Xinyu Wen

Serum microRNA characterization identifies miR-885-5p as a potential marker for detecting liver pathologies

Circulating miRNAs (microRNAs) are emerging as promising biomarkers for several pathological conditions, and the aim of this study was to investigate the feasibility of using serum miRNAs as biomarkers for liver pathologies. Real-time qPCR (quantitative PCR)-based TaqMan MicroRNA arrays were first employed to profile miRNAs in serum pools from patients with HCC (hepatocellular carcinoma) or LC (liver cirrhosis) and from healthy controls. Five miRNAs (i.e. miR-885-5p, miR-574-3p, miR-224, miR-215 and miR-146a) that were up-regulated in the HCC and LC serum pools were selected and further quantified using real-time qPCR in patients with HCC, LC, CHB (chronic hepatitis B) or GC (gastric cancer) and in normal controls. The present study revealed that more than 110 miRNA species in the serum samples and wide distribution ranges of serum miRNAs were observed. The levels of miR-885-5p were significantly higher in sera from patients with HCC, LC and CHB than in healthy controls or GC patients. miR-885-5p yielded an AUC [the area under the ROC (receiver operating characteristic) curve] of 0.904 [95% CI (confidence interval), 0.837–0.951, P<0.0001) with 90.53% sensitivity and 79.17% specificity in discriminating liver pathologies from healthy controls, using a cut off value of 1.06 (normalized). No correlations between increased miR-885-5p and liver function parameters [AFP (α-fetoprotein), ALT (alanine aminotransferase), AST (aspartate aminotransferase) and GGT (γ-glutamyl transpeptidase)] were observed in patients with liver pathologies. In summary, miR-885-5p is significantly elevated in the sera of patients with liver pathologies, and our data suggest that serum miRNAs could serve as novel complementary biomarkers for the detection and assessment of liver pathologies.

Serological AFP/Golgi protein 73 could be a new diagnostic parameter of hepatic diseases.

We have investigated the changing rule of serum form of GP73 (sGP73) in different hepato‐pathologic processes and identified the sGP73 role in inflammation, fibrosis and carcinogenesis since sGP73 has been regarded as a candidate tumor marker. Quantitative enzyme‐linked immunosorbent assay detected sGP73 in 535 subjects with hepatocellular carcinoma (HCC), liver cirrhosis (LC), hepatitis, focal nodular hyperplasia (FNH), angioma, intra‐hepatic cholangio‐carcinoma (ICC) and metastatic cancer from adenocarcinomas (MC). Median sGP73 in LC was higher than in HCC and hepatitis (p = 0.001), and sGP73 in all three groups were higher than those in healthy individuals (p < 0.001); sGP73 in LC patients with Child‐Pugh class A was lower than in class B and C (p = 0.001), no significant difference was found between early and advanced HCC groups (110.4 μg/L vs. 102.8 μg/L). AFP/GP73 had a sensitivity of 75.8% and specificity of 79.7% with an area under the receiver operating curve (AUROC) of 0.844 vs. 0.812 for AFP (p = 0.055) with a sensitivity of 95.2% and specificity of 47.1%; in detecting early HCC, AUROC of AFP/GP73 was 0. 804 vs. 0.766 for AFP (p = 0.086). sGP73 correlated with AST, AST/ALT, ALB, A/G and ALP in LC. The positive rate of sGP73 in angioma, FNH, ICC, and MC was 0, 50, 63.3, 53.3%, respectively; AFP/GP73 was 0.796 with the sensitivity of 81.4% and specificity of 70.0% when differentiating MC from AFP‐negative HCC. Increased sGP73 is related to hepatic impairment and chronic fibrosis, and when combined with AFP could improve the differential diagnosis of hepatic diseases.

Development of serum parameters panels for the early detection of pancreatic cancer

Early detection of pancreatic cancer is promising for improving clinical outcome; however, no effective biomarker has yet been identified. Here, we detected 61 clinical serum parameters in 200 healthy controls (Ctrls), 163 pancreatic ductal adenocarcinoma (PDAC) patients and 109 benign pancreatitis patients (Benign) in the training group. A metropolis algorithm with Monte Carlo simulation was used for identifying parameter panels. Sera from 183 Ctrl, 129 PDAC and 95 Benign individuals were used for cross‐validation. Samples from 77 breast, 72 cervical, 101 colorectal, 138 gastric, 108 prostate and 132 lung cancer patients were collected for evaluating cancer selectivity. A panel consisting of carbohydrate antigen (CA)19‐9, albumin (ALB), C‐reactive protein (CRP) and interleukin (IL)−8 had the highest diagnostic value for discriminating between PDAC and Ctrl. The sensitivity (SN) was 99.39% for all‐stage, 96.10% for early‐stage and 98.80% for advanced‐stage PDAC at 90% specificity (SP). In the validation group, the sensitivities were 93.80, 93.10 and 94.40%, respectively, at 90% SP. This panel also identified 80.52% of the breast cancer, 66.67% cervical cancer, 86.14% colorectal cancer, 89.86% gastric cancer, 71.30% prostate cancer and 93.85% lung cancer samples as non‐PDAC. The panel consisting of CA19‐9, carbon dioxide, CRP and IL‐6 panel had the highest diagnostic value for discriminating between PDAC and Benign. The SN was 74.23% for all‐stage, 75.30% for early‐stage and 74.40% for advanced‐stage PDAC at 90% SP. In the validation group, the sensitivities were 72.10, 76.10 and 67.20%, respectively, at 90% SP. Our parameter panels may aid in the early detection of PDAC to improve clinical outcome.

