A novel genomic signature predicting FDG uptake in diverse metastatic tumors.

ABSTRACT:

Background

Building a universal genomic signature predicting the intensity of FDG uptake in diverse metastatic tumors may allow us to understand better the biological processes underlying this phenomenon and their requirements of glucose uptake.

Methods

A balanced training set (n = 71) of metastatic tumors including some of the most frequent histologies, with matched PET/CT quantification measurements and whole human genome gene expression microarrays, was used to build the signature. Selection of microarray features was carried out exclusively on the basis of their strong association with FDG uptake (as measured by SUVmean35) by means of univariate linear regression. A thorough bioinformatics study of these genes was performed, and multivariable models were built by fitting

SUBMITTER: Crespo-Jara A 

PROVIDER: S-EPMC5773462 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature