Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Aberrant activation of signaling pathways downstream of epidermal growth factor receptor (EGFR) has been hypothesized to be one of the mechanisms of cetuximab (a monoclonal antibody against EGFR) resistance in head and neck squamous cell carcinoma (HNSCC). To infer relevant and specific pathway activation downstream of EGFR from gene expression in HNSCC, we generated gene expression signatures using immortalized keratinocytes (HaCaT) subjected to ligand stimulation and transfected with EGFR, RELA/p65, or HRAS ^Val12D.

Results

The gene expression patterns that distinguished the HaCaT variants and conditions were inferred using the Markov chain Monte Carlo (MCMC) matrix factorization algorithm Coordinated Gene Activity in Pattern Sets (CoGAPS). This approach inferred gene expression signatures with greater relevance to cell signaling pathway activation than the expression signatures inferred with standard linear models. Furthermore, the pathway signature generated using HaCaT-HRAS ^Val12D further associated with the cetuximab treatment response in isogenic cetuximab-sensitive (UMSCC1) and -resistant (1CC8) cell lines.

Conclusions

Our data suggest that the CoGAPS algorithm can generate gene expression signatures that are pertinent to downstream effects of receptor signaling pathway activation and potentially be useful in modeling resistance mechanisms to targeted therapies.

Related collections

Most cited references 32

Record: found
Abstract: found
Article: not found

Cluster analysis and display of genome-wide expression patterns.

P. T. Spellman, P. O. Brown, D Botstein … (1998)

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

0 comments Cited 1865 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1.

N. Agrawal, M Frederick, C. R. Pickering … (2011)

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. To explore the genetic origins of this cancer, we used whole-exome sequencing and gene copy number analyses to study 32 primary tumors. Tumors from patients with a history of tobacco use had more mutations than did tumors from patients who did not use tobacco, and tumors that were negative for human papillomavirus (HPV) had more mutations than did HPV-positive tumors. Six of the genes that were mutated in multiple tumors were assessed in up to 88 additional HNSCCs. In addition to previously described mutations in TP53, CDKN2A, PIK3CA, and HRAS, we identified mutations in FBXW7 and NOTCH1. Nearly 40% of the 28 mutations identified in NOTCH1 were predicted to truncate the gene product, suggesting that NOTCH1 may function as a tumor suppressor gene rather than an oncogene in this tumor type.

0 comments Cited 604 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

Charles Vaske, Stephen Benz, J Sanborn … (2010)

Motivation: High-throughput data is providing a comprehensive view of the molecular changes in cancer tissues. New technologies allow for the simultaneous genome-wide assay of the state of genome copy number variation, gene expression, DNA methylation and epigenetics of tumor samples and cancer cell lines. Analyses of current data sets find that genetic alterations between patients can differ but often involve common pathways. It is therefore critical to identify relevant pathways involved in cancer progression and detect how they are altered in different patients. Results: We present a novel method for inferring patient-specific genetic activities incorporating curated pathway interactions among genes. A gene is modeled by a factor graph as a set of interconnected variables encoding the expression and known activity of a gene and its products, allowing the incorporation of many types of omic data as evidence. The method predicts the degree to which a pathway's activities (e.g. internal gene states, interactions or high-level ‘outputs’) are altered in the patient using probabilistic inference. Compared with a competing pathway activity inference approach called SPIA, our method identifies altered activities in cancer-related pathways with fewer false-positives in both a glioblastoma multiform (GBM) and a breast cancer dataset. PARADIGM identified consistent pathway-level activities for subsets of the GBM patients that are overlooked when genes are considered in isolation. Further, grouping GBM patients based on their significant pathway perturbations divides them into clinically-relevant subgroups having significantly different survival outcomes. These findings suggest that therapeutics might be chosen that target genes at critical points in the commonly perturbed pathway(s) of a group of patients. Availability:Source code available at http://sbenz.github.com/Paradigm Contact: jstuart@soe.ucsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

0 comments Cited 323 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): BMC Genomics

Journal ID (iso-abbrev): BMC Genomics

Title: BMC Genomics

Publisher: BioMed Central

ISSN (Electronic): 1471-2164

Publication date Collection: 2012

Publication date (Electronic): 1 May 2012

Volume: 13

Page: 160

Affiliations

[1 ]Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD, USA

[2 ]Department of Radiation Oncology, Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA

[3 ]Department of Otolaryngology, Hokkaido University, Sapporo, Hokkaido, Japan

[4 ]Department of Pharmacology and Experimental Therapeutics, Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA

[5 ]Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, PA, USA

[6 ]Department of Health Science Informatics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA

Article

Publisher ID: 1471-2164-13-160

DOI: 10.1186/1471-2164-13-160

PMC ID: 3460736

PubMed ID: 22549044

SO-VID: 31c1e703-542c-4a84-9ab9-99afdbc96c87

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma

Read this article at

Abstract

Background

Results

Conclusions

Related collections

Genes & Diseases

Most cited references 32

Cluster analysis and display of genome-wide expression patterns.

Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1.

Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

Author and article information

Journal

Affiliations

Article

History

Categories

Comments

Comment on this article

Similar content 345

Cited by 11

Most referenced authors 1,417