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A novel BMX variant promotes tumor cell growth and migration in lung adenocarcinoma.

ABSTRACT: The non-receptor tyrosine kinase BMX has been reported in several solid tumors. However, the alternative splicing of BMX and its clinical relevance in lung cancer remain to be elucidated. Exon1.0 array was used to identify a novel alternative splicing of BMX, BMX?N, which was confirmed by rapid amplification of cDNA ends and reverse transcription-polymerase chain reaction. BMX?N, resulting from exon skipping with excluding exon 1 to exon 8 of BMX gene, was found in 12% human lung adenocarcinoma specimens. BMX?N is not found in paired pathologically normal lungs and positively correlated with EGFR mutation in lung adenocarcinomas. Moreover, BMX?N increases cell proliferation, neoplastic transformation, and migratory property of human non-small cell lung cancer cells. The function of BMX?N in lung cancer might be presumably due to enhanced ERK signaling.

SUBMITTER: Wang Y

PROVIDER: S-EPMC5464877 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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A novel BMX variant promotes tumor cell growth and migration in lung adenocarcinoma.

Wang Ye Y Xia Jufeng J Fang Zhaoyuan Z Li Fei F Li Duo D Wang Zuoyun Z Feng Yan Y Zhang Jian J Chen Haiquan H Ji Hongbin H Liu Hongyan H

Oncotarget 20170501 20

The non-receptor tyrosine kinase BMX has been reported in several solid tumors. However, the alternative splicing of BMX and its clinical relevance in lung cancer remain to be elucidated. Exon1.0 array was used to identify a novel alternative splicing of BMX, BMXΔN, which was confirmed by rapid amplification of cDNA ends and reverse transcription-polymerase chain reaction. BMXΔN, resulting from exon skipping with excluding exon 1 to exon 8 of BMX gene, was found in 12% human lung adenocarcinoma ...[more]

PMID: 28422715

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Project description:Activation of c-Met plays a critical role in tumorigenesis, migration and invasion in lung cancer. Here, we explored the therapeutic efficacy of a novel small-molecule c-Met inhibitor (BPI-9016M) in lung adenocarcinoma and investigated the underlying molecular mechanisms. Method: BPI-9016M, a c-Met tyrosine kinase receptor inhibitor, was used to treat patient-derived xenografts (PDX) from lung adenocarcinoma in NOD/SCID mice. Immunohistochemistry and Western blot analysis were used to determine the expression of c-Met and its downstream signaling molecules. CCK8, wound healing, and trans-well assays were used to analyze cell proliferation, spreading, migration and invasion. RNA sequencing and quantitative real-time PCR (qPCR) was used to screen and validate the expression of downstream genes in lung adenocarcinoma cells treated with BPI-9016M. Luciferase reporter assay was used to detect the interaction between miRNA and the targeted gene. Results: BPI-9016M significantly suppressed growth in three out of four lung adenocarcinoma PDX models, particularly in the tumors with high expression of c-Met. In lung adenocarcinoma cell lines, BPI-9016M treatment resulted in increased miR203, which reduced migration and invasion and also repressed Dickkopf-related protein 1 (DKK1) expression. Forced overexpression of DKK1 or down-regulation of miR203 reversed the inhibitory effect of BPI-9016M on migration and invasion. C-Met was verified to positively and negatively associate with DKK1 and miR203, respectively. High expression of c-Met/DKK1 or low expression of miR203 related to poor outcome of lung adenocarcinoma patients. Furthermore, we observed significantly enhanced tumor cell growth inhibition upon combining BPI-9016M treatment with miR203 mimics or DKK1 siRNA. Conclusion: Our data indicated that BPI-9016M is an effective agent against lung adenocarcinoma, particularly in tumors with c-Met activation, and likely functions through upregulation of miR203 leading to reduced DKK1 expression.

Dataset Information

A novel BMX variant promotes tumor cell growth and migration in lung adenocarcinoma.

Publications

A novel BMX variant promotes tumor cell growth and migration in lung adenocarcinoma.

Similar Datasets

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