Noninvasive Identification of Immune-Related Biomarkers in Hepatocellular Carcinoma

The Combined Detection of Immune Genes for Predicting the Prognosis of Patients With Non-Small Cell Lung Cancer

Lung cancer is one of the leading causes of cancer-related death. In recent years, there has been an increasing interest in the fields of tumor and immunity. This study focused on the possible prognostic value of immune genes in non-small cell lung cancer patients. We used The Cancer Genome Atlas (TCGA) to download gene expression data and clinical information of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). The immune gene list was downloaded from the Immport database. We then constructed immune gene prognostic models on the basis of Cox regression analysis. We further evaluated the clinical significance of the models via survival analysis, receiver operating characteristic (ROC) curves, and independent prognostic factor analysis. Moreover, we analyzed the associations of prognostic models with both mutation burdens and neoantigens. Using the Gene Expression Omnibus (GEO) and Kaplan-Meier plotter databases, we evaluated the validity of the prognostic models. The prognostic model of LUAD included 13 immune genes, and the prognostic model of LUSC contained 10 immune genes. High-risk patients based on prognostic models had a lower 5-year survival rate than did low-risk patients. The ROC curve analysis demonstrated the prediction accuracy of the prognostic models, as the area under the curve (AUC) was 0.742, 0.707, and 0.711 for LUAD, and 0.668, 0.703, and 0.668 for LUSC, when the predicted survival times were 1, 3, and 5 years, respectively. The mutation burden analysis showed that mutation level was associated with the risk score in patients with LUAD. The analysis based on GEO and Kaplan-Meier plotter demonstrated the prognostic validity of the models. Therefore, immune gene-related models of LUAD and LUSC can predict prognosis. Further study of these genes may enable us to better distinguish between LUAD and LUSC and lead to improvement in immunotherapy for lung cancer.

lncRNA DUXAP8 Facilitates Multiple Malignant Phenotypes and Resistance to PARP Inhibitor in HCC via Upregulating FOXM1

In this study, we examined the clinical significance and molecular mechanisms of a long non-coding RNA (lncRNA), double homeobox A pseudogene 8 (DUXAP8) in hepatocellular carcinoma (HCC). DUXAP8 expression was compared using quantitative real-time PCR in HCC versus adjacent tissues and in HCC cell lines versus normal hepatic epithelial cells. The correlations between DUXAP8 level and clinicopathological features were analyzed. Assays including MTT, colony-forming analysis, Transwell assay, western blot, xenograft formation, experimental metastasis, luciferase assay, RNA pull-down, and RNA immunoprecipitation were used to examine DUXAP8-induced malignant phenotypes, its regulation on forkhead box protein M1 (FOXM1), and the importance of FOXM1 in mediating DUXAP8 phenotypes. Our results showed that DUXAP8 was significantly upregulated in HCC tissues or cell lines associated with tumors of advanced grades, tumors that were positive for lymph node metastasis, and patients with poor overall survival. DUAXP8 was essential in maintaining multiple malignant phenotypes (including resistance to olaparib) both in vitro and in vivo. Mechanistically, DUXAP8 upregulated FOXM1 expression by sponging miR-485-5p and interacting with the RNA-binding protein Fused in Sarcoma (FUS). Functionally, FOXM1 essentially mediated the oncogenic phenotypes of DUXAP8. Collectively, DUXAP8 acts through two distinct mechanisms to upregulate FOXM1 and becomes a pleotropic oncogenic lncRNA in HCC.

Usefulness of Circulating Methylated p16 as a Noninvasive Molecular Biomarker for Hepatitis C-Related Hepatocellular Carcinoma with Normal Serum Alpha-Fetoprotein Levels

Background

Screening of hepatocellular carcinoma (HCC) is challenged especially in patients with normal alpha-fetoprotein (AFP) levels. Aberrant p16 methylation has been implicated in HCC.

Objectives and Aims

This study aimed to assess serum methylated p16 (MP16) expression levels and to evaluate MP16 diagnostic performance in HCC detection among HCV-infected Egyptian patients with normal AFP levels.

Methods

MP16 levels were quantified using real-time PCR in 230 serum samples (30 healthy controls, 95 with HCV-HCC, 40 with chronic hepatitis C "CHC" and 65 with HCV cirrhosis). Diagnostic performance of MP16 for diagnosis of HCC was done using receiver operator characteristic curve analysis.

Results

Serum MP16 levels were significantly higher in HCC than CHC, cirrhosis, and healthy subjects and significantly higher in HCC with normal AFP levels than those with higher AFP. ROC curves revealed promising diagnostic performance for MP16 in discriminating HCC with normal AFP levels from non-HCC cases. This predictive ability improved by combining MP16 and AFP (AUC of 0.872 with 100% sensitivity, 76.5% specificity, 79.1% positive predictive value, 100% negative predictive value, and 87.5% accuracy).

Conclusion

MP16 can be a potential noninvasive molecular biomarker for HCC detection in patients with hepatic mass(es) and normal AFP levels especially in those where liver biopsy and radiological imaging cannot be done.