33 research outputs found
Theoretical and Experimental Adsorption Studies of Polyelectrolytes on an Oppositely Charged Surface
Using self-assembly techniques, x-ray reflectivity measurements, and computer
simulations, we study the effective interaction between charged polymer rods
and surfaces. Long-time Brownian dynamics simulations are used to measure the
effective adhesion force acting on the rods in a model consisting of a planar
array of uniformly positively charged, stiff rods and a negatively charged
planar substrate in the presence of explicit monovalent counterions and added
monovalent salt ions in a continuous, isotropic dielectric medium. This
electrostatic model predicts an attractive polymer-surface adhesion force that
is weakly dependent on the bulk salt concentration and that shows fair
agreement with a Debye-Huckel approximation for the macroion interaction at
salt concentrations near 0.1 M. Complementary x-ray reflectivity experiments on
poly(diallyldimethyl ammonium) chloride (PDDA) monolayer films on the native
oxide of silicon show that monolayer structure, electron density, and surface
roughness are likewise independent of the bulk ionic strength of the solution.Comment: Revtex, prb format; uses amssym
Combining the Tyrosine Kinase Inhibitor Cabozantinib and the mTORC1/2 Inhibitor Sapanisertib Blocks ERK Pathway Activity and Suppresses Tumor Growth in Renal Cell Carcinoma.
UNLABELLED: Current treatment approaches for renal cell carcinoma (RCC) face challenges in achieving durable tumor responses due to tumor heterogeneity and drug resistance. Combination therapies that leverage tumor molecular profiles could offer an avenue for enhancing treatment efficacy and addressing the limitations of current therapies. To identify effective strategies for treating RCC, we selected ten drugs guided by tumor biology to test in six RCC patient-derived xenograft (PDX) models. The multitargeted tyrosine kinase inhibitor (TKI) cabozantinib and mTORC1/2 inhibitor sapanisertib emerged as the most effective drugs, particularly when combined. The combination demonstrated favorable tolerability and inhibited tumor growth or induced tumor regression in all models, including two from patients who experienced treatment failure with FDA-approved TKI and immunotherapy combinations. In cabozantinib-treated samples, imaging analysis revealed a significant reduction in vascular density, and single-nucleus RNA sequencing (snRNA-seq) analysis indicated a decreased proportion of endothelial cells in the tumors. SnRNA-seq data further identified a tumor subpopulation enriched with cell-cycle activity that exhibited heightened sensitivity to the cabozantinib and sapanisertib combination. Conversely, activation of the epithelial-mesenchymal transition pathway, detected at the protein level, was associated with drug resistance in residual tumors following combination treatment. The combination effectively restrained ERK phosphorylation and reduced expression of ERK downstream transcription factors and their target genes implicated in cell-cycle control and apoptosis. This study highlights the potential of the cabozantinib plus sapanisertib combination as a promising treatment approach for patients with RCC, particularly those whose tumors progressed on immune checkpoint inhibitors and other TKIs.
SIGNIFICANCE: The molecular-guided therapeutic strategy of combining cabozantinib and sapanisertib restrains ERK activity to effectively suppress growth of renal cell carcinomas, including those unresponsive to immune checkpoint inhibitors
Author Correction:Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts (Nature Genetics, (2021), 53, 1, (86-99), 10.1038/s41588-020-00750-6)
This paper was originally published without open access. As of the date of this correction, the paper is available online as an open-access paper under a Creative Commons Attribution 4.0 International License. *Lists of authors and their affiliations appear online
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Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment.
Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs\u27 recapitulation of human tumors
Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer
Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease
Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples
Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts
Cholesterol-induced modifications in lipid bilayers: a simulation study.
We present analysis of new configurational bias Monte Carlo and molecular dynamics simulation data for bilayers of dipalmitoyl phosphatidyl choline and cholesterol for dipalmitoyl phosphatidyl choline:cholesterol ratios of 24:1, 47:3, 11.5:1, 8:1, 7:1, 4:1, 3:1, 2:1, and 1:1, using long molecular dynamics runs and interspersed configurational bias Monte Carlo to ensure equilibration and enhance sampling. In all cases with cholesterol concentrations above 12.5% the area per molecule of the heterogeneous membrane varied linearly with cholesterol fraction. By extrapolation to pure cholesterol, we find the cross-sectional area of cholesterol in these mixtures is approximately 22.3 A(2). From the slope of the area/molecule relationship, we also find that the phospholipid in these mixtures is in a liquid ordered state with an average cross-sectional area per lipid of 50.7 A(2), slightly above the molecular area of a pure phospholipid gel. For lower concentrations of cholesterol, the molecular area rises above the straight line, indicating the "melting" of at least some of the phospholipid into a fluid state. Analysis of the lateral distribution of cholesterol molecules in the leaflets reveals peaks in radial distributions of cholesterols at multiples of approximately 5 A. These peaks grow in size as the simulation progresses, suggesting a tendency for small subunits of one lipid plus one cholesterol, hydrogen bonded together, to act as one composite particle, and perhaps to aggregate with other composites. Our results are consistent with experimentally observed effects of cholesterol, including the condensation effect of cholesterol in phospholipid monolayers and the tendency of cholesterol-rich domains to form in cholesterol-lipid bilayers. We are continuing to analyze this tendency on longer timescales and for larger bilayer patches