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Integrative dual-track transcriptomics reveals stage-specific coordination, regulatory divergence, and HSP90AA1-associated remodeling in human folliculogenesis.

Human folliculogenesis depends on coordinated yet non-identical developmental remodeling in the oocyte and its surrounding granulosa cells. When these two compartments remain synchronized and when they diverge into lineage-specific regulatory states, however, remains incompletely resolved. Here we performed an integrative dual-track re-analysis of the human RNA-seq dataset GSE107746, modeling oocytes and granulosa cells as distinct but developmentally linked compartments across follicular progression. Analysis of 148 sequencing libraries showed that compartment identity was the dominant source of transcriptomic variation, supporting compartment-aware downstream interpretation. Within this framework, oocytes followed a relatively continuous developmental trajectory, with substantial transcriptional remodeling already evident across adjacent stages, whereas granulosa cells showed weaker early-stage contrasts but markedly stronger late-stage reorganization, particularly around the antral and preovulatory transitions. Functional enrichment indicated that oocyte maturation was associated with RNA-processing and broader genome-regulatory remodeling, whereas granulosa maturation was dominated by progressive mitochondrial and bioenergetic activation. Co-expression analysis showed that both compartments contained strong late-stage programmes together with inverse early-state modules, indicating a shared systems-level architecture of maturation, although the hub-gene composition and biological content of these programmes were largely compartment-specific. Machine-learning validation reinforced this asymmetry: oocyte stage classification was best recovered from a compact eigengene-based representation, whereas granulosa stage discrimination was better resolved by a broader differential-expression-derived feature set. At the gene level, HSP90AA1 emerged as a stage-associated marker with compartment-specific behavior, showing progressive attenuation across oocyte development, assignment to the selected oocyte blue module, and sharper transitional dynamics in granulosa cells. Together, these findings support a model in which human folliculogenesis proceeds through coordinated but non-equivalent transcriptomic remodeling, with shared developmental logic at the systems level but distinct molecular execution in germline and somatic compartments.

Co-expression networks↗

Analysis of cell migration using whole-genome expression profiling of migratory cells in the Drosophila ovary.

Cell migration contributes to normal development and homeostasis as well as to pathological processes such as inflammation and tumor metastasis. Previous genetic screens have revealed signaling pathways that govern follicle cell migrations in the Drosophila ovary, but few downstream targets of the critical transcriptional regulators have been identified. To characterize the gene expression profile of two migratory cell populations and identify Slbo targets, we purified border cells and centripetal cells expressing the mouse CD8 antigen and carried out whole-genome microarray analysis. Genes predicted to control actin dynamics and the endocytic and secretory pathways were overrepresented in the migratory cell transcriptome. Mutations in five genes, including ttk, failed to complement previously isolated mutations that cause cell migration defects in mosaic clones. Functional analysis revealed a role for the Notch-activating protease Kuzbanian in border cell migration and identified Tie as a guidance receptor for the border cells.

Animals↗

The path from molecular indicators of exposure to describing dynamic biological systems in an aquatic organism: microarrays and the fathead minnow.

The extent to which humans and wildlife are exposed to toxicants is an important focus of environmental research. This work has been directed toward the development of molecular indicators diagnostic for exposure to various stressors in freshwater fish. Research includes the discovery of genes, indicative of environmental exposure, in the Agency's long-established aquatic toxicological organism, the fathead minnow (Pimephales promelas). Novel cDNAs and coding sequences will be used in DNA microarray analyses for pattern identification of stressor-specific, differentially up- and down-regulated genes. The methods currently used to discover genes in this organism, for which few annotated nucleic acid sequences exist, are cDNA subtraction libraries, differential display, exploiting PCR primers for known genes of other members of the family Cyprinidae and use of degenerate PCR primers designed from regions of moderate protein homology. Single or multiple genes noted as being differentially expressed in microarray analyses will then be used in separate studies to measure bioavailable stressors in the laboratory and field. These analyses will be accomplished by quantitative RT-PCR. Moving from analysis of single gene exposures to the global state of the transcriptome offers possibilities that those genes identified by DNA microarray analyses might be critical components of dynamic biological systems and networks, wherein chemical stressors exert toxic effects through various modes of action. Additionally, the ability to discriminate bioavailability of stressors in complex environmental mixtures, and correlation with adverse effects downstream from these early molecular events, presents challenging new ground to be broken in the area of risk assessment.

