Evaluating hybrid controls methodology in early-phase oncology trials: A simulation study based on the MORPHEUS-UC trial.

Phase Ib/II oncology trials, despite their small sample sizes, aim to provide information for optimal internal company decision-making concerning novel drug development. Hybrid controls (a combination of the current control arm and controls from one or more sources of historical trial data [HTD]) can be used to increase statistical precision. Here we assess combining two sources of Roche HTD to construct a hybrid control in targeted therapy for decision-making via an extensive simulation study. Our simulations are based on the real data of one of the experimental arms and the control arm of the MORPHEUS-UC Phase Ib/II study and two Roche HTD for atezolizumab monotherapy. We consider potential complications such as model misspecification, unmeasured confounding, different sample sizes of current treatment groups, and heterogeneity among the three trials. We evaluate two frequentist methods (with both Cox and Weibull accelerated failure time [AFT] models) and three different commensurate priors in Bayesian dynamic borrowing (with a Weibull AFT model), and modifications within each of those, when estimating the effect of treatment on survival outcomes and measures of effect such as marginal hazard ratios. We assess the performance of these methods in different settings and the potential of generalizations to supplement decisions in early-phase oncology trials. The results show that the proposed joint frequentist methods and noninformative priors within Bayesian dynamic borrowing with no adjustment on covariates are preferred, especially when treatment effects across the three trials are heterogeneous. For generalization of hybrid control methods in such settings, we recommend more simulation studies.

Knockdown of ENTPD5 inhibits tumor metastasis and growth via regulating the GRP78/p-eIF-2α/CHOP pathway in serous ovarian cancer.

BACKGROUND: Dysregulation of Ectonucleoside Triphospahate Diphosphohydrolase 5 (ENTPD5) in tumors might be associated with tumor progression, while the role of ENTPD5 in the growth and metastasis of serous ovarian cancer (SOC) is still unclear. METHODS: ENTPD5 expression patterns in ovarian cancer tissues were analyzed by qRT-PCR and immunohistochemistry assay (IHC). Two SOC cell lines, SKOV3 and OVCAR8, were stably transfected with lentivirus to build knockdown and overexpression cell lines. Clone formation assay, collagen gel droplet culture technology, wound healing assay and flow cytometry were used to assess the migration and growth traits of SOC cells. Expression levels of ENTPD5, glucose regulated protein 78 (GRP78), eukaryotic translation initiation factor 2 alpha (eIF-2α), phosphorylated -eIF-2α and, C/EBP homologous protein (CHOP) in SOC cells were detected by Western blot. RESULTS: Compared to fallopian tube tissues, the expression of ENTPD5 was significantly higher in tumor tissues obtained from SOC patients, and positively correlated with clinical stage and metastasis. ENTPD5 knockdown robustly inhibited cell proliferation, migration, whereas ENTPD5 overexpression elicited the opposite effect on SOC cells. ENTPD5 knockdown arrested cell cycle in G0/G1 phase and increased apoptosis. Importantly, ENTPD5 knockdown was associated with significantly decreased protein levels for GRP78, CHOP, and p-eIF-2α, suggesting possible involvement of ENTPD5 in endoplasmic reticulum stress (ERS). CONCLUSIONS: Our study demonstrates that ENTPD5 knockdown inhibited SOC cell proliferation, migration and restrained the activation of the GRP78/p-eIF-2α/CHOP pathway, which provides a potentially effective therapeutic target for the treatment of SOC.

Spline-based accelerated failure time model.

The accelerated failure time (AFT) model has been suggested as an alternative to the Cox proportional hazards model. However, a parametric AFT model requires the specification of an appropriate distribution for the event time, which is often difficult to identify in real-life studies and may limit applications. A semiparametric AFT model was developed by Komárek et al based on smoothed error distribution that does not require such specification. In this article, we develop a spline-based AFT model that also does not require specification of the parametric family of event time distribution. The baseline hazard function is modeled by regression B-splines, allowing for the estimation of a variety of smooth and flexible shapes. In comprehensive simulations, we validate the performance of our approach and compare with the results from parametric AFT models and the approach of Komárek. Both the proposed spline-based AFT model and the approach of Komárek provided unbiased estimates of covariate effects and survival curves for a variety of scenarios in which the event time followed different distributions, including both simple and complex cases. Spline-based estimates of the baseline hazard showed also a satisfactory numerical stability. As expected, the baseline hazard and survival probabilities estimated by the misspecified parametric AFT models deviated from the truth. We illustrated the application of the proposed model in a study of colon cancer.