LINC00174 Facilitates Cell Proliferation, Cell Migration and Tumor Growth of Osteosarcoma via Regulating the TGF-β/SMAD Signaling Pathway and Upregulating SSH2 Expression

Mitophagy-related long non-coding RNA signature predicts prognosis and drug response in Ovarian Cancer

BACKGROUND

Ovarian cancer (OC) is the most malignant tumor with the worst prognosis in female reproductive system. Mitophagy and long non-coding RNAs (lncRNAs) play pivotal roles in tumorigenesis, development, and drug resistance. The effects of mitophagy-related lncRNAs on OC prognosis and therapeutic response remain unelucidated.

METHODS

We retrieved OC-related RNA sequence, copy number variation, somatic mutation, and clinicopathological information from The Cancer Genome Atlas database and mitophagy-related gene sets from the Reactome database. Pearson's correlation analysis was used to distinguish mitophagy-related lncRNAs. A prognostic lncRNA signature was constructed using UniCox, LASSO, and forward stepwise regression analysis. Individuals with a risk score above or below the median were classified as high- or low-risk groups, respectively. The risk model was analyzed using the Kaplan-Meier estimator, receiver operating characteristic curve, decision curve analysis, and Cox regression analysis and validated using an internal dataset. LINC00174 was validated in clinical samples and OC cell lines. We also reviewed reports on the role of LINC00174 in cancer. Subsequently, a nomogram model was constructed. Furthermore, the Genomics of Drug Sensitivity in Cancer database was used to explore the relationship between the risk model and anti-tumor drug sensitivity. Gene set variation analysis was performed to assess potential differences in biological functions between the two groups. Finally, a lncRNA prognostic signature-related competing endogenous RNA (ceRNA) network was constructed.

RESULTS

The prognostic signature showed that patients in the high-risk group had a poorer prognosis. The nomogram exhibited satisfactory accuracy and predictive potential. LINC00174 mainly acts as an oncogene in cancer and is upregulated in OC; its knockdown inhibited the proliferation and migration, and promoted apoptosis of OC cells. High-risk patients were more insensitive to cisplatin and olaparib than low-risk patients. The ceRNA network may help explore the potential regulatory mechanisms of lncRNAs.

CONCLUSION

The mitophagy-related lncRNA signature can help estimate the survival and drug sensitivity, the ceRNA network may provide novel therapeutic targets for patients with OC.

LINC00174 Promotes Colon Cancer Progression by Regulating Inflammation and Glycolysis by Targeting the MicroRNA-2467-3p/Enolase 3 Axis

Objective

To elucidate the mechanism by which LINC00174 promotes colon cancer progression by targeting the microRNA-2467-3p (miR-2467-3p)/enolase 3 (ENO3) axis to regulate inflammation and glycolysis.

Methods

The expression of LINC00174 and ENO3 in colon cancer tissues, its relationship with survival rate, and correlation were analyzed using bioinformatic analysis. The effects of LINC00174 overexpression and silencing on the biological behavior of and inflammation in colon cancer cells were analyzed via transfection experiments. The target relationships between miR-2467-3p or LINC00174 and ENO3 were verified using sequence prediction and the dual-luciferase reporter assay, respectively. Furthermore, LINC00174- and/or miR-2467-3p-overexpressing cells were prepared to determine the effects on ENO3 protein levels and glycolysis. Finally, the effects of LINC00174 and/or miR-2467-3p overexpression on colon cancer, ENO3 protein levels, and inflammation were analyzed using a tumor-bearing mice model.

Results

LINC00174 and ENO3 were overexpressed and associated with a lower survival rate. LINC00174 was positively correlated with ENO3 in colon cancer tissues. Furthermore, the overexpression of LINC00174 in colon cancer cell lines promoted the proliferation, migration, and invasion of colon cancer cells and inflammation but inhibited apoptosis. The overexpression of miR-2467-3p inhibited ENO3 protein levels, which was attenuated via LINC00174 overexpression. Furthermore, it inhibited the biological behavior of and inflammation and glycolysis in colon cancer cells and blocked their LINC00174-induced promotion. Moreover, using animal experiments, the regulatory effects of LINC00174 on tumor growth, ENO3 protein levels, and inflammation via miR-2467-3p were confirmed.

