Initiatives such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) have generated high-quality, multi-platform molecular data from thousands of frozen tumor samples. While these initiatives have provided invaluable insight into cancer biology, a tremendous potential resource remains largely untapped in formalin-fixed, paraffin-embedded (FFPE) samples that are more readily available, but which can present technical challenges due to crosslinking of fragile molecules such as RNA.
Researchers from the University of Texas MD Anderson Cancer Center extracted RNA from FFPE primary melanomas and assessed two gene expression platforms — genome-wide RNA sequencing (RNA-seq) and targeted NanoString — for their ability to generate coherent biological signals. To do so, they generated an improved approach to quantifying gene expression pathways, in which we refine pathway scores through correlation-guided gene subsetting. The researchers also make comparisons to the TCGA and other publicly available melanoma datasets.
Comparison of the gene expression patterns to each other, to established biological modules, and to clinical and immunohistochemical data confirmed the fidelity of biological signals from both platforms using FFPE samples to known biology. Moreover, correlations with patient outcome data were consistent with previous frozen-tissue-based studies.
RNA sequencing (RNA-seq) and NanoString compare favorably on the same samples
(A) Schematic of the sample processing workflow. (B) Spearman correlation values for all 1,362 genes shared by the RNA-seq and NanoString datasets, as well as stratified by expression and dynamic range. Probes with low expression were assigned to the “low expression” category even if they had low dynamic range. Student t test was performed for nonoverlapping categories. (*)P < .001. (C) Topmost highly and poorly correlating genes between the platforms, presented as a heatmap of the RNA-seq data. (D) Median absolute deviation divided by the median (MAD/M), a measurement of dynamic range, for the RNA-seq data. Each dot is a gene corresponding to one in (C). Avg, average; Corr., correlation.
FFPE samples from previously difficult-to-access cancer types – such as small primary melanomas – represents a valuable and previously unexploited source of analyte for RNA-seq and NanoString platforms. This work provides an important step towards the use of such platforms to unlock novel molecular underpinnings and inform future biologically-driven clinical decisions.