The Potential of Single Cell RNA-Sequencing Data for the Prediction of Gastric Cancer Serum Biomarkers

Kirill E. Medvedev, Anna V. Savelyeva, Aditya Bagrodia, Nick V. Grishin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Gastric cancer (GC) is the sixth most common worldwide malignancy and the third leading cancer cause of death. Early diagnosis and effective after-surgical monitoring can significantly improve survival rates. Previous studies have revealed several serum biomarkers that are elevated in GC patients, including CEA, CA19-9, and CA72-4. However, sensitivity of these biomarkers is below 30%. Identification of more sensitive and specific to GC markers is critical for individualized therapy of this disease. Here we developed an approach for single-cell transcriptomic data analysis that identifies secretory proteins that are abundantly expressed in GC cells and that could be measurable in the blood. Using early GC scRNA-seq data, we identified 19 secretory proteins significantly overexpressed in GC cells. Notably, 4 proteins (IL32, KLK10, KLK7, OLFM4) have demonstrated more superior sensitivity in comparison to conventional serum markers in previous studies. Moreover, 2 proteins, F12 and CFD, were not previously associated with GC and were not utilized for serum-based testing of other malignancies. Proposed approach has a high potential to be used for serum marker identification in other types of cancers and presented here data could be a source for the development of more sensitive and specific diagnostic panel for early gastric cancer detection and patient post-treatment monitoring.

Original languageEnglish (US)
Title of host publicationMathematical and Computational Oncology - Second International Symposium, ISMCO 2020, 2020, Proceedings
EditorsGeorge Bebis, Max Alekseyev, Heyrim Cho, Jana Gevertz, Maria Rodriguez Martinez
PublisherSpringer Science and Business Media Deutschland GmbH
Pages79-84
Number of pages6
ISBN (Print)9783030645106
DOIs
StatePublished - 2020
Event2nd International Symposium on Mathematical and Computational Oncology, ISMCO 2020 - San Diego, United States
Duration: Oct 8 2020Oct 10 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12508 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Symposium on Mathematical and Computational Oncology, ISMCO 2020
CountryUnited States
CitySan Diego
Period10/8/2010/10/20

Keywords

  • Biomarkers of gastric cancer
  • Gastric cancer
  • Gastric cancer secretome

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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