Downregulation of GNA14 in hepatocellular carcinoma indicates an unfavorable prognosis

Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a challenging disease to evaluate in terms of prognosis, requiring close attention to the prognosis of HCC patients. Exosomes have been shown to play an important role in HCC development and have significant potential in managing HCC patient prognosis, as they are detectable in patients' blood. By using small extracellular vesicular RNA, liquid biopsies can reflect the underlying physiological and pathological status of the originating cells, providing a valuable assessment of human health. No study has explored the diagnostic value of mRNA expression changes in exosomes for liver cancer. The present study investigated establishing a risk prognosis model based on mRNA expression levels in exosomes from blood samples of liver cancer patients and evaluated its diagnostic and prognostic value, providing new targets for liver cancer detection. We obtained mRNA data from HCC patients and normal controls from the TCGA and exoRBase 2.0 databases and established a risk prognostic assessment model using exosomes-related risk genes selected through prognostic analysis and Lasso Cox analysis. The patients were divided into high-risk and low-risk groups based on median risk score values to validate the independence and evaluability of the risk score. The clinical value of the model was further analyzed using a nomograph model, and the efficacy of immunotherapy and cell-origin types of prognostic risk genes were further assessed in the high- and low-risk groups by immune checkpoint and single-cell sequencing. A total of 44 genes were found to be significantly associated with the prognosis of HCC patients. From this group, we selected six genes (CLEC3B, CYP2C9, GNA14, NQO1, NT5DC2, and S100A9) as exosomal risk genes and used them as a basis for the risk prognosis model. The clinical information of HCC patients from the TCGA and ICGC databases demonstrated that the risk prognostic score of the model established in this study was an independent prognostic factor with good robustness. When pathological stage and risk prognostic score were incorporated into the model to predict clinical outcomes, the nomograph model had the best clinical benefit. Furthermore, immune checkpoint assays and single-cell sequencing analysis suggested that exosomal risk genes were derived from different cell types and that immunotherapy in the high-risk groups could be beneficial. Our study demonstrated that the prognostic scoring model based on exosomal mRNA was highly effective. The six genes selected using the scoring model have been previously reported to be associated with the occurrence and development of liver cancer. However, this study is the first to confirm that these related genes existed in the blood exosomes, which could be used for liquid biopsy of patients with liver cancer, thereby avoiding the need for puncture diagnosis. This approach has a high value in clinical application. Through single-cell sequencing, we found that the six genes in the risk model originate from multiple cell types. This finding suggests that the exosomal characteristic molecules secreted by different types of cells in the microenvironment of liver cancer may serve as diagnostic markers.

GNA14's interaction with RACK1 inhibits hepatocellular carcinoma progression through reducing MAPK/JNK and PI3K/AKT signaling pathway

Gαq subfamily proteins play critical roles in many biological functions including cardiovascular development, angiogenesis, and tumorigenesis of melanoma. However, the understanding of G Protein Subunit Alpha 14 (GNA14) in diseases, especially in cancers is limited. Here, we revealed that GNA14 was significantly low expression in Human hepatocellular carcinoma (HCC) samples. Low GNA14 expression was correlated with aggressive clinicopathological features. Moreover, the overall survival (OS) and disease-free survival (DFS) of high GNA14 expression HCC patients were much better than low GNA14 expression group. Lentivirus-mediated GNA14 knockdown significantly promoted the growth of liver cancer in vitro and in vivo. However, opposing results were observed when GNA14 is upregulated. Mechanistically, We identified receptor for activated C kinase 1 (RACK1) as a binding partner of GNA14 by co-immunoprecipitation and mass spectrometry (MS). Glutathione-S-transferase (GST) pull-down assay further verified the direct interaction between GNA14 and RACK1. RNA-Seq and loss- and gain-of-function assays also confirmed that GNA14 reduced the activity of both MAPK/JNK and PI3K/AKT signaling pathways through RACK1. GNA14 synergized with U73122 (PLC inhibitor) to enhance this effect. Further studies suggested that GNA14 potentially competed with protein kinase C (PKC) to bind with RACK1, consequently reducing the stability of PKC. Moreover, we also showed that GNA14’supression of p-AKT protein level depended on sufficient RACK1 expression. In conclusion, we indicated a different role of GNA14, which acted as a suppressor inhibiting liver cancer progression through MAPK/JNK and PI3K/AKT signaling pathways. Due to this, GNA14 served as a potentially valuable prognostic biomarker for liver cancer.