The goal of the project was to develop a technique that would be useful for assessment of FFPE blocks with the same accuracy as gene expression profiling so that we could use this for interrogation of other collected case series. We reasoned that such a technique would have wide application in DLBCL research and clinical trials. In this study, we show that the qNPA technology can categorize DLBCL into GCB and ABC subtypes with high accuracy as compared to GEP. Importantly, both the laboratory work and classification analysis were performed blinded to the COO category based on the previous GEP and used cases from the one of our previously published papers which was used to define ABC and GCB in the literature. Also, the algorithm previously used for GEP classification was again employed with no modifications. Of note, there were no technical difficulties with any of the pathological materials although they were collected retrospectively from a variety of institutions and countries with different fixation methods. This could be a significant advantage of the qNPA technique over IHC, which may be sensitive to fixation and antigen retrieval methods. Of note, neither previous IHC nor molecular studies have reported on the rate of unsuccessful or uninterpretable cases.
Other methods for comparing mRNA levels in paraffin embedded tissues rather than frozen tissues are also under development as recently demonstrated using the Affymetrix system.(20
) While accurate, the Affimetrix method still requires RNA extraction and performs best with a linear amplification technique in order to provide a sufficient amount of template. Additionally, the study excluded any cases previously assigned to the Unclassifiable category using complete GEP from previous studies, thus eliminating 11 of 59 samples, resulting in a 48 case series with a call rate of 93.8% using 100 of the most predictive genes.(21
) In the current study, we used all available samples including those with gene expression profiles that had previously fallen into the Unclassifiable category.(15
As shown in the model comparison, the larger number of genes that can be included in an assay, the more similar the results will be to the original complete GEP model with 187 genes. The assay tested in this study was based on the most statistically powerful 14 genes, of which 12 were finally used. However, additional genes could be readily added to the design that would undoubtedly further improve the accuracy compared to complete gene expression profiling.
Limitations of the qNPA assay include the relatively complicated technology compared to IHC and use of a patented array that is not widely implemented at this time. Of interest, a new imaging platform has just been announced that will use a Luminex bead technology called the qBead Assay (Luminex Corporation, Austin, Texas) rather than the Omix imager used for this project. Advantages include the lack of RNA extraction, use of FFPE tissues, and more quantitative data than IHC. The qNPA method yielded data on all cases with a perfect “intent to categorize” rate, while the failure rate of other methods has not been reported. In summary, we report here a method that has the potential for significant impact on future DLBCL research and clinical trial development not only with regard to COO classification but also in the development of other applications of GEP data.