MAXX (Mutation Allelic Expression Extractor) Software

Case ID:
UA20-157
Invention:

This technology comprises a program to mathematically identify complex mutations in genes in order to obtain more meaningful information from tumor sequencing data than would be available from single nucleotide variations. This was done to better understand the impact of a given mutation within cancer, thus RNA-sequencing data was used to categorize mutations based on their allelic expression. The development of MAXX is highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions. Therefore, differentiating mutations based on their mutant allele expression via MAXX represents a means to parse somatic variants in tumor genomes to help elucidate a gene’s respective role in cancer.

Background:
Cancer is a complex disease, initiated by DNA alterations within genes that control multiple hallmarks of tumori-genesis, such as deregulated cell growth and genomic instability. Genetic alterations are essential for cancer initiation and progression. A problem in cancer biology exists in differentiating mutations that drive the tumor phenotype from mutations that do not affect tumor fitness remains a fundamental challenge. The present technology is an effective software program that can mathematically identify complex mutations to analyze and interpret tumor sequencing data to better understand genetic influences on cancer.

Applications:

  • Software to examine genetic alternations
  • Mathematically identify mutations in genes

Advantages:

  • Highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions
  • Results from MAXX show that mutations can be separated into three groups based on their expression of the mutant allele
Patent Information:
Contact For More Information:
Lewis Humphreys
Licensing Manager, Eller College of Mngmt & OTT
The University of Arizona
lewish@tla.arizona.edu
Lead Inventor(s):
Adam Grant
Keywords: