Dataset Information

Single-cell mutational profiling and clonal phylogeny in cancer.

ABSTRACT: The development of cancer is a dynamic evolutionary process in which intraclonal, genetic diversity provides a substrate for clonal selection and a source of therapeutic escape. The complexity and topography of intraclonal genetic architectures have major implications for biopsy-based prognosis and for targeted therapy. High-depth, next-generation sequencing (NGS) efficiently captures the mutational load of individual tumors or biopsies. But, being a snapshot portrait of total DNA, it disguises the fundamental features of subclonal variegation of genetic lesions and of clonal phylogeny. Single-cell genetic profiling provides a potential resolution to this problem, but methods developed to date all have limitations. We present a novel solution to this challenge using leukemic cells with known mutational spectra as a tractable model. DNA from flow-sorted single cells is screened using multiplex targeted Q-PCR within a microfluidic platform allowing unbiased single-cell selection, high-throughput, and comprehensive analysis for all main varieties of genetic abnormalities: chimeric gene fusions, copy number alterations, and single-nucleotide variants. We show, in this proof-of-principle study, that the method has a low error rate and can provide detailed subclonal genetic architectures and phylogenies.

SUBMITTER: Potter NE

PROVIDER: S-EPMC3847780 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Single-cell mutational profiling and clonal phylogeny in cancer.

Potter Nicola E NE Ermini Luca L Papaemmanuil Elli E Cazzaniga Giovanni G Vijayaraghavan Gowri G Titley Ian I Ford Anthony A Campbell Peter P Kearney Lyndal L Greaves Mel M

Genome research 20130920 12

The development of cancer is a dynamic evolutionary process in which intraclonal, genetic diversity provides a substrate for clonal selection and a source of therapeutic escape. The complexity and topography of intraclonal genetic architectures have major implications for biopsy-based prognosis and for targeted therapy. High-depth, next-generation sequencing (NGS) efficiently captures the mutational load of individual tumors or biopsies. But, being a snapshot portrait of total DNA, it disguises ...[more]

PMID: 24056532

Similar Datasets

Project description:BackgroundSynchronous tumors can be independent primary tumors or a primary-metastatic (clonal) pair, which may have clinical implications. Mutational profiling of tumor DNA is increasingly common in the clinic. We investigated whether mutational profiling can distinguish independent from clonal tumors in breast and other cancers, using a carefully defined test based on the Clonal Likelihood Score (CLS = 100 x # shared high confidence (HC) mutations/ # total HC mutations).MethodsStatistical properties of a formal test using the CLS were investigated. A high CLS is evidence in favor of clonality; the test is implemented as a one-sided binomial test of proportions. Test parameters were empirically determined using 16,422 independent breast tumor pairs and 15 primary-metastatic tumor pairs from 10 cancer types using The Cancer Genome Atlas.ResultsWe validated performance of the test with its established parameters, using five published data sets comprising 15,758 known independent tumor pairs (maximum CLS = 4.1%, minimum p-value = 0.48) and 283 known tumor clonal pairs (minimum CLS 13%, maximum p-value <0.01), across renal cell, testicular, and colorectal cancer. The CLS test correctly classified all validation samples but one, which it appears may have been incorrectly classified in the published data. As proof-of-concept we then applied the CLS test to two new cases of invasive synchronous bilateral breast cancer at our institution, each with one hormone receptor positive (ER+/PR+/HER2-) lobular and one triple negative ductal carcinoma. High confidence mutations were identified by exome sequencing and results were validated using deep targeted sequencing. The first tumor pair had CLS of 81% (p-value < 10-15), supporting clonality. In the second pair, no common mutations of 184 variants were validated (p-value >0.99), supporting independence. A plausible molecular mechanism for the shift from hormone receptor positive to triple negative was identified in the clonal pair.ConclusionWe have developed the statistical properties of a carefully defined Clonal Likelihood Score test from mutational profiling of tumor DNA. Under identified conditions, the test appears to reliably distinguish between synchronous tumors of clonal and of independent origin in several cancer types. This approach may have scientific and clinical utility.

Dataset Information

Single-cell mutational profiling and clonal phylogeny in cancer.

Publications

Single-cell mutational profiling and clonal phylogeny in cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets