Search PubMed⌕ Search

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.

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

At least 307 records · Page 17Linked to original sources
PubMed2000

Comprehensive lipid analysis: a powerful metanomic tool for predictive and diagnostic medicine.

The power and accuracy of predictive diagnostics stand to improve dramatically as a result of lipid metanomics. The high definition of data obtained with this approach allows multiple rather than single metabolites to be used in markers for a group. Since as many as 40 fatty acids are quantified from each lipid class, and up to 15 lipid classes can be quantified easily, more than 600 individual lipid metabolites can be measured routinely for each sample. Because these analyses are comprehensive, only the most appropriate and unique metabolites are selected for their predictive value. Thus, comprehensive lipid analysis promises to greatly improve predictive diagnostics for phenotypes that directly or peripherally involve lipids. A broader and possibly more exciting aspect of this technology is the generation of metabolic profiles that are not simply markers for disease, but metabolic maps that can be used to identify specific genes or activities that cause or influence the disease state. Metanomics is, in essence, functional genomics from metabolite analysis. By defining the metabolic basis for phenotype, researchers and clinicians will have an extraordinary opportunity to understand and treat disease. Much in the same way that gene chips allow researchers to observe the complex expression response to a stimulus, metanomics will enable researchers to observe the complex metabolic interplay responsible for defining phenotype. By extending this approach beyond the observation of individual dysregulations, medicine will begin to profile not single diseases, but health. As health is the proper balance of all vital metabolic pathways, comprehensive or metanomic analysis lends itself very well to identifying the metabolite distributions necessary for optimum health. Comprehensive and quantitative analysis of lipids would provide this degree of diagnostic power to researchers and clinicians interested in mining metabolic profiles for biological meaning.

Biomarkers↗
PubMed2003

The quest for the mechanisms of life.

The genomic revolution, manifested by the sequencing of the complete genome of many organisms, along with technological advances, such as DNA microarrays and developments in high-throughput analysis of proteins, metabolites, and isotopic tracer distribution patterns, challenged the conventional ways in which questions are approached in the biological sciences: (a) rather than examining a small number of genes and/or reactions at any one time;, we can now analyze gene expression and protein activity in the context of systems of interacting genes and gene products; (b) comprehensive analysis of biological systems requires the integration of all cellular fingerprints: genome sequence, maps of gene expression, protein expression, metabolic output, and in vivo enzymatic activity; and (c) collecting, managing, and analyzing comparable data from various cellular profiles requires expertise from several fields that transcend traditional discipline boundaries. While researchers in systems biology have still to address difficult challenges in both experimental and computational arenas, they possess, for the first time, the opportunity to unravel the mechanisms of life. The enormous impact of these discoveries in diverse areas, such as metabolic engineering, strain selection, drug screening and development, bioprocess development, disease prognosis and diagnosis, gene and other medical therapies, is an obvious motivation for pursuing integrated analyses of cellular systems.

Cell Physiological Phenomena↗
PubMed2005

Expression profiling in the aging brain: a perspective.

To evaluate molecular events associated with the aging process in animal models and human tissues, microarray analysis is performed at the regional and cellular levels to define transcriptional patterns or mosaics that may lead to better understanding of the mechanism(s) that drive senescence. In this review, we outline the experimental and analytical issues associated with high-throughput genomic analyses in aging brain and other tissues for a comprehensive evaluation of the current state of microarray analysis in aging paradigms. Ultimately, the goal of these studies is to apply functional genomics and proteomics approaches to aging research to develop new tools to assess age in cell- and tissue-specific manners in order to develop aging biomarkers for pharmacotherapeutic interventions and disease prevention.

Adult↗
PubMed2006

Proteomic methods in nutrition.

PURPOSE OF REVIEW: Proteomics, the comprehensive analysis of a protein complement in a cell, tissue or biological fluid at a given time, is a key player in the family of -omic disciplines, which encompass genomics (gene analysis), transcriptomics (gene expression analysis) and metabolomics (metabolite profiling). This review summarizes the state of the art of proteomics technology and puts it into perspective for food-related research. Learning from proteomic experiences in the pharmaceutical context, this article may help to translate proteomics into nutrition and health. RECENT FINDINGS: Mass spectrometric technology has progressed enormously with regard to mass accuracy, resolution and peptide sequencing power. Likewise, upstream separation, depletion and enrichment techniques now allow us to deal with the large complexity and wide dynamic range of proteomic samples more efficiently. Consequently, proteomic studies now provide a broader, but still far from complete, coverage of a given proteome. SUMMARY: Proteomics adapted and applied to the context of nutrition and health has the potential to deliver biomarkers for health and comfort, reveal early indicators of disease disposition, assist in differentiating dietary responders from non-responders, and, last but not least, discover bioactive, beneficial food components.

Biomarkers↗
PubMed2002

Shotgun proteomics: tools for the analysis of complex biological systems.

Recent interest in proteomics has been fueled by the completion of multiple genome projects and ignited by the common need of biologists to rapidly and comprehensively evaluate complex samples of proteins on a global level. 'Shotgun proteomics' refers to the direct analysis of complex protein mixtures to rapidly generate a global profile of the protein complement within the mixture. This approach has been facilitated by the use of multidimensional protein identification technology (MudPIT), which incorporates multidimensional high-pressure liquid chromatography (LC/LC), tandem mass spectrometry (MS/MS) and database-searching algorithms. This review will focus on the most recent advances in methodologies for shotgun proteomics and address the limitations of the application of each to real biological samples.

Algorithms↗
PubMed2004

DNA array-based gene profiling in tumor immunology.

Recent advances in tumor immunology have fostered the clinical implementation of different immunotherapy modalities. However, the alternate success of such regimens underscores the fact that the molecular mechanisms underlying tumor immune rejection are still poorly understood. Given the complexity of the immune system network and the multidimensionality of tumor-host interactions, the comprehension of tumor immunology might greatly benefit from high-throughput DNA array analysis, which can portray the molecular kinetics of immune response on a genome-wide scale, thus accelerating the accumulation of knowledge and ultimately catalyzing the development of new hypotheses in cell biology. Although in its infancy, the implementation of DNA array technology in tumor immunology studies has already provided investigators with novel data and intriguing hypotheses on the cascade of molecular events leading to an effective immune response against cancer. Although the principles of DNA array-based gene profiling techniques have become common knowledge, the need for mastering this technique to produce meaningful data and correctly interpret this enormous output of information is critical and represents a tremendous challenge for investigators. In the present work, we summarize the main technical features and critical issues characterizing this powerful laboratory tool and review its applications in the fascinating field of cancer immunogenomics.

Base Sequence↗
PubMed2004

Automated array-based genomic profiling in chronic lymphocytic leukemia: development of a clinical tool and discovery of recurrent genomic alterations.

B cell chronic lymphocytic leukemia (B-CLL) is characterized by a highly variable clinical course. Recurrent chromosomal imbalances provide significant prognostic markers. Risk-adapted therapy based on genomic alterations has become an option that is currently being tested in clinical trials. To supply a robust tool for such large scale studies, we developed a comprehensive DNA microarray dedicated to the automated analysis of recurrent genomic imbalances in B-CLL by array-based comparative genomic hybridization (matrix-CGH). Validation of this chip in a series of 106 B-CLL cases revealed a high specificity and sensitivity that fulfils the criteria for application in clinical oncology. This chip is immediately applicable within clinical B-CLL treatment trials that evaluate whether B-CLL cases with distinct chromosomal abnormalities should be treated with chemotherapy of different intensities and/or stem cell transplantation. Through the control set of DNA fragments equally distributed over the genome, recurrent genomic imbalances were discovered: trisomy of chromosome 19 and gain of the MYCN oncogene correlating with an elevation of MYCN mRNA expression.

Automation↗
PubMed2025

Integrating multi-omics approaches in acute myeloid leukemia (AML): Advancements and clinical implications.

Acute myeloid leukemia (AML) is a highly heterogeneous and aggressive hematologic malignancy characterized by clonal proliferation of myeloid precursors. Despite significant advancements in genomic profiling and targeted therapies, patient outcomes remain suboptimal due to disease complexity, resistance mechanisms, and high relapse rates. The integration of multi-omics approaches-spanning genomics, epigenomics, transcriptomics, proteomics, and metabolomics-has revolutionized AML research, offering a comprehensive understanding of leukemogenesis, tumor heterogeneity, and therapeutic vulnerabilities. Recent studies leveraging high-throughput sequencing, mass spectrometry, and advanced computational tools have uncovered novel biomarkers, clonal evolution dynamics, and microenvironmental interactions that drive AML progression and resistance. For instance, single-cell multi-omics has revealed chemotherapy-resistant leukemic stem cell populations, while proteogenomic analyses have identified actionable targets such as MCL1 and metabolic dependencies like OXPHOS. Clinically, integrated omics platforms are refining risk stratification, minimal residual disease (MRD) monitoring, and personalized therapy selection. However, challenges such as data integration complexity, cost barriers, and ethical considerations remain. This review highlights the transformative potential of multi-omics in AML, emphasizing recent advancements in technology, biomarker discovery, and therapeutic innovation. By bridging the gap between molecular insights and clinical practice, multi-omics integration promises to redefine AML management, paving the way for precision oncology and improved patient outcomes.

