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RAS Pathway Activation and Microenvironmental Adaptation as Hallmarks of Myeloid Sarcoma.

UNLABELLED: Myeloid sarcoma, an aggressive extramedullary subtype of acute myeloid leukemia (AML), occurs in approximately 20% of patients and remains strikingly understudied in large-scale genomic and multiomic investigations. The key drivers of its tumor evolution are largely unknown; timely detection in asymptomatic patients poses a clinical challenge, and effective treatment options are limited, as patients are often excluded from clinical trials, rendering it a largely neglected disease entity. In this study, we demonstrate that myeloid sarcoma evolves from medullary AML but exhibits distinct site-specific clonal evolution. This is supported by unique transcriptional signatures of myeloid sarcoma, reflecting adaptation to the extramedullary microenvironment. We establish a proof of concept that circulating tumor DNA (ctDNA) sequencing captures the molecular composition of myeloid sarcoma, offering a potential noninvasive approach for molecular profiling of extramedullary AML. Our findings highlight marked differences between medullary AML and myeloid sarcoma, including universal molecular evolution and RAS pathway activation as disease hallmarks. SIGNIFICANCE: We provide a comprehensive multiomic characterization of myeloid sarcoma, identifying key molecular pathways that contribute to its development, and suggest ctDNA as a noninvasive method of detection. We identify RAS pathway activation and transcriptional adaptation to the solid tissue microenvironment as cardinal features of myeloid sarcoma, suggesting novel therapeutic avenues.

Sarcoma, Myeloid↗

Genomewide expression profiling in the zebrafish embryo identifies target genes regulated by Hedgehog signaling during vertebrate development.

Hedgehog proteins play critical roles in organizing the embryonic development of animals, largely through modulation of target gene expression. Little is currently known, however, about the kinds and numbers of genes whose expression is controlled, directly or indirectly, by Hedgehog activity. Using techniques to globally repress or activate Hedgehog signaling in zebrafish embryos followed by microarray-based expression profiling, we have discovered a cohort of genes whose expression responds significantly to loss or gain of Hedgehog function. We have confirmed the Hedgehog responsiveness of a representative set of these genes with whole-mount in situ hybridization as well as real time PCR. In addition, we show that the consensus Gli-binding motif is enriched within the putative regulatory elements of a sizeable proportion of genes that showed positive regulation in our assay, indicating that their expression is directly induced by Hedgehog. Finally, we provide evidence that the Hedgehog-dependent spatially restricted transcription of one such gene, nkx2.9, is indeed mediated by Gli1 through a single Gli recognition site located within an evolutionarily conserved enhancer fragment. Taken together, this study represents the first comprehensive survey of target genes regulated by the Hedgehog pathway during vertebrate development. Our data also demonstrate for the first time the functionality of the Gli-binding motif in the control of Hedgehog signaling-induced gene expression in the zebrafish embryo.

Animals↗

Comprehensive Analysis of Differentially Expressed Genes and Immune Infiltration in Burn Injury: Key Biomarkers and Pathways.

BACKGROUND: Burn injuries trigger complex immune responses and gene expression changes, impacting wound healing and systemic inflammation. Understanding these changes is crucial for identifying biomarkers and therapeutic targets. METHODS: We analyzed two gene expression omnibus datasets (wound tissue [GSE8056] and blood [GSE37069]) to identify differentially expressed genes (DEGs) in burn injury samples versus controls. Immune cell proportions were assessed using CIBERSORT. Functional enrichment analyses (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) and protein-protein interaction networks were constructed to identify key genes and pathways. RESULTS: We identified 1170 upregulated and 1227 downregulated DEGs. Gene Ontology analysis revealed enrichment in neutrophil activation, inflammatory response, and extracellular matrix organization. Kyoto Encyclopedia of Genes and Genomes analysis highlighted cytokine-cytokine receptor interaction, TNF, and IL-17 signaling pathways. Immune infiltration analysis showed significant changes in neutrophils, macrophages (M1/M2), and T-cell subsets. Protein-protein interaction network analysis identified five hub genes: JUN, STAT1, Bcl2, MMP9, and TLR2. CONCLUSIONS: This study provides a comprehensive bioinformatic analysis of gene expression and immune responses in burn injuries. The identified DEGs, hub genes, and pathways offer insights into the immune response mechanisms and suggest potential targets for diagnostic and therapeutic interventions in burn injury management.

