Benchmarking the accuracy of structure-based binding affinity predictors on Spike-ACE2 deep mutational interaction set.

Since the start of COVID-19 pandemic, a huge effort has been devoted to understanding the Spike (SARS-CoV-2)-ACE2 recognition mechanism. To this end, two deep mutational scanning studies traced the impact of all possible mutations across receptor binding domain (RBD) of Spike and catalytic domain of human ACE2. By concentrating on the interface mutations of these experimental data, we benchmarked six commonly used structure-based binding affinity predictors (FoldX, EvoEF1, MutaBind2, SSIPe, HADDOCK, and UEP). These predictors were selected based on their user-friendliness, accessibility, and speed. As a result of our benchmarking efforts, we observed that none of the methods could generate a meaningful correlation with the experimental binding data. The best correlation is achieved by FoldX (R = -0.51). When we simplified the prediction problem to a binary classification, that is, whether a mutation is enriching or depleting the binding, we showed that the highest accuracy is achieved by FoldX with a 64% success rate. Surprisingly, on this set, simple energetic scoring functions performed significantly better than the ones using extra evolutionary-based terms, as in Mutabind and SSIPe. Furthermore, we demonstrated that recent AI approaches, mmCSM-PPI and TopNetTree, yielded comparable performances to the force field-based techniques. These observations suggest plenty of room to improve the binding affinity predictors in guessing the variant-induced binding profile changes of a host-pathogen system, such as Spike-ACE2. To aid such improvements we provide our benchmarking data at https://github.com/CSB-KaracaLab/RBD-ACE2-MutBench with the option to visualize our mutant models at https://rbd-ace2-mutbench.github.io/.

Alternative splicing and gene co-expression network-based analysis of dizygotic twins with autism-spectrum disorder and their parents.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high heritability, however, understanding the complexity of the underlying genetic basis has proven to be a challenging task. We hypothesized that dissecting the aberrations in alternative splicing (AS) and their effects on expression networks might provide insight. Therefore, we performed AS and co-expression analyses of total RNA isolated from Peripheral Blood Mononuclear Cells (PBMCs) of two pairs of dizygotic (DZ) twins with non-syndromic autism and their parents. We identified 183 differential AS events in 146 genes, seven of them being Simons Foundation Autism Research Initiative (SFARI) Category 1-3 genes, three of which had previously been reported to be alternatively spliced in ASD post-mortem brains. Gene co-expression analysis identified 7 modules with 513 genes, 5 of which were SFARI Category 1 or Category 2 genes. Among differentially AS genes within the modules, ZNF322 and NR4A1 could be potentially interesting targets for further investigations.

In Silico Methods for the Identification of Diagnostic and Favorable Prognostic Markers in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML), the most common type of acute leukemia in adults, is mainly asymptomatic at early stages and progresses/recurs rapidly and frequently. These attributes necessitate the identification of biomarkers for timely diagnosis and accurate prognosis. In this study, differential gene expression analysis was performed on large-scale transcriptomics data of AML patients versus corresponding normal tissue. Weighted gene co-expression network analysis was conducted to construct networks of co-expressed genes, and detect gene modules. Finally, hub genes were identified from selected modules by applying network-based methods. This robust and integrative bioinformatics approach revealed a set of twenty-four genes, mainly related to cell cycle and immune response, the diagnostic significance of which was subsequently compared against two independent gene expression datasets. Furthermore, based on a recent notion suggesting that molecular characteristics of a few, unusual patients with exceptionally favorable survival can provide insights for improving the outcome of individuals with more typical disease trajectories, we defined groups of long-term survivors in AML patient cohorts and compared their transcriptomes versus the general population to infer favorable prognostic signatures. These findings could have potential applications in the clinical setting, in particular, in diagnosis and prognosis of AML.

Differential expression of full-length and NH2 terminally truncated FAM134B isoforms in normal physiology and cancer.

Selective autophagy of the endoplasmic reticulum (ER), namely ER-phagy, is mediated by ER-localized receptors, which are recognized and sequestered by GABARAP/LC3B-decorated phagophores and transferred to lysosomes for degradation. Being one such receptor, FAM134B plays critical roles in cellular processes such as protein quality control and neuronal survival. FAM134B has also been associated with different cancers, although its exact role remains elusive. We report here that the FAM134B gene encodes not one but at least two different protein isoforms: the full-length and the NH2 terminally truncated forms. Their relative expression shows extreme variation, both within normal tissues and among cancer types. Expression of full-length FAM134B is restricted to the brain, testis, spleen, and prostate. In contrast, NH2 terminally truncated FAM134B is dominant in the heart, skeletal muscle, kidney, pancreas, and liver. We compared wild-type and knockout mice to study the role of the Fam134b gene in starvation. NH2 terminally truncated FAM134B-2 was induced in the liver, skeletal muscle, and heart but not in the pancreas and stomach following starvation. Upon starvation, Fam134b-/- mice differed from wild-type mice by less weight loss and less hyperaminoacidemic and hypocalcemic response but increased levels of serum albumin, total serum proteins, and α-amylase. Interestingly, either NH2 terminally truncated FAM134B or both isoforms were downregulated in liver, lung, and colon cancers. In contrast, upregulation was observed in stomach and chromophobe kidney cancers.NEW & NOTEWORTHY We reported tissues expressing FAM134B-2 such as the kidney, muscle, heart, and pancreas, some of which exhibit stimulated expression upon nutrient starvation. We also demonstrated the effect of Fam134b deletion during ad libitum and starvation conditions. Resistance to weight loss and hypocalcemia, accompanied by an increase in serum albumin and α-amylase levels, indicate critical roles of Fam134b in physiology. Furthermore, the differential expression of FAM134B isoforms was shown to be significantly dysregulated in human cancers.

Expression dynamics of repetitive DNA in early human embryonic development.

BACKGROUND: The last decade witnessed a number of genome-wide studies on human pre-implantation, which mostly focused on genes and provided only limited information on repeats, excluding the satellites. Considering the fact that repeats constitute a large portion of our genome with reported links to human physiology and disease, a thorough understanding of their spatiotemporal regulation during human embryogenesis will give invaluable clues on chromatin dynamics across time and space. Therefore, we performed a detailed expression analysis of all repetitive DNA elements including the satellites across stages of human pre-implantation and embryonic stem cells. RESULTS: We uncovered stage-specific expressions of more than a thousand repeat elements whose expressions fluctuated with a mild global decrease at the blastocyst stage. Most satellites were highly expressed at the 4-cell level and expressions of ACRO1 and D20S16 specifically peaked at this point. Whereas all members of the SVA elements were highly upregulated at 8-cell and morula stages, other transposons and small RNA repeats exhibited a high level of variation among their specific subtypes. Our repeat enrichment analysis in gene promoters coupled with expression correlations highlighted potential links between repeat expressions and nearby genes, emphasising mostly 8-cell and morula specific genes together with SVA_D, LTR5_Hs and LTR70 transposons. The DNA methylation analysis further complemented the understanding on the mechanistic aspects of the repeatome's regulation per se and revealed critical stages where DNA methylation levels are negatively correlating with repeat expression. CONCLUSIONS: Taken together, our study shows that specific expression patterns are not exclusive to genes and long non-coding RNAs but the repeatome also exhibits an intriguingly dynamic pattern at the global scale. Repeats identified in this study; particularly satellites, which were historically associated with heterochromatin, and those with potential links to nearby gene expression provide valuable insights into the understanding of key events in genomic regulation and warrant further research in epigenetics, genomics and developmental biology.

C-Reactive Protein and Platelet-Lymphocyte Ratio as Potential Tumor Markers in Low-Alpha-Fetoprotein Hepatocellular Carcinoma.

The hepatocellular carcinoma (HCC) tumor marker alpha-fetoprotein (AFP) is only elevated in about half of the HCC patients, limiting its usefulness in following the effects of therapy or screening. New markers are needed. It has been previously noted that the inflammation markers C-reactive protein (CRP) and platelet-lymphocyte ratio (PLR) are prognostically important and may reflect HCC aggressiveness. We therefore examined these 2 markers in a low-AFP HCC cohort and found that for HCCs > 2 cm, both markers significantly rise with an increasing maximum tumor diameter (MTD). We calculated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index value for each marker, and their area-under-the-curve values for each MTD group. Patients were dichotomized into 2 groups based on the CRP and PLR from the receiver-operating characteristic curve analysis. In the logistic regression models of the 4 different MTD patient groups, CRP and PLR levels were statistically significant to estimate MTD in univariate logistic regression models of MTD groups > 2 cm. CRP and PLR were then combined, and the combination was statistically significant to estimate MTD groups of 3-, 4-, and 5-cm cutoffs. CRP and PLR thus have potential as tumor markers for low-AFP HCC patients, and possibly for screening.

RTFAdb: A database of computationally predicted associations between retrotransposons and transcription factors in the human and mouse genomes.

In recent years, retrotransposons have gained increasing attention as a source of binding motifs for transcription factors (TFs). Despite the substantial roles of these mobile genetic elements in the regulation of gene expression, a comprehensive resource enabling the investigation of retrotransposon species that are bound by TFs is still lacking. Herein, I introduce for the first time a novel database called RTFAdb, which allows exploring computationally predicted associations between retrotransposons and TFs in diverse cell lines and tissues of human and mouse. My database, using over 3.000 TF ChIP-seq binding profiles collected from human and mouse samples, makes possible searching more than 1.500 retrotransposon species in the binding sites of a total of 596 TFs. RTFAdb is freely available at http://tools.ibg.deu.edu.tr/rtfa/ and has the potential to offer novel insights into mammalian transcriptional networks by providing an additional layer of information regarding the regulatory roles of retrotransposons.

PlanTEnrichment: A tool for enrichment analysis of transposable elements in plants.

Transposable elements (TEs) are mobile DNA sequences that play roles in gene regulation, and have a potential to influence the expression of nearby genes by functioning as cis-regulatory sequences. However, bioinformatics tools facilitating analysis of the associations between TEs and nearby genes in plants are still lacking. We therefore reanalyzed the comprehensive annotation data of gene models and TEs of 11 plant species available in Ensembl Plants database, and built an up-to-date, unique tool called PlanTEnrichment, enabling enrichment analysis of TEs located within the upstream regions of a given gene list. PlanTEnrichment takes, for example, a group of differentially expressed genes under a particular biological condition as input and returns the list of TEs associated with those genes, along with their calculated enrichment scores and statistical significances. PlanTEnrichment is freely available at http://tools.ibg.deu.edu.tr/plantenrichment/ and is likely to substantially enhance our understanding of the role of TEs in diverse biological processes.

Retinoids and EZH2 inhibitors cooperate to orchestrate anti-oncogenic effects on bladder cancer cells.

The highly mutated nature of bladder cancers harboring mutations in chromatin regulatory genes opposing Polycomb-mediated repression highlights the importance of targeting EZH2 in bladder cancer. Furthermore, the critical role of the retinoic acid signaling pathway in the development and homeostasis of the urothelium, and the anti-oncogenic effects of retinoids are well established. Therefore, our aim is to simultaneously target EZH2 and retinoic acid signaling in bladder cancer to potentiate the therapeutic response. Here we report that this coordinated targeting strategy stimulates an anti-oncogenic profile, as reflected by inducing a synergistic reduction in cell viability that was associated with increased apoptosis and cell cycle arrest in a cooperative and orchestrated manner. This study characterized anti-oncogenic transcriptional reprogramming centered on the transcriptional regulator CHOP by stimulating the endoplasmic reticulum stress response. We further portrayed a molecular mechanism whereby EZH2 maintains H3K27me3-mediated repression of a subset of genes involved in unfolded protein responses, reflecting the molecular mechanism underlying this co-targeting strategy. These findings highlight the importance of co-targeting the EZH2 and retinoic acid pathway in bladder cancers and encourage the design of novel treatments employing retinoids coupled with EZH2 inhibitors in bladder carcinoma.

Generation of Anterior Segment of the Eye Cells from hiPSCs in Microfluidic Platforms.

Ophthalmic diseases affect many people, causing partial or total loss of vision and a reduced quality of life. The anterior segment of the eye accounts for nearly half of all visual impairment that can lead to blindness. Therefore, there is a growing demand for ocular research and regenerative medicine that specifically targets the anterior segment to improve vision quality. This study aims to generate a microfluidic platform for investigating the formation of the anterior segment of the eye derived from human induced pluripotent stem cells (hiPSC) under various spatial-mechanoresponsive conditions. Microfluidic platforms are developed to examine the effects of dynamic conditions on the generation of hiPSCs-derived ocular organoids. The differentiation protocol is validated, and mechanoresponsive genes are identified through transcriptomic analysis. Several culture strategies is implemented for the anterior segment of eye cells in a microfluidic chip. hiPSC-derived cells showed anterior eye cell characteristics in mRNA and protein expression levels under dynamic culture conditions. The expression levels of yes-associated protein and transcriptional coactivator PDZ binding motif (YAP/TAZ) and PIEZO1, varied depending on the differentiation and growth conditions of the cells, as well as the metabolomic profiles under dynamic culture conditions.

mESAdb: microRNA expression and sequence analysis database.

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.

PlanTEnrichment: A How-to Guide on Rapid Identification of Transposable Elements Associated with Regions of Interest in Select Plant Genomes.

Transposable elements (TEs) are repeat elements that can relocate or create novel copies of themselves in the genome and contribute to genomic complexity and expansion, via events such as chromosome recombination or regulation of gene expression. However, given the large number of such repeats across the genome, identifying repeats of interest can be a challenge in even well-annotated genomes, especially in more complex, TE-rich plant genomes. Here, we describe a protocol for PlanTEnrichment, a database we created comprising information on 11 plant genomes to analyze stress-associated TEs using publicly available data. By selecting a genome and providing a list of genes or genomic regions whose TE associations the user wants to identify, the user can rapidly obtain TE subfamilies found near the provided regions, as well as their superfamily and class, and the enrichment values of the repeats. The results also provide the locations of individual repeat instances found, alongside the input regions or genes they are associated with, and a bar graph of the top ten most significant repeat subfamilies identified. PlanTEnrichment is freely available at http://tools.ibg.deu.edu.tr/plantenrichment/ and can be used by researchers with rudimentary or no proficiency in computational analysis of TE elements, allowing for expedience in the identification of TEs of interest and helping further our understanding of the potential contributions of TEs in plant genomes.

StemnesScoRe: an R package to estimate the stemness of glioma cancer cells at single-cell resolution.

Background/aim: Glioblastoma is the most heterogeneous and the most difficult-to-treat type of brain tumor and one of the deadliest among all cancers. The high plasticity of glioma cancer stem cells and the resistance they develop against multiple modalities of therapy, along with their high heterogeneity, are the main challenges faced during treatment of glioblastoma. Therefore, a better understanding of the stemness characteristics of glioblastoma cells is needed. With the development of various single-cell technologies and increasing applications of machine learning, indices based on transcriptomic and/or epigenomic data have been developed to quantitatively measure cellular states and stemness. In this study, we aimed to develop a glioma-specific stemness score model using scATAC-seq data for the first time. Materials and methods: We first applied three powerful machine-learning algorithms, i.e. random forest, gradient boosting, and extreme gradient boosting, to glioblastoma scRNA-seq data to discover the most important genes associated with cellular states. We then identified promoter and enhancer regions associated with these genes. After downloading the scATAC-seq peaks and their read counts for each patient, we identified the overlapping regions between the single-cell peaks and the peaks of genes obtained through machine-learning algorithms. Then we calculated read counts that were mapped to these overlapping regions. We finally developed a model capable of estimating the stemness score for each glioma cell using overlapping regions and the importance of genes predictive of glioblastoma cellular states. We also created an R package, accessible to all researchers regardless of their coding proficiency. Results: Our results showed that mesenchymal-like stem cells display higher stemness scores compared to neural-progenitor-, oligodendrocyte-progenitor-, and astrocyte-like cells. Conclusion: scATAC-seq can be used to assess heterogeneity in glioblastoma and identify cells with high stemness characteristics. The package is publicly available at https://github.com/Necla/StemnesScoRe and includes documentation with implementation of a real-data experiment.

"In the light of evolution:" keratins as exceptional tumor biomarkers.

Keratins (KRTs) are the intermediate filament-forming proteins of epithelial cells, classified, according to their physicochemical properties, into "soft" and "hard" keratins. They have a key role in several aspects of cancer pathophysiology, including cancer cell invasion and metastasis, and several members of the KRT family serve as diagnostic or prognostic markers. The human genome contains both, functional KRT genes and non-functional KRT pseudogenes, arranged in two uninterrupted clusters on chromosomes 12 and 17. This characteristic renders KRTs ideal for evolutionary studies. Herein, comprehensive phylogenetic analyses of KRT homologous proteins in the genomes of major taxonomic divisions were performed, so as to fill a gap in knowledge regarding the functional implications of keratins in cancer biology among tumor-bearing species. The differential expression profiles of KRTs in diverse types of cancers were investigated by analyzing high-throughput data, as well. Several KRT genes, including the phylogenetically conserved ones, were found to be deregulated across several cancer types and to participate in a common protein-protein interaction network. This indicates that, at least in cancer-bearing species, these genes might have been under similar evolutionary pressure, perhaps to support the same important function(s). In addition, semantic relations between KRTs and cancer were detected through extensive text mining. Therefore, by applying an integrative in silico pipeline, the evolutionary history of KRTs was reconstructed in the context of cancer, and the potential of using non-mammalian species as model organisms in functional studies on human cancer-associated KRT genes was uncovered.

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment.

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas.

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

Differential Occupancy and Regulatory Interactions of KDM6A in Bladder Cell Lines.

Epigenetic deregulation is a critical theme which needs further investigation in bladder cancer research. One of the most highly mutated genes in bladder cancer is KDM6A, which functions as an H3K27 demethylase and is one of the MLL3/4 complexes. To decipher the role of KDM6A in normal versus tumor settings, we identified the genomic landscape of KDM6A in normal, immortalized, and cancerous bladder cells. Our results showed differential KDM6A occupancy in the genes involved in cell differentiation, chromatin organization, and Notch signaling depending on the cell type and the mutation status of KDM6A. Transcription factor motif analysis revealed HES1 to be enriched at KDM6A peaks identified in the T24 bladder cancer cell line; moreover, it has a truncating mutation in KDM6A and lacks a demethylase domain. Our co-immunoprecipitation experiments revealed TLE co-repressors and HES1 as potential truncated and wild-type KDM6A interactors. With the aid of structural modeling, we explored how truncated KDM6A could interact with TLE and HES1, as well as RUNX and HHEX transcription factors. These structures provide a solid means of studying the functions of KDM6A independently of its demethylase activity. Collectively, our work provides important contributions to the understanding of KDM6A malfunction in bladder cancer.

TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype and is associated with increased survival in cancer patients with high tumor macrophage content.