Humans↗
PubMed2025

A pluripotent stem cell atlas of multilineage differentiation.

Human pluripotent stem cells offer a scalable platform to study genetic and signalling mechanisms governing cell lineage decisions during differentiation. Genome-wide and single-cell transcriptomics technologies likewise offer high-throughput analysis of heterogeneous cell differentiation states. While in vivo development has been extensively characterised using these technologies, there remains a need for comprehensive single-cell transcriptomic profiling of stem cell differentiation from pluripotency. Understanding gene expression changes governing differentiation in vitro is key to developing high fidelity differentiation protocols and understanding fundamental mechanisms of development. We generated a single-cell RNA sequencing time course to study the role of developmental signalling pathways on multilineage diversification from pluripotency in vitro. The combined dataset of over 60,000 cells spans cell types from a time course of differentiation across all germ layers, ranging from gastrulation cell states to progenitor and committed cell types. These data provide a diverse benchmarking reference point to compare against in vivo development and advance understanding of signalling regulation of differentiation, providing insights into protocol development, drug screening, and regenerative medicine applications.

Pluripotent Stem Cells↗
PubMed2005

The MMA1 gene family of cancer-testis antigens has multiple alternative splice variants: characterization of their expression profile, the genomic organization, and transcript properties.

Previously, we reported the identification of MMA1A by screening for differential gene expression in two human melanoma cell lines displaying diverse metastatic behavior after subcutaneous inoculation into nude mice. Splice variant MMA1B, which also was identified through database homology searches, showed a high degree of similarity with the MMA1A for exons 1, 2, and 4, but was missing exon 3. Through extensive expression profiling among normal and tumor samples, both MMA1A and -1B were found to belong to the family of cancer-testis antigens. In this study, we identified four additional alternatively spliced MMA1 variants, named MMA1C, MMA1D, MMA1E, and MMA1F. Generally, these novel MMA1 transcripts differ from MMA1A in that exon 2 or exon 3 is enlarged because of the use of alternative splice sites in intron 2 of the MMA1 gene. Moreover, MMA1E also lacks exon 3, as was previously seen in MMA1B. In screening for expression of the novel MMA1 transcripts in normal and tumor tissues, we demonstrated that MMA1C, -1D, and -1E also are members of the cancer-testis antigen family. MMA1F was found in only one melanoma metastasis sample and therefore is believed to have been expressed incidentally. Furthermore, we comprehensively elucidated the genomic structure of the MMA1 gene and the characteristic features of the alternatively spliced MMA1 transcripts.

Alternative Splicing↗
PubMed2026

Genome-wide characterization of the bZIP gene family in Rattus norvegicus and expression profiling analysis during brain development.

BACKGROUND: The brown rat (Rattus norvegicus) serves as a cornerstone model organism in biomedical research, particularly for understanding physiological homeostasis and stress responses. The basic leucine zipper (bZIP) transcription factor family is a pivotal regulatory network involved in growth, organogenesis, and neurodevelopment. Despite its importance, a systematic characterization of the bZIP gene family in rats has remained elusive. RESULTS: In this study, we performed a genome-wide identification of 61 RnbZIP genes, which were categorized into 10 distinct subfamilies based on phylogenetic relationships and chromosomal localization. Structural analysis revealed conserved motif arrangements within subfamilies, while collinearity analysis identified significant gene duplication events-predominantly tandem and segmental duplications-that have driven the evolutionary expansion of the RnbZIP family. Quantitative analysis showed that members within the same subfamily shared 45%-92% sequence similarity (calculated using the BLOSUM62 scoring matrix), and all duplicated gene pairs underwent strong purifying selection (Ka/Ks&#x2009;<&#x2009;1). Comparative genomics across seven rodent species further underscored the evolutionary conservation and divergence of these factors. Expression profiling across diverse organs and brain developmental stages indicated that RnbZIP genes exhibit high tissue specificity. Notably, 10 candidate genes, including RnbZIP01, RnbZIP02, and RnbZIP08, demonstrated dynamic expression patterns during brain maturation, suggesting their essential roles in neurodevelopmental processes. CONCLUSIONS: Our findings provide a comprehensive structural and evolutionary framework for the RnbZIP gene family, highlighting their potential regulatory functions in rat organogenesis and brain development. This study establishes a valuable resource for further functional characterization of specific bZIP members in mammalian neurological systems.

Animals↗
PubMed2026

Single-cell multiomics reveals exosome-mediated reprogramming and clonotypic remodeling of T cells in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and immunogenic subtype lacking targeted therapies. While tumor-derived exosomes are known to modulate immune function, their direct impact on human T cell plasticity and antigen specificity remains poorly defined. Here, we conducted a comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples. Integrating single-cell RNA-seq, V(D)J sequencing, non-coding RNA profiling, bulk and single-cell cytokine analyses, we uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes. Exosome-treated T cells displayed skewing toward regulatory and dysfunctional phenotypes, including Th17-like, Treg, and PD-1&#x207a;/PD-L1&#x207a; Tfh cells. Functional profiling revealed suppression of early activation markers and cytokine responses, alongside selective preservation of cytotoxic features in &#x3b3;&#x3b4; T and NKT subsets. Transcriptomic and miRNA network analyses demonstrated widespread downregulation of immune effector genes (e.g., HBEGF and TNFSF9) mediated by exosome-delivered regulatory miRNAs (has-miR-98-5p). Notably, exosome-stimulated T cells displayed distinct clonotypic expansions, characterized by the emergence of five tumor-specific &#x3b3;&#x3b4; TCR clonotypes and 30 unique &#x3b1;&#x3b2; TCR CDR3 sequences that were absent in mock-treated controls, underscoring the role of exosomes in shaping TCR repertoire dynamics.

Humans↗
PubMed2002

Characterisation of the DNA-binding profile of barley HvCBF1 using an enzymatic method for rapid, quantitative and high-throughput analysis of the DNA-binding activity.

A rapid and quantitative DNA-binding assay was developed based on the translational fusion of a DNA-binding protein (DBP) with a Neocallimastix patriciarum beta-1,4-D-glucanase, CelD. CelD releases a fluorescent 4-methylumbelliferyl product from 4-methylumbelliferyl cellobioside. This hydrolysis activity was used to quantify the amount of DBP-CelD bound to an immobilised biotin-labelled target sequence. The DNA-binding assay can be performed in a 96-well plate format for high- throughput analysis of putative DBPs. This method was applied to analysis of the binding properties and sequence selectivity of a cold-inducible transcription factor HvCBF1 from barley containing an AP2 DNA-binding domain. A base-scanning approach using degenerate oligonucleotide probes was employed for rapid identification of the conserved core motif of the HvCBF1 binding site. Quantitative analysis of the binding site of HvCBF1 using systematic base substitution revealed that a (G/a) (C/t)CGAC sequence was sufficient to constitute a functional motif, where the lower-case letters represent less efficient bases. The method enables us to provide accurate and quantitative data on a comprehensive DNA-binding profile for a cold-inducible AP2 transcription factor as well as information on environmental parameters potentially influencing the DNA-binding activity. The accurate binding sequence data facilitate identification of candidate genes regulated by HvCBF1 from genome sequence databases.

Base Sequence↗
PubMed2025

PlantPan: A comprehensive multi-species plant pan-genome database.

The pan-genome represents the complete genomic diversity of specific species, serving as a valuable resource for studying species evolution, crop domestication, and guiding crop breeding and improvement. While there are several single-species-specific plant pan-genome databases, the availability of multi-species pan-genome databases is limited. Additionally, variations in methods and data types used for plant pan-genome analysis across different databases hinder the comparison and integration of pan-genome information from various projects at multi-species or single-species levels. To tackle this challenge, we introduce PlantPan, a comprehensive database housing the results of pan-genome analysis for 195 genomes from 11 plant species. PlantPan aims to provide extensive information, including gene-centric and sequence-centric pan-genome information, graph-based pan-genome, pan-genome openness profiles, gene functions and its variation characteristics, homologous genes, and gene clusters across different species. Statistically, PlantPan incorporates 9&#x2009;163&#x2009;011 genes, 694&#x2009;191 gene clusters, 526&#x2009;973&#x2009;370 genome variations, and 1&#x2009;616&#x2009;089 non-redundant genome variation groups at the species level, 33&#x2009;455,098 genome synteny, and 177&#x2009;827 non-redundant genome synteny groups at the species level. Regarding functional genes, PlantPan contains 5&#x2009;222&#x2009;720 genes related to transcription factors, 395&#x2009;247 literature-reported resistance genes, 455&#x2009;748 predicted microbial/disease resistance genes, and 1&#x2009;612&#x2009;112 genes related to molecular pathways. In summary, PlantPan is a vital platform for advancing the application of pan-genomes in molecular breeding for crops and evolutionary research for plants.

Genome, Plant↗
PubMedDate not supplied

Applications of microarray in reproductive medicine.

In the genomic era, cDNA microarray (DNA chip) technology has become a very important and powerful tool for high-throughput comprehensive analysis of gene expression, genotyping and re-sequencing applications in almost every field of biomedical research. Large-scale transcriptional profiling analyses using microarrays are frequently used to explore gene expression patterns in order to better understand the molecular mechanisms of physiology and pathogenesis: these are the basis for the development of new diagnostic and therapeutic strategies. Recently, this powerful technique has been used with laser capture microdissection (LCM) and linear aRNA amplification (in vitro transcription), and used in reproductive medical research. Recent studies of microarray-related techniques used to study oocyte fertilization, early embryo development, implantation and some infertility-related diseases (endometriosis and myoma) are discussed and summarized in this review.

Animals↗
PubMed2003

A systematic profile of DNA methylation in human cancer cell lines.

Human cancer cell lines are commonly used in basic cancer research to understand the behavior of primary tumors. Aberrations in the DNA methylation patterns are nowadays recognized as a hallmark of the cancer cell. However, no comprehensive study defines the DNA methylation environment present in the established cancer cell lines used in everyday laboratory-based research. To address this matter, we have analyzed 70 widely used human cancer cell lines of 12 different tumor types for CpG island promoter hypermethylation of 15 tumor suppressor genes, global 5-methylcytosine genomic content, chemical response to the demethylating agent 5-aza-2'-deoxycytidine, and their genetic haplotype for methyl-group metabolism genes. Several conclusions arise from our study: (a) a specific profile of CpG island hypermethylation exists for each tumor type, allowing its classification within hierarchical clusters according to the originating tissue; (b) cancer cell lines generally have higher levels of CpG island hypermethylation than primary tumors, because of the contribution of particular CpG islands and tumor types; and (c) there are no major differences between cell lines in their 5-methylcytosine DNA content, efficacy of 5-aza-2'-deoxycytidine treatment, and distribution of allelotypes of methyl-group metabolism genes. Our data provide a basis for a better use of human cancer cell lines in basic and translational research with respect to their DNA methylation environment.

5-Methylcytosine↗
PubMed2025

Genomic and Transcriptomic Landscape of Epstein-Barr Virus-Positive Inflammatory Follicular Dendritic Cell Sarcoma: A Multicenter Study.

Epstein-Barr virus (EBV)-positive inflammatory follicular dendritic cell sarcoma (EBV+ IFDCS) is a rare indolent malignant neoplasm, which occurs almost exclusively in the liver or spleen and may arise from a common EBV-infected mesenchymal cell that differentiates along the follicular or fibroblastic dendritic cell pathway. Despite its rarity, it presents a pressing need for an improved understanding of its genetic underpinnings and potential treatment strategies for recurrent or disseminated cases. To address this, we conducted comprehensive whole-exome sequencing and transcriptome sequencing (mRNA-seq) analyses on 31 and 6 cases of EBV+ IFDCS, respectively, collected from multiple centers in China. We also compared the genetic features of EBV+ IFDCS with those of other EBV-associated malignancies. Our analyses revealed a relatively high somatic mutation rate and widespread copy number variations affecting the major histocompatibility complex-I/II in EBV+ IFDCS. Integrated mutational profiling identified key signaling pathways involved in epigenetic regulation, NF-&#x3ba;B signaling, RTK/RAS/PI(3)K, and the Hippo pathway. Furthermore, we identified several frequently altered genes that could serve as potential therapeutic targets in EBV+ IFDCS. Transcriptomic analysis unveiled significant upregulation of pathways related to virus infection, immune responses, and multiple immune checkpoint genes in EBV+ IFDCS. Comparative analysis demonstrated clear genetic distinctions between EBV+ IFDCS and other EBV-associated tumors. In conclusion, our study provides comprehensive insights into the unique genomic and transcriptomic landscape of EBV+ IFDCS. We have identified multiple genetic alterations that likely contribute to the development and progression of this malignancy. Our results suggest that targeted therapy and immune checkpoint inhibitors may hold promise as potential therapeutic approaches for patients with recurrent or disseminated EBV+ IFDCS.

Humans↗