Long non-coding RNA NEAT1 facilitates the growth, migration, and invasion of ovarian cancer cells via the let-7 g/MEST/ATGL axis

Molecular Mechanisms of Tumorgenesis and Metastasis of Long Non-coding RNA (lncRNA) NEAT1 in Human Solid Tumors; An Update

The expression of the nuclear paraspeckle assembly transcript 1 (NEAT1), as a well-known long non-coding RNA (lncRNA), is often upregulated in varied types of cancers and associated with poor survival outcomes in patients suffering from tumors. NEAT1 promotes the tumors growth by influencing the various genes' expression profile that regulate various aspects of tumor cell behavior, in particular tumor growth, metastasis and drug resistance. This suggests that NEAT1 are capable of serving as a new diagnostic biomarker and target for therapeutic intervention. Through interrelation with enhancer of zeste homolog 2 (EZH2), NEAT1 acts as a scaffold RNA molecule, and thus regulating the expression EZH2-associated genes. Additionally, by perform as miRNA sponge, it constrains suppressing the interactions between miRNAs-mediated degradation of target mRNAs. In light of this, NEAT1 inhibition by small interfering RNA (siRNA) hampers tumorgenesis. We summarize recent findings about the expression, biological functions, and regulatory process of NEAT1 in human tumors. It specifically emphasizes the clinical significance of NEAT1 as a novel diagnostic biomarker and a promising therapeutic mark for many types of cancers.

Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning

Background

Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques generate extensive gene expression data, yet only a few of these genes are relevant to clinical diagnosis.

Methods

Methods for feature selection (FS) address the challenges of high dimensionality in extensive datasets. This study proposes a computational framework that applies FS techniques to identify genes highly associated with platinum-based chemotherapy response on SOC patients. Using SOC datasets from the Gene Expression Omnibus (GEO) database, LASSO and varSelRF FS methods were employed. Machine learning classification algorithms such as random forest (RF) and support vector machine (SVM) were also used to evaluate the performance of the models.

Results

The proposed framework has identified biomarkers panels with 9 and 10 genes that are highly correlated with platinum-paclitaxel and platinum-only response in SOC patients, respectively. The predictive models have been trained using the identified gene signatures and accuracy of above 90% was achieved.

Conclusions

In this study, we propose that applying multiple feature selection methods not only effectively reduces the number of identified biomarkers, enhancing their biological relevance, but also corroborates the efficacy of drug response prediction models in cancer treatment.

Lipid droplets provide metabolic flexibility for cancer progression

A hallmark of cancer cells is their remarkable ability to efficiently adapt to favorable and hostile environments. Due to a unique metabolic flexibility, tumor cells can grow even in the absence of extracellular nutrients or in stressful scenarios. To achieve this, cancer cells need large amounts of lipids to build membranes, synthesize lipid-derived molecules, and generate metabolic energy in the absence of other nutrients. Tumor cells potentiate strategies to obtain lipids from other cells, metabolic pathways to synthesize new lipids, and mechanisms for efficient storage, mobilization, and utilization of these lipids. Lipid droplets (LDs) are the organelles that collect and supply lipids in eukaryotes and it is increasingly recognized that the accumulation of LDs is a new hallmark of cancer cells. Furthermore, an active role of LD proteins in processes underlying tumorigenesis has been proposed. Here, by focusing on three major classes of LD-resident proteins (perilipins, lipases, and acyl-CoA synthetases), we provide an overview of the contribution of LDs to cancer progression and discuss the role of LD proteins during the proliferation, invasion, metastasis, apoptosis, and stemness of cancer cells.

LncRNAs-circRNAs as Rising Epigenetic Binary Superstars in Regulating Lipid Metabolic Reprogramming of Cancers

As one of novel hallmarks of cancer, lipid metabolic reprogramming has recently been becoming fascinating and widely studied. Lipid metabolic reprogramming in cancer is shown to support carcinogenesis, progression, distal metastasis, and chemotherapy resistance by generating ATP, biosynthesizing macromolecules, and maintaining appropriate redox status. Notably, increasing evidence confirms that lipid metabolic reprogramming is under the control of dysregulated non-coding RNAs in cancer, especially lncRNAs and circRNAs. This review highlights the present research findings on the aberrantly expressed lncRNAs and circRNAs involved in the lipid metabolic reprogramming of cancer. Emphasis is placed on their regulatory targets in lipid metabolic reprogramming and associated mechanisms, including the clinical relevance in cancer through lipid metabolism modulation. Such insights will be pivotal in identifying new theranostic targets and treatment strategies for cancer patients afflicted with lipid metabolic reprogramming.

