Papers by THEODOSIA CHARITOU
IEEE access, 2024
Regulatory compliance in the pharmaceutical industry is challenging, requiring dedicated resource... more Regulatory compliance in the pharmaceutical industry is challenging, requiring dedicated resources and meticulous control over production processes to ensure adherence to established regulatory guidelines, specifically ALCOA+ (Attributable, Legible, Contemporaneous, Original, Accurate, Complete, Consistent, Enduring, and Available) principles. This paper introduces an innovative approach to assess pharma regulatory compliance, utilizing a network model of the production process. The model dynamically configures production line characteristics based on manufacturing process data, overcoming complexity and scalability challenges. Purpose: The main purpose is to address the challenges of regulatory compliance in the pharmaceutical industry by introducing a novel approach using a network model. The research question involves assessing the effectiveness of this model in ensuring compliance with ALCOA+ principles. Methods: The approach involves dynamic configuration of the network model parameters based on manufacturing process data. Network analysis methods are then applied to evaluate the conformity of manufacturing process data to ALCOA+ principles. Results: Testing the proposed approach on a real dataset from a representative pharma production line demonstrates its effectiveness in assessing pharma regulatory compliance. The results highlight the potential of network modelling in managing data quality and integrity within the regulatory framework. Conclusions: The study concludes that the network model offers a strategic solution for evaluating and ensuring regulatory compliance in pharmaceutical manufacturing. The approach shows promise in addressing the complexities of data management within the stringent regulatory framework of the industry.
Agnodice: indexing experimentally supported bacterial sRNA-RNA interactions
MBio, Mar 13, 2024
Nature Communications, Jan 24, 2020
Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how o... more Protein-protein-interaction networks (PPINs) organize fundamental biological processes, but how oncogenic mutations impact these interactions and their functions at a network-level scale is poorly understood. Here, we analyze how a common oncogenic KRAS mutation (KRAS G13D) affects PPIN structure and function of the Epidermal Growth Factor Receptor (EGFR) network in colorectal cancer (CRC) cells. Mapping >6000 PPIs shows that this network is extensively rewired in cells expressing transforming levels of KRAS G13D (mtKRAS). The factors driving PPIN rewiring are multifactorial including changes in protein expression and phosphorylation. Mathematical modelling also suggests that the binding dynamics of low and high affinity KRAS interactors contribute to rewiring. PPIN rewiring substantially alters the composition of protein complexes, signal flow, transcriptional regulation, and cellular phenotype. These changes are validated by targeted and global experimental analysis. Importantly, genetic alterations in the most extensively rewired PPIN nodes occur frequently in CRC and are prognostic of poor patient outcomes.
Predictive maintenance in pharmaceutical manufacturing lines using deep transformers
Procedia Computer Science, 2023
British Journal of Cancer, May 28, 2019
BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, le... more BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, leading to resistance to EGFRtargeted therapies. METHODS: To better understand the cellular reprogramming which occurs in mutant KRAS cells, we have undertaken a systemslevel analysis of four CRC cell lines which express either wild type (wt) KRAS or the oncogenic KRAS G13D allele (mtKRAS). RESULTS: RNAseq revealed that genes involved in ribosome biogenesis, mRNA translation and metabolism were significantly upregulated in mtKRAS cells. Consistent with the transcriptional data, protein synthesis and cell proliferation were significantly higher in the mtKRAS cells. Targeted metabolomics analysis also confirmed the metabolic reprogramming in mtKRAS cells. Interestingly, mtKRAS cells were highly transcriptionally responsive to EGFR activation by TGFα stimulation, which was associated with an unexpected downregulation of genes involved in a range of anabolic processes. While TGFα treatment strongly activated protein synthesis in wtKRAS cells, protein synthesis was not activated above basal levels in the TGFα-treated mtKRAS cells. This was likely due to the defective activation of the mTORC1 and other pathways by TGFα in mtKRAS cells, which was associated with impaired activation of PKB signalling and a transient induction of AMPK signalling. CONCLUSIONS: We have found that mtKRAS cells are substantially rewired at the transcriptional, translational and metabolic levels and that this rewiring may reveal new vulnerabilities in oncogenic KRAS CRC cells that could be exploited in future.