Burns↗

Circular RNAs orchestrate integrated post-transcriptional responses to combined heat and drought stress in rice.

Circular RNAs (circRNAs) are emerging post-transcriptional regulators, yet their landscape and functional roles in rice under combined abiotic stress remain largely unexplored. Here, we systematically reanalyzed strand-specific RNA-seq data to characterize circRNAs responsive to simultaneous heat and drought stress. Following quality control, read mapping, and dual-algorithm prediction using CIRI2 and CIRCexplorer2, we identified 208 high-confidence circRNAs distributed across all 12 chromosomes. Comparative profiling revealed 83 circRNAs uniquely expressed in control samples, 51 in stressed samples, and 74 shared between conditions, indicating stress-dependent circularization. Junction-read analysis highlighted a spectrum of circularization strength, ranging from highly abundant circRNAs with dominant junction reads to low-confidence candidates masked by linear transcript background. Genomic annotation showed that circRNAs primarily originated from exonic and intergenic regions, with a pronounced negative-strand bias; several genes generated multiple circRNA isoforms via alternative back-splicing. Functional enrichment of host genes suggested involvement in protein folding, nutrient reservoir activity, RNA degradation, and branched-chain amino acid catabolism, implicating roles in stress adaptation and metabolic regulation. Differential expression analysis identified seven circRNAs specifically induced under combined stress conditions. Network topology analysis pinpointed key miRNAs-including osa-miR414, osa-miR1439, and osa-miR2919-as candidate topological hubs within the predicted network. Their predicted target genes, such as those encoding stress-responsive transcription factors and signaling proteins, suggest potential roles in coordinating post-transcriptional responses to combined stress. Network topology analysis pinpointed key miRNAs-including osa-miR414, osa-miR1439, and osa-miR2919-as candidate topological hubs within the predicted network. Their predicted target genes, such as those encoding stress-responsive transcription factors and signaling proteins, suggest potential roles in coordinating post-transcriptional responses to combined stress. Overall, this study provides a comprehensive map of circRNAs in rice under combined heat and drought stress, suggests their potential as ceRNAs based on predictive analysis, and lays a foundation for future experimental validation of circRNA-mediated regulation.

Oryza↗

KLHL17 as a Prognostic Indicator and Therapeutic Target in Cervical Cancer: A Comprehensive Analysis.

