SLIT-ROBO families of proteins mediate axon pathfinding and their expression is not solely confined to nervous system. Aberrant expression of SLIT-ROBO genes was repeatedly shown in a wide variety of cancers, yet data about their collective behavior in hepatocellular carcinoma (HCC) is missing. Hence, we quantified SLIT-ROBO transcripts in HCC cell lines, and in normal and tumor tissues from liver.

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures.

CpG hypermethylation in gene promoters is a frequent mechanism of tumor suppressor gene silencing in various types of cancers. It usually occurs at early steps of cancer progression and can be detected easily, giving rise to development of promising biomarkers for both detection and progression of cancer, including breast cancer. 5-aza-2'-deoxycytidine (AZA) is a DNA demethylating and anti-cancer agent resulting in induction of genes suppressed via DNA hypermethylation.

WDR81 (WD repeat-containing protein 81) is associated with cerebellar ataxia, mental retardation and disequilibrium syndrome (CAMRQ2, [MIM 610185]). Human and mouse studies suggest that it might be a gene of importance during neurodevelopment. This study aimed at fully characterizing the structure of the wdr81 transcript, detecting the possible transcript variants and revealing its expression profile in zebrafish, a powerful model organism for studying development and disease.

Background: Prognostic biomarkers for cancer have the power to change the course of disease if they add value beyond known prognostic factors, if they can help shape treatment protocols, and if they are reliable. The aim of this study was to identify such biomarkers for colon cancer and to understand the molecular mechanisms leading to prognostic stratifications based on these biomarkers. Methods and Findings: We used an in house R based script (SSAT) for the in silico discovery of stage-independent prognostic biomarkers using two cohorts, GSE17536 and GSE17537, that include 177 and 55 colon cancer patients, respectively. This identified 2 genes, ULBP2 and SEMA5A, which when used jointly, could distinguish patients with distinct prognosis. We validated our findings using a third cohort of 48 patients ex vivo. We find that in all cohorts, a combined ULBP2/SEMA5A classification (SU-GIB) can stratify distinct prognostic sub-groups with hazard ratios that range from 2.4 to 4.5 (p≤0.01) when overall- or cancer-specific survival is used as an end-measure, independent of confounding prognostic parameters. In addition, our preliminary analyses suggest SU-GIB is comparable to Oncotype DX colon(®) in predicting recurrence in two different cohorts (HR: 1.5-2; p≤0.02). SU-GIB has potential as a companion diagnostic for several drugs including the PI3K/mTOR inhibitor BEZ235, which are suitable for the treatment of patients within the bad prognosis group. We show that tumors from patients with worse prognosis have low EGFR autophosphorylation rates, but high caspase 7 activity, and show upregulation of pro-inflammatory cytokines that relate to a relatively mesenchymal phenotype. Conclusions: We describe two novel genes that can be used to prognosticate colon cancer and suggest approaches by which such tumors can be treated. We also describe molecular characteristics of tumors stratified by the SU-GIB signature.

microRNA expression and sequence analysis database (http://konulab.fen.bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.

Transcriptome experiments are performed to assess protein abundance through mRNA expression analysis. Expression levels of genes vary depending on the experimental conditions and the cell response. Transcriptome data must be diverse and yet comparable in reference to stably expressed genes, even if they are generated from different experiments on the same biological context from various laboratories. In this study, expression patterns of 9090 microarray samples grouped into 381 NCBI-GEO datasets were investigated to identify novel candidate reference genes using randomizations and Receiver Operating Characteristic (ROC) curves. The analysis demonstrated that cell type specific reference gene sets display less variability than a united set for all tissues. Therefore, constitutively and stably expressed, origin specific novel reference gene sets were identified based on their coefficient of variation and percentage of occurrence in all GEO datasets, which were classified using Medical Subject Headings (MeSH). A large number of MeSH grouped reference gene lists are presented as novel tissue specific reference gene lists. The most commonly observed 17 genes in these sets were compared for their expression in 8 hepatocellular, 5 breast and 3 colon carcinoma cells by RT-qPCR to verify tissue specificity. Indeed, commonly used housekeeping genes GAPDH, Actin and EEF2 had tissue specific variations, whereas several ribosomal genes were among the most stably expressed genes in vitro. Our results confirm that two or more reference genes should be used in combination for differential expression analysis of large-scale data obtained from microarray or next generation sequencing studies. Therefore context dependent reference gene sets, as presented in this study, are required for normalization of expression data from diverse technological backgrounds.

The zebrafish has become a popular model for studying normal brain aging due to its large fecundity, conserved genome, and available genetic tools; but little data exists about neurobiological age-related alterations. The current study tested the hypothesis of an association between brain aging and synaptic protein loss across males and females. Western blot analysis of synaptophysin (SYP), a presynaptic vesicle protein, and postsynaptic density-95 (PSD-95) and gephyrin (GEP), excitatory and inhibitory postsynaptic receptor-clustering proteins, respectively, was performed in young, middle-aged, and old male and female zebrafish (Danio rerio) brains. Univariate and multivariate analyses demonstrated that PSD-95 significantly increased in aged females and SYP significantly decreased in males, but GEP was stable. Thus, these key synaptic proteins vary across age in a sexually dimorphic manner, which has been observed in other species, and these consequences may represent selective vulnerabilities for aged males and females. These data expand our knowledge of normal aging in zebrafish, as well as further establish this model as an appropriate one for examining human brain aging.

As mutations in SARS-CoV-2 virus accumulate rapidly, novel primers that amplify this virus sensitively and specifically are in demand. We have developed a webserver named CoVrimer by which users can search for and align existing or newly designed conserved/degenerate primer pair sequences against the viral genome and assess the mutation load of both primers and amplicons. CoVrimer uses mutation data obtained from an online platform established by NGDC-CNCB (12 May 2021) to identify genomic regions, either conserved or with low levels of mutations, from which potential primer pairs are designed and provided to the user for filtering based on generalized and SARS-CoV-2 specific parameters. Alignments of primers and probes can be visualized with respect to the reference genome, indicating variant details and the level of conservation. Consequently, CoVrimer is likely to help researchers with the challenges posed by viral evolution and is freely available at http://konulabapps.bilkent.edu.tr:3838/CoVrimer/.

Cholinergic Receptor Nicotinic Alpha 5 (CHRNA5) is an important susceptibility locus for nicotine addiction and lung cancer. Depletion of CHRNA5 has been associated with reduced cell viability, increased apoptosis and alterations in cellular motility in different cancers yet not in breast cancer. Herein we first showed the expression of CHRNA5 was variable and positively correlated with the fraction of total genomic alterations in breast cancer cell lines and tumors indicating its potential role in DNA damage response (DDR). Next, we demonstrated that silencing of CHRNA5 expression in MCF7 breast cancer cell line by RNAi affected expression of genes involved in cytoskeleton, TP53 signaling, DNA synthesis and repair, cell cycle, and apoptosis. The transcription profile of CHRNA5 depleted MCF7 cells showed a significant positive correlation with that of A549 lung cancer cell line while exhibiting a negative association with the CHRNA5 co-expression profile obtained from Cancer Cell Line Encylopedia (CCLE). Moreover, it exhibited high similarities with published MCF7 expression profiles obtained from exposure to TP53 inducer nutlin-3a and topoisomerase inhibitors. We then demonstrated that CHRNA5 siRNA treatment reduced cell viability and DNA synthesis indicating G1 arrest while it significantly increased apoptotic sub-G1 cell population. Accordingly, we observed lower levels of phosphorylated RB (Ser807/811) and an increased BAX/BCL2 ratio in RNAi treated MCF7 cells. We also showed that CHRNA5 RNAi transcriptome correlated negatively with DDR relevant gene expression profile in breast cancer gene expression datasets while the coexposure to topoisomerase inhibitors in the presence of CHRNA5 RNAi enhanced chemosensitivity potentially due to reduced DDR. CHRNA5 RNAi consistently lowered total CHEK1 mRNA and protein levels as well as phosphorylated CHEK1 (Ser345) in MCF7 cells. We also detected a significant positive correlation between the expression levels of CHRNA5 and CHEK1 in CCLE, TCGA and METABRIC breast cancer datasets. Our study suggests CHRNA5 RNAi is associated with cell cycle inhibition, apoptosis as well as reduced DDR and increased drug sensitivity in breast cancer yet future studies are warranted since dose- and cell line-specific differences exist in response to CHRNA5 depletion. Gene expression microarray data can be accessed from GEO database under the accession number GSE89333.

Acetylcholinesterase (AChE), an enzyme responsible for degradation of acetylcholine, has been identified as a prognostic marker in liver cancer. Although in vivo Ache tumorigenicity assays in mouse are present, no established liver cancer xenograft model in zebrafish using an ache mutant background exists. Herein, we developed an embryonic zebrafish xenograft model using epithelial (Hep3B) and mesenchymal (SKHep1) liver cancer cell lines in wild-type and ache sb55 sibling mutant larvae after characterization of cholinesterase expression and activity in cell lines and zebrafish larvae. The comparison of fluorescent signal reflecting tumor size at 3-days post-injection (dpi) revealed an enhanced tumorigenic potential and a reduced migration capacity in cancer cells injected into homozygous ache sb55 mutants when compared with the wild-type. Increased tumor load was confirmed using an ALU based tumor DNA quantification method modified for use in genotyped xenotransplanted zebrafish embryos. Confocal microscopy using the Huh7 cells stably expressing GFP helped identify the distribution of tumor cells in larvae. Our results imply that acetylcholine accumulation in the microenvironment directly or indirectly supports tumor growth in liver cancer. Use of this model system for drug screening studies holds potential in discovering new cholinergic targets for treatment of liver cancers.