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

A novel mixed integer programming for multi-biomarker panel identification by distinguishing malignant from benign colorectal tumors

Multi-biomarker panels can capture the nonlinear synergy among biomarkers and they are important to aid in the early diagnosis and ultimately battle complex diseases. However, identification of these multi-biomarker panels from case and control data is challenging. For example, the exhaustive search method is computationally infeasible when the data dimension is high. Here, we propose a novel method, MILP_k, to identify serum-based multi-biomarker panel to distinguish colorectal cancers (CRC) from benign colorectal tumors. Specifically, the multi-biomarker panel detection problem is modeled by a mixed integer programming to maximize the classification accuracy. Then we measured the serum profiling data for 101 CRC patients and 95 benign patients. The 61 biomarkers were analyzed individually and further their combinations by our method. We discovered 4 biomarkers as the optimal small multi-biomarker panel, including known CRC biomarkers CEA and IL-10 as well as novel biomarkers IMA and NSE. This multi-biomarker panel obtains leave-one-out cross-validation (LOOCV) accuracy to 0.7857 by nearest centroid classifier. An independent test of this panel by support vector machine (SVM) with threefold cross validation gets an AUC 0.8438. This greatly improves the predictive accuracy by 20% over the single best biomarker. Further extension of this 4-biomarker panel to a larger 13-biomarker panel improves the LOOCV to 0.8673 with independent AUC 0.8437. Comparison with the exhaustive search method shows that our method dramatically reduces the searching time by 1000-fold. Experiments on the early cancer stage samples reveal two panel of biomarkers and show promising accuracy. The proposed method allows us to select the subset of biomarkers with best accuracy to distinguish case and control samples given the number of selected biomarkers. Both receiver operating characteristic curve and precision-recall curve show our methods consistent performance gain in accuracy. Our method also shows its advantage in capturing synergy among selected biomarkers. The multi-biomarker panel far outperforms the simple combination of best single features. Close investigation of the multi-biomarker panel illustrates that our method possesses the ability to remove redundancy and reveals complementary biomarker combinations. In addition, our method is efficient and can select multi-biomarker panel with more than 5 biomarkers, for which the exhaustive methods fail. In conclusion, we propose a promising model to improve the clinical data interpretability and to serve as a useful tool for other complex disease studies. Our small multi-biomarker panel, CEA, IL-10, IMA, and NSE, may provide insights on the disease status of colorectal diseases. The implementation of our method in MATLAB is available via the website: http://doc.aporc.org/wiki/MILP_k.

The differential diagnostic model for serous peptidomics in HBV carriers established by MALDI-TOF-MS analysis

OBJECTIVES Hepatitis B virus (HBV) can result in asymptomatic carrier (AsC) state or chronic inflammation of liver, which depends on the host immunity. We therefore investigated the peptidomic profiling in the process of HBV infection. DESIGN AND METHODS In this study, serum from 116 HBV infected (AsC and chronic hepatitis), 60 HBV-immunized and 70 normal subjects was treated with MB-WCX (weak cation exchange based magnetic beads) kits and analyzed by the Clinprot/Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF-MS) techniques. Purified serous proteins were subjected to FT-ICR-MS analysis, and Western blot further confirmed the results. RESULTS The specific model comprised of two peptides m/z 2882.89 and 4476.12 could distinguish HBV infected from healthy (HBV-immunized and normal) group and showed 95.5% of the sensitivity and 95.4% of the specificity by cross-validation analysis. 40/56 HBV infected and 43/50 healthy subjects could be correctly classified by the model. The area under the receiving operating curves (AUROC) of m/z 2882.89 and 4476.12, identified as subunits of fibrinogen beta chain (FBG) Bβ10-42 and nucleophosmin (NPM) respectively, were both up to 0.88 when discriminating AsC from the healthy group. The expression of Bβ10-42 and NPM decreased significantly in the plasma of HBV infected individuals by Western blot analysis. CONCLUSIONS There were specific serum peptide profilings for host responses to HBV infection, and m/z 2882.89 and 4476.12 could be valuable follow-up and prognostic tools for HBV infection.

