Similar Datasets
Project description:Heterogeneity between patients poses a significant challenge in cancer drug development. Although success of a drug candidate in the clinic depends on efficacy across large numbers of diverse patients, only a few in vivo preclinical models are used for assaying a preclinical drug candidate due to the lack of scalability of traditional xenograft models. To address this limitation, we developed GENEVA, a scalable platform that enables the measurement of molecular and phenotypic responses to drug perturbations at single-cell resolution, both in 3D and in vivo. GENEVA models the genetic diversity of cancer by combining multiple patient-derived cell lines and cancer cell lines into pooled 3D cultures and xenograft models, allowing us to study drug responses across a wide range of genetic backgrounds within a single experiment. This platform integrates high-resolution transcriptomics with multiplexed single-cell profiling, providing a unique ability to uncover the interplay between cancer genotypes and drug responses. In this study, we apply GENEVA to investigate KRAS G12C inhibitors and demonstrate that mitochondrial activation is a key driver of cell death following KRAS inhibition. Additionally, we identify epithelial to mesenchymal transition (EMT) as a prominent resistance mechanism to KRAS G12C inhibition using in vivo GENEVA mice. These findings highlight the utility of GENEVA in identifying novel therapeutic targets and optimizing combination therapies, while underscoring its potential to bridge the gap between preclinical cancer models and patient outcomes by modeling the complexity of tumor heterogeneity in a scalable and robust assay.
2024-12-26 | GSE283141 | GEO
Project description:Heterogeneity between patients poses a significant challenge in cancer drug development. Although success of a drug candidate in the clinic depends on efficacy across large numbers of diverse patients, only a few in vivo preclinical models are used for assaying a preclinical drug candidate due to the lack of scalability of traditional xenograft models. To address this limitation, we developed GENEVA, a scalable platform that enables the measurement of molecular and phenotypic responses to drug perturbations at single-cell resolution, both in 3D and in vivo. GENEVA models the genetic diversity of cancer by combining multiple patient-derived cell lines and cancer cell lines into pooled 3D cultures and xenograft models, allowing us to study drug responses across a wide range of genetic backgrounds within a single experiment. This platform integrates high-resolution transcriptomics with multiplexed single-cell profiling, providing a unique ability to uncover the interplay between cancer genotypes and drug responses. In this study, we apply GENEVA to investigate KRAS G12C inhibitors and demonstrate that mitochondrial activation is a key driver of cell death following KRAS inhibition. Additionally, we identify epithelial to mesenchymal transition (EMT) as a prominent resistance mechanism to KRAS G12C inhibition using in vivo GENEVA mice. These findings highlight the utility of GENEVA in identifying novel therapeutic targets and optimizing combination therapies, while underscoring its potential to bridge the gap between preclinical cancer models and patient outcomes by modeling the complexity of tumor heterogeneity in a scalable and robust assay.
2024-12-26 | GSE282350 | GEO
Project description:Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations
| PRJNA1193214 | ENA
Project description:Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations [11 cancer cell lines]
| PRJNA1188170 | ENA
Project description:Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations [8 cancer cell lines]
| PRJNA1192231 | ENA
Project description:Plant responses to environmental heterogeneity depend on life-history traits, which could relate to phenotypical and genetic characteristics. To elucidate this relationship, we examined the variation in population genetics and functional traits of short- and long-lived Artemisia species that are co-occurring in the steppes of Mongolia. Mongolian steppes represent stressful and water-limited habitats, demanding phenotypic modifications in the short term and/or genetic adaptation in the long term. However, detailed knowledge is missing about both plant phenotypic and genetic differentiation, and their interrelationships in temperate grasslands. Here, we investigated 21 populations of the widely distributed subshrub Artemisia frigida and the herbaceous biennial Artemisia scoparia. Genetic variation was assessed with newly developed simple sequence repeats (SSRs) markers. Functional trait data were collected from each individual, and data on environmental variables was collected for each population. We detected significantly higher genetic diversity in the biennial species (H E = 0.86) compared with the perennial (H E = 0.79). For both species, the largest share of genetic variation was partitioned within populations (96%). Population genetic structure in the biennial A. scoparia was weak, while the perennial A. frigida showed some spatial genetic structure, which was impacted by geographical factors, soil nutrients, and precipitation amount. Morphology-related functional traits (i.e., plant height) were predominantly associated with environmental variables rather than with genetic variation, whereas physiology-related trait (i.e., specific leaf area [SLA]) was partly genetically determined.
