Background
Metastasis is the predominant cause of mortality in patients with breast cancer. Long noncoding RNAs (lncRNAs) have been shown to drive important phenotypes in tumors, including invasion and metastasis. However, the lncRNAs involved in metastasis and their molecular and cellular mechanisms are still largely unknown.
Conclusion
Therefore, our findings propose LacRNA as a potential prognostic biomarker and a new therapeutic strategy.
Methods
The transcriptional and posttranscriptional processing of LINC00478-associated cytoplasmic RNA (LacRNA) was determined by RT-qPCR, semiquantitative PCR and 5'/3' RACE. Paired-guide CRISPR/cas9 and CRISPR/dead-Cas9 systems was used to knock out or activate the expression of LacRNA. Cell migration and invasion assay was performed to confirm the phenotype of LacRNA. Tail vein model and mammary fat pad model were used for in vivo study. The LacRNA-PHB2-cMyc axis were screened and validated by RNA pulldown, mass spectrometry, RNA immunoprecipitation and RNA-seq assays.
Results
Here, we identified a novel cytoplasmic lncRNA, LacRNA (LINC00478-associated cytoplasmic RNA), derived from nucleus-located lncRNA LINC00478. The nascent transcript of LINC00478 full-length (LINC00478_FL) was cleaved and polyadenylated, simultaneously yielding 5' ends stable expressing LacRNA, which is released into the cytoplasm, and long 3' ends of nuclear-retained lncRNA. LINC00478_3'RNA was rapidly degraded. LacRNA significantly inhibited breast cancer invasion and metastasis in vitro and in vivo. Mechanistically, LacRNA physically interacted with the PHB domain of PHB2 through its 61-140-nt region. This specific binding affected the formation of the autophagy degradation complex of PHB2 and LC3, delaying the degradation of the PHB2 protein. Unexpectedly, LacRNA specifically interacted with PHB2, recruited c-Myc and promoted c-Myc ubiquitination and degradation. The negatively regulation of Myc signaling ultimately inhibited breast cancer metastasis. Furthermore, LacRNA and LacRNA-mediated c-Myc signaling downregulation are significantly associated with good clinical outcomes, take advantage of these factors we constructed a prognostic predict model.