Systematic methods for profiling tumor genomic alterations remain underdeveloped, with current clinical profiling usually being confined to identification of limited numbers of oncogene point mutations. At present, there is no systematic technique for interrogating tumor samples in situ for a comprehensive panel of “actionable” cancer gene alterations—ie, alterations that might affect treatment decisions.
Wagle and colleagues from the Dana-Farber Cancer Institute, Boston, recently reported use of a targeted, massively parallel sequencing approach to detect genomic alterations in formalin-fixed, paraffin-embedded (FFPE) tumor samples. The technique used by these investigators is an adaptation of exon capture (a hybrid selection method that enriches for coding sequences prior to sequencing) and massively parallel sequencing methods that allowed multiple barcoded tumor DNA samples to be pooled into a single sequencing reaction while preserving deep sequencing of the targeted regions. This approach simultaneously identifies mutations and chromosomal copy-number alterations in tumor material.
Impact on Personalized Medicine
In this proof-of-concept study, 137 potentially actionable genes (encoding approximately 400,000 coding bases) known to undergo somatic alterations in cancer were sequenced from 10 pooled FFPE tumor DNA samples. A nearly 400-fold mean sequence coverage was achieved, and single-nucleotide variants as well as small insertions/deletions and chromosomal copy-number alterations were simultaneously detected with high accuracy compared with other methods currently in clinical use (eg, OncoMap, a mass-spectrometric genotyping technology that interrogates more than 400 known mutations in 33 cancer genes). Biologically or clinically meaningful alterations were detected in all 10 FFPE samples, including 2 samples that contained only 10% to 20% tumor cells.
As the authors stated, “[T]argeted, massively parallel sequencing offers a promising method to detect genetic alterations across a large panel of cancer genes…. This approach may ultimately impact clinical practice by offering a categorical means to identify genetic changes affecting genes and pathways targeted by existing and emerging drugs, thereby speeding the advent of personalized cancer medicine.” ■