Ozlen Konu

Metabolic dysfunction-associated steatotic liver disease (MASLD) is linked to western diet and sedentary lifestyle. While larval zebrafish are powerful discovery tools, standardized diets inducing early-stage MASLD are lacking. Here, we developed and early-stage zebrafish MASLD model (9–12 days post fertilization), using a custom western diet (WD) enriched in palmitate, cholesterol, and fructose. Time dependent fat accumulation and gut-liver histopathological changes were assessed, alongside affordable bulk RNA sequencing across diets and time points. The WD effectively induced hepatic steatosis and hepatocyte ballooning, alongside lipid accumulation in the intestinal bulb. While boiled egg yolk (BEY) triggers strong lipid accumulation, it also induces hepatic sinusoid lipid accumulation and dilation. High throughput transcriptomic analysis revealed that WD triggers a suppression of cholesterol and lipid biosynthesis while BEY activates cholesterol biosynthesis and cyp7a1 expression compared to the regular diet fed larvae with same regime. WD further activated lipid transport signatures and stress-adaptive ribosome biogenesis by 12 dpf. This study features WD as an effective inducer of early MASLD in early-stage zebrafish larvae at a stage amenable to larval drug screening.

Metabolic dysfunction-associated steatotic liver disease (MASLD), the leading cause of chronic liver pathologies worldwide, represents a growing clinical burden. Its diagnosis remains reliant on liver biopsy that limits early detection and the ability to capture molecular changes across disease progression. A systematic understanding of stage-dependent gene expression changes is essential to identify biomarkers and effectively characterize disease mechanisms. Therefore recent studies provided databases for searching genes as well as prediction of multi-gene signatures for disease progression. However, there is still a need for interactive and comprehensive meta-analysis of datasets of MASLD patients with available histological metadata. Herein, we performed a meta-analysis of RNA-seq datasets using NAFLD Activity Score (NAS; n = 897) and fibrosis stage (n = 856) upon conducting pairwise comparisons across histological stages and identified differentially expressed genes associated with disease progression. Most importantly, we provide our findings via a dedicated web server, the MASLD-META NETWORK ( https://masld.scilicium.com ), enabling users to interactively explore meta-analysis results across diverse network modalities. In addition, we characterized gene expression dynamics across increasing disease stages to identify consistent progression-associated pathways using Louvain clustering. Network-based parameters such as centrality in combination with meta-analysis scores further highlighted central genes and pathways implicated in disease mechanisms. Accordingly, MASLD-META NETWORK enabled an integrative reassessment of recently published gene signatures, identifying COL1A1, COL3A1, THBS2, FBLN5, and PDGFA as the most central genes, and SULF2, MMP14, IL32, GPNMB, and COL3A1 as candidate markers of earlier transcriptional alterations. Network analysis of MASLD associated biological modules further identified LAMA2 and LAMA3 as previously unrecognized central candidate targets.

Isoxazole derivatives have emerged as promising scaffolds in anticancer drug discovery, yet their therapeutic potential remains to be fully harnessed. Here, we report on the synthesis and biological evaluation of two novel biotin-conjugated isoxazole derivatives (C160 and C161) related to the parent compound EB38. Across a panel of liver, prostate, and breast cancer cell lines, both derivatives exhibited significantly enhanced antiproliferative and pro-apoptotic activities compared to EB38, with consistently lower IC₅₀ values in 2D cultures and superior efficacy in 3D spheroid models. Mechanistic studies revealed that C160 and C161 robustly inhibit phosphorylation of JAK1 and STAT1, thereby suppressing JAK/STAT signaling and inducing apoptotic marker cleavage (PARP, Caspase-3, Caspase-7). Direct target engagement was further validated by CETSA and DARTS assays, which demonstrated thermal and proteolytic stabilization of endogenous JAK1 in the presence of C160. Molecular docking and HADDOCK simulations supported JAK1 as a direct cellular target, with binding affinities comparable to the clinically approved inhibitor Ruxolitinib. Importantly, zebrafish embryotoxicity assays confirmed that these derivatives do not elicit general cytotoxicity, even at doses substantially exceeding those effective in vitro. Collectively, our findings establish biotinylated isoxazole derivatives as potent JAK1-targeting anticancer agents with strong antiproliferative and pro-apoptotic activity, supporting their further development as promising candidates for targeted cancer therapy.

