Development and clinical validation of a novel 9-gene prognostic model based on multi-omics in pancreatic adenocarcinoma.

The prognoses of patients with pancreatic adenocarcinoma (PAAD) remain poor due to the lack of biomarkers for early diagnosis and effective prognosis prediction. RNA sequencing, single nucleotide polymorphism, and copy number variation data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes. GISTIC 2.0 was used to identify significantly amplified or deleted genes, and Mutsig 2.0 was used to analyze the mutation data. The Lasso method was used to construct a risk prediction model. The Rms package was used to evaluate the overall predictive performance of the signature. Finally, Western blot and polymerase chain reaction were performed to evaluate gene expression. A total of 54 candidate genes were obtained after integrating the genomic mutated genes and prognosis-related genes. The Lasso method was used to ascertain 9 characteristic genes, including UNC13B, TSPYL4, MICAL1, KLHDC7B, KLHL32, AIM1, ARHGAP18, DCBLD1, and CACNA2D4. The 9-gene signature model was able to help stratify samples at risk in the training and external validation cohorts. In addition, the overall predictive performance of our model was found to be superior to that of other models. KLHDC7B, AIM1, DCBLD1, TSPYL4, and MICAL1 were significantly highly expressed in tumor tissues compared to normal tissues. ARHGAP18 and CACNA2D4 had no difference in expression between tumor and normal tissues. UNC13B and KLHL32 expression in the normal group was higher than in the tumor group. The 9-gene signature constructed in this study can be used as a novel prognostic marker to predict the survival of patients with pancreatic adenocarcinoma.

[Hepatitis B virus X protein induces malignant transformation tendency of Chang liver cells involving p16(INK4a) hypermethylation].

OBJECTIVE: To study the relationship between hepatitis B virus X (HBx) protein and DNA methylation of p16(INK4a) and the role of HBx in the carcinogenesis of hepatocellular carcinoma. METHODS: Eukaryonic expression vectors pcDNA3.1B-HBx and pcDNA3.1B were transduced into Chang liver cells by using Lipofectamine 2000 to establish the Chang-HBx liver cell line (HBx expression) and Chang-vector liver cell line (non-HBx expression). RT-PCR and Western blot were used to test the expression of p16(INK4a) in the two cell lines. The level of p16(INK4a) promoter methylation was tested by methylation specific PCR (MSP). The proliferation curves were drew by CCK-8, and S-phase in cell cycle and apoptosis were observed by flow cytometry. RESULTS: Hypermethylation of p16 can be mediated by HBx, which decreases the expression of mRNA and protein of p16. Chang-HBx cells grow faster. Chang-HBx cells have much higher S-phase population (28.96% vs. 21.53%, P<0.001; 28.96% vs. 21.5%, P<0.001) and lower apoptosis rate (2.71% vs. 3.69%, P<0.001; 2.71% vs. 3.36%, P<0.001) than Chang-vector cells and Chang cells respectively. CONCLUSION: p16(INK4a) expression was repressed by HBx protein via DNA methylation of p16(INK4a), which can induce the malignant transformation tendency of Chang cells.

LncRNA WWOX-AS1 sponges miR-20b-5p in hepatocellular carcinoma and represses its progression by upregulating WWOX.

Increasing evidence has revealed that long noncoding RNAs (lncRNAs) emerge as pivotal regulators in diverse cancers, including hepatocellular carcinoma (HCC). This study was conducted to investigate the role of lncRNA WWOX antisense RNA 1 (WWOX-AS1) in HCC progression. Our present study illustrated that WWOX-AS1 was lowly expressed in HCC tissues and cell lines. High WWOX-AS1 expression was further confirmed to predict a favorable prognosis in HCC patients. Through functional assays, we observed that upregulated WWOX-AS1 was correlated with decreased cell proliferation, migration, epithelial to mesenchymal transition (EMT) process and increased cell apoptosis, suggesting that WWOX-AS1 exerted anti-carcinogenic role in the development of HCC. Moreover, WWOX, the nearby gene of WWOX-AS1, was found at a low level in HCC tissues and cell lines. Furthermore, there was a positive relationship between WWOX-AS1 and WWOX. Additionally, WWOX overexpression hampered cell proliferation, migration, EMT process and induced cell apoptosis in HCC. Mechanically, WWOX-AS1 was identified as a cytoplasmic RNA in HCC cells and sponged miR-20b-5p to regulate WWOX expression. Rescue assays further indicated that WWOX knockdown counteracted WWOX-AS1 overexpression-mediated suppressive function on HCC progression. Collectively, WWOX-AS1/miR-20b-5p/WWOX axis suppresses HCC tumorigenesis, hinting a potential molecular mechanism for the therapy of HCC patients.

