Literature DB >> 33723745

Understanding breast cancer heterogeneity through non-genetic heterogeneity.

Neda Barzgar Barough1,2, Fakhrosadat Sajjadian1,3, Nazila Jalilzadeh1,4, Hajar Shafaei2, Kobra Velaei5,6.   

Abstract

Intricacy in treatment and diagnosis of breast cancer has been an obstacle due to genotype and phenotype heterogeneity. Understanding of non-genetic heterogeneity mechanisms along with considering role of genetic heterogeneity may fill the gaps in landscape painting of heterogeneity. The main factors contribute to non-genetic heterogeneity including: transcriptional pulsing/bursting or discontinuous transcriptions, stochastic partitioning of components at cell division and various signal transduction from tumor ecosystem. Throughout this review, we desired to provide a conceptual framework focused on non-genetic heterogeneity, which has been intended to offer insight into prediction, diagnosis and treatment of breast cancer.

Entities:  

Keywords:  Breast cancer; Heterogeneity; Non-genetic heterogeneity; Phenotype; Tumor microenvironment

Mesh：

Year:  2021        PMID： 33723745     DOI： 10.1007/s12282-021-01237-w

Source DB:  PubMed          Journal:  Breast Cancer        ISSN： 1340-6868            Impact factor:   4.239


  92 in total

1.  Gene Regulation: Stable Noise.

Authors:  Jonathan R Chubb
Journal:  Curr Biol       Date:  2016-01-25       Impact factor: 10.834

2.  Non-genetic heterogeneity from stochastic partitioning at cell division.

Authors:  Dann Huh; Johan Paulsson
Journal:  Nat Genet       Date:  2010-12-26       Impact factor: 38.330

Review 3.  Stochasticity in gene expression: from theories to phenotypes.

Authors:  Mads Kaern; Timothy C Elston; William J Blake; James J Collins
Journal:  Nat Rev Genet       Date:  2005-06       Impact factor: 53.242

Review 4.  Dynamic regulation of transcriptional states by chromatin and transcription factors.

Authors:  Ty C Voss; Gordon L Hager
Journal:  Nat Rev Genet       Date:  2013-12-17       Impact factor: 53.242

5.  Stochastic modelling reveals mechanisms of metabolic heterogeneity.

Authors:  Mona K Tonn; Philipp Thomas; Mauricio Barahona; Diego A Oyarzún
Journal:  Commun Biol       Date:  2019-03-21

Review 6.  A framework for advancing our understanding of cancer-associated fibroblasts.

Authors:  Erik Sahai; Igor Astsaturov; Edna Cukierman; David G DeNardo; Mikala Egeblad; Ronald M Evans; Douglas Fearon; Florian R Greten; Sunil R Hingorani; Tony Hunter; Richard O Hynes; Rakesh K Jain; Tobias Janowitz; Claus Jorgensen; Alec C Kimmelman; Mikhail G Kolonin; Robert G Maki; R Scott Powers; Ellen Puré; Daniel C Ramirez; Ruth Scherz-Shouval; Mara H Sherman; Sheila Stewart; Thea D Tlsty; David A Tuveson; Fiona M Watt; Valerie Weaver; Ashani T Weeraratna; Zena Werb
Journal:  Nat Rev Cancer       Date:  2020-01-24       Impact factor: 60.716

7.  An update to the Monro-Kellie doctrine to reflect tissue compliance after severe ischemic and hemorrhagic stroke.

Authors:  Anna C J Kalisvaart; Cassandra M Wilkinson; Sherry Gu; Tiffany F C Kung; Jerome Yager; Ian R Winship; Frank K H van Landeghem; Frederick Colbourne
Journal:  Sci Rep       Date:  2020-12-16       Impact factor: 4.379

8.  Quantifying intrinsic and extrinsic control of single-cell fates in cancer and stem/progenitor cell pedigrees with competing risks analysis.

Authors:  J A Cornwell; R M Hallett; S Auf der Mauer; A Motazedian; T Schroeder; J S Draper; R P Harvey; R E Nordon
Journal:  Sci Rep       Date:  2016-06-01       Impact factor: 4.379

9.  Metabolic gene alterations impact the clinical aggressiveness and drug responses of 32 human cancers.

Authors:  Musalula Sinkala; Nicola Mulder; Darren Patrick Martin
Journal:  Commun Biol       Date:  2019-11-14

10.  Layered material platform for surface plasmon resonance biosensing.

Authors:  F Wu; P A Thomas; V G Kravets; H O Arola; M Soikkeli; K Iljin; G Kim; M Kim; H S Shin; D V Andreeva; C Neumann; M Küllmer; A Turchanin; D De Fazio; O Balci; V Babenko; B Luo; I Goykhman; S Hofmann; A C Ferrari; K S Novoselov; A N Grigorenko
Journal:  Sci Rep       Date:  2019-12-30       Impact factor: 4.379
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  1 in total

1.  Evaluation of Adjuvant Treatments for Adenoid Cystic Carcinoma of the Breast: A Population-Based, Propensity Score Matched Cohort Study from the SEER Database.

Authors:  Liu Yang; Chaobin Wang; Miao Liu; Shu Wang
Journal:  Diagnostics (Basel)       Date:  2022-07-21
  1 in total

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