TY - GEN
T1 - The Potential of Single Cell RNA-Sequencing Data for the Prediction of Gastric Cancer Serum Biomarkers
AU - Medvedev, Kirill E.
AU - Savelyeva, Anna V.
AU - Bagrodia, Aditya
AU - Grishin, Nick V.
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Biomarkers of gastric cancer
KW - Gastric cancer
KW - Gastric cancer secretome
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U2 - 10.1007/978-3-030-64511-3_8
DO - 10.1007/978-3-030-64511-3_8
M3 - Conference contribution
AN - SCOPUS:85097809145
SN - 9783030645106
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 79
EP - 84
BT - Mathematical and Computational Oncology - Second International Symposium, ISMCO 2020, 2020, Proceedings
A2 - Bebis, George
A2 - Alekseyev, Max
A2 - Cho, Heyrim
A2 - Gevertz, Jana
A2 - Rodriguez Martinez, Maria
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Symposium on Mathematical and Computational Oncology, ISMCO 2020
Y2 - 8 October 2020 through 10 October 2020
ER -