Exploring the role of lncrna neat1 knockdown in regulating apoptosis across multiple cancer types: A review

Long non-coding RNAs (lncRNAs) have emerged as pivotal regulators of gene expression, contributing significantly to a diverse range of cellular processes, including apoptosis. One such lncRNA is NEAT1, which is elevated in several types of cancer and aid in cancer growth. However, recent studies have also demonstrated that the knockdown of NEAT1 can inhibit cancer cells proliferation, movement, and infiltration while enhancing apoptosis. This article explores the function of lncRNA NEAT1 knockdown in regulating apoptosis across multiple cancer types. We explore the existing understanding of NEAT1's involvement in the progression of malignant conditions, including its structure and functions. Additionally, we investigate the molecular mechanisms by which NEAT1 modulates the cell cycle, cellular proliferation, apoptosis, movement, and infiltration in diverse cancer types, including acute myeloid leukemia, breast cancer, cervical cancer, colorectal cancer, esophageal squamous cell carcinoma, glioma, non-small cell lung cancer, ovarian cancer, prostate cancer, and retinoblastoma. Furthermore, we review the recent studies investigating the therapeutic potential of NEAT1 knockdown in cancer treatment. Targeting the lncRNA NEAT1 presents a promising therapeutic approach for treating cancer. It has shown the ability to suppress cancer cell proliferation, migration, and invasion while promoting apoptosis in various cancer types.

The long non-coding RNA NEAT1 promotes the progression of human ovarian cancer through targeting miR-214-3p and regulating angiogenesis

BACKGROUND

Angiogenesis and metastasis contributes substantially to the poor outcome of patients with ovarian cancer. We aimed to explore the role and mechanisms of the long non-coding RNA NEAT1 (nuclear enriched abundant transcript 1) in regulating angiogenesis and metastasis of human ovarian cancer. NEAT1 expression in human ovarian cancer tissues and cell lines including SKOV-3 and A2780 was investigated through in situ hybridization. Gene knockdown and overexpressing were achieved through lentivirus infection, transfection of plasmids or microRNA mimics. Cell viability was measured with the cell counting kit-8 assay, while apoptosis was determined by flow cytometry. Cell migration and invasion were evaluated by transwell experiments, and protein expression was determined by western blot assays or immunohistochemistry. Duo-luciferase reporter assay was employed to confirm the interaction between NEAT1 and target microRNA. In vivo tumor growth was evaluated in nude mice with xenografted SKOV-3/A2780 cells, and blood vessel formation in tumor was examined by histological staining.

RESULTS

NEAT1 was highly expressed in ovarian cancer tissues of patients and cell lines. MiR-214-3p was identified as a sponging target of NEAT1, and they antagonizedeach other in a reciprocal manner. NEAT1-overexpressing SKOV-3 and A2780 cells had significantly increased proliferation, reduced apoptosis, and augmented abilities of migration and invasion, while cells with NEAT1-knockdown displayed markedly attenuated traits of malignancies. Additionally, the levels of NEAT1 appeared to be positively correlated with the expression levels of angiogenesis-related molecules, including Semaphorin 4D (Sema4D), Sema4D receptor Plexin B1, T-lymphoma invasion and metastasis-inducing protein-1 (Tiam1), and Rho-like GTPases Rac1/2/3. In the xenograft mouse model, more NEAT1 expression resulted in faster in vivo tumor growth, more blood vessel formation in tumor tissues, as well as higher expression levels of angiogenesis-related molecules and CD31.

CONCLUSIONS

NEAT1 promotes angiogenesis and metastasis in human ovarian cancer. NEAT1 and miR-214-3p are promising targets for developing therapeutics to treat human ovarian cancer.

Knockdown of circMFN2 inhibits cell progression and glycolysis by miR-198/CUL4B pathway in ovarian cancer

Circular RNA (circRNA) regulates malignant tumors, including ovarian cancer (OC). The present research study aimed to reveal the biological mechanism of circRNA mitofusin 2 (circMFN2) in OC. Cell biological behaviors were investigated using clonogenicity assay, EdU assay, transwell assay, and flow cytometry analysis. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot analysis were implemented to detect the levels of circMFN2, miR-198, Cullin 4B (CUL4B), and apoptosis-related proteins. Glycolysis was assessed by glucose assay kit, lactate assay kit, and ATP level detection kit. The relationships among miR-198, circMFN2, and CUL4B were verified by dual-luciferase reporter assay and RNA immunoprecipitation assay. The xenograft mice model was used to analyze tumor growth in vivo. The expression of circMFN2 and CUL4B was increased, while miR-330-5p was decreased in OC tissues or cells. The absence of CircMFN2 hindered cell proliferation, migration, invasion, and glycolysis and promoted apoptosis in OC cells. We found that circMFN2 promoted CUL4B expression via sponging miR-198. MiR-198 depletion reversed circMFN2 knockdown-induced effects in OC cells. Furthermore, CUL4B overexpression overturned the inhibitory effect of miR-198 in OC cells. And the absence of circMFN2 inhibited tumor growth in vivo. CircMFN2 repressed OC progression by regulating the miR-198/CUL4B axis.

Extracellular vesicles derived from M2-polarized tumor-associated macrophages promote immune escape in ovarian cancer through NEAT1/miR-101-3p/ZEB1/PD-L1 axis

Evidence has been presented demonstrating that CD8⁺ T cells confer anti-cancer effects, which offers a promising approach to enhance immunotherapy. M2-polarized tumor-associated macrophages (TAMs) could transfer RNA to cancer cells by secreting extracellular vesicles (EVs) and stimulate immune escape of cancer cells. Thus, the current study aimed at exploring how EVs derived from M2-polarized TAMs (M2-TAMs) affected the proliferation of ovarian cancer (OC) cells and apoptosis of CD8⁺ T cells. M2-TAMs were observed in OC tissues, which promoted proliferation of OC cells and CD8⁺ T cell apoptosis by secreting EVs. OC-associated differentially expressed gene NEAT1 was screened by bioinformatics analysis. The in vitro and in vivo effects of TAM-EVs-NEAT1 and its regulatory mechanism were assessed using gain- and loss-of-function assays in co-culture systems of TAMs-derived EVs, OC cells, and CD8⁺ T cells and in tumor-bearing mice. NEAT1 was highly expressed in M2-derived EVs and OC cells co-cultured with M2-derived EVs. NEAT1 sponged miR-101-3p to increase ZEB1 and PD-L1 expression. In vitro and in vivo assays confirmed the tumor-supporting effects of NEAT1 delivered by M2-derived EVs on OC cell proliferation and CD8⁺ T cell apoptosis as well as tumor growth. Collectively, M2-derived EVs containing NEAT1 exerted a tumor-promoting role in OC via the miR-101-3p/ZEB1/PD-L1 axis.

Molecular Interactions of the Long Noncoding RNA NEAT1 in Cancer

As one of the best-studied long noncoding RNAs, nuclear paraspeckle assembly transcript 1 (NEAT1) plays a pivotal role in the progression of cancers. NEAT1, especially its isoform NEAT1-1, facilitates the growth and metastasis of various cancers, excluding acute promyelocytic leukemia. NEAT1 can be elevated via transcriptional activation or stability alteration in cancers changing the aggressive phenotype of cancer cells. NEAT1 can also be secreted from other cells and be delivered to cancer cells through exosomes. Hence, elucidating the molecular interaction of NEAT1 may shed light on the future treatment of cancer. Herein, we review the molecular function of NEAT1 in cancer progression, and explain how NEAT1 interacts with RNAs, proteins, and DNA promoter regions to upregulate tumorigenic factors.

Downregulated Dual-Specificity Protein Phosphatase 1 in Ovarian Carcinoma: A Comprehensive Study With Multiple Methods

Introduction: We aimed to explore the abnormal expression of dual-specificity protein phosphatase 1 (DUSP1) and its latent molecular mechanisms in ovarian carcinoma (OVCA).

Materials and Methods: Two clinical cohorts collected from two different hospitals were used to evaluate the expression of DUSP1 protein in OVCA tissues. RNA-sequencing and microarray datasets were utilised to verify DUSP1 expression at mRNA levels in both OVCA tissues and in the peripheral blood of OVCA patients. Furthermore, an integrated calculation was performed to pool the standard mean difference (SMD) from each cohort in order to comprehensively assess the expression of DUSP1 in OVCA. Furthermore, we examined the relationship among DUSP1, tumour microenvironment (TME), and chemotherapy resistance in OVCA. Moreover, we used pathway enrichment analysis to explore the underlying mechanisms of DUSP1 in OVCA.

Results: A pooled SMD of −1.19 (95% CI [−2.00, −0.38], p = 0.004) with 1,240 samples revealed that DUSP1 was downregulated in OVCA at both mRNA and protein levels. The area under the receiver operating characteristic curve of 0.9235 indicated the downregulated DUSP1 in peripheral blood may have a non-invasive diagnostic value in OVCA. Through six algorithms, we identified that DUSP1 may related to tumour-infiltrating T cells and cancer associated fibroblasts (CAFs) in OVCA. Pathway enrichment demonstrated that DUSP1 might participate in the mitogen-activated protein kinase (MAPK) signalling pathway. Furthermore, DUSP1 may have relations with chemotherapy resistance, and a favourable combining affinity was observed in the paclitaxel-DUSP1 docking model.

Conclusion: DUSP1 was downregulated in OVCA, and this decreasing trend may affect the infiltration of CAFs. Finally, DUSP1 may have a targeting relation with paclitaxel and participate in MAPK signaling pathways.

Recent Advances on the Role of ATGL in Cancer

The hypoxic state of the tumor microenvironment leads to reprogramming lipid metabolism in tumor cells. Adipose triglyceride lipase, also known as patatin-like phospholipase= domain-containing protein 2 and Adipose triglyceride lipase (ATGL), as an essential lipid metabolism-regulating enzyme in cells, is regulated accordingly under hypoxia induction. However, studies revealed that ATGL exhibits both tumor-promoting and tumor-suppressing effects, which depend on the cancer cell type and the site of tumorigenesis. For example, elevated ATGL expression in breast cancer is accompanied by enhanced fatty acid oxidation (FAO), enhancing cancer cells’ metastatic ability. In prostate cancer, on the other hand, tumor activity tends to be negatively correlated with ATGL expression. This review outlined the regulation of ATGL-mediated lipid metabolism pathways in tumor cells, emphasizing the Hypoxia-inducible factors 1 (HIF-1)/Hypoxia-inducible lipid droplet-associated (HIG-2)/ATGL axis, peroxisome proliferator-activated receptor (PPAR)/G0/G1 switch gene 2 (G0S2)/ATGL axis, and fat-specific protein 27 (FSP-27)/Early growth response protein 1 (EGR-1)/ATGL axis. In the light of recent research on different cancer types, the role of ATGL on tumorigenesis, tumor proliferation, and tumor metastasis was systemically reviewed.

Increased co-expression of MEST and BRCA1 is associated with worse prognosis and immune infiltration in ovarian cancer

OBJECTIVE

The crosstalk between tumor microenvironment (TME) and cancer cells plays a critical role in the occurrence and development of ovarian cancer. Imprinted gene MEST is a tumor-promoting factor that modulates several carcinogenic signaling pathways. This study aimed to investigate the expression pattern of MEST and its association with immune cell infiltration.

METHODS

The transcriptome data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database was utilized, and the expression and immune characteristics of MEST were verified by immunohistochemistry of ovarian cancer specimens. Kaplan-Meier Plotter was used to assess the prognostic value in patients with ovarian cancer.

