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Identification and characterization of optimal gene expression markers for detection of breast cancer metastasis.

Sentinel lymph node (SLN) status is highly predictive of overall axillary lymph node involvement in breast cancer. Historically, SLN-positive patients have undergone axillary lymph node dissection in a second surgery. Intraoperative SLN analysis could reduce the cost and complications of a second surgery; however, existing histopathological methods lack standardization and exhibit poor sensitivity. Rapid molecular methods may lead to improved intraoperative diagnosis of SLN metastasis. In this study, we used a genome-wide gene expression analysis of breast and other tissues to identify seven putative markers for detecting breast cancer metastasis. We assessed the utility of these markers for identifying clinically actionable metastases in lymph nodes through reverse transcriptase-polymerase chain reaction analysis of SLNs from 254 breast cancer patients. Polymerase chain reaction signals were compared to pathology on a per-patient basis. The optimal two-gene combination, mammaglobin and cytokeratin 19, detected clinically actionable metastasis in breast SLNs with 90% sensitivity and 94% specificity. Application of stringent criteria for identifying presumptive hematoxylin- and eosin-positive samples increased sensitivity and specificity to 91 and 97%, respectively. This study represents the first comprehensive demonstration of the utility of gene expression markers for detecting clinically actionable breast metastases. An intraoperative molecular assay using these markers has the potential to significantly reduce second surgeries for patients undergoing SLN dissection.

Biomarkers, Tumor↗

Ultra-processed Foods, Cancer, and Early-onset Cancer: A Comprehensive Review.

The classification of foods according to their degree of processing, and particularly the concept of ultra-processed foods, is relatively new. Consumption of ultra-processed foods has increased markedly worldwide in recent decades. Their growing consumption has coincided with a rising global burden of cancer, including marked increases in several cancers diagnosed before age 50 years. In this comprehensive review, we summarize trends in ultra-processed food consumption and the sociodemographic, psychological, and behavioral characteristics associated with higher intake. We further review the epidemiological evidence linking ultra-processed foods with cancer incidence and mortality, with particular attention to the limited but emerging evidence relevant to early-onset cancer. Potential mechanisms linking ultra-processed foods to cancer include unfavorable nutrient displacement, changes in body composition and fat deposition, and increased exposure to additives, processing by-products, and other chemicals. These influences may converge on a range of biological pathways, including metabolic dysfunction, chronic inflammation, immune dysregulation, gut microbiome disruption, DNA damage and genomic instability, and epigenetic alterations. Substantial uncertainties remain, including heterogeneous exposure definitions and classification practices, limitations in dietary assessment and temporal exposure capture, residual confounding, and the complexity of putative biological mechanisms. We conclude by highlighting key research challenges and future directions, along with considerations related to policy, regulation, and industry practices.

Ultra-processed foods↗

A Nuclear Receptor Atlas: macrophage activation.

Macrophage activation is an essential cellular process underlying innate immunity, enabling the body to combat bacteria and other pathogens. In addition to host defense, activated macrophages play a central role in atherogenesis, autoimmunity, and a variety of inflammatory diseases. As members of the Nuclear Receptor Signaling Atlas (NURSA) program, we employed quantitative real-time PCR (qPCR) to provide a comprehensive assessment of changes in expression of the 49 members of the murine nuclear receptor superfamily. In this study, we have identified a network of 28 nuclear receptors associated with the activation of bone marrow-derived macrophages by lipopolysaccharide or the prototypic cytokine interferon gamma. More than half of this network is deployed in three intricate and highly scripted temporal phases that are unique for each activator. Thus, early receptors whose expression peaks within 4 h after lipopolysaccharide exposure, such as glucocorticoid receptor, peroxisome proliferator-activated receptor gamma, and neuronal growth factor 1B, are found as late rising markers of the interferon gamma cascade, occurring 16 h or later. The discovery of precise serial expression patterns reveals that macrophage activation is the product of an underlying process that impacts the genome within minutes and identifies a collection of new therapeutic targets for controlling inflammation by disruption of presumptive regulatory cascades.

Animals↗

Personalized medicine strategy for MPNSTs: using precision oncology on PDOX models to inform tumor boards.

BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are a heterogeneous group of aggressive soft tissue sarcomas with poor prognosis. Currently there is a lack of effective treatments for MPNSTs. Here, we propose a personalized medicine approach that integrates a precision oncology strategy guided by MPNST genomic analysis, with a functional validation of treatment response in an orthotopic xenograft model (PDOX) derived from the same MPNST. METHODS: Comprehensive whole genome sequencing analysis was performed in primary MPNSTs, relapses and (in one case) metastases, following disease progression in two independent individuals. Matched MPNST PDOX models were generated by orthotopically implanting tumor fragments near the sciatic nerve of immunodeficient mice. Candidate targeted combination therapies were prioritized based on genomic alterations and tested in vivo in the PDOX models. RESULTS: The feasibility of the developed strategy is illustrated for two MPNST patients, one Neurofibromatosis type 1 (NF1) individual that developed two independent MPNSTs and another sporadic MPNST case with multiple metastatic relapses. Genomic analysis revealed a remarkable degree of genomic stability across primary MPNSTs and their successive relapses in each patient, and even metastases in one individual. While based on a small number of cases requiring additional analyses, this finding aligns with previous evidence suggesting a fair genomic conservation throughout tumor evolution. This stability supports the identification of consistent therapeutic vulnerabilities throughout disease progression. Among the therapies tested, co-treatment of MEK inhibitor (MEKi) plus bromodomain inhibitor (BETi) elicited the highest antitumor activity, resulting in approximately 60% tumor volume reduction in the sporadic MPNST PDX model, whose patient has been receiving this therapy for eight months with sustained remission. CONCLUSIONS: This study demonstrates the feasibility and clinical utility of integrating genomic-driven precision oncology with PDOX-based functional testing for MPNSTs. This strategy may support molecular tumor boards (MTBs) in their treatment decisions. The observed genomic stability supports the use of longitudinal tumor profiling to guide treatment, and the success of MEKi+BETi highlights its potential as a combination therapy for MPNSTs.

Precision Medicine↗

Gene finding in the chicken genome.

BACKGROUND: Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method. RESULTS: We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. CONCLUSIONS: De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.

Animals↗

Quantitative transcript imaging in normal and heat-shocked Drosophila embryos by using high-density oligonucleotide arrays.

Embryonic development in Drosophila is characterized by an early phase during which a cellular blastoderm is formed and gastrulation takes place, and by a later postgastrulation phase in which key morphogenetic processes such as segmentation and organogenesis occur. We have focused on this later phase in embryogenesis with the goal of obtaining a comprehensive analysis of the zygotic gene expression that occurs during development under normal and altered environmental conditions. For this, a functional genomic approach to embryogenesis has been developed that uses high-density oligonucleotide arrays for large-scale detection and quantification of gene expression. These oligonucleotide arrays were used for quantitative transcript imaging of embryonically expressed genes under standard conditions and in response to heat shock. In embryos raised under standard conditions, transcripts were detected for 37% of the 1,519 identified genes represented on the arrays, and highly reproducible quantification of gene expression was achieved in all cases. Analysis of differential gene expression after heat shock revealed substantial expression level changes for known heat-shock genes and identified numerous heat shock-inducible genes. These results demonstrate that high-density oligonucleotide arrays are sensitive, efficient, and quantitative instruments for the analysis of large scale gene expression in Drosophila embryos.

Animals↗

Profiling the humoral immune response to infection by using proteome microarrays: high-throughput vaccine and diagnostic antigen discovery.

Despite the increasing availability of genome sequences from many human pathogens, the production of complete proteomes remains at a bottleneck. To address this need, a high-throughput PCR recombination cloning and expression platform has been developed that allows hundreds of genes to be batch-processed by using ordinary laboratory procedures without robotics. The method relies on high-throughput amplification of each predicted ORF by using gene specific primers, followed by in vivo homologous recombination into a T7 expression vector. The proteins are expressed in an Escherichia coli-based cell-free in vitro transcription/translation system, and the crude reactions containing expressed proteins are printed directly onto nitrocellulose microarrays without purification. The protein microarrays are useful for determining the complete antigen-specific humoral immune-response profile from vaccinated or infected humans and animals. The system was verified by cloning, expressing, and printing a vaccinia virus proteome consisting of 185 individual viral proteins. The chips were used to determine Ab profiles in serum from vaccinia virus-immunized humans, primates, and mice. Human serum has high titers of anti-E. coli Abs that require blocking to unmask vaccinia-specific responses. Naive humans exhibit reactivity against a subset of 13 antigens that were not associated with vaccinia immunization. Naive mice and primates lacked this background reactivity. The specific profiles between the three species differed, although a common subset of antigens was reactive after vaccinia immunization. These results verify this platform as a rapid way to comprehensively scan humoral immunity from vaccinated or infected humans and animals.

Animals↗

Computational prediction of the effects of non-synonymous single nucleotide polymorphisms in human DNA repair genes.

Non-synonymous single nucleotide polymorphisms (nsSNPs) represent common genetic variation that alters encoded amino acids in proteins. All nsSNPs may potentially affect the structure or function of expressed proteins and could therefore have an impact on complex diseases. In an effort to evaluate the phenotypic effect of all known nsSNPs in human DNA repair genes, we have characterized each polymorphism in terms of different functional properties. The properties are computed based on amino acid characteristics (e.g. residue volume change); position-specific phylogenetic information from multiple sequence alignments and from prediction programs such as SIFT (Sorting Intolerant From Tolerant) and PolyPhen (Polymorphism Phenotyping). We provide a comprehensive, updated list of all validated nsSNPs from dbSNP (public database of human single nucleotide polymorphisms at National Center for Biotechnology Information, USA) located in human DNA repair genes. The list includes repair enzymes, genes associated with response to DNA damage as well as genes implicated with genetic instability or sensitivity to DNA damaging agents. Out of a total of 152 genes involved in DNA repair, 95 had validated nsSNPs in them. The fraction of nsSNPs that had high probability of being functionally significant was predicted to be 29.6% and 30.9%, by SIFT and PolyPhen respectively. The resulting list of annotated nsSNPs is available online (http://dna.uio.no/repairSNP), and is an ongoing project that will continue assessing the function of coding SNPs in human DNA repair genes.

Computational Biology↗

RNAi analysis of genes expressed in the ovary of Caenorhabditis elegans.

As a step towards comprehensive functional analysis of genomes, systematic gene knockout projects have been initiated in several organisms [1]. In metazoans like C. elegans, however, maternal contribution can mask the effects of gene knockouts on embryogenesis. RNA interference (RNAi) provides an alternative rapid approach to obtain loss-of-function information that can also reveal embryonic roles for the genes targeted [2,3]. We have used RNAi to analyze a random set of ovarian transcripts and have identified 81 genes with essential roles in embryogenesis. Surprisingly, none of them maps on the X chromosome. Of these 81 genes, 68 showed defects before the eight-cell stage and could be grouped into ten phenotypic classes. To archive and distribute these data we have developed a database system directly linked to the C. elegans database (Wormbase). We conclude that screening cDNA libraries by RNAi is an efficient way of obtaining in vivo function for a large group of genes. Furthermore, this approach is directly applicable to other organisms sensitive to RNAi and whose genomes have not yet been sequenced.

Animals↗

Comprehensive sampling of gene expression in human cell lines with massively parallel signature sequencing.

Whereas information is rapidly accumulating about the structure and position of genes encoded in the human genome, less is known about the complexity and relative abundance of their expression in individual human cells and tissues. Here, we describe the characteristics of the transcriptomes of two cultured cell lines, HB4a (normal breast epithelium) and HCT-116 (colon adenocarcinoma), using massively parallel signature sequencing (MPSS). We generated in excess of 10(7) short signature sequences per cell line, thus providing a comprehensive snapshot of gene expression, within the technical limitations of the method. The number of genes expressed at one copy per cell or more in either of the lines was estimated to be between 10,000 and 15,000. The vast majority of the transcripts found in these cells can be mapped to known genes and their polyadenylation variants. Among the genes that could be identified from their signature sequences, approximately 8,500 were expressed by both cell lines, whereas 6,000 showed cellular specificity. Taking into account sequence tags that map uniquely to the genome but not to known transcripts, overall the data are consistent with an upper limit of 17,000 for the total number of genes expressed at more than one copy per cell in one or both of the two cell lines examined.

Adenocarcinoma↗

Advances in proteomic technologies.

Proteomics is a rapidly emerging set of key technologies that are being used to identify proteins and map their interactions in a cellular context. With the sequencing of the human genome, the scope of proteomics has shifted from protein identification and characterization to include protein structure, function and protein-protein interactions. Technologies used in proteomic research include two-dimensional gel electrophoresis, mass spectrometry, yeast two-hybrids screens, and computational prediction programs. While some of these technologies have been in use for a long time, they are currently being applied to study physiology and cellular processes in high-throughput formats. It is the high-throughput approach that defines and characterizes modern proteomics. In this review, we discuss the current status of these experimental and computational technologies relevant to the three major aspects of proteomics-characterization of proteomes, identification of proteins, and determination of protein function. We also briefly discuss the development of new proteomic technologies that are based on recent advances in analytical and biochemical techniques, engineering, microfabrication, and computational prowess. The integration of these advances with established technologies is invaluable for the drive toward a comprehensive understanding of protein structure and function in the cellular milieu.