Senescence is a permanent proliferation arrest in response to cell stress such as DNA damage. It contributes strongly to tissue aging and serves as a major barrier against tumor development. Most tumor cells are believed to bypass the senescence barrier (become "immortal") by inactivating growth control genes such as TP53 and CDKN2A. They also reactivate telomerase reverse transcriptase. Senescence-to-immortality transition is accompanied by major phenotypic and biochemical changes mediated by genome-wide transcriptional modifications. This appears to happen during hepatocellular carcinoma (HCC) development in patients with liver cirrhosis, however, the accompanying transcriptional changes are virtually unknown. We investigated genome-wide transcriptional changes related to the senescence-to-immortality switch during hepatocellular carcinogenesis. Initially, we performed transcriptome analysis of senescent and immortal clones of Huh7 HCC cell line, and identified genes with significant differential expression to establish a senescence-related gene list. Through the analysis of senescence-related gene expression in different liver tissues we showed that cirrhosis and HCC display expression patterns compatible with senescent and immortal phenotypes, respectively; dysplasia being a transitional state. Gene set enrichment analysis revealed that cirrhosis/senescence-associated genes were preferentially expressed in non-tumor tissues, less malignant tumors, and differentiated or senescent cells. In contrast, HCC/immortality genes were up-regulated in tumor tissues, or more malignant tumors and progenitor cells. In HCC tumors and immortal cells genes involved in DNA repair, cell cycle, telomere extension and branched chain amino acid metabolism were up-regulated, whereas genes involved in cell signaling, as well as in drug, lipid, retinoid and glycolytic metabolism were down-regulated. Based on these distinctive gene expression features we developed a 15-gene hepatocellular immortality signature test that discriminated HCC from cirrhosis with high accuracy. Our findings demonstrate that senescence bypass plays a central role in hepatocellular carcinogenesis engendering systematic changes in the transcription of genes regulating DNA repair, proliferation, differentiation and metabolism.

The epithelial to mesenchymal transition (EMT) and the mesenchymal to epithelial transition (MET) are two critical biological processes that are involved in both physiological events such as embryogenesis and development and also pathological events such as tumorigenesis. They present with dramatic changes in cellular morphology and gene expression exhibiting acute changes in E-cadherin expression. Despite the comprehensive understanding of EMT, the regulation of MET is far from being understood. To find novel regulators of MET, we hypothesized that such factors would correlate with Cdh1 expression. Bioinformatics examination of several expression profiles suggested Elf3 as a strong candidate. Depletion of Elf3 at the onset of MET severely impaired the progression to the epithelial state. This MET defect was explained, in part, by the absence of E-cadherin at the plasma membrane. Moreover, during MET, ELF3 interacts with the Grhl3 promoter and activates its expression. Our findings present novel insights into the regulation of MET and reveal ELF3 as an indispensable guardian of the epithelial state. A better understanding of MET will, eventually, lead to better management of metastatic cancers.

Cluster analysis is one of the most widely used exploratory methods for visualization and grouping of gene expression patterns across multiple samples or treatment groups. Although several existing online tools can annotate clusters with functional terms, there is no all-in-one webserver to effectively prioritize genes/clusters using gene essentiality as well as congruency of mRNA-protein expression. Hence, we developed CAP-RNAseq that makes possible (1) upload and clustering of bulk RNA-seq data followed by identification, annotation and network visualization of all or selected clusters; and (2) prioritization using DepMap gene essentiality and/or dependency scores as well as the degree of correlation between mRNA and protein levels of genes within an expression cluster. In addition, CAP-RNAseq has an integrated primer design tool for the prioritized genes. Herein, we showed using comparisons with the existing tools and multiple case studies that CAP-RNAseq can uniquely aid in the discovery of co-expression clusters enriched with essential genes and prioritization of novel biomarker genes that exhibit high correlations between their mRNA and protein expression levels. CAP-RNAseq is applicable to RNA-seq data from different contexts including cancer and available at http://konulabapps.bilkent.edu.tr:3838/CAPRNAseq/ and the docker image is downloadable from https://hub.docker.com/r/konulab/caprnaseq.