A Phase Ib/II study of IGF-neutralising antibody xentuzumab with enzalutamide in metastatic castration-resistant prostate cancer.

BACKGROUND: This multicentre, open-label, Phase Ib/II trial evaluated the insulin-like growth factor (IGF) 1/2 neutralising antibody xentuzumab plus enzalutamide in metastatic castrate-resistant prostate cancer (mCRPC). METHODS: The trial included Phase Ib escalation and expansion parts and a randomised Phase II part versus enzalutamide alone. Primary endpoints in the Phase Ib escalation, Phase Ib expansion and Phase II parts were maximum tolerated dose (MTD), prostate-specific antigen response and investigator-assessed progression-free survival (PFS), respectively. Patients in the Phase Ib escalation and Phase II parts had progressed on/after docetaxel/abiraterone. RESULTS: In the Phase Ib escalation (n = 10), no dose-limiting toxicities were reported, and xentuzumab 1000 mg weekly plus enzalutamide 160 mg daily (Xe1000 + En160) was defined as the MTD and recommended Phase 2 dose. In the Phase Ib expansion (n = 24), median PFS was 8.2 months, and one patient had a confirmed, long-term response. In Phase II (n = 86), median PFS for the Xe1000 + En160 and En160 arms was 7.4 and 6.2 months, respectively. Subgroup analysis suggested trends towards benefit with Xe1000 + En160 in patients whose tumours had high levels of IGF1 mRNA or PTEN protein. Overall, the combination was well tolerated. CONCLUSIONS: Xentuzumab plus enzalutamide was tolerable but lacked antitumour activity in unselected patients with mCRPC. CLINICAL TRIAL REGISTRATION: EudraCT number 2013-004011-41.

A phase Ib/II study of xentuzumab, an IGF-neutralising antibody, combined with exemestane and everolimus in hormone receptor-positive, HER2-negative locally advanced/metastatic breast cancer.

BACKGROUND: Xentuzumab-a humanised IgG1 monoclonal antibody-binds IGF-1 and IGF-2, inhibiting their growth-promoting signalling and suppressing AKT activation by everolimus. This phase Ib/II exploratory trial evaluated xentuzumab plus everolimus and exemestane in hormone receptor-positive, locally advanced and/or metastatic breast cancer (LA/MBC). METHODS: Patients with hormone receptor-positive/HER2-negative LA/MBC resistant to non-steroidal aromatase inhibitors were enrolled. Maximum tolerated dose (MTD) and recommended phase II dose (RP2D) of xentuzumab/everolimus/exemestane were determined in phase I (single-arm, dose-escalation). In phase II (open-label), patients were randomised 1:1 to the RP2D of xentuzumab/everolimus/exemestane or everolimus/exemestane alone. Randomisation was stratified by the presence of visceral metastases. Primary endpoint was progression-free survival (PFS). RESULTS: MTD was determined as xentuzumab 1000 mg weekly plus everolimus 10 mg/day and exemestane 25 mg/day. A total of 140 patients were enrolled in phase II (70 to each arm). Further recruitment was stopped following an unfavourable benefit-risk assessment by the internal Data Monitoring Committee appointed by the sponsor. Xentuzumab was discontinued; patients could receive everolimus/exemestane if clinically indicated. Median PFS was 7.3 months (95% CI 3.3-not calculable) in the xentuzumab/everolimus/exemestane group and 5.6 months (3.7-9.1) in the everolimus/exemestane group (hazard ratio 0.97, 95% CI 0.57-1.65; P = 0.9057). In a pre-specified subgroup of patients without visceral metastases at screening, xentuzumab/everolimus/exemestane showed evidence of PFS benefit versus everolimus/exemestane (hazard ratio 0.21 [0.05-0.98]; P = 0.0293). Most common any-cause adverse events in phase II were diarrhoea (29 [41.4%] in the xentuzumab/everolimus/exemestane group versus 20 [29.0%] in the everolimus/exemestane group), mucosal inflammation (27 [38.6%] versus 21 [30.4%]), stomatitis (24 [34.3%] versus 24 [34.8%]), and asthenia (21 [30.0%] versus 24 [34.8%]). CONCLUSIONS: Addition of xentuzumab to everolimus/exemestane did not improve PFS in the overall population, leading to early discontinuation of the trial. Evidence of PFS benefit was observed in patients without visceral metastases when treated with xentuzumab/everolimus/exemestane, leading to initiation of the phase II XENERA™-1 trial (NCT03659136). TRIAL REGISTRATION: ClinicalTrials.gov, NCT02123823 . Prospectively registered, 8 March 2013.

Mutational profiles of metastatic colorectal cancer treated with FOLFIRI plus cetuximab or bevacizumab before and after secondary resection (AIO KRK 0306; FIRE-3).

Secondary resection of metastases is recommended in metastatic colorectal cancer (mCRC). Data describing changes in mutational profiles of corresponding primary tumor and metastatic tissue after conversion treatment are limited. Next generation sequencing was performed in formalin-fixed mCRC samples from patients of the FIRE-3 trial (FOLFIRI plus cetuximab or bevacizumab) before treatment start (baseline) and after secondary resection of metastases (post baseline). Changes of mutational profiles and tumor mutational burden (TMB) were assessed within a post-hoc analysis. Median overall survival (OS), progression-free survival (PFS) and objective response rate (ORR) were compared between treatment arms. Paired tumor samples were obtained from 25 patients (19 RAS wild-type, 6 RAS mutant by pyrosequencing). ORR (92.0% vs 58.0%) and OS (60.8 vs 35.4 months, hazard ratio = 0.39 [95% CI 0.14-1.12], P = .08) were higher for patients receiving cetuximab. After conversion therapy, 56 alterations (42 in the cetuximab and 14 in the bevacizumab arm) were newly observed in 18 patients (9 each treated with cetuximab or bevacizumab). Gains (n = 21) and losses (n = 21) of alterations occurred during cetuximab-based treatment, while mainly gains of alterations occurred during bevacizumab (n = 10). Three of nine patients treated with cetuximab that presented a change of mutational profiles, developed resistance to cetuximab. Mutational profiles were largely comparable before and after treatment with anti-VEGF or anti-EGFR directed monoclonal antibodies after secondary resection. Mutations associated with resistance to anti-EGFR antibodies were observed in only one-third of patients.

Midazolam microdosing applied in early clinical development for drug-drug interaction assessment.

AIMS: We aimed to incorporate a pharmacologically inactive midazolam microdose into early clinical studies for the assessment of CYP3A drug-drug interaction liability. METHODS: Three early clinical studies were conducted with substances (Compounds A, B and C) which gave positive CYP3A perpetrator signals in vitro. A 75 µg dose of midazolam was administered alone (baseline CYP3A activity) followed by administration with the highest dose groups tested for each compound on Day 1/3 and Day 14 or Day 17. Midazolam exposure (AUC0-∞ , Cmax ) during administration with the test substances was compared to baseline data via an analysis of variance on log-transformed data. Partial AUC2-4 ratios were also compared to AUC0-∞ ratios using linear regression on log-transformed data. RESULTS: Test compound Cmax values exceeded relevant thresholds for drug-drug interaction liability. Midazolam concentrations were quantifiable over the full profiles for all subjects in all studies. Point estimates of the midazolam AUC0-∞ gMean ratios ranged from 108.3 to 127.1% for Compound A, from 93.3 to 114.5% for Compound B, and from 92.0 to 96.7% for the two highest dose groups of Compound C. Cmax gMean ratios were in the same range. Thus, no relevant drug-drug interactions were evident, based on the results of midazolam microdosing. AUC2-4 ratios from these studies were comparable to the AUC0-∞ ratios. CONCLUSION: Midazolam microdosing incorporated into early clinical studies is a feasible tool for reducing dedicated drug-drug interaction studies, meaning reduced subject burden. Limited sampling could further reduce subject burden, costs and needed resources.

Multivariate binary classification of imbalanced datasets-A case study based on high-dimensional multiplex autoimmune assay data.

The classification of a population by a specific trait is a major task in medicine, for example when in a diagnostic setting groups of patients with specific diseases are identified, but also when in predictive medicine a group of patients is classified into specific disease severity classes that might profit from different treatments. When the sizes of those subgroups become small, for example in rare diseases, imbalances between the classes are more the rule than the exception and make statistical classification problematic when the error rate of the minority class is high. Many observations are classified as belonging to the majority class, while the error rate of the majority class is low. This case study aims to investigate class imbalance for Random Forests and Powered Partial Least Squares Discriminant Analysis (PPLS-DA) and to evaluate the performance of these classifiers when they are combined with methods to compensate imbalance (sampling methods, cost-sensitive learning approaches). We evaluate all approaches with a scoring system taking the classification results into consideration. This case study is based on one high-dimensional multiplex autoimmune assay dataset describing immune response to antigens and consisting of two classes of patients: Rheumatoid Arthritis (RA) and Systemic Lupus Erythemathodes (SLE). Datasets with varying degrees of imbalance are created by successively reducing the class of RA patients. Our results indicate possible benefit of cost-sensitive learning approaches for Random Forests. Although further research is needed to verify our findings by investigating other datasets or large-scale simulation studies, we claim that this work has the potential to increase awareness of practitioners to this problem of class imbalance and stresses the importance of considering methods to compensate class imbalance.