Phototherapy Alters the Plasma Metabolite Profile in Infants Born Preterm with Hyperbilirubinemia.

OBJECTIVE: To investigate the effects of gestational age (GA) and phototherapy on the plasma metabolite profile of preterm infants with neonatal hyperbilirubinemia (NHB). STUDY DESIGN: From a cohort of prospectively enrolled infants born preterm (N=92), plasma samples of very preterm (VPT; GA, 28+0 to 31+6 weeks, N =27) and moderate/late preterm (M/LPT; GA, 32+0 to 35+6 weeks, N =33) infants requiring phototherapy for NHB were collected prior to the initiation of phototherapy and 24 hours after starting phototherapy. An additional sample was collected 48 hours after starting phototherapy in a randomly selected subset (N=30; VPT N=15; M/LPT N=15). Metabolite profiles were determined using ultraperformance liquid chromatography tandem mass spectroscopy. Two-way ANCOVA was used to identify metabolites that differed between GA groups and timepoints after adjusting for total serum bilirubin (TSB) levels (FDR q-value<0.05). Top impacted pathways were identified using pathway over-representation analysis. RESULTS: Phototherapy was initiated at lower TSB (mean ± SD mg/dL) levels in VPT compared with M/LPT infants (7.3 ± 1.4 vs. 9.9 ± 1.9, p<0.01). We identified 664 metabolites that were significant for a phototherapy effect, 191 metabolites significant for GA, and 46 metabolites significant for GA x phototherapy interaction (FDR q-value<0.05). Longer duration phototherapy had a larger mean effect size (24 hours post-phototherapy: d=0.36; 48 hours post-phototherapy: d=0.43). Top pathways affected by phototherapy included membrane lipid metabolism, one-carbon metabolism, creatine biosynthesis, and oligodendrocyte differentiation. CONCLUSION: Phototherapy alters the plasma metabolite profile more than GA in preterm infants with NHB, affecting pathways related to lipid and one-carbon metabolism, energy biosynthesis, and oligodendrocyte differentiation.

Multiple augmented reduced rank regression for pan-cancer analysis.

Statistical approaches that successfully combine multiple datasets are more powerful, efficient, and scientifically informative than separate analyses. To address variation architectures correctly and comprehensively for high-dimensional data across multiple sample sets (ie, cohorts), we propose multiple augmented reduced rank regression (maRRR), a flexible matrix regression and factorization method to concurrently learn both covariate-driven and auxiliary structured variations. We consider a structured nuclear norm objective that is motivated by random matrix theory, in which the regression or factorization terms may be shared or specific to any number of cohorts. Our framework subsumes several existing methods, such as reduced rank regression and unsupervised multimatrix factorization approaches, and includes a promising novel approach to regression and factorization of a single dataset (aRRR) as a special case. Simulations demonstrate substantial gains in power from combining multiple datasets, and from parsimoniously accounting for all structured variations. We apply maRRR to gene expression data from multiple cancer types (ie, pan-cancer) from The Cancer Genome Atlas, with somatic mutations as covariates. The method performs well with respect to prediction and imputation of held-out data, and provides new insights into mutation-driven and auxiliary variations that are shared or specific to certain cancer types.

Multiple Augmented Reduced Rank Regression for Pan-Cancer Analysis.

Statistical approaches that successfully combine multiple datasets are more powerful, efficient, and scientifically informative than separate analyses. To address variation architectures correctly and comprehensively for high-dimensional data across multiple sample sets (i.e., cohorts), we propose multiple augmented reduced rank regression (maRRR), a flexible matrix regression and factorization method to concurrently learn both covariate-driven and auxiliary structured variation. We consider a structured nuclear norm objective that is motivated by random matrix theory, in which the regression or factorization terms may be shared or specific to any number of cohorts. Our framework subsumes several existing methods, such as reduced rank regression and unsupervised multi-matrix factorization approaches, and includes a promising novel approach to regression and factorization of a single dataset (aRRR) as a special case. Simulations demonstrate substantial gains in power from combining multiple datasets, and from parsimoniously accounting for all structured variation. We apply maRRR to gene expression data from multiple cancer types (i.e., pan-cancer) from TCGA, with somatic mutations as covariates. The method performs well with respect to prediction and imputation of held-out data, and provides new insights into mutation-driven and auxiliary variation that is shared or specific to certain cancer types.

