Cancer classification algorithm

Identify critical cancer biomarkers from a single clinical sample

 

  1. Reference based method for gene biomarker discovery
  2. Classify cancer type using gene expression data
  3. Diagnosis, prognosis from a single clinical sample
  4. Novel algorithm requires no prior knowledge to use

 
Licensing Manager: Tyler Scherr, Ph.D.
tyler.scherr@unmc.edu or 402-559-2140
 

Description

Identify critical cancer biomarkers from a single clinical sample

 
A new and powerful algorithm could help in the diagnosis and prognosis of any cancer.
 
The discovery of cancer-specific gene biomarkers can significantly improve diagnosis and enable personalized therapy. Unlike current cancer screening strategies that are largely based on imaging techniques, this algorithm represents a purely data-driven method to identify biomarkers.
 
Unlike other gene discovery algorithms under development, this technology requires relatively less processing power, yet provides true single-sample diagnostic potential. Plus, the novel software is easy to use, and does not require medical knowledge for the user.
 
As a proof-of-concept, the inventors have used the algorithm to positively identify specific biomarkers in colorectal, stomach and lung cancer samples. However, the algorithm could be further trained to theoretically identify biomarkers for many different diseases.
 
Contact Tyler Scherr, Ph.D., at tyler.scherr@unmc.edu or 402-559-2140 to discuss licensing opportunities.
 

Additional Information

 

Intellectual Property

  1. Patent pending