Literature DB >> 30017637

Explaining the dynamics of tumor aggressiveness: At the crossroads between biology, artificial intelligence and complex systems.

Caterina A M La Porta1, Stefano Zapperi2.   

Abstract

Facing metastasis is the most pressing challenge of cancer research. In this review, we discuss recent advances in understanding phenotypic plasticity of cancer cells, highlighting the kinetics of cancer stem cell and the role of the epithelial mesenchymal transition for metastasis. It appears that the tumor micro-environment plays a crucial role in triggering phenotypic transitions, as we illustrate discussing the challenges posed by macrophages and cancer associated fibroblasts. To disentangle the complexity of environmentally induced phenotypic transitions, there is a growing need for novel advanced algorithms as those proposed in our recent work combining single cell data analysis and numerical simulations of gene regulatory networks. We conclude discussing recent developments in artificial intelligence and its applications to personalized cancer treatment.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cancer stem cells; Metastasis; Phenotypic switching; Precision medicine

Mesh:

Year:  2018        PMID: 30017637     DOI: 10.1016/j.semcancer.2018.07.003

Source DB:  PubMed          Journal:  Semin Cancer Biol        ISSN: 1044-579X            Impact factor:   15.707


  3 in total

1.  The Concomitant Expression of Human Endogenous Retroviruses and Embryonic Genes in Cancer Cells under Microenvironmental Changes is a Potential Target for Antiretroviral Drugs.

Authors:  Alessandro Giovinazzo; Emanuela Balestrieri; Vita Petrone; Ayele Argaw-Denboba; Chiara Cipriani; Martino Tony Miele; Sandro Grelli; Paola Sinibaldi-Vallebona; Claudia Matteucci
Journal:  Cancer Microenviron       Date:  2019-11-05

2.  Autocrine TGF-β1/miR-200s/miR-221/DNMT3B regulatory loop maintains CAF status to fuel breast cancer cell proliferation.

Authors:  Xi Tang; Gang Tu; Guanglun Yang; Xing Wang; Linmin Kang; Liping Yang; Huan Zeng; Xueying Wan; Yina Qiao; Xiaojiang Cui; Manran Liu; Yixuan Hou
Journal:  Cancer Lett       Date:  2019-03-06       Impact factor: 8.679

Review 3.  High-throughput proteomics: a methodological mini-review.

Authors:  Miao Cui; Chao Cheng; Lanjing Zhang
Journal:  Lab Invest       Date:  2022-08-03       Impact factor: 5.502

  3 in total

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