Identification of immune subtypes and prognosis of hepatocellular carcinoma based on immune checkpoint gene expression profile.

The significant response of immunotherapy is currently limited to a small number of patients, which has a high degree of selectivity. Therefore, distinguishing the immune subtypes of the tumor is necessary for patients who may benefit from immune checkpoint therapy. Clinical data and RNA expression data from The Cancer Genome Atlas (TCGA) and GENE EXPRESSION OMNIBUS (GEO) databases were used to study the relationship of immune regulatory pathways with immune subtypes, and the effects on the prognosis of hepatocellular carcinoma (HCC) patients. Eight immune checkpoint coding genes (ICGs) were obtained that closely related to prognosis. Adaptive immune pathway genes (CD8A, CD68, GZMB, and NOS2) show significant positive correlation with most of ICGs. Therefore, adaptive immune pathway genes may play a certain regulatory role in the expression of ICGs. Among the four immune subtypes, the group with low expression level of PD-L1, IDO1 and CTLA4, and high expression of CD8A had showed the best prognosis. The prognosis was the worst in the group with low expression of PD-L1, IDO1 and CTLA4, and showed low expression of CD8A. This research proposed a method to analyze the gene expression profile of immune checkpoints. The present method can be applied to identify the relationship between immune subtype of HCC and the prognosis, providing basis for gene immunotherapy in HCC patients.

Development and Validation of a Novel 8 Immune Gene Prognostic Signature Based on the Immune Expression Profile for Hepatocellular Carcinoma.

BACKGROUND: The immune microenvironment plays a vital role in the development of hepatocellular carcinoma (HCC). This study explored novel immune-related biomarkers to predict the prognosis of patients with HCC. METHODS: RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes; the Lasso method was used to construct the prognosis risk model. Validation was performed on the International Cancer Genome Consortium (ICGC) cohort, and the C-index was calculated to evaluate its overall predictive performance. Western blots were conducted to evaluate the expression of genes. RESULTS: There were 320 immune-related genes, 40 of which were significantly related to prognosis. Eight immune gene signatures (CKLF, IL12A, CCL20, PRELID1, GLMN, ACVR2A, CD7, and FYN) were established by Lasso Cox regression analysis. This immune signature performed well in different cohorts and can be an independent risk factor for prognosis. In addition, the overall predictive performance of this model was higher than the other models reported previously. CONCLUSION: The predictive immune model will enable patients with HCC to be more accurately managed in immunotherapy.

Identification of an extracellular vesicle-related gene signature in the prediction of pancreatic cancer clinical prognosis.

Although extracellular vesicles (EVs) in body fluid have been considered to be ideal biomarkers for cancer diagnosis and prognosis, it is still difficult to distinguish EVs derived from tumor tissue and normal tissue. Therefore, the prognostic value of tumor-specific EVs was evaluated through related molecules in pancreatic tumor tissue. NA sequencing data of pancreatic adenocarcinoma (PAAD) were acquired from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). EV-related genes in pancreatic cancer were obtained from exoRBase. Protein-protein interaction (PPI) network analysis was used to identify modules related to clinical stage. CIBERSORT was used to assess the abundance of immune and non-immune cells in the tumor microenvironment. A total of 12 PPI modules were identified, and the 3-PPI-MOD was identified based on the randomForest package. The genes of this model are involved in DNA damage and repair and cell membrane-related pathways. The independent external verification cohorts showed that the 3-PPI-MOD can significantly classify patient prognosis. Moreover, compared with the model constructed by pure gene expression, the 3-PPI-MOD showed better prognostic value. The expression of genes in the 3-PPI-MOD had a significant positive correlation with immune cells. Genes related to the hypoxia pathway were significantly enriched in the high-risk tumors predicted by the 3-PPI-MOD. External databases were used to verify the gene expression in the 3-PPI-MOD. The 3-PPI-MOD had satisfactory predictive performance and could be used as a prognostic predictive biomarker for pancreatic cancer.

