In this study, we demonstrate that various histopathological types of thyroid tumors have distinct miRNA profiles, which further differ within the same tumor type, reflecting specific oncogenic mutations. A limited set of miRNAs can be used diagnostically with high accuracy to detect thyroid cancer in the surgical and preoperative FNA samples.

We consider the problem of comparing the gene expression levels of cells grown under two different conditions using cDNA microarray data. We use a quality index, computed from duplicate spots on the same slide, to filter out outlying spots, poor quality genes and problematical slides. We also perform calibration experiments to show that normalization between fluorescent labels is needed and that the normalization is slide dependent and non-linear. A rank invariant method is suggested to select non-differentially expressed genes and to construct normalization curves in comparative experiments. After normalization the residuals from the calibration data are used to provide prior information on variance components in the analysis of comparative experiments. Based on a hierarchical model that incorporates several levels of variations, a method for assessing the significance of gene effects in comparative experiments is presented. The analysis is demonstrated via two groups of experiments with 125 and 4129 genes, respectively, in Escherichia coli grown in glucose and acetate.

With the rapid advances of various high-throughput technologies, generation of ‘-omics’ data is commonplace in almost every biomedical field. Effective data management and analytical approaches are essential to fully decipher the biological knowledge contained in the tremendous amount of experimental data. Meta-analysis, a set of statistical tools for combining multiple studies of a related hypothesis, has become popular in genomic research. Here, we perform a systematic search from PubMed and manual collection to obtain 620 genomic meta-analysis papers, of which 333 microarray meta-analysis papers are summarized as the basis of this paper and the other 249 GWAS meta-analysis papers are discussed in the next companion paper. The review in the present paper focuses on various biological purposes of microarray meta-analysis, databases and software and related statistical procedures. Statistical considerations of such an analysis are further scrutinized and illustrated by a case study. Finally, several open questions are listed and discussed.

Data mining was performed on 28 330 unique peptide tandem mass spectra for which sequences were assigned with high confidence. By dividing the spectra into different sets based on structural features and charge states of the corresponding peptides, chemical interactions involved in promoting specific cleavage patterns in gas-phase peptides were characterized. Pairwise fragmentation maps describing cleavages at all Xxx-Zzz residue combinations for b and y ions reveal that the difference in basicity between Arg and Lys results in different dissociation patterns for singly charged Arg- and Lys-ending tryptic peptides. While one dominant protonation form (proton localized) exists for Arg-ending peptides, a heterogeneous population of different protonated forms or more facile interconversion of protonated forms (proton partially mobile) exists for Lys-ending peptides. Cleavage C-terminal to acidic residues dominates spectra from singly charged peptides that have a localized proton and cleavage N-terminal to Pro dominates those that have a mobile or partially mobile proton. When Pro is absent from peptides that have a mobile or partially mobile proton, cleavage at each peptide bond becomes much more prominent. Whether the above patterns can be found in b ions, y ions, or both depends on the location of the proton holder(s) in multiply protonated peptides. Enhanced cleavages C-terminal to branched aliphatic residues (Ile, Val, Leu) are observed in both b and y ions from peptides that have a mobile proton, as well as in y ions from peptides that have a partially mobile proton; enhanced cleavages N-terminal to these residues are observed in b ions from peptides that have a partially mobile proton. Statistical tools have been designed to visualize the fragmentation maps and measure the similarity between them. The pairwise cleavage patterns observed expand our knowledge of peptide gas-phase fragmentation behaviors and may be useful in algorithm development that employs improved models to predict fragment ion intensities.

Women are twice as likely as men to develop major depressive disorder (MDD) and are more prone to recurring episodes. Hence, we tested the hypothesis that the illness may associate with robust molecular changes in female subjects, and investigated large-scale gene expression in the postmortem brain of MDD subjects paired with matched controls (n=21 pairs). We focused on the lateral/basolateral/basomedian (LBNC) complex of the amygdala as a neural hub of mood regulation affected in MDD. Among the most robust findings were downregulated transcripts for genes coding for GABA interneuron-related peptides, including somatostatin (SST), tachykinin, neuropeptide Y (NPY) and cortistatin, in a pattern reminiscent to that previously reported in mice with low BDNF. Changes were confirmed by quantitative PCR and not explained by demographic, technical or known clinical parameters. BDNF itself was significantly downregulated at the RNA and protein levels in MDD subjects. Investigating putative mechanisms, we show that this core MDD-related gene profile (including SST, NPY, TAC1, RGS4, CORT) is recapitulated by complementary patterns in mice with constitutive (BDNF-heterozygous) or activity-dependent (Exon IV knockout) decreases in BDNF function, with a common effect on SST and NPY. Together, these results provide both direct (low RNA/protein) and indirect (low BDNF-dependent gene pattern) evidence for reduced BDNF function in the amygdala of female subjects with MDD. Supporting studies in mutant mice models suggest a complex mechanism of low constitutive and activity-dependent BDNF function in MDD, particularly affecting SST/NPY-related GABA neurons, thus linking the neurotrophic and GABA hypotheses of depression.

