Biology subjects

Kemkar, S.

Publications and source records attributed to Kemkar, S..

3 recordsLinked to original sources

bioRxiv2026

Coupled Cell-Intrinsic and Microenvironmental Heterogeneity Drives Divergent Trajectories in Castration-Resistant Prostate Cancer

Castration-resistant prostate cancer emerges from coupling between cell-intrinsic heterogeneity and microenvironmental constraints. Mechanistically dissecting this coupling, rather than either factor in isolation, is the central aim of this study. To systematically study the effect of intrinsic and extrinsic spatial axes on disease trajectories, we developed an integrated multiscale framework: a cellular signaling model (MHS) parameterized with TCGA genomic data from control, biochemical recurrence (BR), and treatment-resistant (TR) cohorts, coupled to a spatial agent-based model (ABM). Machine learning surrogates trained on the MHS model identified PTEN, MDM4, and AR as dominant intrinsic drivers, using SHAP-based feature ranking. Clinical validation via Kaplan-Meier and Cox regression across cBioPortal cohorts confirmed these rankings: AR alterations (median OS 20 vs. 86 months), PTEN loss (54 vs. 77 months), and MDM4 amplification (33 vs. 75 months) predicted poor overall survival outcomes independently. At the tissue scale, ABM simulations were run to study the effect of microenvironmental (cell-extrinsic) factors such as physical confinement, androgen uptake kinetics, and adhesion-motility strength, on disease progression. This spatiotemporal analysis revealed that identical genetic alterations produce varied selection outcomes depending on microenvironmental context. Extending this coupling logic to the individual patient level, we parameterized the MHS model using gene expression profiles from 14 patients in the EUREKA1 prospective registry. Patient-specific androgen sensitivity ratios, the ratio of net cell growth under high versus low testosterone, stratified patients by model-predicted androgen dependence without requiring longitudinal PSA observations and showed that PTEN deletion shifts the proliferative response toward androgen independence in a patient-specific magnitude set by the broader expression background. This provides a model-based route from genomic data at diagnosis to personalized prediction of ADT resistance risk. Together, these findings establish that CRPC emergence is an emergent property of the intrinsic-extrinsic coupling, that neither molecular nor spatial analyses in isolation can predict clinical trajectories, and that mechanistic integration of both is required for accurate patient stratification.

systems biology↗

bioRxiv2025

Modeling tumor transport and growth with poroelastic biopolymer networks

The mechanical properties of the extracellular matrix (ECM) regulate tumor growth and invasion in the tumor microenvironment. Models of biopolymer networks have been used to investigate the impact of elasticity and viscoelasticity of ECM on tumor behavior. Under tumor compression, these networks also show poroelastic behavior that is governed by the resistance to water flow through their pores. This work investigates the hypothesis that poroelastic properties regulate tumor growth. Here, alginate hydrogels with tunable ionic and hybrid ionic/covalent crosslinking are used as a model biopolymer system. Hydrogel stiffness, viscoelasticity, and stress relaxation behavior were characterized using stepwise axial compression. Among these properties, we find poroelastic fluid outflow dominates ECM stress relaxation, as the measured water flux was significantly affected under compression. Continuum mechanics-based modeling was developed to formulate and calculate the chemical potential gradients of water (solvent) in the hydrogels under compression. This framework was extended into an advection-diffusion framework to quantify growth factor (solute) distribution under varying strengths of stress and diffusion indexed by the relative strength of convective to diffusive transport, characterized by the Peclet number. An agent-based computational simulation showed that tumor growth was affected by Peclet number. Together, these results highlight the role of the poroelastic properties of ECM on water flux and transport in the tumor microenvironment.

biophysics↗

bioRxiv2021

Selection in a growing bacterial/yeast colony biases results of mutation accumulation experiments.

Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments performed with organisms such as Drosophila have an effective population size of one. However, in MA experiments with bacteria and yeast, a single founder is allowed to grow to a size of a colony (~108). The effective population size in these experiments is of the order of 10. In this scenario, while it is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth and therefore, the MA experiment; this effect has not been tested explicitly. In this work, we simulate colony growth and perform an MA experiment, and demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over represented by a factor greater than two. The DFE of beneficial and deleterious mutations are accurately captured in an MA experiment. We show that the effect of selection in a growing colony varies non-monotonically and that, in the face of natural selection dictating an MA experiment, estimates of mutation rate of an organism is not trivial. We perform experiments with 160 MA lines of E. coli, and demonstrate that rate of change of mean fitness is a non-monotonic function of the colony size, and that selection acts differently in different sectors of a growing colony. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

evolutionary biology↗