INTRODUCTION: This study aims to clarify the role of kelch like family member 17 (KLHL17) in cervical cancer (CESC) is unclear. OBJECTIVE: To clarify this uncertainty, our research employed bioinformatics analysis coupled with experimental corroboration. METHODS: We utilized the Cancer Genome Atlas (TCGA) database to assess the expression of KLHL17 in various cancers, specifically CESC, and to explore its association with clinical characteristics, diagnostic utility, and prognostic significance in CESC. The current investigation delved into the potential regulatory pathways related to KLHL17, examining its connection with the infiltration of immune cells, the expression of immune checkpoint genes, the status of microsatellite instability (MSI), and the efficacy of diverse therapeutic agents in CESC. The research analyzed KLHL17 expression patterns using single-cell sequencing data from CESC samples and investigated the genetic variations of KLHL17 within this context. KLHL17 expression was validated using GSE145372. The presence and levels of KLHL17 in different cell lines were validated through quantitative real-time PCR (qRT-PCR) assays. RESULTS: KLHL17 exhibited irregular expression profiles across various cancer types, including CESC. Furthermore, increased KLHL17 levels in CESC patients were significantly associated with a lower progression-free survival (PFS) rate (hazard ratio: 1.62; 95% confidence interval: 1.01-2.60, p = 0.044). Moreover, KLHL17 expression emerged as a distinct prognostic indicator for CESC patients (p = 0.031). It has been associated with various biological pathways, such as cytokine-cytokine receptor interaction, primary immunodeficiency, cell adhesion molecules (CAMs), chemokine signaling pathway, steroid hormone biosynthesis, and others. The expression levels of KLHL17 were found to correlate with the presence of immune cells, the expression of immune checkpoint genes, and the status of MSI within CESC. Furthermore, KLHL17 expression exhibited a significant and inverse correlation with XMD15-27, rTRAIL, Paclitaxel, tp4ek, and tp4ek-k6. Furthermore, KLHL17 was found to be significantly positively regulated in CESC cell lines. DISCUSSION: The findings suggest that KLHL17 is involved in the progression of CESC and may serve as a potential prognostic marker and therapeutic target. KLHL17's association with immune cell infiltration and immune checkpoint genes indicates a role in immuneevasion. Future research should focus on validating these findings through independent datasets and experimental studies to elucidate the molecular mechanisms underlying KLHL17's role in CESC progression and immune regulation. CONCLUSION: KLHL17 is a promising prognostic marker and potential therapeutic target in CESC.

Humans↗

An ultracentrifugation analysis of two hundred fish genomes.

The goal of this study was to provide a comprehensive view of the compositional characteristics of fish genomes. We therefore expanded the number of fish species that we had explored so far in their DNAs by analytical ultracentrifugation in CsCl density gradient from 122 to 201. This study included representatives from three out of nine orders of Elasmobranchs (sharks and rays), both orders of dipnoan lungfishes, and both orders of chondrosteans (sturgeons and bichirs). We also studied 19 out of 38 teleostean orders, which represent all but four (minor) superorders of the subdivision Teleostei, a group comprising about 23,600 species (96% of all extant fishes). This leaves for further studies two subclasses, Holocephali (chimaeras), and Coelacanthimorpha (gombessas). In spite of this substantial increase in the number of species and orders analysed, all average properties (the modal buoyant density, rho(0), the average buoyant density, , the CsCl profile asymmetry, A, and the compositional heterogeneity, H), and all their ranges were unchanged compared to a previous study [J. Mol. Evol. 31 (1990) 265]. This suggests that, in all likelihood, the properties reported in the present paper can be considered as generally valid for all fish genomes.

Animals↗

Transcriptional profiling of the heart reveals chamber-specific gene expression patterns.

Cardiac chamber-specific gene expression is critical for the normal development and function of the heart. To investigate the genetic basis of cardiac anatomical specialization, we have undertaken a nearly genome-wide transcriptional profiling of the four heart chambers and the interventricular septum. Rigorous statistical analysis has allowed the identification of known and novel members of gene families that are felt to be important in cardiac development and function, including LIM proteins, homeobox proteins, wnt and T-box pathway proteins, as well as structural proteins like actins and myosins. In addition, these studies have allowed the identification of thousands of additional differentially expressed genes, for which there is little structural or functional information. Clustering of genes with known and unknown functions provides insights into signaling pathways that are essential for development and maintenance of chamber-specific features. To facilitate future research in this area, a searchable internet database has been constructed that allows study of the chamber-specific expression of any gene represented on this comprehensive microarray. It is anticipated that further study of genes identified through this effort will provide insights into the specialization of heart chamber tissues, and their specific roles in cardiac development, aging, and disease.

Analysis of Variance↗

Gene expression profiles of progressive pancreatic endocrine tumours and their liver metastases reveal potential novel markers and therapeutic targets.

