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Two prognostic platforms based on expression signatures are commercially available: OncotypeDx, based on a 21-gene signature measured on paraffin-embedded samples by polymerase chain reaction (PCR) [5], and Mammaprint, the 70-gene "Amsterdam signature" measured by a microarray [6], [7], [8], [9].
With advances in genome-wide gene expression technologies, classification of cancer subtypes based on expression signatures is widespread and results in many biomarkers for various cancers.
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Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy.
The gene-expression matrices for the available genes were used as input of k-means clustering implemented in R v.2.11, with k = 2 and using 100,000 iterations to split the samples of each dataset into two groups based on expression of the signature genes.
We defined an embryonic mammary signature based on expression profiles of genes found highly expressed within midgestation (E12.5-stage) embryonic epithelium compared with postnatal mammary epithelial cells described in Additional file 2[ 13, 13].
Given that many cancer cells undergo some degree of epithelial-mesenchymal transition (EMT), we also defined an embryonic mammary mesenchymal signature based on expression profiles of genes found highly expressed within embryonic mammary mesenchymal tissue compared with postnatal mammary cells (see Additional file 14).
One major advantage of diagnostic signatures based on expression profiles with respect to existing practices is that a test based on circulating miRNA biomarkers is inherently much less invasive than a mammography or a colonoscopy.
Xenografts were assigned to either the low- or high-proliferation group based on expression of the reduced proliferation signature.
To our knowledge, this is the first example of a gene signature based on expression of lncRNAs only.
Applying our previously established DART algorithm [ 31], for each patient in each cohort a DART score was calculated based on expression of the MaSC gene signature, whereby a high activation score indicated a high similarity of gene expression with the MaSC signature.
Figure 3 shows the hierarchical clustering heatmap of patient samples based on expression profiles of the 35-gene signature.
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