Dys-regulated Gene Expression Networks by Meta-Analysis of Microarray Data on Oral Squamous Cell Carcinoma

Background: Oral squamous cell carcinoma (OSCC) is the sixth most common type of carcinoma worldwide. Development of OSCC is a multi-step process involving genes related to cell cycle, growth control, apoptosis, DNA damage response and other cellular regulators. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of OSCC gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets has opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated.

Results: In this work we performed a meta-analysis on four microarray and four datasets of gene expression data on OSCC in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Sixteen dys-regulated pathways implicated in OSCC were mined out from the four published datasets, and most importantly three pathways were first reported. Those regulatory pathways and biological processes which are significantly enriched have been investigated by means of literatures and meanwhile, four genes of the maximally altered pathways, ECM-receptor interaction, were validated and identified by qRT-PCR as a possible candidate of aggressiveness of OSCC.

Conclusion: we have developed a robust method for analyzing pathways altered in OSCC using three expression array data sets. This study sets a stage for the further discovery of the basic mechanisms that may underlie a diseased state and would help in identifying critical nodes in the pathway that can be targeted for diagnosis and therapeutic intervention. In addition, those who are interested in our approach can obtain the software package (MATLAB platform) by email freely

Serum N‐glycans outperform CA19‐9 in diagnosis of extrahepatic cholangiocarcinoma

Extensive efforts have been devoted to improve the diagnosis of extrahepatic cholangiocarcinoma (ECCA) due to its silent clinical character and lack of effective diagnostic biomarkers. Specific alterations in N‐glycosylation of glycoproteins are considered a key component in cancer progression, which can serve as a distinct molecular signature for cancer detection. This study aims to find potential serum N‐glycan markers for ECCA. In total, 255 serum samples from patients with ECCA (n = 106), benign bile tract disease (BBD, n = 60) and healthy controls (HC, n = 89) were recruited. Only 2 μL of serum from individual patients was used in this assay where the N‐glycome of serum glycoproteins was profiled by DNA sequencer‐assisted fluorophore‐assisted capillary electrophoresis (DSA‐FACE) technology. Multi‐parameter models were constructed by combining the N‐glycans and carbohydrate antigen 19‐9 (CA19‐9) which is currently used clinically. Quantitative analyses showed that among 13 N‐glycan structures, the bifucosylated triantennary N‐glycan (peak10, NA3F2) presented the best diagnostic performance for distinguishing ECCA from BBD and HC. Two diagnostic models (Glycotest1 and Glycotest2) performed better than single N‐glycan or CA19‐9. Additionally, two N‐glycan structures (peak9, NA3Fb; peak12, NA4Fb) were tightly related to lymph node metastasis in ECCA patients. In conclusion, sera of ECCA showed relatively specific N‐glycome profiling patterns. Serum N‐glycan markers and models are novel, valuable and noninvasive alternatives in ECCA diagnosis and progression monitoring.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139072/1/elps6272.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139072/2/elps6272_am.pd

Prediction of steady-state plasma concentrations of olanzapine in Chinese Han in patients based on a retrospective population pharmacokinetic model

Purpose: To develop robust methods of establishing a population pharmacokinetics (Pop-PK) model of olanzapine, using existing hospital in-patient information, in order to predict the steady-state plasma concentration of olanzapine tablets in Chinese Han inpatients, thus providing guidance for individualized therapy for mental disorders.Methods: A retrospective study analyzing and predicting the steady-state plasma olanzapineconcentration was performed using nonlinear mixed-effect modeling (Phoenix® NLME8). The effects of ten potential covariates, including age, gender, Body Mass Index, fasting lipid, family history, alcohol and smoking status in 107 Chinese Han patients with steady-state plasma olanzapine concentration were collected from the hospital information system (HIS) in Wuhan Mental Health Center from Feb 2017 to Jul 2019.Results: The final model was validated using bootstrap and visual predictive check (VPC) and was found to fit the one-compartment mixed error model. Smoking status was found to be the only factor affecting olanzapine tablets clearance. The standard Pop-PK parameters apparent volume of distribution (VL/F) and clearance (CL/F) were 223 L and 12.4 Lꞏh-1, respectively.Conclusion: The Pop-PK model for olanzapine established with the data from HIS is effective inpredicting the plasma olanzapine tablets concentration of individual Chinese in-patients. This Pop-PK model approach can now be adapted to optimize other antipsychotic drugs

Circulating miR-15b and miR-130b in serum as potential markers for detecting hepatocellular carcinoma: a retrospective cohort study

Objective: Serum α-fetoprotein (AFP) is the most commonly used biomarker for screening hepatocellular carcinoma (HCC) but fails to detect about half of the patients. Thus, we investigated if circulating microRNAs (miRNAs) could outperform AFP for HCC detection. Design: A retrospective cohort study. Setting: Two clinical centres in China. Participants: The exploration phase included 96 patients with HCC who received primary curative hepatectomy, and the validation phase included 29 hepatitis B carriers, 57 patients with HCC and 30 healthy controls. Main outcome measures: Expression of miRNAs was measured by real-time quantitative reverse transcription-PCR. Areas under receiver operating characteristic curves were used to determine the feasibility of using serum miRNA concentration as a diagnostic marker for defining HCC. A multivariate logistic regression analysis was used to evaluate performances of combined serum miRNAs. Results: In the exploration phase, miRNA profiling on resected tumour/adjacent non-tumour tissues identified miR-15b, miR-21, miR-130b and miR-183 highly expressed in tumours. These miRNAs were also detectable in culture supernatants of HCC cell lines and in serum samples of patients. Remarkably, these serum miRNAs were markedly reduced after surgery, indicating the tumour-derived source of these circulating miRNAs. In a cross-centre validation study, combined miR-15b and miR-130b demonstrated as a classifier for HCC detection, yielding a receiver operating characteristic curve area of 0.98 (98.2% sensitivity and 91.5% specificity). The detection sensitivity of the classifier in a subgroup of HCCs with low AFP (<20 ng/ml) was 96.7%. The classifier also identified early-stage HCC cases that could not be detected by AFP. Conclusion: The combined miR-15b and miR-130b classifier is a serum biomarker with clinical value for HCC screening.published_or_final_versio