We aimed to identify peripheral blood mononuclear cell (PBMC) gene expression profiles predictive of poor outcomes in idiopathic pulmonary fibrosis (IPF) by performing microarray experiments of PBMCs in discovery and replication cohorts of IPF patients. Microarray analyses identified 52 genes associated with transplant-free survival (TFS) in the discovery cohort. Clustering the microarray samples of the replication cohort using the 52-gene outcome-predictive signature distinguished two patient groups with significant differences in TFS. We studied the pathways associated with TFS in each independent microarray cohort and identified decreased expression of “The costimulatory signal during T cell activation” Biocarta pathway and, in particular, the genes CD28, ICOS, LCK, and ITK, results confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A proportional hazards model, including the qRT-PCR expression of CD28, ICOS, LCK, and ITK along with patient’s age, gender, and percent predicted forced vital capacity (FVC%), demonstrated an area under the receiver operating characteristic curve of 78.5% at 2.4 months for death and lung transplant prediction in the replication cohort. To evaluate the potential cellular source of CD28, ICOS, LCK, and ITK expression, we analyzed and found significant correlation of these genes with the PBMC percentage of CD4+CD28+ T cells in the replication cohort. Our results suggest that CD28, ICOS, LCK, and ITK are potential outcome biomarkers in IPF and should be further evaluated for patient prioritization for lung transplantation and stratification in drug studies.

H epatocellular carcinomas (HCC) and hepatoblastomas of childhood (HPBL) are two types of liver cancer with high mortality and morbidity and international prevalence. There have been several recent studies of patterns of gene expression and molecular classification of HCC. [1][2][3][4] The studies demonstrated that HCC can be clustered in subgroups of gene expression patterns that have different prognostic and clinical behavior. Other recent studies also examined similarities between HCC precursor lesions (low and high grade liver nodules) and demonstrated significant similarities but also differences between HCC and precursor lesions. 5 In this study, we also focused on gene expression of HCC and HPBL, but from a different perspective than previous studies. We utilized a set of tissues from normal liver (NL), HCC, HPBL and tumor adjacent (AT) tissues and determined gene expression patterns not as a ratio of tumor vs. normal, but rather as absolute separate values for each unique tissue. This allowed standard but stringent statistical analysis not feasible when gene expression is only viewed as a fold change over normal tissues. Identification of gene expression patterns of liver tumors from this perspective allows identification of the main differences between the tumor subtypes and the adjacent nontumor (but often cirrhotic) liver; it also offers the potential of defining new therapeutic and diagnostic modalities. Our findings include some genes already shown to increase in HCC, thus validating our overall approach. Our results also revealed many other genes, not so far involved with biology of liver tumors. In addition, we carried a whole genome analysis of 27 HCC and determined chromosomal loci with genetic abnormalities common to most of the HCC. Materials and MethodsSee Supplemental information at the HEPATOLOGY

With aging, significant changes in circadian rhythms occur, including a shift in phase toward a “morning” chronotype and a loss of rhythmicity in circulating hormones. However, the effects of aging on molecular rhythms in the human brain have remained elusive. Here, we used a previously described time-of-death analysis to identify transcripts throughout the genome that have a significant circadian rhythm in expression in the human prefrontal cortex [Brodmann’s area 11 (BA11) and BA47]. Expression levels were determined by microarray analysis in 146 individuals. Rhythmicity in expression was found in ∼10% of detected transcripts (P < 0.05). Using a metaanalysis across the two brain areas, we identified a core set of 235 genes (q < 0.05) with significant circadian rhythms of expression. These 235 genes showed 92% concordance in the phase of expression between the two areas. In addition to the canonical core circadian genes, a number of other genes were found to exhibit rhythmic expression in the brain. Notably, we identified more than 1,000 genes (1,186 in BA11; 1,591 in BA47) that exhibited age-dependent rhythmicity or alterations in rhythmicity patterns with aging. Interestingly, a set of transcripts gained rhythmicity in older individuals, which may represent a compensatory mechanism due to a loss of canonical clock function. Thus, we confirm that rhythmic gene expression can be reliably measured in human brain and identified for the first time (to our knowledge) significant changes in molecular rhythms with aging that may contribute to altered cognition, sleep, and mood in later life.