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PubMed2006

Molecular dynamics of the Shewanella oneidensis response to chromate stress.

Temporal genomic profiling and whole-cell proteomic analyses were performed to characterize the dynamic molecular response of the metal-reducing bacterium Shewanella oneidensis MR-1 to an acute chromate shock. The complex dynamics of cellular processes demand the integration of methodologies that describe biological systems at the levels of regulation, gene and protein expression, and metabolite production. Genomic microarray analysis of the transcriptome dynamics of midexponential phase cells subjected to 1 mm potassium chromate (K(2)CrO(4)) at exposure time intervals of 5, 30, 60, and 90 min revealed 910 genes that were differentially expressed at one or more time points. Strongly induced genes included those encoding components of a TonB1 iron transport system (tonB1-exbB1-exbD1), hemin ATP-binding cassette transporters (hmuTUV), TonB-dependent receptors as well as sulfate transporters (cysP, cysW-2, and cysA-2), and enzymes involved in assimilative sulfur metabolism (cysC, cysN, cysD, cysH, cysI, and cysJ). Transcript levels for genes with annotated functions in DNA repair (lexA, recX, recA, recN, dinP, and umuD), cellular detoxification (so1756, so3585, and so3586), and two-component signal transduction systems (so2426) were also significantly up-regulated (p < 0.05) in Cr(VI)-exposed cells relative to untreated cells. By contrast, genes with functions linked to energy metabolism, particularly electron transport (e.g. so0902-03-04, mtrA, omcA, and omcB), showed dramatic temporal alterations in expression with the majority exhibiting repression. Differential proteomics based on multidimensional HPLC-MS/MS was used to complement the transcriptome data, resulting in comparable induction and repression patterns for a subset of corresponding proteins. In total, expression of 2,370 proteins were confidently verified with 624 (26%) of these annotated as hypothetical or conserved hypothetical proteins. The initial response of S. oneidensis to chromate shock appears to require a combination of different regulatory networks that involve genes with annotated functions in oxidative stress protection, detoxification, protein stress protection, iron and sulfur acquisition, and SOS-controlled DNA repair mechanisms.

Anion Transport Proteins↗

PubMed2026

PSIP1::TBL1X: a recurrent gene fusion in pancreatic neuroendocrine tumors.

Effective treatment of metastatic neuroendocrine tumors (NETs) is limited by a lack of targeted therapies and clinically useful predictive biomarkers. We applied complementary genomic profiling technologies, including optical genome mapping (OGM) and whole exome sequencing (WES), to 70 liver metastases of NETs from multiple anatomical primary sites to identify actionable genomic alterations. We detected recurrent fusions involving TBL1X (PSIP1::TBL1X) and BEND2 (CHD7::BEND2 and NEO1::BEND2) by OGM in pancreatic neuroendocrine tumors (pNETs). The expression of the PSIP1::TBL1X fusion was confirmed by PacBio Iso-Seq long-read transcriptome sequencing and nested rtPCR, and fusion protein expression was established by western blotting. Expression of the PSIP1::TBL1X fusion was also assayed in a separate cohort of 31 specimens from 28 pNET cases by rtPCR. Across both cohorts, PSIP1::TBL1X was identified in 11% of pNET patients with available metastatic tissue, but was not detected in primary tumor specimens. All PSIP1::TBL1X fusion isoforms were found to retain early exons of PSIP1 and the complete coding sequence of TBL1X. Consistent with prior reports, BEND2 fusions were associated with high-grade tumors and may represent a clinically useful biomarker for aggressive disease. Notably, TBL1X and BEND2 fusions did not co-occur with ATRX/DAXX mutations, defining a distinct molecular subgroup of pNETs. This study highlights the importance of structural variant profiling in molecular profiling studies and supports a revised view of the role of gene fusions in neuroendocrine malignancies.

Humans↗

PubMed2004

Modulation of gene expression by hypoxia in human umbilical cord vein endothelial cells: A transcriptomic and proteomic study.

