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Review
. 2015 Sep;26(9):1830-1837.
doi: 10.1093/annonc/mdv184. Epub 2015 Apr 21.

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine

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Free article
Review

A new generation of cancer genome diagnostics for routine clinical use: overcoming the roadblocks to personalized cancer medicine

J M Heuckmann et al. Ann Oncol. 2015 Sep.
Free article

Abstract

The identification of 'druggable' kinase gene alterations has revolutionized cancer treatment in the last decade by providing new and successfully targetable drug targets. Thus, genotyping tumors for matching the right patients with the right drugs have become a clinical routine. Today, advances in sequencing technology and computational genome analyses enable the discovery of a constantly growing number of genome alterations relevant for clinical decision making. As a consequence, several technological approaches have emerged in order to deal with these rapidly increasing demands for clinical cancer genome analyses. Here, we describe challenges on the path to the broad introduction of diagnostic cancer genome analyses and the technologies that can be applied to overcome them. We define three generations of molecular diagnostics that are in clinical use. The latest generation of these approaches involves deep and thus, highly sensitive sequencing of all therapeutically relevant types of genome alterations-mutations, copy number alterations and rearrangements/fusions-in a single assay. Such approaches therefore have substantial advantages (less time and less tissue required) over PCR-based methods that typically have to be combined with fluorescence in situ hybridization for detection of gene amplifications and fusions. Since these new technologies work reliably on routine diagnostic formalin-fixed, paraffin-embedded specimens, they can help expedite the broad introduction of personalized cancer therapy into the clinic by providing comprehensive, sensitive and accurate cancer genome diagnoses in 'real-time'.

Keywords: FFPE; cancer; cancer genome diagnostics; personalized medicine.

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