Assessment of Tumor Mutational Burden and Outcomes in Patients With Diverse Advanced Cancers Treated With Immunotherapy.

Importance: There are few studies assessing the association of tumor mutational burden (TMB) and clinical outcomes in a large cohort of patients with diverse advanced cancers. Objective: To clinically validate a TMB biomarker from a next-generation sequencing targeted gene panel assay. Design, Setting, and Participants: A prespecified cohort study using the deidentified clinicogenomic Tempus database of patients sequenced between 2018 and 2022, which contained retrospective, observational data originating from 300 cancer sites including 199 community sites and 101 academic sites. Patients with advanced solid tumors across 8 cancer types and more than 20 histologies, sequenced with Tempus xT who were treated with immune checkpoint inhibitors (ICIs) in the first-line or second-line setting were included. Data were analyzed from September 2018 to August 2022. Exposure: Treatment with US Food and Drug Administration (FDA)-approved antiprogrammed cell death-1/programmed cell death-ligand 1 (PD-1/PD-L1) ICI and/or in combination with a cytotoxic T-lymphocyte-associated protein-4 ICI. Main Outcomes and Measures: The primary outcome was the association of tumor mutational burden (TMB) binary category (high [≥10 mut/mb] vs low) with overall survival (OS) in patients treated with ICIs. Secondary outcomes were progression-free survival (PFS), and time to progression (TTP). Results: In the evaluable cohort of 674 patients, the median (IQR) age was 69.4 (28.6-89.8) years, 271 patients (40.2%) were female, and 435 patients (64.5%) were White. The most common advanced cancers were non-small cell lung cancer (330 patients [49.0%]), followed by bladder cancer (148 patients [22.0%]), and head and neck squamous cell carcinoma (96 patients [14.8%]). Median (IQR) follow-up was 7.2 (3.2-14.1) months. High TMB (TMB-H) cancers (206 patients [30.6%]) were significantly associated with longer OS than low TMB (TMB-L) cancers (hazard ratio [HR], 0.72; upper confidence bound [UCB], 0.91; P = .01). In a prospective subset of 403 patients treated with ICIs after TMB testing, TMB-H cancers (135 patients [33.5%]) were significantly associated with longer OS (HR, 0.61; UCB, 0.84; P = .005), PFS (HR, 0.62; UCB, 0.82; P = .003), and TTP (HR, 0.67; UCB, 0.92; P = .02) than TMB-L cancers. An overall survival benefit was seen regardless of the type of ICI used (pembrolizumab, 339 patients; HR, 0.67; UCB, 0.94; P = .03), other ICIs (64 patients; HR, 0.37; UCB, 0.85; P = .03), and after adjusting for PD-L1 and microsatellite stability status (403 patients; HR = 0.67; UCB, 0.92; P = .02). Conclusions and Relevance: In this cohort study of patients with advanced solid tumors treated with ICIs in diverse clinics, TMB-H cancers were significantly associated with improved clinical outcomes compared with TMB-L cancers.

A model-based approach to designing developmental toxicology experiments using sea urchin embryos.

The key aim of this paper is to suggest a more quantitative approach to designing a dose-response experiment, and more specifically, a concentration-response experiment. The work proposes a departure from the traditional experimental design to determine a dose-response relationship in a developmental toxicology study. It is proposed that a model-based approach to determine a dose-response relationship can provide the most accurate statistical inference for the underlying parameters of interest, which may be estimating one or more model parameters or pre-specified functions of the model parameters, such as lethal dose, at maximal efficiency. When the design criterion or criteria can be determined at the onset, there are demonstrated efficiency gains using a more carefully selected model-based optimal design as opposed to an ad-hoc empirical design. As an illustration, a model-based approach was theoretically used to construct efficient designs for inference in a developmental toxicity study of sea urchin embryos exposed to trimethoprim. This study compares and contrasts the results obtained using model-based optimal designs versus an ad-hoc empirical design.

Linear Vertigo in Benign Paroxysmal Positional Vertigo: Prevalence and Mechanism.