Identification of MicroRNAs Involved in Growth Arrest and Apoptosis in Hydrogen Peroxide-Treated Human Hepatocellular Carcinoma Cell Line HepG2

Although both oxidative stress and microRNAs (miRNAs) play vital roles in physiological and pathological processes, little is known about the interactions between them. In this study, we first described the regulation of H2O2 in cell viability, proliferation, cycle, and apoptosis of human hepatocellular carcinoma cell line HepG2. Then, miRNAs expression was profiled after H2O2 treatment. The results showed that high concentration of H2O2 (600 μM) could decrease cell viability, inhibit cell proliferation, induce cell cycle arrest, and finally promote cell apoptosis. Conversely, no significant effects could be found under treatment with low concentration (30 μM). miRNAs array analysis identified 131 differentially expressed miRNAs (125 were upregulated and 6 were downregulated) and predicted 13504 putative target genes of the deregulated miRNAs. Gene ontology (GO) analysis revealed that the putative target genes were associated with H2O2-induced cell growth arrest and apoptosis. The subsequent bioinformatics analysis indicated that H2O2-response pathways, including MAPK signaling pathway, apoptosis, and pathways in cancer and cell cycle, were significantly affected. Overall, these results provided comprehensive information on the biological function of H2O2 treatment in HepG2 cells. The identification of miRNAs and their putative targets may offer new diagnostic and therapeutic strategies for liver cancer.

Prognostic value of serum leptin in advanced lung adenocarcinoma patients with cisplatin/pemetrexed chemotherapy

Cisplatin/pemetrexed chemotherapy has been established as a standard treatment in lung adenocarcinoma. However, the response to the cisplatin/pemetrexed combination varies considerably among patients due to individual variations. Thus, novel biomarkers are required to aid the prediction of the response to the cisplatin/pemetrexed combination. We hypothesized that leptin expression may be a determinant for prognosis in lung adenocarcinoma patients with cisplatin/pemetrexed chemotherapy. Serum from consenting patients with lung adenocarcinoma were obtained for the measurement of leptin and associated tumor biomarkers. Leptin expression was measured by radioimmunoassay. Carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), CA15-3, CA125, CA72-4, cytokeratin 19 fragment (CYFRA21-1) and neuron-specific enolase (NSE) expression were determined by electrochemiluminescence immunoassays. Serum squamous cell carcinoma antigen levels were measured using a microparticle enzyme immunoassay. The associations between serum leptin and tumor biomarker expression were evaluated by Spearman’s correlation analysis. Serum CEA, CA19-9, CA15-3, CA125, CA72-4, CYFRA21-1 and NSE levels showed no obvious difference among patients. However, a trend towards an improved prognosis was observed in patients with lower serum leptin at diagnosis and an increase during cisplatin/pemetrexed chemotherapy. The results indicated that the serum leptin level has prognostic indications in patients with advanced lung adenocarcinoma during cisplatin/pemetrexed chemotherapy, which indicates that it may be a useful marker for the prognosis of cancer patients undergoing chemotherapy treatment.

Identification and characterization of novel serum microRNAs in unstable angina pectoris and subclinical atherosclerotic patients.

BACKGROUND MicroRNAs (miRNAs) are involved in cardiac developmental and pathological processes, and serum profile is useful for identifying novel miRNAs. METHODS AND RESULTS Serum samples were collected from unstable angina pectoris (UAP) and subclinical atherosclerotic (AS) patients. Solexa sequencing was used to predict novel miRNAs in 15 control individuals, 15 AS patients and 15 UAP patients. After bioinformatics analysis and filtering out in the newest version of miRbase (version 20.0), three novel miRNAs were validated in 80 control individuals, 80 AS patients and 80 UAP patients by quantitative reverse transcriptase polymerase chain reaction. Two of the three novel microRNAs (N1 and N3) were expressed at the highest levels in the AS group. N1 had an area under curve (AUC) of 0.811 (95% confidence interval 0.743-0.880) for AS. N3 showed a moderate separation with an area under curve (AUC) of 0.748 (95% confidence interval 0.664-0.833) for AS. Combined the two novel microRNAs can significantly distinguish AS from control. CONCLUSIONS Three novel miRNAs were identified by Solexa sequencing and two of them may be new potential predictors for arthrosclerosis.

Clinical utility of serum tumor markers and cytokines in cervical cancer and neoplasia

a Li Juan, Hong-li Tong and Peng-jun Zhang contributed equally to this study. *Corresponding author: Ya-ping Tian , Department of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, 100853, P.R. China, E-mail: tianyp61@gmail.com Li Juan, Hong-li Tong, Peng-jun Zhang, Xin-yu Wen, Yan-hong Gao and Jing-zhu Nan: Department of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, 100853, P.R. China