Ken CN Chang, Gladys Arreaza, John Kang, Maureen Maguire, Ping Qiu and Matthew J Marton
Abstract
We previously developed a “concordance calculator” to quantify reproducibility of multi-variant calls among next generation sequencing (NGS) samples and replicates. This tool and a novel replicate approach have been also used to eliminate many different technical artifacts including post tissue collection modifications (PTCM) such as deamination and oxidation artifacts. Here we apply this approach to study the impact of tumor heterogeneity among consecutive FFPE tissue sections across entire tumor blocks and cannot detect any impact of heterogeneity among different sections/regions of tumors in terms of mutation profiles using the NGS AmpliSeq Cancer Panel, even though the tumor was visibly heterogeneous according to the H&E images and pathological review. RNA expression profiling using a NanoString Cancer Panel found significantly different expression patterns among different sections/ regions. Additional studies in a different tissue type also found no detectable discrepancies among different tissue sections in terms of their mutation profiles. If confirmed by further studies, these results using FFPE tissue sections would suggest that DNA mutation signatures as novel biomarkers for cancer diagnosis and prognosis might be less sensitive to tumor heterogeneity than RNA-based expression signatures, at least based on the performance and sensitivity of current DNA/RNA profiling technologies. Use of the concordance calculator to quantify reproducibility of multi-variant calls among Next Generation Sequencing replicates and to eliminate many different technical artifacts including PTCM also allowed us to develop an unconventional validation strategy. We call this validation approach “in situ analytical validation and evaluation (iSAVE).” As a proof of concept, we evaluated the RainDance ThunderBolts Cancer Panel and demonstrated analytical validation directly on each and every clinical sample. This strategy also comprises using a set of normal FFPE tissue samples in the validation process to eliminate platform-, panel-, amplicon-, library-preparation-, and mutation calling pipeline specific artifacts.
