**8. Conclusion**

Based on the TCGA data, other studies have also proposed molecular signatures, namely the prognostic model "Classification of Ovarian Cancer" (CLOVAR), for which 23 genes involved in the platinum-induced DNA damage repair are predictive of treatment response among HGSOC patients [103]. Recently, the ARIEL2 clinical trial showed that the combination of *BRCA* mutational status with the degree of genome-wide loss of heterozygosity (LOH) in the tumor could predict the rucaparib treatment response. *BRCA*-mutated patients (germline or somatic) or *BRCA* wild-type with high LOH had longer PFS and clinical response to rucapa-

The concept of *BRCA*ness must be promptly clarified, as the associated phenotypes define a clinical subpopulation of EOC patients with common characteristics. These include high response rates to both first-line platinum-based treatment and to relapse therapies (including platinum based), long treatment-free intervals (even in recurrent disease), and improved OAS and include mainly serous tumors. The HRD phenotype (somatic or germline) might be complemented with other molecular defects, beyond *BRCA* deficiencies, which lead to an analogous clinical profile and be targeted for PARP inhibition [34, 105]. Commercial tests are already available, and multiple clinical trials (as ARIEL3 and NOVA) are ongoing to investigate PARP inhibition in *BRCA* wild-type patients and to identify a putative predictive

Although *BRCA*ness signature definition can provide valuable information regarding the magnitude of the benefit of targeted therapy, these biomarkers may not be unique for the determination of the likelihood of treatment sensitivity/resistance. To date, besides *BRCA* mutations and HRD status, platinum sensitivity remains the best biomarker of PARP inhibitor response. Platinum sensitivity correlates with HRD, and platinum-sensitive tumors are more responsive to PARP inhibitors than platinum-resistant tumors, whatever the genetic background [33, 78]. Therefore, perhaps the PARP inhibitors administration should be offered

Platinum-based compounds are among the most active and used cytotoxic agents in the clinical practice. They exert their biological effect by acting as alkylating agents by the ability to covalently bind to DNA, leading to the formation of intrastrand and interstrand DNA adducts that promote cell-cycle arrest and tumor cell apoptosis. The mechanisms underlying the development of chemoresistant phenotypes in OC are not fully recognized. Interindividual variation in platinum-drug response might be a major determinant for OC. This is suggested from the wide variability in the PFI and its direct association with a platinum response, as well as the finding that intrinsic resistance to these compounds, occur in up to a fifth of OC patients [106–109]. Mechanisms involved in platinum resistance are likely to be multifactorial although seems to be greatly determined by the platinum detoxification pathway and DNA

While platinum therapy is prescribed to achieve a target exposure based on renal function, the dose of taxanes is based on body surface area. Taxanes are microtubule-stabilizing drugs,

rib, when compared with *BRCA* wild-type and low LOH patients [104].

70 Ovarian Cancer - From Pathogenesis to Treatment

**7. Pharmacogenomics for future predictive marker definition**

to all OC patients that respond to platinum-based treatment.

damage repair ability [54, 108, 110–113].

signature.

Achieving an individualized therapeutic strategy will only be possible through the identification of feasible, validated, and reproducible biomarkers in the clinical practice that will allow the prediction of the likelihood of response to a given treatment. Biomarker validation is crucial, both in respect of predictive ability and sensitivity/specificity, and should be stated previously in the definition of treatment subgroups [106, 107, 118, 119].

Research in OC treatment evolution and improvement needs to focus on the identification of interindividual determinants, which is often associated with genetic polymorphisms to identify potential biomarkers and/or treatment targets. Circulating tumor cells or tumor nanovesicles (as exosomes) may help to identify the molecular targets. Consequently, the incorporation of molecular and genetic information into integrated clinical models may be a potential approach in order to define predictive nomograms. Pharmacogenomics will be important in clinical practice to improve efficacy, reduce toxicity, and predict nonresponders to several therapies, thus allowing for individualized treatment strategies.