RESULTS

We found that high expression of MEST was associated with diminished immune cell infiltration and worse prognosis of ovarian cancer patients in independent cohorts. There was a positive correlation between MEST and BRCA1 expression. The MEST^highBRCA1^high ovarian cancer group was correlated with lower infiltration of CD4⁺ cells, CD57⁺ cells, CD68⁺ cells and MPO⁺ cells, had worse overall survival (OS) in TCGA (HR = 1.57, p = 0.0004) and GSE27651 (HR = 4.27, p = 0.0002) cohorts, and predicted poor progress free survival (PFS) in GSE9891 (HR = 1.76, p = 0.0098) and GSE15622 (HR = 4.80, p = 0.0121) cohorts. Moreover, the expression of PD-L1 predicted unfavorable OS (HR = 2.48, p = 0.0415) and PFS (HR = 2.36, p = 0.0215) in MEST^lowBRCA1^low ovarian cancer group in GSE9891 cohort.

CONCLUSION

These findings suggest that the co-expression of MEST and BRCA1 may be an ideal combination for predicting the prognosis and response to immunotherapy in patients with ovarian cancer.

SYNCRIP Modulates the Epithelial-Mesenchymal Transition in Hepatocytes and HCC Cells

Heterogeneous nuclear ribonucleoproteins (hnRNPs) control gene expression by acting at multiple levels and are often deregulated in epithelial tumors; however, their roles in the fine regulation of cellular reprogramming, specifically in epithelial–mesenchymal transition (EMT), remain largely unknown. Here, we focused on the hnRNP-Q (also known as SYNCRIP), showing by molecular analysis that in hepatocytes it acts as a “mesenchymal” gene, being induced by TGFβ and modulating the EMT. SYNCRIP silencing limits the induction of the mesenchymal program and maintains the epithelial phenotype. Notably, in HCC invasive cells, SYNCRIP knockdown induces a mesenchymal–epithelial transition (MET), negatively regulating their mesenchymal phenotype and significantly impairing their migratory capacity. In exploring possible molecular mechanisms underlying these observations, we identified a set of miRNAs (i.e., miR-181-a1-3p, miR-181-b1-3p, miR-122-5p, miR-200a-5p, and miR-let7g-5p), previously shown to exert pro- or anti-EMT activities, significantly impacted by SYNCRIP interference during EMT/MET dynamics and gathered insights, suggesting the possible involvement of this RNA binding protein in their transcriptional regulation.

A ferroptosis-related lncRNA signature predicts prognosis in ovarian cancer patients

Background

Ovarian cancer (OC) is a common gynecological malignant tumor with poor prognosis. Ferroptosis is an iron-dependent modality of regulated cell death. The purpose of this study was to determine the prognostic ability of ferroptosis-related long non-coding RNAs (lncRNAs) in OC patients and construct a ferroptosis-related lncRNA prognostic model.

Methods

The Cancer Genome Atlas (TCGA) and FerrDb databases were used to collect RNA sequencing data of OC patients and ferroptosis-related genes, respectively. OC patients were randomly assigned to the training or testing set. Pearson correlation analysis was used to identify ferroptosis-related lncRNAs. Univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate regression analyses were performed in the training set to develop a predictive model. The model was validated in the testing set and entire set. Survival analysis, receiver operating characteristic curves, independent prognostic factor analysis, and correlation analysis with clinical features were performed to evaluate the predictive value of the model. A nomogram was established to predict the survivability of OC patients over 1, 3, and 5 years. The distribution of distinct groups was investigated using principal component analysis, and the underlying the biological functions were explored using gene set enrichment analysis.

Results

Eleven ferroptosis-related lncRNAs were determined to establish the prognostic model. Patients in the high-risk group had poor prognosis compared with the low-risk group in the training, testing and entire sets. The area under the receiver operating characteristic curve corresponding to 1-, 3-, and 5-year survival were 0.731, 0.796, and 0.805 in the training set; 0.704, 0.597, and 0.655 in the testing set; and 0.715, 0.691, and 0.736, in the entire set, respectively. The risk score correlated with age and grade. The risk score was also an independent prognostic factor in OC. A nomogram with high C-index (0.68) was constructed. An intuitive observation of the principal component analysis revealed a distinction between high- and low-risk groups, and gene set enrichment analysis indicated that cancer-related pathways were enriched in the high-risk group.

Conclusions

The signature composed of 11 ferroptosis-related lncRNAs accurately predicted the prognosis of OC patients.