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PubMed2025

Identification of Novel Wraparound Transcripts in JC Polyomavirus.

JC polyomavirus (JCPyV) is a ubiquitous pathogen that causes progressive multifocal leukoencephalopathy (PML). Although a recent study using next-generation sequencing (NGS) provided detailed transcriptome atlases for polyomaviruses (PyVs) such as BK polyomavirus and simian virus 40, the transcriptome of JCPyV remains poorly characterized. Here, we conducted a comprehensive analysis using both short-read and long-read NGS technologies to construct a transcriptome atlas of JCPyV. RNA extracted from IMR-32 and HEK293 cells transfected with the circular JCPyV genome was analyzed, leading to the identification of 39 previously uncharacterized viral transcripts in addition to 12 known ones. Among the novel transcripts, we identified wraparound transcripts, conserved across PyVs, which are generated through continuous, multicyclic transcription of the circular viral genome. These included both late transcripts containing leader-to-leader repeated sequences and SuperT transcripts with multiple LxCxE motifs. Notably, wraparound transcripts, including SuperT transcripts, were also detected in brain tissues from PML patients. Collectively, this study significantly expands our understanding of the JCPyV transcriptome, revealing the expression of wraparound transcripts in PML lesions. These findings provide valuable insights into the molecular basis of JCPyV gene expression and PML pathogenesis, potentially facilitating the development of effective countermeasures against PML.

JC Virus↗

PubMed2006

Membrane-associated transcripts in Arabidopsis; their isolation and characterization by DNA microarray analysis and bioinformatics.

Membrane-associated, integral membrane and secreted proteins are of key importance in many cellular processes. For most of the 28,952 predicted proteins in Arabidopsis, the actual subcellular localization has not been demonstrated experimentally. So far, their potential membrane-association has been deduced from algorithms that predict transmembrane domains and signal peptides. However, the comprehensiveness and accuracy of these algorithms is still limited. The majority of membrane-associated and secreted proteins is synthesized on membrane-bound polysomes. Therefore, the isolation and characterization of mRNA associated with membrane-bound polysomes offers an experimental tool for the genome-wide identification of these proteins. Here we describe an efficient method to isolate mRNA from membrane-bound polysomes and report on the validation of the method to enrich for transcripts encoding membrane-associated and secreted proteins. The sensitivity and reproducibility of the isolation method was investigated by DNA microarray analysis. Pearson correlations between transcript levels obtained from three replicate isolations showed that the method is highly reproducible. A significant enrichment for mRNAs encoding proteins containing predicted transmembrane domains and signal peptides was observed in the membrane-bound polysomal fraction. In this fraction, 301 transcripts were classified by gene ontologies as 'cellular component unknown', and potentially encode previously unrecognized secreted or membrane-associated proteins.

Algorithms↗

PubMed2004

New challenges in gene expression data analysis and the extended GEPAS.

Since the first papers published in the late nineties, including, for the first time, a comprehensive analysis of microarray data, the number of questions that have been addressed through this technique have both increased and diversified. Initially, interest focussed on genes coexpressing across sets of experimental conditions, implying, essentially, the use of clustering techniques. Recently, however, interest has focussed more on finding genes differentially expressed among distinct classes of experiments, or correlated to diverse clinical outcomes, as well as in building predictors. In addition to this, the availability of accurate genomic data and the recent implementation of CGH arrays has made mapping expression and genomic data on the chromosomes possible. There is also a clear demand for methods that allow the automatic transfer of biological information to the results of microarray experiments. Different initiatives, such as the Gene Ontology (GO) consortium, pathways databases, protein functional motifs, etc., provide curated annotations for genes. Whereas many resources on the web focus mainly on clustering methods, GEPAS has evolved to cope with the aforementioned new challenges that have recently arisen in the field of microarray data analysis. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://gepas.bioinfo.cnio.es.

Gene Expression Profiling↗

PubMed2002

Metabonomic applications in toxicity screening and disease diagnosis.

Biofluid NMR spectroscopy is a powerful tool providing a comprehensive metabolic profile of the low molecular weight components in biofluids that reflect concentrations and fluxes of endogenous metabolites involved in key intermediary cellular pathways, thereby giving an indication of an organisms physiological or pathophysiological status [1]. The interaction of pharmacological agents with cells and tissues can also be monitored using recently developed high resolution magic-angle spinning (HRMAS) NMR spectroscopic technology for biological matrices [1]. However, recent developments in both spectrometer and software technology has resulted in improved capacity for sample handling, leading to a rapid growth in the size of toxicological spectral databases, and increased the complexity of the biological spectral data generated. Thus more emphasis has been placed on the need to develop improved automated procedures for data processing and interpretation. By harnessing chemometric tools for analysis of complex spectral data, the toxicological consequences of xenobiotic exposure can be evaluated efficiently on line. Automation of spectral processing procedures and the construction of mathematically based 'expert systems' for the prediction of drug-induced toxicity founded on IH NMR spectral profiles have now been achieved. Chemometric analysis of biological NMR spectra has provided the main analytical platform for metabonomic analysis, providing a systems approach to evaluating pathophysiological or genetic influences on the metabolic status of an organism [1]. This technology is currently being given high-priority in the pharmaceutical industry with respect to development of efficient high throughput toxicity screening systems for lead candidate selection. In this article, we review the recent developments in metabonomics and consider their application in toxicological screening, disease diagnosis and functional genomics.

Animals↗

PubMed2005

Novel isothermal, linear nucleic acid amplification systems for highly multiplexed applications.

BACKGROUND: Global analysis of the genome, transcriptome, and proteome is facilitated by the recent development of tools for large-scale, highly parallel analysis. We describe a novel nucleic acid amplification system that generates products by several methods. 3'-Ribo-SPIA primes cDNA synthesis at the 3' polyA tail, and whole transcript (WT)-Ribo-SPIA primes cDNA synthesis across the full length of the transcripts and thus provides whole-transcriptome amplification, independent of the 3' polyA tail. METHODS: We developed isothermal linear nucleic acid amplification systems, which use a single chimeric primer, for amplification of DNA (SPIA) and RNA (Ribo-SPIA). The latter allows mRNA amplification from as little as 1 ng of total RNA. Amplification efficiency was calculated based on the delta threshold cycle between nonamplified cDNA targets and amplified cDNA. The amounts and quality of total RNA and amplification products were determined after purification of the amplification products. GeneChip array gene expression profiling and real-time PCR were used to test the accuracy and reproducibility of the method. Quantification of cDNA products (before and after amplification) at the 2 loci along the transcripts was used to assess product length (for evaluation of the 3'-initiated Ribo-SPIA) and equal representation throughout the length of the transcript (for evaluation of the whole transcript amplification system, WT-Ribo-SPIA). RESULTS: Ribo-SPIA-based global RNA amplification exhibited linearity over 6 orders of magnitude of transcript abundance and generated microgram amounts of amplified cDNA from as little as 1 ng of total RNA. CONCLUSIONS: The described methods enable comprehensive gene expression profiling and analysis from limiting biological samples. The WT-Ribo-SPIA procedure, which enables amplification of non-polyA-tailed RNA, is suitable for amplification and gene expression analysis of both eukaryotic and prokaryotic biological samples.

Gene Expression Profiling↗

PubMed2025

A comprehensive analysis of supermere, exomere, and extracellular vesicle isolation and cargo in colorectal cancer.

Biofluids contain a heterogeneous mixture of extracellular vesicles and non-vesicular nanoparticles (including exomeres and supermeres) that transport a diverse array of proteins, RNA, and lipids. Our previous efforts to characterize the contents of these carriers in colorectal cancer relied on 2D culture systems requiring large-scale setups and time-consuming ultracentrifugation-based isolation. To streamline this process, we have combined 3D hollow-fiber bioreactor production and fast-protein liquid chromatography-based size-exclusion chromatography. Here, we compare the impact of culture methods and purification strategies on small extracellular vesicle, exomere, and supermere cargo. Proteomic analyses show consistently distinct profiles for extracellular vesicles, exomeres, and supermeres regardless of culture conditions or isolation method. In contrast, these two variables influence small RNAs, their base modifications, and lipidomic profiles. We present an online tool to query these and future secretome datasets (https://superomics.shinyapps.io/browse).

Humans↗

PubMed2024

Exploring the prognostic landscape of oral squamous cell carcinoma through mitochondrial damage-related genes.

Oral squamous cell carcinoma (OSCC), the most prevalent form of oral cancer, poses significant challenges to the medical community due to its high recurrence rate and low survival rate. Mitochondrial Damage-Related Genes (MDGs) have been closely associated with the occurrence, metastasis, and progression of OSCC. Consequently, we constructed a prognostic model for OSCC based on MDGs and identified potential mitochondrial damage-related biomarkers. Gene expression profiles and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Differential analysis was conducted to identify MDGs associated with OSCC. COX analysis was employed to screen seven prognosis-related MDGs and build a prognostic prediction model for OSCC. Cases were categorized into low-risk or high-risk groups based on the optimal risk score threshold. Kaplan-Meier (KM) analysis revealed significant survival differences (P < 0.05). Additionally, the area under the ROC curve (AUC) for patient survival at 1 year, 3 years, and 5 years were 0.687, 0.704, and 0.70, respectively, indicating a high long-term predictive accuracy of the prognostic model. To enhance predictive accuracy, age, gender, risk score, and TN staging were incorporated into a nomogram and verified using calibration curves. Risk scoring based on MDGs was identified as a potential independent prognostic biomarker. Furthermore, BID and SLC25A20 were identified as two potential independent mitochondrial damage-related prognostic biomarkers, offering new therapeutic targets for OSCC.

Humans↗

PubMed2002

Targets of gene amplification and overexpression at 17q in gastric cancer.

DNA copy number gains and amplifications at 17q are frequent in gastriccancer, yet systematic analyses of the 17q amplicon have not been performed. In this study, we carried out a comprehensive analysis of copy number and expression levels of 636 chromosome 17-specific genes in gastric cancer by using a custom-made chromosome 17-specific cDNA microarray. Analysis of DNA copy number changes by comparative genomic hybridization on cDNA microarray revealed increased copy numbers of 11 known genes (ERBB2, TOP2A, GRB7, ACLY, PIP5K2B, MPRL45, MKP-L, LHX1, MLN51, MLN64, and RPL27) and seven expressed sequence tags (ESTs) that mapped to 17q12-q21 region. To investigate the genes transcribed at the 17q, we performed gene expression analyses on an identical cDNA microarray. Our expression analysis showed overexpression of 8 genes (ERBB2, TOP2A, GRB2, AOC3, AP2B1, KRT14, JUP, and ITGA3) and two ESTs. Of the commonly amplified transcripts, an uncharacterized EST AA552509 and the TOP2A gene were most frequently overexpressed in 82% of the samples. Additional studies will be initiated to understand the possible biological and clinical significance of these genes in gastric cancer development and progression.

Blotting, Northern↗

PubMed2004

Global impact of mature biofilm lifestyle on Escherichia coli K-12 gene expression.

The formation of biofilm results in a major lifestyle switch that is thought to affect the expression of multiple genes and operons. We used DNA arrays to study the global effect of biofilm formation on gene expression in mature Escherichia coli K-12 biofilm. We show that, when biofilm is compared with the exponential growth phase, 1.9% of the genes showed a consistent up- or downregulation by a factor greater than two, and that 10% of the E. coli genome is significantly differentially expressed. The functions of the genes induced in these conditions correspond to stress response as well as energy production, envelope biogenesis and unknown functions. We provide evidence that the expression of stress envelope response genes, such as the psp operon or elements of the cpx and rpoE pathways, is a general feature of E. coli mature biofilms. We also compared biofilm with the stationary growth phase and showed that the biofilm lifestyle, although sharing similarities with the stationary growth phase, triggers the expression of specific sets of genes. Using gene disruption of 54 of the most biofilm-induced genes followed by a detailed phenotypic study, we validated the biological relevance of our analysis and showed that 20 of these genes are required for the formation of mature biofilm. This group includes 11 genes of previously unknown function. These results constitute a comprehensive analysis of the global transcriptional response triggered in mature E. coli biofilms and provide insights into its physiological signature.

Biofilms↗

PubMed2006

Comprehensive analysis of the renal transcriptional response to acute uranyl nitrate exposure.

BACKGROUND: Chemical and radiological toxicities related to uranium acute exposure have been widely studied in nuclear fuel workers and military personnel. It is well known that uranyl nitrate induces acute renal failure (ARF). However, the mechanisms of this metal-induced injury are not well defined at the molecular level. RESULTS: Renal function and histology were assessed in mice receiving uranyl nitrate (UN(+)) and controls (UN(-)). To identify the genomic response to uranium exposure, serial analysis gene expression (SAGE) of the kidney was performed in both groups. Over 43,000 mRNA SAGE tags were sequenced. A selection of the differentially expressed transcripts was confirmed by real-time quantitative PCR and Western blotting. UN(+) animals developed renal failure and displayed the characteristic histological lesions of UN nephropathy. Of the >14,500 unique tags identified in both libraries, 224 had a modified expression level; they are known to participate in inflammation, ion transport, signal transduction, oxidative stress, apoptosis, metabolism, and catabolism. Several genes that were identified had not previously been evaluated within the context of toxic ARF such as translationally controlled tumor protein, insulin like growth factor binding protein 7 and ribosomal protein S29, all apoptosis related genes. CONCLUSION: We report a comprehensive description of the UN induced modifications in gene expression levels, including the identification of genes previously unrelated to ARF. The study of these genes and the metabolisms they control should improve our understanding of toxic ARF and enlighten on the molecular targets for potential therapeutic interventions.

Acute Kidney Injury↗

PubMed2005

Changes of anti-oxidative enzymes and MDA content under soil water deficits among 10 wheat (Triticum aestivum L.) genotypes at maturation stage.

Drought is a world-spread problem seriously influencing grain production and quality, the loss of which is the total for other natural disasters, with increasing global climate change making the situation more serious. Wheat is the staple food for more than 35% of world population, so wheat anti-drought physiology study is of importance to wheat production and biological breeding for the sake of coping with abiotic and biotic conditions. Much research is involved in this hot topic, but the pace of progress is not so large because of drought resistance being a multiple-gene-control quantitative character and wheat genome being larger (16,000Mb). On the other hand, stress adaptive mechanisms are quite different, with stress degree, time course, materials, soil quality status and experimental plots, thus increasing the complexity of the issue in question. Additionally, a little study is related to the whole life circle of wheat, which cannot provide a comprehensive understanding of its anti-drought machinery. We selected 10 kinds of wheat genotypes as materials, which have potential to be applied in practice, and measured change of relative physiological indices through wheat whole growing-developmental circle (i.e. seedling, tillering and maturing). Here, we reported the anti-oxidative results of maturation stage (the results of seedling and tillering stage have been published) in terms of activities of POD, SOD, CAT and MDA content as follows: (1) 10 wheat genotypes can be grouped into three kinds (A-C, respectively) according to their changing trend of the measured indices; (2) A group performed better resistance drought under the condition of treatment level 1 (appropriate level), whose activities of anti-oxidative enzymes (POD, SOD, CAT) were higher and MDA lower; (3) B group exhibited stronger anti-drought under treatment level 2 (light-stress level), whose activities of anti-oxidative enzymes were higher and MDA lower; (4) C group expressed anti-drought to some extent under treatment level 3 (serious-stress level), whose activities of anti-oxidative enzymes were stronger, MDA lower; (5) these results demonstrated that different wheat genotypes have different physiological mechanisms to adapt themselves to changing drought stress, whose molecular basis is discrete gene expression profiling (transcriptom); (6) our results also showed that the concept and method accepted and adopted by most researchers [T.C. Hsiao, Plant response to water stress, Ann. Rev. Plant Physiol. 24 (1973) 519-570], that 75% FC is a proper supply for higher plants, was doubted, because this level could not reflect the true suitable level of different wheat genotypes. The study in this respect is the key to wheat anti-drought and biological-saving water agriculture; (7) our research can provide insights into physiological mechanisms of crop anti-drought and direct practical materials for wheat anti-drought breeding; (8) the physiological study of wheat is more urgent up-to-date and molecular aspects are needed, but cannot substitute this important part. The combination of both is an important strategy and a key and (9) POD, SOD and CAT activities and MDA content of different wheat genotypes had quite different changing trend at different stages and under different soil water stress conditions, which was linked with their origin of cultivation and individual soil water threshold.

Antioxidants↗

PubMed2004

Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes.

We describe a comprehensive modeling approach to combining genomic and clinical data for personalized prediction in disease outcome studies. This integrated clinicogenomic modeling framework is based on statistical classification tree models that evaluate the contributions of multiple forms of data, both clinical and genomic, to define interactions of multiple risk factors that associate with the clinical outcome and derive predictions customized to the individual patient level. Gene expression data from DNA microarrays is represented by multiple, summary measures that we term metagenes; each metagene characterizes the dominant common expression pattern within a cluster of genes. A case study of primary breast cancer recurrence demonstrates that models using multiple metagenes combined with traditional clinical risk factors improve prediction accuracy at the individual patient level, delivering predictions more accurate than those made by using a single genomic predictor or clinical data alone. The analysis also highlights issues of communicating uncertainty in prediction and identifies combinations of clinical and genomic risk factors playing predictive roles. Implicated metagenes identify gene subsets with the potential to aid biological interpretation. This framework will extend to incorporate any form of data, including emerging forms of genomic data, and provides a platform for development of models for personalized prognosis.

Bayes Theorem↗

PubMed2026

Functional analysis of Candida albicans protein kinases identifies Crk1 as a modulator of epithelial cell damage.

UNLABELLED: The commensal and pathogenic lifestyles of the opportunistic fungal pathogen Candida albicans require complex signaling networks regulated by protein kinases. To investigate the role of C. albicans protein kinases at the intestinal epithelial interface, we screened a comprehensive protein kinase deletion library for the capacity of the mutants to damage intestinal epithelial cells (IEC). Mutants showing altered IEC cytotoxicity relative to the wild type were further analyzed for their growth and morphology, focusing on hyper-damaging strains to identify kinases that rather prevent host cell damage. Deletion of CRK1 caused increased IEC-specific damage, despite slower growth, reduced hyphal length, and reduced adhesion as compared to wild-type cells. While tissue invasion levels and the formation of transcellular tunnels of the crk1Δ/Δ mutant were increased, the translocation capacity through the IEC barrier was reduced. Transcriptional and metabolic profiling suggested a role for Crk1 in metabolic adaptation to carbon and nitrogen sources, which was validated by showing that high glucose and amino acids are required for crk1Δ/Δ to cause increased IEC damage. Deletion of CRK1 rendered C. albicans more susceptible to cell wall and membrane stressors, but caused higher resistance to a catalase-specific and histidine biosynthesis inhibitor. This phenotypic pattern of medium- and epithelial cell type-specific cytotoxicity displayed by a C. albicans protein kinase mutant suggests that Crk1 regulates processes linked to carbon and amino acid metabolism that are relevant to interactions with intestinal epithelial cells. IMPORTANCE: Microbial signal transduction pathways regulate adaptation to changing environmental conditions and facilitate the success of many microbes during interactions with their hosts. The fungal pathobiont Candida albicans exists as a harmless commensal on mucosal surfaces of most humans but can also cause superficial and invasive infections under certain circumstances. Both lifestyles require complex signaling networks, predominantly regulated by protein kinases. The C. albicans genome was predicted to encode 108 protein kinases, yet nearly 50% remain uncharacterized. We aimed to dissect the role of C. albicans protein kinases during the transition from commensal to pathogen. We showed that multiple protein kinase genes are involved in epithelial cell damage. Particularly, the protein kinase gene Crk1 was of interest because deletion of CRK1 caused increased damage to intestinal epithelial cells under distinct conditions. Our study links Crk1 with regulation of metabolic processes relevant for commensalism and pathogenicity of C. albicans.

Candida albicans↗

PubMed2006

The transcriptome of human oocytes.

