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10.1126/science.aai8478 http://scihub22266oqcxt.onion/10.1126/science.aai8478 C5519096!5519096!28360267     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Science 2017 ; 355 (6332): ä Nephropedia Template TP {{tp|p=28360267|t=2017. Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq |pdf=|usr=}}{{28360267}} gab.com Text Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq JO: Science http://www.kidney.de/pget.php?&tw=1&pmid=28360267 #FOAvip INTRODUCTION: Tumor fitness, evolution, and resistance to therapy are governed by selection of malignant cells with specific genotypes, by expression programs related to cellular phenotypes, and by influences of the tumor microenvironment (TME). Although bulk tumor analysis can interrogate the genetic state of tumor cells with high precision, bulk expression profiles average the diverse cells within each tumor, thereby masking critical differences and providing limited insight into cancer cell programs and TME influences. Single-cell RNA sequencing (scRNA-seq) can help to address those challenges but incurs financial and logistic considerations, including the time required to accrue large cohorts of fresh tumor specimen for single-cell analysis. RATIONALE: We reasoned that scRNA-seq of a limited number of representative tumors could be combined with bulk data from large cohorts to decipher differences between tumor subclasses. In this approach, bulk samples collected for large cohorts, such as from The Cancer Genome Atlas (TCGA), are first used to define the combined effects of differences in cancer cell genotypes, phenotypes, and the composition of the TME. Single-cell analysis of a limited set of representative tumors is then used to distinguish those effects. We applied this approach to understand the differences between two types of isocitrate dehydrogenase (IDH)-mutant gliomas: astrocytoma (IDH-A) and oligodendroglioma (IDH-O). IDH-A and IDH-O are distinguished by co-occurring signature genetic events and by histopathology and are thought to recapitulate distinct glial lineages. By combining 9879 scRNA-seq profiles from 10 IDH-A tumors, 4347 scRNA-seq profiles from six IDH-O tumors, and 165 TCGA bulk RNA profiles, we could decipher differences between these two tumor types at single-cell resolution. RESULTS: We find that differences in bulk expression profiles between IDH-A and IDH-O are primarily explained by the impact of signature genetic events and TME composition, but not by distinct expression programs of glial lineages in the malignant cells. We infer that both IDH-A and IDH-O share the same developmental hierarchy, consisting in each case of three subpopulations of malignant cells: nonproliferating cells differentiated along the astrocytic and oligodendrocytic lineages, and proliferative undifferentiated cells that resemble neural stem/progenitor cells. By analyzing tumors of different clinical grades, we observe that higher-grade tumors present enhanced proliferation, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia programs in the TME. CONCLUSION: Our approach provides a general framework to decipher differences between classes of human tumors by decoupling cancer cell genotypes, phenotypes, and the composition of the TME. The shared glial lineages and developmental hierarchies observed in IDH-A and IDH-O suggest a common progenitor for all IDH-mutant gliomas, shedding light on a longstanding debate in gliomagenesis. In contrast to the similarity in glial lineages, IDH-A and IDH-O differ significantly in their TME, and in particular in the abundance of microglia/macrophage cells. Microglia and macrophages also differ between IDH-A tumors of different grades. Our study redefines the cellular composition of human IDH-mutant gliomas, with important implications for disease management. Twit Text FOAVip Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq ????Science http://www.kidney.de/pget.php?&tw=1&pmid=28360267 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28360267 #FOAvip English Wikipedia <ref>{{Cite pmid|28360267}}</ref> Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq #MMPMID28360267 Venteicher AS; Tirosh I; Hebert C; Yizhak K; Neftel C; Filbin MG; Hovestadt V; Escalante LE; Shaw ML; Rodman C; Gillespie SM; Dionne D; Luo CC; Ravichandran H; Mylvaganam R; Mount C; Onozato ML; Nahed BV; Wakimoto H; Curry WT; Iafrate AJ; Rivera MN; Frosch MP; Golub TR; Brastianos PK; Getz G; Patel AP; Monje M; Cahill DP; Rozenblatt-Rosen O; Louis DN; Bernstein BE; Regev A; Suvà ML Science 2017[Mar]; 355 (6332): ä PMID28360267show ga INTRODUCTION: Tumor fitness, evolution, and resistance to therapy are governed by selection of malignant cells with specific genotypes, by expression programs related to cellular phenotypes, and by influences of the tumor microenvironment (TME). Although bulk tumor analysis can interrogate the genetic state of tumor cells with high precision, bulk expression profiles average the diverse cells within each tumor, thereby masking critical differences and providing limited insight into cancer cell programs and TME influences. Single-cell RNA sequencing (scRNA-seq) can help to address those challenges but incurs financial and logistic considerations, including the time required to accrue large cohorts of fresh tumor specimen for single-cell analysis. RATIONALE: We reasoned that scRNA-seq of a limited number of representative tumors could be combined with bulk data from large cohorts to decipher differences between tumor subclasses. In this approach, bulk samples collected for large cohorts, such as from The Cancer Genome Atlas (TCGA), are first used to define the combined effects of differences in cancer cell genotypes, phenotypes, and the composition of the TME. Single-cell analysis of a limited set of representative tumors is then used to distinguish those effects. We applied this approach to understand the differences between two types of isocitrate dehydrogenase (IDH)-mutant gliomas: astrocytoma (IDH-A) and oligodendroglioma (IDH-O). IDH-A and IDH-O are distinguished by co-occurring signature genetic events and by histopathology and are thought to recapitulate distinct glial lineages. By combining 9879 scRNA-seq profiles from 10 IDH-A tumors, 4347 scRNA-seq profiles from six IDH-O tumors, and 165 TCGA bulk RNA profiles, we could decipher differences between these two tumor types at single-cell resolution. RESULTS: We find that differences in bulk expression profiles between IDH-A and IDH-O are primarily explained by the impact of signature genetic events and TME composition, but not by distinct expression programs of glial lineages in the malignant cells. We infer that both IDH-A and IDH-O share the same developmental hierarchy, consisting in each case of three subpopulations of malignant cells: nonproliferating cells differentiated along the astrocytic and oligodendrocytic lineages, and proliferative undifferentiated cells that resemble neural stem/progenitor cells. By analyzing tumors of different clinical grades, we observe that higher-grade tumors present enhanced proliferation, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia programs in the TME. CONCLUSION: Our approach provides a general framework to decipher differences between classes of human tumors by decoupling cancer cell genotypes, phenotypes, and the composition of the TME. The shared glial lineages and developmental hierarchies observed in IDH-A and IDH-O suggest a common progenitor for all IDH-mutant gliomas, shedding light on a longstanding debate in gliomagenesis. In contrast to the similarity in glial lineages, IDH-A and IDH-O differ significantly in their TME, and in particular in the abundance of microglia/macrophage cells. Microglia and macrophages also differ between IDH-A tumors of different grades. Our study redefines the cellular composition of human IDH-mutant gliomas, with important implications for disease management. äDecoupling genetics, lineages, and microenvironment in IDH-mutant glio(epmc).pdf DeepDyve Pubget Overpricing