Mitochondria-derived small RNAs as diagnostic biomarkers in lung cancer patients through a novel ratio-based expression analysis methodology.

Small non-coding RNAs are potential diagnostic biomarkers for lung cancer. Mitochondria-derived small RNA (mtRNA) is a novel regulatory small non-coding RNA that only recently has been identified and cataloged. Currently, there are no reports of studies of mtRNA in human lung cancer. Currently, normalization methods are unstable, and they often fail to identify differentially expressed small non-coding RNAs (sncRNAs). In order to identify reliable biomarkers for lung cancer screening, we used a ratio-based method using mtRNAs newly discovered in human peripheral blood mononuclear cells. In the discovery cohort (AUC = 0.981) and independent validation cohort (AUC = 0.916) the prediction model of eight mtRNA ratios distinguished lung cancer patients from controls. The prediction model will provide reliable biomarkers that will allow blood-based screening to become more feasible and will help make lung cancer diagnosis more accurate in clinical practice.

Development of predicitve models to distinguish metals from non-metal toxicants, and individual metal from one another.

BACKGROUND: Evaluating the toxicity of chemical mixture and their possible mechanism of action is still a challenge for humans and other organisms. Microarray classifier analysis has shown promise in the toxicogenomic area by identifying biomarkers to predict unknown samples. Our study focuses on identifying gene markers with better sensitivity and specificity, building predictive models to distinguish metals from non-metal toxicants, and individual metal from one another, and furthermore helping understand underlying toxic mechanisms. RESULTS: Based on an independent dataset test, using only 15 gene markers, we were able to distinguish metals from non-metal toxicants with 100% accuracy. Of these, 6 and 9 genes were commonly down- and up-regulated respectively by most of the metals. 8 out of 15 genes belong to membrane protein coding genes. Function well annotated genes in the list include ADORA2B, ARNT, S100G, and DIO3. Also, a 10-gene marker list was identified that can discriminate an individual metal from one another with 100% accuracy. We could find a specific gene marker for each metal in the 10-gene marker list. Function well annotated genes in this list include GSTM2, HSD11B, AREG, and C8B. CONCLUSIONS: Our findings suggest that using a microarray classifier analysis, not only can we create diagnostic classifiers for predicting an exact metal contaminant from a large scale of contaminant pool with high prediction accuracy, but we can also identify valuable biomarkers to help understand the common and underlying toxic mechanisms induced by metals.

Effects of small nucleolar RNA SNORD44 on the proliferation, apoptosis and invasion of glioma cells.

To master the effect of small nucleolar RNA, SNORD44, on the proliferation, apoptosis and invasion of glioma cells and its relevant mechanism. SNORD44 and GAS5 expression in glioma tissues and cells was detected through qRT-PCR. Then, the glioma cell lines (U87 and U251) were divided into different groups with different treatments. Cell proliferation was determined by MTT assay, while the abilities of the cell migration and invasion were measured by wound-healing test and Transwell assay, respectively. Cell apoptosis were detected by flow cytometry and TUNEL assay. The expression of apoptosis proteins was quantified through Western blotting. Finally, the xenograft models were established on nude mice to investigate the effects of SNORD44 on the growth of glioma and the expressions of Ki67, MMP2 and MMP9 in vivo. SNORD44 and GAS5 were down-regulated in glioma tissues and cells in a positive correlation. Either SNORD44 or GAS5 overexpression decreased the proliferation, invasion and migration of U87 and U251 cells with the up-regulation of apoptosis rates, as well as the expressions of cleaved PARP, caspase 3, caspase 8 and caspase 9. Moreover, the in vivo experiment showed that overexpression of SNORD44 blocked the growth of glioma xenograft in nude mice accompanying with the inhibition of Ki67, MMP2 and MMP9 expressions. The combination overexpression of SNORD44 and GAS5 gained better inhibitory effects on glioma cells. Overexpression of SNORD44 and GAS5 activate the caspase-dependent apoptosis pathway to facilitate the apoptosis with the inhibited proliferation, invasion and migration of glioma cells.

Global lipidomics reveals two plasma lipids as novel biomarkers for the detection of squamous cell lung cancer: A pilot study.