TP53 is the most frequently mutated transcription factor (TF) in sporadic cancers; and its targets exhibit dysregulation at the level of expression in both cancer and non-cancer pathologies. However, there is not yet a web-based tool that enables meta-analysis and visualization of TP53-related gene expression datasets, although several databases exist to access and annotate TP53 target information. To address this gap, we developed TP53-META, an interactive R Shiny-based web tool that allows users to upload and simultaneously analyze user's or integrated public RNA-seq datasets for effects of TP53 depletion and/or induction on the transcriptome. TP53-META can be used to visualize significant expression clusters as well as TF-TF, pathway-pathway, disease-gene and treatment-gene networks to determine the extent to which selected treatment contrasts are associated with TP53 regulated transcriptional programs. We demonstrated the utility of TP53-META through two case studies. In the first, using an in-house RNA-seq data from MCF7 cells treated with siRNA against a target gene of interest, i.e., CHRNA5, alone or in combination with an siRNA against TP53, we identified transcriptomic changes induced by CHRNA5 depletion that were either associated with TP53 signaling or maintained independently of TP53 by comparing with selected public datasets in TP53-META. In the second, we demonstrated the user data upload functionality of TP53-META before meta-analysis and extracted commonly modulated TP53-related genes in liver fibrosis using public RNA-seq datasets. TP53-META is available at http://konulabapps.bilkent.edu.tr:3838/TP53-Meta1.5/ and the docker image is downloadable from https://github.com/erenkumak/TP53-Meta. By facilitating meta-analysis, clustering, and network-based visualizations, TP53-META enables researchers to efficiently integrate and explore TP53-related transcriptomic datasets from diverse sources, and help uncover robust expression patterns, and investigate context-specific TP53 functions.

Small scale molecular network patterns and motifs are crucial for systems level understanding of cellular information transduction. A subgroup of such patterns consists of only 2 molecules, which we named as mutually acting pairs. Using randomizations, we statistically explored such gene pair designs, i.e. mutually positive (PP) or negative (NN) and positive-negative (PN) pairs, in two comprehensive and distinct large-scale molecular networks from literature; the human protein signaling network (PSN) and the human gene regulatory network (GRN). While the numbers of NN and PN pairs were significantly higher, the number of PP pairs was significantly lower than randomly expected values. Genes participating in mutual pairs were more connected than other genes. The connectivity of mutual gene pairs differed between the two networks. NN genes were more connected than PP and PN in GRN for all types of degree values, including in, out, positive or negative connections, but less connected for in-degree and more connected for out-degree values in PSN. They also had significantly high number of intersections with each other and PN pairs than randomly expected values, indicating potential cooperative mechanisms. The three mutual interaction designs we examined had distinct RNA and protein expression correlation characteristics. NN protein pairs were uniquely over-represented across normal tissue samples, whose negative correlations were lost across cancer tissue samples. PP and PN pairs showed non-random positive RNA or protein expression correlation across normal or cancer tissue samples. Moreover, we developed an online tool, i.e., MGPNet, for further user specific analysis of mutual gene pairs. For example, we identified SNCA with significantly enriched negatively correlated NN pairs with ubiquitin-proteasome members only in normal tissues. Unique non-random characteristics of mutual gene/protein pairs identified in two different comprehensive human molecular networks could provide valuable information for a better understanding of molecular design principles between normal and cancer states.