Conclusion

LINC00174 promotes the glycolysis, inflammation, proliferation, migration, and invasion of colon cancer cells and inhibits apoptosis. The cancer-promoting mechanism of LINC00174 is related to targeting miR-2467-3p to promote ENO3 protein levels.

Roles of TGF‑β signalling pathway‑related lncRNAs in cancer (Review)

Long non-coding RNAs (lncRNAs) are a class of RNAs that are >200 nucleotides in length that do not have the ability to be translated into protein but are associated with numerous diseases, including cancer. The involvement of lncRNAs in the signalling of certain signalling pathways can promote tumour progression; these pathways include the transforming growth factor (TGF)-β signalling pathway, which is related to tumour development. The expression of lncRNAs in various tumour tissues is specific, and their interaction with the TGF-β signalling pathway indicates that they may serve as new tumour markers and therapeutic targets. The present review summarized the role of TGF-β pathway-associated lncRNAs in regulating tumorigenesis in different types of cancer and their effects on the TGF-β signalling pathway.

GWAS on Imputed Whole-Genome Sequence Variants Reveal Genes Associated with Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss)

Genome-wide association studies (GWAS) allow the identification of associations between genetic variants and important phenotypes in domestic animals, including disease-resistance traits. Whole Genome Sequencing (WGS) data can help increase the resolution and statistical power of association mapping. Here, we conduced GWAS to asses he facultative intracellular bacterium Piscirickettsia salmonis, which affects farmed rainbow trout, Oncorhynchus mykiss, in Chile using imputed genotypes at the sequence level and searched for candidate genes located in genomic regions associated with the trait. A total of 2130 rainbow trout were intraperitoneally challenged with P. salmonis under controlled conditions and genotyped using a 57K single nucleotide polymorphism (SNP) panel. Genotype imputation was performed in all the genotyped animals using WGS data from 102 individuals. A total of 488,979 imputed WGS variants were available in the 2130 individuals after quality control. GWAS revealed genome-wide significant quantitative trait loci (QTL) in Omy02, Omy03, Omy25, Omy26 and Omy27 for time to death and in Omy26 for binary survival. Twenty-four (24) candidate genes associated with P. salmonis resistance were identified, which were mainly related to phagocytosis, innate immune response, inflammation, oxidative response, lipid metabolism and apoptotic process. Our results provide further knowledge on the genetic variants and genes associated with resistance to intracellular bacterial infection in rainbow trout.

Hypermethylated PODN represses the progression of osteosarcoma by inactivating the TGF-β/Smad2/3 pathway

BACKGROUND

PODN is reported to be an promising biomarker for prognosis of osteosarcoma (OS), while the specific function of PODN has not been explored in OS. This study is designed to explore the function and underlying mechanism of PODN in OS.

METHODS

The mRNA expression of PODN was determined using qRT-PCR. Protein levels of PODN, DNMT1, DNMT3A, DNMT3B, TGF-β1, Smad2/3 and p-Smad2/3 were detected using western blot. The methylation of PODN was determined with methylation-specific PCR. Moreover, CCK-8 assay and colony formation assay were used for assessing the proliferation of OS cells. Transwell assay was used to evaluate migration and invasion abilities of OS cells. Immunohistochemical staining was performed to determine the protein expression of Ki67 and PODN in tumor tissues. For constructing a xenograft tumor model, MG-63 cells were introduced into the right side of the mouse back via subcutaneous injection.

RESULTS

PODN was lowly expressed and was hypermethylated in OS tissues and cells. PODN overexpression prevented OS cells from proliferating, migrating and invading, and inhibited tumorigenesis in xenograft mice. After PODN overexpression, protein levels of TGF-β1 and p-Smad2/3 were decreased in OS cells. Meantime, the suppressive effects of PODN overexpression on proliferation, migration and invasion of OS cells as well as mouse tumorigenesis were partly counteracted by TGF-β1 overexpression.