Electrophoresis, Gel, Two-Dimensional↗

Metabolic-state-dependent remodeling of the transcriptome in response to anoxia and subsequent reoxygenation in Saccharomyces cerevisiae.

We conducted a comprehensive genomic analysis of the temporal response of yeast to anaerobiosis (six generations) and subsequent aerobic recovery ( approximately 2 generations) to reveal metabolic-state (galactose versus glucose)-dependent differences in gene network activity and function. Analysis of variance showed that far fewer genes responded (raw P value of or=2 generations) with the activation of Upc2- and Mot3-regulated networks involved in sterol and cell wall homeostasis. The response to reoxygenation was rapid (<5 min) and similar in both media, dominated by Yap1 networks involved in oxidative stress/redox regulation and the concomitant activation of heme-regulated ones. Our analyses revealed extensive networks of genes subject to combinatorial regulation by both heme-dependent (e.g., Hap1, Hap2/3/4/5, Rox1, Mot3, and Upc2) and heme-independent (e.g., Yap1, Skn7, and Puf3) factors under these conditions. We also uncover novel functions for several cis-regulatory sites and trans-acting factors and define functional regulons involved in the physiological acclimatization to changes in oxygen availability.

Anaerobiosis↗

Genomewide gain-of-function genetic screen identifies functionally active genes in mouse embryonic stem cells.

Embryonic stem (ES) cells hold great promise for the future of medicine. To elucidate the molecular mechanisms that control ES cell self-renewal and differentiation, a comprehensive knowledge of the molecules involved in these processes is required. Here we describe an effective approach for genomewide identification of functionally active genes in ES cells. This approach combines genetic screens based on cDNA libraries with microarray detection methods to permit high-throughput functional analyses. We implement this strategy to identify genes whose overexpression can maintain phenotypic properties of undifferentiated mouse ES cells under differentiation-inducing conditions, specifically in the absence of leukemia inhibitory factor. The identified genes encode a variety of regulatory proteins whose function in ES cells was previously unknown. Moreover, our approach is capable of detecting genes whose overexpression promote differentiation or cell death. Overall, our studies establish a methodology for highly sensitive identification of genes that confer particular phenotypes on ES cells.

Animals↗

Dynamic changes of anti-oxidative enzymes of 10 wheat genotypes at soil water deficits.

Drought is a world-spread problem seriously influencing crop 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 (16,000 Mb). On the other hand, stress adaptive mechanisms are quite different, with stress degree, different growth and developmental stages, time course, materials 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, tillage and maturing). Here, we reported the dynamic anti-oxidative results of whole stage (i.e. seedling, tillage and maturing) in terms of activities of POD, SOD, CAT of 10 wheat genotypes as follows: (1) 10 wheat genotypes can be grouped into three kinds (A, B and 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, whose activities of anti-oxidative enzymes (POD, SOD, CAT) were higher; (3) B group exhibited stronger anti-drought under treatment level 2, whose activities of anti-oxidative enzymes were higher; (4) C group expressed anti-drought to some extent under treatment level 3, 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--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; (7) our research can provide insights into physiological mechanisms of crop anti-drought and direct practical materials for wheat anti-drought breeding; (8) POD, SOD and CAT activities 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 stress threshold; (9) our primary results also firstly displayed that the changing trend for wheat adapting to environmental stress during life circle was an S-shaped curve, which is, by chance, consistent with Plant Growth Grand Periodicity Curve.

Antioxidants↗

Head and neck squamous cell carcinoma transcriptome analysis by comprehensive validated differential display.

Head and neck squamous cell carcinoma (HNSCC) is common worldwide and is associated with a poor rate of survival. Identification of new markers and therapeutic targets, and understanding the complex transformation process, will require a comprehensive description of genome expression, that can only be achieved by combining different methodologies. We report here the HNSCC transcriptome that was determined by exhaustive differential display (DD) analysis coupled with validation by different methods on the same patient samples. The resulting 820 nonredundant sequences were analysed by high throughput bioinformatics analysis. Human proteins were identified for 73% (596) of the DD sequences. A large proportion (>50%) of the remaining unassigned sequences match ESTs (expressed sequence tags) from human tumours. For the functionally annotated proteins, there is significant enrichment for relevant biological processes, including cell motility, protein biosynthesis, stress and immune responses, cell death, cell cycle, cell proliferation and/or maintenance and transport. Three of the novel proteins (TMEM16A, PHLDB2 and ARHGAP21) were analysed further to show that they have the potential to be developed as therapeutic targets.

Amino Acid Sequence↗

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↗

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↗

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↗