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Feldman, L.

Publications and source records attributed to Feldman, L..

2 recordsLinked to original sources

Patient-Derived Glioma Models Preserve Tumor Heterogeneity and Identify Stearoyl-CoA Desaturase1 (SCD1) as a Candidate Biomarker for Precision Immunotherapy

Background: Pediatric and adult brain tumors, including glioblastoma, astrocytoma, ependymoma, and medulloblastoma, remain associated with poor prognosis despite advances in surgery, radiation, and chemotherapy. Therapeutic resistance, tumor heterogeneity, and treatment-related toxicity highlight the need for clinically relevant models that enable precision medicine and immunotherapy development. Methods: Freshly dispersed tumors (FDTs), low-passage patient-derived brain tumor (PBT) spheroid lines, and matched patient-derived xenograft (PDX) models were established from patients with primary brain tumors. Models were characterized using single-cell and bulk RNA sequencing, whole-exome sequencing, multiparameter flow cytometry, and immunohistochemistry. PBTs were compared with matched FDTs to evaluate model fidelity. Results: PBT lines were established in approximately 68% of cases and retained key patient-specific genomic alterations, including IDH1, MGMT, TP53, and PTEN, with expression of therapeutically relevant targets, including IL13R2, EGFR, HER2, WNT1, JAK1/2, and NOTCH1-4. Gene expression profiles of PBTs closely correlated with matched FDTs (R = 0.38, P = 0.0038). PBT and PDX models preserved intratumoral heterogeneity and non-clonal populations, enabling identification of therapy-resistant subclones during in vitro selection. Molecular analyses identified Stearoyl-CoA Desaturase1 (SCD1) as an overexpressed biomarker across glioma PBTs and matched patient tumors. Ingenuity Pathway Analysis identified SCD1 as an upstream regulator of EGFR-, TP53-, and CYCS-associated signaling networks implicated in tumor progression and immune suppression. Conclusions: Clinically relevant PBT and matched PDX models recapitulate molecular, transcriptional, and histopathological characteristics of primary brain tumors. These platforms provide tools for biomarker discovery, therapeutic testing, and precision immunotherapy development, while identifying SCD1 as a biomarker and therapeutic target in glioma.

cancer biology

Stimulus-responsive self-assembly of enzymatic fractal structures by computational design

Fractal topologies, which are statistically self-similar over multiple length scales, are pervasive in nature. The recurrence of patterns at increasing length scales in fractal-shaped branched objects, e.g., trees, lungs, and sponges, results in high effective surface areas, and provides key functional advantages, e.g., for molecular trapping and exchange. Mimicking these topologies in designed protein-based assemblies will provide access to novel classes of functional biomaterials for wide ranging applications. Here, we describe a modular, multi-scale computational design method for the reversible self-assembly of proteins into tunable supramolecular fractal-like topologies in response to phosphorylation. Computationally-guided atomic-resolution modeling of fusions of symmetric, oligomeric proteins with Src homology 2 (SH2) binding domain and its phosphorylatable ligand peptide was used to design iterative branching leading to fractal-like assembly formation by enzymes of the atrazine degradation pathway. Structural characterization using various microscopy techniques and Cryo-electron tomography revealed a variety of dendritic, hyperbranched, and sponge-like topologies which are self-similar over three decades ([~]10nm-10m) of length scale, in agreement with models from multi-scale computational simulations. We demonstrate control over mesoscale topology (by linker design), formation dynamics, and functional enhancements due to dynamic multi-component assemblies constructed with three atrazine degradation pathway enzymes. The described design method should enable the construction of a variety of novel, spatiotemporally responsive catalytic biomaterials featuring fractal topologies.

biophysics