Long noncoding RNAs (lncRNAs) play a critical role in the initiation and progression of colorectal cancer (CRC), but little is known about the function of lncRNAs in the colorectal liver metastasis (CLM). This study was designed to identify specific lncRNAs correlating to liver metastasis of CRC, and to further assess their clinical value.Seventeen patients with primary CRC lesions, adjacent normal mucosa, and synchronous liver metastases lesions were divided into discovery set (six patients) and test set (11 patients). Transcriptome sequencing (RNAseq) was used to screen differential expression of lncRNAs in the discovery set. Based on bioinformatics data, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was used to verify the target lncRNA in test set. The relationships between target lncRNA and clinical values were analysed in an expanded validation set of additional 91 patients. 23 upregulated and 14 downregulated lncRNAs were detected for distinguishing synchronous liver metastases, primary CRC lesions from adjacent normal mucosa in the RNAseq set. The expression levels of four lncRNAs in the 37 lncRNA signature were verified by qRT-PCR in the test set. Compared with the paired normal mucosa, high expression levels of lnc-small-nucleolar RNA host gene 15 (SNHG15) were detected not only in primary CRC lesions but also in liver metastases lesions in the test set.Furthermore, in the expanded validation set, high expression of lnc-SNHG15 was significantly associated with lymph-node metastasis and liver metastasis (p < 0.05), and patients displaying high lncRNA-SNHG15 expression exhibited a shorter median overall survival duration than those displaying low expression (30.7 vs. 35.2 months; p = 0.003).Multivariate analyses demonstrated that lncRNA-SNHG15 overexpression may serve as a poor prognostic biomarker for CRC patients (p = 0.049; Cox's regression: 2.731). Lnc-SNHG15 overexpression was significantly associated with CLM and high-expression of lnc-SNHG15 in CRC was an independent predictor of poor survival. K E Y W O R D S colorectal liver metastasis, lncRNA-SHNG15, long noncoding RNA J Cell Physiol. 2019;234:7032-7039. wileyonlinelibrary.com/journal/jcp 7032 |
The chemoresistance of 5-fluorouracil (5-FU) limited the application of chemotherapy in colorectal cancer (CRC) treatment. Herein, we aimed to uncover the potential mechanism behind the 5-FU resistance of CRC cells. Methods: The abundance of long noncoding RNA urothelial carcinoma associated 1 (lncRNA UCA1), microRNA-23b-3p (miR-23b-3p) and zinc finger protein 281 (ZNF281) was measured by quantitative real-time polymerase chain reaction (qRT-PCR) in CRC tissues and cells. Western blot was conducted to examine autophagy-related proteins, apoptosisassociated proteins and ZNF281 in CRC tissues and cells. Cell counting kit-8 (CCK8) assay was performed to detect the viability and inhibitory concentration 50% (IC50) value of 5-FU of CRC cells. The apoptosis of CRC cells was measured by flow cytometry. The binding sites between miR-23b-3p and UCA1 or ZNF281 were predicted by miRcode and Starbase software, respectively, and the combination was confirmed by dual-luciferase reporter assay and RIP assay. Murine xenograft model was established to verify the role of UCA1 on the 5-FU resistance of CRC in vivo. Results: The 5-FU resistance of CRC was positively related to the level of UCA1 and autophagy. UCA1 accelerated the 5-FU resistance of CRC cells through facilitating autophagy and suppressing apoptosis. MiR-23b-3p was a target of UCA1 in 293T and CRC cells. The knockdown of miR-23b-3p reversed the inhibitory effects of UCA1 interference on the 5-FU resistance and autophagy and the promoting impact on the apoptosis of CRC cells. ZNF281 could bind to miR-23b-3p in 293T cells. MiR-23b-3p elevated the 5-FU sensitivity through down-regulating ZNF281 in CRC cells. UCA1 interference enhanced the 5-FU sensitivity of CRC through miR-23b-3p/ZNF281 axis in vivo. Conclusion: UCA1 mediated 5-FU resistance of CRC cells through facilitating autophagy and inhibiting apoptosis via miR-23b-3p/ZNF281 axis in vivo and in vitro.
Multiplicative noise, also known as speckle noise, is signal dependent and difficult to remove. Based on a fourth-order PDE model, this paper proposes a novel approach to remove the multiplicative noise on images. In practice, Fourier transform and logarithm strategy are utilized on the noisy image to convert the convolutional noise into additive noise, so that the noise can be removed by using the traditional additive noise removal algorithm in frequency domain. For noise removal, a new fourth-order PDE model is developed, which avoids the blocky effects produced by second-order PDE model and attains better edge-preserve ability. The performance of the proposed method has been evaluated on the images with both additive and multiplicative noise. Compared with some traditional methods, experimental results show that the proposed method obtains superior performance on different PSNR values and visual quality.
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