Literature DB >> 19461917

Statistical aspects of gene signatures and molecular targets.

Mithat Gönen1.   

Abstract

Evolution of high-throughput technologies has enabled us to quantify several thousands of gene expressions simultaneously. Several oncologic applications have emerged, two of which will be discussed: developing gene signatures and finding molecular targets. This article emphasizes the different nature of statisitical methods used and required for developing gene signatures and identifying molecular targets. Routine and careful consideration of validation methods are essential for developing gene signatures. Choice of model development methodology seems to be less critical. Because of the way gene signatures are developed, even after careful validation, it is unlikely that they will yield a direct link to molecular targets. Identifying molecular targets will require more careful and focused experimentation than large-sample microarray studies.

Year:  2009        PMID: 19461917      PMCID: PMC2684735     

Source DB:  PubMed          Journal:  Gastrointest Cancer Res        ISSN: 1934-7820


  10 in total

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Authors:  D J Sargent
Journal:  Cancer       Date:  2001-04-15       Impact factor: 6.860

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Authors:  Giovanni Parmigiani; Elizabeth S Garrett-Mayer; Ramaswamy Anbazhagan; Edward Gabrielson
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Review 4.  Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting.

Authors:  Alain Dupuy; Richard M Simon
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5.  Sorting out breast-cancer gene signatures.

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6.  Two models for outcome prediction - a comparison of logistic regression and neural networks.

Authors:  R Linder; I R König; C Weimar; H C Diener; S J Pöppl; A Ziegler
Journal:  Methods Inf Med       Date:  2006       Impact factor: 2.176

7.  The prognostic role of a gene signature from tumorigenic breast-cancer cells.

Authors:  Rui Liu; Xinhao Wang; Grace Y Chen; Piero Dalerba; Austin Gurney; Timothy Hoey; Gavin Sherlock; John Lewicki; Kerby Shedden; Michael F Clarke
Journal:  N Engl J Med       Date:  2007-01-18       Impact factor: 91.245

Review 8.  Roadmap for developing and validating therapeutically relevant genomic classifiers.

Authors:  Richard Simon
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9.  Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan.

Authors:  Maguy Del Rio; Franck Molina; Caroline Bascoul-Mollevi; Virginie Copois; Frédéric Bibeau; Patrick Chalbos; Corinne Bareil; Andrew Kramar; Nicolas Salvetat; Caroline Fraslon; Emmanuel Conseiller; Virginie Granci; Benjamin Leblanc; Bernard Pau; Pierre Martineau; Marc Ychou
Journal:  J Clin Oncol       Date:  2007-03-01       Impact factor: 44.544

10.  A gene-expression signature as a predictor of survival in breast cancer.

Authors:  Marc J van de Vijver; Yudong D He; Laura J van't Veer; Hongyue Dai; Augustinus A M Hart; Dorien W Voskuil; George J Schreiber; Johannes L Peterse; Chris Roberts; Matthew J Marton; Mark Parrish; Douwe Atsma; Anke Witteveen; Annuska Glas; Leonie Delahaye; Tony van der Velde; Harry Bartelink; Sjoerd Rodenhuis; Emiel T Rutgers; Stephen H Friend; René Bernards
Journal:  N Engl J Med       Date:  2002-12-19       Impact factor: 91.245

  10 in total
  9 in total

1.  Network based consensus gene signatures for biomarker discovery in breast cancer.

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Review 2.  The molecular basis of chemoradiosensitivity in rectal cancer: implications for personalized therapies.

Authors:  Marian Grade; Hendrik A Wolff; Jochen Gaedcke; B Michael Ghadimi
Journal:  Langenbecks Arch Surg       Date:  2012-03-02       Impact factor: 3.445

Review 3.  Radiotherapy resistance: identifying universal biomarkers for various human cancers.

Authors:  Irina Larionova; Militsa Rakina; Elena Ivanyuk; Yulia Trushchuk; Alena Chernyshova; Evgeny Denisov
Journal:  J Cancer Res Clin Oncol       Date:  2022-02-03       Impact factor: 4.322

4.  Network and data integration for biomarker signature discovery via network smoothed T-statistics.

Authors:  Yupeng Cun; Holger Fröhlich
Journal:  PLoS One       Date:  2013-09-03       Impact factor: 3.240

5.  Functional characterization of breast cancer using pathway profiles.

Authors:  Feng Tian; Yajie Wang; Michael Seiler; Zhenjun Hu
Journal:  BMC Med Genomics       Date:  2014-07-21       Impact factor: 3.063

6.  Particle swarm optimization artificial intelligence technique for gene signature discovery in transcriptomic cohorts.

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Journal:  Comput Struct Biotechnol J       Date:  2022-09-26       Impact factor: 6.155

7.  Biomarker gene signature discovery integrating network knowledge.

Authors:  Yupeng Cun; Holger Fröhlich
Journal:  Biology (Basel)       Date:  2012-02-27

8.  Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition.

Authors:  Assya Trofimov; Joseph Paul Cohen; Yoshua Bengio; Claude Perreault; Sébastien Lemieux
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

9.  From hype to reality: data science enabling personalized medicine.

Authors:  Holger Fröhlich; Rudi Balling; Niko Beerenwinkel; Oliver Kohlbacher; Santosh Kumar; Thomas Lengauer; Marloes H Maathuis; Yves Moreau; Susan A Murphy; Teresa M Przytycka; Michael Rebhan; Hannes Röst; Andreas Schuppert; Matthias Schwab; Rainer Spang; Daniel Stekhoven; Jimeng Sun; Andreas Weber; Daniel Ziemek; Blaz Zupan
Journal:  BMC Med       Date:  2018-08-27       Impact factor: 8.775

  9 in total

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