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

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Biochemistry (Moscow), Supplement Series B: Biomedical Chemistry Aims and scope Submit manuscript

Abstract

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.

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Funding

This work was supported by the Priority 2030 program under the project “Establishment of a regional center for oncogenetic research on the basis of the Privolzhsky Research Medical University of the Ministry of Health of the Russian Federation of the strategic project “Fundamental Oncology,” approved by the order of April 1, 2022 no. “85/Osn/Pr” funded by the Priority 2030 program. Research at the Sechenov First Moscow State Medical University was supported by the Russian Science Foundation, grant no. 20-75-10071.

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Authors and Affiliations

  1. Privolzhsky Research Medical University, Ministry of Health of the Russian Federation, 603000, Nizhny Novgorod, Russia

    N. R. Khilal, D. I. Knyazev, T. F. Kovaleva & N. Y. Katkova

  2. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, 119991, Moscow, Russia

    M. V. Suntsova & A. A. Buzdin

  3. Moscow Institute of Physics and Technology, 141701, Dolgoprudny, Moscow oblast, Russia

    A. A. Guryanova, M. I. Sorokin & A. A. Buzdin

  4. PathoBiology Group, European Organization for Research and Treatment of Cancer, Brussels, 1200, Belgium

    M. I. Sorokin & A. A. Buzdin

  5. Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, 117997, Russian Academy of Sciences, Moscow, Russia

    A. A. Buzdin

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  2. M. V. Suntsova
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  3. D. I. Knyazev
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  4. A. A. Guryanova
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  5. T. F. Kovaleva
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  6. M. I. Sorokin
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  7. A. A. Buzdin
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  8. N. Y. Katkova
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Contributions

Anton A. Buzdin, Tatiana F. Kovaleva, Nadezhda Y. Katkova—concept and supervision of the work; Nadezhda R. Khilal, Maria V. Suntsova, Dmitry I. Knyazev, Anastasia А. Guryanova, Maxim I. Sorokin—conducting experiments; Maria V. Suntsova, Nadezhda R. Khilal—discussion of the results; Maxim I. Sorokin, Maria V. Suntsova, Nadezhda R. Khilal—writing the text; Anton A. Buzdin—editing the text of the article.

Corresponding author

Correspondence to N. R. Khilal.

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Abbreviations: RNAseq, RNA sequencing; DV200, the percentage of RNA fragments with a length greater than 200 bp; CNR, cancer-to-normal ratio; PAL, molecular pathway activation levels; BES, balanced efficiency scores; TCGA, The Cancer Genome Atlas.

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Khilal, N.R., Suntsova, M.V., Knyazev, D.I. et al. Adaptation and Experimental Validation of Clinical RNA Sequencing Protocol Oncobox for MGI DNBSEQ-G50 Platform. Biochem. Moscow Suppl. Ser. B 17, 172–182 (2023). https://doi.org/10.1134/S1990750823600589

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