Summary Fibroblasts display extensive transcriptional heterogeneity, yet functional annotation and characterization of their heterocellular relationships remains incomplete. Using mass cytometry, we chart the stromal composition of 18 murine tissues and 5 spontaneous tumor models, with an emphasis on mesenchymal phenotypes. This analysis reveals extensive stromal heterogeneity across tissues and tumors, and identifies coordinated relationships between mesenchymal and immune cell subsets in pancreatic ductal adenocarcinoma. Expression of CD105 demarks two stable and functionally distinct pancreatic fibroblast lineages, which are also identified in murine and human healthy tissues and tumors. Whereas CD105-positive pancreatic fibroblasts are permissive for tumor growth in vivo , CD105-negative fibroblasts are highly tumor suppressive. This restrictive effect is entirely dependent on functional adaptive immunity. Collectively, these results reveal two functionally distinct pancreatic fibroblast lineages and highlight the importance of mesenchymal and immune cell interactions in restricting tumor growth.
High-throughput drug combination screening provides a systematic strategy to discover unexpected combinatorial synergies in pre-clinical cell models. However, phenotypic combinatorial screening with multi-dose matrix assays is experimentally expensive, especially when the aim is to identify selective combination synergies across a large panel of cell lines or patient samples. Here we implemented DECREASE, an efficient machine learning model that requires only a limited set of pairwise dose-response measurements for accurate prediction of drug combination synergy and antagonism. Using a compendium of 23,595 drug combination matrices tested in various cancer cell lines, and malaria and Ebola infection models, we demonstrate how cost-effective experimental designs with DECREASE capture almost the same degree of information for synergy and antagonism detection as the fully-measured dose-response matrices. Measuring only the diagonal of the matrix provides an accurate and practical option for combinatorial screening. The open-source web-implementation enables applications of DECREASE to both pre-clinical and translational studies.
BackgroundMoths of genus Dendrolimus (Lepidoptera: Lasiocampidae) are among the major pests of coniferous forests worldwide. Taxonomy and nomenclature of this genus are not entirely established, and there are many species with a controversial taxonomic position. We present a comparative evolutionary analysis of the most economically important Dendrolimus species in Eurasia.ResultsOur analysis was based on the nucleotide sequences of COI and COII mitochondrial genes and ITS2 spacer of nuclear ribosomal genes. All known sequences were extracted from GenBank. Additional 112 new sequences were identified for 28 specimens of D. sibiricus, D. pini, and D. superans from five regions of Siberia and the Russian Far East to be able to compare the disparate data from all previous studies. In total, 528 sequences were used in phylogenetic analysis. Two clusters of closely related species in Dendrolimus were found. The first cluster includes D. pini, D. sibiricus, and D. superans; and the second, D. spectabilis, D. punctatus, and D. tabulaeformis. Species D. houi and D. kikuchii appear to be the most basal in the genus.ConclusionGenetic difference among the second cluster species is very low in contrast to the first cluster species. Phylogenetic position D. tabulaeformis as a subspecies was supported. It was found that D. sibiricus recently separated from D. superans. Integration of D. sibiricus mitochondrial DNA sequences and the spread of this species to the west of Eurasia have been established as the cause of the unjustified allocation of a new species: D. kilmez. Our study further clarifies taxonomic problems in the genus and gives more complete information on the genetic structure of D. pini, D. sibiricus, and D. superans.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0463-5) contains supplementary material, which is available to authorized users.
Pancreatic ductal adenocarcinoma (PDA) is a lethal malignancy with a complex microenvironment. Dichotomous tumour-promoting and -restrictive roles have been ascribed to the tumour microenvironment, however the effects of individual stromal subsets remain incompletely characterised. Here, we describe how heterocellular Oncostatin M (OSM) - Oncostatin M Receptor (OSMR) signalling reprograms fibroblasts, regulates tumour growth and metastasis. Macrophage-secreted OSM stimulates inflammatory gene expression in cancer-associated fibroblasts (CAFs), which in turn induce a pro-tumourigenic environment and engage tumour cell survival and migratory signalling pathways. Tumour cells implanted in Osm-deficient (Osm−/−) mice display an epithelial-dominated morphology, reduced tumour growth and do not metastasise. Moreover, the tumour microenvironment of Osm−/− animals exhibit increased abundance of α smooth muscle actin positive myofibroblasts and a shift in myeloid and T cell phenotypes, consistent with a more immunogenic environment. Taken together, these data demonstrate how OSM-OSMR signalling coordinates heterocellular interactions to drive a pro-tumourigenic environment in PDA.
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