The identification of genes and deduced pathways from the mature human oocyte can help us better understand oogenesis, folliculogenesis, fertilization, and embryonic development. Human metaphase II oocytes were used within minutes after removal from the ovary, and its transcriptome was compared with a reference sample consisting of a mixture of total RNA from 10 different normal human tissues not including the ovary. RNA amplification was performed by using a unique protocol. Affymetrix Human Genome U133 Plus 2.0 GeneChip arrays were used for hybridizations. Compared with reference samples, there were 5,331 transcripts significantly up-regulated and 7,074 transcripts significantly down-regulated in the oocyte. Of the oocyte up-regulated probe sets, 1,430 have unknown function. A core group of 66 transcripts was identified by intersecting significantly up-regulated genes of the human oocyte with those from the mouse oocyte and from human and mouse embryonic stem cells. GeneChip array results were validated using RT-PCR in a selected set of oocyte-specific genes. Within the up-regulated probe sets, the top overrepresented categories were related to RNA and protein metabolism, followed by DNA metabolism and chromatin modification. This report provides a comprehensive expression baseline of genes expressed in in vivo matured human oocytes. Further understanding of the biological role of these genes may expand our knowledge on meiotic cell cycle, fertilization, chromatin remodeling, lineage commitment, pluripotency, tissue regeneration, and morphogenesis.

Animals↗

PubMed2006

Identification of putative oncogenes in lung adenocarcinoma by a comprehensive functional genomic approach.

Amplification and overexpression of putative oncogenes confer growth advantages for tumor development. We used a functional genomic approach that integrated simultaneous genomic and transcript microarray, proteomics, and tissue microarray analyses to directly identify putative oncogenes in lung adenocarcinoma. We first identified 183 genes with increases in both genomic copy number and transcript in six lung adenocarcinoma cell lines. Next, we used two-dimensional polyacrylamide gel electrophoresis and mass spectrometry to identify 42 proteins that were overexpressed in the cancer cells relative to normal cells. Comparing the 183 genes with the 42 proteins, we identified four genes - PRDX1, EEF1A2, CALR, and KCIP-1 - in which elevated protein expression correlated with both increased DNA copy number and increased transcript levels (all r > 0.84, two-sided P < 0.05). These findings were validated by Southern, Northern, and Western blotting. Specific inhibition of EEF1A2 and KCIP-1 expression with siRNA in the four cell lines tested suppressed proliferation and induced apoptosis. Parallel fluorescence in situ hybridization and immunohistochemical analyses of EEF1A2 and KCIP-1 in tissue microarrays from patients with lung adenocarcinoma showed that gene amplification was associated with high protein expression for both genes and that protein overexpression was related to tumor grade, disease stage, Ki-67 expression, and a shorter survival of patients. The amplification of EEF1A2 and KCIP-1 and the presence of overexpressed protein in tumor samples strongly suggest that these genes could be oncogenes and hence potential targets for diagnosis and therapy in lung adenocarcinoma.

Adenocarcinoma↗

PubMed2026

Oncogenic PIK3CA reprograms glutamine metabolism to drive bladder cancer progression.

BACKGROUND: Genomic analysis has revealed that approximately 40% of bladder cancer (BLCA) tumors harbor alterations in the PI3K/AKT pathway, with PIK3CA mutations occurring in 15-25% of cases. PIK3CA, which encodes the catalytic p110α subunit of PI3K, plays a critical role in regulating cell survival, proliferation, and metabolism. However, the metabolic and functional consequences of PIK3CA mutations in BLCA remain poorly defined. METHODS: To investigate the role of PIK3CA mutations in BLCA, we performed targeted sequencing on tumors from patients, identifying recurrent alterations. Using CRISPR/Cas9 knock-in models in SCaBER and UM-UC-3 cell lines, we introduced the PIK3CA E545K mutation to study its effects. We conducted transcriptomic profiling, targeted metabolomics, and stable isotope tracing to assess metabolic reprogramming. Functional assays measured proliferation, mitochondrial complex I activity, and glutaminolysis. Orthotopic xenografts in mice were used to evaluate in vivo tumor growth and metabolism. RESULTS: PIK3CA mutations were present in 20% of cases, consistent with TCGA data. The E545K and E545Q hotspots accounted for 70% of these mutations. PIK3CA E545K strongly activated PI3K/AKT signaling. Transcriptomic analysis revealed enrichment of OXPHOS, fatty acid metabolism, and mTORC1 signaling. Metabolomics indicated changes in TCA cycle metabolites and enhanced reductive carboxylation of glutamine to citrate, driving fatty acid synthesis. Mutant cells showed increased expression of GLS1 and FASN, higher proliferation rates, and elevated mitochondrial complex I activity. In vivo, PIK3CA-mutant xenografts displayed significantly increased tumor growth. CONCLUSION: PIK3CA mutations are frequent drivers of metabolic reprogramming in BLCA, leading to increased glutamine flux, elevated OXPHOS activity, and enhanced fatty acid synthesis, all of which contribute to tumor progression. These findings provide the first comprehensive evidence that PIK3CA-driven metabolic alterations are both biomarkers of aggressive disease and actionable therapeutic targets. The efficacy of PI3Kα inhibition in combination with metabolic targets may support its potential in precision medicine for PIK3CA-mutant BLCA and highlights the value of integrating metabolic biomarkers into treatment strategies for advanced BLCA.