Phenothiazines (PTZ) are antipsychotics known to modulate a variety of neurotransmitter activities that include dopaminergic and cholinergic signaling and have been identified as potential anticancer agents in vitro. However, it is important to also test whether a highly cytotoxic, repurposed, or novel PTZ has low toxicity and neuromodulatory activity in vivo using vertebrate model organisms, such as zebrafish. In this study, we synthesized novel phenothiazines and screened them in vitro in liver cancer and in vivo in zebrafish embryos/larvae. The syntheses of several intermediate PTZ 10-yl acyl chlorides were followed by elemental analysis and determination of 1H NMR and 13C NMR mass (ESI+) spectra of a large number of novel PTZ 10-carboxamides. Cytotoxicities of 28 PTZ derivatives (1–28) screened against Hep3B and SkHep1 liver cancer cell lines revealed five intermediate and five novel leads along with trifluoperazine (TFP), prochlorperazine (PCP), and perphenazine, which are relatively more cytotoxic than the basic PTZ core. Overall, the derivatives were more cytotoxic to Hep3B than SkHep1 cells. Moreover, in silico target screening identified cholinesterases as some of the commonest targets of the screened phenothiazines. Interestingly, molecular docking studies with acetylcholinesterase (AChE) and butyrylcholinesterase proteins showed that the most cytotoxic compounds 1, 3, PCP, and TFP behaved similar to Huprin W in their amino acid interactions with the AChE protein. The highly cytotoxic intermediate PTZ derivative 1 exhibited a relatively lower toxicity profile than those of 2 and 3 during the zebrafish development. It also modulated in vivo the cholinesterase activity in a dose-dependent manner while significantly increasing the total cholinesterase activity and/or ACHE mRNA levels, independent of the liver cancer cell type. Our screen also identified novel phenothiazines, i.e., 8 and 10, with significant cytotoxic and cholinesterase modulatory effects in liver cancer cells; yet both compounds had low levels of toxicity in zebrafish. Moreover, they modulated the cholinesterase activity or expression of ACHE in a cancer cell line-specific manner, and compound 10 significantly inhibited the cholinesterase activity in zebrafish. Accordingly, using a successful combination of in silico, in vitro, and in vivo approaches, we identified several lead anticancer and cholinesterase modulatory PTZ derivatives for future research.

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.

Zebrafish as a preclinical drug induced liver injury (DILI) model provides multiple advantages ranging from ease of breeding and maintenance, availability of different strains and transgenic fish amenable to study liver function, and highly conserved liver structure and function with the human liver. In this review, the authors have aimed to provide an account of the metabolic enzymes that take roles in drug detoxification in both human and zebrafish in a comparative manner and exemplify several recent models in studying liver functionality. Moreover, the authors emphasize the difficulties associated with studying idiosyncratic DILI in preclinical models and propose that zebrafish could be an important complement to mice in testing functions of genes that are associated with DILI with respect to different drugs in human genome-wide association studies (GWAS) Catalog. Finally, this review highlights the state-of-the-art in the development of novel transgenic reporter strains that can be used to study degree and molecular mechanisms of hepatotoxicity caused by drugs in zebrafish. All of these will help researchers to use effectively the available resources in the zebrafish DILI models, while advocating potential leads that can be taken to provide advancements in a better understanding and treatment of DILI.

Regulation of intracellular calcium concentrations, [Ca ⁺⁺ ] _i is important in maintaining the viability of normal as well as cancer cells and can be mediated by tumor microenvironment. Calcium release-activated calcium channel protein (ORAI) calcium channels on the plasma membrane (PM) become physically connected by stromal interaction molecules (STIMs) to the endoplasmic reticulum (ER), on which paralogous receptors of inositol phosphate and of ryanodine are also present along with ATP2A/SERCA (sarco/endoplasmic reticulum calcium ATPases) subunits (also known as PM-ER geneset). Proper expression of this functionally and physically interconnected geneset is essential for the maintenance of [Ca ⁺⁺ ] _i , yet has not been interrogated as a whole for its role in cancer prognosis using multivariable Cox regression. In the present study, we examined whether the expression profile of the PM-ER geneset exhibited prognostic significance across different cancers found in The Cancer Genome Atlas (TCGA) by generating gene-cancer-by-survival networks, in which the nodes represented either genes or cancers and the edges, the logarithmically transformed hazard ratios for overall survival (OS). We then applied network clustering to identify the gene-cancer subnetworks with high connectivity, among which uveal melanoma (UVM) emerged exhibiting the highest degree of genes ( k = 10). BAP1 , a well-known [Ca ⁺⁺ ] _i regulator and a tumor suppressor, was not found to be significant in predicting OS by PM-ER geneset for UVM, yet it was for several others, including mesothelioma (MESO). Moreover, the best subset of the PM-ER geneset obtained by lasso predicted OS in the TCGA UVM cohort with an area under the receiver operating characteristics (AUC) of 91.4%, comparable to or better than previous prognostic signatures in the literature. Our findings indicate that homeostasis of [Ca ⁺⁺ ] _i is an essential determinant of prognosis in multiple cancers and particularly in UVM. The proposed gene-cancer-by-survival network approach can be extended with other gene sets as well as different survival types.