205These results suggest that gene expression profi ling of breast biopsies may become
a valuable method for adequately characterizing and choosing treatment modality
for patients with breast cancer.
Gene expression microarray technology is helpful in all phases of the discovery,
development and subsequent use of new cancer therapeutics, e.g., the identifi cation
of potential targets for molecular therapeutics. It can be used to identify molecular
biomarkers for proof of concept studies, pharmacodynamic endpoints and prog-
nostic markers for predicting outcome and patient selection. Expression profi ling
can be used alongside gene knockout or knockdown methods such as RNA
interference.
Catalog of Cancer Genes for Personalized Therapy
Personalized medicine for cancer will eventually require a comprehensive catalog
of cancer genes to enable physicians to select the best combination therapy for each
patient based on the cellular pathways disrupted in their tumor and the specifi c
nature of the disruptions. Such a catalog will also guide therapeutic development by
identifying druggable targets.
Although a few cancer genes are mutated in a high proportion of tumors of a
given type (>20 %), most are mutated at intermediate frequencies (2–20 %). To
explore the feasibility of creating a comprehensive catalog of cancer genes,
researchers at Broad Institute (Cambridge, MA) analyzed somatic point mutations
in exome sequences from ~5,000 human cancers and their matched normal-tissue
samples across 21 cancer types (Lawrence et al. 2014 ). Using the MutSig tool,
which weighs mutational burden as compared to the background mutation rate,
mutational clustering, and enrichment of mutations in conserved regions, the
researchers searched for candidate cancer genes. After fi ltering the data, they found
3 million SNVs, among other mutations, which are almost all known cancer genes
in these tumor types. Their analysis also identifi ed 33 genes that were not previ-
ously known to be signifi cantly mutated in cancer, including genes related to prolif-
eration, apoptosis, genome stability, chromatin regulation, immune evasion, RNA
processing and protein homeostasis.
By combining the 22 MutSig lists, the researchers developed Cancer5000 set of
254 genes. Down-sampling analysis indicates that larger sample sizes will reveal
many more genes mutated at clinically important frequencies. Many new candidate
cancer genes remain to be discovered beyond those in the current Cancer5000 set.
Researchers estimate that near-saturation may be achieved with 600–5,000 samples
per tumor type, depending on background mutation frequency. The results may
help to guide the next stage of cancer genomics. A comprehensive cancer catalog,
would not only guide personalized cancer treatment, but also improve our under-
standing of the mechanisms at play in cancer as well as spur the development of
new therapies.
Impact of Molecular Diagnostics on the Management of Cancer