Analysis of cancer metabolism with high-throughput technologies.

ABSTRACT:

Background

Recent advances in genomics and proteomics have allowed us to study the nuances of the Warburg effect--a long-standing puzzle in cancer energy metabolism--at an unprecedented level of detail. While modern next-generation sequencing technologies are extremely powerful, the lack of appropriate data analysis tools makes this study difficult. To meet this challenge, we developed a novel application for comparative analysis of gene expression and visualization of RNA-Seq data.

Results

We analyzed two biological samples (normal human brain tissue and human cancer cell lines) with high-energy, metabolic requirements. We calculated digital topology and the copy number of every expressed transcript. We observed subtle but remarkable qualitative and quantitative differences

SUBMITTER: Markovets AA 

PROVIDER: S-EPMC3236851 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature