Modeling craniofacial development reveals spatiotemporal constraints on robust patterning of the mandibular arch

How does pattern formation occur accurately when confronted with tissue growth and stochastic fluctuations (noise) in gene expression? Dorso-ventral (D-V) patterning of the mandibular arch specifies upper versus lower jaw skeletal elements through a combination of Bone morphogenetic protein (Bmp), Endothelin-1 (Edn1), and Notch signaling, and this system is highly robust. We combine NanoString experiments of early D-V gene expression with live imaging of arch development in zebrafish to construct a computational model of the D-V mandibular patterning network. The model recapitulates published genetic perturbations in arch development. Patterning is most sensitive to changes in Bmp signaling, and the temporal order of gene expression modulates the response of the patterning network to noise. Thus, our integrated systems biology approach reveals non-intuitive features of the complex signaling system crucial for craniofacial development, including novel insights into roles of gene expression timing and stochasticity in signaling and gene regulation

Epithelial Migration and Non-adhesive Periderm Are Required for Digit Separation during Mammalian Development.

The fusion of digits or toes, syndactyly, can be part of complex syndromes, including van der Woude syndrome. A subset of van der Woude cases is caused by dominant-negative mutations in the epithelial transcription factor Grainyhead like-3 (GRHL3), and Grhl3-/-mice have soft-tissue syndactyly. Although impaired interdigital cell death of mesenchymal cells causes syndactyly in multiple genetic mutants, Grhl3-/- embryos had normal interdigital cell death, suggesting alternative mechanisms for syndactyly. We found that in digit separation, the overlying epidermis forms a migrating interdigital epithelial tongue (IET) when the epithelium invaginates to separate the digits. Normally, the non-adhesive surface periderm allows the IET to bifurcate as the digits separate. In contrast, in Grhl3-/- embryos, the IET moves normally between the digits but fails to bifurcate because of abnormal adhesion of the periderm. Our study identifies epidermal developmental processes required for digit separation

A Randomized Ph2 Study of MEDI0680 in Combination With Durvalumab vs. Nivolumab Monotherapy in Patients With Advanced or Metastatic Clear Cell Renal Cell Carcinoma

BACKGROUND: MEDI0680 is a humanized anti-programmed cell death-1 (PD-1) antibody and durvalumab is an anti-PD-L1 antibody. Combining treatment using these antibodies may improve efficacy versus blockade of PD-1 alone. This phase 2 study evaluated antitumor activity and safety of MEDI0680 plus durvalumab versus nivolumab monotherapy in immunotherapy naïve patients with advanced clear cell renal cell carcinoma who received at least one prior line of anti-angiogenic therapy. METHODS: Patients received either MEDI0680 (20 mg/kg) with durvalumab (750 mg) or nivolumab (240 mg), all IV Q2W. The primary endpoint was investigator-assessed objective response rate (ORR). Secondary endpoints included best overall response, progression-free survival (PFS), safety, overall survival (OS), and immunogenicity. Exploratory endpoints included changes in circulating tumor DNA (ctDNA), baseline tumor mutational burden (TMB), and tumor-infiltrated immune cell profiles. RESULTS: Sixty-three patients were randomized (combination, n = 42; nivolumab, n = 21). ORR was 16.7% (7/42; 95% CI, 7.0-31.4) with combination treatment and 23.8% (5/21; 95% CI, 8.2- 47.2) with nivolumab. Median PFS was 3.6 months in both arms; median OS was not reached in either arm. Due to AEs, 23.8% of patients discontinued MEDI0680 and durvalumab and 14.3% of patients discontinued nivolumab. In the combination arm, reduction in ctDNA fraction was associated with longer PFS. ctDNA mutational analysis did not demonstrate an association with response in either arm. Tumor-infiltrated immune profiles showed an association between immune cell activation and response in the combination arm. CONCLUSIONS: MEDI0680 combined with durvalumab was safe and tolerable; however, it did not improve efficacy versus nivolumab monotherapy

Stochastic Simulation of Multiscale Reaction-Diffusion Models via First Exit Times

Mathematical models are important tools in systems biology, since the regulatory networks in biological cells are too complicated to understand by biological experiments alone. Analytical solutions can be derived only for the simplest models and numerical simulations are necessary in most cases to evaluate the models and their properties and to compare them with measured data. This thesis focuses on the mesoscopic simulation level, which captures both, space dependent behavior by diffusion and the inherent stochasticity of cellular systems. Space is partitioned into compartments by a mesh and the number of molecules of each species in each compartment gives the state of the system. We first examine how to compute the jump coefficients for a discrete stochastic jump process on unstructured meshes from a first exit time approach guaranteeing the correct speed of diffusion. Furthermore, we analyze different methods leading to non-negative coefficients by backward analysis and derive a new method, minimizing both the error in the diffusion coefficient and in the particle distribution. The second part of this thesis investigates macromolecular crowding effects. A high percentage of the cytosol and membranes of cells are occupied by molecules. This impedes the diffusive motion and also affects the reaction rates. Most algorithms for cell simulations are either derived for a dilute medium or become computationally very expensive when applied to a crowded environment. Therefore, we develop a multiscale approach, which takes the microscopic positions of the molecules into account, while still allowing for efficient stochastic simulations on the mesoscopic level. Finally, we compare on- and off-lattice models on the microscopic level when applied to a crowded environment

Simulation of stochastic diffusion via first exit times

In molecular biology it is of interest to simulate diffusion stochastically. In the mesoscopic model we partition a biological cell into unstructured subvolumes. In each subvolume the number of molecules is recorded at each time step and molecules can jump between neighboring subvolumes to model diffusion. The jump rates can be computed by discretizing the diffusion equation on that unstructured mesh. If the mesh is of poor quality, due to a complicated cell geometry, standard discretization methods can generate negative jump coefficients, which no longer allows the interpretation as the probability to jump between the subvolumes. We propose a method based on the mean first exit time of a molecule from a subvolume, which guarantees positive jump coefficients. Two approaches to exit times, a global and a local one, are presented and tested in simulations on meshes of different quality in two and three dimensions

Stochastic diffusion processes on Cartesian meshes

Diffusion of molecules is simulated stochastically by letting them jump between voxels in a Cartesian mesh. The jump coefficients are first derived using finite difference, finite element, and finite volume approximations of the Laplacian on the mesh. An alternative is to let the first exit time for a molecule in random walk in a voxel define the jump coefficient. Such coefficients have the advantage of always being non-negative. These four different ways of obtaining the diffusion propensities are compared theoretically and in numerical experiments. A finite difference and a finite volume approximation generate the most accurate coefficients