Researchers Use Microarray-Based Gene Expression Technology to Help Classify Tumor Profiles and Stratify Treatment Options
NEW YORK--(BUSINESS WIRE)-- ChipDX LLC, a New York-based online molecular diagnostics and personalized medicine company, discovered and validated a genetic signature for early-stage colon cancer and is developing an online screening application to enable clinicians to more accurately identify risk of recurrence. In the study, published in the December issue of the British Journal of Cancer, ChipDX demonstrates how the 163-gene signature stratifies colon cancer patients into high- and low-risk groups for recurrence with greater accuracy than current methods.
“We discovered a set of genes that were strongly associated with outcome, independent to current measurements of prognosis. By combining measurements of these genes, performed with Affymetrix® GeneChip® technology, and a robust predictive algorithm we were able to predict which individuals were at the greatest risk of recurrence within a five-year follow-up period,” said Ryan van Laar, PhD, ChipDX Founder and Chief Scientific Officer. “This unique signature’s ability to generate a highly personalized assessment of recurrence risk may one day assist physicians in deciding whether individuals with early-stage colon cancer should receive chemotherapy in addition to surgery.”
Currently, ChipDX is making the algorithm available for research use only through an online gene expression analysis platform at www.ChipDX.com and is reviewing regulatory requirements and partners to market it as a test for future diagnostic use.
“Dr. van Laar’s discovery demonstrates the advancement in gene expression array applications and further points to the significance and relevance of this technology,” said Kevin Cannon, Vice President of Marketing, Gene Expression Applications, at Affymetrix. “ChipDX’ online analysis platform embodies the Affymetrix goal of moving applications downstream from the basic research markets into clinical applications to vastly improve diagnosis and lead to better informed decisions for the most common cancers.”
Colon cancer, which causes 655,000 deaths worldwide each year, is the fourth most common form of cancer in the United States and the third leading cause of cancer-related death in the western world. Physicians currently use a method called clinical staging to measure the extent of disease spread at the time of diagnosis. Patients who are diagnosed with early-stage tumors (1-2) generally do not receive chemotherapy; however, approximately 20 percent of stage 2 patients develop recurrence within five years. In the study, the ChipDX algorithm is shown to stratify early-stage colon cancer patients with greater accuracy than clinical staging.
“Ultimately, we hope our predictive gene signature will help doctors to identify these early-stage ‘high-risk’ patients and offer them more personalized treatment options based on a set of genes related to survival above and beyond traditional assessments of outcome,” said Dr. van Laar. “If treatment is tailored to the precise nature of a patient’s tumor, the life-saving potential is greater.”
ChipDX developed its prognostic algorithm by analyzing data from a 2009 study of 232 US-based colon cancer patients (Smith, et al., 2009)1. An independent validation series of 60 stage 2 and 3 Australian colon cancer patients was used to validate the discovery (Jorissen, et al., 2009)2. Both studies utilized Affymetrix® GeneChip® Human Genome U133 Plus 2.0 Array profiles of colon cancer patients. The method of gene expression data analysis performed was designed to identify genes significantly associated with recurrence independent of the patient’s age at diagnosis, tumor grade, or disease stage.
The ChipDX online platform performs multi-gene diagnostic analysis on whole-genome Affymetrix GeneChip data for research applications. An important component of the platform is the proprietary ChipDX Quality Module™, developed by analyzing more than 3,000 GeneChip profiles of multiple tumor types generated in laboratories around the world. This module ensures that each assay meets a high level of data integrity before a diagnostic analysis is performed. After this analysis, the data can be submitted to the newly created Colon Cancer Module, which uses the recently published 163-gene predictive algorithm to generate an individualized assessment of recurrence risk, in real-time. The ChipDX online analysis system is compatible with the Affymetrix GeneChip platform and currently available only for clinical research and assessment.
About ChipDX
ChipDX develops and delivers novel multi-gene diagnostic and prognostic assays for oncology research use only. The aim of the company is to increase access to advanced, well-validated predictive and prognostic assays through collaborations with existing diagnostic service providers and also through its modular, online delivery system: www.ChipDX.com. Other microarray-based tests currently in development include prognostic assays for early-stage breast and lung cancer, as well as a diagnostic tool for characterizing metastatic or poorly differentiated tumors.
1 Smith JJ, Deane NG, Wu F, Merchant NB, Zhang B, Jiang A, Lu P, Johnson JC, Schmidt C, Bailey CE, Eschrich S, Kis C, Levy S, Washington MK, Heslin MJ, Coffey RJ, Yeatman TJ, Shyr Y, Beauchamp RD (2009) Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer. Gastroenterology 138: 958–968
2 Jorissen RN, Gibbs P, Christie M, Prakash S, Lipton L, Desai J, Kerr D, Aaltonen LA, Arango D, Kruhøffer M, Orntoft TF, Andersen CL, Gruidl M, Kamath VP, Eschrich S, Yeatman TJ, Sieber OM (2009) Metastasis-associated gene expression changes predict poor outcomes in patients with dukes stage B and C colorectal cancer. Clin Cancer Res 15:7642– 7651
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CONTACT:
ChipDX LLC
Dr. Ryan van Laar, 347-857-9415
Founder, CSO
[email protected]
KEYWORDS: United States North America New York
INDUSTRY KEYWORDS: Surgery Technology Internet Software Health Biotechnology Genetics Oncology Radiology Research Science
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