Use of deep neural network ensembles to identify embryonicfetal transition markers: Repression of COX7A1 in embryonic and cancer cells

Michael D. West, Ivan Labat, Hal Sternberg, Dana Larocca, Igor Nasonkin, Karen B. Chapman, Ratnesh Singh, Eugene Makarev, Alex Aliper, Andrey Kazennov, Andrey Alekseenko, Nikolai Shuvalov, Evgenia Cheskidova, Aleksandr Alekseev, Artem Artemov, Evgeny Putin, Polina Mamoshina, Nikita Pryanichnikov, Jacob Larocca, Karen CopelandEvgeny Izumchenko, Mikhail Korzinkin, Alex Zhavoronkov

Research output: Contribution to journalArticle

Abstract

Here we present the application of deep neural network (DNN) ensembles trained on transcriptomic data to identify the novel markers associated with the mammalian embryonic-fetal transition (EFT). Molecular markers of this process could provide important insights into regulatory mechanisms of normal development, epimorphic tissue regeneration and cancer. Subsequent analysis of the most significant genes behind the DNNs classifier on an independent dataset of adult-derived and human embryonic stem cell (hESC)-derived progenitor cell lines led to the identification of COX7A1 gene as a potential EFT marker. COX7A1, encoding a cytochrome C oxidase subunit, was up-regulated in post-EFT murine and human cells including adult stem cells, but was not expressed in pre-EFT pluripotent embryonic stem cells or their in vitro-derived progeny. COX7A1 expression level was observed to be undetectable or low in multiple sarcoma and carcinoma cell lines as compared to normal controls. The knockout of the gene in mice led to a marked glycolytic shift reminiscent of the Warburg effect that occurs in cancer cells. The DNN approach facilitated the elucidation of a potentially new biomarker of cancer and pre-EFT cells, the embryoonco phenotype, which may potentially be used as a target for controlling the embryonic-fetal transition.

Original languageEnglish (US)
Pages (from-to)7796-7811
Number of pages16
JournalOncotarget
Volume9
Issue number8
DOIs
StatePublished - Jan 1 2018

Keywords

  • Cancer marker
  • Deep neural network
  • Embryonic-fetal transition
  • Stem cells
  • Warburg effect

ASJC Scopus subject areas

  • Oncology

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    West, M. D., Labat, I., Sternberg, H., Larocca, D., Nasonkin, I., Chapman, K. B., Singh, R., Makarev, E., Aliper, A., Kazennov, A., Alekseenko, A., Shuvalov, N., Cheskidova, E., Alekseev, A., Artemov, A., Putin, E., Mamoshina, P., Pryanichnikov, N., Larocca, J., ... Zhavoronkov, A. (2018). Use of deep neural network ensembles to identify embryonicfetal transition markers: Repression of COX7A1 in embryonic and cancer cells. Oncotarget, 9(8), 7796-7811. https://doi.org/10.18632/oncotarget.23748