Up-regulation of RNF187 induces hepatocellular carcinoma cell epithelial to mesenchymal transitions.

Ring finger protein 187 (RNF187) has been identified to be a co-activator linking c Jun to Ras signaling. However, the expression and function of RNF187 in hepatocellular carcinomas (HCC) remains unclear. Here, we tried to determine the expression and roles of RNF187 in hepatocellular carcinomas (HCC).The expression of RNF187 was determined in HCC tissues and cell lines, and we found that RNF187 expressed highly in HCC tissues compared with the corresponding adjacent liver tissues both in mRNA and protein level, which was consistent with the result of immunohistochemistry on HCC tissue microarrays. In HCC cell lines, the level of RNF187 was positively associated with the HCC cells metastatic potential. By the RNF187 interference and cDNA transfection, we showed that the high level of RNF187 induced the HCC cells invasion and metastasis both in vitro and in vivo, as well as the high ability of colony formation.Mechanistically, we detected the high level of RNF187 promoted cell scatter by inducing epithelial-mesenchymal transition (EMT). Clinically, the high level of RNA187 was significantly correlated with a malignant phenotype, including larger tumor size, multiple tumors, and microvascular invasion. Importantly, high level of RNF187 correlated with HCC patients' shorter OS and lower disease free survival rates than those with low level of RNF187. Our results revealed that elevated expression of RNF187 induced hepatocellular carcinoma cell epithelial to mesenchymal transitions, and represented a novel marker for predicting the poor prognosis of HCC.

Genomic aberrations in the HTPAP promoter affect tumor metastasis and clinical prognosis of hepatocellular carcinoma.

We previously reported that the intronic tagSNP +357G/C in the metastasis suppressor HTPAP is associated with metastasis and prognosis of hepatocellular carcinoma (HCC). The aim of this study was to investigate whether SNPs in the HTPAP promoter modulate HTPAP expression and prognosis of HCC. Genomic DNA from 572 microdissected HCCs were genotyped by pyrosequencing and verified by direct sequencing. Haplotype blocks were analyzed. Reporter plasmids were constructed and transfected into HCC cell lines. Transcriptional activities of plasmids were analyzed by dual-luciferase reporter systems. HTPAP expression was measured by real-time quantitative PCR, western blots, and tissue microarrays. Invasion was assessed by Matrigel assays. The prognostic values of HTPAP promoter SNPs in HCC were evaluated by Kaplan-Meier and Cox regression analyses. We identified six SNPs, including -1053A/G and +64G/C, in the HTPAP promoter. The SNPs were in complete linkage disequilibrium, resulting in three promoter haplotypes (promoter I:-1053AA/+64GG, promoter II: -1053AG/+64GC, and promoter III: -1053GG/+64CC). Promoter I manifested the highest luciferase index (p<0.005). However, no significant difference was observed between promoters II and III. We consistently found that HTPAP mRNA and protein levels were significantly higher in promoter I than that of promoter II+III (p<0.001). Invasion was increased in HCC cells transfected with promoters II+III compared to those transfected with promoter I (p<0.05). The HTPAP promoter II+III haplotype was associated with significantly increased metastasis compared to that of promoter I (p = 0.023). The postoperative five-year overall survival of patients with promoters II+III was lower than that of patients with promoter I (p = 0.006). Multivariate analysis showed that the promoter II+III haplotype was an adverse prognostic marker in HCC. The genetic variants at loci -1053 and +64 of the HTPAP promoter affect the expression of HTPAP, which might be a novel determinant and target for HCC prognosis.