Safety and efficacy of mirvetuximab soravtansine, a folate receptor alpha (FRα)-targeting antibody-drug conjugate (ADC), in combination with bevacizumab in patients with platinum-resistant ovarian cancer.

PURPOSE: Evaluate the antitumor activity and safety profile of the combination of mirvetuximab soravtansine and bevacizumab in patients with platinum-resistant ovarian cancer. METHODS: Patients with recurrent epithelial ovarian, fallopian tube, or primary peritoneal cancer, whose most recent platinum-free interval was ≤6 months, were administered mirvetuximab soravtansine (6 mg/kg adjusted ideal body weight) and bevacizumab (15 mg/kg), intravenously, once every 3 weeks. Eligibility included FRα expression by immunohistochemistry (IHC; ≥25% of cells with ≥2+ intensity). Prior bevacizumab and/or PARP inhibitor (PARPi) treatment were permitted. The primary endpoint was confirmed objective response rate (ORR). Secondary endpoints included duration of response (DOR), progression-free survival (PFS), and safety. RESULTS: Ninety-four patients received combination treatment with mirvetuximab soravtansine and bevacizumab. Median age was 62 years (range, 39-81). Fifty-two percent had ≥3 prior therapies; 59% had prior bevacizumab; and 27% had prior PARPi. ORR was 44% (95% CI 33, 54) with 5 complete responses, median DOR 9.7 months (95% CI 6.9, 14.1), and median PFS 8.2 months (95% CI 6.8, 10.0). Treatment-related adverse events were consistent with the profiles of each agent, with the most common being blurred vision (all grades 57%; grade 3, 1%), diarrhea (54%; grade 3, 1%), and nausea (51%; grade 3, 1%). CONCLUSION: The mirvetuximab soravtansine plus bevacizumab doublet is an active and well-tolerated regimen in patients with FRα-expressing platinum-resistant ovarian cancer. Promising activity was observed for patients regardless of level of FRα expression or prior bevacizumab. These data underscore the potential for mirvetuximab soravtansine as the combination partner of choice for bevacizumab in this setting.

Efficacy and Safety of Mirvetuximab Soravtansine in Patients With Platinum-Resistant Ovarian Cancer With High Folate Receptor Alpha Expression: Results From the SORAYA Study.

PURPOSE: Single-agent chemotherapies have limited activity and considerable toxicity in patients with platinum-resistant epithelial ovarian cancer (PROC). Mirvetuximab soravtansine (MIRV) is an antibody-drug conjugate targeting folate receptor α (FRα). SORAYA is a single-arm, phase II study evaluating efficacy and safety of MIRV in patients with PROC. METHODS: SORAYA enrolled FRα-high patients with PROC who had received one to three prior therapies, including required bevacizumab. The primary end point was confirmed objective response rate (ORR) by investigator; duration of response was the key secondary end point. RESULTS: One hundred six patients were enrolled; 105 were evaluable for efficacy. All patients had received prior bevacizumab, 51% had three prior lines of therapy, and 48% received a prior poly ADP-ribose polymerase inhibitor. Median follow-up was 13.4 months. ORR was 32.4% (95% CI, 23.6 to 42.2), including five complete and 29 partial responses. The median duration of response was 6.9 months (95% CI, 5.6 to 9.7). In patients with one to two priors, the ORR by investigator was 35.3% (95% CI, 22.4 to 49.9) and in patients with three priors was 30.2% (95% CI, 18.3 to 44.3). The ORR by investigator was 38.0% (95% CI, 24.7 to 52.8) in patients with prior poly ADP-ribose polymerase inhibitor exposure and 27.5% (95% CI, 15.9 to 41.7) in those without. The most common treatment-related adverse events (all grade and grade 3-4) were blurred vision (41% and 6%), keratopathy (29% and 9%), and nausea (29% and 0%). Treatment-related adverse events led to dose delays, reductions, and discontinuations in 33%, 20%, and 9% of patients, respectively. CONCLUSION: MIRV demonstrated consistent clinically meaningful antitumor activity and favorable tolerability and safety in patients with FRα-high PROC who had received up to three prior therapies, including bevacizumab, representing an important advance for this biomarker-selected population.