| S-EPMC11486663 | biostudies-literature
Project description:The distribution of plasmids related to the fertility factor F was examined in the ECOR reference collection of Escherichia coli. Probes specific for four F-related genes were isolated and used to survey the collection by DNA hybridization. To estimate the genetic diversity of genes in F-like plasmids, DNA sequences were obtained for four plasmid genes. The phylogenetic relationships among the plasmids in the ECOR strains is very different from that of the strains themselves. This finding supports the view that plasmid transfer has been frequent within and between the major groups of ECOR. Furthermore, the sequences indicate that recombination between genes in plasmids takes place at a considerably higher frequency than that observed for chromosomal genes. The plasmid genes, and by inference the plasmids themselves, are mosaic in structure with different regions acquired from different sources. Comparison of gene sequences from a variety of naturally occurring plasmids suggested a plausible donor of some of the recombinant regions as well as implicating a chi site in the mechanism of genetic exchange. The relatively high rate of recombination in F-plasmid genes suggests that conjugational gene transfer may play a greater role in bacterial population structure than previously appreciated.
| S-EPMC1207381 | biostudies-other
Project description:BackgroundHuman pathogens transmitted through environmental pathways are subject to stress and pressures outside of the host. These pressures may cause pathogen pathovars to diverge in their environmental persistence and their infectivity on an evolutionary time-scale. On a shorter time-scale, a single-genotype pathogen population may display wide variation in persistence times and exhibit biphasic decay.MethodsWe use a transmission modeling framework to develop an infectious disease model with biphasic pathogen decay. We take a differential algebra approach to assessing model identifiability, calculate basic reproduction numbers by the next generation method, and use simulation to explore model dynamics.ResultsFor both long and short time-scales, we demonstrate that epidemic-potential-preserving trade-offs have implications for epidemic dynamics: less infectious, more persistent pathogens cause epidemics to progress more slowly than more infectious, less persistent (labile) pathogens, even when the overall risk is the same. Using identifiability analysis, we show that the usual disease surveillance data does not sufficiently inform these underlying pathogen population dynamics, even when combined with basic environmental monitoring data. However, risk could be indirectly ascertained by developing methods to separately monitor labile and persistent subpopulations. Alternatively, determining the relative infectivity of persistent pathogen subpopulations and the rates of phenotypic conversion will help ascertain how much disease risk is associated with the long tails of biphasic decay.ConclusionA better understanding of persistence-infectivity trade-offs and associated dynamics can improve our ecological understanding of environmentally transmitted pathogens, as well as our risk assessment and disease control strategies.
| S-EPMC6530054 | biostudies-literature
Project description:BACKGROUND: Although horizontal gene transfer plays a pivotal role in bacteriophage evolution, many lytic phage genomes are clearly shaped by vertical evolution. We investigated the influence of minor genomic deletions and insertions on various phage-related phenotypic and serological properties. FINDINGS: We collected ten different isolates of Pseudomonas aeruginosa bacteriophage ?KMV. All sequenced genomes (42-43 kb, long direct terminal repeats) are nearly identical, which intuitively implied strongly similar infections cycles. However, their latent periods vary between 21 and 28 minutes and they are able to lyse between 5 and 58% of a collection of 107 clinical P. aeruginosa strains. We also noted that phages with identical tail structures displayed profound differences in host spectra. Moreover, point mutations in tail and spike proteins were sufficient to evade neutralization by two phage-specific antisera, isolated from rabbits. CONCLUSION: Although all analyzed phages are 83-97% identical at the genome level, they display a surprisingly large variation in various phenotypic properties. The small overlap in host spectrum and their ability to readily escape immune defences against a nearly identical phage are promising elements for the application of these phages in phage therapy.
| S-EPMC3072928 | biostudies-literature
Project description:When adaptive phenotypic variation or quantitative trait loci map within an inverted segment of a chromosome, researchers often despair because the suppression of crossing over will prevent the discovery of selective target genes that established the rearrangement. If an inversion polymorphism is old enough, then the accumulation of gene conversion tracts offers the promise that quantitative trait loci or selected loci within inversions can be mapped. The inversion polymorphism of Drosophila pseudoobscura is a model system to show that gene conversion analysis is a useful tool for mapping selected loci within inversions. D. pseudoobscura has over 30 different chromosomal arrangements on the third chromosome (Muller C) in natural populations and their frequencies vary with changes in environmental habitats. Statistical tests of five D. pseudoobscura gene arrangements identified outlier genes within inverted regions that had potentially heritable variation, either fixed amino acid differences or differential expression patterns. We use genome sequences of the inverted third chromosome (Muller C) to infer 98,443 gene conversion tracts for a total coverage of 142 Mb or 7.2× coverage of the 19.7 Mb chromosome. We estimated gene conversion tract coverage in the 2,668 genes on Muller C and tested whether gene conversion coverage was similar among arrangements for outlier vs non-outlier loci. Outlier genes had lower gene conversion tract coverage among arrangements than the non-outlier genes suggesting that selection removes exchanged DNA in the outlier genes. These data support the hypothesis that the third chromosome in D. pseudoobscura captured locally adapted combinations of alleles prior to inversion mutation events.
| S-EPMC11457094 | biostudies-literature