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Oncogenic pathway signatures in human cancers as a guide to targeted therapies

Author

Listed:
  • Andrea H. Bild

    (Duke University
    Department of Molecular Genetics and Microbiology)

  • Guang Yao

    (Duke University
    Department of Molecular Genetics and Microbiology)

  • Jeffrey T. Chang

    (Duke University
    Department of Molecular Genetics and Microbiology)

  • Quanli Wang

    (Duke University)

  • Anil Potti

    (Duke University
    Department of Medicine)

  • Dawn Chasse

    (Duke University
    Department of Molecular Genetics and Microbiology)

  • Mary-Beth Joshi

    (Department of Surgery)

  • David Harpole

    (Department of Surgery)

  • Johnathan M. Lancaster

    (University of South Florida
    University of South Florida)

  • Andrew Berchuck

    (Duke University Medical Center
    Gynecology, Duke University Medical Center)

  • John A. Olson

    (Duke University
    Department of Surgery)

  • Jeffrey R. Marks

    (Department of Surgery)

  • Holly K. Dressman

    (Duke University
    Department of Molecular Genetics and Microbiology)

  • Mike West

    (Duke University)

  • Joseph R. Nevins

    (Duke University
    Department of Molecular Genetics and Microbiology)

Abstract

Tumour profiling advances Molecular tumour profiling is one way in which effective targeted cancer treatment regimes might be developed. Two groups report significant developments in this direction. Bild et al. studied gene expression patterns that reflect the activation of various oncogenic (cancer-causing) signal transduction pathways. Using combinations of these pathway signatures, they predict which patients with breast, lung or ovarian cancer have a particularly poor prognosis. The ability to identify molecular pathways that are deregulated in a particular cancer in this way might be used to predict its sensitivity to specific therapeutic drugs. Solit et al. studied tumour cells with mutations in the RAS and BRAF genes, thought to cause cancer at least in part by activating the MEK/ERK signalling pathway. They show that tumours with the BRAF mutation, but not RAS, are highly sensitive to PD0325901, an MEK inhibitor that is in early-stage clinical trials in patients with melanoma, colon, breast and lung cancers. So by testing for the presence of BRAF mutations it may be possible to identify those patients most likely to benefit from this type of drug.

