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  1. Article: Pancreatic cancer mutationscape: revealing the link between modular restructuring and intervention efficacy amidst common mutations.

    Plaugher, Daniel / Murrugarra, David

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Across cancer types, the prognosis for pancreatic cancer (PC) is among the worst and options for treatment are limited. There is increasing evidence that biological systems, including PC, are modular in both structure and function. Complex biological ... ...

    Abstract Across cancer types, the prognosis for pancreatic cancer (PC) is among the worst and options for treatment are limited. There is increasing evidence that biological systems, including PC, are modular in both structure and function. Complex biological signaling networks such as gene regulatory networks (GRNs) are proving to be composed of subcategories that are interconnected and hierarchically ranked. These networks contain highly dynamic processes that ultimately dictate cellular function over time. In this work, we use an established Boolean multicellular signaling network of PC to show that the variance in topological rankings of the most phenotypically influential modules implies a strong relationship between structure and function. We further show that induction of mutations alters the modular structure, which analogously influences the aggression and controllability of the disease
    Language English
    Publishing date 2024-01-30
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.01.27.577546
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Phenotype control techniques for Boolean gene regulatory networks.

    Plaugher, Daniel / Murrugarra, David

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What’s more, BNs provide a course-grained approach, not only to understanding ... ...

    Abstract Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What’s more, BNs provide a course-grained approach, not only to understanding molecular communications, but also for targeting pathway components that alter the long-term outcomes of the system. This has come to be known as
    Language English
    Publishing date 2023-04-18
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.04.17.537158
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Phenotype Control techniques for Boolean gene regulatory networks.

    Plaugher, Daniel / Murrugarra, David

    Bulletin of mathematical biology

    2023  Volume 85, Issue 10, Page(s) 89

    Abstract: Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What's more, BNs provide a course-grained approach, not only to understanding ... ...

    Abstract Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What's more, BNs provide a course-grained approach, not only to understanding molecular communications, but also for targeting pathway components that alter the long-term outcomes of the system. This has come to be known as phenotype control theory. In this review we study the interplay of various approaches for controlling gene regulatory networks such as: algebraic methods, control kernel, feedback vertex set, and stable motifs. The study will also include comparative discussion between the methods, using an established cancer model of T-Cell Large Granular Lymphocyte Leukemia. Further, we explore possible options for making the control search more efficient using reduction and modularity. Finally, we will include challenges presented such as the complexity and the availability of software for implementing each of these control techniques.
    MeSH term(s) Gene Regulatory Networks ; Mathematical Concepts ; Models, Biological ; Phenotype ; Software
    Language English
    Publishing date 2023-08-30
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ZDB-ID 184905-0
    ISSN 1522-9602 ; 0007-4985 ; 0092-8240
    ISSN (online) 1522-9602
    ISSN 0007-4985 ; 0092-8240
    DOI 10.1007/s11538-023-01197-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.B 754: Show issues Location:
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  4. Article ; Online: Modeling the Pancreatic Cancer Microenvironment in Search of Control Targets.

    Plaugher, Daniel / Murrugarra, David

    Bulletin of mathematical biology

    2021  Volume 83, Issue 11, Page(s) 115

    Abstract: Pancreatic ductal adenocarcinoma is among the leading causes of cancer-related deaths globally due to its extreme difficulty to detect and treat. Recently, research focus has shifted to analyzing the microenvironment of pancreatic cancer to better ... ...

