Literature DB >> 20479229

Information-theoretic analysis of phenotype changes in early stages of carcinogenesis.

F Remacle1, Nataly Kravchenko-Balasha, Alexander Levitzki, R D Levine.   

Abstract

Cancer is a multistep process characterized by altered signal transduction, cell growth, and metabolism. To identify such processes in early carcinogenesis we use an information theoretic approach to characterize gene expression quantified as mRNA levels in primary keratinocytes (K) and human papillomavirus 16 (HPV16)-transformed keratinocytes (HF1 cells) from early (E) and late (L) passages and from benzo(a)pyrene-treated (BP) L cells. Our starting point is that biological signaling processes are subjected to the same quantitative laws as inanimate, nonequilibrium chemical systems. Environmental and genomic constraints thereby limit the maximal thermodynamic entropy that the biological system can reach. The procedure uncovers the changes in gene expression patterns in different networks and defines the significance of each altered network in the establishment of a particular phenotype. The development of transformed HF1 cells is shown to be represented by one major transcription pattern that is important at all times. Two minor transcription patterns are also identified, one that contributes at early times and a distinguishably different pattern that contributes at later times. All three transcription patterns defined by our analysis were validated by gene expression values and biochemical means. The major transcription pattern includes reduced transcripts participating in the apoptotic network and enhanced transcripts participating in cell cycle, glycolysis, and oxidative phosphorylation. The two minor patterns identify genes that are mainly involved in lipid or carbohydrate metabolism.

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Year:  2010        PMID: 20479229      PMCID: PMC2890488          DOI: 10.1073/pnas.1005283107

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  13 in total

1.  Fundamental patterns underlying gene expression profiles: simplicity from complexity.

Authors:  N S Holter; M Mitra; A Maritan; M Cieplak; J R Banavar; N V Fedoroff
Journal:  Proc Natl Acad Sci U S A       Date:  2000-07-18       Impact factor: 11.205

2.  Singular value decomposition for genome-wide expression data processing and modeling.

Authors:  O Alter; P O Brown; D Botstein
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-29       Impact factor: 11.205

3.  Downregulation of Akt1 inhibits anchorage-independent cell growth and induces apoptosis in cancer cells.

Authors:  X Liu; Y Shi; E K Han; Z Chen; S H Rosenberg; V L Giranda; Y Luo; S C Ng
Journal:  Neoplasia       Date:  2001 Jul-Aug       Impact factor: 5.715

4.  Enhancement of anchorage-independent growth of human pancreatic carcinoma MIA PaCa-2 cells by signaling from protein kinase C to mitogen-activated protein kinase.

Authors:  Keiko Ishino; Hidesuke Fukazawa; Mayumi Shikano; Motoi Ohba; Toshio Kuroki; Yoshimasa Uehara
Journal:  Mol Carcinog       Date:  2002-08       Impact factor: 4.784

5.  Deregulated Akt3 activity promotes development of malignant melanoma.

Authors:  Jill M Stahl; Arati Sharma; Mitchell Cheung; Melissa Zimmerman; Jin Q Cheng; Marcus W Bosenberg; Mark Kester; Lakshman Sandirasegarane; Gavin P Robertson
Journal:  Cancer Res       Date:  2004-10-01       Impact factor: 12.701

6.  Shift from apoptotic to necrotic cell death during human papillomavirus-induced transformation of keratinocytes.

Authors:  Nataly Kravchenko-Balasha; Sarit Mizrachy-Schwartz; Shoshana Klein; Alexander Levitzki
Journal:  J Biol Chem       Date:  2009-02-16       Impact factor: 5.157

7.  Optimization of energy-consuming pathways towards rapid growth in HPV-transformed cells.

Authors:  Sarit Mizrachy-Schwartz; Nataly Kravchenko-Balasha; Hannah Ben-Bassat; Shoshana Klein; Alexander Levitzki
Journal:  PLoS One       Date:  2007-07-11       Impact factor: 3.240

8.  Genome Expression Pathway Analysis Tool--analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context.

Authors:  Markus Weniger; Julia C Engelmann; Jörg Schultz
Journal:  BMC Bioinformatics       Date:  2007-06-02       Impact factor: 3.169

9.  Potential energy landscape and robustness of a gene regulatory network: toggle switch.

Authors:  Keun-Young Kim; Jin Wang
Journal:  PLoS Comput Biol       Date:  2007-02-14       Impact factor: 4.475

10.  Autocrine laminin-5 ligates alpha6beta4 integrin and activates RAC and NFkappaB to mediate anchorage-independent survival of mammary tumors.

Authors:  Nastaran Zahir; Johnathon N Lakins; Alan Russell; WenYu Ming; Chandrima Chatterjee; Gabriela I Rozenberg; M Peter Marinkovich; Valerie M Weaver
Journal:  J Cell Biol       Date:  2003-12-22       Impact factor: 10.539

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  41 in total

1.  On a fundamental structure of gene networks in living cells.

Authors:  Nataly Kravchenko-Balasha; Alexander Levitzki; Andrew Goldstein; Varda Rotter; A Gross; F Remacle; R D Levine
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-05       Impact factor: 11.205

2.  Thermodynamically inspired classifier for molecular phenotypes of health and disease.

Authors:  Marc T Facciotti
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-07       Impact factor: 11.205

3.  Protein signaling networks from single cell fluctuations and information theory profiling.

Authors:  Young Shik Shin; F Remacle; Rong Fan; Kiwook Hwang; Wei Wei; Habib Ahmad; R D Levine; James R Heath
Journal:  Biophys J       Date:  2011-05-18       Impact factor: 4.033

4.  Statistical thermodynamics of transcription profiles in normal development and tumorigeneses in cohorts of patients.

Authors:  F Remacle; R D Levine
Journal:  Eur Biophys J       Date:  2015-08-20       Impact factor: 1.733

5.  Surprisal analysis characterizes the free energy time course of cancer cells undergoing epithelial-to-mesenchymal transition.

Authors:  Sohila Zadran; Rameshkumar Arumugam; Harvey Herschman; Michael E Phelps; R D Levine
Journal:  Proc Natl Acad Sci U S A       Date:  2014-08-25       Impact factor: 11.205

6.  A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes.

Authors:  Nataly Kravchenko-Balasha; Hannah Johnson; Forest M White; James R Heath; R D Levine
Journal:  J Phys Chem B       Date:  2016-04-12       Impact factor: 2.991

7.  A novel estimator of the interaction matrix in Graphical Gaussian Model of omics data using the entropy of non-equilibrium systems.

Authors:  Ahmad Borzou; Rovshan G Sadygov
Journal:  Bioinformatics       Date:  2021-05-05       Impact factor: 6.937

8.  Critical Points in Tumorigenesis: A Carcinogen-Initiated Phase Transition Analyzed via Single-Cell Proteomics.

Authors:  Suresh Kumar Poovathingal; Nataly Kravchenko-Balasha; Young Shik Shin; Raphael David Levine; James R Heath
Journal:  Small       Date:  2016-01-18       Impact factor: 13.281

9.  Free energy rhythms in Saccharomyces cerevisiae: a dynamic perspective with implications for ribosomal biogenesis.

Authors:  A Gross; Caroline M Li; F Remacle; R D Levine
Journal:  Biochemistry       Date:  2013-02-20       Impact factor: 3.162

10.  Thermodynamic energetics underlying genomic instability and whole-genome doubling in cancer.

Authors:  Francoise Remacle; Thomas G Graeber; R D Levine
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-21       Impact factor: 11.205

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