Suggested Citation

  • Andrea H. Bild & Guang Yao & Jeffrey T. Chang & Quanli Wang & Anil Potti & Dawn Chasse & Mary-Beth Joshi & David Harpole & Johnathan M. Lancaster & Andrew Berchuck & John A. Olson & Jeffrey R. Marks &, 2006. "Oncogenic pathway signatures in human cancers as a guide to targeted therapies," Nature, Nature, vol. 439(7074), pages 353-357, January.
    • Handle: RePEc:nat:nature:v:439:y:2006:i:7074:d:10.1038_nature04296
    DOI: 10.1038/nature04296
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    2. Xuan Bich Trinh & Wiebren A A Tjalma & Luc Y Dirix & Peter B Vermeulen & Dieter J Peeters & Dimcho Bachvarov & Marie Plante & Els M Berns & Jozien Helleman & Steven J Van Laere & Peter A van Dam, 2011. "Microarray-Based Oncogenic Pathway Profiling in Advanced Serous Papillary Ovarian Carcinoma," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-9, July.
    3. Matthias Weber & Martin Schumacher & Harald Binder, 2014. "Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs," Tinbergen Institute Discussion Papers 14-089/I, Tinbergen Institute.
    4. Junjie Su & Byung-Jun Yoon & Edward R Dougherty, 2009. "Accurate and Reliable Cancer Classification Based on Probabilistic Inference of Pathway Activity," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-10, December.
    5. Carey K Anders & Chaitanya R Acharya & David S Hsu & Gloria Broadwater & Katherine Garman & John A Foekens & Yi Zhang & Yixin Wang & Kelly Marcom & Jeffrey R Marks & Sayan Mukherjee & Joseph R Nevins , 2008. "Age-Specific Differences in Oncogenic Pathway Deregulation Seen in Human Breast Tumors," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-8, January.
    6. Andrew E Teschendorff & Michel Journée & Pierre A Absil & Rodolphe Sepulchre & Carlos Caldas, 2007. "Elucidating the Altered Transcriptional Programs in Breast Cancer using Independent Component Analysis," PLOS Computational Biology, Public Library of Science, vol. 3(8), pages 1-16, August.
    7. Dario Zimmerli & Chiara S. Brambillasca & Francien Talens & Jinhyuk Bhin & Renske Linstra & Lou Romanens & Arkajyoti Bhattacharya & Stacey E. P. Joosten & Ana Moises Silva & Nuno Padrao & Max D. Welle, 2022. "MYC promotes immune-suppression in triple-negative breast cancer via inhibition of interferon signaling," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    8. Lucas Joseph & Carvalho Carlos & West Mike, 2009. "A Bayesian Analysis Strategy for Cross-Study Translation of Gene Expression Biomarkers," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-28, February.
    9. Balázs Győrffy & Pawel Surowiak & Jan Budczies & András Lánczky, 2013. "Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-8, December.
    10. Brian D Bennett & Qing Xiong & Sayan Mukherjee & Terrence S Furey, 2012. "A Predictive Framework for Integrating Disparate Genomic Data Types Using Sample-Specific Gene Set Enrichment Analysis and Multi-Task Learning," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    11. Verena Jabs & Karolina Edlund & Helena König & Marianna Grinberg & Katrin Madjar & Jörg Rahnenführer & Simon Ekman & Michael Bergkvist & Lars Holmberg & Katja Ickstadt & Johan Botling & Jan G Hengstle, 2017. "Integrative analysis of genome-wide gene copy number changes and gene expression in non-small cell lung cancer," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-23, November.
    12. Haleh Yasrebi & Peter Sperisen & Viviane Praz & Philipp Bucher, 2009. "Can Survival Prediction Be Improved By Merging Gene Expression Data Sets?," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-14, October.
    13. Mariëlle I Gallegos Ruiz & Karijn Floor & Paul Roepman & José A Rodriguez & Gerrit A Meijer & Wolter J Mooi & Ewa Jassem & Jacek Niklinski & Thomas Muley & Nico van Zandwijk & Egbert F Smit & Kristin , 2008. "Integration of Gene Dosage and Gene Expression in Non-Small Cell Lung Cancer, Identification of HSP90 as Potential Target," PLOS ONE, Public Library of Science, vol. 3(3), pages 1-8, March.
    14. Eun Sung Park & Ju-Seog Lee & Hyun Goo Woo & Fenghuang Zhan & Joanna H Shih & John D Shaughnessy Jr. & J Frederic Mushinski, 2007. "Heterologous Tissue Culture Expression Signature Predicts Human Breast Cancer Prognosis," PLOS ONE, Public Library of Science, vol. 2(1), pages 1-16, January.
    15. Hu, Jianwei & Chai, Hao, 2013. "Adjusted regularized estimation in the accelerated failure time model with high dimensional covariates," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 96-114.
    16. Hung-Chia Chen & Wen Zou & Tzu-Pin Lu & James J Chen, 2014. "A Composite Model for Subgroup Identification and Prediction via Bicluster Analysis," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-14, October.
    17. Ju Han Kim, 2012. "Chapter 8: Biological Knowledge Assembly and Interpretation," PLOS Computational Biology, Public Library of Science, vol. 8(12), pages 1-12, December.
    18. Dennis Kostka & Rainer Spang, 2008. "Microarray Based Diagnosis Profits from Better Documentation of Gene Expression Signatures," PLOS Computational Biology, Public Library of Science, vol. 4(2), pages 1-6, February.
    19. Ilya Kupershmidt & Qiaojuan Jane Su & Anoop Grewal & Suman Sundaresh & Inbal Halperin & James Flynn & Mamatha Shekar & Helen Wang & Jenny Park & Wenwu Cui & Gregory D Wall & Robert Wisotzkey & Satnam , 2010. "Ontology-Based Meta-Analysis of Global Collections of High-Throughput Public Data," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-13, September.
    20. Kuang Du & Shiyou Wei & Zhi Wei & Dennie T. Frederick & Benchun Miao & Tabea Moll & Tian Tian & Eric Sugarman & Dmitry I. Gabrilovich & Ryan J. Sullivan & Lunxu Liu & Keith T. Flaherty & Genevieve M. , 2021. "Pathway signatures derived from on-treatment tumor specimens predict response to anti-PD1 blockade in metastatic melanoma," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    21. Peter Langfelder & Paul S Mischel & Steve Horvath, 2013. "When Is Hub Gene Selection Better than Standard Meta-Analysis?," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-16, April.
    22. Daphne R Friedman & Joseph E Lucas & J Brice Weinberg, 2013. "Clinical and Biological Relevance of Genomic Heterogeneity in Chronic Lymphocytic Leukemia," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    23. Ruoqi Peng & Sriram Sridhar & Gaurav Tyagi & Jonathan E Phillips & Rosario Garrido & Paul Harris & Lisa Burns & Lorena Renteria & John Woods & Leena Chen & John Allard & Palanikumar Ravindran & Hans B, 2013. "Bleomycin Induces Molecular Changes Directly Relevant to Idiopathic Pulmonary Fibrosis: A Model for “Active” Disease," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-15, April.
    24. Yun-Yong Park & Eun Sung Park & Sang Bae Kim & Sang Cheol Kim & Bo Hwa Sohn & In-Sun Chu & Woojin Jeong & Gordon B Mills & Lauren Averett Byers & Ju-Seog Lee, 2012. "Development and Validation of a Prognostic Gene-Expression Signature for Lung Adenocarcinoma," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-10, September.

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