March highlights of Genome Medicine: epigenetics, classifying cancers, next-generation sequencing and more

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The March issue of Genome Medicine  has a range of exciting articles across our broad scope.

Research from Andrew Teschendorff and colleagues demonstrates that epigenetic variation in normal cells collected before the onset of disease is predictive of future cervical cancer risk. Their findings could provide the basis for an innovative clinical test that can diagnose cancer years in advance of any signs or symptoms. A more detailed summary of the study can be read in this blog. Further highlighting the promise of epigenetic variation for diagnosing cancer, Moshe Szyf provides a comprehensive review of approaches for classifying breast cancer subtypes using DNA methylation signatures.

New and improved methods for classifying and differentiating cancer subgroups are important for translating cancer biomarker discovery into clinical practice. In another research article published this month, Gunes Gundem and Nuria Lopez-Bigas describe a computational method for analyzing transcriptomic changes specific to different tumor types,  and defining clinically relevant patient subgroups based on unique gene expression profiles. By applying their approach, sample-level enrichment analysis (SLEA), to gene expression datasets, the authors detect shared stress phenotypes across multiple cancer types and a chromosomal instability gene signature associated with worse prognosis in breast cancer.

A new computational method with a different purpose is also reported in this issue. This method, Haplous, which was developed by Sampsa Hautaniemi’s group, involves a rule-based approach for identifying rare identical-by-descent haplotypes from genome-wide data. Using Haplous, the authors identify haplotypes with potential disease-causing variants in familial lymphoma data, to which linkage analysis could not be applied.

Three Research Highlights were published in March, including Si Houn Hahn’s discussion of targeted next-generation sequencing (NGS) approaches for diagnosing mitochondrial disease. Hahn emphasizes that the genetic heterogeneity of mitochondrial disorders is much broader than previously thought, so NGS could be a useful clinical tool for screening the most relevant candidate genes.  The article has been highly accessed, highlighting the ongoing interest in sequencing-based approaches for diagnosing and understanding disease.

Capturing the excitement about recent advances in the interconnected fields of systems biology and genomics, Barbara Stranger and colleagues report on the Keystone Symposium ‘Complex Traits: Genomics and Computational approaches’. One of the topics discussed at this meeting was strategies for drug repositioning, and in this article, Yvonne Li and Steven Jones review the current approaches for repositioning drugs and the challenges that remain.

Finally, Stephen Kingsmore and colleagues reflect on the potential impact of next-generation sequencing and bioinformatic approaches on community genetics programs in low- and middle-income countries.

Look out for the April issue of Genome Medicine, which is a special issue focusing on Disease Metabolomics, and will feature articles from leading researchers in this field.

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