Abstract

Rationale: Twist is a key transcription factor for induction of epithelial-mesenchymal transition (EMT), which promotes cell migration, invasion, and cancer metastasis, confers cancer cells with stem cell-like characteristics, and provides therapeutic resistance. However, the functional roles and targeted genes of Twist in EMT and cancer progression remain elusive.

Methods: The potential targeted genes of Twist were identified from the global transcriptomes of T47D/Twist cells by microarray analysis. EMT phenotype was detected by western blotting and immunofluorescence of marker proteins. The dual-luciferase reporter and chromatin immunoprecipitation assays were employed to observe the direct transcriptional induction of ROR1 by Twist. A lung metastasis model was used to study the pro-metastatic role of Twist and ROR1 by injecting MDA-MB-231 cells into tail vein of nude mice. Bio-informatics analysis was utilized to measure the metastasis-free survival of breast cancer patients.

Results: Twist protein was proved to directly activate the transcription of ROR1 gene, a receptor of Wnt5a in non-canonical WNT signaling pathway. Silencing of ROR1 inhibited EMT process, cell migration, invasion, and cancer metastasis of basal-like breast cancer (BLBC) cells. Knockdown of ROR1 also ameliorated the pro-metastatic effect of Twist. Furthermore, analyses of clinical specimens indicated that high expression of both ROR1 and Twist tightly correlates with poor metastasis-free survival of breast cancer patients.

Conclusion: ROR1 is a targeted gene of Twist. Twist/ROR1 signaling is critical for invasion and metastasis of BLBC cells.

Document Type

Article

Publication Date

4-9-2018

Notes/Citation Information

Published in Theranostics, v. 8, issue 10, p. 2739-2751.

© Ivyspring International Publisher

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.

Digital Object Identifier (DOI)

https://doi.org/10.7150/thno.21477

Funding Information

This work was supported by grants from Science and Technology Program of Guangzhou, China (201508020102) to Tiebang Kang; National Natural Science Foundation of China (81672629), and Science and Technology Program of Guangzhou, China (201707010331) to Jian Shi.

Related Content

Supplementary figures and tables. http://www.thno.org/v08p2739s1.pdf

thnov08p2739s1.pdf (2333 kB)
Supplementary figures and tables.

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