Hypoxia is a characteristic feature of many human pathologies, including cancer. The sustained proliferation rate of tumor cells leads to alterations of the tumor microenvironment, that progressively becomes more acidic, nutrient-deprived, and hypoxic. The reduced partial pressure of oxygen triggers the onset of an adaptive response, aimed at increasing the local oxygen concentration by several complementary actions. Although directly exposed to the blood stream, endothelial cells lining the vascular lumen in tumors also can be exposed to hypoxia and therefore can contribute to the onset of the adaptive response that leads to tumor angiogenesis. Aiming at getting a detailed insight into the oxygen-dependent regulation of the transcriptional program of vascular endothelial cells and at identifying new relevant markers that may be used as targets for therapeutic intervention in tumor angiogenesis, we have performed a broad-range transcriptomic analysis, using the Affymetrix HG-U133A Gene Chips, of mRNA expression levels in human umbilical cord vein endothelial cells (HUVEC), exposed in vitro to hypoxia for different time periods. The transcriptomic analysis was complemented by a semiquantitative reverse transcriptase-polymerase chain reaction (RT-PCR) analysis of mRNA levels and alternative splicing for some selected extracellular matrix protein genes, and by a proteomic analysis, using two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and tandem mass spectrometry for protein separation and identification, of hypoxic and normoxic HUVEC whole-cell lysates and subcellular fractions. Our analysis confirmed previous findings on genes whose expression is regulated by oxygen concentration but also identified new genes (e.g., CXCR4, claudin 3, CD24, tetranectin, Del-1, procollagen lysyl hydroxylase 1 and 2) which are transcriptionally upregulated in hypoxic conditions.

Alternative Splicing↗

PubMed2005

Lessons from large-scale gene profiling of the liver in alcoholic liver disease.

This review examines the studies pertaining to large-scale gene profiling of liver cells and the whole liver as performed with the aid of macro- or microarray gene detection technology under the conditions of alcohol-induced liver injury. The review emphasizes the variability of the data as a function of strain, species, and model of alcohol-induced liver injury employed in different studies. Further, the review highlights the importance of determining if changes in transcriptome expression are parallelled by changes in proteome and metabolome of the liver. On the basis of such data, models can be constructed to unravel new mechanistic aspects of alcohol-induced liver injury and to design novel therapies for alcoholic liver disease.

Journal Article↗

PubMed2025

Maternal Immune Activation Disrupts Epigenomic and Functional Maturation of Cortical Excitatory Neurons.

Elevated levels of maternal pro-inflammatory cytokines during gestation can disrupt offspring neural development, increasing the risk of neurodevelopmental disorders. We studied the effects of Poly(I:C)-induced maternal immune activation (PIC-MIA) during mid-gestation on developing cortical excitatory neurons' DNA methylation and transcriptome. PIC-MIA disrupted the developmental regulation of synapse-related genes and of genes implicated in autism spectrum disorders. Genomic regions that gain or lose DNA methylation during normal development were altered following PIC-MIA, including neurodevelopmental transcription factor binding sites. The DNA methylation and transcriptional changes were consistent with a delay in excitatory neuron maturation. Whole-cell recordings showed that PIC-MIA preferentially altered the physiological development of layer 5 excitatory neurons. Taken together, present results suggest that alterations in the epigenome, through the disruption of circuit formation, may drive the long-term consequences of maternal infection during gestation.

DNA methylation↗

PubMed2025

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗

PubMed2004

Ecotoxicogenomics: the challenge of integrating genomics into aquatic and terrestrial ecotoxicology.

Rapid progress in the field of genomics (the study of how an individual's entire genetic make-up, the genome, translates into biological functions) is beginning to provide tools that may assist our understanding of how chemicals can impact on human and ecosystem health. In many ways, if scientific and regulatory efforts in the 20th century have sought to establish which chemicals cause damage to ecosystems, then the challenge in ecotoxicology for the 21st century is to understand the mechanisms of toxicity to different wildlife species. In the human context, 'toxicogenomics' is the study of expression of genes important in adaptive responses to toxic exposures and a reflection of the toxic processes per se. Given the parallel implications for ecological (environmental) risk assessment, we propose the term 'ecotoxicogenomics' to describe the integration of genomics (transcriptomics, proteomics and metabolomics) into ecotoxicology. Ecotoxicogenomics is defined as the study of gene and protein expression in non-target organisms that is important in responses to environmental toxicant exposures. The potential of ecotoxicogenomic tools in ecological risk assessment seems great. Many of the standardized methods used to assess potential impact of chemicals on aquatic organisms rely on measuring whole-organism responses (e.g. mortality, growth, reproduction) of generally sensitive indicator species at maintained concentrations, and deriving 'endpoints' based on these phenomena (e.g. median lethal concentrations, no observed effect concentrations, etc.). Whilst such phenomenological approaches are useful for identifying chemicals of potential concern they provide little understanding of the mechanism of chemical toxicity. Without this understanding, it will be difficult to address some of the key challenges that currently face aquatic ecotoxicology, e.g. predicting toxicant responses across the very broad diversity of the phylogenetic groups present in aquatic ecosystems; estimating how changes at one ecological level or organisation will affect other levels (e.g. predicting population-level effects); predicting the influence of time-varying exposure on toxicant responses. Ecotoxicogenomic tools may provide us with a better mechanistic understanding of aquatic ecotoxicology. For ecotoxicogenomics to fulfil its potential, collaborative efforts are necessary through the parallel use of model microorganisms (e.g. Saccharomyces cerevisiae) together with aquatic (e.g. Danio rerio, Daphnia magna, Lemna minor and Xenopus tropicalis) and terrestrial (e.g. Arabidopsis thailiana, Caenorhabdites elegans and Eisenia foetida) plants, animals and microorganisms.

Ecology↗

PubMed2026

Third-generation whole-genome sequencing reveals the role of CNTNAP2 as a tumor suppressor gene in high-risk neuroblastomas.

BACKGROUND: Neuroblastoma is a common and aggressive pediatric sympathetic nervous system tumor. Genomic structural variants (SVs) contribute substantially to neuroblastoma, yet remain under-characterized in high-risk neuroblastomas. We aimed to elucidate neuroblastoma pathogenesis using third-generation whole-genome sequence high-risk cases to identify driver aberrations and explore potential therapeutic strategies. METHODS: We analyzed third-generation whole-genome sequencing data of 20 high-risk neuroblastoma samples and combined the findings with those obtained from the analysis of clinical samples, in vitro models, and public datasets. RESULTS: The contactin-associated protein-like 2 (CNTNAP2) gene was observed to be frequently aberrated because of structural variants in high-risk neuroblastoma samples. CNTNAP2 expression was significantly correlated with favorable histology and could be used to predict prognosis using clinical samples and neuroblastoma datasets. Overexpression and knockdown experiments and transcriptomic analysis revealed that CNTNAP2 was primarily involved in neuronal differentiation and axon guidance pathways; moreover, CNTNAP2 was required for neuroblastoma differentiation and affected cancer stemness. Immunoprecipitation and mass spectrometry revealed that CNTNAP2 interacted with cytoskeletal proteins like drebrin 1 (DBN1) and myosin-heavy chain 9 (MYH9). CNTNAP2 dynamically reorganises actin and microtubules for DBN1-mediated neuronal differentiation. CNTNAP2 also reduces CTNNB1 transcription and β-catenin pathway activation by inhibiting MYH9 nuclear translocation. CNTNAP2 overexpression in neuroblastoma cell lines resulted in cell cycle arrest, decreased cell proliferation and metastasis. CONCLUSIONS: The recurrent loss of CNTNAP2 in neuroblastoma contributes to an aggressive phenotype by impairing neuronal differentiation and increasing cancer stemness. These findings may serve as a foundation for developing therapeutic strategies to overcome barriers to differentiation.

Humans↗

PubMed2006

Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: zero-inflated Poisson regression models to predict abundance of undetected proteins.

MOTIVATION: Integrated analysis of global scale transcriptomic and proteomic data can provide important insights into the metabolic mechanisms underlying complex biological systems. However, because the relationship between protein abundance and mRNA expression level is complicated by many cellular and physical processes, sophisticated statistical models need to be developed to capture their relationship. RESULTS: In this study, we describe a novel data-driven statistical model to integrate whole-genome microarray and proteomic data collected from Desulfovibrio vulgaris grown under three different conditions. Based on the Poisson distribution pattern of proteomic data and the fact that a large number of proteins were undetected (excess zeros), zero-inflated Poisson (ZIP)-based models were proposed to define the correlation pattern between mRNA and protein abundance. In addition, by assuming that there is a probability mass at zero representing unexpressed genes and expressed proteins that were undetected owing to technical limitations, a Potential ZIP model was established. Two significant improvements introduced by this approach are (1) the predicted protein abundance level values for experimentally detected proteins are corrected by considering their mRNA levels and (2) protein abundance values can be predicted for undetected proteins (in the case of this study, approximately 83% of the proteins in the D.vulgaris genome) for better biological interpretation. We demonstrated the use of these statistical models by comparatively analyzing proteomic and microarray results from D.vulgaris grown on lactate-based versus formate-based media. These models correctly predicted increased expression of Ech hydrogenase and decreased expression of Coo hydrogenase for D.vulgaris grown on formate.

Adenosine Triphosphate↗

PubMed2005

Proteomics in nutrition research: principles, technologies and applications.

The global profiling of the whole protein complement of the genome expressed in a particular cell or organ, or in plasma or serum, makes it possible to identify biomarkers that respond to alterations in diet or to treatment, and that may have predictive value for the modelling of biological processes. Proteomics has not yet been applied on a large scale in nutritional studies, yet it has advantages over transcriptome profiling techniques in that it directly assesses the entities that carry out the biological functions. The present review summarizes the different approaches in proteomics research, with special emphasis on the current technical 'workhorses': two-dimensional (2D)-PAGE with immobilized pH gradients and protein identification by MS. Using a work-flow approach, we provide information and advice on sample handling and preparation, protein solubilization and pre-fractionation, protein separation by 2D-PAGE, detection and quantification via computer-assisted analysis of gels, and protein identification and characterization techniques by means of MS. Examples from nutritional studies employing proteomics are provided to demonstrate not only the advantages but also the limitations of current proteome analysis platforms.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2025

Evolutionary engineering and molecular characterization of an antimycin A-resistant Saccharomyces cerevisiae strain: the key role of pleiotropic drug resistance (PDR1).

Antimycin A, an antifungal agent that inhibits mitochondrial respiration, provides a useful model for studying resistance mechanisms. Antifungal resistance is an escalating clinical concern with limited treatment options available. To understand the molecular mechanisms of antimycin A resistance, a genetically stable, antimycin A-resistant Saccharomyces cerevisiae strain was successfully developed for the first time through an evolutionary engineering strategy, based on long-term systematic application of gradually increasing antimycin A stress in repetitive batch cultures without prior chemical mutagenesis. Comparative whole genome resequencing analysis of the evolved strain ant905-9 revealed two missense mutations in PDR1 and PRP8 genes involved in pleiotropic drug resistance and RNA splicing, respectively. Using CRISPR/Cas9 genome editing tools, the identified mutations were introduced individually and together into the reference strain, and it was confirmed that the Pdr1p.M732R mutation alone confers antimycin A-resistance in S. cerevisiae. Comparative transcriptomic analysis of the reverse-engineered Pdr1p.M732R strain showed alterations in PDR (pleiotropic drug resistance), transmembrane transport, vesicular trafficking, and autophagy pathways. Our results highlight the potential key role of PDR1 in antifungal drug resistance. This study provides new insights into mitochondrial drug resistance and the adaptive potential of yeast under respiratory stress.

Saccharomyces cerevisiae↗

PubMed2026

Genome-Wide Identification and Expression Pattern of the ANK Gene Family in Sorghum bicolor Under Salt Stress.

The Ankyrin-repeat proteins (ANKs) play a key role in plant development and in response to abiotic stress. This research identified family members of the ANK genes in Sorghum bicolor at the whole-genome level, analyzed their sequence characteristics, evolutionary relationships, and expression patterns, and provided a scientific basis for elucidating the functionality of SbANK genes and for salt-tolerant breeding. Using bioinformatics methods, this study conducted a comprehensive identification of the SbANK gene family, analyzing its physicochemical properties, domain composition, chromosomal distribution, colinearity relationships, promoter cis-acting elements, and conserved protein motifs. Transcriptomic data and qRT-PCR were used to detect changes in their expression under salt stress. A total of 186 ANK family members were identified in the Sorghum bicolor genome, classified into 13 subfamilies and unevenly distributed across 10 chromosomes. Intra-species colinearity analysis revealed 7 pairs of duplicated genes, while inter-species colinearity analysis showed that S. bicolor and Oryza sativa share 88 pairs of orthologs, far exceeding the number found in Arabidopsis thaliana (11 pairs). Promoter analysis indicated that SbANK genes are enriched with cis-acting elements associated with hormone responses (particularly MeJA elements, accounting for 51.7%) and stress responses (particularly anaerobic-inducible elements, accounting for 60.9%). Transcriptomic expression analysis revealed that SbANK genes exhibit distinct tissue specificity, with the ANK-IQ subfamily highly expressed in leaves and the ANK-M subfamily showing the most widespread response under salt stress. Expression levels of the 10 candidate genes showing the most significant responses to salt stress were analyzed using qRT-PCR. The results indicated that SbANK91, SbANK135, and SbANK136 were significantly upregulated under 200 mmol/L NaCl treatment. The SbANK family is distinguished by a large number of member genes and structural diversity, with the ANK-M subfamily being the primary group responding to salt stress. SbANK91, SbANK135, and SbANK136 are identified as putative candidate genes for salt stress responses.

Sorghum↗

PubMed2002

Integrating cancer genomics and proteomics in the post-genome era.

The dawn of the post-genome era is leading to extraordinary opportunities in biomedicine. Our group has embarked on a major effort to integrate genomics, transcriptomics and proteomics for the profiling of tumor tissues, an approach we refer to as operomics. Our major goals are the molecular classification of tumors and the identification of markers for the early detection of cancer. Molecular analyses of tumors rely on microdissected tissues, which are simultaneously investigated for genomic, transcriptomic and proteomic changes. Genomic alterations in tumor cells being investigated include deletions, amplifications and methylation changes across the entire genome as well as point mutations in specific genes. Expression analysis at the RNA level is being undertaken using oligonucleotide and cDNA based microarrays. An important aspect of our approach is the large-scale identification and quantitative analysis of tumor proteins in whole cell lysates as well as in protein compartments. Protein separation strategies include two-dimensional polyacrylamide gel electrophoresis and liquid chromatography. Specific protein subsets, of interest include membrane proteins, secreted proteins and antigenic proteins as sources of biomarkers for early detection of cancer. Our current approach is illustrated with findings stemming from our studies of human gliomas.

Brain Neoplasms↗

PubMed2024

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Humans↗

PubMed2025

Subgenomic divergence and functional innovation following whole-genome duplication in Maleae species of Rosaceae.

Whole-genome duplication (WGD) drives plant evolution by inducing karyotype rearrangements and gene loss through subgenome fractionation. In this study, we investigate post-WGD evolutionary dynamics in Rosaceae, focusing on Maleae species, which uniquely experienced an additional WGD. Using phylogenetic and synteny analyses, we reveal that chromosomal breakpoints act as hotspots for localized fractionation, contributing to blurred homoeologous origins and influencing gene retention patterns. Here, we reconstruct karyotype evolution across Rosaceae subfamilies, highlighting chromosome reductions and lineage-specific rearrangements in Dryadoideae, Rosoideae, and Amygdaloideae. We also identify a bias for retaining transcription factors and hormone-related genes from older WGDs in subsequent polyploidy events. Transcriptome analysis classifies WGD-derived genes in Maleae species, such as apple and loquat, into three expression groups, with hormone-enriched genes playing roles in lignification and fruit-related innovations. These findings demonstrate the interplay between chromosomal breakpoints, biased retention, and functional divergence, revealing their contributions to genomic and phenotypic evolution in Maleae and their adaptive success within Rosaceae.

