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Cancer genome-sequencing study design

Key Points

  • This article focuses on the aims, methodological requisites and study designs of cancer genome-sequencing studies. Thus far, most cancer genome-sequencing studies have had the aims of discovering driver mutations, identifying somatic mutational signatures, characterizing clonal evolution and/or advancing personalized medicine.

  • Key aspects of second-generation cancer genome-sequencing study design include full sequencing of the matched normal genome of the cancer type, at least 30-fold redundant sequence coverage for the detection of inherited and somatic single-nucleotide variation and verification resequencing to confirm the somatic status of acquired mutations.

  • Single-patient studies are hypothesis-generating and have the potential to inform clinical practice, but they do not allow for generalization of findings. The discovery cohort is a group of cancers of the same type, or subtype, subject to second-generation sequencing. Discovery cohort studies have the potential to detect recurrent somatic mutations of genes and pathways.

  • Multi-ome discovery cohorts use second-generation technology to sequence an assortment of genomes, exomes and/or transcriptomes in a group of cancers of the same type or subtype.

Abstract

Discoveries from cancer genome sequencing have the potential to translate into advances in cancer prevention, diagnostics, prognostics, treatment and basic biology. Given the diversity of downstream applications, cancer genome-sequencing studies need to be designed to best fulfil specific aims. Knowledge of second-generation cancer genome-sequencing study design also facilitates assessment of the validity and importance of the rapidly growing number of published studies. In this Review, we focus on the practical application of second-generation sequencing technology (also known as next-generation sequencing) to cancer genomics and discuss how aspects of study design and methodological considerations — such as the size and composition of the discovery cohort — can be tailored to serve specific research aims.

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Figure 1: Cancer genome second-generation-sequencing study designs.
Figure 2: The integration of transcriptome and epigenome with whole-genome sequencing.

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Acknowledgements

J.C.M. thanks the Canadian Institutes of Health Research and the Michael Smith Foundation for Health Research for their support. M.A.M. is the University of British Columbia, Canada Research Chair in Genome Science.

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Correspondence to Marco A. Marra.

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Second-generation sequencing cancer genomics study aims (PDF 155 kb)

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Glossary

Driver mutations

Somatic mutations that have a role in creating, controlling and/or directing some aspect of the cancer phenotype.

Kataegis

From the Greek meaning 'thunderstorm', this refers to clusters of somatic single-nucleotide variants that often colocalize with somatic structural variants.

Chromothripsis

From the Greek meaning 'chromosome shattering', this refers to a single event of genome shattering and reassembly that results in complex somatic structural variations characterized by oscillating copy number and tens to hundreds of rearrangements that localize to one or a few chromosomes.

Redundant sequence coverage

The total number of bases sequenced divided by the total number of bases in the haploid genome.

B allele frequencies

Frequencies equal to B/(A+B), where A is the count for the reference nucleotide at an inherited single-nucleotide polymorphism (SNP) position, and B is the count for the alternate nucleotide at that same SNP position.

Paired-end reads

Sequencing reads from each end of the same DNA molecule. Knowing the sequence of both reads and the length of the DNA molecule improves mapping to a reference sequence, de novo assembly and detecting structural variations.

Chimeric genes

A combination of segments of two or more genes that forms a new gene.

Split reads

Sequencing reads that align to non-contiguous spans of the reference sequence owing to somatic structural variation.

Mass-spectrometric genotyping

A method that generates locus-specific amplicons followed by primer extension that incorporates mass-modified dideoxynucleotides at the single-nucleotide polymorphism position. A mass spectrometer then measures the differential mass of the products.

Multi-ome discovery cohort

A cohort of cancer genomes, exomes and/or transcriptomes; more than one omic measurement per sample is not necessary.

Allelic imbalances

Unequal transcript levels of the alleles of a gene.

Integration omics

Examining how somatic mutation or deregulation of a genome, transcriptome and/or epigenome converge on a pathway, process or gene; more than one omic measurement per sample is not necessary. For example, gene inactivation through single-nucleotide variants or epigenomic silencing.

Interaction omics

Examining how the somatic mutation or deregulation of the genome, transcriptome and/or epigenome affect one another; more than one omic measurement per sample is ideal. For example, somatic copy number variants can have effects on transcript levels.

Custom capture

Hybridization or amplification of selected regions of the genome to specifically capture loci for second-generation sequencing.

Ultra-deep second-generation resequencing

Greater than 100-fold redundant sequence coverage of a targeted selection of somatic mutations.

Multi-region sequencing

Sequencing of distinct regions of the same solid tumour, this allows for the examination of intra-tumour heterogeneity and clonal evolution.

Clinically actionable drug targets

Biological molecules or processes that can be targeted by an existing or experimental drug.

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Mwenifumbo, J., Marra, M. Cancer genome-sequencing study design. Nat Rev Genet 14, 321–332 (2013). https://doi.org/10.1038/nrg3445

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