Journal Article↗

PubMed2002

Altered gene expression profiles of rat lung in response to an emission particulate and its metal constituents.

Comprehensive and systematic approaches are needed to understand the molecular basis for the health effects of particulate matter (PM) reported in epidemiological studies. Due to the complex nature of the pollutant and the altered physiological conditions of predisposed populations, it has been difficult to establish a direct cause and effect relationship. A high-throughput technology such as gene expression profiling may be useful in identifying molecular networks implicated in the health effects of PM and its causative constituents. Differential gene expression profiles derived for rat lungs exposed to PM and its constituent metals using a custom rat cardiopulmonary cDNA array are presented here. This array consists of 84 cardiopulmonary-related genes representing various biological functions such as lung injury/inflammation, repair/remodeling, structural and matrix alterations, and vascular contractility, as well as six expressed sequence tags (ESTs). The cDNA array was hybridized with (32)P-labeled cDNA generated from rat lung RNA. Total lung RNA was isolated from male Sprague-Dawley rats at 3 and 24 h following intratracheal instillation of either saline, residual oil fly ash (ROFA; 3.3 mg/kg), or its most toxic metallic constituents, nickel (NiSO(4); 3.3 mmol/kg) and vanadium (VSO(4); 5.7 mmol/kg). Metal concentrations reflected the levels present in one ROFA instillate. Densitometric scans of the array blots indicated ROFA- and metal-specific increased expression (1.5 to 3-fold) of stress response, inflammatory, and repair-related genes, and also genes involved in vascular contractility and thrombogenic activity. Expression of multiple cytokines in ROFA exposed rat lung compared to Ni and V suggest the role and importance of understanding constituent interactions in PM toxicity. Expression profiling using genomic approaches will aid in our understanding of toxicant-specific altered molecular pathways in lung injury and pathogenesis.

Air Pollutants↗

PubMed2006

Transcriptomic and phylogenetic analysis of Kpna genes: a family of nuclear import factors modulated in xenobiotic-mediated liver growth.

OBJECTIVES: We have identified a member of the karyopherin (importin) alpha family of nuclear import factors as being modulated in rat liver following exposure to the hypolipidaemic and liver growth agent Wy-14,643. To examine the hypothetical role of this protein family as a checkpoint in receptor-mediated signalling, we characterized the rat karyopherin alpha (Kpna) gene family and present cDNA sequences and gene structures for all six rat Kpna genes. Further, we have assembled a comprehensive panel of Kpna coding regions from a range of metazoa, which we have subjected to phylogenetic analysis: This represents by far the most complete phylogenetic study of metazoan karyopherins, including several evolutionary intermediates not previously examined. The phylogeny reveals three Kpna subfamilies with distinct, conserved gene structures, shedding light on the evolutionary origins of this multigene family in metazoa. METHODS AND RESULTS: Using quantitative PCR, we have analysed Kpna transcript levels in 44 rat tissues; Kpna transcripts show a wide variation in their distribution both in absolute and relative terms, suggestive of specialized roles for each member. We also demonstrate that Kpna genes are regulated in rat liver and isolated hepatocytes in a xenobiotic-specific manner for a number of chemically distinct liver growth agents. CONCLUSIONS: In light of the crucial role of nuclear import in mediating the genomic changes elicited through nuclear receptor activation, we postulate that changes in the levels of specific karyopherins alpha during xenobiotic-mediated liver growth represent an important component of the cellular response to the external stimuli that trigger these events.

Active Transport, Cell Nucleus↗