RESUMEN
Cervical cancer (CC) remains one of the leading malignancies afflicting females worldwide, with its aetiology associated with long-term papillomavirus infection. Recent studies have shifted their focus and research attention to the relationship between long non-coding RNAs (lncRNAs) and CC therapeutic. Thus, the aim of the current study was to investigate the underlying mechanism of lncRNA LINC01305 on the cell invasion, migration and epithelial-mesenchymal transition (EMT) of CC cells via modulation of the PI3K/Akt signalling pathway by targeting tenascin-X B (TNXB). The expressions of LINC01305, TNXB, MMP2, MMP9, E-cadherin, vimentin, PI3K, Akt, p-PI3K, p-Akt and TNXB were detected in this study. After which, the cell invasion and migration abilities of the CC cells were determined respectively. Bioinformatics and the application of a dual luciferase reporter gene assay provided verification indicating that TNXB is the target gene of lncRNA LINC01305. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blot analysis methods revealed that the expressions of MMP2, MMP9, vimentin, PI3K, Akt, p-PI3K and p-Akt were decreased following the down-regulation of LncRNA LINC01305 or overexpression of TNXB. LncRNA LINC01305 silencing or TNXB overexpression was noted to decrease the migration and invasion of SiHa cells. Taken together, the key findings of the current study present evidence suggesting that lncRNA LINC01305 silencing suppresses EMT, invasion and migration via repressing the PI3K/Akt signalling pathway by means of targeting TNXB in CC cells, which ultimately provides novel insight and identification of potential therapeutic targets for CC.
Asunto(s)
Transición Epitelial-Mesenquimal/genética , Regulación Neoplásica de la Expresión Génica , Fosfatidilinositol 3-Quinasas/genética , Proteínas Proto-Oncogénicas c-akt/genética , ARN Largo no Codificante/genética , Tenascina/genética , Antígenos CD/genética , Antígenos CD/metabolismo , Apoptosis/genética , Cadherinas/genética , Cadherinas/metabolismo , Línea Celular Tumoral , Movimiento Celular , Proliferación Celular , Biología Computacional/métodos , Femenino , Células HeLa , Humanos , Metaloproteinasa 2 de la Matriz/genética , Metaloproteinasa 2 de la Matriz/metabolismo , Metaloproteinasa 9 de la Matriz/genética , Metaloproteinasa 9 de la Matriz/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , ARN Largo no Codificante/antagonistas & inhibidores , ARN Largo no Codificante/metabolismo , ARN Interferente Pequeño/genética , ARN Interferente Pequeño/metabolismo , Transducción de Señal , Tenascina/metabolismo , Neoplasias del Cuello Uterino/genética , Neoplasias del Cuello Uterino/metabolismo , Neoplasias del Cuello Uterino/patología , Vimentina/genética , Vimentina/metabolismoRESUMEN
AIMS: To enhance ovarian tumor diagnosis beyond conventional methods, this study explored combining diffusion-weighted magnetic resonance imaging (DWI-MRI) and serum biomarkers (Mucin 1 [MUC1], MUC13, and MUC16) for distinguishing borderline from malignant epithelial ovarian tumors. METHODS: A total of 126 patients, including 71 diagnosed with borderline (BEOTs) and 55 with malignant epithelial ovarian tumors (MEOTs), underwent preoperative DWI-MRI. Region of interest (ROI) was manually drawn along the solid component's boundary of the largest tumor, focusing on areas with potentially the lowest apparent diffusion coefficient (ADC). For entirely cystic tumors, a free-form ROI enclosed the maximum number of septa while targeting the lowest ADC. Serum biomarkers were determined using enzyme-linked immunosorbent assay. RESULTS: Basic morphological traits proved inadequate for malignancy diagnosis, warranting this investigation. BEOTs had an ADC mean of (1.670 ± 0.250) × 103 mm2 /s, while MEOTs had a lower ADC mean of (1.332 ± 0.481) × 103 mm2 /s, with a sensitivity of 63.6% and specificity of 90.1%. Median MUC1 (167.0 U/mL vs. 87.3 U/mL), MUC13 (12.44 ng/mL vs. 7.77 ng/mL), and MUC16 (180.6 U/mL vs. 36.1 U/mL) levels were higher in MEOTs patients. The biomarker performance was: MUC1, sensitivity 50.9%, specificity 100%; MUC13, sensitivity 56.4%, specificity 78.9%; MUC16, sensitivity 83.64%, specificity 100%. Combining serum biomarkers and ADC mean resulted in a sensitivity of 96.4% and specificity of 100%. CONCLUSION: The integration of DWI-MRI with serum biomarkers (MUC1, MUC13, and MUC16) achieves exceptional diagnostic accuracy, offering a powerful tool for the precise differentiation between borderline and malignant epithelial ovarian tumors.