This study aimed to determine the prevalence and mechanism of linear vertigo reported by the patients during the attacks of benign paroxysmal positional vertigo (BPPV). We prospectively evaluated the characteristics (rotational vs. linear) of positional vertigo in 70 patients with posterior and horizontal canal BPPV using a questionnaire allowing multiple choices. In patients with linear vertigo, we further assessed the directionality of linear vertigo. We adopted the velocity-storage model to explain the occurrence and direction of linear vertigo in these patients with BPPV. Patients reported only rotational vertigo in 46 (46/70, 65.7%), only linear vertigo in 10 (14.3%), and both rotational and linear vertigo in 14 (20%). The patients experienced fear from rotational vertigo in 54 (54/70, 77.1%) and from linear vertigo in 20 (20/70, 28.6%). The direction of linear vertigo was concordant with the direction of inertial acceleration predicted by the velocity-storage model. Patients with BPPV may experience linear as well as rotational vertigo during the attacks. This linear vertigo may be ascribed to centrally estimated inertial acceleration.

Optimal designs for asymmetric sigmoidal response curves in bioassays and immunoassays.

The 5-parameter logistic (5PL) model is frequently used to model and analyze responses from bioassays and immunoassays which can be skewed. Various types of optimal experimental designs for 2, 3 and 4-parameter logistic models have been reported but not for the more complicated 5PL model. We construct different types of optimal designs for studying various features of the 5PL model and show that commonly used designs in bioassays and immunoassays are generally inefficient for statistical inference. To facilitate use of such designs in practice, we create a user-friendly software package to generate various tailor-made optimal designs for the 5PL model and evaluate robustness properties of a design under a variation of criteria, model forms and misspecification in the nominal values of the model parameters.

Optimal designs based on the maximum quasi-likelihood estimator.

We use optimal design theory and construct locally optimal designs based on the maximum quasi-likelihood estimator (MqLE), which is derived under less stringent conditions than those required for the MLE method. We show that the proposed locally optimal designs are asymptotically as efficient as those based on the MLE when the error distribution is from an exponential family, and they perform just as well or better than optimal designs based on any other asymptotically linear unbiased estimators such as the least square estimator (LSE). In addition, we show current algorithms for finding optimal designs can be directly used to find optimal designs based on the MqLE. As an illustrative application, we construct a variety of locally optimal designs based on the MqLE for the 4-parameter logistic (4PL) model and study their robustness properties to misspecifications in the model using asymptotic relative efficiency. The results suggest that optimal designs based on the MqLE can be easily generated and they are quite robust to mis-specification in the probability distribution of the responses.

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

Transgenic soybean plants overexpressing O-acetylserine sulfhydrylase accumulate enhanced levels of cysteine and Bowman-Birk protease inhibitor in seeds.

Soybeans provide an excellent source of protein in animal feed. Soybean protein quality can be enhanced by increasing the concentration of sulfur-containing amino acids. Previous attempts to increase the concentration of sulfur-containing amino acids through the expression of heterologous proteins have met with limited success. Here, we report a successful strategy to increase the cysteine content of soybean seed through the overexpression of a key sulfur assimilatory enzyme. We have generated several transgenic soybean plants that overexpress a cytosolic isoform of O-acetylserine sulfhydrylase (OASS). These transgenic soybean plants exhibit a four- to tenfold increase in OASS activity when compared with non-transformed wild-type. The OASS activity in the transgenic soybeans was significantly higher at all the stages of seed development. Unlike the non-transformed soybean plants, there was no marked decrease in the OASS activity even at later stages of seed development. Overexpression of cytosolic OASS resulted in a 58-74% increase in protein-bound cysteine levels compared with non-transformed wild-type soybean seeds. A 22-32% increase in the free cysteine levels was also observed in transgenic soybeans overexpressing OASS. Furthermore, these transgenic soybean plants showed a marked increase in the accumulation of Bowman-Birk protease inhibitor, a cysteine-rich protein. The overall increase in soybean total cysteine content (both free and protein-bound) satisfies the recommended levels required for the optimal growth of monogastric animals.