Lipids are known to serve important roles in energy storage, membrane structure and signal transduction as well as in human cancers. In the present study, lipidomics was employed in order to identify plasma lipid markers for the early detection of lung cancer. Mass spectrometry was performed to profile 390 individual lipids in 44 plasma samples obtained from a training discovery cohort, which included 22 patients with squamous cell lung carcinoma (SqCC) and 22 high-risk individuals. An additional cohort that included 22 high-risk individuals and 22 patients with SqCC was further used for validation. During the training stage, a total of 20 distinct lipids that were significantly distributed between the high-risk and SqCC cases, were identified. A panel of 2 lipid markers (C18:2 cholesterol esters and sphingomyelin 22:0) were then further defined using the training accuracy values of 95.5% sensitivity, 90.9% specificity and 95.2% area under the receiver operating characteristic curve (AUC). The validation accuracy values applied for the additional cohort were 93.9% sensitivity, 92.9% specificity and 98.7% AUC. Thus, in the present study, 2 lipid markers that were able to discern SqCC patients from high-risk individuals with a high sensitivity, specificity and accuracy, were identified. These results may provide vital information for the development of a quick and safe blood test for the early diagnosis of SqCC.

Epigallocatechin-3-gallate inhibits growth and induces apoptosis in esophageal cancer cells through the demethylation and reactivation of the p16 gene.

The present study aimed to investigate the effect of treatment with epigallocatechin-3-gallate (EGCG) on the human esophageal cancer cell line ECa109 and elucidate the associated underlying mechanisms. ECa109 cells were cultured and treated with increasing concentrations of EGCG for various durations. Cell viability was evaluated using the MTT assay and apoptosis was detected using flow cytometry. The methylation status of the cyclin-dependent kinase inhibitor 2A (p16) gene was analyzed using the methylation-specific polymerase chain reaction (PCR). p16 mRNA and protein expression was measured using reverse transcription-quantitative PCR and western blot analysis, respectively. The results of the present study demonstrated that, following treatment with EGCG, ECa109 cell viability was significantly decreased, while the rate of apoptosis was significantly increased (P<0.01), in a dose- and time-dependent manner. Following treatment of ECa109 cells with EGCG, p16 gene demethylation, and its mRNA and protein expression, were significantly increased compared with the untreated cells (P<0.01). EGCG may induce ECa109 cell apoptosis and inhibit cell growth through p16 gene demethylation, which restores its expression.

Expression levels of resistant genes affect cervical cancer prognosis.

Tumor cells may develop multidrug resistance (MDR) to various chemotherapy regimens. Such resistance reduces the sensitivity of cells to chemotherapy drugs, leading to the failure of cervical cancer (CC) treatment and disease progression. The present study aimed to investigate the role of MDR1, lung resistance protein (LRP) and placental glutathione S­transferase π 1 (GSTP1) in CC and MDR, and the prognostic value of these genes. The mRNA expression levels of these resistance­associated genes were determined in 47 CC and 20 healthy cervical tissue samples. Subsequently, the data was analyzed alongside clinicopathological parameters. The mRNA expression levels of MDR1, LRP and GSTP1 in CC were 0.57±0.32, 0.58±0.29 and 0.44±0.24, respectively, whereas those in healthy cervical tissues were 0.19±0.10, 0.17±0.14 and 0.18±0.10, respectively. Therefore, the expression levels of these genes were significantly greater in CC compared with healthy cervical tissue (P<0.05). mRNA expression levels of MRD1 were increased in the well differentiated group (0.68±0.27) compared with the poorly differentiated group (0.38±0.33; P<0.05). No significant differences were observed between LRP and GSTP1 mRNA expression levels and tumor differentiation or clinical stage of the patients (P>0.05). Multivariate logistic regression indicated that the degree of differentiation and the MDR1 gene expression levels were predictors of CC prognosis (P<0.05). The survival rate of patients in the MDR1­negative group was significantly greater compared with the MDR1­positive group (P<0.05). The results of the present study therefore suggested that MDR1 gene expression is a predictor of poor survival in CC.

Global lipidomics identified plasma lipids as novel biomarkers for early detection of lung cancer.

PURPOSE: Lipids play roles in membrane structure, energy storage, and signal transduction as well as in human cancers. Here we adopt lipidomics to identify plasma lipid markers for early screening and detection of lung cancer. EXPERIMENTAL DESIGN: Using mass spectrometry, we profiled 390 individual lipids using training and validation strategy in a total of 346 plasma samples from 199 early NSCLC patients, including 113 adenocacinoma and 86 squamous cell cancers (SqCC), and from 147 healthy controls. RESULTS: In the training stage, we found distinct lipid groups that were significantly distributed between NSCLC cases and healthy controls. We further defined a panel of four lipid markers (LPE(18:1), ePE(40:4), C(18:2)CE and SM(22:0)) for prediction of early cancer with a accuracy of 82.3% AUC (Area under ROC curve), sensitivity of 81.9% and specificity of 70.7% at the training stage and yielded the predictive power with accuracy (AUC,80.8%), sensitivity 78.7%, specificity 69.4% and in the validation stage. CONCLUSIONS: Using lipidomics we identified several lipid markers capable of discerning early stage lung carcinoma from healthy individuals, which might be further developed as a quick, safe blood test for early diagnosis of this disease.

Relationship between the expression of MDR1 in hepatocellular cancer and its biological behaviors.

OBJECTIVE: By the detection of HBV infection, AFP and AST, the targets of biological behavior and the gene expression of multi-drug resistance gene 1 (MDR1) in hepatocellular carcinoma (HCC), we investigate characteristics of the expression of MDR1 in HCC and its relationship with HCC biological behavior. METHODS: Using real-time fluorescence quantitative PCR (FQ-PCR) to detect the expressions of MDR1 in 102 samples of HCC tissue and 20 samples of non-cancerous tissue, we analyze the relationship between expressions of MDR1 and biological characteristics of HCC. RESULTS: The expression of MDR1 in HCC is 0.55 ± 0.27, and in normal liver tissues is 0.23 ± 0.10, respectively. The expression in HCC is higher than it in normal liver tissue, the difference is statistically significant (P<0.05) and the difference between the expression and the HCC envelopes is statistically significant, and the expression increases along with the increase of Edmondson classification (P<0.05). HBV infection, AFP positive, the rise of AST, all these factors have positive correlations with the expression (r=0.463, 0.473, 0.299). In MDR1 expressions of HCC patients, the survival curve of the negative is higher than that of the positive, but the difference is not statistically significant. CONCLUSION: There are drug resistance phenomena in HCC, MDR1 expression may play an important role in primary HCC drug resistance. HBV infection can be detected as a reference indicator of HCC chemotherapy resistance, plasma levels of AFP, AST can be used as a reference index change dynamic monitoring of MDR1 expression.

Hepatitis B virus infection in hepatocellular carcinoma tissues upregulates expression of DNA methyltransferases.

PURPOSE: Our previous research identified that Hepatitis B virus (HBV) infection results in the increased methylation of p16; however, the mechanism(s) of the methylation changes observed following HBV infection are yet to be deduced. DNA methylation is governed by the interaction of DNA methyltransferases (DNMT). To investigate the expression of DNMT in cancerous tissue, cirrhotic tissues and non-cancerous tissue, we examined the relationship between HBV infection and DNMT expression. METHODS: We compared the mRNA expression levels of the four DNMTs in cancerous, cirrhotic and matched non-cancerous tissues of HCC with HBV infection by real-time PCR. RESULTS: The results showed that compared with the level in the corresponding non-cancerous liver tissues, the levels of DNMT1, DNMT3A and DNMT3B were elevated in 54.5%, 68.2% and 38.6% of cancerous tissues and 31.4%, 40% and 25.8% of cirrhotic tissues, respectively. The average mRNA expression for DNMT2 in cancerous and cirrhotic tissues of HCC was not significantly different from that in the corresponding non-cancerous liver tissues. In HBV-associated tissue samples, both the average level and the elevated frequency of DNMT1, DNMT3A and DNMT3B mRNA expression were significantly higher than in non-HBV-associated cirrhotic and cancerous tissues; even in non-cancerous tissues, the mRNA levels of DNMT1 and DNMT3A in HBV-associated samples were significantly higher than in the non-HBV-associated samples. Correlations analysis demonstrated a significant association between HBV infection and the overexpression of DNMTs and p16 methylation. CONCLUSIONS: The results of our current study suggest that persistent HBV infection can stimulate the overexpression of DNMTs, particularly DNMT1, DNMT3A and DNMT3B, which may result in the hyper-methylation/inactivation of p16, thus indirectly regulating the progression of hepatocellular carcinogenesis.

Nonlinear dose-response relationship between radon exposure and the risk of lung cancer: evidence from a meta-analysis of published observational studies.

Although radon exposure (RE) has been confirmed to increase the risk of lung cancer (LC), questions remain about the shape of the dose-response relationship between RE and the risk of LC. We carried out a dose-response meta-analysis to investigate and quantify the potential dose-response association between residential and occupational exposure to radon and the risk of LC. All cohort and case-control studies published in English and Chinese on Embase, PubMed, and China National Knowledge Infrastructure (CNKI) digital databases through November 2013 were identified systematically. We extracted effect measures (relative risk, odds ratio, standardized mortality ratio, standardized incidence ratio, or standardized rate ratio) from individual studies to generate pooled results using meta-analysis approaches. We derived meta-analytic estimates using random-effects models taking into account the correlation between estimates. Restricted cubic splines and generalized least-squares regression methods were used to model a potential curvilinear relationship and to carry out a dose-response meta-analysis. Stratified analysis, sensitivity analysis, and assessment of bias were performed in our meta-analysis. Sixty publications fulfilling the inclusion criteria for this meta-analysis were finally included. Occupational RE was associated with LC [risk ratio 1.86, 95% confidence interval (CI)=1.67-2.09; I²=92.2%; 27 prospective studies], for pooled risk estimate of the: standardized mortality ratio [2.00 (95% CI=1.82-2.32)]; standardized incidence ratio [1.45 (95% CI=1.20-1.74)]; relative risk [2.10 (95% CI=1.64-2.69)]. In a subgroup analysis of uranium miners and residents exposed to occupational uranium, the summary risk was 2.23 (95% CI=1.86-2.68) and 1.23 (95% CI=1.05-1.44). The overall meta-analysis showed evidence of a nonlinear association between RE and the risk of LC (P(nonlinearity)<0.014); in addition, the point value of residential radon also improved the results quantitatively, where odds ratios were 1.11 (95% CI=1.07-1.15) and 1.21 (95% CI=1.14-1.29) when the radon concentration was at the point of 100 and 200 Bq/m³ compared with the lowest. For 17 prospective studies with at least three categories of occupational cumulative radon dose, the dose-risk model estimated a risk ratio of 1.26 (95% CI=1.21-1.30) for 100 working level months and 1.51 (95% CI=1.38-1.65) for 200 working level months, respectively. The assessment of risk of bias within individual studies and across studies indicated risk that was unlikely to alter these results markedly. This meta-analysis shows a nonlinear dose-response association between environmental RE and the risk of LC. This increased risk is particularly apparent when the cumulative exposure to radon is well beyond that resulting from exposure to the recommended limit concentration for a prolonged period of time.

Promoter hypermethylation of p14 (ARF) , RB, and INK4 gene family in hepatocellular carcinoma with hepatitis B virus infection.

Both hepatitis B virus (HBV) and gene methylation play important roles in hepatocarcinogenesis. However, their association between HBV infection and gene methylation is not fully understood. Cell cycle control involving RB1 gene-related cell inhibitors is one of the main regulatory pathways were reported to be altered in hepatocellular carcinoma (HCC). The purpose of this research is to assess the methylation status of p14 (ARF) and INK4 gene family (p14 (ARF) , p15 (INK4B) , p16 (INK4A) , and p18 (INK4C) ) in HCC with HBV infection and HCC without it, and discuss possible role of HBV-induced hypermethylation in the mechanism of hepatocarcinogenesis. Methylation status of RB, p14 (ARF) , and INK4 gene family in 64 case of HCC with HBV infection and 24 cases without it were detected by methylation-specific polymerase chain reaction, and HBV-DNA of the plasma were detected by quantitative real-time polymerase chain reaction. p14 (ARF) , p15 (INK4B) , p16 (INK4A) , and RB hypermethylation were observed in 30 (34.1%), 50 (56.8%), 62 (70.5%), and 24(27.3%) of 88 hepatocellular carcinomas, respectively. Methylation frequencies of them between HCC with HBV infection and HCC without it were 43.8% versus 8.3 % (p14 (ARF) ), 68.9% versus 25% (p15 (INK4B) ), 90.6% versus 16.7% ( p16 (INK4A) ), and 28.1 % versus 25% (RB), respectively. In HBV-associated HCC, the numbers of methylated genes were also more than HCC without virus infection, more than two methylated genes were seen in 48 of 64 (75 %) cases; more than three methylated genes were found in 32 of 64 (50%); correspondently, no one case has more than two genes methylated. p18 (INK4C) methylation product was not found in cancerous or non-cancerous tissues of 88 HCC. HBV infection is associated with p14 (ARF) , p15 (INK4B) , p16 (INK4A) , and RB gene methylation (P = 0.048, 0.035, 0.02); HBV-DNA replication is associated with p14 (ARF) , p15 (INK4B) , p16 (INK4A) , and RB gene methylation (P = 0.048, 0.035, 0.02); high rate of p14 (ARF) , p15 (INK4B) , and p16 (INK4A) in HCC with HBV infection suggests that HBV-induced hypermethylation may be one of the mechanisms of HBV involved in hepatocellular carcinogenesis.