Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma

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Abstract

Purpose

To identify stage I lung adenocarcinoma patients with a poor prognosis who will benefit from adjuvant therapy.

Patients and Methods

Whole gene expression profiles were obtained at 19 time points over a 48-hour time course from human primary lung epithelial cells that were stimulated with epidermal growth factor (EGF) in the presence or absence of a clinically used EGF receptor tyrosine kinase (RTK)-specific inhibitor, gefitinib. The data were subjected to a mathematical simulation using the State Space Model (SSM). “Gefitinib-sensitive” genes, the expressional dynamics of which were altered by addition of gefitinib, were identified. A risk scoring model was constructed to classify high- or low-risk patients based on expression signatures of 139 gefitinib-sensitive genes in lung cancer using a training data set of 253 lung adenocarcinomas of North American cohort. The predictive ability of the risk scoring model was examined in independent cohorts of surgical specimens of lung cancer.

Results

The risk scoring model enabled the identification of high-risk stage IA and IB cases in another North American cohort for overall survival (OS) with a hazard ratio (HR) of 7.16 (P = 0.029) and 3.26 (P = 0.0072), respectively. It also enabled the identification of high-risk stage I cases without bronchioalveolar carcinoma (BAC) histology in a Japanese cohort for OS and recurrence-free survival (RFS) with HRs of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively.

Conclusion

The set of 139 gefitinib-sensitive genes includes many genes known to be involved in biological aspects of cancer phenotypes, but not known to be involved in EGF signaling. The present result strongly re-emphasizes that EGF signaling status in cancer cells underlies an aggressive phenotype of cancer cells, which is useful for the selection of early-stage lung adenocarcinoma patients with a poor prognosis.

Trial Registration

The Gene Expression Omnibus (GEO) GSE31210

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Most cited references 19

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

Andrea Bild, Guang Yao, Jeffrey Chang … (2006)

The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.

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Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.

Kerby Shedden, Jeremy M. G. Taylor, Steven A. Enkemann … (2008)

Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.

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Roles for growth factors in cancer progression.

Esther Witsch, Michael Sela, Yosef Yarden (2010)

Under physiological conditions, cells receive fate-determining signals from their tissue surroundings, primarily in the form of polypeptide growth factors. Integration of these extracellular signals underlies tissue homeostasis. Although departure from homeostasis and tumor initiation are instigated by oncogenic mutations rather than by growth factors, the latter are the major regulators of all subsequent steps of tumor progression, namely clonal expansion, invasion across tissue barriers, angiogenesis, and colonization of distant niches. Here, we discuss the relevant growth factor families, their roles in tumor biology, as well as the respective downstream signaling pathways. Importantly, cancer-associated activating mutations that impinge on these pathways often relieve, in part, the reliance of tumors on growth factors. On the other hand, growth factors are frequently involved in evolvement of resistance to therapeutic regimens, which extends the roles for polypeptide factors to very late phases of tumor progression and offers opportunities for cancer therapy.

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Author and article information

Contributors

: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2012

Publication date (Electronic): 19 September 2012

Volume: 7

Issue: 9

Electronic Location Identifier: e43923

Affiliations

[1 ]Division of Systems Biomedical Technology, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan

[2 ]Human Genome Center, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan

[3 ]Division of Genome Biology, National Cancer Center Research Institute, Chuo-ku, Tokyo, Japan

[4 ]Institute of Statistical Mathematics, Tachikawa-shi, Tokyo, Japan

[5 ]Department of Thoracic Surgery, Tokyo Medical University, Shinjuku-ku, Tokyo, Japan

[6 ]Department of Surgery, Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America

[7 ]Division of Multistep Carcinogenesis, National Cancer Center Research Institute, Chuo-ku, Tokyo, Japan

University of Texas MD Anderson Cancer Center, United States of America

Author notes

* E-mail: ngotoh@ 123456ims.u-tokyo.ac.jp

Competing Interests: The authors have declared that no competing interests exist.

Conceived and designed the experiments: MY Rui Yamaguchi AN TK JY SM NG. Performed the experiments: MY TK. Analyzed the data: MY Rui Yamaguchi AN TK M. Nagasaki TS SI AS KU YH Ryo Yoshida TH M. Nomura DB JY SM NG. Contributed reagents/materials/analysis tools: TK JY. Wrote the paper: MY Rui Yamaguchi AN TK TS SI JY NG.

[¤]

Current address: Department of Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, United States of America

Article

Publisher ID: PONE-D-12-05356

DOI: 10.1371/journal.pone.0043923

PMC ID: 3446964

PubMed ID: 23028479

SO-VID: e45494d8-798d-49b4-8ea7-ce304131f03b

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 23 February 2012

Date accepted : 27 July 2012

Page count

Pages: 11

Funding

This work was supported by a grant for the 3rd-term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan ( http://www.mhlw.go.jp/english/) to JY, TK, and NG, by Grant-in-Aid for Scientific Research on Innovative Areas from the Ministry of Education, Culture, Sports, Science & Technology (MEXT) of Japan ( http://www.mext.go.jp/english/) to NG (22130009), by Research and Development of the Next-Generation Integrated Simulation of Living Matter, a part of the Development and Use of the Next-Generation Supercomputer Project of MEXT of Japan ( http://www.mext.go.jp/english/) to SM, and by the National Cancer Center Research and Development Fund to TK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Epidermal Growth Factor Receptor Tyrosine Kinase Defines Critical Prognostic Genes of Stage I Lung Adenocarcinoma

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Abstract

Purpose

Patients and Methods

Results

Conclusion

Trial Registration

Related collections

PLOS Climate

Most cited references 19

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

Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study.

Roles for growth factors in cancer progression.

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