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      Single-cell analyses to tailor treatments

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Single-cell RNA-seq could play a key role in personalized medicine by facilitating characterization of cells, pathways, and genes associated with human diseases such as cancer.

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          Most cited references 10

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          Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.

          To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.
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            Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

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              Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma.

              Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures. We infer that most cancer cells are differentiated along two specialized glial programs, whereas a rare subpopulation of cells is undifferentiated and associated with a neural stem cell expression program. Cells with expression signatures for proliferation are highly enriched in this rare subpopulation, consistent with a model in which CSCs are primarily responsible for fuelling the growth of oligodendroglioma in humans. Analysis of copy number variation (CNV) shows that distinct CNV sub-clones within tumours display similar cellular hierarchies, suggesting that the architecture of oligodendroglioma is primarily dictated by developmental programs. Subclonal point mutation analysis supports a similar model, although a full phylogenetic tree would be required to definitively determine the effect of genetic evolution on the inferred hierarchies. Our single-cell analyses provide insight into the cellular architecture of oligodendrogliomas at single-cell resolution and support the cancer stem cell model, with substantial implications for disease management.
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                Author and article information

                Journal
                Sci Transl Med
                Sci Transl Med
                STM
                Science Translational Medicine
                American Association for the Advancement of Science
                1946-6234
                1946-6242
                20 September 2017
                2017
                : 9
                : 408
                Affiliations
                [1 ]Institute for Medical Engineering & Science (IMES) and Department of Chemistry, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
                [2 ]Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
                [3 ]Ragon Institute of Massachusetts General Hospital, MIT, and Harvard, Cambridge, MA 02139, USA
                [4 ]The Centre for Personalised Medicine and Division of Pediatrics, Department of Clinical and Experimental Medicine, Linköping University, 58183 Linköping, Sweden
                Author notes
                [* ]Corresponding author. Email: shalek@ 123456mit.edu (A.K.S.); mikael.benson@ 123456liu.se (M.B.)
                Article
                STM-09-eaan4730
                10.1126/scitranslmed.aan4730
                5645080
                28931656
                © 2017 The Authors, some rights reserved

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Cancer

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