The intrinsic nature of tumour behaviour (stable vs progressive) and the presence of liver metastases are key factors in determining the outcome of patients with a pancreatic endocrine tumour (PET). Previous expression profile analyses of PETs were limited to non-homogeneous groups or to primary lesions only. The aim of this study was to investigate the gene expression profiles of a more uniform series of sporadic, non-functioning (NF) PETs with progressive disease and, for the first time, their liver metastases, on the Affymetrix human genome U133A and B GeneChip set. Thirteen NF PET samples (eight primaries and five liver metastases) from ten patients with progressive, metastatic disease, three cell lines (BON, QGP and CM) and four purified islet samples were analysed. The same samples were employed for confirmation of candidate gene expression by means of quantitative RT-PCR, while a further 37 PET and 15 carcinoid samples were analysed by immunohistochemistry. Analysis of genes differentially expressed between islets and primaries and metastases revealed 667 up- and 223 down-regulated genes, most of which have not previously been observed in PETs, and whose gene ontology molecular function has been detailed. Overexpression of bridging integrator 1 (BIN1) and protein Z dependent protease inhibitor (SERPINA10) which may represent useful biomarkers, and of lymphocyte specific protein tyrosine kinase (LCK) and bone marrow stromal cell antigen (BST2) which could be used as therapeutic targets, has been validated. When primary tumours were compared with metastatic lesions, no significantly differentially expressed genes were found, in accord with cluster analysis which revealed a striking similarity between primary and metastatic lesions, with the cell lines clustering separately. We have provided a comprehensive list of differentially expressed genes in a uniform set of aggressive NF PETs. A number of dysregulated genes deserve further in-depth study as potentially promising candidates for new diagnostic and treatment strategies. The analysis of liver metastases revealed a previously unknown high level of similarity with the primary lesions.

Adult↗

Omic space: coordinate-based integration and analysis of genomic phenomic interactions.

MOTIVATION: With the recent progress in genomics, various data sets of omic interactions describing networks of omic elements have become available. In order to obtain reliable hypotheses from the data, it is effective to integrate interactions from different sorts of data sets. In order to facilitate a coordinate-based integration and analysis of omic interactions, we introduce the concept of an omic space comprising a comprehensive set of omic planes. Genomic, transcriptomic, proteomic, metabolomic, phenomic and other omic planes are defined by two orthogonal genomic-coordinate axes. RESULTS: We show that the omic space concept helps us to assimilate biological findings comprehensively into hypotheses or models combining higher-order phenomena and lower-order mechanisms by demonstrating that a comprehensive ranking of correspondences among interactions in the space can be used effectively for estimating candidates of responsible gene pairs for epistatic interacting loci of tumors in mice. We also show that the omic space offers a convenient framework for database integration, by presenting a system named the 'Genome <==> Phenome Superhighway' (GPS) that serves as a framework for integration and visualization of omic interactions based on omic spaces of some model species including Homo sapiens, Mus musculus, Caenorhabditis elegans and Arabidopsis thaliana. AVAILABILITY: For the GPS web site, see http://omicspace.riken.jp/gps/.

Algorithms↗

Functional analysis of the polyketide synthase genes in the filamentous fungus Gibberella zeae (anamorph Fusarium graminearum).

Polyketides are a class of secondary metabolites that exhibit a vast diversity of form and function. In fungi, these compounds are produced by large, multidomain enzymes classified as type I polyketide synthases (PKSs). In this study we identified and functionally disrupted 15 PKS genes from the genome of the filamentous fungus Gibberella zeae. Five of these genes are responsible for producing the mycotoxins zearalenone, aurofusarin, and fusarin C and the black perithecial pigment. A comprehensive expression analysis of the 15 genes revealed diverse expression patterns during grain colonization, plant colonization, sexual development, and mycelial growth. Expression of one of the PKS genes was not detected under any of 18 conditions tested. This is the first study to genetically characterize a complete set of PKS genes from a single organism.

Amino Acid Sequence↗

Gene expression alterations in human prostate cancer.

