Tracking Cancer Genetic Evolution using OncoTrack

Asoke K. Talukder, Mahima Agarwal, Kenneth Buetow, Patrice P. Denèfle

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


It is difficult for existing methods to quantify, and track the constant evolution of cancers due to high heterogeneity of mutations. However, structural variations associated with nucleotide number changes show repeatable patterns in localized regions of the genome. Here we introduce SPKMG, which generalizes nucleotide number based properties of genes, in statistical terms, at the genome-wide scale. It is measured from the normalized amount of aligned NGS reads in exonic regions of a gene. SPKMG values are calculated within OncoTrack. SPKMG values being continuous numeric variables provide a statistical metric to track DNA level changes. We show that SPKMG measures of cancer DNA show a normative pattern at the genome-wide scale. The analysis leads to the discovery of core cancer genes and also provides novel dynamic insights into the stage of cancer, including cancer development, progression, and metastasis. This technique will allow exome data to also be used for quantitative LOH/CNV analysis for tracking tumour progression and evolution with a higher efficiency.

Original languageEnglish (US)
Article number29647
JournalScientific reports
StatePublished - Jul 14 2016

ASJC Scopus subject areas

  • General


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