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Implementing personalized cancer genomics in clinical trials

Abstract

The recent surge in high-throughput sequencing of cancer genomes has supported an expanding molecular classification of cancer. These studies have identified putative predictive biomarkers signifying aberrant oncogene pathway activation and may provide a rationale for matching patients with molecularly targeted therapies in clinical trials. Here, we discuss some of the challenges of adapting these data for rare cancers or molecular subsets of certain cancers, which will require aligning the availability of investigational agents, rapid turnaround of clinical grade sequencing, molecular eligibility and reconsidering clinical trial design and end points.

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Figure 1: Development and application of biomarkers for oncology.
Figure 2: Strategies for next-generation sequencing in cancer.
Figure 3: Prospective clinical trial designs incorporating genomic sequencing.

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Acknowledgements

S.R. is supported by Pelotonia, the American Cancer Society (grant MRSG-12-194-01), the Landon-Foundation AACR Innovator Award for Personalized Cancer Medicine, and a Young Investigator Award from the Prostate Cancer Foundation. Special thanks to J. Bush for reading the manuscript and A. Marsell for administrative support.

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Correspondence to Sameek Roychowdhury.

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Glossary

Amplicon-based sequencing

The use of PCR to selectively amplify small genomic regions for sequencing.

Clinical Laboratory Improvements Amendment

(CLIA). A US regulatory standard that applies to all clinical laboratory testing.

Depth of coverage

Also known as sequencing depth; the number of times a genome position has been sequenced to ensure data accuracy.

Driver mutations

Mutations that are implicated in cancer biology and provide a growth advantage at some point during the development of cancer, causing positive selection for the mutation.

Next-generation sequencing

(NGS). Also referred to as high-throughput sequencing and massively parallel sequencing. Refers to technologies that parallelize DNA sequencing effectively to produce millions of sequences in a rapid and cost-effective manner.

Orthogonal platform

A second DNA sequencing technology used to confirm data obtained through next-generation sequencing.

Passenger mutations

Mutations that do not contribute to cancer biology and do not appear to provide a growth advantage, but are carried along with driver mutations.

Transcriptome sequencing

Also referred to as RNAseq or whole-transcriptome shotgun sequencing. The sequencing of cDNA generated from total RNA. Transcriptome sequencing can provide data on gene expression, alternatively spliced transcripts, non-coding RNA and gene fusions or rearrangements.

Whole-exome sequencing

Also referred to as targeted exome capture. The selective application of next-generation sequencing to the coding regions of the genome using complementary oligonucleotide probes that selectively hybridize and capture the desired genomic regions of interest. Whole-exome sequencing represents approximately 20,000 genes or a little more than 1% of the whole genome, and is therefore a cheaper strategy than whole-genome sequencing. Targeted gene sequencing can be completed for a shorter defined list of genes: for example, for 200 to 1,000 or more cancer-related genes.

Whole-genome sequencing

Complete sequencing of an organism's entire DNA sequence, including exons and non-coding genome regions.

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Simon, R., Roychowdhury, S. Implementing personalized cancer genomics in clinical trials. Nat Rev Drug Discov 12, 358–369 (2013). https://doi.org/10.1038/nrd3979

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