SEARCH · Search PubMed

Results for “Comprehensive genomic profiling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4Linked to original sources

PubMed2004

The Rice PIPELINE: a unification tool for plant functional genomics.

The Rice Genome Research Project in Japan performs genome sequencing and comprehensive expression profiling, constructs genetic and physical maps, collects full-length cDNAs and generates mutant lines, all aimed at improving the breeding of the rice plant as a food source. The National Institute of Agrobiological Sciences in Tsukuba, Japan, has accumulated numerous rice biological resources and has already successfully produced a high-quality genome sequence, a high-density genetic map with 3000 markers, 30,000 full-length cDNAs, over 700 expression profiles with a 9000 cDNA microarray and 15,000 flanking sequences with Tos17 insertions in about 3765 mutant lines from about 50,000 transposon insertion lines. These resources are available in the public domain. A new unification tool for functional genomics, called Rice PIPELINE, has also been developed for the dynamic collection and compilation of genomics data (genome sequences, full-length cDNAs, gene expression profiles, mutant lines, cis elements) from various databases. The mission of Rice PIPELINE is to provide a unique scientific resource that pools publicly available rice genomic data for search by clone sequence, clone name, GenBank accession number, or keyword. The web-based form of Rice PIPELINE is available at http://cdna01.dna.affrc.go.jp/PIPE/.

Computational Biology↗

PubMed2003

Cancer target discovery using SAGE.

Cancer is a genetic disease. Genetic events including mutations, chromosomal gains, losses and rearrangements, along with epigenetic alterations, lead to significant transcriptional changes in cancer cells. Changes in the expression of many genes associated with the onset and progression of cancer likely contribute to the cancerous phenotype. SAGE (Serial Analysis of Gene Expression) is an expression profiling method that allows for global, unbiased and quantitative characterisation of transcriptomes. The expression of thousands of genes can be analysed simultaneously without prior knowledge of their sequence, thus leading to the discovery of novel transcripts. In addition to characterising normal and malignant gene expression patterns, SAGE can be used to identify downstream targets of tumour suppressors and oncogenes and further annotate genomes. Comprehensive analyses of expression profiles using SAGE will yield many new diagnostic and prognostic markers as well as therapeutic targets in cancer.

Antineoplastic Agents↗

PubMed2001

Global profiling of gene expression in cancer using genomics and proteomics.

Global profiling of gene expression at the genomic level using DNA microarrays and at the protein level using a variety of technologies have followed separate paths. Studies of gene expression for several types of tumors, using DNA microarrays, have been published recently that are informative with respect to delineating distinct patterns of gene expression among subsets of related tumors. Proteomics-based profiling uniquely allows delineation of global changes in protein expression patterns resulting from transcriptional and post-transcriptional control, post-translational modifications and shifts in proteins between different cellular compartments. Some of the current technologies for proteome profiling and the application of proteomics to the analysis of tumor tissues are reviewed. Given that comprehensive expression profiles obtained using genomics and proteomics are highly complementary, a combined approach to profiling may well uncover expression patterns that could not be predicted using a single approach.

Gene Expression Profiling↗

PubMed2006

The transcription factor Gcr1 stimulates cell growth by participating in nutrient-responsive gene expression on a global level.

Transcriptomic reprogramming is critical to the coordination between growth and cell cycle progression in response to changing extracellular conditions. In Saccharomyces cerevisiae, the transcription factor Gcr1 contributes to this coordination by supporting maximum expression of G1 cyclins in addition to regulating both glucose-induced and glucose-repressed genes. We report here the comprehensive genome-wide expression profiling of gcr1Delta cells. Our data show that reduced expression of ribosomal protein genes in gcr1Delta cells is detectable both 20 min after glucose addition and in steady-state cultures of raffinose-grown cells, showing that this defect is not the result of slow growth or growth on a repressing sugar. However, the large cell phenotype of the gcr1Delta mutant occurs only in the presence of repressing sugars. GCR1 deletion also results in aberrant derepression of numerous glucose repressed loci; glucose-grown gcr1Delta cells actively respire, demonstrating that this global alteration in transcription corresponds to significant changes at the physiological level. These data offer an insight into the coordination of growth and cell division by providing an integrated view of the transcriptomic, phenotypic, and metabolic consequences of GCR1 deletion.

Carbon↗

PubMed2025

An Annotated Biobank of Triple-Negative Breast Cancer Patient-Derived Xenografts Features Treatment-Naïve and Longitudinal Samples during Neoadjuvant Chemotherapy.

UNLABELLED: Triple-negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC. To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in A Robust TNBC Evaluation fraMework to Improve Survival clinical trial (ARTEMIS, NCT02276443), including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT treatment and from metastatic disease. Models were established from both chemosensitive and chemoresistant tumors, and nearly 30% of the PDX models were capable of metastasizing to the lungs. Comprehensive molecular profiling demonstrated conservation of genomes and transcriptomes between patient and corresponding PDX tumors, with representation of all major transcriptional subtypes. Transcriptional changes observed in the longitudinal PDX models highlighted dysregulation in pathways associated with DNA integrity, extracellular matrix interactions, the ubiquitin-proteasome system, epigenetics, and inflammatory signaling. These alterations revealed a complex network of adaptations associated with chemoresistance. Overall, this PDX biobank provides a valuable tool for tackling the most pressing issues facing the clinical management of TNBC. SIGNIFICANCE: The development of a patient-derived xenograft biobank that comprehensively captures the genomic and transcriptional diversity of triple-negative breast cancer promises to be a robust resource to investigate and overcome chemoresistance and metastasis.

Animals↗

PubMed2002

Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer.

BACKGROUND: Drug resistance in breast cancer is a major obstacle to successful chemotherapy. In this study we used cDNA microarray technology to examine gene expression profiles obtained from fine needle aspiration (FNA) of primary breast tumors before and after systemic chemotherapy. Our goal was to determine the feasibility of obtaining representative expression array profiles from limited amounts of tissue and to identify those expression profiles that correlate with treatment response. METHODS: Repeat presurgical FNA samples were taken from six patients who were to undergo primary surgical treatment. Additionally, a group of 10 patients who were to receive neoadjuvant chemotherapy underwent two FNAs before chemotherapy (adriamycin 60 mg/m2 and cyclophosphamide 600 mg/m2) followed by another FNA on day 21 after the first cycle. Total RNA was amplified with T7 Eberwine's procedure and labeled cDNA was hybridized onto a 7600-feature glass cDNA microarray. RESULTS: We identified candidate gene expression profiles that might distinguish tumors with complete response to chemotherapy from tumors that do not respond, and found that the number of genes that change after one cycle of chemotherapy was 10 times greater in the responding group than in the non-responding group. CONCLUSION: This study supports the suitability of FNA-derived cDNA microarray expression profiling of breast cancers as a comprehensive genomic approach for studying the mechanisms of drug resistance. Our findings also demonstrate the potential of monitoring post-chemotherapy changes in expression profiles as a measure of pharmacodynamic effect and suggests that these approaches might yield useful results when validated by larger studies.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2005

The Plasmodium falciparum sexual development transcriptome: a microarray analysis using ontology-based pattern identification.

The sexual stages of malarial parasites are essential for the mosquito transmission of the disease and therefore are the focus of transmission-blocking drug and vaccine development. In order to better understand genes important to the sexual development process, the transcriptomes of high-purity stage I-V Plasmodium falciparum gametocytes were comprehensively profiled using a full-genome high-density oligonucleotide microarray. The interpretation of this transcriptional data was aided by applying a novel knowledge-based data-mining algorithm termed ontology-based pattern identification (OPI) using current information regarding known sexual stage genes as a guide. This analysis resulted in the identification of a sexual development cluster containing 246 genes, of which approximately 75% were hypothetical, exhibiting highly-correlated, gametocyte-specific expression patterns. Inspection of the upstream promoter regions of these 246 genes revealed putative cis-regulatory elements for sexual development transcriptional control mechanisms. Furthermore, OPI analysis was extended using current annotations provided by the Gene Ontology Consortium to identify 380 statistically significant clusters containing genes with expression patterns characteristic of various biological processes, cellular components, and molecular functions. Collectively, these results, available as part of a web-accessible OPI database (http://carrier.gnf.org/publications/Gametocyte), shed light on the components of molecular mechanisms underlying parasite sexual development and other areas of malarial parasite biology.

Animals↗

PubMed2002

Molecular and biologic basis of upper gastrointestinal malignancy--esophageal carcinoma.

Esophageal cancer is one of the most deadly forms of gastrointestinal cancer. Even though the incidence of esophageal adenocarcinoma has been rising in Western populations over the past two decades, esophageal squamous cell carcinoma remains the predominant type of esophageal malignancy in the remainder of the world. With the recent advances in molecular biology, high-output genome wide screening has provided comprehensive profiles of molecular alterations in human esophageal carcinomas. The elucidation of the basic mechanisms of esophageal carcinogenesis brings with it the promise of developing treatment and preventive strategies that are based on the molecular biology of these tumors. The genetic alterations discussed in this article are not unique to the formation of esophageal carcinomas and represent only a fraction of the molecular changes found in these tumors. The goal of this article is to provide the clinician with a useful conceptual basis for evaluating studies on the molecular mechanisms underlying the development of esophageal carcinomas.

Adenocarcinoma↗

PubMed2000

USAGE: a web-based approach towards the analysis of SAGE data. Serial Analysis of Gene Expression.

MOTIVATION: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should reside on a central server and be accessed via the internet. Since such an application was not available we developed the USAGE package. RESULTS: USAGE is a web-based application that comprises an integrated set of tools, which offers many functions for analysing and comparing SAGE data. Additionally, USAGE includes a statistical method for the planning of new SAGE experiments. USAGE is available in a multi-user environment giving users the option of sharing data. USAGE is interfaced to a relational database to store data and analysis results. The USAGE query editor allows the composition of queries for searching this database. Several database functions have been included which enable the selection and combination of data. USAGE provides the biologist increased functionality and flexibility for analysing SAGE data. AVAILABILITY: USAGE is freely accessible for academic institutions at http://www.cmbi.kun.nl/usage/. The source code of USAGE is freely available for academic institutions on request from the first author.

Databases, Factual↗

PubMed2006

High resolution analysis of non-small cell lung cancer cell lines by whole genome tiling path array CGH.

Chromosomal regions harboring tumor suppressors and oncogenes are often deleted or amplified. Array comparative genomic hybridization detects segmental DNA copy number alterations in tumor DNA relative to a normal control. The recent development of a bacterial artificial chromosome array, which spans the human genome in a tiling path manner with >32,000 clones, has facilitated whole genome profiling at an unprecedented resolution. Using this technology, we comprehensively describe and compare the genomes of 28 commonly used non-small cell lung carcinoma (NSCLC) cell models, derived from 18 adenocarcinomas (AC), 9 squamous cell carcinomas and 1 large cell carcinoma. Analysis at such resolution not only provided a detailed genomic alteration template for each of these model cell lines, but revealed novel regions of frequent duplication and deletion. Significantly, a detailed analysis of chromosome 7 identified 6 distinct regions of alterations across this chromosome, implicating the presence of multiple novel oncogene loci on this chromosome. As well, a comparison between the squamous and AC cells revealed alterations common to both subtypes, such as the loss of 3p and gain of 5p, in addition to multiple hotspots more frequently associated with only 1 subtype. Interestingly, chromosome 3q, which is known to be amplified in both subtypes, showed 2 distinct regions of alteration, 1 frequently altered in squamous and 1 more frequently altered in AC. In summary, our data demonstrate the unique information generated by high resolution analysis of NSCLC genomes and uncover the presence of genetic alterations prevalent in the different NSCLC subtypes.

Carcinoma, Non-Small-Cell Lung↗

PubMed2003

The ERGO genome analysis and discovery system.

The ERGO (http://ergo.integratedgenomics.com/ERGO/) genome analysis and discovery suite is an integration of biological data from genomics, biochemistry, high-throughput expression profiling, genetics and peer-reviewed journals to achieve a comprehensive analysis of genes and genomes. Far beyond any conventional systems that facilitate functional assignments, ERGO combines pattern-based analysis with comparative genomics by visualizing genes within the context of regulation, expression profiling, phylogenetic clusters, fusion events, networked cellular pathways and chromosomal neighborhoods of other functionally related genes. The result of this multifaceted approach is to provide an extensively curated database of the largest available integration of genomes, with a vast collection of reconstructed cellular pathways spanning all domains of life. Although access to ERGO is provided only under subscription, it is already widely used by the academic community. The current version of the system integrates 500 genomes from all domains of life in various levels of completion, 403 of which are available for subscription.

Animals↗

PubMed2007

Transcriptomic adaptations in rice suspension cells under sucrose starvation.

Sugar is an important resource for energy generation and developmental regulation in plants, and sucrose starvation causes enormous changes in cellular morphology, enzyme activities and gene expression. Genome-wide gene expression profiling provides a comprehensive knowledge of gene expression under nutrient depletion and senescence; however, that of a monocot model plant, rice, under sucrose depletion is still under investigation. Here, the time-course monitoring of gene expression profiles in sucrose-starved rice (Oryza sativa cv Tainung67) suspension cells was investigated by 21495 probes contained in Agilent rice chip. In sucrose-starved cells, the induced vacuolar biogenesis coincided with significantly upregulated transcripts of H+-pyrophosphatase, delta-TIP, one putative alpha-TIP, several vacuolar proteases and proteinase inhibitors, and one OsATG3. To survey the overall metabolic adaptations under sucrose depletion, the genes with significantly altered expression level were incorporated into multiple metabolic pathways. Most genes encoding enzymes involved in biosynthesis and degradation pathways of various macromolecules were comprehensively down-and upregulated, respectively, with sucrose starvation. Transcriptional regulation of gene expression is important for physiological adaptations to environmental stress, and many transcription factors, including bZIPs, NACs, and WRKY, showed significant increase in transcriptional level under sucrose starvation. Concurrently, statistical analysis revealed that their corresponding consensus cis-elements, such as ABA-responsive element, CACG, ACI, ACII and CTTATCC, were frequently found in the promoter regions of many sucrose starvation-upregulated genes. Particle bombardment-mediated and luciferase activity-based transient promoter assays revealed the CTTATCC, derived form TATCCA, and the AC motifs to be promising sucrose-starvation responsive activators in rice suspension cells.

Base Sequence↗

PubMedDate not supplied

Genomic assessment of pediatric acute leukemia.

Advances in molecular genetics have revolutionized our understanding of acute myeloid and lymphoblastic leukemia. Structural and numerical chromosomal aberrations are common, and their detection is vital for leukemia diagnosis, risk stratification, and monitoring of response to therapy. Fusion proteins resulting from chromosomal translocations are necessary but not sufficient for leukemogenesis, and there is intense research activity to elucidate the cooperating molecular abnormalities that may be suitable targets for novel therapeutic approaches. Candidate gene approaches have identified mutations in kinases and transcription factors in a proportion of patients, but more comprehensive genomic approaches are required. Gene expression profiling accurately classifies known subtypes of acute leukemia and has highlighted potentially leukemogenic abnormalities in gene expression. Newer techniques, such as single-nucleotide polymorphism arrays to analyze changes in gene copy number and zygosity, cancer genome sequencing, and RNA interference, are promising tools to identify mutations, although at present, data from these approaches are limited. This review provides an overview of these techniques in clinical practice and as research tools to develop new therapeutic approaches in pediatric leukemia.

Acute Disease↗

PubMed2026

Beyond borders: plasmids drive a shared antibiotic resistome in European urban water systems.

BACKGROUND: Urban wastewater systems (UWSs) act as reservoirs and conduits for the dissemination of antibiotic resistance genes (ARGs), with plasmids playing a central role in their spread. Despite their significance, the diversity and persistence of plasmids in UWSs remain underexplored. RESULTS: This study applies a multi-omics approach, including metagenomic and direct plasmidome sequencing, high-throughput qPCR array, and whole genome sequencing of plasmid isolates, to comprehensively profile the microbial plasmidome and resistome on 78 samples across UWSs in Denmark, Spain, and the UK. We successfully uncovered an extensive plasmid and ARG diversity that could not be fully captured by a single method, especially identified 78,574 plasmids, including 20,925 plasmids previously unreported. We also observed that plasmids carried a disproportionate share of clinically relevant ARGs, particularly beta-lactamase resistance genes; most importantly, they were preferentially located on transmissible plasmids. Furtherly, plasmids harbor ARG can enhance their persistence in wastewater ecosystems, especially harboring multiple types of ARGs. Moreover, Bacteroides emerged as a unique persistent ARG reservoir not only for harboring and disseminating diverse resistance genes especially in residential-relevant areas, but also emerged as a major driver of antimicrobial resistance dynamics across different wastewater treatment processes. CONCLUSIONS: Overall, this work provides the first attempt at a holistic description of the UWSs' resistome, its structure, dynamics, and mobility and significantly expands the current knowledge. Video Abstract.

