scholarly journals An atlas of the tissue and blood metagenome in cancer reveals novel links between bacteria, viruses and cancer

2019 ◽  
Author(s):  
Sven Borchmann
Keyword(s):  
Massively Parallel Sequencing ◽  
Current Knowledge ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tumor Stage ◽  
Cancer Genes ◽  
Large Patient ◽  
Or Gene ◽  
Novel Associations ◽  
Insight Into

ABSTRACTHost tissue infections by bacteria and viruses can cause cancer. Massively parallel sequencing now routinely generates datasets large enough to contain detectable traces of bacterial and viral nucleic acids of taxa that colonize the examined tissue or are integrated into the host genome. However, this hidden resource has not been comprehensively studied in large patient cohorts.In the present study, 3000 whole genome sequencing datasets are leveraged to gain insight into novel links between viruses, bacteria and cancer. The resulting map confirms known links and expands current knowledge by identifying novel associations. Moreover, the detection of certain bacteria or viruses is associated with profound differences in patient and tumor phenotypes, such as patient age, tumor stage, survival, somatic mutations in cancer genes or gene expression profiles.Overall, these results provide a detailed, unprecedented map of links between viruses, bacteria and cancer that can serve as a reference for future studies.

scholarly journals An atlas of the tissue and blood metagenome in cancer reveals novel links between bacteria, viruses and cancer

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Sven Borchmann
Keyword(s):  
Massively Parallel Sequencing ◽  
Current Knowledge ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tumor Stage ◽  
Genome Project ◽  
Host Genome ◽  
Cancer Genes ◽  
Large Patient ◽  
Or Gene

Abstract Background Host tissue infections by bacteria and viruses can cause cancer. Known viral carcinogenic mechanisms are disruption of the host genome via genomic integration and expression of oncogenic viral proteins. An important bacterial carcinogenic mechanism is chronic inflammation. Massively parallel sequencing now routinely generates datasets large enough to contain detectable traces of bacterial and viral nucleic acids of taxa that colonize the examined tissue or are integrated into the host genome. However, this hidden resource has not been comprehensively studied in large patient cohorts. Methods In the present study, 3025 whole genome sequencing datasets and, where available, corresponding RNA-seq datasets are leveraged to gain insight into novel links between viruses, bacteria, and cancer. Datasets were obtained from multiple International Cancer Genome Consortium studies, with additional controls added from the 1000 genome project. A customized pipeline based on KRAKEN was developed and validated to identify bacterial and viral sequences in the datasets. Raw results were stringently filtered to reduce false positives and remove likely contaminants. Results The resulting map confirms known links and expands current knowledge by identifying novel associations. Moreover, the detection of certain bacteria or viruses is associated with profound differences in patient and tumor phenotypes, such as patient age, tumor stage, survival, and somatic mutations in cancer genes or gene expression profiles. Conclusions Overall, these results provide a detailed, unprecedented map of links between viruses, bacteria, and cancer that can serve as a reference for future studies and further experimental validation.

Classical Cancer Biology: Misconceptions and Limitations

2017 ◽  
Author(s):  
Abicumaran Uthamacumaran
Keyword(s):  
Cancer Cells ◽  
Cancer Biology ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transformed Cells ◽  
Epigenetic Landscape ◽  
Normal Cells ◽  
Cancer Models ◽  
Stem Cell Division ◽  
Insight Into

Cancer is the co-evolution of cancer cells and their turbulent microenvironment, characterized by dynamical hyper-chaotic gene expression profiles. However, cancers should not be viewed as the result of random mutations and malfunctioning information processing systems. Rather, it is the selective advantages conferred by adaptive evolution of cellular biosystems. Although on a systemic scale, cancer is defined as a disease, on a cellular basis they outperform healthy (non-transformed cells) in terms of survival and reproductive success. Their enhanced longevity pathways, metastatic invasion, extended telomeres, dynamical morphogenesis, regenerative stem cell division and environment-specific metabolic cascades indicate they are adaptive evolutionary cell states that have surpassed the boundaries normal cells are confined to. Therefore, the paper presents a brief summary of currently existing classical cancer models in the field of mathematical biology and the misconceptions of cancer epimetabolomes to further advance cancer research beyond its current limits. Through an insight into the mathematical behaviors of cancer cells, a quantum adaptive epigenetic landscape is proposed to explain the selective evolutionary dominance of cancer cells.

scholarly journals The Diverse Roles of the Global Transcriptional Regulator PhoP in the Lifecycle of Yersinia pestis

Pathogens ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1039
Author(s):  
Hana S. Fukuto ◽  
Gloria I. Viboud ◽  
Viveka Vadyvaloo
Keyword(s):  
Yersinia Pestis ◽  
Current Knowledge ◽  
Response Regulator ◽  
Expression Profiles ◽  
Critical Role ◽  
Gene Expression Profiles ◽  
Acanthamoeba Castellanii ◽  
Wide Range

