Literature DB >> 25132268

Single-cell gene expression signatures reveal melanoma cell heterogeneity.

M Ennen1, C Keime1, D Kobi1, G Mengus1, D Lipsker2, C Thibault-Carpentier1, I Davidson1.   

Abstract

It is well established that tumours are not homogenous, but comprise cells with differing invasive, proliferative and tumour-initiating potential. A major challenge in cancer research is therefore to develop methods to characterize cell heterogeneity. In melanoma, proliferative and invasive cells are characterized by distinct gene expression profiles and accumulating evidence suggests that cells can alternate between these states through a process called phenotype switching. We have used microfluidic technology to isolate single melanoma cells grown in vitro as monolayers or melanospheres or in vivo as xenografted tumours and analyse the expression profiles of 114 genes that discriminate the proliferative and invasive states by quantitative PCR. Single-cell analysis accurately recapitulates the specific gene expression programmes of melanoma cell lines and defines subpopulations with distinct expression profiles. Cell heterogeneity is augmented when cells are grown as spheres and as xenografted tumours. Correlative analysis identifies gene-regulatory networks and changes in gene expression under different growth conditions. In tumours, subpopulations of cells that express specific invasion and drug resistance markers can be identified amongst which is the pluripotency factor POUF51 (OCT4) whose expression correlates with the tumorigenic potential. We therefore show that single-cell analysis can be used to define and quantify tumour heterogeneity based on detection of cells with specific gene expression profiles.

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Year:  2014        PMID: 25132268     DOI: 10.1038/onc.2014.262

Source DB:  PubMed          Journal:  Oncogene        ISSN: 0950-9232            Impact factor:   9.867


  31 in total

1.  Mitf is the key molecular switch between mouse or human melanoma initiating cells and their differentiated progeny.

Authors:  Y Cheli; S Giuliano; S Guiliano; T Botton; S Rocchi; V Hofman; P Hofman; P Bahadoran; C Bertolotto; R Ballotti
Journal:  Oncogene       Date:  2011-01-31       Impact factor: 9.867

2.  GLI2 and M-MITF transcription factors control exclusive gene expression programs and inversely regulate invasion in human melanoma cells.

Authors:  Delphine Javelaud; Vasileia-Ismini Alexaki; Marie-Jeanne Pierrat; Keith S Hoek; Sylviane Dennler; Leon Van Kempen; Corine Bertolotto; Robert Ballotti; Simon Saule; Véronique Delmas; Alain Mauviel
Journal:  Pigment Cell Melanoma Res       Date:  2011-08-18       Impact factor: 4.693

3.  Inverse expression states of the BRN2 and MITF transcription factors in melanoma spheres and tumour xenografts regulate the NOTCH pathway.

Authors:  A E Thurber; G Douglas; E C Sturm; S E Zabierowski; D J Smit; S N Ramakrishnan; E Hacker; J H Leonard; M Herlyn; R A Sturm
Journal:  Oncogene       Date:  2011-02-28       Impact factor: 9.867

4.  Mitf regulation of Dia1 controls melanoma proliferation and invasiveness.

Authors:  Suzanne Carreira; Jane Goodall; Laurence Denat; Mercedes Rodriguez; Paolo Nuciforo; Keith S Hoek; Alessandro Testori; Lionel Larue; Colin R Goding
Journal:  Genes Dev       Date:  2006-12-15       Impact factor: 11.361

5.  Regulation of autologous immunity to the mouse 5T4 oncofoetal antigen: implications for immunotherapy.

Authors:  Fernanda V Castro; Mariam Al-Muftah; Kate Mulryan; Hui-Rong Jiang; Jan-Wouter Drijfhout; Sumia Ali; Andrzej J Rutkowski; Milena Kalaitsidou; David E Gilham; Peter L Stern
Journal:  Cancer Immunol Immunother       Date:  2011-11-30       Impact factor: 6.968

6.  Heterogeneous phenotype of human melanoma cells with in vitro and in vivo features of tumor-initiating cells.

Authors:  Michela Perego; Monica Tortoreto; Gabrina Tragni; Luigi Mariani; Paola Deho; Antonino Carbone; Mario Santinami; Roberto Patuzzo; Pamela Della Mina; Antonello Villa; Graziella Pratesi; Giacomo Cossa; Paola Perego; Maria G Daidone; Malcolm R Alison; Giorgio Parmiani; Licia Rivoltini; Chiara Castelli
Journal:  J Invest Dermatol       Date:  2010-04-08       Impact factor: 8.551

