Adaptation and Experimental Validation of Clinical RNA Sequencing Protocol Oncobox for MGI DNBSEQ-G50 Platform

RNA sequencing (RNAseq) is currently a method of choice for the high-throughput RNA-level analysis of gene expression. Furthermore, RNAseq data can be used for the prediction of numerous cancer biomarkers e.g. microsatellite instability, tumor mutational burden, gene signatures, and immunohistochemical markers expression. In this analysis, central step is comparison with the pre-existing pool of normal/healthy control tissue profiles. However, technically different RNAseq platforms and protocols usually provide poorly compatible gene expression outputs that can be difficult to pool together and analyze in a direct comparison due to platform/protocol-specific bias. We recently published Oncobox RNA sample preparation and sequencing protocol for Illumina platform that can be used for the analysis of gene expression in cancer molecular diagnostics to personalize treatments, as validated in preclinical and clinical studies. Here we report adaptation of this protocol for DNBSEQ-G50 engine of a competitor MGI sequencing platform. We demonstrate common clustering and similar gene expression portraits for the RNAseq profiles obtained for the same 16 formalin-fixed, paraffin-embedded model experimental cancer biosamples using both Illumina and MGI sequencing platforms. The adopted Oncobox protocol enables retention of the case-to-normal ratios, calculated values of molecular pathway activation, and also of predicted cancer drug efficiency scores. Our findings suggest clinical applicability of Oncobox molecular diagnostics with both Illumina and MGI sequencing platforms. This also evidence that no specific data harmonization is needed to compare the molecular profiles obtained with either platform when using the Oncobox protocol, e.g. with the previously published ANTE experimental panel of normal tissues.