There is an increasing need to construct a risk-prediction scoring system for survival data and identify important risk factors (e.g., biomarkers) for patient screening and treatment recommendation. However, most existing methodologies either rely on strong model assumptions (e.g., proportional hazards) or only handle binary outcomes. In this article, we propose a flexible method that simultaneously selects important risk factors and identifies the optimal linear combination of risk factors by maximizing a pseudo-likelihood function based on the time-dependent area under the receiver operating characteristic curve. Our method is particularly useful for risk evaluation and recommendation of optimal subsequent treatments. We show that the proposed method has desirable theoretical properties, including asymptotic normality and the oracle property after variable selection. Numerical performance is evaluated on several simulation data sets and an application to hepatocellular carcinoma data.

The aim of this paper is to conduct a systematic and theoretical analysis of estimation and inference for a class of functional mixed effects models (FMEM). Such FMEMs consist of fixed effects that characterize the association between longitudinal functional responses and covariates of interest and random effects that capture the spatial-temporal correlations of longitudinal functional responses. We propose local linear estimates of refined fixed effect functions and establish their weak convergence along with a simultaneous confidence band for each fixed-effect function. We propose a global test for the linear hypotheses of varying coefficient functions and derive the associated asymptotic distribution under the null hypothesis and the asymptotic power under the alternative hypothesis are derived. We also establish the convergence rates of the estimated spatial-temporal covariance operators and their associated eigenvalues and eigenfunctions. We conduct extensive simulations and apply our method to a white-matter fiber data set from a national database for autism research to examine the finite-sample performance of the proposed estimation and inference procedures.

There is an increasing need to construct a risk-prediction scoring system for survival data and identify important risk factors (e.g., biomarkers) for patient screening and treatment recommendation. However, most existing methodologies either rely on strong model assumptions (e.g., proportional hazards) or only handle binary outcomes. In this article, we propose a flexible method that simultaneously selects important risk factors and identifies the optimal linear combination of risk factors by maximizing a pseudo-likelihood function based on the time-dependent area under the receiver operating characteristic curve. Our method is particularly useful for risk evaluation and recommendation of optimal subsequent treatments. We show that the proposed method has desirable theoretical properties, including asymptotic normality and the oracle property after variable selection. Numerical performance is evaluated on several simulation data sets and an application to hepatocellular carcinoma data.

Many longitudinal imaging studies have collected repeated diffusion tensor magnetic resonance imaging data to understand white matter maturation and structural connectivity pattern in normal controls and diseased subjects. There is an urgent demand for the development of statistical methods for the analysis of diffusion properties along fiber tracts and clinical data obtained from longitudinal studies. Jointly analyzing repeated fiber-tract diffusion properties and covariates (e.g., age or gender) raises several major challenges including (i) infinite-dimensional functional response data, (ii) complex spatial-temporal correlation structure, and (iii) complex spatial smoothness. To address these challenges, this article is to develop a functional mixed effects modeling (FMEM) framework to delineate the dynamic changes of diffusion properties along major fiber tracts and their association with a set of covariates of interest and the structure of the variability of these white matter tract properties in various longitudinal studies. Our FMEM consists of a functional mixed effects model for addressing all three challenges, an efficient method for spatially smoothing varying coefficient functions, an estimation method for estimating the spatial-temporal correlation structure, a test procedure with local and global test statistics for testing hypotheses of interest associated with functional response, and a simultaneous confidence band for quantifying the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FMEM and to demonstrate that FMEM significantly outperforms the standard pointwise mixed effects modeling approach. We apply FMEM to study the spatial-temporal dynamics of white-matter fiber tracts in a clinical study of neurodevelopment.

