Absolute assignment of XXXX intrinsic molecular subtype.

@entity1 @entity74 @entity0
BACKGROUND: Massively parallel gene expression profiling has provided a more objective, molecular-level characterization of @entity0 subtypes. Several bioinformatics tools are available to infer @entity1 subtype from a gene expression profile including the well-studied PAM50. The specific algorithmic methods used in these tools require access to a broad @entity1 dataset. The choice of subtype for an individual is determined relative to all other @entity1 across the panel, making subtypes heavily dependent on the composition of the dataset. Our aim was to develop a bioinformatics approach assigning absolute @entity0 subtypes, independent of dataset composition. METHODS: Using a dataset of 4924 @entity0 @entity1 , we defined a new bioinformatics approach: @entity74 ( @entity74 ) that assigns subtype from a gene expression profile for an individual sample without the need for a large, diverse, and normalized dataset. We evaluated the agreement of @entity74 with PAM50 and compared subtype assignment and prognostic value of the subtypes. We assessed @entity74 ' robustness using a benchmark set of tests including subtype reproducibility between technologies, gene removal, and normal gene expression contamination, and compared it with PAM50. All statistical tests, except where noted, were two-sided. RESULTS: @entity74 vastly agreed with PAM50, with 76% and 77% agreement for cross validation and the test set, respectively, and the prognostic capacity of the intrinsic subtypes was preserved. @entity74 is fully stable, and its absolute nature enables its use on a wide range of datasets and technologies, including RNA-seq. CONCLUSIONS: The instability of a @entity0 subtyping scheme like PAM50 could have important consequences in clinical management of @entity1 . @entity74 is a fully stable and robust subtyping scheme that recapitulates PAM50.
