miR-137-LAPTM4B regulates cytoskeleton organization and cancer metastasis via the RhoA-LIMK-Cofilin pathway in osteosarcoma.
Ruyu YanDan LiuJunjie WangMinxia LiuHongjuan GuoJing BaiShuo YangJun ChangZhihong YaoZuozhang YangTomas BlomKecheng ZhouPublished in: Oncogenesis (2023)
Osteosarcoma (OS) is a rare malignant bone tumor but is one leading cause of cancer mortality in childhood and adolescence. Cancer metastasis accounts for the primary reason for treatment failure in OS patients. The dynamic organization of the cytoskeleton is fundamental for cell motility, migration, and cancer metastasis. Lysosome Associated Protein Transmembrane 4B (LAPTM4B) is an oncogene participating in various biological progress central to cancer biogenesis. However, the potential roles of LAPTM4B in OS and the related mechanisms remain unknown. Here, we established the elevated LAPTM4B expression in OS, and it is essential in regulating stress fiber organization through RhoA-LIMK-cofilin signaling pathway. In terms of mechanism, our data revealed that LAPTM4B promotes RhoA protein stability by suppressing the ubiquitin-mediated proteasome degradation pathway. Moreover, our data show that miR-137, rather than gene copy number and methylation status, contributes to the upregulation of LAPTM4B in OS. We report that miR-137 is capable of regulating stress fiber arrangement, OS cell migration, and metastasis via targeting LAPTM4B. Combining results from cells, patients' tissue samples, the animal model, and cancer databases, this study further suggests that the miR-137-LAPTM4B axis represents a clinically relevant pathway in OS progression and a viable target for novel therapeutics.
Keyphrases
- papillary thyroid
- cell proliferation
- signaling pathway
- long non coding rna
- copy number
- squamous cell
- end stage renal disease
- gene expression
- poor prognosis
- cell migration
- stem cells
- chronic kidney disease
- dna methylation
- ejection fraction
- childhood cancer
- long noncoding rna
- cardiovascular disease
- coronary artery disease
- cardiovascular events
- cystic fibrosis
- single cell
- escherichia coli
- risk assessment
- genome wide
- depressive symptoms
- deep learning
- prognostic factors
- big data
- drug delivery
- single molecule
- early life
- body composition
- artificial intelligence
- stress induced
- cell cycle arrest
- cancer therapy