Animals↗

Application of global analysis techniques to Corynebacterium glutamicum: new insights into nitrogen regulation.

The regulation of nitrogen metabolism in the amino acid producer Corynebacterium glutamicum was subject of research for several decades. While previous studies focused on single enzymes or pathways, the publication of the C. glutamicum genome sequence gave a fresh impetus to research, since a global investigation of metabolism and regulation networks became possible based on these data. This communication summarizes the advances made by different studies, in which global analysis approaches were used to characterize the C. glutamicum nitrogen starvation response. A combination of bioinformatics approaches, transcriptome and proteome analyses as well as chemostat experiments revealed new insights into the nitrogen control network of C. glutamicum. C. glutamicum reacts to a limited nitrogen supply with a rearrangement of the cellular transport capacity, changes in metabolic pathways for nitrogen assimilation and amino acid biosynthesis, an increased energy generation and increased protein stability. With the aid of chemostat experiments, in which different growth rates were obtained by nitrogen limitation, general starvation effects could be distinguished from specific nitrogen limitation-dependent changes. The core adaptations on the level of transcription are controlled by the master regulator of nitrogen control, the TetR-type protein AmtR. This global regulator governs transcription of at least 33 genes via binding to a palindromic consensus motif (AmtR box). Genes with AmtR box-containing promoters were identified by genome-wide screening and validated, besides by other methods, by transcriptome analyses using DNA microarrays.

Bacterial Proteins↗

Enterococcus faecalis GP1764 induces an early differential gene expression in the intestine on key pathways related to cellular immune response and gut barrier function in chickens.

The aim of the present study was to elucidate the mode of action of Enterococcus faecalis GP1764 in improving performance traits during the starter phase by analyzing genome-wide gene expression and its interaction with microbial populations in the intestine of chickens challenged with an NSP-rich diet. At day 7, microbiota populations from ileal and cecal contents and transcriptomics from jejunal and cecal mucosa were analyzed between Control (Ctrl) and Enterococcus faecalis GP1764 (EntF) groups. Results from microbiota analysis demonstrated that EntF shifted β-diversity indices in ileum (neutral (p= 0.006) and phylogenetic (p= 0.006)) and caecum (phylogenetic (p= 0.017)). Transcriptomics revealed 43 differentially expressed genes for EntF vs. Ctrl in the jejunal mucosa. Of these, MHCY-36 (MHC-I-Related), RAG2 and MUC19-like genes were upregulated in EntF vs. Ctrl, protein-coding genes with immunomodulatory capacities as supported by GSEA and Cytoscape-ClueGo pathway analyses. Results suggest an intestinal immunomodulation induced through presentation of B vitamins metabolites, synthetized by EntF, to an undescribed subset of innate-like unconventional T lymphocytes in chickens, similar to MAIT cells in mammals. These cells could contribute to antibacterial responses and repair of damaged barrier tissue after inflammatory processes. The upregulation of the MUC19-like gene expression observed in the jejunal mucosa can protect gut integrity via the promotion of mucus production by goblet cells. Finally, RAG2, involved in V(D)J coding segments recombination in B- and T-cells may provide a greater recognition of foreign invaders, allowing the animals to efficiently fight against pathogenic infections. Collectively, these results suggest an important role of EntF in promoting the capacity of animals to rapidly act against pathogenic challenges, herein, inducing resilience towards dietary ingredients with anti-nutritional activity that impart moderate inflammation in chickens.

Enterococcus faecalis↗

Changes of DNA methylation and gene expression profile in placental villi and chorioamniotic membranes under preeclampsia.

BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication with elusive pathogenesis. Although epigenetic dysregulation is implicated, its layer-specific placental roles are poorly defined. This study aimed to identify shared and layer-specific epigenetic alterations in PE by profiling DNA methylation and gene expression in placental villi (PV) and chorioamniotic membranes (CAM). RESEARCH DESIGN AND METHODS: PV and CAM samples were collected from 7 normal and 8 PE pregnancies, and three public DNA methylation datasets (GSE98224, GSE44667, GSE75196) were integrated. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified based on whole-genome methylation and transcriptome sequencing. Layer-specific and shared gene sets were identified by cross-analysis, with functional annotation using Gene Ontology (GO). RESULTS: EM-seq revealed a hypermethylation-dominant, tissue-specific methylation landscape in PE placentas. Cross-tissue comparison identified shared DMGs between the two layers, including nine key genes consistently altered in public datasets. Integrated analysis in PV further identified 22 co-dysregulated genes, enriched in thermoregulation, maternal-fetal immunity, signal transduction, and cell differentiation. CONCLUSIONS: This study elucidates the shared and layer-specific dysregulation of gene networks at methylomic and transcriptomic levels in PE placenta. Comparing PV and CAM highlights placental epigenetic heterogeneity and dysfunction, offering novel clues for mechanistic research and layer-targeted therapies.

Humans↗

Macrophage characteristics of stem cells revealed by transcriptome profiling.

We previously showed that the phenotypes of adipocyte progenitors and macrophages were close. Using functional analyses and microarray technology, we first tested whether this intriguing relationship was specific to adipocyte progenitors or could be shared with other progenitors. Measurements of phagocytic activity and gene profiling analysis of different progenitor cells revealed that the latter hypothesis should be retained. These results encouraged us to pursue and to confirm our analysis with a gold-standard stem cell population, embryonic stem cells or ESC. The transcriptomic profiles of ESC and macrophages were clustered together, unlike differentiated ESC. In addition, undifferentiated ESC displayed higher phagocytic activity than other progenitors, and they could phagocytoze apoptotic bodies. These data suggest that progenitors and stem cells share some characteristics of macrophages. This opens new perspectives on understanding stem cell phenotype and functionalities such as a putative role of stem cells in tissue remodeling by discarding dead cells but also their immunomodulation or fusion properties.

Algorithms↗

High MGMT expression identifies aggressive colorectal cancer with distinct genomic features and immune evasion properties.

INTRODUCTION: The epigenetic silencing of O6-methylguanine DNA methyltransferase (MGMT) is associated with reduced DNA repair capacity, carcinogenesis and increased sensitivity to alkylating chemotherapy. However, the biological role and clinical significance of MGMT overexpression in cancer remains poorly understood. METHODS: Using multiplexed quantitative immunofluorescence we measured the localized levels of MGMT protein, γH2AX and CD8+ T cells in multiple retrospective colorectal cancer (CRC) cohorts. Genomic and transcriptomic features of selected cases were also studied with whole exome DNA sequencing and genome-wide methylation analysis. MGMT-methylated human CRC cells SW620 were transfected with an MGMT-containing plasmid and co-cultured with allogeneic peripheral blood mononuclear cells. RESULTS: A subset of CRCs showed MGMT protein upregulation associated with lower γH2AX, reduced CD8+ tumor infiltrating lymphocytes (TILs), mismatch repair proficient (pMMR) status and shorter survival. CD8+ TILs were more distant from MGMT-expressing cells than MGMT-negative cells and the MGMT promoter methylation status did not highly correlate with MGMT protein levels in CRC. In genomic/transcriptomic analysis, high MGMT expression was associated with a lower nonsynonymous somatic mutational burden, higher transition-to-transversion mutation ratio, increased deleterious TP53 variants and distinct transcriptomic profiles. The exogenous expression of MGMT in SW620 CRC cells reduced the number of spontaneous nonsynonymous mutations, reproduced mutational features of MGMT-high CRC and limited the in vitro T-cell-mediated killing of malignant cells induced by proinflammatory cytokines in tumor/immune cell co-cultures. CONCLUSIONS: MGMT overexpression identifies a previously undescribed subset of CRCs with distinct biological and clinical properties including reduced mutagenesis, adaptive immune evasion, predominantly pMMR phenotype and aggressive clinical course. Direct, quantitative assessment of MGMT protein expression using spatially resolved analysis is more reliable than inference of MGMT expression by promoter methylation status in CRC.

Humans↗

Tag-based approaches for transcriptome research and genome annotation.

With the increasing number of whole genome sequences available, genomic research has shifted toward the annotation of functional elements and transcribed regions. Thus, the related field of transcriptome research requires accurate methods for the profiling of genes that are not biased by known sequence information, and that also allow for the identification of promoter regions. Starting with serial analysis of gene expression (SAGE), methods making use of short sequencing tags have greatly contributed to transcriptome studies. Here we review recent developments in the use of short sequencing tags in expression profiling, gene discovery and genome annotation. These tags are obtained from the 5' end of mRNAs, both terminal ends of mRNAs, or genomic regions. The 5' end-specific tags, with their ability to identify transcripts along with their transcriptional start sites, will be of particular interest for gene network studies and may become one of the most important approaches in systems biology.

Animals↗

Induction of apoptosis in mouse liver by microcystin-LR: a combined transcriptomic, proteomic, and simulation strategy.

Microcystins (MCs) are a family of cyclic heptapeptide hepatotoxins produced by freshwater species of cyanobacteria that have been implicated in the development of liver cancer, necrosis, and even deadly intrahepatic bleeding. MC-LR, the most toxic MC variant, is also the most commonly encountered in a contaminated aquatic system. This study presents the first data in the toxicological research of MCs that combines the use of standard apoptotic assays with transcriptomics, proteomic technologies, and computer simulations. By using histochemistry, DNA fragmentation assays, and flow cytometry analysis, we determined that MC-LR causes rapid, dose-dependent apoptosis in mouse liver when BALB/c mice are treated with MC-LR for 24 h at doses of either 50, 60, or 70 microg/kg of body weight. We then used gene expression profiling to demonstrate differential expressions (>2-fold) of 61 apoptosis-related genes in cells treated with MC-LR. Further proteomic analysis identified a total of 383 proteins of which 35 proteins were up-regulated and 30 proteins were down-regulated more than 2.5-fold when compared with controls. Combining computer simulations with the transcriptomic and proteomic data, we found that low doses (50 microg/kg) of MC-LR lead to apoptosis primarily through the BID-BAX-BCL-2 pathway, whereas high doses of MC-LR (70 microg/kg) caused apoptosis via a reactive oxygen species pathway. These results indicated that MC-LR exposure can cause apoptosis in mouse liver and revealed two independent pathways playing a major regulatory role in MC-LR-induced apoptosis, thereby contributing to a better understanding of the hepatotoxicity and the tumor-promoting mechanisms of MCs.

Animals↗

Integrative single-cell and genomic analysis reveals NMB as a driver of metastatic adaptation in esophageal squamous cell carcinoma via metabolic rewiring and immune evasion.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) has high mortality, and metastasis is the leading cause of patient death. Neuromedin B (NMB) promotes tumor development in various cancers, yet its role in ESCC metastasis remains unclear. METHODS: We integrated single-cell transcriptomic data from matched primary and metastatic ESCC lesions (GSE309392) with bulk transcriptomic cohorts from TCGA and GSE53624. In silico gene perturbation, ligand-receptor communication analysis, and single-cell prognostic model construction were performed, followed by functional validation through siRNA-mediated NMB knockdown in TE-1 and KYSE30 cell lines. RESULTS: NMB was identified as a key gene enriched in metastatic ESCC lesions, and its high expression was associated with coordinated upregulation of oxidative phosphorylation pathway genes and aldo-keto reductase family antioxidant enzymes (AKR1C1, AKR1C2, AKR1B10). Genomic analysis revealed that NMB-high tumors carried a higher clonal mutation burden and a markedly increased frequency of NFE2L2 activating mutations (23% vs. 8%, P = 0.04). In silico knockout and correlation analysis identified AKR1C1 as a downstream effector of NMB. NMB expression was negatively correlated with CD8+ T cell and activated NK cell infiltration. CellChat analysis revealed communication between NMB-positive cells and monocytes via the TGM2-ADGRG1 axis, and specifically detected IFNG signaling. In the single-cell prognostic model, NMB-positive cells accounted for 50% of the high-risk group but only 20% of the low-risk group. TCGA-based survival analysis demonstrated that high NMB expression was associated with shorter overall survival (HR = 2.98, P = 0.03). In vitro NMB-targeted RNA interference markedly inhibited proliferation, colony formation, and migration in TE-1 and KYSE30 cells. CMap screening identified the endothelin-PDE5-cGMP axis as a potential therapeutic target. CONCLUSION: NMB serves as a key driver of metastatic adaptation in ESCC, conferring a survival advantage to tumor cells during metastatic colonization through genomic evolution and immune remodeling, with metabolic adaptation as a downstream consequence of genomic alterations.

NMB↗

Integrative multi-omics and single-cell analysis identifies EGFR pathway activation and metabolic reprogramming as potential synthetic lethal vulnerabilities in resistance to the FGFR inhibitor AZD4547.

BACKGROUND: Although fibroblast growth factor receptor (FGFR) inhibitors (FGFRi) have demonstrated clinical promise, the inevitable emergence of acquired resistance remains a critical bottleneck, severely compromising their long-term clinical efficacy. The pan-cancer molecular landscape and heterogeneous mechanisms driving this resistance, ranging from genetic alterations to dynamic network rewiring, remain poorly understood. METHODS: We integrated large-scale pharmacogenomic profiling of the FGFR inhibitor AZD4547 from the GDSC2 and PRISM databases with single-cell RNA sequencing to dissect the multi-omics landscape of FGFRi resistance across 312 cell lines from 8 cancer types. This multi-omics framework was further extended by machine learning modeling and systematic synthetic lethality screening to uncover actionable therapeutic targets. In vitro viability assays and western blot analysis were subsequently conducted to experimentally evaluate the predicted FGFR-EGFR synthetic lethality. RESULTS: Our dual-database analysis unveiled a multi-dimensional atlas of FGFRi resistance. We identified cancer-specific genomic drivers, such as ELF4 amplification in glioblastoma, alongside key transcriptomic markers including UCP2 and FSCN1, highlighting a shift towards metabolic reprogramming and epithelial-mesenchymal transition (EMT). Single-cell analysis unveiled that resistance is linked to the heterogeneous enrichment of baseline subpopulations characterized by distinct metaprograms, including cell-cycle dysregulation. Furthermore, a random forest model built on a LASSO-derived transcriptomic signature was constructed, demonstrating promising predictive capability for AZD4547 sensitivity (mean test-set AUC = 0.73, 95% CI [0.63, 0.80]); the signature generalized well to erdafitinib but showed limited transferability to some other FGFR inhibitors (e.g. pemigatinib, BGJ398). Most notably, our synthetic lethal screening revealed a convergent reliance on compensatory RTK signaling (specifically EGFR pathway enrichment) and downstream MAPK/PI3K cascades in resistant phenotypes, providing converging computational evidence for EGFR pathway activation as an adaptive bypass mechanism. This predicted synthetic lethality was experimentally supported in two FGFR-dependent cell line models (RT112 and CCLP1), in which combined FGFR-EGFR inhibition produced marked synergistic antiproliferative effects. CONCLUSIONS: This study establishes a comprehensive multi-omics atlas of resistance to the FGFR inhibitor AZD4547, delineating convergent mechanisms of metabolic reprogramming and EGFR-mediated bypass signaling. Our findings characterize the resistance as a dynamic network rewiring and nominate rational combination strategies to overcome this therapeutic bottleneck. While FGFR-EGFR co-inhibition is experimentally supported, metabolic co-targeting remains a computationally derived, hypothesis-generating strategy.

Benzamides↗

Microarray analysis of IFN-gamma response genes in astrocytes.

IFN-gamma (IFN-gamma) has been shown to activate astrocytes to acquire immune functions. In this study the effect of IFN-gamma on murine astrocytes was investigated via microarray analysis. The activating effect of IFN-gamma on the astrocyte transcriptome showed predominance toward pathways involved in adaptive immunity, initiation of the immune response and innate immunity. Previously unknown astrocytic genes expressed included members of the p47 GTPases and guanine nucleotide binding protein (GBP) families. Down-regulatory effects of IFN-gamma stimulation were confined to pathways involved in growth regulation, cell differentiation and cell adhesion. This data supports the notion that astrocytes are an important immunocompetant cell in the brain and indicate that astrocytes may have a significant role in various infectious diseases such as Toxoplasmic Encephalitis and neurological diseases with an immunological component such as Alzheimer's and autoimmune disorders.

Animals↗

Experimental trial for diagnosis of pancreatic ductal carcinoma based on gene expression profiles of pancreatic ductal cells.

Pancreatic ductal carcinoma (PDC) remains one of the most intractable human malignancies, mainly because of the lack of sensitive detection methods. Although gene expression profiling by DNA microarray analysis is a promising tool for the development of such detection systems, a simple comparison of pancreatic tissues may yield misleading data that reflect only differences in cellular composition. To directly compare PDC cells with normal pancreatic ductal cells, we purified MUC1-positive epithelial cells from the pancreatic juices of 25 individuals with a normal pancreas and 24 patients with PDC. The gene expression profiles of these 49 specimens were determined with DNA microarrays containing >44 000 probe sets. Application of both Welch's analysis of variance and effect size-based selection to the expression data resulted in the identification of 21 probe sets corresponding to 20 genes whose expression was highly associated with clinical diagnosis. Furthermore, correspondence analysis and 3-D projection with these probe sets resulted in separation of the transcriptomes of pancreatic ductal cells into distinct but overlapping spaces corresponding to the two clinical classes. To establish an accurate transcriptome-based diagnosis system for PDC, we applied supervised class prediction algorithms to our large data set. With the expression profiles of only five predictor genes, the weighted vote method diagnosed the class of samples with an accuracy of 81.6%. Microarray analysis with purified pancreatic ductal cells has thus provided a basis for the development of a sensitive method for the detection of PDC.

Carcinoma, Pancreatic Ductal↗

Microarrays: new tools to unravel parasite transcriptomes.

The ability to monitor the expression levels of thousands of genes in a single microarray experiment is a huge progression from conventional Northern blot analysis or PCR-based techniques. Microarrays can play a pivotal role in the mass screening of genes in a wide range of fields including parasitology. The relatively few parasites that can be readily cultured or isolated from a host, as compared with cell lines or tissue sources, makes microarray technology ideal for maximizing experimental results from a limiting source of starting material. Khan et al. (1999 a) commented in an early review of microarray technology " With this system in place, one can anticipate a time when data from thousands of gene expression experiments will be available for meta-analysis........leading to more robust results and subtle conclusions". Now in 2005, microarrays represent a very powerful resource that can play an important role in the characterization and annotation of the transcriptomes of many parasites of medical and veterinary importance.

Animals↗

Attribution of PM2.5-Induced Transcriptomic Perturbation to Toxic Components.

Ambient fine particulate matter (PM2.5) is a chemically complex mixture whose health impacts are not fully captured by particle mass. Here, we developed an interpretable chemotranscriptomic framework to attribute PM2.5-induced molecular perturbations to toxicity-relevant components. PM2.5 collected from urban roadside and coastal environments was separated into whole, extractable, and unextractable fractions, characterized by LC/GC × GC-HRMS-based nontarget analysis and inductively coupled plasma mass spectrometry (ICP-MS), and evaluated using cytotoxicity testing and transcriptomic profiling in human bronchial epithelial cells. Urban PM2.5 exhibited greater cytotoxic potency per unit mass than coastal PM2.5, with extractable fractions accounting for most cytotoxic and pathway-level responses. Transcriptomics revealed distinct site-specific modes of action: urban PM2.5 preferentially induced oxidative stress, xenobiotic metabolism, and cell cycle suppression, consistent with acute, nonapoptotic injury, whereas coastal PM2.5 elicited weaker cytotoxicity but stronger interferon-mediated immune and apoptosis-related signaling. Integrating chemical abundance with pathway activity using random forest regression, SHAP interpretation, and mechanistic corroboration reduced 5,033 detected features to 444 pathway-linked candidate drivers. Fewer than 5% of features explained ∼95% of cumulative model contribution. Standard-confirmed contributors included plasticizer-related compounds, aromatic and heteroaromatic combustion products, and copper for urban PM2.5 and secondary/aged organics and nickel for coastal PM2.5. These findings support mechanism-informed prioritization of hazardous PM2.5 components beyond mass-based assessment.

Particulate Matter↗

The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases.

The increasing availability of genomic and transcriptomic sequencing has uncovered diverse genomic alterations and distinct gene expression profiles driving hematologic diseases, yet a data integration and sharing platform dedicated to hematology remains lacking. We developed the American Society of Hematology (ASH) HematOmics Program (ASHOP; ashop.hematology.org), a resource for exploring somatic alterations and gene fusions, transcriptomic results, and clinical data from 5960 patients spanning B-cell precursor and T-cell acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndromes, and chronic lymphocytic leukemia. Users can explore genomic alteration landscapes and comutation patterns via lollipop and matrix plots and analyze significantly altered genes in user-defined subcohorts. Transcriptomes can be explored through interactive uniform manifold approximation and projections, clustering, differential expression, and pathway enrichment. Genomic, transcriptomic features, and clinical outcomes can be correlated in a user-driven manner or combined to precisely define study cohorts. We illustrate the following 4 use cases of ASHOP: (1) stratification of DUX4-rearranged B-cell leukemias into Early/Multipotent and Committed subgroups with distinct outcomes, (2) characterization of HOXA/HOXB expression patterns in acute myeloid leukemias, (3) correlating mutational burden with mismatch repair deficiency and mutational signatures, and (4) investigation of TP53 alteration landscape. ASHOP is an open-access resource to inform genomic and transcriptomic data interpretation for hematologic malignancies and will expand to support additional diseases and data modalities from the ASH community.

Humans↗

Analysis of altered genomic expression profiles in the senescent and diseased myocardium using cDNA microarrays.

Cardiac function deteriorates with aging or disease. Short term, any changes in heart function may be beneficial, but long term the alterations are often detrimental. At a molecular level, functional adaptations involve quantitative and qualitative changes in gene expression. Analysis of all the RNA transcripts present in a cell's population (transcriptome) offers unprecedented opportunities to map these transitions. Microarrays (chips), capable of evaluating thousands of transcripts in one assay, are ideal for transcriptome analyses. Gene expression profiling provides information about the dynamics of total genome expression in response to environmental changes and may point to candidate genes responsible for the cascade of events that result in disease or are a consequence of aging. The aim of this review is to describe how comparisons of cellular transcriptomes by cDNA array based techniques provide information about the dynamics of total gene expression, and how the results can be applied to the study of cardiovascular disease and aging.

Cardiovascular Diseases↗