Multiple Molecular Data Sets and the Classification of Adult Diffuse Gliomas  

Oleh:

Ellison, David W.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The New England Journal of Medicine (keterangan: ada di Proquest) vol. 372 no. 26 (Jun. 2015), page 2555-2557.

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Perpustakaan FK Nomor Panggil: N08.K Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In these days of individualized precision medicine and “big data” generated by means of next-generation sequencing, there are expectations that new therapeutic strategies for cancer will be quickly conceived and then realized in the clinic. Next-generation sequencing has certainly provided new insights into some cancers, stimulating the study of underlying biologic mechanisms and the development of targeted treatments. But even when whole-genome sequencing reveals that the genetic landscape of a cancer consists largely of known recurrent mutations, the power of data sets from multiple complementary molecular platforms — exome, transcriptome, and microRNA sequencing alongside DNA methylation, DNA copy number, and protein arrays — to reveal how the disease might be classified or stratified at the molecular level presents an opportunity to reappraise clinical strategies. This opportunity has arisen with the publication of two articles describing the analysis of such data sets in the Journal: data sets generated in the Cancer Genome Atlas (TCGA) study of adult diffuse “lower-grade” gliomas1 and in a complementary large-scale study of genetic alterations across a range of diffuse gliomas.

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