Plasmids↗

PubMed2026

Fatty acid biosynthesis inhibitors fabimycin and triclosan trigger distinct resistance mutations in FabI and potently kill Gram-negative pathogens.

In the effort to develop efficacious antibacterials that engage targets for which there is no pre-existing resistance, inhibition of the enoyl-acyl carrier protein reductase FabI has shown promise, with triclosan and fabimycin as representative members of the two major drug classes that show activity against important bacterial pathogens. Here, we use a morbidostat and whole genome sequencing to comprehensively evaluate the resistance profiles that arise in pathogenic bacteria in response to these FabI inhibitors. When assessed against E. coli, fabimycin and triclosan were found to induce primarily non-overlapping resistance profiles leading to minimal cross-resistance between the two compounds. Furthermore, in vivo evaluation of the prominent resistant mutants indicates poor fitness, with the most fit mutant still susceptible to fabimycin. Collectively, these results suggest the combination use of two antibiotics that engage different positions on the same target as a means to kill pathogenic bacteria and limit resistance.

Journal Article↗

PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗

PubMed2005

Breast cancer gene expression profiling: clinical trial and practice implications.

The advent of high-throughput array-based technology and the sequencing of the human genome has provided the opportunity to begin comprehensive molecular and genetic profiling of cancers. Such efforts have, in a limited time, given us new insights into breast cancer biology and confirmed that the disease is considerably more heterogeneous than can be predicted by traditional histopathological methods. The estrogen receptor has been found to be the most dominant factor influencing the molecular composition of breast cancer and, in addition, novel subgroups of breast cancer with differing clinical outcomes have been observed. These may have substantial management implications for breast cancer patients and facilitate individualized rather than empirical oncological prescription. Furthermore, new methods of prognostic classification have been developed using array technology. The challenges ahead lie in refining the use of the technology, proper validation of discoveries, and the large-scale collaborative efforts necessary for the incorporation of genomic knowledge into the design and conduct of clinical trials. This will lead, ultimately, to the application of user-friendly tools derived from this technology to everyday patient care.

Biomarkers, Tumor↗

PubMed2026

Genomic reconstruction of the Pakistani Roma reveals dual South Asian ancestry, medieval bottlenecks, and the early dispersal routes of the Romani people.

The Roma people represent one of the largest and most historically enigmatic diasporas in Eurasia, illuminating human migration patterns and cultural resilience across continents. Despite extensive research on European Roma as the diaspora endpoint, the genetic legacy of their putative South Asian source populations remains critically underexplored, leaving fundamental gaps in understanding the pre-diaspora demographic structure and early dispersal dynamics. This study uniquely positions Pakistani Roma as a potential ancestral reservoir, offering a rare window into the pre-migration phase distinct from derived European Roma populations shaped by centuries of post-dispersal admixture. We analyze 82 Pakistani Roma from Punjab using high-resolution genome-wide SNP data and comprehensive mitochondrial haplogroup profiling to reconstruct their genetic origins, population structure, and historical trajectory. Analyses reveal a dual ancestry profile comprising 50-82% Indus Valley related, 20-30% Onge related, and up to 26% Steppe derived components, with three distinct subgroups exhibiting varying affinities along a South Asian to Central Western Eurasian continuum reflecting jati-like endogamy. A severe demographic bottleneck ~800 years ago coincides with medieval socio-political upheavals, while major Eurasian admixture is dated to ~660 years ago. Mitochondrial haplogroups H (45.12%) and M (26.83%) underscore dual maternal influences from West and South Eurasia. Pakistani Roma retain substantially higher South Asian ancestry than their European counterparts, establishing them as a genetically distinct population preserving the ancestral pre-diaspora state. These findings redefine the Romani origin narrative and underscore the critical value of understudied South Asian minorities in reconstructing complex human migration pathways and diaspora formation mechanisms.

Humans↗