Deep IDA: A Deep Learning Method for Integrative Discriminant Analysis of Multi-View Data with Feature Ranking-An Application to COVID-19 severity.

COVID-19 severity is due to complications from SARS-Cov-2 but the clinical course of the infection varies for individuals, emphasizing the need to better understand the disease at the molecular level. We use clinical and multiple molecular data (or views) obtained from patients with and without COVID-19 who were (or not) admitted to the intensive care unit to shed light on COVID-19 severity. Methods for jointly associating the views and separating the COVID-19 groups (i.e., one-step methods) have focused on linear relationships. The relationships between the views and COVID-19 patient groups, however, are too complex to be understood solely by linear methods. Existing nonlinear one-step methods cannot be used to identify signatures to aid in our understanding of the complexity of the disease. We propose Deep IDA (Integrative Discriminant Analysis) to address analytical challenges in our problem of interest. Deep IDA learns nonlinear projections of two or more views that maximally associate the views and separate the classes in each view, and permits feature ranking for interpretable findings. Our applications demonstrate that Deep IDA has competitive classification rates compared to other state-of-the-art methods and is able to identify molecular signatures that facilitate an understanding of COVID-19 severity.

Boosting the Energy Density of Li||CFx Primary Batteries Using a 1,3-Dimethyl-2-imidazolidinone-Based Electrolyte.

Elevating the discharge voltage plateau is regarded as the most effective strategy to improve the energy density of Li||CFx batteries in consideration of the finite capacity of CFx (x ∼ 1) cathodes. Here, an electrolyte, with LiBF4 in 1,3-dimethyl-2-imidazolidinone (DMI)/1,2-dimethoxyethane (DME), is developed for the first time to substantially promote the discharge voltage of CFx without compromising the available discharge capacity. DME possesses the property of low viscosity, while DMI functions to increase the voltage plateau during discharge owing to its moderate nucleophilicity and donor number, which decreases the energy barrier for breaking C-F bonds. The optimized electrolyte exhibits a significantly high average discharge voltage of 2.69 V at a current density of 10 mA g-1, which is 11.6% higher than the control electrolyte (2.41 V). In addition, a high energy density of 2099 Wh kg-1 is achieved in the optimized electrolyte (vs 1905 Wh kg-1 in the control electrolyte), showing great potential for practical applications.

Adjusting win statistics for dependent censoring.

For composite outcomes whose components can be prioritized on clinical importance, the win ratio, the net benefit and the win odds apply that order in comparing patients pairwise to produce wins and subsequently win proportions. Because these three statistics are derived using the same win proportions and they test the same hypothesis of equal win probabilities in the two treatment groups, we refer to them as win statistics. These methods, particularly the win ratio and the net benefit, have received increasing attention in methodological research and in design and analysis of clinical trials. For time-to-event outcomes, however, censoring may introduce bias. Previous work has shown that inverse-probability-of-censoring weighting (IPCW) can correct the win ratio for bias from independent censoring. The present article uses the IPCW approach to adjust win statistics for dependent censoring that can be predicted by baseline covariates and/or time-dependent covariates (producing the CovIPCW-adjusted win statistics). Theoretically and with examples and simulations, we show that the CovIPCW-adjusted win statistics are unbiased estimators of treatment effect in the presence of dependent censoring.

The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring.

