Literature DB >> 31659104

Acquisition of Invasiveness by Breast Adenocarcinoma Cells Engages Established Hallmarks and Novel Regulatory Mechanisms.

Hanaa Mousa1, Mahmoud Elgamal1, Reham Ghazal Marei1, Nazariy Souchelnytskyi2, Kah-Wai Lin1,3, Serhiy Souchelnytskyi4.   

Abstract

BACKGROUND/AIM: Proteomics of invasiveness opens a window on the complexity of the metastasis-engaged mechanisms. The extend and types of this complexity require elucidation.
MATERIALS AND METHODS: Proteomics, immunohistochemistry, immunoblotting, network analysis and systems cancer biology were used to analyse acquisition of invasiveness by human breast adenocarcinoma cells.
RESULTS: We report here that invasiveness network highlighted the involvement of hallmarks such as cell proliferation, migration, cell death, genome stability, immune system regulation and metabolism. Identified involvement of cell-virus interaction and gene silencing are potentially novel cancer mechanisms. Identified 6,113 nodes with 11,055 edges affecting 1,085 biological processes show extensive re-arrangements in cell physiology. These high numbers are in line with a similar broadness of networks built with diagnostic signatures approved for clinical use.
CONCLUSION: Our data emphasize a broad systemic regulation of invasiveness, and describe the network of this regulation. Copyright
© 2019, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Entities:  

Keywords:  Breast cancer; invasiveness; proteomics; systems biology

Year:  2019        PMID: 31659104      PMCID: PMC6885374          DOI: 10.21873/cgp.20153

Source DB:  PubMed          Journal:  Cancer Genomics Proteomics        ISSN: 1109-6535            Impact factor:   4.069


  42 in total

1.  Tissue proteomics of the human mammary gland: towards an abridged definition of the molecular phenotypes underlying epithelial normalcy.

Authors:  José M A Moreira; Teresa Cabezón; Irina Gromova; Pavel Gromov; Vera Timmermans-Wielenga; Isidro Machado; Antonio Llombart-Bosch; Niels Kroman; Fritz Rank; Julio E Celis
Journal:  Mol Oncol       Date:  2010-10-08       Impact factor: 6.603

Review 2.  Next generation of network medicine: interdisciplinary signaling approaches.

Authors:  Tamas Korcsmaros; Maria Victoria Schneider; Giulio Superti-Furga
Journal:  Integr Biol (Camb)       Date:  2017-02-20       Impact factor: 2.192

Review 3.  Mechanisms of cancer cell invasion.

Authors:  Erik Sahai
Journal:  Curr Opin Genet Dev       Date:  2005-02       Impact factor: 5.578

4.  Identification of markers associated with highly aggressive metastatic phenotypes using quantitative comparative proteomics.

Authors:  Mikkel G Terp; Rikke R Lund; Ole N Jensen; Rikke Leth-Larsen; Henrik J Ditzel
Journal:  Cancer Genomics Proteomics       Date:  2012 Sep-Oct       Impact factor: 4.069

5.  Introduction: Cancer Gene Networks.

Authors:  Robert Clarke
Journal:  Methods Mol Biol       Date:  2017

6.  Human oncogenic viruses: nature and discovery.

Authors:  Yuan Chang; Patrick S Moore; Robin A Weiss
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-10-19       Impact factor: 6.237

7.  Breast cancer prognosis signature: linking risk stratification to disease subtypes.

Authors:  Fulong Yu; Fei Quan; Jinyuan Xu; Yan Zhang; Yi Xie; Jingyu Zhang; Yujia Lan; Huating Yuan; Hongyi Zhang; Shujun Cheng; Yun Xiao; Xia Li
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

Review 8.  MicroRNAs: target recognition and regulatory functions.

Authors:  David P Bartel
Journal:  Cell       Date:  2009-01-23       Impact factor: 41.582

9.  Development and verification of the PAM50-based Prosigna breast cancer gene signature assay.

Authors:  Brett Wallden; James Storhoff; Torsten Nielsen; Naeem Dowidar; Carl Schaper; Sean Ferree; Shuzhen Liu; Samuel Leung; Gary Geiss; Jacqueline Snider; Tammi Vickery; Sherri R Davies; Elaine R Mardis; Michael Gnant; Ivana Sestak; Matthew J Ellis; Charles M Perou; Philip S Bernard; Joel S Parker
Journal:  BMC Med Genomics       Date:  2015-08-22       Impact factor: 3.063

Review 10.  Machine learning and feature selection for drug response prediction in precision oncology applications.

Authors:  Mehreen Ali; Tero Aittokallio
Journal:  Biophys Rev       Date:  2018-08-10
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  2 in total

Review 1.  Targeted and systemic insights into the crosstalk between DNA-dependent protein kinase catalytic subunit and receptors of estrogen, progesterone and epidermal growth factor in the context of cancer.

Authors:  Soubiya Mohammed Rizwan Ansari; Farah Saleh Hijazi; Serhiy Souchelnytskyi
Journal:  Mol Biol Rep       Date:  2021-11-03       Impact factor: 2.316

2.  COVID-19 engages clinical markers for the management of cancer and cancer-relevant regulators of cell proliferation, death, migration, and immune response.

Authors:  Serhiy Souchelnytskyi; Andriy Nera; Nazariy Souchelnytskyi
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

  2 in total

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