Yersinia pestis, the causative agent of plague, has a complex infectious cycle that alternates between mammalian hosts (rodents and humans) and insect vectors (fleas). Consequently, it must adapt to a wide range of host environments to achieve successful propagation. Y. pestis PhoP is a response regulator of the PhoP/PhoQ two-component signal transduction system that plays a critical role in the pathogen’s adaptation to hostile conditions. PhoP is activated in response to various host-associated stress signals detected by the sensor kinase PhoQ and mediates changes in global gene expression profiles that lead to cellular responses. Y. pestis PhoP is required for resistance to antimicrobial peptides, as well as growth under low Mg2+ and other stress conditions, and controls a number of metabolic pathways, including an alternate carbon catabolism. Loss of phoP function in Y. pestis causes severe defects in survival inside mammalian macrophages and neutrophils in vitro, and a mild attenuation in murine plague models in vivo, suggesting its role in pathogenesis. A Y. pestisphoP mutant also exhibits reduced ability to form biofilm and to block fleas in vivo, indicating that the gene is also important for establishing a transmissible infection in this vector. Additionally, phoP promotes the survival of Y. pestis inside the soil-dwelling amoeba Acanthamoeba castellanii, a potential reservoir while the pathogen is quiescent. In this review, we summarize our current knowledge on the mechanisms of PhoP-mediated gene regulation in Y. pestis and examine the significance of the roles played by the PhoP regulon at each stage of the Y. pestis life cycle.

scholarly journals Identification of Lung-Cancer-Related Genes with the Shortest Path Approach in a Protein-Protein Interaction Network

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Bi-Qing Li ◽  
Jin You ◽  
Lei Chen ◽  
Jian Zhang ◽  
Ning Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Shortest Path ◽  
Protein Interaction ◽  
Expression Profiles ◽  
Shortest Paths ◽  
Gene Expression Profiles ◽  
Cancer Genes ◽  
Ppi Network ◽  
Protein Protein Interaction

Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC). In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI) network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra’s algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutationPvalue less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.

scholarly journals Sex-Biased Expression of Pharmacogenes Across Human Tissues

Biomolecules ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1206
Author(s):  
Maria Laura Idda ◽  
Ilaria Campesi ◽  
Giovanni Fiorito ◽  
Andrea Vecchietti ◽  
Silvana Anna Maria Urru ◽  
...  
Keyword(s):  
Drug Response ◽  
Current Knowledge ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tissue Expression ◽  
Systematic Investigation ◽  
Individual Response ◽  
Human Tissues ◽  
Expression Of Genes ◽  
Human Pharmacology

Individual response to drugs is highly variable and largely influenced by genetic variants and gene-expression profiles. In addition, it has been shown that response to drugs is strongly sex-dependent, both in terms of efficacy and toxicity. To expand current knowledge on sex differences in the expression of genes relevant for drug response, we generated a catalogue of differentially expressed human transcripts encoded by 289 genes in 41 human tissues from 838 adult individuals of the Genotype-Tissue Expression project (GTEx, v8 release) and focused our analysis on relevant transcripts implicated in drug response. We detected significant sex-differentiated expression of 99 transcripts encoded by 59 genes in the tissues most relevant for human pharmacology (liver, lung, kidney, small intestine terminal ileum, skin not sun-exposed, and whole blood). Among them, as expected, we confirmed significant differences in the expression of transcripts encoded by the cytochromes in the liver, CYP2B6, CYP3A7, CYP3A5, and CYP1A1. Our systematic investigation on differences between male and female in the expression of drug response-related genes, reinforce the need to overcome the sex bias of clinical trials.

scholarly journals Single-cell intracellular epitope and transcript detection revealing signal transduction dynamics

2020 ◽  
Author(s):  
Francesca Rivello ◽  
Erik van Buijtenen ◽  
Kinga Matuła ◽  
Jessie A.G.L. van Buggenum ◽  
Paul Vink ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Single Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Receptor ◽  
B Cell Receptor ◽  
Protein Levels ◽  
Inhibitory Drug ◽  
Insight Into ◽  
Transcript Detection

AbstractCurrent high-throughput single-cell multi-omics methods cannot concurrently map changes in (phospho)protein levels and the associated gene expression profiles. We present QuRIE-seq (Quantification of RNA and Intracellular Epitopes by sequencing) and use multi-factor omics analysis (MOFA+) to map signal transduction over multiple timescales. We demonstrate that QuRIE-seq can trace the activation of the B-cell receptor pathway at the minute and hour time-scale and provide insight into the mechanism of action of an inhibitory drug, Ibrutinib.

scholarly journals Discovering novel driver mutations from pan-cancer analysis of mutational and gene expression profiles

