KCNAB2 overexpression inhibits human non-small-cell lung cancer cell growth in vitro and in vivo.

Non-small-cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases. NSCLC patients often have poor prognosis demanding urgent identification of novel biomarkers and potential therapeutic targets. KCNAB2 (regulatory beta subunit2 of voltage-gated potassium channel), encoding aldosterone reductase, plays a pivotal role in regulating potassium channel activity. In this research, we tested the expression of KCNAB2 as well as its potential functions in human NSCLC. Bioinformatics analysis shows that expression of KCNAB2 mRNA is significantly downregulated in human NSCLC, correlating with poor overall survival. In addition, decreased KCNAB2 expression was detected in different NSCLC cell lines and local human NSCLC tissues. Exogenous overexpression of KCNAB2 potently suppressed growth, proliferation and motility of established human NSCLC cells and promoted NSCLC cells apoptosis. In contrast, CRISPR/Cas9-induced KCNAB2 knockout further promoted the malignant biological behaviors of NSCLC cells. Protein chip analysis in the KCNAB2-overexpressed NSCLC cells revealed that KCNAB2 plays a possible role in AKT-mTOR cascade activation. Indeed, AKT-mTOR signaling activation was potently inhibited following KCNAB2 overexpression in NSCLC cells. It was however augmented by KCNAB2 knockout. In vivo, the growth of subcutaneous KCNAB2-overexpressed A549 xenografts was significantly inhibited. Collectively, KCNAB2 could be a novel effective gene for prognosis prediction of NSCLC. Targeting KCNAB2 may lead to the development of advanced therapies.

Identification of matrix-remodeling associated 5 as a possible molecular oncotarget of pancreatic cancer.

Pancreatic cancer has an extremely poor prognosis. Here we examined expression, potential functions and underlying mechanisms of MXRA5 (matrix remodeling associated 5) in pancreatic cancer. Bioinformatics studies revealed that MXRA5 transcripts are significantly elevated in pancreatic cancer tissues, correlating with the poor overall survival, high T-stage, N1 and pathologic stage of the patients. MXRA5 mRNA and protein expression is significantly elevated in microarray pancreatic cancer tissues and different pancreatic cancer cells. In primary and immortalized (BxPC-3 and PANC-1 lines) pancreatic cancer cells, shRNA-induced MXRA5 silencing or CRISPR/Cas9-mediated MXRA5 knockout suppressed cell survival, proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), while provoking cell apoptosis. Conversely, forced overexpression of MXRA5 further promoted pancreatic cancer cell progression and EMT. Bioinformatics studies and the protein chip analyses revealed that differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) in MXRA5-overexpressed primary pancreatic cancer cells were enriched in the PI3K-Akt-mTOR cascade. Indeed, Akt-mTOR activation in primary human pancreatic cancer cells was inhibited by MXRA5 shRNA or knockout, but was augmented following MXRA5 overexpression. In vivo, the growth of MXRA5 KO PANC-1 xenografts was largely inhibited in nude mice. Moreover, intratumoral injection of adeno-associated virus-packed MXRA5 shRNA potently inhibited primary pancreatic cancer cell growth in nude mice. Akt-mTOR activation was also largely inhibited in the MXRA5-depleted pancreatic cancer xenografts. Contrarily MXRA5 overexpression promoted primary pancreatic cancer cell growth in nude mice. Together, overexpressed MXRA5 is important for pancreatic cancer cell growth possibly through promoting EMT and Akt-mTOR activation. MXRA5 could be a potential therapeutic oncotarget for pancreatic cancer.

Bioinformatics analysis and experimental verification of the prognostic and biological significance mediated by fatty acid metabolism related genes for hepatocellular carcinoma.

