Month: December 2016

iDriver

[PMID:27797769] [Bioinformatics]

Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework

“integrated mutations, gene expression, DNA copy numbers, DNA methylation and protein abundance, all available in The Cancer Genome Atlas (TCGA) and developed iDriver, a non-parametric Bayesian framework based on multivariate statistical modeling to identify driver genes in an unsupervised fashion.”

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Ark

[PMID:28003258] [Bioinformatics]

The Ark: a customizable web-based data management tool for health and medical research

“The system provides data management for core research information including demographic, phenotype, biospecimen and pedigree data, in addition to supporting typical investigator requirements such as tracking participant consent and correspondence, whilst also being able to generate custom data exports and reports.” It could be a good alternative to Progeny.

DISCOVER

[PMID:27986087] [Genome Biology]

A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence

“In cancer, mutually exclusive or co-occurring somatic alterations across genes can suggest functional interactions. Existing tests for such patterns make the unrealistic assumption of identical gene alteration probabilities across tumors. We present Discrete Independence Statistic Controlling for Observations with Varying Event Rates (DISCOVER), a novel test that is more sensitive than other methods and controls its false positive rate. A pan-cancer analysis using DISCOVER finds no evidence for widespread co-occurrence, and most co-occurrences previously detected do not exceed expectation by chance. Many mutual exclusivities are identified involving well-known genes related to cell cycle and growth factor signaling, as well as lesser known regulators of Hedgehog signaling.” “We compared the performance of DISCOVER to that of several other published mutual exclusivity tests: MEMo, muex, mutex, CoMEt, MEGSA, and TiMEx.”

DCCs

[PMID:27974798] [Nature]

Mechanism of early dissemination and metastasis in Her2+ mammary cancer

[PMID:27974799] [Nature]

Early dissemination seeds metastasis in breast cancer

“progesterone-induced signalling triggers migration of cancer cells from early lesions shortly after HER2 activation, but promotes proliferation in advanced primary tumour cells. The switch from migration to proliferation was regulated by increased HER2 expression and tumour-cell density involving microRNA-mediated progesterone receptor downregulation, and was reversible. Cells from early, low-density lesions displayed more stemness features, migrated more and founded more metastases than cells from dense, advanced tumours.”

[PMID:27974802] [Nature]

Metastasis: Pathways of parallel progression

On the contrary, a recent paper supports the model of late dissemination of breast cancer cells to the bone marrow. Work from Kevin White and Peter Van Loo.

[PMID:27931250] [Genome Biology]

Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing