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Usage Information

Myo9b is a key player in SLIT/ROBO-mediated lung tumor suppression
Ruirui Kong, … , Wei Feng, Jane Y. Wu
Ruirui Kong, … , Wei Feng, Jane Y. Wu
Published November 3, 2015
Citation Information: J Clin Invest. 2015;125(12):4407-4420. https://doi.org/10.1172/JCI81673.
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Research Article Oncology

Myo9b is a key player in SLIT/ROBO-mediated lung tumor suppression

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Abstract

Emerging evidence indicates that the neuronal guidance molecule SLIT plays a role in tumor suppression, as SLIT-encoding genes are inactivated in several types of cancer, including lung cancer; however, it is not clear how SLIT functions in lung cancer. Here, our data show that SLIT inhibits cancer cell migration by activating RhoA and that myosin 9b (Myo9b) is a ROBO-interacting protein that suppresses RhoA activity in lung cancer cells. Structural analyses revealed that the RhoGAP domain of Myo9b contains a unique patch that specifically recognizes RhoA. We also determined that the ROBO intracellular domain interacts with the Myo9b RhoGAP domain and inhibits its activity; therefore, SLIT-dependent activation of RhoA is mediated by ROBO inhibition of Myo9b. In a murine model, compared with control lung cancer cells, SLIT-expressing cells had a decreased capacity for tumor formation and lung metastasis. Evaluation of human lung cancer and adjacent nontumor tissues revealed that Myo9b is upregulated in the cancer tissue. Moreover, elevated Myo9b expression was associated with lung cancer progression and poor prognosis. Together, our data identify Myo9b as a key player in lung cancer and as a ROBO-interacting protein in what is, to the best of our knowledge, a newly defined SLIT/ROBO/Myo9b/RhoA signaling pathway that restricts lung cancer progression and metastasis. Additionally, our work suggests that targeting the SLIT/ROBO/Myo9b/RhoA pathway has potential as a diagnostic and therapeutic strategy for lung cancer.

Authors

Ruirui Kong, Fengshuang Yi, Pushuai Wen, Jianghong Liu, Xiaoping Chen, Jinqi Ren, Xiaofei Li, Yulong Shang, Yongzhan Nie, Kaichun Wu, Daiming Fan, Li Zhu, Wei Feng, Jane Y. Wu

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Usage data is cumulative from October 2024 through October 2025.

Usage JCI PMC
Text version 865 138
PDF 106 31
Figure 377 17
Supplemental data 57 5
Citation downloads 74 0
Totals 1,479 191
Total Views 1,670
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