Background: TNF-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily that can either induce cell death or activate survival pathways after binding to death receptors (DRs) DR4 or DR5. TRAIL is investigated as a therapeutic agent in clinical trials due to its selective toxicity to transformed cells. Macrophages can be polarized into pro-inflammatory/tumor-fighting M1 macrophages or anti-inflammatory/tumor-supportive M2 macrophages and an imbalance between M1 and M2 macrophages can promote diseases. Therefore, identifying modulators that regulate macrophage polarization is important to design effective macrophage-targeted immunotherapies. The impact of TRAIL on macrophage polarization is not known. Methods: Primary human monocyte-derived macrophages were pre-treated with either TRAIL or with DR4 or DR5-specific ligands and then polarized into M1, M2a, or M2c phenotypes in vitro. The expression of M1 and M2 markers in macrophage subtypes was analyzed by RNA sequencing, qPCR, ELISA, and flow cytometry. Furthermore, the cytotoxicity of the macrophages against U937 AML tumor targets was assessed by flow cytometry. TCGA datasets were also analyzed to correlate TRAIL with M1/M2 markers, and the overall survival of cancer patients. Results: TRAIL increased the expression of M1 markers at both mRNA and protein levels while decreasing the expression of M2 markers at the mRNA level in human macrophages. TRAIL also shifted M2 macrophages towards an M1 phenotype. Our data showed that both DR4 and DR5 death receptors play a role in macrophage polarization. Furthermore, TRAIL enhanced the cytotoxicity of macrophages against the AML cancer cells in vitro. Finally, TRAIL expression was positively correlated with increased expression of M1 markers in the tumors from ovarian and sarcoma cancer patients and longer overall survival in cases with high, but not low, tumor macrophage content. Conclusions: TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype via both DR4 and DR5. Our study defines TRAIL as a new regulator of macrophage polarization and suggests that targeting DRs can enhance the anti-tumorigenic response of macrophages in the tumor microenvironment by increasing M1 polarization.

FLI1 and FRA1 transcription factors drive the transcriptional regulatory networks characterizing muscle invasive bladder cancer.

Bladder cancer is mostly present in the form of urothelium carcinoma, causing over 150,000 deaths each year. Its histopathological classification as muscle invasive (MIBC) and non-muscle invasive (NMIBC) is the most prominent aspect, affecting the prognosis and progression of this disease. In this study, we defined the active regulatory landscape of MIBC and NMIBC cell lines using H3K27ac ChIP-seq and used an integrative approach to combine our findings with existing data. Our analysis revealed FRA1 and FLI1 as two critical transcription factors differentially regulating MIBC regulatory landscape. We show that FRA1 and FLI1 regulate the genes involved in epithelial cell migration and cell junction organization. Knock-down of FRA1 and FLI1 in MIBC revealed the downregulation of several EMT-related genes such as MAP4K4 and FLOT1. Further, ChIP-SICAP performed for FRA1 and FLI1 enabled us to infer chromatin binding partners of these transcription factors and link this information with their target genes. Finally, we show that knock-down of FRA1 and FLI1 result in significant reduction of invasion capacity of MIBC cells towards muscle microenvironment using IC-CHIP assays. Our results collectively highlight the role of these transcription factors in selection and design of targeted options for treatment of MIBC.

Early biventricular molecular responses to an acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) remains as one of the most common lethal diseases in the world and therefore it is necessary to understand its effect on molecular basis. Genome-wide microarray analysis provides us to predict potential biomarkers and signaling pathways for this purpose. OBJECTIVES: The aim of this study is to understand the molecular basis of the immediate right ventricular cellular response to left ventricular AMI. MATERIAL AND METHODS: A rat model of left anterior descending coronary artery ligation was used to assess the effect of left ventricular AMI on both the right ventricle as a remote zone and the left ventricle as an ischemic/infarct zone. Microarray technology was applied to detect the gene expression. Gene Ontology and KEGG pathways analysis were done to identify effected pathways and related genes. RESULTS: We found that immune response, cell chemotaxis, inflammation, cytoskeleton organization are significantly deregulated in ischemic zone as early response within 30 min. Unexpectedly, there were several affected signaling pathways such as cell chemotaxis, regulation of endothelial cell proliferation, and regulation of caveolea regulation of anti-apoptosis, regulation of cytoskeleton organization and cell adhesion on the remote zone in the right ventricle. CONCLUSION: This data demonstrates that there is an immediate molecular response in both ventricles after an AMI. Although the ischemia did not histologically involve the right ventricle; there is a clear molecular response to the infarct in the left ventricle. This provides us new insights to understand molecular mechanisms behind AMI and to find more effective drug targets.