    Abstract Pancreatic ductal adenocarcinoma is among the leading causes of cancer-related deaths globally due to its extreme difficulty to detect and treat. Recently, research focus has shifted to analyzing the microenvironment of pancreatic cancer to better understand its key molecular mechanisms. This microenvironment can be represented with a multi-scale model consisting of pancreatic cancer cells (PCCs) and pancreatic stellate cells (PSCs), as well as cytokines and growth factors which are responsible for intercellular communication between the PCCs and PSCs. We have built a stochastic Boolean network (BN) model, validated by literature and clinical data, in which we probed for intervention strategies that force this gene regulatory network (GRN) from a diseased state to a healthy state. To do so, we implemented methods from phenotype control theory to determine a procedure for regulating specific genes within the microenvironment. We identified target genes and molecules, such that the application of their control drives the GRN to the desired state by suppression (or expression) and disruption of specific signaling pathways that may eventually lead to the eradication of the cancer cells. After applying well-studied control methods such as stable motifs, feedback vertex sets, and computational algebra, we discovered that each produces a different set of control targets that are not necessarily minimal nor unique. Yet, we were able to gain more insight about the performance of each process and the overlap of targets discovered. Nearly every control set contains cytokines, KRas, and HER2/neu, which suggests they are key players in the system's dynamics. To that end, this model can be used to produce further insight into the complex biological system of pancreatic cancer with hopes of finding new potential targets.
    MeSH term(s) Carcinoma, Pancreatic Ductal/genetics ; Gene Expression Regulation, Neoplastic ; Humans ; Mathematical Concepts ; Pancreatic Neoplasms/genetics ; Tumor Microenvironment
    Language English
    Publishing date 2021-10-11
    Publishing country United States
    Document type Journal Article
    ZDB-ID 184905-0
    ISSN 1522-9602 ; 0007-4985 ; 0092-8240
    ISSN (online) 1522-9602
    ISSN 0007-4985 ; 0092-8240
    DOI 10.1007/s11538-021-00937-w
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 754: Show issues Location:
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  5. Article ; Online: Uncovering potential interventions for pancreatic cancer patients via mathematical modeling.

    Plaugher, Daniel / Aguilar, Boris / Murrugarra, David

    Journal of theoretical biology

    2022  Volume 548, Page(s) 111197

    Abstract: Pancreatic Ductal Adenocarcinoma (PDAC) is widely known for its poor prognosis because it is often diagnosed when the cancer is in a later stage. We built a Boolean model to analyze the microenvironment of pancreatic cancer in order to better understand ... ...

    Abstract Pancreatic Ductal Adenocarcinoma (PDAC) is widely known for its poor prognosis because it is often diagnosed when the cancer is in a later stage. We built a Boolean model to analyze the microenvironment of pancreatic cancer in order to better understand the interplay between pancreatic cancer, stellate cells, and their signaling cytokines. Specifically, we have used our model to study the impact of inducing four common mutations: KRAS, TP53, SMAD4, and CDKN2A. After implementing the various mutation combinations, we used our stochastic simulator to derive aggressiveness scores based on simulated attractor probabilities and long-term trajectory approximations. These aggression scores were then corroborated with clinical data. Moreover, we found sets of control targets that are effective among common mutations. These control sets contain nodes within both the pancreatic cancer cell and the pancreatic stellate cell, including PIP3, RAF, PIK3 and BAX in pancreatic cancer cell as well as ERK and PIK3 in the pancreatic stellate cell. Many of these nodes were found to be differentially expressed among pancreatic cancer patients in the TCGA database. Furthermore, literature suggests that many of these nodes can be targeted by drugs currently in circulation. The results herein help provide a proof of concept in the path towards personalized medicine through a means of mathematical systems biology. All data and code used for running simulations, statistical analysis, and plotting is available on a GitHub repository athttps://github.com/drplaugher/PCC_Mutations.
    MeSH term(s) Carcinoma, Pancreatic Ductal/genetics ; Carcinoma, Pancreatic Ductal/pathology ; Humans ; Mutation ; Pancreatic Neoplasms/genetics ; Pancreatic Neoplasms/pathology ; Tumor Microenvironment/genetics ; Pancreatic Neoplasms
    Language English
    Publishing date 2022-06-22
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2972-5
    ISSN 1095-8541 ; 0022-5193
    ISSN (online) 1095-8541
    ISSN 0022-5193
    DOI 10.1016/j.jtbi.2022.111197
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 923: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
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  6. Article ; Online: EZH2 Inhibition Promotes Tumor Immunogenicity in Lung Squamous Cell Carcinomas.