CONCLUSIONS

PODN overexpression inactivated the TGF-β/Smad2/3 pathway to suppress OS development in vitro and in vivo.

circ-RANGAP1/MicroRNA-542-3p/Myosin Regulatory Light Chain Interacting Protein Axis Modulates the Osteosarcoma Cell Progression

Objective

This study is aimed at exploring the influence of circular RNA- (circRNA-) RANGAP1 targeting microRNA- (miR-) 542-3p/myosin regulatory light chain interacting protein (MYLIP) on the biological function of osteosarcoma (OS) cells.

Methods

Tumor tissues and normal tissues were collected from OS patients and circ-RANGAP1, miR-542-3p, and MYLIP expression was tested by RT-qPCR. The correlation between the clinicopathology/prognosis of patients with OS and circ-RANGAP1 expression was observed. Human OS cell line MG-63 was screened to determine the influences of circ-RANGAP1 and miR-542-3p on OS cell progression. The targeting relation of circ-RANGAP1, miR-542-3p, and MYLIP was probed.

Results

circ-RANGAP1 expression was elevated in tumor tissues from OS patients, which was correlated to the poor clinicopathology. circ-RANGAP1 expression was augmented in males or patients younger than 20 years old or patients with advanced OS. Higher circ-RANGAP1 expression indicated a poor prognosis in OS patients. After silencing circ-RANGAP1 or elevating miR-542-3p in MG63 cells, cell progression was limited. miR-542-3p downregulation reduced the therapeutic efficacy of silenced circ-RANGAP1. circ-RANGAP1 bound with miR-542-3p to target MYLIP.

Conclusion

Silenced circ-RANGAP1 boosts MYLIP expression via competitive binding of miR-542-3p to facilitate OS cell progression.

Long non-coding RNAs and cancer mechanisms: Immune cells and inflammatory cytokines in the tumor microenvironment

Chronic inflammation and immune response are two central hallmarks of the tumor microenvironment (TME), teeming with immune cells and inflammatory cytokines that promote tumor progression. Intriguingly, there is mutual regulation between immune cells and cytokines. Indeed, the differentiation and function of immune cells depend on cytokines secreted from tumor cells, whereas immune activation affects the dynamics of cytokines, reshaping the TME together. Long non-coding RNAs (lncRNAs) as a blooming molecule are virtually involved in physiology and pathology events, especially TME. Notably, the regulatory loop between lncRNAs and cytokines or immune activation plays a vital role in tumor growth. Thus, this review concentrates on the interaction between lncRNAs and immune cells. It puts special attention to the intertwist between lncRNAs and cytokines or immune cells, providing a theoretical basis for lncRNAs as a potential biomarker and therapeutic tumor target.

Identification of N6-methylandenosine related LncRNAs biomarkers associated with the overall survival of osteosarcoma

PURPOSE

Osteosarcoma (OS) is a differentiation disease caused by the genetic and epigenetic differentiation of mesenchymal stem cells into osteoblasts. OS is a common, highly malignant tumor in children and adolescents. Fifteen to 20 % of the patients find distant metastases at their first visit. The purpose of our study was to identify biomarkers for tracking the prognosis and treatment of OS to improve the survival rate of patients.

MATERIALS AND METHODS

In this study, which was based on Therapeutically Applicable Research to Generate Effective Treatments (TARGET), we searched for m6A related lncRNAs in OS. We constructed a network between lncRNA and m6A, and built an OS prognostic risk model.

RESULTS

We identified 14,581 lncRNAs by using the dataset from TARGET. We obtained 111 m6A-related lncRNAs through a Pearson correlation analysis. A network was built between lncRNA and m6A genes. Eight m6A-related lncRNAs associated with survival were identified through a univariate Cox analysis. A selection operator (LASSO) Cox regression was used to construct a prognostic risk model with six genes (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) obtained through least absolute shrinkage. We also discovered upregulated levels of DLGAP1-AS2 and m6A methylation in osteosarcoma tissues/cells compared with normal tissues/osteoblasts cells.

CONCLUSION

We constructed a risk score prognosis model of m6A-related lncRNAs (RP11-286E11.1, LINC01426, AC010127.3, DLGAP1-AS2, RP4-657D16.3, AC002398.11) using the dataset downloaded from TRAGET. We verified the value of the model by dividing all samples into test groups and training groups. However, the role of m6A-related lncRNAs in osteosarcoma needs to be further researched by cell and in vivo studies.