The win ratio method has received much attention in methodological research, ad hoc analyses, and designs of prospective studies. As the primary analysis, it supported the approval of tafamidis for the treatment of cardiomyopathy to reduce cardiovascular mortality and cardiovascular-related hospitalization. However, its dependence on censoring is a potential shortcoming. In this article, we propose the inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic (i.e., the IPCW-adjusted win ratio statistic) to overcome censoring issues. We consider independent censoring, common censoring across endpoints, and right censoring. We develop an asymptotic variance estimator for the logarithm of the IPCW-adjusted win ratio statistic and evaluate it via simulation. Our simulation studies show that, as the amount of censoring increases, the unadjusted win proportions may decrease greatly. Consequently, the bias of the unadjusted win ratio estimate may increase greatly, producing either an overestimate or an underestimate. We demonstrate theoretically and through simulation that the IPCW-adjusted win ratio statistic gives an unbiased estimate of treatment effect.

Comparative analysis of cellular expression pattern of schizophrenia risk genes in human versus mouse cortex.

BACKGROUND: Schizophrenia is a common psychiatric disease with high hereditary. The identification of schizophrenia risk genes (SRG) has shed light on its pathophysiological mechanisms. Mouse genetic models have been widely used to study the function of SRG in the brain with a cell type specific fashion. However, whether the cellular expression pattern of SRG is conserved between human and mouse brain is not thoroughly studied. RESULTS: We analyzed the single-cell transcription of 180 SRG from human and mouse primary visual cortex (V1). We compared the percentage of glutamatergic, GABAergic and non-neuronal cells that express each SRG between mouse and human V1 cortex. Thirty percent (54/180) of SRG had significantly different expression rate in glutamatergic neurons between mouse and human V1 cortex. By contrast, only 5.6% (10/180) of SRG showed significantly different expression in GABAergic neurons, which is similar with the ratio of SRG (15/180) with species difference in total cell populations. Strikingly, the percentage of non-neuronal cells expressing all SRG are indistinguishable between human and mouse V1 cortex. We further analyzed the biological significance of differentially expressed SRG by gene ontology. The species-different SRG in glutamatergic neurons are highly expressed in dendrite and axon. They are enriched in the biological process of response to stimulus. However, the differentially expressed SRG in GABAergic neurons are enriched in the regulation of organelle organization. CONCLUSION: GABAergic neurons are more conserved in the expression of SRG than glutamatergic neurons while the non-neuronal cells show the species conservation for the expression of all SRG. It should be cautious to use mouse models to study those SRG which show different cellular expression pattern between human and mouse cortex.

Single-agent erlotinib versus oral etoposide in patients with recurrent or refractory pediatric ependymoma: a randomized open-label study.

Overexpression of human epidermal growth factor receptor (HER/EGFR) is associated with various tumors, including ependymomas. To investigate whether EGFR inhibition was of benefit in pediatric patients with recurrent ependymoma, a multi-center, randomized, open-label, phase 2 study of oral erlotinib versus oral etoposide was undertaken. Twenty-five patients were randomized to receive erlotinib 85 mg/m(2) daily or etoposide 50 mg/m(2)/day for 21 consecutive days followed by a 7-day rest period. Courses were repeated every 28 days. In the erlotinib arm, no patient achieved a complete, partial, or minor response, and only 2 (15.4 %) patients showed stable disease as their best response. In the etoposide arm, 2 patients (16.7 %) demonstrated partial responses, 1 (8.3 %) patient demonstrated a minor response, and 2 (16.7 %) showed prolonged stable disease, for a prolonged disease control rate of 41.7 %. Three patients received at least nine cycles of etoposide (range 9-24 cycles) before discontinuing at the request of the physician and/or family. Four patients who failed etoposide in this study received erlotinib in a companion single arm study; none had a response. The futility criteria were met at the second interim analysis, and both studies were discontinued. Pharmacokinetics of erlotinib were similar to previous observations in pediatric patients. Overall, erlotinib was well tolerated and safety was consistent with its established profile in adults. The overall risk-benefit profile does not support the use of erlotinib in pediatric patients with recurrent ependymoma, whereas single-agent etoposide appears to have efficacy in a subset of patients.

Adjuvant Erlotinib Versus Placebo in Patients With Stage IB-IIIA Non-Small-Cell Lung Cancer (RADIANT): A Randomized, Double-Blind, Phase III Trial.

