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1.
J Cancer ; 13(9): 2872-2883, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35912012

RESUMEN

Purpose: Liver kinase B1 (LKB1), also known as serine/threonine kinase 11, was considered as a tumor suppressor, which exhibited anti-cancer activity in a variety of cancers. However, the effect of LKB1 in thyroid cancer remains unclear. Methods: In the study, MTT assay, colony formation assay, flow cytometry, western blot analysis, wound healing assay, transwell assays, quantitative real-time PCR, HUVEC migration assay, ELISA assay, tube formation assay and nude mice xenograft were used to investigate the anti-cancer capacity of LKB1 in thyroid cancer in vitro and in vivo. Results: In the present study, we found that the expression of LKB1 was lower in thyroid cancer tissues and cell lines, compared with the adjacent normal tissue and thyroid epithelial cell. After construction of stable clone cells with ectopic LKB1 overexpression, the findings revealed that LKB1 overexpression exerted anti-proliferative and pro-apoptotic property in thyroid cancer TPC-1 and BCPAP cells. In addition, LKB1 overexpression could inhibit migration and invasion, downregulate MMP2 and MMP9 expressions, and reverse EMT in thyroid cancer cells. Furthermore, overexpression of LKB1 attenuated HUVEC recruitment, decreased the expression of VEGFA and inhibited the formation of new vessels in thyroid cancer cells. To validate the underlying mechanism of LKB1 in thyroid cancer, the results showed that LKB1 could positively regulate SIK1 in thyroid cancer TPC-1 and BCPAP cells. Additionally, the SIK1 inhibitor HG-9-91-01 could partially abrogate the anti-proliferative and anti-metastatic effect of LKB1, and reverse MET (mesenchymal-to-epithelial transition) mediated by LKB1 overexpression. Ultimately, the results in vivo revealed that LKB1 overexpression exhibited a strong inhibitory effect of tumorigenicity and presented anti-angiogenic characteristic in nude mice xenograft model. Conclusion: the results demonstrated that LKB1 could inhibit proliferation, metastasis phenotype and angiogenesis, and reverse EMT in thyroid cancer in vitro and vivo via the upregulation of SIK1, suggesting that LKB1 could be considered as a potential therapeutic target for the treatment of thyroid cancer.

4.
Neuroinformatics ; 14(3): 339-51, 2016 07.
Artículo en Inglés | MEDLINE | ID: mdl-27075850

RESUMEN

Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.


Asunto(s)
Mapeo Encefálico/métodos , Encéfalo/fisiología , Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética , Procesamiento de Señales Asistido por Computador , Animales , Humanos , Reproducibilidad de los Resultados , Programas Informáticos
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