Gene expression signatures are a key tool for decision-making in breast cancer. In 2000 Perou et al. identified 4 intrinsic subtypes of breast cancer from gene expression data: LumA, LumB, HER2-enriched and Basal-like. These breast cancer subtypes yielded a superior prognostic impact than classical immunohistochemistry factors. From the initial intrinsic subtype, a 50-gene signature was developed for subtype assignment. PAM50 is being successfully used in multiplexed gene expression platforms such as NanoString nCounter®, which is the basis for the Prosigna® test. The latter was approved for the risk of distant relapse estimation in postmenopausal women with hormone receptor+, node+/- early stage breast cancer patients; and is a daily-used tool assessing the need of adjuvant chemotherapy.
The analyses were performed in paraffin embedded tissues (FFPE) from 96 patients recruited in a multicenter, prospective, non-randomized triple negative breast cancer trial (NCT01560663). Pre-treatment core biopsies were performed following clinical practice guidelines and conserved as FFPE for further RNA extraction. PAM50 was performed on both NanoString nCounter® and RNA-Seq technologies. Subtype assignment was based on the nearest centroid classification following this procedure for both platforms.
Subtype calling agreed on 96% of the cases (NanoString nCounter®/RNA-Seq discordances: 3 Basal-like/HER2-enriched and 1 HER2-enriched/LumA). Both the Spearman correlation to each of the centroids and the risk of recurrence (ROR) were above 0.89 in both platforms. Furthermore, the agreement on proliferation score reached up to 0.97. In addition, 82% of the individual PAM50 genes showed a correlation coefficient >0.80.
The RNA-Seq is a fundamental research tool for whole transcriptome analysis. However, it cannot be massively used in the daily clinical practice, due to its processing time requirements and economic costs. We demonstrated that the RNA-Seq technology provides similar results to the NanoString nCounter®, with the latter providing lower cost and more simplicity in its use.
Clinical trial identification
Legal entity responsible for the study
Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM)
All authors have declared no conflicts of interest.