Ploidy-Seq: inferring mutational chronology by sequencing polyploid tumor subpopulations

Genome Medicine
Ankit MalhotraNicholas Navin

Abstract

Human cancers are frequently polyploid, containing multiple aneuploid subpopulations that differ in total DNA content. In this study we exploit this property to reconstruct evolutionary histories, by assuming that mutational complexity increases with time. We developed an experimental method called Ploidy-Seq that uses flow-sorting to isolate and enrich subpopulations with different ploidy prior to next-generation genome sequencing. We applied Ploidy-Seq to a patient with a triple-negative (ER-/PR-/HER2-) ductal carcinoma and performed whole-genome sequencing to trace the evolution of point mutations, indels, copy number aberrations, and structural variants in three clonal subpopulations during tumor growth. Our data show that few mutations (8% to 22%) were shared between all three subpopulations, and that the most aggressive clones comprised a minority of the tumor mass. We expect that Ploidy-Seq will have broad applications for delineating clonal diversity and investigating genome evolution in many human cancers.

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Datasets Mentioned

BETA
SRP013572

Methods Mentioned

BETA
exome sequencing
single cell sequencing
FACS
PCR
electrophoresis
Illumina sequencing
SGA
genotyping
Ploidy-Seq
neddylation

Software Mentioned

GATK Unified Genotyper
PurBayes R
Annovar
sga
BEDTools
GATK SelectVariants
BLAT
SW
cBio portal for Cancer Genomics ( )
R package

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