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hypothesis that these tumors have continued dependence on such 3′UTR lesions,
and that direct targeting may be a viable future treatment approach.
Poly(ADP-ribose)polymerase (PARP) inhibitors have shown promising activity
in patients with BRCA1/2 mutation-associated ovarian and breast cancers. Olaparib
(AstraZeneca), a PARP inhibitor is, in two phase III trials for ovarian cancer.
Understanding more about the molecular abnormalities involved in BRCA-like
tumors, exploring novel therapeutic trial strategies and drug combinations, and
defi ning potential predictive biomarkers, is critical to rapidly advancing the fi eld of
PARP inhibitor therapy and improve clinical outcomes (Lee et al. 2014 ).
BRACAnalysis (Myriad Genetics) is being used as a companion test for olaparib to
pick out ovarian cancer patients who are best responders to olaparib.
Prognosis of Ovarian Cancer Based on CLOVAR
The Cancer Genome Atlas catalog has been used to develop a prognostic model of
HGS-OvCa classifi cation called “Classifi cation of Ovarian Cancer” (CLOVAR),
which is based on subtype and survival gene expression profi les (Verhaak et al.
2013 ). Rather than relying on the 193 genes previously used in the signature of
survival, the researchers focused on a smaller set, choosing the 100 genes whose
expression were the most or least indicative of good prognosis from the full 481
TCGA HGS-OvCa sample set. Similarly, the researchers then revamped the subtype
gene expression signature by narrowing the initial list of 800 genes down to 100
genes. Applied to a validation set, this new survival signature could stratify HGS-
OvCa samples into a good prognosis group and a poor prognosis group. The worst
outcome group, accounting for 23 % of all cases, was associated with a median
survival of 23 months and a platinum resistance rate of 63 %, versus a median sur-
vival of 46 months and platinum resistance rate of 23 % in other cases. Associating
the outcome prediction model with BRCA1/BRCA2 mutation status, residual dis-
ease after surgery, and disease stage further optimized outcome classifi cation. The
results of this study suggest that combining LOVAR survival, immunoreactivity,
and mesenchymal scores with BRCA1/BRCA2 mutation status provides optimal
outcome predictions. The spectrum of outcomes observed in this study and their
association with CLOVAR signatures suggests variations in underlying tumor biol-
ogy. The association uncovered between the CLOVAR survival, immunoreactive,
and mesenchymal gene signature scores suggests an active role for the stromal
tumor microenvironment in the pathogenesis of HGS-OvCa and may indicate pos-
sible targets for cancer therapies. An improved understanding of ovarian carcinoma
development may ultimately lead to more effective treatments. Prospective valida-
tion of the CLOVAR model in the context of additional prognostic variables such as
BRCA mutation status, age, grade, and residual disease may provide a rationale for
optimal combination of patient and treatment regimens. A prospective study would
be most revealing when assessing the predictive capacities of the CLOVAR signa-
tures in conjunction with other prognostic factors.
10 Personalized Therapy of Cancer