A Gold Standard-Derived Modular Barcoding Approach to Cancer Transcriptomics.

A challenge with studying cancer transcriptomes is in distilling the wealth of information down into manageable portions of information. In this resource, we develop an approach that creates and assembles cancer type-specific gene expression modules into flexible barcodes, allowing for adaptation to a wide variety of uses. Specifically, we propose that modules derived organically from high-quality gold standards such as The Cancer Genome Atlas (TCGA) can accurately capture and describe functionally related genes that are relevant to specific cancer types.

Biological Validation of RNA Sequencing Data from Formalin-Fixed Paraffin-Embedded Primary Melanomas.

Purpose: 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.

Materials And Methods: We 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.