Background: Liver cancer is among the leading causes of death related to cancer around the world. The most frequent type of human liver cancer is hepatocellular carcinoma (HCC). Fatty acid (FA) metabolism is an emerging hallmark that plays a promoting role in numerous malignancies. This study aimed to discover a FA metabolism-related risk signature and formulate a better model for HCC patients' prognosis prediction. Methods: We collected mRNA expression data and clinical parameters of patients with HCC using the TCGA databases, and the differential FA metabolism-related genes were explored. To create a risk prognostic model, we carried out the consensus clustering as well as univariate and multivariate Cox regression analyses. 16 genes were used to establish a prognostic model, which was then validated in the ICGC dataset. The accuracy of the model was performed using receiver operating characteristic (ROC) analyses, decision curve analysis (DCA) and nomogram. The immune cell infiltration level of risk genes was evaluated with single-sample GSEA (ssGSEA) algorithm. To reflect the response to immunotherapy, immunophenoscore (IPS) was obtained from TCGA-LIHC. Then, the expression of the candidate risk genes (p < 0.05) was validated by qRT-PCR, Western blotting and single-cell transcriptomics. Cellular function assays were performed to revealed the biological function of HAVCR1. Results: According to the TCGA-LIHC cohort analysis, the majority of the FA metabolism-related genes were expressed differentially in the HCC and normal tissues. The prognosis of patients with high-risk scores was observed to be worse. Multivariate COX regression analysis confirmed that the model can be employed as an independent prognosis factor for HCC patients. Furthermore, ssGSEA analysis revealed a link between the model and the levels of immune cell infiltration. Our model scoring mechanism also provides a high predictive value in HCC patients receiving anti-PDL1 immunotherapy. One of the FA metabolism-related genes, HAVCR1, displays a significant differential expression between normal and HCC cell lines. Hepatocellular carcinoma cells (Huh7, and HepG2) proliferation, motility, and invasion were all remarkably inhibited by HAVCR1 siRNA. Conclusion: Our study identified a novel FA metabolism-related prognostic model, revealing a better potential treatment and prevention strategy for HCC.

Identification of phosphoenolpyruvate carboxykinase 1 as a potential therapeutic target for pancreatic cancer.

Pancreatic cancer is the third leading cause of cancer-related mortalities and is characterized by rapid disease progression. Identification of novel therapeutic targets for this devastating disease is important. Phosphoenolpyruvate carboxykinase 1 (PCK1) is the rate-limiting enzyme of gluconeogenesis. The current study tested the expression and potential functions of PCK1 in pancreatic cancer. We show that PCK1 mRNA and protein levels are significantly elevated in human pancreatic cancer tissues and cells. In established and primary pancreatic cancer cells, PCK1 silencing (by shRNA) or CRISPR/Cas9-induced PCK1 knockout potently inhibited cell growth, proliferation, migration and invasion, and induced robust apoptosis activation. Conversely, ectopic overexpression of PCK1 in pancreatic cancer cells accelerated cell proliferation and migration. RNA-seq analyzing of differentially expressed genes (DEGs) in PCK1-silenced pancreatic cancer cells implied that DEGs were enriched in the PI3K-Akt-mTOR cascade. In pancreatic cancer cells, Akt-mTOR activation was largely inhibited by PCK1 shRNA, but was augmented after ectopic PCK1 overexpression. In vivo, the growth of PCK1 shRNA-bearing PANC-1 xenografts was largely inhibited in nude mice. Akt-mTOR activation was suppressed in PCK1 shRNA-expressing PANC-1 xenograft tissues. Collectively, PCK1 is a potential therapeutic target for pancreatic cancer.

Prognostic value of LAT-1 status in solid cancer: A systematic review and meta-analysis.

BACKGROUND: The expression of the L-type amino acid transporter 1 (LAT1) plays a significant role in tumor progression. However, it remains unclear whether high LAT1 expression correlates with poor prognosis of solid tumor patients. Here, we conducted a meta-analysis to assess the potential of LAT1 in predicting the prognosis of tumor patients. METHODS AND FINDINGS: A total of 4,579 cases were analyzed from 35 qualified studies. In patients with solid tumors, elevated expression of LAT1 is associated with poor prognosis (overall survival [OS]: pooled hazard ratio (HR) = 1.848, 95% confidence interval (CI) = 1.620-2.108, P < 0.001; disease free survival [DFS]: pooled HR = 1.923, 95% CI = 1.585-2.333, P < 0.001; progression free survival [PFS]: pooled HR = 1.345, 95% CI = 1.133-1.597, P = 0.001). Furthermore, in subgroup analysis, we found an association between high LAT1 expression and poor OS in non-small cell lung cancer (HR = 1.554, 95% CI = 1.345-1.794, P < 0.001), pancreatic cancer (HR = 2.052, 95% CI = 1.613-2.724, P < 0.001) and biliary tract cancer (HR = 2.253, 95% CI = 1.562-3.227, P < 0.001). CONCLUSION: The results of this meta-analysis indicate the reliability and potential of using LAT1 expression as a predictive biomarker in solid cancers prior to treatment. However, further studies with larger sample sizes would be beneficial for fully evaluating the predictive value of LAT1 expression for clinical applications.