7.  A tumor suppressor function for the lipid phosphatase INPP4B in melanocytic neoplasms.

Authors:  Rolando Perez-Lorenzo; Kamraan Z Gill; Che-Hung Shen; Feng X Zhao; Bin Zheng; Hans-Joachim Schulze; David N Silvers; Georg Brunner; Basil A Horst
Journal:  J Invest Dermatol       Date:  2013-11-28       Impact factor: 8.551

8.  Identification of novel epigenetically modified genes in human melanoma via promoter methylation gene profiling.

Authors:  Suhu Liu; Suping Ren; Paul Howell; Oystein Fodstad; Adam I Riker
Journal:  Pigment Cell Melanoma Res       Date:  2007-06-28       Impact factor: 4.693

9.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

Review 10.  Tumour heterogeneity and cancer cell plasticity.

Authors:  Corbin E Meacham; Sean J Morrison
Journal:  Nature       Date:  2013-09-19       Impact factor: 49.962

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  37 in total

Review 1.  The master role of microphthalmia-associated transcription factor in melanocyte and melanoma biology.

Authors:  Akinori Kawakami; David E Fisher
Journal:  Lab Invest       Date:  2017-03-06       Impact factor: 5.662

Review 2.  Bioinformatic Analysis of Gene Expression for Melanoma Treatment.

Authors:  Akinori Kawakami; David E Fisher
Journal:  J Invest Dermatol       Date:  2016-12       Impact factor: 8.551

3.  Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors.

Authors:  A K Mitra; U K Mukherjee; T Harding; J S Jang; H Stessman; Y Li; A Abyzov; J Jen; S Kumar; V Rajkumar; B Van Ness
Journal:  Leukemia       Date:  2015-12-29       Impact factor: 11.528

4.  Fate mapping melanoma persister cells through regression and into recurrent disease in adult zebrafish.

Authors:  Jana Travnickova; Sarah Muise; Sonia Wojciechowska; Alessandro Brombin; Zhiqiang Zeng; Adelaide I J Young; Cameron Wyatt; E Elizabeth Patton
Journal:  Dis Model Mech       Date:  2022-09-16       Impact factor: 5.732

5.  Single-cell systems biology: probing the basic unit of information flow.

Authors:  Simona Patange; Michelle Girvan; Daniel R Larson
Journal:  Curr Opin Syst Biol       Date:  2017-12-06

Review 6.  The dynamic control of signal transduction networks in cancer cells.

Authors:  Walter Kolch; Melinda Halasz; Marina Granovskaya; Boris N Kholodenko
Journal:  Nat Rev Cancer       Date:  2015-08-20       Impact factor: 60.716

7.  Zebrafish MITF-Low Melanoma Subtype Models Reveal Transcriptional Subclusters and MITF-Independent Residual Disease.

Authors:  Jana Travnickova; Sonia Wojciechowska; Ava Khamseh; Philippe Gautier; Daniel V Brown; Thomas Lefevre; Alessandro Brombin; Ailith Ewing; Amy Capper; Michaela Spitzer; Ramile Dilshat; Colin A Semple; Marie E Mathers; James A Lister; Eiríkur Steingrimsson; Thierry Voet; Chris P Ponting; E Elizabeth Patton
Journal:  Cancer Res       Date:  2019-10-03       Impact factor: 12.701

8.  MiT/TFE Family of Transcription Factors, Lysosomes, and Cancer.

Authors:  Rushika M Perera; Chiara Di Malta; Andrea Ballabio
Journal:  Annu Rev Cancer Biol       Date:  2018-11-28

Review 9.  How Neural Crest Transcription Factors Contribute to Melanoma Heterogeneity, Cellular Plasticity, and Treatment Resistance.

Authors:  Anja Wessely; Theresa Steeb; Carola Berking; Markus Vincent Heppt
Journal:  Int J Mol Sci       Date:  2021-05-28       Impact factor: 5.923

10.  Identification of prognostic genes and construction of a novel gene signature in the skin melanoma based on the tumor microenvironment.

Authors:  Wang Yingjuan; Zhang Li; Cao Wei; Wang Xiaoyuan
Journal:  Medicine (Baltimore)       Date:  2021-05-28       Impact factor: 1.817

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