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242780
Author(s):  
Houriiyah Tegally ◽  
Kevin H. Kensler ◽  
Zahra Mungloo-Dilmohamud ◽  
Anisah W. Ghoorah ◽  
Timothy R. Rebbeck ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Cancer Genomics ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Driver Mutations ◽  
Literature Mining ◽  
Cancer Genes ◽  
Multiple Cancer ◽  
Driver Genes

As the genomic profile across cancers varies from person to person, patient prognosis and treatment may differ based on the mutational signature of each tumour. Thus, it is critical to understand genomic drivers of cancer and identify potential mutational commonalities across tumors originating at diverse anatomical sites. Large-scale cancer genomics initiatives, such as TCGA, ICGC and GENIE have enabled the analysis of thousands of tumour genomes. Our goal was to identify new cancer-causing mutations that may be common across tumour sites using mutational and gene expression profiles. Genomic and transcriptomic data from breast, ovarian, and prostate cancers were aggregated and analysed using differential gene expression methods to identify the effect of specific mutations on the expression of multiple genes. Mutated genes associated with the most differentially expressed genes were considered to be novel candidates for driver mutations, and were validated through literature mining, pathway analysis and clinical data investigation. Our driver selection method successfully identified 116 probable novel cancer-causing genes, with 4 discovered in patients having no alterations in any known driver genes: MXRA5, OBSCN, RYR1, and TG. The candidate genes previously not officially classified as cancer-causing showed enrichment in cancer pathways and in cancer diseases. They also matched expectations pertaining to properties of cancer genes, for instance, showing larger gene and protein lengths, and having mutation patterns suggesting oncogenic or tumor suppressor properties. Our approach allows for the identification of novel putative driver genes that are common across cancer sites using an unbiased approach without any a priori knowledge on pathways or gene interactions and is therefore an agnostic approach to the identification of putative common driver genes acting at multiple cancer sites.

scholarly journals RNA-Seq analysis of genes affected by Cyclophilin A/DIAGEOTROPICA (DGT) in tomato root development

2020 ◽  
Author(s):  
Maria G. Ivanchenko ◽  
Olivia R. Ozguc ◽  
Stephanie R. Bollmann ◽  
Valerie N. Fraser ◽  
Molly Megraw
Keyword(s):  
Developmental Stages ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cyclophilin A ◽  
Developmental Pathways ◽  
Root Tip ◽  
Rna Seq ◽  
Tomato Root ◽  
Initial Comparison ◽  
Insight Into

AbstractCyclophilin A/DIAGEOTROPICA (DGT) has been linked to auxin-regulated development in tomato and appears to affect multiple developmental pathways. Loss of DGT function results in a pleiotropic phenotype that is strongest in the roots, including shortened roots with no lateral branching. Here, we present an RNA-Seq dataset comparing the gene expression profiles of wildtype (‘Ailsa Craig’) and dgt tissues from three spatially separated developmental stages of the tomato root tip, with three replicates for each tissue and genotype. We also identify differentially expressed genes, provide an initial comparison of genes affected in each genotype and tissue, and provide the pipeline used to analyze the data. Further analysis of this dataset can be used to gain insight into the effects of DGT on various root developmental pathways in tomato.

scholarly journals Novel Insight Into Glycosaminoglycan Biosynthesis Based on Gene Expression Profiles

2021 ◽  
Vol 9 ◽  
Author(s):  
Yi-Fan Huang ◽  
Shuji Mizumoto ◽  
Morihisa Fujita
Keyword(s):  
Gene Expression ◽  
Chondroitin Sulfate ◽  
Dermatan Sulfate ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Sulfate Proteoglycan ◽  
Expression Levels ◽  
Core Proteins ◽  
Dermatan Sulfate Proteoglycan ◽  
Insight Into

Glycosaminoglycans (GAGs) including chondroitin sulfate, dermatan sulfate, heparan sulfate, and keratan sulfate, except for hyaluronan that is a free polysaccharide, are covalently attached to core proteins to form proteoglycans. More than 50 gene products are involved in the biosynthesis of GAGs. We recently developed a comprehensive glycosylation mapping tool, GlycoMaple, for visualization and estimation of glycan structures based on gene expression profiles. Using this tool, the expression levels of GAG biosynthetic genes were analyzed in various human tissues as well as tumor tissues. In brain and pancreatic tumors, the pathways for biosynthesis of chondroitin and dermatan sulfate were predicted to be upregulated. In breast cancerous tissues, the pathways for biosynthesis of chondroitin and dermatan sulfate were predicted to be up- and down-regulated, respectively, which are consistent with biochemical findings published in the literature. In addition, the expression levels of the chondroitin sulfate-proteoglycan versican and the dermatan sulfate-proteoglycan decorin were up- and down-regulated, respectively. These findings may provide new insight into GAG profiles in various human diseases including cancerous tumors as well as neurodegenerative disease using GlycoMaple analysis.

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