Previous studies have showed promising but short-lived activity of sorafenib in osteosarcoma treatments. Researches have suggested ameliorated sensitivity to standard dose of conventional cancer therapies in combination with histone deacetylase inhibitors (HDACis) through various mechanisms. Herein, for the first time, we exploited the synergism of combination therapies with sorafenib and chidamide, a member of HDACis, in the control of OS using human OS cell lines and OS xenograft mouse model and discussed interactive mechanisms between the two drugs. The combination therapy exerted a strong synergism in the inhibition of OS cell proliferation, meanwhile prominently induced cell apoptosis and cell cycle arrest in G0/G1 phase in OS cells with increased expression of MCL-1, decreased expression of caspase-3 and P21, along with diminished level of the overlapped protein P-ERK1/2. Furthermore, oral administration of the combined treatment led to a more optical therapeutic outcome, including lower degrees of tumoral cell proliferation, greater extent of apoptosis, along with induction of cell cycle arrest in tumor tissues, while exhibiting minimal toxicity. This study shows that the combination of sorafenib and chidamide can combat OS in a synergistic fashion and prompts the promising development of innovative combined therapeutic strategies for OS.

The insights into interactions between host genetics and gut microbiome (GM) in colorectal tumor susceptibility (CTS) remains lacking. We used Collaborative Cross mouse population model to identify genetic and microbial determinants of Azoxymethane-induced CTS. We identified 4417 CTS-associated single nucleotide polymorphisms (SNPs) containing 334 genes that were transcriptionally altered in human colorectal cancers (CRCs) and consistently clustered independent human CRC cohorts into two subgroups with different prognosis. We discovered a set of genera in early-life associated with CTS and defined a 16-genus signature that accurately predicted CTS, the majority of which were correlated with human CRCs. We identified 547 SNPs associated with abundances of these genera. Mediation analysis revealed GM as mediators partially exerting the effect of SNP UNC3869242 within Duox2 on CTS. Intestine cell-specific depletion of Duox2 altered GM composition and contribution of Duox2 depletion to CTS was significantly influenced by GM. Our findings provide potential novel targets for personalized CRC prevention and treatment.

Purpose

Our preclinical studies showed that lycopene enhanced the anti-prostate cancer efficacy of docetaxel in animal models. A phase I trial (NCT0149519) was conducted to identify an optimum dose of synthetic lycopene in combination with docetaxel (and androgen blockade [androgen deprivation therapy, ADT]), and to evaluate its effect on the safety and pharmacokinetics of docetaxel in men with metastatic prostate cancer.

Methods

Subjects were treated with 21-day cycles of 75 mg/m² docetaxel (and ADT), plus lycopene at 30, 90 or 150 mg/day. A Bayesian model averaging continual reassessment method was used to guide dose escalation. Pharmacokinetics of docetaxel and multiple correlative studies were carried out.

Results

Twenty-four participants were enrolled, 18 in a dose escalation cohort to define the maximum tolerated dose (MTD), and six in a pharmacokinetic cohort. Docetaxel/ADT plus 150 mg/day synthetic lycopene resulted in dose-limiting toxicity (pulmonary embolus) in one out of 12 participants with an estimated probability of .106 and thus was chosen as the MTD. Lycopene increased the AUC_inf and C_max of plasma docetaxel by 9.5% and 15.1%, respectively. Correlative studies showed dose-related changes in circulating endothelial cells and vascular endothelial growth factor A, and reduction in insulin-like growth factor 1R phosphorylation, associated with lycopene therapy.

Conclusions

The combination of docetaxel/ADT and synthetic lycopene has low toxicity and favourable pharmacokinetics. The effects of lycopene on biomarkers provide additional support for the toxicity-dependent MTD definition.

Highlights

The maximum tolerated dose was identified as 150 mg/day of lycopene in combination with docetaxel/ADT for the treatment of metastatic prostate cancer patients. Small increases in plasma exposure to docetaxel were observed with lycopene co-administration. Mechanistically significant effects were seen on angiogenesis and insulin-like growth factor 1 signalling by lycopene co-administration with docetaxel/ADT.

Being the second most common type of primary bone malignancy in children and adolescents, Ewing Sarcoma (ES) encounters the dilemma of low survival rate with a lack of effective treatments. As an emerging approach to combat cancer, RNA therapeutics may expand the range of druggable targets. Since the genome-derived oncolytic microRNA-34a (miR-34a) is down-regulated in ES, restoration of miR-34a-5p expression or function represents a new therapeutic strategy which is, however, limited to the use of chemically-engineered miRNA mimics. Very recently we have developed a novel bioengineering technology using a stable non-coding RNA carrier (nCAR) to achieve high-yield production of biocompatible miRNA prodrugs, which is a great addition to current tools for the assessment of RNA therapeutics. Herein, for the first time, we investigated the biochemical pharmacology of bioengineered miR-34a-5p prodrug (nCAR/miR-34a-5p) in the control of ES using human ES cells and xenograft mouse models. The bioengineered nCAR/miR-34a-5p was precisely processed to mature miR-34a-5p in ES cells and subsequently suppressed cell proliferation, attributable to the enhancement of apoptosis and induction of G2 cell cycle arrest through downregulation of SIRT-1, BCL-2 and CDK6 protein levels. Furthermore, systemic administration of nCAR/miR-34a-5p dramatically suppressed the ES xenograft tumor growth in vivo while showing biocompatibility. In addition, the antitumor effect of bioengineered nCAR/miR-34a-5p was associated with a lower degree of tumoral cell proliferation and greater extent of apoptosis. These findings demonstrate the efficacy of bioengineered miR-34a-5p prodrug for the treatment of ES and support the development of miRNA therapeutics using biocompatible bioengineered miRNA prodrugs.

Being the second most common type of primary bone malignancy in children and adolescents, Ewing Sarcoma (ES) encounters the dilemma of low survival rate with a lack of effective treatments. As an emerging approach to combat cancer, RNA therapeutics may expand the range of druggable targets. Since the genome-derived oncolytic microRNA-34a (miR-34a) is down-regulated in ES, restoration of miR-34a-5p expression or function represents a new therapeutic strategy which is, however, limited to the use of chemically-engineered miRNA mimics. Very recently we have developed a novel bioengineering technology using a stable non-coding RNA carrier (nCAR) to achieve high-yield production of biocompatible miRNA prodrugs, which is a great addition to current tools for the assessment of RNA therapeutics. Herein, for the first time, we investigated the biochemical pharmacology of bioengineered miR-34a-5p prodrug (nCAR/miR-34a-5p) in the control of ES using human ES cells and xenograft mouse models. The bioengineered nCAR/miR-34a-5p was precisely processed to mature miR-34a-5p in ES cells and subsequently suppressed cell proliferation, attributable to the enhancement of apoptosis and induction of G2 cell cycle arrest through downregulation of SIRT-1, BCL-2 and CDK6 protein levels. Furthermore, systemic administration of nCAR/miR-34a-5p dramatically suppressed the ES xenograft tumor growth in vivo while showing biocompatibility. In addition, the antitumor effect of bioengineered nCAR/miR-34a-5p was associated with a lower degree of tumoral cell proliferation and greater extent of apoptosis. These findings demonstrate the efficacy of bioengineered miR-34a-5p prodrug for the treatment of ES and support the development of miRNA therapeutics using biocompatible bioengineered miRNA prodrugs.

Background:Corticosteroids are the mainstay of treatment for peritumor edema but are often associated with significant side effects. Therapies that can reduce corticosteroid use would potentially be of significant benefit to patients. However, currently there are no standardized endpoints evaluating corticosteroid use in neuro-oncology clinical trials. Methods:The Response Assessment in Neuro-Oncology (RANO) Working Group has developed consensus recommendations for endpoints evaluating corticosteroid use in clinical trials in both adults and children with brain tumors. Results:Responders are defined as patients with a 50% reduction in total daily corticosteroid dose compared with baseline or reduction of the total daily dose to ≤2 mg of dexamethasone (or equivalent dose of other corticosteroid); baseline dose must be at least 4 mg of dexamethasone daily (or equivalent dose of other corticosteroids) for at least one week. Patients must have stable or improved Neurologic Assessment in Neuro-Oncology (NANO) score or Karnofsky performance status score or Eastern Cooperative Oncology Group (ECOG) (Lansky score for children age <16 y), and an improved score on a relevant clinical outcome assessment tool. These criteria must be sustained for at least 4 weeks after baseline assessment to be considered a response, and are confirmed 4 weeks after that (ie, 8 wk after baseline assessment) to be considered a sustained response. Conclusions:This RANO proposal for corticosteroid use endpoints in neuro-oncology clinical trials may need to be refined and will require prospective validation in clinical studies.