced apoptosis, and arrested the cell cycle at the G1 phase in BC cells. Notably, the mechanistic investigation revealed that MALAT1 predominantly acted as a competing endogenous RNA in BC by regulating the miR-561-3p/TOP2A axis. Based on our results, MALAT1 upregulation in BC may function as a tumor promoter in BC via directly sponging miRNA 561-3p, and MALAT1 knockdown serves a vital antitumor role in BC cell progression through the miR-561-3p/TOP2A axis.

Non-coding RNAs as potential biomarkers in osteosarcoma

Osteosarcoma (OS) is a primary solid malignant tumor that occurs most frequently in the metaphysis of long bones. More likely to happen to children and adolescents. OS has high mortality and disability rate. However, the etiology and pathogenesis of OS have not been fully understood till now. Due to the lack of effective biomarkers, OS cannot be precisely detected in the early stage. With the application of next-generation and high-throughput sequencing, more and more abnormally expressed non-coding RNAs(ncRNAs) have been identified in OS. Growing evidences have suggested the ncRNAs, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), have played an important role in the tumorigenesis and progression of OS. Thus, they can be served as novel biomarkers for diagnosis, treatment and prognosis. This review summarized the application of ncRNA as biomarkers in OS in detail, and discussed the limitation and future improvement of the potential biomarkers.

LncRNA DUXAP8 as a prognostic biomarker for various cancers: A meta-analysis and bioinformatics analysis

Background: Dual homeoboxes A pseudogene 8 (DUXAP8) is a newly discovered long noncoding RNA that has been shown to function as an oncogene in a variety of human malignant cancers. By integrating available data, this meta-analysis sought to determine the relationship between clinical prognosis and DUXAP8 expression levels in diverse malignancies.

Materials and methods: A systematic search was performed to identify eligible studies from several electronic databases from their inception to 25 October 2021. Pooled odds ratios and hazard ratios with 95% CI were used to estimate the association between DUXAP8 expression and survival. For survival analysis, the Kaplan-Meier method and COX analysis were used. Furthermore, we utilized Spearman’s correlation analysis to explore the correlation between DUXAP8 and tumor mutational burden (TMB), microsatellite instability (MSI), the related genes of mismatch repair (MMR), DNA methyltransferases (DNMTs), and immune checkpoint biomarkers.

Results: Our findings indicated that overexpression of DUXAP8 was related to poor overall survival (OS) (HR = 1.63, 95% CI, 1.49–1.77, p < 0.001). In addition, elevated DUXAP8 expression was closely related to poor OS in several cancers in the TCGA database. Moreover, DUXAP8 expression has been associated with TMB, MSI, and MMR in a variety of malignancies.

Conclusion: This study revealed that DUXAP8 might serve as a prognostic biomarker and potential therapeutic target for cancer. It can be used to improve cancer diagnosis, discover potential treatment targets, and improve prognosis.

Functions of lncRNA DUXAP8 in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) poses a serious threat to public health due to its significant morbidity and mortality rates. The processes of NSCLC formation and development are quite complex and involve numerous regulatory biomolecules. Long non-coding RNAs (lncRNAs) have attracted attention since they have been found to play critical roles in the tumorigenesis of various human malignancies. Recently, double homeobox A pseudogene 8 (DUXAP8) was identified as an oncogenic lncRNA that is overexpressed in different tumor types. In NSCLC, high expression of DUXAP8 is associated with poor prognosis in patients. The regulatory mechanism underlying the oncogenic effects of DUXAP8 can be divided into transcriptional level and post-transcriptional level. DUXAP8 promotes proliferation, epithelial-mesenchymal transition, and aerobic glycolysis in NSCLC cells. Moreover, DUXAP8 shows potential for the diagnosis and treatment of NSCLC. Herein, we review the molecular mechanisms underlying the DUXAP8-mediated phenotypes of NSCLC as well as its potential clinical applications.

Role and Mechanism of circ_0058063/miR-635 Axis in the Malignant Phenotype of Multiple Myeloma RPMI8226 Cells

OBJECTIVE

This study aims to explore circ_0058063 effect on multiple myeloma cells malignant phenotype and its feasible mechanism.

METHODS

We selected 47 cases of multiple myeloma tissues and 47 cases of normal bone marrow tissues and then used RT-qPCR method to test circ_0058063 and miR-635 expression in the tissues. Myeloma cells RPMI8226 were transfected with si-circ_0058063, miR-635 mimic, and si-circ_0058063 + anti-miR-635, respectively. Then, we adopt CCK-8 method, flow cytometry method, and Transwell and western blot methods to detect the influences of knockdown of circ_0058063 or miR-635 overexpression on RPMI8226 cell proliferation, apoptosis, migration, and invasion and also Ki-67, Bax, Bcl-2, MMP-2, and MMP-9 protein expression. The dual luciferase reporter gene assay experiment proved that it has regulatory relationship between circ_0058063 and miR-635.

RESULTS

circ_0058063 expression of multiple myeloma was higher than that in normal bone marrow tissue (P < 0.05), while miR-635 expression was lower than that in normal bone marrow tissue (P < 0.05). Knockdown of circ_0058063 or overexpression of miR-635 could reduce proliferation capacity, migration, invasion cell quantities, and Ki-67, MMP-2, MMP-9, and Bcl-2 protein expression (P < 0.05), while increasing apoptosis rate together with Bax protein expression (P < 0.05). circ_0058063 targets to negatively regulate miR-635, while knocking down miR-635 reverses the influences of knocking down circ_0058063 on RPMI8226 proliferation, apoptosis, migration, and invasion.

CONCLUSION

circ_0058063 expression increased in multiple myeloma tissues. Knocking down its expression may inhibit myeloma proliferation, migration, and invasion by targeting and upregulating miR-635 and also promote cell apoptosis. As for multiple myeloma treatment, circ_0058063/miR-635 may provide new molecular targets.