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Toward understanding and exploiting tumor heterogeneity

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TLDR
A meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity and devised potential solutions are presented here.
Abstract
The extent of tumor heterogeneity is an emerging theme that researchers are only beginning to understand. How genetic and epigenetic heterogeneity affects tumor evolution and clinical progression is unknown. The precise nature of the environmental factors that influence this heterogeneity is also yet to be characterized. Nature Medicine, Nature Biotechnology and the Volkswagen Foundation organized a meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity. Once these key questions were established, the attendees devised potential solutions. Their ideas are presented here.

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Journal ArticleDOI

SCENIC: single-cell regulatory network inference and clustering.

TL;DR: On a compendium of single-cell data from tumors and brain, it is demonstrated that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states.
Journal ArticleDOI

EMT, CSCs, and drug resistance: the mechanistic link and clinical implications

TL;DR: In this paper, the authors discuss the link between the epithelial-to-mesenchymal transition (EMT) and the cancer stem cell (CSC) phenotype and discuss how this knowledge can contribute to improvements in clinical practice.
Journal ArticleDOI

Evidence-Based Diagnosis, Staging, and Treatment of Patients With Hepatocellular Carcinoma.

TL;DR: Studies now aim to identify molecular markers and imaging techniques that can detect patients with HCC at earlier stages and better predict their survival time and response to treatment.
Posted ContentDOI

SCENIC: Single-Cell Regulatory Network Inference And Clustering

TL;DR: SCENIC (Single Cell rEgulatory Network Inference and Clustering) is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs.
Journal ArticleDOI

Rethinking cancer nanotheranostics.

TL;DR: The evolution and state of the art of cancer nanotheranostics is described, with an emphasis on clinical impact and translation, and how diagnosis and therapy are interwoven to solve clinical issues and improve treatment outcomes.
References
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Journal ArticleDOI

Robust enumeration of cell subsets from tissue expression profiles

TL;DR: CIBERSORT outperformed other methods with respect to noise, unknown mixture content and closely related cell types when applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen and fixed tissues, including solid tumors.
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Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells

TL;DR: This work has developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing, which shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays.
Journal ArticleDOI

The prognostic landscape of genes and infiltrating immune cells across human cancers

TL;DR: A pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies is presented and it is found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes.
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