PARP inhibitors for BRCA1/2-mutated and sporadic ovarian cancer: current practice and future directions.

Poly(ADP-ribose) polymerase (PARP) inhibitors cause targeted tumour cell death in homologous recombination (HR)-deficient cancers, including BRCA-mutated tumours, by exploiting synthetic lethality. PARP inhibitors are being evaluated in late-stage clinical trials of ovarian cancer (OC). Recently, olaparib was the first PARP inhibitor approved in the European Union and United States for the treatment of advanced BRCA-mutated OC. This paper reviews the role of BRCA mutations for tumorigenesis and PARP inhibitor sensitivity, and summarises the clinical development of PARP inhibitors for the treatment of patients diagnosed with OC. Among the five key PARP inhibitors currently in clinical development, olaparib has undergone the most extensive clinical investigation. PARP inhibitors have demonstrated durable antitumour activity in BRCA-mutated advanced OC as a single agent in the treatment and maintenance setting, particularly in platinum-sensitive disease. PARP inhibitors are well tolerated; however, further careful assessment of moderate and late-onset toxicity is mandatory in the maintenance and adjuvant setting, respectively. PARP inhibitors are also being evaluated in combination with chemotherapeutic and novel targeted agents to potentiate antitumour activities. Current research is extending the use of PARP inhibitors beyond BRCA mutations to other sensitising molecular defects that result in HR-deficient cancer, and is defining an HR-deficiency signature. Trials are underway to determine whether such a signature will predict sensitivity to PARP inhibitors in women with sporadic OC.

Prediction of early death among patients enrolled in phase I trials: development and validation of a new model based on platelet count and albumin.

BACKGROUND: Selecting patients with 'sufficient life expectancy' for Phase I oncology trials remains challenging. The Royal Marsden Hospital Score (RMS) previously identified high-risk patients as those with ≥ 2 of the following: albumin <35 g l(-1); LDH > upper limit of normal; >2 metastatic sites. This study developed an alternative prognostic model, and compared its performance with that of the RMS. METHODS: The primary end point was the 90-day mortality rate. The new model was developed from the same database as RMS, but it used Chi-squared Automatic Interaction Detection (CHAID). The ROC characteristics of both methods were then validated in an independent database of 324 patients enrolled in European Organization on Research and Treatment of Cancer Phase I trials of cytotoxic agents between 2000 and 2009. RESULTS: The CHAID method identified high-risk patients as those with albumin <33 g l(-1) or ≥ 33 g l(-1), but platelet counts ≥ 400.000 mm(-3). In the validation data set, the rates of correctly classified patients were 0.79 vs 0.67 for the CHAID model and RMS, respectively. The negative predictive values (NPV) were similar for the CHAID model and RMS. CONCLUSION: The CHAID model and RMS provided a similarly high level of NPV, but the CHAID model gave a better accuracy in the validation set. Both CHAID model and RMS may improve the screening process in phase I trials.

Optimal treatment for relapsing ovarian cancer.

The cure rate for women with ovarian cancer has not significantly changed over the past 10 years. However, overall survival from relapsed disease has shown improvement despite a lack of increase in progression-free survival. There are now many therapeutic options for women with relapsed disease. Treatment strategies are still led by the description of relapse as platinum sensitive or resistant/refractory using somewhat arbitrary definitions. Now that there is increased choice of treatment, these definitions are becoming outdated. The current challenges in managing relapsed ovarian cancer are defining the optimal sequence of available drugs as well as timing of treatment for relapsed disease. The abundance of novel therapeutics and molecular targets has compounded the difficulty in identifying best practice but has undoubtedly provided an opportunity to improve the treatment we can offer our patients. The lack of validated biomarkers to inform patient selection remains an area of real need in ovarian cancer. Efforts should be made to increase the use of biomarkers in trial design to aid rational targeting of new therapies. In this review we discuss current practice in the treatment of relapsed ovarian cancer and highlight the most promising emerging therapeutics and strategies being employed in randomized clinical trials.