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Träfflista för sökning "WFRF:(Kretzschmar Warren W.) ;lar1:(ki)"

Sökning: WFRF:(Kretzschmar Warren W.) > Karolinska Institutet

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1.
  • Paczkowski, Marcin, et al. (författare)
  • Reciprocal interactions between tumour cell populations enhance growth and reduce radiation sensitivity in prostate cancer
  • 2021
  • Ingår i: Communications Biology. - : Springer Nature. - 2399-3642. ; 4:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Intratumoural heterogeneity (ITH) contributes to local recurrence following radiotherapy in prostate cancer. Recent studies also show that ecological interactions between heterogeneous tumour cell populations can lead to resistance in chemotherapy. Here, we evaluated whether interactions between heterogenous populations could impact growth and response to radiotherapy in prostate cancer. Using mixed 3D cultures of parental and radioresistant populations from two prostate cancer cell lines and a predator-prey mathematical model to investigate various types of ecological interactions, we show that reciprocal interactions between heterogeneous populations enhance overall growth and reduce radiation sensitivity. The type of interaction influences the time of regrowth after radiation, and, at the population level, alters the survival and cell cycle of each population without eliminating either one. These interactions can arise from oxygen constraints and from cellular cross-talk that alter the tumour microenvironment. These findings suggest that ecological-type interactions are important in radiation response and could be targeted to reduce local recurrence. Using co-culture experiments and mathematical modelling, Paczkowski et al discover that prostate cancer spheroids comprising mixed tumour cell populations display enhanced growth and reduced radiation sensitivity due to competitive and antagonistic interactions between cell populations. This interdisciplinary approach reveals a role for ecological-type interactions in the radiation response and may be used to study other cancer types.
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2.
  • Westrin, Karl Johan, 1989-, et al. (författare)
  • ClusTrast : a short read de novo transcript isoform assembler guided by clustered contigs
  • 2024
  • Ingår i: BMC Bioinformatics. - : Springer Nature. - 1471-2105. ; 25:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Transcriptome assembly from RNA-sequencing data in species without a reliable reference genome has to be performed de novo, but studies have shown that de novo methods often have inadequate ability to reconstruct transcript isoforms. We address this issue by constructing an assembly pipeline whose main purpose is to produce a comprehensive set of transcript isoforms. Results: We present the de novo transcript isoform assembler ClusTrast, which takes short read RNA-seq data as input, assembles a primary assembly, clusters a set of guiding contigs, aligns the short reads to the guiding contigs, assembles each clustered set of short reads individually, and merges the primary and clusterwise assemblies into the final assembly. We tested ClusTrast on real datasets from six eukaryotic species, and showed that ClusTrast reconstructed more expressed known isoforms than any of the other tested de novo assemblers, at a moderate reduction in precision. For recall, ClusTrast was on top in the lower end of expression levels (<15% percentile) for all tested datasets, and over the entire range for almost all datasets. Reference transcripts were often (35–69% for the six datasets) reconstructed to at least 95% of their length by ClusTrast, and more than half of reference transcripts (58–81%) were reconstructed with contigs that exhibited polymorphism, measuring on a subset of reliably predicted contigs. ClusTrast recall increased when using a union of assembled transcripts from more than one assembly tool as primary assembly. Conclusion: We suggest that ClusTrast can be a useful tool for studying isoforms in species without a reliable reference genome, in particular when the goal is to produce a comprehensive transcriptome set with polymorphic variants.
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