Breast cancer PAM50 signature: correlation and concordance between RNA-Seq and digital multiplexed gene expression technologies in a triple negative breast cancer series.

BACKGROUND: Full RNA-Seq is a fundamental research tool for whole transcriptome analysis. However, it is too costly and time consuming to be used in routine clinical practice. We evaluated the transcript quantification agreement between RNA-Seq and a digital multiplexed gene expression platform, and the subtype call after running the PAM50 assay in a series of breast cancer patients classified as triple negative by IHC/FISH. The goal of this study is to analyze the concordance between both expression platforms overall, and for calling PAM50 triple negative breast cancer intrinsic subtypes in particular. RESULTS: The analyses were performed in paraffin-embedded tissues from 96 patients recruited in a multicenter, prospective, non-randomized neoadjuvant triple negative breast cancer trial (NCT01560663). Pre-treatment core biopsies were obtained following clinical practice guidelines and conserved as FFPE for further RNA extraction. PAM50 was performed on both digital multiplexed gene expression and RNA-Seq platforms. Subtype assignment was based on the nearest centroid classification following this procedure for both platforms and it was concordant on 96% of the cases (N = 96). In four cases, digital multiplexed gene expression analysis and RNA-Seq were discordant. The Spearman correlation to each of the centroids and the risk of recurrence were above 0.89 in both platforms while the agreement on Proliferation Score reached up to 0.97. In addition, 82% of the individual PAM50 genes showed a correlation coefficient > 0.80. CONCLUSIONS: In our analysis, the subtype calling in most of the samples was concordant in both platforms and the potential discordances had reduced clinical implications in terms of prognosis. If speed and cost are the main driving forces then the preferred technique is the digital multiplexed platform, while if whole genome patterns and subtype are the driving forces, then RNA-Seq is the preferred method.

Improving nitrogen removal in predenitrification-nitrification biofilters.

The effect on NH4-N removal rates in nitrification biofilters of filtered biodegradable COD and particulate COD leaving predenitrification biofilters was studied in a lab scale plant configured with the separated system of biofilters for secondary nitrogen removal from urban wastewaters. Applying a typical COD load of 11 kg/m3 x day to the predenitrification biofilter and maximizing its COD removal by adding nitrates or by operating an improved control of the internal recycle, only 60% removal of filtered biodegradable COD was found. This value corresponds to the complete removal of the readily biodegradable substrate (30% of influent filtered COD) and 36% of filtered slowly biodegradable substrate (50% of influent COD). The remaining 64% of the latter entered the nitrification biofilter, causing competition between heterotrophs and nitrifiers for dissolved oxygen in the inner layers of the biofilm. Consequently the nitrification rate had relatively low values (0.5 kgN/m3 x d) at 14 degrees C despite using dissolved oxygen levels of 6 mg/l. This behaviour may explain the lower nitrification rates obtained in some cases of nitrification biofilters compared to those in tertiary nitrification after activated sludge processes. The particulate COD entering the nitrification biofilter is associated with the suspended solids leaving the denitrification biofilter which are adsorbed by the external layers of the biofilm, increasing its thickness. The activity of the nitrifiers was affected because of a lack of oxygen when the thickness was left to grow considerably. Therefore no significant particulate COD effect is expected to occur as long as backwashing is carried out with the appropriate frequency.