Limited clinical activity of palbociclib and ribociclib monotherapy in advanced cancers with cyclin D-CDK4/6 pathway alterations in the Dutch DRUP and Australian MoST trials

The Dutch Drug Rediscovery Protocol (DRUP) and the Australian Cancer Molecular Screening and Therapeutic (MoST) Program are similar nonrandomized, multidrug, pan-cancer trial platforms that aim to identify signals of clinical activity of molecularly matched targeted therapies or immunotherapies outside their approved indications. Here, we report results for advanced or metastatic cancer patients with tumors harboring cyclin D-CDK4/6 pathway alterations treated with CDK4/6 inhibitors palbociclib or ribociclib. We included adult patients that had therapy-refractory solid malignancies with the following alterations: amplifications of CDK4, CDK6, CCND1, CCND2 or CCND3, or complete loss of CDKN2A or SMARCA4. Within MoST, all patients were treated with palbociclib, whereas in DRUP, palbociclib and ribociclib were assigned to different cohorts (defined by tumor type and alteration). The primary endpoint for this combined analysis was clinical benefit, defined as confirmed objective response or stable disease ≥16 weeks. We treated 139 patients with a broad variety of tumor types; 116 with palbociclib and 23 with ribociclib. In 112 evaluable patients, the objective response rate was 0% and clinical benefit rate at 16 weeks was 15%. Median progression-free survival was 4 months (95% CI: 3-5 months), and median overall survival 5 months (95% CI: 4-6 months). In conclusion, only limited clinical activity of palbociclib and ribociclib monotherapy in patients with pretreated cancers harboring cyclin D-CDK4/6 pathway alterations was observed. Our findings indicate that monotherapy use of palbociclib or ribociclib is not recommended and that merging data of two similar precision oncology trials is feasible.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Mechanisms of vascular dysfunction in the interleukin-10–deficient murine model of preeclampsia indicate nitric oxide dysregulation

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Benign breast disease increases breast cancer risk independent of underlying familial risk profile: Findings from a Prospective Family Study Cohort

Benign breast disease (BBD) is an established breast cancer (BC) risk factor, but it is unclear whether the magnitude of the association applies to women at familial or genetic risk. This information is needed to improve BC risk assessment in clinical settings. Using the Prospective Family Study Cohort, we used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of BBD with BC risk. We also examined whether the association with BBD differed by underlying familial risk profile (FRP), calculated using absolute risk estimates from the Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model. During 176,756 person-years of follow-up (median: 10.9 years, maximum: 23.7) of 17,154 women unaffected with BC at baseline, we observed 968 incident cases of BC. A total of 4,704 (27%) women reported a history of BBD diagnosis at baseline. A history of BBD was associated with a greater risk of BC: HR = 1.31 (95% CI: 1.14–1.50), and did not differ by underlying FRP, with HRs of 1.35 (95% CI: 1.11–1.65), 1.26 (95% CI: 1.00–1.60), and 1.40 (95% CI: 1.01–1.93), for categories of full-lifetime BOADICEA score <20%, 20 to <35%, ≥35%, respectively. There was no difference in the association for women with BRCA1 mutations (HR: 1.64; 95% CI: 1.04–2.58), women with BRCA2 mutations (HR: 1.34; 95% CI: 0.78–2.3) or for women without a known BRCA1 or BRCA2 mutation (HR: 1.31; 95% CI: 1.13–1.53) (p_interaction = 0.95). Women with a history of BBD have an increased risk of BC that is independent of, and multiplies, their underlying familial and genetic risk.