RNA Sequencing-Based Identification of Ganglioside GD2-Positive Cancer Phenotype

Maxim Sorokin; Irina Kholodenko; Daniel Kalinovsky; Tatyana Shamanskaya; Igor Doronin; Dmitry Konovalov; Aleksei Mironov; Denis Kuzmin; Daniil Nikitin; Sergey Deyev; Anton Buzdin; Roman Kholodenko

doi:10.3390/biomedicines8060142

RNA Sequencing-Based Identification of Ganglioside GD2-Positive Cancer Phenotype

Biomedicines. 2020 May 30;8(6):142. doi: 10.3390/biomedicines8060142.

Authors

Maxim Sorokin^{1

2

3}, Irina Kholodenko⁴, Daniel Kalinovsky¹, Tatyana Shamanskaya⁵, Igor Doronin^{1

6}, Dmitry Konovalov⁵, Aleksei Mironov⁷, Denis Kuzmin⁸, Daniil Nikitin¹, Sergey Deyev^{1

2}, Anton Buzdin^{1

2

8

9}, Roman Kholodenko^{1

6}

Affiliations

¹ Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho- Maklaya St., 117997 Moscow, Russia.
² Sechenov First Moscow State Medical University, 8-2, Trubetskaya St., 119992 Moscow, Russia.
³ Omicsway Corp., 340 S Lemon Ave, 6040, Walnut, CA 91789, USA.
⁴ Orekhovich Institute of Biomedical Chemistry, 10, Pogodinskaya St., 119121 Moscow, Russia.
⁵ D. Rogachev Federal Research Center of Pediatric Hematology, Oncology and Immunology, 1, Samory Mashela St., 117997 Moscow, Russia.
⁶ Real Target LLC, 108841 Moscow, Russia.
⁷ Skolkovo Institute of Science and Technology, 3, Nobelya St., 121205 Moscow, Russia.
⁸ Moscow Institute of Physics and Technology (National Research University), 141700 Moscow, Russia.
⁹ Oncobox ltd., 121205 Moscow, Russia.

Abstract

The tumor-associated ganglioside GD2 represents an attractive target for cancer immunotherapy. GD2-positive tumors are more responsive to such targeted therapy, and new methods are needed for the screening of GD2 molecular tumor phenotypes. In this work, we built a gene expression-based binary classifier predicting the GD2-positive tumor phenotypes. To this end, we compared RNA sequencing data from human tumor biopsy material from experimental samples and public databases as well as from GD2-positive and GD2-negative cancer cell lines, for expression levels of genes encoding enzymes involved in ganglioside biosynthesis. We identified a 2-gene expression signature combining ganglioside synthase genes ST8SIA1 and B4GALNT1 that serves as a more efficient predictor of GD2-positive phenotype (Matthews Correlation Coefficient (MCC) 0.32, 0.88, and 0.98 in three independent comparisons) compared to the individual ganglioside biosynthesis genes (MCC 0.02-0.32, 0.1-0.75, and 0.04-1 for the same independent comparisons). No individual gene showed a higher MCC score than the expression signature MCC score in two or more comparisons. Our diagnostic approach can hopefully be applied for pan-cancer prediction of GD2 phenotypes using gene expression data.

Keywords: GD2-positive tumors; NGS; RNA sequencing; ganglioside GD2; ganglioside biosynthesis; glioma; immunotherapy; molecular diagnostics; neuroblastoma; targeted therapy.

Abstract

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