Exosomes are small membranous vesicles released by many kinds of cells, and are indispensable in cell-to-cell communication by delivering functional biological components both locally and systemically. Long non-coding RNAs (lncRNAs) are long transcripts over 200 nucleotides that exhibit no or limited protein-coding potentials. LncRNAs are dramatic gene expression regulators, and can be selectively sorted into exosomes. Exosomal lncRNAs derived from cancer cells and stromal cells can mediate the generation of pre-metastatic niches (PMNs) and thus promote the progression of cancer. In this review, we summarized the fundamental biology and characteristics of exosomal lncRNAs. Besides, we provided an overview of current research on functions of exosomal lncRNAs between cancer cells and non-cancer cells. A deep understanding of exosomal lncRNAs’ role in cancer will be facilitated to find important implications for cancer development and treatment.
Background Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with high mortality. Advanced stage upon diagnosis and cancer metastasis are the main reasons for the dismal prognosis of HCC in large part. The role of proliferation associated protein 2G4 (PA2G4) in tumorigenesis and cancer progression has been widely investigated in various cancers. However, whether and how PA2G4 participates in HCC metastasis is still underexplored. Results We found that the mRNA and protein levels of PA2G4 were higher in HCC samples than in normal liver tissues, and high expression of PA2G4 in HCC was correlated with a poor prognosis, by an integrative analysis of immunohistochemistry (IHC), western blot and bioinformatic approach. Moreover, the expression of PA2G4 was elevated in HCC patients with metastases than those metastasis-free. Cell migration, invasion, phalloidin staining and western blot analyses demonstrated that PA2G4 promoted epithelial to mesenchymal transition (EMT) of HCC cells in vitro. And a lung metastasis animal model exhibited that PA2G4 enhanced metastatic ability of HCC cells in vivo. RNA-sequencing combined with dual luciferase reporter assay and evaluation of mRNA half-time indicated that PA2G4 increased FYN expression by stabilizing its mRNA transcript. Recovering the impaired FYN level induced by PA2G4 knockdown rescued the impeded cell mobilities. Furthermore, endogenous immunoprecipitation (IP) and in-situ immunofluorescence (IF) showed that YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) was the endogenous binding patterner of PA2G4. In addition, RNA binding protein immunoprecipitation (RIP) and anti- N6-methyladenosine immunoprecipitation (MeRIP) assays demonstrated that FYN mRNA was N6-methyladenosine (m6A) modified and bound with PA2G4, as well as YTHDF2. Moreover, the m6A catalytic ability of YTHDF2 was found indispensable for the regulation of FYN by PA2G4. At last, the correlation of expression levels between PA2G4 and FYN in HCC tissues was verified by IHC and western blot analysis. Conclusions These results indicate that PA2G4 plays a pro-metastatic role by increasing FYN expression through binding with YTHDF2 in HCC. PA2G4 may become a reliable prognostic marker or therapeutic target for HCC patients.
Hepatocellular carcinoma (HCC) has been recognized as the third leading cause of cancer-related deaths worldwide. There is increasing evidence that the abnormal expression of autophagy-related genes plays an important role in the occurrence and development of HCC. Therefore, the study of autophagy-related genes can further elucidate the genetic drivers of cancer and provide valuable therapeutic targets for clinical treatment. In this study, we used 232 autophagy-related genes extracted from the Human Autophagy Database (HADb) and Molecular Signatures Database (MSigDB) to construct 1884 autophagy-related gene pairs. On this basis, we developed a prognostic model based on autophagy-related gene pairs using least absolute shrinkage and selection operator (LASSO) Cox regression to evaluate the prognosis of patients after liver cancer resection. We then used 845 liver cancer samples from three different databases to test the reliability of the risk signature through survival analysis, receiver operating characteristic (ROC) curve analysis, univariate and multivariate analysis. To further explore the underlying biological mechanisms, we conducted an enrichment analysis of autophagy-related genes. Finally, we combined the signature with independent prognostic factors to construct a nomogram. Based on the autophagy-related gene pair (ARGP) signature, we can divide patients into high- or low-risk groups. Survival analysis and ROC curve analysis verified the validity of the signature (AUC: 0.786—0.828). Multivariate Cox regression showed that the risk score can be used as an independent predictor of the clinical outcomes of liver cancer patients. Notably, this model has a more accurate predictive effect than most prognostic models for hepatocellular carcinoma. Moreover, our model is a powerful supplement to the HCC staging indicator, and a nomogram comprising both indicators can provide a better prognostic effect. Based on pairs of multiple autophagy-related genes, we proposed a prognostic model for predicting the overall survival rate of HCC patients after surgery, which is a promising prognostic indicator. This study confirms the importance of autophagy in the occurrence and development of HCC, and also provides potential biomarkers for targeted treatments.
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