    DuCote, Tanner J / Song, Xiulong / Naughton, Kassandra J / Chen, Fan / Plaugher, Daniel R / Childress, Avery R / Gellert, Abigail R / Skaggs, Erika M / Qu, Xufeng / Liu, Jinze / Liu, Jinpeng / Li, Fei / Wong, Kwok-Kin / Brainson, Christine F

    Cancer research communications

    2024  Volume 4, Issue 2, Page(s) 388–403

    Abstract: Two important factors that contribute to resistance to immune checkpoint inhibitors (ICI) are an immune-suppressive microenvironment and limited antigen presentation by tumor cells. In this study, we examine whether inhibition of the methyltransferase ... ...

    Abstract Two important factors that contribute to resistance to immune checkpoint inhibitors (ICI) are an immune-suppressive microenvironment and limited antigen presentation by tumor cells. In this study, we examine whether inhibition of the methyltransferase enhancer of zeste 2 (EZH2) can increase ICI response in lung squamous cell carcinomas (LSCC). Our in vitro experiments using two-dimensional human cancer cell lines as well as three-dimensional murine and patient-derived organoids treated with two inhibitors of the EZH2 plus IFNγ showed that EZH2 inhibition leads to expression of both MHC class I and II (MHCI/II) expression at both the mRNA and protein levels. Chromatin immunoprecipitation sequencing confirmed loss of EZH2-mediated histone marks and gain of activating histone marks at key loci. Furthermore, we demonstrate strong tumor control in models of both autochthonous and syngeneic LSCC treated with anti-PD1 immunotherapy with EZH2 inhibition. Single-cell RNA sequencing and immune cell profiling demonstrated phenotypic changes toward more tumor suppressive phenotypes in EZH2 inhibitor-treated tumors. These results indicate that EZH2 inhibitors could increase ICI responses in patients undergoing treatment for LSCC.
    Significance: The data described here show that inhibition of the epigenetic enzyme EZH2 allows derepression of multiple immunogenicity factors in LSCC, and that EZH2 inhibition alters myeloid cells in vivo. These data support clinical translation of this combination therapy for treatment of this deadly tumor type.
    MeSH term(s) Humans ; Mice ; Animals ; Carcinoma, Non-Small-Cell Lung ; Carcinoma, Squamous Cell/drug therapy ; Cell Line ; Enzyme Inhibitors ; Lung Neoplasms/drug therapy ; Lung/pathology ; Tumor Microenvironment ; Enhancer of Zeste Homolog 2 Protein/genetics
    Chemical Substances Enzyme Inhibitors ; EZH2 protein, human (EC 2.1.1.43) ; Enhancer of Zeste Homolog 2 Protein (EC 2.1.1.43)
    Language English
    Publishing date 2024-01-24
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ISSN 2767-9764
    ISSN (online) 2767-9764
    DOI 10.1158/2767-9764.CRC-23-0399
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: EZH2 inhibition promotes tumor immunogenicity in lung squamous cell carcinomas.

    DuCote, Tanner J / Song, Xiulong / Naughton, Kassandra J / Chen, Fan / Plaugher, Daniel R / Childress, Avery R / Edgin, Abigail R / Qu, Xufeng / Liu, Jinze / Liu, Jinpeng / Li, Fei / Wong, Kwok-Kin / Brainson, Christine F

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Two important factors that contribute to resistance to immune checkpoint inhibitors (ICIs) are an immune-suppressive microenvironment and limited antigen presentation by tumor cells. In this study, we examine if inhibition of the methyltransferase EZH2 ... ...

    Abstract Two important factors that contribute to resistance to immune checkpoint inhibitors (ICIs) are an immune-suppressive microenvironment and limited antigen presentation by tumor cells. In this study, we examine if inhibition of the methyltransferase EZH2 can increase ICI response in lung squamous cell carcinomas (LSCCs). Our
    Language English
    Publishing date 2023-06-08
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.06.06.543919
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Inter-library loan at ZB MED

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