We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Expands Web-based Online Analysis Modules for Research and Clinical Access

Expands Web-based Online Analysis Modules for Research and Clinical Access

Expands Web-based Online Analysis Modules for Research and Clinical Access

Expands Web-based Online Analysis Modules for Research and Clinical Access

Read time:

Want a FREE PDF version of This News Story?

Complete the form below and we will email you a PDF version of "Expands Web-based Online Analysis Modules for Research and Clinical Access"

First Name*
Last Name*
Email Address*
Company Type*
Job Function*
Would you like to receive further email communication from Technology Networks?

Technology Networks Ltd. needs the contact information you provide to us to contact you about our products and services. You may unsubscribe from these communications at any time. For information on how to unsubscribe, as well as our privacy practices and commitment to protecting your privacy, check out our Privacy Policy

ChipDX LLC, has discovered a gene expression signature present in the cells of early-stage breast tumors that indicates the chance of the tumor recurring within 10 years. This genomic information was used to develop a prognostic test, BreastGeneDX, which ChipDX plans to have FDA-cleared for clinician access via an online analysis system.

This personalized assessment of recurrence risk may assist in making informed decisions about monitoring and treatment options that are especially important for patients diagnosed with early-stage breast cancer.

In a peer-reviewed study published in the Journal of Molecular Diagnostics (JMD), ChipDX analyzed whole-genome profiles from 477 breast cancer patients. Using a novel multivariate approach they indentified 200 genes associated with outcome that is independent to standard prognostic such as age, tumor grade, and size.

The genes were used to train a predictive algorithm to classify future patients as high or low risk of recurrence. To demonstrate the significance and reproducibility of the test, a retrospective analysis of genomic and survival data from an additional 1,016 patients was performed.

“One in eight U.S. women are diagnosed with breast cancer during their lifetime, last year in the U.S. alone 40,000 women died of this disease despite an increase in early detection and growing treatment options,” said Ryan van Laar, PhD, ChipDX Founder and Chief Scientific Officer. “New methods for identifying patients at high risk of relapse like BreastGeneDX will help clinicians reduce this staggering death toll by tailoring treatment to the individual patient. We’re determined to pursue options for making this technology affordable, reliable, and accessible worldwide.”

The BreastGeneDX test was designed for use with the Affymetrix GeneChip® Microarray Instrument System for in vitro diagnostic (IVD) and is currently available online for research use only (RUO). Datasets used in the development and validation study were generated using GeneChip® Human Genome U133A and HG-U133 Plus 2.0 arrays.

“We are thrilled to see ChipDX’ progress in developing signatures for the most common cancers and expanding its unique online analysis system to create access to such informative and actionable information,” said Kevin Cannon, PhD, Affymetrix Vice President of Strategic Marketing for Gene Expression Applications. “The ChipDX approach to molecular diagnostics is futuristic and will continue to move our applications into clinical markets, increasing the potential to save lives by improving treatment decisions.”

In the study, a multivariate analysis of the independent validation series results showed the BreastGeneDX to be the strongest predictor of outcome in each validation series, compared to other methods of predicting breast cancer prognosis.

In untreated node-negative patients, 88 percent sensitivity and 44 percent specificity for 10-year recurrence-free survival was observed. Positive and negative predictive values were 32 percent and 92 percent, respectively.

Patients with the ‘high-risk’ 200-gene profile, appear to significantly benefit from systemic adjuvant therapy, compared to those with the same genomic profile who did not receive treatment.