PURPOSE: Epidermal growth factor receptor (EGFR) -tyrosine kinase inhibitors have proven efficacy in advanced non-small-cell lung cancer (NSCLC). We hypothesized that erlotinib would be efficacious in the adjuvant setting. PATIENTS AND METHODS: An international randomized, double-blind, placebo-controlled study was conducted in patients with completely resected IB to IIIA NSCLC whose tumors expressed EGFR protein by immunohistochemistry or EGFR amplification by fluorescence in situ hybridization. Patients were assigned 2:1 to erlotinib 150 mg once per day or placebo for 2 years. Stratification factors were stage, histology, previous adjuvant chemotherapy, smoking status, EGFR amplification status, and country. The primary end point was disease-free survival (DFS); key secondary end points were overall survival (OS) and DFS and OS in patients whose tumors had EGFR-activating mutations (EGFRm-positive). RESULTS: A total of 973 patients were randomly assigned (November 26, 2007, to July 7, 2010). There was no statistically significant difference in DFS (median, 50.5 months for erlotinib and 48.2 months for placebo; hazard ratio, 0.90; 95% CI, 0.74 to 1.10; P = .324). Among the 161 patients (16.5%) in the EGFRm-positive subgroup, DFS favored erlotinib (median, 46.4 v 28.5 months; hazard ratio, 0.61; 95% CI, 0.38 to 0.98; P = .039), but this was not statistically significant because of the hierarchical testing procedure. OS data are immature. Rash and diarrhea were common adverse events occurring in 528 (86.4%) and 319 (52.2%) patients treated with erlotinib, respectively, versus 110 (32.1%) and 54 (15.7%) patients receiving placebo. The most common grade 3 adverse events in patients treated with erlotinib were rash (22.3%) and diarrhea (6.2%). CONCLUSION: Adjuvant erlotinib did not prolong DFS in patients with EGFR-expressing NSCLC or in the EGFRm-positive subgroup. Further evaluation of erlotinib is warranted in the EGFRm-positive subgroup.

Arterial thromboembolic events in patients with metastatic carcinoma treated with chemotherapy and bevacizumab.

BACKGROUND: Although combination treatment with bevacizumab (humanized monoclonal antibody against vascular endothelial growth factor) and chemotherapy improves survival of patients with various metastatic carcinomas, an increased risk of arterial thromboembolic events has been observed in some trials. We characterized this risk by performing post hoc analyses of randomized controlled trials that evaluated combination treatment with bevacizumab and chemotherapy versus chemotherapy alone. Low-dose aspirin was permitted in these trials, and its safety was also analyzed. METHODS: Data were pooled from five randomized controlled trials that included a total of 1745 patients with metastatic colorectal, breast, or non-small-cell lung carcinoma. The risk of an arterial or venous thromboembolic event was assessed by simple incidence rates, rates per 100 person-years, and/or hazard ratios (HRs). The association between patient characteristics and risk of an arterial thromboembolic event was investigated primarily by Cox proportional hazards regression. The relationship between low-dose aspirin and bleeding was explored by incidence rates and rates per 100 person-years. RESULTS: Combined treatment with bevacizumab and chemotherapy, compared with chemotherapy alone, was associated with increased risk for an arterial thromboembolic event (HR = 2.0, 95% confidence interval [CI] = 1.05 to 3.75; P = .031) but not for a venous thromboembolic event (HR = 0.89, 95% CI = 0.66 to 1.20; P = .44). The absolute rate of developing an arterial thromboembolism was 5.5 events per 100 person-years for those receiving combination therapy and 3.1 events per 100 person-years for those receiving chemotherapy alone (ratio = 1.8, 95% CI = 0.94 to 3.33; P = .076). Development of an arterial thromboembolic event was associated with a prior arterial thromboembolic event (P<.001) or age of 65 years or older (P = .01). Baseline or on-study aspirin use was associated with modest increases in grade 3 and 4 bleeding events in both treatment groups, from 3.6% to 4.7% for bevacizumab-treated patients and from 1.7% to 2.2% for control subjects. CONCLUSIONS: Combination treatment with bevacizumab and chemotherapy, compared with chemotherapy alone, was associated with an increased risk of arterial thromboembolism but not venous thromboembolism.