Prostate cancer is a disease with a great degree of variation in biological aggressiveness and clinical prognosis. Although more than 30% of the older-aged male population develops prostate cancer, defined by histologic examination, a large number of these cases does not reach the stage displaying clinical symptoms. Among those patients with clinical prostate cancer, only a fraction of cases demonstrate life-threatening biological aggressiveness. Parallel to the clinical complexity of this disease, abnormalities in the prostate cancer genome have been reported in 21 of 23 pairs of human chromosomes, but none can be accountable for the dominant event in the development of prostate cancer. In order to understand the genetic nature of this disease, a comprehensive analysis of its gene expression patterns is needed. This article will review several recent publications in the area of gene expression analysis using microarray technology. I will discuss some of our findings in the area of gene expression alteration in benign prostate tissue adjacent to prostate cancer. The implication of these studies in potential clinical application will be explored.

Gene Expression Profiling↗

Estrogen receptor target gene: an evolving concept.

Estrogen receptor (ER) functions as a transcription factor to induce gene expression events sufficient for cell division and breast cancer progression. A significant body of work exists on the identification of ER gene targets and the cofactors that contribute to these transcription events, yet surprisingly little is known of the cis-regulatory elements involved. In this review, we investigate the advances in technology that contribute to a comprehensive understanding of ER target genes and explore recent work identifying cis-regulatory domains that augment transcription of these targets. Specifically, we find that ER association with gene targets results from an association with the pioneer factor FoxA1, responsible for recruitment of ER to the genome. Recruitment of ER to the genome does not occur at promoter proximal regions, but instead involves distal enhancer elements that function to tether the ER complex to the target gene promoters. These advances in technology permit a more detailed investigation of ER activity and may aid in the development of superior drug interventions.

Animals↗

A comprehensive transcript index of the human genome generated using microarrays and computational approaches.

BACKGROUND: Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22. RESULTS: The combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale. CONCLUSIONS: These data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized.

Chromosomes, Human, Pair 20↗

Molecular classification of breast tumors: toward improved diagnostics and treatments.

Recent advances in gene expression profiling and other "omics" technologies have revolutionized cancer research and hold the potential of also revolutionizing clinical practice. These high-throughout approaches have radically changed our ability to study cells and tissues in a more comprehensive way. Combined with advanced bioinformatics and the possibility to simulate biological processes in computers, this field of "systems biology" allows us to study the organism as a whole entity. This chapter describes the molecular classification and characterization of breast tumors into distinct subtypes by using DNA microarrays and discusses the statistical relationships of the subgroups with clinical features of the disease.

BRCA1 Protein↗

Molecular portraits and the family tree of cancer.

The twenty-first century heralds a new era for the biological sciences and medicine. The tools of our time are allowing us to analyze complex genomes more comprehensively than ever before. A principal technology contributing to this explosion of information is the DNA microarray, which enables us to study genome-wide expression patterns in complex biological systems. Although the potential of microarrays is yet to be fully realized, these tools have shown great promise in deciphering complex diseases such as cancer. The early results are painting a detailed portrait of cancer that illustrates the individuality of each tumor and allows familial relationships to be recognized through the identification of cell types sharing common expression patterns.

DNA, Neoplasm↗

Gene networks as a tool to understand transcriptional regulation.

Gene regulatory networks, or simply gene networks (GNs), have shown to be a promising approach that the bioinformatics community has been developing for studying regulatory mechanisms in biological systems. GNs are built from the genome-wide high-throughput gene expression data that are often available from DNA microarray experiments. Conceptually, GNs are (un)directed graphs, where the nodes correspond to the genes and a link between a pair of genes denotes a regulatory interaction that occurs at transcriptional level. In the present study, we had two objectives: 1) to develop a framework for GN reconstruction based on a Bayesian network model that captures direct interactions between genes through nonparametric regression with B-splines, and 2) to demonstrate the potential of GNs in the analysis of expression data of a real biological system, the yeast pheromone response pathway. Our framework also included a number of search schemes to learn the network. We present an intuitive notion of GN theory as well as the detailed mathematical foundations of the model. A comprehensive analysis of the consistency of the model when tested with biological data was done through the analysis of the GNs inferred for the yeast pheromone pathway. Our results agree fairly well with what was expected based on the literature, and we developed some hypotheses about this system. Using this analysis, we intended to provide a guide on how GNs can be effectively used to study transcriptional regulation. We also discussed the limitations of GNs and the future direction of network analysis for genomic data. The software is available upon request.

