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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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Integrative analysis of 111 reference human epigenomes

TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.

Revealing the vectors of cellular identity with single-cell genomics

TL;DR: Single-cell genomics has now made it possible to create a comprehensive atlas of human cells and has reopened definitions of a cell's identity and of the ways in which identity is regulated by the cell's molecular circuitry.
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The Tabula Sapiens: a multiple organ single cell transcriptomic atlas of humans

Stephen R. Quake
- 04 Mar 2022 - 
TL;DR: A human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor, enabled molecular characterization of more than 400 cell types, their distribution across tissues and tissue specific variation in gene expression.
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Macrophages as tools and targets in cancer therapy

TL;DR: In this paper , the authors proposed a set of macrophage-targeting strategies that include inhibitors of cytokines and chemokines involved in the recruitment and polarization of tumour-promoting myeloid cells as well as activators of their antitumorigenic and immunostimulating functions.
References
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SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq Data

TL;DR: SCSA is presented, an automatic tool to annotate cell types from scRNA-seq data, based on a score annotation model combining differentially expressed genes (DEGs) and confidence levels of cell markers from both known and user-defined information.
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Single-Cell RNA-Seq Reveals Dynamic Change in Tumor Microenvironment During Pancreatic Ductal Adenocarcinoma Malignant Progression

TL;DR: It was found that ductal cells were not dominant component while tumor infiltrating immune cells and pancreatic stellate cells gradually accumulated during tumor development, which is valuable for understanding the crosstalk inside tumor.
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Measuring intratumor heterogeneity by network entropy using RNA-seq data

TL;DR: The proposed transcriptome-based ITH is useful to characterize heterogeneity of a tumor sample at RNA level and it is found that cell cycle related pathways have significant contribution to increasing heterogeneity on the network during clonal evolution.
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Comparing subjective and digital image analysis HER2/neu expression scores with conventional and modified FISH scores in breast cancer

TL;DR: Comparisons with conventional and modified FISH scores in breast cancer suggest that HER2/neu DIA scoring is a cost-effective supplementary tool in surgical pathology and was better correlated with HercepTest 3+ consensus and DIA scores than were conventional Fish scores.
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Multi-omics profiling of the tumor microenvironment: Paving the way to precision immuno-oncology

TL;DR: This Mini Review gives an overview of the methodologies that allow studying the heterogeneity of the TME from multi-omics data generated from bulk samples, single cells, or images of tumor-tissue slides, and discusses how this broader vision of the cellular heterogeneity and plasticity of tumors offers the opportunity to rationally design precision immuno-oncology treatments.
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