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Comprehensive molecular portraits of human breast tumours

A. McCullough
- 01 Jan 2013 - 
- Vol. 2013, pp 286-288
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This article is published in Yearbook of Pathology and Laboratory Medicine.The article was published on 2013-01-01. It has received 5867 citations till now.

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Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival

TL;DR: For 515 patients from six tumor sites, RNA-seq data from The Cancer Genome Atlas was used to identify mutations that were predicted to be immunogenic in that they yielded mutational epitopes presented by the MHC proteins encoded by each patient's autologous HLA-A alleles that were associated with increased patient survival.
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Forkhead box proteins: tuning forks for transcriptional harmony

TL;DR: The functional complexities of FOX proteins are coming to light and have established these transcription factors as possible therapeutic targets and putative biomarkers for specific cancers.
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Multi-omics Data Integration, Interpretation, and Its Application.

TL;DR: This review collected the tools and methods that adopt integrative approach to analyze multiple omics data and summarized their ability to address applications such as disease subtyping, biomarker prediction, and deriving insights into the data.
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Microbiome analyses of blood and tissues suggest cancer diagnostic approach

TL;DR: Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.
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Journal ArticleDOI

Comprehensive molecular portraits of human breast tumours

Daniel C. Koboldt, +355 more
- 04 Oct 2012 - 
TL;DR: The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.