Bayes Theorem↗

A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers. While the aberrant expression of circadian rhythm-related genes has been implicated in cancer pathogenesis, its comprehensive role in CRC progression and predicted therapeutic vulnerabilities remains inadequately characterized. METHODS: Bulk and single-cell RNA-sequencing data were integrated from multiple CRC cohorts. A circadian rhythm signature (CRS) was developed through machine learning algorithms and validated for prognostic value. Comprehensive analyses of tumor microenvironment, genomic alterations, and drug sensitivity were performed. Furthermore, the biological function of the core gene, BHLHE40, was validated in CRC cell lines through CCK-8, EdU, and wound healing assays. RESULTS: Single-cell analysis demonstrated an elevated expression signature of circadian rhythm-related genes in dendritic cells. The optimized CRS, comprising 14 circadian rhythm-related genes, successfully categorized patients into high- and low-risk groups. Patients with a high CRS showed markedly poorer overall survival and computationally inferred immunosuppressive features, including reduced CD8+ T cell infiltration and increased M2 macrophage polarization. Genomic analysis revealed enhanced mutation burden in TP53 and alterations in RTK-RAS/WNT pathways. Notably, in vitro assays confirmed that BHLHE40 is significantly overexpressed in CRC cells. Knockdown of BHLHE40 markedly inhibited tumor cell proliferation and migration. Drug sensitivity profiling identified bexarotene and SMER-3 as potential therapeutic options for high-CRS patients. A nomogram integrating CRS with clinical parameters demonstrated superior predictive accuracy for 1-, 3-, and 5-year survival. CONCLUSIONS: The CRS represents a promising prognostic biomarker that reflects tumor immune status and genomic features, providing valuable insights for personalized treatment strategies in CRC.

Circadian rhythm↗

The rapid identification of Acinetobacter species using Fourier transform infrared spectroscopy.

AIMS: Fourier transform infrared (FT-IR) was used to analyse a selection of Acinetobacter isolates in order to determine if this approach could discriminate readily between the known genomic species of this genus and environmental isolates from activated sludge. METHODS AND RESULTS: FT-IR spectroscopy is a rapid whole-organism fingerprinting method, typically taking only 10 s per sample, and generates 'holistic' biochemical profiles (or 'fingerprints') from biological materials. The cluster analysis produced by FT-IR was compared with previous polyphasic taxonomic studies on these isolates and with 16S-23S rDNA intergenic spacer region (ISR) fingerprinting presented in this paper. FT-IR and 16S-23S rDNA ISR analyses together indicate that some of the Acinetobacter genomic species are particularly heterogeneous and poorly defined, making characterization of the unknown environmental isolates with the genomic species difficult. CONCLUSIONS: Whilst the characterization of the isolates from activated sludge revealed by FT-IR and 16S-23S rDNA ISR were not directly comparable, the dendrogram produced from FT-IR data did correlate well with the outcomes of the other polyphasic taxonomic work. SIGNIFICANCE AND IMPACT OF THE STUDY: We believe it would be advantageous to pursue this approach further and establish a comprehensive database of taxonomically well-defined Acinetobacter species to aid the identification of unknown strains. In this instance, FT-IR may provide the rapid identification method eagerly sought for the routine identification of Acinetobacter isolates from a wide range of environmental sources.

Acinetobacter↗