Genome, Plant↗

PubMed2026

Bridging Organ-on-a-Chip and Omics: A Multi-Dimensional Frontier in Biomedical Research.

Organ-on-a-Chip (OOC) technology offers a powerful platform for replicating human tissue-specific microenvironments, thereby narrowing the translational gap between conventional biomedical models and actual human physiology. Concurrently, omics technologies deliver comprehensive molecular-level insights into biological systems. This review highlights the transformative potential of integrating OOC platforms with high-throughput omics methodologies. We systematically examine the classification, structural configurations, and engineering principles underlying OOC systems, alongside the defining attributes of key omics domains-genomics, transcriptomics, proteomics, and metabolomics. The convergence of dynamic OOC models with advanced omics technologies enables high-resolution, multi-dimensional analyses across numerous biomedical applications, including drug metabolism, disease mechanisms, environmental toxicity assessments, and host-microbiome interactions. This interdisciplinary integration is driving a paradigm shift in precision and translational medicine. However, several challenges remain to be addressed, such as the development of whole-organ mimetics, adaptation of sample collection techniques, and real-time artificial intelligence-based integration of biosensor data with multi-omics datasets. Addressing these hurdles will be vital for unlocking the full potential of this technological synergy in biomedical science.

Multiomics↗

PubMed2025

Intratumoral B cell and interferon signatures in newly diagnosed glioblastoma are associated with longer survival in patients treated with SurVaxM.

Glioblastoma (GBM) has proved difficult to treat, and there is dire need for more effective therapies. In a single arm phase IIa trial (NCT02455557), treatment of newly diagnosed GBM patients with the peptide vaccine SurVaxM resulted in promising median progression-free and overall survival. To investigate molecular features that associate with GBM responsiveness to SurVaxM, retrospective whole exome and RNA sequencing was performed on patient tumors (n = 34) collected prior to standard of care treatment plus SurVaxM. Differential gene expression and mutational profiles were characterized between patients with short-term (OS < 18 months) or long-term (OS ≥ 18 months) overall survival. Greater expression of interferon, complement, and humoral immunity signatures were associated with long-term survival. Deconvolution of transcriptomes identified enrichment of intratumoral memory B cell populations in long-term survivors that were validated by CD20 staining in matched samples. A five-gene expression signature and a B cell specific signature predicted survival within the SurVaxM-treated cohort, however, these signatures were not associated with improved outcomes in a similarly treated population obtained from The Cancer Genome Atlas (TCGA) that did not receive immunotherapeutic intervention. Although prospective validation is ongoing, the findings in this discovery cohort specify molecular features of GBM associated with better overall survival and potential responsiveness to immunotherapy with SurVaxM.

Humans↗

PubMed2003

Gene expression profile of Campylobacter jejuni in response to growth temperature variation.

The foodborne pathogen Campylobacter jejuni is the primary causative agent of gastroenteritis in humans. In the present study a whole genome microarray of C. jejuni was constructed and validated. These DNA microarrays were used to measure changes in transcription levels over time, as C. jejuni cells responded to a temperature increase from 37 to 42 degrees C. Approximately 20% of the C. jejuni genes were significantly up- or downregulated over a 50-min period after the temperature increase. The global change in C. jejuni transcriptome was found to be essentially transient, with only a small subset of genes still differentially expressed after 50 min. A substantial number of genes with a downregulated coexpression pattern were found to encode for ribosomal proteins. This suggests a short growth arrest upon temperature stress, allowing the bacteria to reshuffle their energy toward survival and adaptation to the new growth temperature. Genes encoding chaperones, chaperonins, and heat shock proteins displayed the most dramatic and rapid upregulation immediately after the temperature change. Interestingly, genes encoding proteins involved in membrane structure modification were differentially expressed, either up- or downregulated, suggesting a different protein membrane makeup at the two different growth temperatures. Overall, these data provide new insights into the primary response of C. jejuni to surmount a sudden temperature upshift, allowing the bacterium to survive and adapt its transcriptome to a new steady state.

Bacterial Proteins↗