Translational Vision Science & Technology, Jul 14, 2017
Purpose: Success of Ebola virus (EBOV) as a human pathogen relates at the molecular level primari... more Purpose: Success of Ebola virus (EBOV) as a human pathogen relates at the molecular level primarily to blockade the host cell type I interferon (IFN) antiviral response. Most individuals who survive Ebola virus disease (EVD) develop a chronic disease syndrome: approximately one-quarter of survivors suffer from uveitis, which has been associated with presence of EBOV within the eye. Clinical observations of post-Ebola uveitis indicate involvement of retinal pigment epithelial cells. Methods: We inoculated ARPE-19 human retinal pigment epithelial cells with EBOV, and followed course of infection by immunocytochemistry and measurement of titer in culture supernatant. To interrogate transcriptional responses of infected cells, we combined RNA sequencing with in silico pathway, gene ontology, transcription factor binding site, and network analyses. We measured infection-induced changes of selected transcripts by reverse transcription-quantitative polymerase chain reaction. Results: Human retinal pigment epithelial cells were permissive to infection with EBOV, and supported viral replication and release of virus in high titer. Unexpectedly, 28% of 560 upregulated transcripts in EBOV-infected cells were type I IFN responsive, indicating a robust type I IFN response. Following EBOV infection, cells continued to express multiple immunomodulatory molecules linked to ocular immune privilege. Conclusions: Human retinal pigment epithelial cells may serve as an intraocular reservoir for EBOV, and the molecular response of infected cells may contribute to the persistence of live EBOV within the human eye. Translational Relevance: This bedside-to-bench research links ophthalmic findings in survivors of EVD who suffer from uveitis with interactions between retinal pigment epithelial cells and EBOV. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Genetics Selection Evolution, Mar 31, 2016
Network biology is a rapidly developing area of biomedical research and reflects the current view... more Network biology is a rapidly developing area of biomedical research and reflects the current view that complex phenotypes, such as disease susceptibility, are not the result of single gene mutations that act in isolation but are rather due to the perturbation of a gene's network context. Understanding the topology of these molecular interaction networks and identifying the molecules that play central roles in their structure and regulation is a key to understanding complex systems. The falling cost of next-generation sequencing is now enabling researchers to routinely catalogue the molecular components of these networks at a genome-wide scale and over a large number of different conditions. In this review, we describe how to use publicly available bioinformatics tools to integrate genome-wide 'omics' data into a network of experimentally-supported molecular interactions. In addition, we describe how to visualize and analyze these networks to identify topological features of likely functional relevance, including network hubs, bottlenecks and modules. We show that network biology provides a powerful conceptual approach to integrate and find patterns in genome-wide genomic data but we also discuss the limitations and caveats of these methods, of which researchers adopting these methods must remain aware.
Pharmacogenomics Journal, Sep 28, 2022
Available drugs have been used as an urgent attempt through clinical trials to minimize severe ca... more Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the genedisease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.
Biology, Jun 10, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Predictive maintenance in pharmaceutical manufacturing lines using deep transformers
Procedia Computer Science, 2023
The Pharmacogenomics Journal
Available drugs have been used as an urgent attempt through clinical trials to minimize severe ca... more Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the genedisease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.
Biology
MAGE (Meta-Analysis of Gene Expression) is a Python open-source software package designed to perf... more MAGE (Meta-Analysis of Gene Expression) is a Python open-source software package designed to perform meta-analysis and functional enrichment analysis of gene expression data. We incorporate standard methods for the meta-analysis of gene expression studies, bootstrap standard errors, corrections for multiple testing, and meta-analysis of multiple outcomes. Importantly, the MAGE toolkit includes additional features for the conversion of probes to gene identifiers, and for conducting functional enrichment analysis, with annotated results, of statistically significant enriched terms in several formats. Along with the tool itself, a web-based infrastructure was also developed to support the features of this package.
This a preprint and has not been peer reviewed. Data may be preliminary.
Genetics Selection Evolution, 2016
Network biology is a rapidly developing area of biomedical research and reflects the current view... more Network biology is a rapidly developing area of biomedical research and reflects the current view that complex phenotypes, such as disease susceptibility, are not the result of single gene mutations that act in isolation but are rather due to the perturbation of a gene's network context. Understanding the topology of these molecular interaction networks and identifying the molecules that play central roles in their structure and regulation is a key to understanding complex systems. The falling cost of next-generation sequencing is now enabling researchers to routinely catalogue the molecular components of these networks at a genome-wide scale and over a large number of different conditions. In this review, we describe how to use publicly available bioinformatics tools to integrate genome-wide 'omics' data into a network of experimentally-supported molecular interactions. In addition, we describe how to visualize and analyze these networks to identify topological features of likely functional relevance, including network hubs, bottlenecks and modules. We show that network biology provides a powerful conceptual approach to integrate and find patterns in genome-wide genomic data but we also discuss the limitations and caveats of these methods, of which researchers adopting these methods must remain aware.
