Literature DB >> 32776157

A systems biology approach to discovering pathway signaling dysregulation in metastasis.

Robert Clarke1,2, Pavel Kraikivski3, Brandon C Jones4, Catherine M Sevigny4, Surojeet Sengupta4, Yue Wang5.   

Abstract

Total metastatic burden is the primary cause of death for many cancer patients. While the process of metastasis has been studied widely, much remains to be understood. Moreover, few agents have been developed that specifically target the major steps of the metastatic cascade. Many individual genes and pathways have been implicated in metastasis but a holistic view of how these interact and cooperate to regulate and execute the process remains somewhat rudimentary. It is unclear whether all of the signaling features that regulate and execute metastasis are yet fully understood. Novel features of a complex system such as metastasis can often be discovered by taking a systems-based approach. We introduce the concepts of systems modeling and define some of the central challenges facing the application of a multidisciplinary systems-based approach to understanding metastasis and finding actionable targets therein. These challenges include appreciating the unique properties of the high-dimensional omics data often used for modeling, limitations in knowledge of the system (metastasis), tumor heterogeneity and sampling bias, and some of the issues key to understanding critical features of molecular signaling in the context of metastasis. We also provide a brief introduction to integrative modeling that focuses on both the nodes and edges of molecular signaling networks. Finally, we offer some observations on future directions as they relate to developing a systems-based model of the metastatic cascade.

Entities:  

Keywords:  Bioinformatics; Breast cancer; Computational modeling; Mathematical modeling; Metastasis; Multiscale modeling; Pathway analysis; Signaling; Systems biology

Mesh:

Year:  2020        PMID: 32776157      PMCID: PMC7487029          DOI: 10.1007/s10555-020-09921-7

Source DB:  PubMed          Journal:  Cancer Metastasis Rev        ISSN: 0167-7659            Impact factor:   9.264


  72 in total

Review 1.  Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.

Authors:  Robert Clarke; John J Tyson; Ming Tan; William T Baumann; Lu Jin; Jianhua Xuan; Yue Wang
Journal:  Endocr Relat Cancer       Date:  2019-06       Impact factor: 5.678

Review 2.  The properties of high-dimensional data spaces: implications for exploring gene and protein expression data.

Authors:  Robert Clarke; Habtom W Ressom; Antai Wang; Jianhua Xuan; Minetta C Liu; Edmund A Gehan; Yue Wang
Journal:  Nat Rev Cancer       Date:  2008-01       Impact factor: 60.716

Review 3.  Classifying collective cancer cell invasion.

Authors:  Peter Friedl; Joseph Locker; Erik Sahai; Jeffrey E Segall
Journal:  Nat Cell Biol       Date:  2012-08       Impact factor: 28.824

Review 4.  Unravelling the complexity of metastasis - molecular understanding and targeted therapies.

Authors:  Nilay Sethi; Yibin Kang
Journal:  Nat Rev Cancer       Date:  2011-09-23       Impact factor: 60.716

Review 5.  Genetic insights into the morass of metastatic heterogeneity.

Authors:  Kent W Hunter; Ruhul Amin; Sarah Deasy; Ngoc-Han Ha; Lalage Wakefield
Journal:  Nat Rev Cancer       Date:  2018-02-09       Impact factor: 60.716

6.  Transcriptional diversity and bioenergetic shift in human breast cancer metastasis revealed by single-cell RNA sequencing.

Authors:  Ryan T Davis; Kerrigan Blake; Dennis Ma; Mari B Ishak Gabra; Grace A Hernandez; Anh T Phung; Ying Yang; Dustin Maurer; Austin E Y T Lefebvre; Hamad Alshetaiwi; Zhengtao Xiao; Juan Liu; Jason W Locasale; Michelle A Digman; Eric Mjolsness; Mei Kong; Zena Werb; Devon A Lawson
Journal:  Nat Cell Biol       Date:  2020-03-06       Impact factor: 28.824

Review 7.  Targeting metastasis.

Authors:  Patricia S Steeg
Journal:  Nat Rev Cancer       Date:  2016-04       Impact factor: 60.716

Review 8.  In Vitro Tumor Models: Advantages, Disadvantages, Variables, and Selecting the Right Platform.

Authors:  Moriah E Katt; Amanda L Placone; Andrew D Wong; Zinnia S Xu; Peter C Searson
Journal:  Front Bioeng Biotechnol       Date:  2016-02-12

9.  2D and 3D cell cultures - a comparison of different types of cancer cell cultures.

Authors:  Marta Kapałczyńska; Tomasz Kolenda; Weronika Przybyła; Maria Zajączkowska; Anna Teresiak; Violetta Filas; Matthew Ibbs; Renata Bliźniak; Łukasz Łuczewski; Katarzyna Lamperska
Journal:  Arch Med Sci       Date:  2016-11-18       Impact factor: 3.318

10.  Plug-and-Play In Vitro Metastasis System toward Recapitulating the Metastatic Cascade.

Authors:  Bing-Syuan Ni; Ching Tzao; Jen-Huang Huang
Journal:  Sci Rep       Date:  2019-12-02       Impact factor: 4.379

View more
  4 in total

1.  Experimental models of endocrine responsive breast cancer: strengths, limitations, and use.

Authors:  Robert Clarke; Brandon C Jones; Catherine M Sevigny; Leena A Hilakivi-Clarke; Surojeet Sengupta
Journal:  Cancer Drug Resist       Date:  2021-07-08

2.  Crosstalk between Plk1, p53, cell cycle, and G2/M DNA damage checkpoint regulation in cancer: computational modeling and analysis.

Authors:  Yongwoon Jung; Pavel Kraikivski; Ranjan K Dash; Sajad Shafiekhani; Scott S Terhune
Journal:  NPJ Syst Biol Appl       Date:  2021-12-09

Review 3.  Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era.

Authors:  Dina G Moussa; Paras Ahmad; Tamer A Mansour; Walter L Siqueira
Journal:  Front Cell Infect Microbiol       Date:  2022-06-17       Impact factor: 6.073

4.  HNRNPA2B1 regulates tamoxifen- and fulvestrant-sensitivity and hallmarks of endocrine resistance in breast cancer cells.

Authors:  Belinda J Petri; Kellianne M Piell; Gordon C South Whitt; Ali E Wilt; Claire C Poulton; Norman L Lehman; Brian F Clem; Matthew A Nystoriak; Marcin Wysoczynski; Carolyn M Klinge
Journal:  Cancer Lett       Date:  2021-07-14       Impact factor: 9.756

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.