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

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TLDR
Tirosh et al. as discussed by the authors applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells.
Abstract
Single-cell expression profiles of melanoma Tumors harbor multiple cell types that are thought to play a role in the development of resistance to drug treatments. Tirosh et al. used single-cell sequencing to investigate the distribution of these differing genetic profiles within melanomas. Many cells harbored heterogeneous genetic programs that reflected two different states of genetic expression, one of which was linked to resistance development. Following drug treatment, the resistance-linked expression state was found at a much higher level. Furthermore, the environment of the melanoma cells affected their gene expression programs. Science, this issue p. 189 Melanoma cells show transcriptional heterogeneity. 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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Journal ArticleDOI

Automatic Cell Type Annotation Using Marker Genes for Single-Cell RNA Sequencing Data

Yu Chen, +1 more
- 01 Oct 2022 - 
TL;DR: An Automatic Cell type Annotation Method (ACAM) is proposed, which delineates a clear framework to conduct automatic cell annotation through representative cluster identification, representative cluster annotation using marker genes, and the remaining cells’ classification.

Towards a circuit-based understanding of neuropsychiatric disorders: circuit-specific contributions to major depressive disorder and addiction

TL;DR: This dissertation aims to shed light on how discrete aspects of circuits involving the NAc and VP contribute to discrete behavioral aspects of addiction and MDD, and highlights the circuit-specific changes governing neuropsychiatric disorders that may provide a platform for more specific treatments.
Dissertation

Transcriptomic and taxonomic profiling of periodontitis by massively parallel sequencing

Anna Lundmark
TL;DR: The main aim of this thesis was to add to current knowledge of the disease by generating the transcriptomic and taxonomic profiles from gingival tissue and saliva samples collected from patients with periodontitis and from healthy controls.
Journal ArticleDOI

Spatially Annotated Single Cell Sequencing for Unraveling Intratumor Heterogeneity

TL;DR: S spatially annotated singlecell sequencing is introduced, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution, thereby unraveling the mechanistic basis for intratumor heterogeneity.
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Journal Article

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Journal ArticleDOI

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