Involvement of NEAT1/miR-133a axis in promoting cervical cancer progression via targeting SOX4.

NEAT1 is an important tumor oncogenic gene in various tumors. Nevertheless, its involvement remains poorly studied in cervical cancer. Our study explored the functional mechanism of NEAT1 in cervical cancer. NEAT1 level in several cervical cancer cells was quantified and we found NEAT1 was greatly upregulated in vitro. NEAT1 knockdown inhibited cervical cancer development through repressing cell proliferation, colony formation, capacity of migration, and invasion and also inducing the apoptosis. For another, microRNA (miR)-133a was downregulated in cervical cancer cells and NEAT1 negatively modulated miR-133a expression. Subsequently, we validated that miR-133a functioned as a potential target of NEAT1. Meanwhile, SOX4 is abnormally expressed in various cancers. SOX4 was able to act as a downstream target of miR-133a and silencing of SOX4 can restrain cervical cancer progression. In addition, in vivo assays were conducted to prove the role of NEAT1/miR-133a/SOX4 axis in cervical cancer. These findings implied that NEAT1 served as a competing endogenous RNA to sponge miR-133a and regulate SOX4 in cervical cancer pathogenesis. To sum up, it was implied that NEAT1/miR-133a/SOX4 axis was involved in cervical cancer development.

Radiomics analysis based on multiparametric magnetic resonance imaging for differentiating early stage of cervical cancer.

Objective: To investigate the performance of multiparametric magnetic resonance imaging (MRI)-based radiomics models in differentiating early stage of cervical cancer (Stage I-IIa vs. IIb-IV). Methods: One hundred patients with cervical cancer who underwent preoperative MRI between June 2020 and March 2022 were retrospectively enrolled. Training (n = 70) and testing cohorts (n = 30) were assigned by stratified random sampling. The clinical and pathological features, including age, histological subtypes, tumor grades, and node status, were compared between the two cohorts by t-test or chi-square test. Radiomics features were extracted from each volume of interest (VOI) on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps. The data balance of the training cohort was resampled by synthesizing minority oversampling techniques. Subsequently, the adiomics signatures were constructed by the least absolute shrinkage and selection operator algorithm and minimum-redundancy maximum-relevance with 10-fold cross-validation. Logistic regression was applied to predict the cervical cancer stages (low [I-IIa]) and (high [IIb-IV] FIGO stages). The receiver operating characteristic curve (area under the curve [AUC]) and decision curve analysis were used to assess the performance of the radiomics model. Results: The characteristics of age, histological subtypes, tumor grades, and node status were not significantly different between the low [I-IIa] and high [IIb-IV] FIGO stages (p > 0.05 for both the training and test cohorts). Three models based on T2WI, ADC maps, and the combined were developed based on six radiomics features from T2WI and three radiomics features from ADC maps, with AUCs of 0.855 (95% confidence interval [CI], 0.777-0.934) and 0.823 (95% CI, 0.727-0.919), 0.861 (95% CI, 0.785-0.936) and 0.81 (95% CI, 0.701-0.918), 0.934 (95% CI, 0.884-0.984) and 0.902 (95% CI, 0.832-0.972) in the training and test cohorts. Conclusion: The radiomics models combined T2W and ADC maps had good predictive performance in differentiating the early stage from locally advanced cervical cancer.

lncRNA SNHG15 Induced by SOX12 Promotes the Tumorigenic Properties and Chemoresistance in Cervical Cancer via the miR-4735-3p/HIF1a Pathway.

Cervical cancer (CC) is one of the most common malignancies in females, with high prevalence and mortality globally. Despite advances in diagnosis and therapeutic strategies developed in recent years, CC is still a major health burden worldwide. The molecular mechanisms underlying the development of CC need to be understood. In this study, we aimed to demonstrate the role of lncRNA SNHG15 in CC progression. Using qRT-PCR, we determined that lncRNA SNHG15 is highly expressed in CC tumor tissues and cells. lncRNA SNHG15 knockdown also reduces the tumorigenic properties of CC in vitro, as determined using the MTT, EdU, flow cytometry, and transwell assays. Using bioinformatics analysis, RNA pull-down, ChIP, and luciferase reporter assays, we verified the molecular mechanisms of lncRNA SNHG15 in CC progression and found that lncRNA SNHG15 expression in CC cells is transcriptionally regulated by SOX12; moreover, lncRNA SNHG15 promotes CC progression via the miR-4735-3p/HIF1a axis. This study can provide a potential target for CC diagnosis or therapeutic strategies in the future.

Long noncoding RNA LINC00657 inhibits cervical cancer development by sponging miR-20a-5p and targeting RUNX3.

Long noncoding RNAs act essential regulators in cervical cancer progression. Our study aimed to investigate the underlying function and molecular mechanisms of LINC00657 in cervical cancer. QRT-PCR results indicated that LINC00657 was significantly decreased in cervical cancer. Gain-and loss-of-function experiments were performed in SiHa and HeLa. Functional assays demonstrated that LINC00657 inhibited cervical cancer cell growth, migration and invasion. Moreover, miR-20a-5p was confirmed as a target of LINC00657. Furthermore, miR-20a-5p promoted the development of cervical cancer via targeting RUNX3. DR5 acts as a vital promoter in activating NK cells and is a downstream target of RUNX3. We found that LINC00657 overexpression promoted the cytotoxic activity of NK cells via regulating RUNX3/DR5 axis. Therefore, LINC00657 suppressed cervical cancer progression via inducing miR-20a-5p/RUNX3/DR5 mediated NK cell tolerance. In conclusion, LINC00657 was identified as a novel tumor-suppressor in cervical cancer and could function as a potential therapeutic target for clinical treatment.

The Long Noncoding RNA MALAT-1 Is Highly Expressed in Ovarian Cancer and Induces Cell Growth and Migration.

BACKGROUND: Metastasis associated in lung adenocarcinoma transcript-1 (MALAT-1) is overexpressed during cancer progression and promotes cell migration and invasion in many solid tumors. However, its role in ovarian cancer remains poorly understood. METHODS: Expressions of MALAT-1 were detected in 37 normal ovarian tissues and 45 ovarian cancer tissues by reverse transcription polymerase chain reaction (RT-PCR). Cell proliferation was observed by CCK-8 assay; Flow cytometry was used to measure cell cycle and apoptosis; Cell migration was detected by transwell migration and invasion assay. In order to evaluate the function of MALAT-1, shRNA combined with DNA microarray and Functional enrichment analysis were performed to determine the transcriptional effects of MALAT-1 silencing in OVCAR3 cells. RNA and protein expression were measured by qRT-PCR and Western blotting, respectively. RESULTS: We found that upregulation of MALAT-1 mRNA in ovarian cancer tissues and enhanced MALAT-1 expression was associated with FIGO stage. Knockdown of MALAT-1 expression in OVCAR3 cells inhibited cell proliferation, migration, and invasion, leading to G0/G1 cell cycle arrest and apoptosis. Overexpressed MALAT-1 expression in SKOV3 cells promoted cell proliferation, migration and invasion. Downregulation of MALAT-1 resulted in significant change of gene expression (at least 2-fold) in 449 genes, which regulate proliferation, cell cycle, and adhesion. As a consequence of MALAT-1 knockdown, MMP13 protein expression decreased, while the expression of MMP19 and ADAMTS1 was increased. CONCLUSIONS: The present study found that MALAT-1 is highly expressed in ovarian tumors. MALAT-1 promotes the growth and migration of ovarian cancer cells, suggesting that MALAT-1 may be an important contributor to ovarian cancer development.