No abstract

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. Nucleosome assembly protein 1-like 5 (NAP1L5) is a protein-coding gene that encodes a protein similar to nucleosome assembly protein 1 (NAP1). It is a histone chaperone that plays an important role in gene transcription in organisms. However, the role of NAP1L5 in the pathogenesis of hepatocellular carcinoma remains to be elucidated. In this study, low expression of NAP1L5 was found in hepatocellular carcinoma, and the downregulation of NAP1L5 was related to shorter survival and disease-free survival. In addition, its expression is also related to the tumor size and recurrence of hepatocellular carcinoma. The overexpression and knockdown of NAP1L5 by plasmid and siRNA showed that NAP1L5 inhibited the proliferation, migration and invasion and induced apoptosis of hepatoma cells. In vivo experiments confirmed that NAP1L5 can inhibit the growth and metastasis of hepatocellular carcinoma cells. In the mechanistic study, we found that NAP1L5 affects the occurrence and development of hepatocellular carcinoma by regulating MYH9 to inhibit the PI3K/AKT/mTOR signaling pathway. As a functional tumor suppressor, NAP1L5 is expressed at low levels in HCC. NAP1L5 inhibits the PI3K/AKT/mTOR signaling pathway in hepatocellular carcinoma by regulating MYH9. It may be a new potential target for liver cancer treatment.

Background : Hepatocellular carcinoma (HCC) is one of the most common clinical malignant tumors, resulting in high mortality and poor prognosis. Studies have found that LncRNA plays an important role in the onset, metastasis and recurrence of hepatocellular carcinoma. The immune system plays a vital role in the development, progression, metastasis and recurrence of cancer. Therefore, immune-related lncRNA can be used as a novel biomarker to predict the prognosis of hepatocellular carcinoma. Methods : The transcriptome data and clinical data of HCC patients were obtained by using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA‑LIHC), and immune-related genes were extracted from the Molecular Signatures Database (IMMUNE RESPONSE M19817 and IMMUNE SYSTEM PROCESS M13664). By constructing the co-expression network and Cox regression analysis, 13 immune-lncRNAs was identified to predict the prognosis of HCC patients. Patients were divided into high risk group and low risk group by using the risk score formula, and the difference in overall survival (OS) between the two groups was reflected by Kaplan-Meier survival curve. The time - dependent receiver operating characteristics (ROC) analysis and principal component analysis (PCA) were used to evaluate 13 immune -lncRNAs signature. Results : Through TCGA - LIHC extracted from 343 cases of patients with hepatocellular carcinoma RNA - Seq data and clinical data, 331 immune-related genes were extracted from the Molecular Signatures Database , co-expression networks and Cox regression analysis were constructed, 13 immune-lncRNAs signature was identified as biomarkers to predict the prognosis of patients. At the same time using the risk score median divided the patients into high risk and low risk groups, and through the Kaplan-Meier survival curve analysis found that high-risk group of patients' overall survival (OS) less low risk group of patients. The AUC value of the ROC curve is 0.828, and principal component analysis (PCA) results showed that patients could be clearly divided into two parts by immune-lncRNAs, which provided evidence for the use of 13 immune-lncRNAs signature as prognostic markers. Conclusion : Our study identified 13 immune-lncRNAs signature that can effectively predict the prognosis of HCC patients, which may be a new prognostic indicator for predicting clinical outcomes.