Biology subjects

Conrad, C.

Publications and source records attributed to Conrad, C..

3 recordsLinked to original sources

bioRxiv2018

pheno-seq - linking 3D phenotypes of clonal tumor spheroids to gene expression

3D-culture systems have advanced cancer modeling by reflecting physiological characteristics of in-vivo tissues, but our understanding of functional intratumor heterogeneity including visual phenotypes and underlying gene expression is still limited. Single-cell RNA-sequencing is the method of choice to dissect transcriptional tumor cell heterogeneity in an unbiased way, but this approach is limited in correlating gene expression with contextual cellular phenotypes.\n\nTo link morphological features and gene expression in 3D-culture systems, we present pheno-seq for integrated high-throughput imaging and transcriptomic profiling of clonal tumor spheroids. Specifically, we identify characteristic EMT expression signatures that are associated with invasive growth behavior in a 3D breast cancer model. Additionally, pheno-seq determined transcriptional programs containing lineage-specific markers that can be linked to heterogeneous proliferative capacity in a patient-derived 3D model of colorectal cancer. Finally, we provide evidence that pheno-seq identifies morphology-specific genes that are missed by scRNA-seq and inferred single-cell regulatory states without acquiring additional single cell expression profiles. We anticipate that directly linking molecular features with patho-phenotypes of cancer cells will improve the understanding of intratumor heterogeneity and consequently be useful for translational research.

genomics↗

bioRxiv2017

Unraveling mitotic protein networks by 3D multiplexed epitope drug screening

Three-dimensional protein localization intricately determines the functional coordination of cellular processes. The complex spatial context of protein landscape has been assessed by multiplexed immunofluorescent staining1-3 or mass spectrometry4, applied to 2D cell culture with limited physiological relevance5 or tissue sections. Here, we present 3D SPECS, an automated technology for 3D Spatial characterization of Protein Expression Changes by microscopic Screening. This workflow encompasses iterative antibody staining of proteins, high-content imaging, and machine learning based classification of mitotic states. This is followed by mapping of spatial protein localization into a spherical, cellular coordinate system, the basis used for model-based prediction of spatially resolved affinities of various mitotic proteins. As a proof-of-concept, we mapped twelve epitopes in 3D cultured epithelial breast spheroids and investigated the network effects of mitotic cancer drugs with known limited success in clinical trials6-8. Our approach reveals novel insights into spindle fragility and global chromatin stress, and predicts unknown interactions between proteins in specific mitotic pathways. 3D SPECSs ability to map potential drug targets by multiplexed immunofluorescence in 3D cell cultured models combined with our automized high content assay will inspire future functional protein expression and drug assays.

systems biology↗

bioRxiv2017

Resolving Drug Effects In Patient-Derived Cancer Cells Links Organoid Responses To Genome Alterations

Cancer drug screening in patient-derived cells holds great promise for personalized oncology and drug discovery but lacks standardization. Whether cells are cultured as conventional monolayer or advanced organoid cultures influences drug effects and thereby drug selection and clinical success. To precisely compare drug profiles in differently cultured primary cells, we developed DeathPro, an automated microscopy-based assay to resolve drug-induced cell death and proliferation inhibition. Using DeathPro, we screened cells from ovarian cancer patients in monolayer or organoid culture with clinically relevant drugs. Drug-induced growth arrest and efficacy of cytostatic drugs differed between the two culture systems. Interestingly, drug effects in organoids were more diverse and had lower therapeutic potential. Genomic analysis revealed novel links between drug sensitivity and DNA repair deficiency in organoids that were undetectable in monolayers. Thus, our results highlight the dependency of cytostatic drugs and pharmacogenomic associations on culture systems, and guide culture selection for drug tests.

cancer biology↗