British Journal of Cancer, 2019
BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, le... more BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, leading to resistance to EGFRtargeted therapies. METHODS: To better understand the cellular reprogramming which occurs in mutant KRAS cells, we have undertaken a systemslevel analysis of four CRC cell lines which express either wild type (wt) KRAS or the oncogenic KRAS G13D allele (mtKRAS). RESULTS: RNAseq revealed that genes involved in ribosome biogenesis, mRNA translation and metabolism were significantly upregulated in mtKRAS cells. Consistent with the transcriptional data, protein synthesis and cell proliferation were significantly higher in the mtKRAS cells. Targeted metabolomics analysis also confirmed the metabolic reprogramming in mtKRAS cells. Interestingly, mtKRAS cells were highly transcriptionally responsive to EGFR activation by TGFα stimulation, which was associated with an unexpected downregulation of genes involved in a range of anabolic processes. While TGFα treatment strongly activated protein synthesis in wtKRAS cells, protein synthesis was not activated above basal levels in the TGFα-treated mtKRAS cells. This was likely due to the defective activation of the mTORC1 and other pathways by TGFα in mtKRAS cells, which was associated with impaired activation of PKB signalling and a transient induction of AMPK signalling. CONCLUSIONS: We have found that mtKRAS cells are substantially rewired at the transcriptional, translational and metabolic levels and that this rewiring may reveal new vulnerabilities in oncogenic KRAS CRC cells that could be exploited in future.
MOESM1 of Using biological networks to integrate, visualize and analyze genomics data
Additional file 1: Table S1. Case study gene expression data. Description: 514 genes from Lawless... more Additional file 1: Table S1. Case study gene expression data. Description: 514 genes from Lawless et al. [30] that were found to be significantly up-regulated more than threefold in monocytes isolated from milk at either 36 or 48Â h post-infection (hpi) with the pathogen Streptococcus uberis that causes mastitis in cattle.
Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D
Nature Communications
Retinal Pigment Epithelial Cells are a Potential Reservoir for Ebola Virus in the Human Eye
Translational vision science & technology, 2017
Success of Ebola virus (EBOV) as a human pathogen relates at the molecular level primarily to blo... more Success of Ebola virus (EBOV) as a human pathogen relates at the molecular level primarily to blockade the host cell type I interferon (IFN) antiviral response. Most individuals who survive Ebola virus disease (EVD) develop a chronic disease syndrome: approximately one-quarter of survivors suffer from uveitis, which has been associated with presence of EBOV within the eye. Clinical observations of post-Ebola uveitis indicate involvement of retinal pigment epithelial cells. We inoculated ARPE-19 human retinal pigment epithelial cells with EBOV, and followed course of infection by immunocytochemistry and measurement of titer in culture supernatant. To interrogate transcriptional responses of infected cells, we combined RNA sequencing with in silico pathway, gene ontology, transcription factor binding site, and network analyses. We measured infection-induced changes of selected transcripts by reverse transcription-quantitative polymerase chain reaction. Human retinal pigment epithelial...
Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D
Nature Communications
British Journal of Cancer, 2019
BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, le... more BACKGROUND: Activating mutations in KRAS frequently occur in colorectal cancer (CRC) patients, leading to resistance to EGFR-targeted therapies. METHODS: To better understand the cellular reprogramming which occurs in mutant KRAS cells, we have undertaken a systems-level analysis of four CRC cell lines which express either wild type (wt) KRAS or the oncogenic KRAS G13D allele (mtKRAS). RESULTS: RNAseq revealed that genes involved in ribosome biogenesis, mRNA translation and metabolism were significantly upregulated in mtKRAS cells. Consistent with the transcriptional data, protein synthesis and cell proliferation were significantly higher in the mtKRAS cells. Targeted metabolomics analysis also confirmed the metabolic reprogramming in mtKRAS cells. Interestingly, mtKRAS cells were highly transcriptionally responsive to EGFR activation by TGFα stimulation, which was associated with an unexpected downregulation of genes involved in a range of anabolic processes. While TGFα treatment strongly activated protein synthesis in wtKRAS cells, protein synthesis was not activated above basal levels in the TGFα-treated mtKRAS cells. This was likely due to the defective activation of the mTORC1 and other pathways by TGFα in mtKRAS cells, which was associated with impaired activation of PKB signalling and a transient induction of AMPK signalling. CONCLUSIONS: We have found that mtKRAS cells are substantially rewired at the transcriptional, translational and metabolic levels and that this rewiring may reveal new vulnerabilities in oncogenic KRAS CRC cells that could be exploited in future. British Journal of Cancer https://doi.
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Papers by THEODOSIA CHARITOU