MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning

Yu Guo; Minghao Li; Yang Hu; Tianyi Zang

doi:10.1109/BIBM55620.2022.9995080

MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning

Yu Guo
, Minghao Li
, Yang Hu
, Tianyi Zang^*

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology
Beidahuang Industry Group General Hospital

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Recent studies have shown that lung adenocarcinoma (LUAD) patients have a higher risk and worse prognosis of COVID-19 caused by SARS-CoV-2 compared to normal samples. Whereas, in addition to the receptor for SARS-CoV-2, other genes also deserve attention. In our study, we identified 19 differentially methylated genes (DMGs) that were co-upregulated in LUAD and COVID-19 samples. These 19 DMGs mainly regulated the immune-related and multiple viral infection signaling pathways. Gene Ontology and pathway enrichment analysis were applied with these genes. Then, 6 key DMGs (MTOR, ACE, IGF1, PTPRC, C3, and PTGS2) were identified by constructing and analyzing the protein-protein interaction (PPI) network. Besides, MTOR was significantly associated with 5 prognostic markers (CDO1, NEURL4, SMAP1, NPEPPS, IQCK) identified by survival analysis based on machine learning. In total, MTOR hypermethylation may be related to the susceptibility of LUAD patients to SARS-CoV-2 and the prognosis of LUAD patients suffering from COVID-19.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
Editors	Donald Adjeroh, Qi Long, Xinghua Shi, Fei Guo, Xiaohua Hu, Srinivas Aluru, Giri Narasimhan, Jianxin Wang, Mingon Kang, Ananda M. Mondal, Jin Liu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2397-2402
Number of pages	6
ISBN (Electronic)	9781665468190
DOIs	https://doi.org/10.1109/BIBM55620.2022.9995080
State	Published - 2022
Externally published	Yes
Event	2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 - Las Vegas, United States Duration: 6 Dec 2022 → 8 Dec 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

Conference

Conference	2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022
Country/Territory	United States
City	Las Vegas
Period	6/12/22 → 8/12/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

LUAD
MTOR
SARS-CoV-2
machine learning
multi-omics

Access to Document

10.1109/BIBM55620.2022.9995080

Cite this

Guo, Y., Li, M., Hu, Y., & Zang, T. (2022). MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning. In D. Adjeroh, Q. Long, X. Shi, F. Guo, X. Hu, S. Aluru, G. Narasimhan, J. Wang, M. Kang, A. M. Mondal, & J. Liu (Eds.), Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 (pp. 2397-2402). (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM55620.2022.9995080

Guo, Yu ; Li, Minghao ; Hu, Yang et al. / MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning. Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. editor / Donald Adjeroh ; Qi Long ; Xinghua Shi ; Fei Guo ; Xiaohua Hu ; Srinivas Aluru ; Giri Narasimhan ; Jianxin Wang ; Mingon Kang ; Ananda M. Mondal ; Jin Liu. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 2397-2402 (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022).

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title = "MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning",

abstract = "Recent studies have shown that lung adenocarcinoma (LUAD) patients have a higher risk and worse prognosis of COVID-19 caused by SARS-CoV-2 compared to normal samples. Whereas, in addition to the receptor for SARS-CoV-2, other genes also deserve attention. In our study, we identified 19 differentially methylated genes (DMGs) that were co-upregulated in LUAD and COVID-19 samples. These 19 DMGs mainly regulated the immune-related and multiple viral infection signaling pathways. Gene Ontology and pathway enrichment analysis were applied with these genes. Then, 6 key DMGs (MTOR, ACE, IGF1, PTPRC, C3, and PTGS2) were identified by constructing and analyzing the protein-protein interaction (PPI) network. Besides, MTOR was significantly associated with 5 prognostic markers (CDO1, NEURL4, SMAP1, NPEPPS, IQCK) identified by survival analysis based on machine learning. In total, MTOR hypermethylation may be related to the susceptibility of LUAD patients to SARS-CoV-2 and the prognosis of LUAD patients suffering from COVID-19.",

keywords = "LUAD, MTOR, SARS-CoV-2, machine learning, multi-omics",

author = "Yu Guo and Minghao Li and Yang Hu and Tianyi Zang",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 ; Conference date: 06-12-2022 Through 08-12-2022",

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series = "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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editor = "Donald Adjeroh and Qi Long and Xinghua Shi and Fei Guo and Xiaohua Hu and Srinivas Aluru and Giri Narasimhan and Jianxin Wang and Mingon Kang and Mondal, \{Ananda M.\} and Jin Liu",

booktitle = "Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022",

address = "美国",

}

Guo, Y, Li, M, Hu, Y & Zang, T 2022, MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning. in D Adjeroh, Q Long, X Shi, F Guo, X Hu, S Aluru, G Narasimhan, J Wang, M Kang, AM Mondal & J Liu (eds), Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Institute of Electrical and Electronics Engineers Inc., pp. 2397-2402, 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022, Las Vegas, United States, 6/12/22. https://doi.org/10.1109/BIBM55620.2022.9995080

MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning. / Guo, Yu; Li, Minghao; Hu, Yang et al.
Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. ed. / Donald Adjeroh; Qi Long; Xinghua Shi; Fei Guo; Xiaohua Hu; Srinivas Aluru; Giri Narasimhan; Jianxin Wang; Mingon Kang; Ananda M. Mondal; Jin Liu. Institute of Electrical and Electronics Engineers Inc., 2022. p. 2397-2402 (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning

AU - Guo, Yu

AU - Li, Minghao

AU - Hu, Yang

AU - Zang, Tianyi

PY - 2022

Y1 - 2022

N2 - Recent studies have shown that lung adenocarcinoma (LUAD) patients have a higher risk and worse prognosis of COVID-19 caused by SARS-CoV-2 compared to normal samples. Whereas, in addition to the receptor for SARS-CoV-2, other genes also deserve attention. In our study, we identified 19 differentially methylated genes (DMGs) that were co-upregulated in LUAD and COVID-19 samples. These 19 DMGs mainly regulated the immune-related and multiple viral infection signaling pathways. Gene Ontology and pathway enrichment analysis were applied with these genes. Then, 6 key DMGs (MTOR, ACE, IGF1, PTPRC, C3, and PTGS2) were identified by constructing and analyzing the protein-protein interaction (PPI) network. Besides, MTOR was significantly associated with 5 prognostic markers (CDO1, NEURL4, SMAP1, NPEPPS, IQCK) identified by survival analysis based on machine learning. In total, MTOR hypermethylation may be related to the susceptibility of LUAD patients to SARS-CoV-2 and the prognosis of LUAD patients suffering from COVID-19.

AB - Recent studies have shown that lung adenocarcinoma (LUAD) patients have a higher risk and worse prognosis of COVID-19 caused by SARS-CoV-2 compared to normal samples. Whereas, in addition to the receptor for SARS-CoV-2, other genes also deserve attention. In our study, we identified 19 differentially methylated genes (DMGs) that were co-upregulated in LUAD and COVID-19 samples. These 19 DMGs mainly regulated the immune-related and multiple viral infection signaling pathways. Gene Ontology and pathway enrichment analysis were applied with these genes. Then, 6 key DMGs (MTOR, ACE, IGF1, PTPRC, C3, and PTGS2) were identified by constructing and analyzing the protein-protein interaction (PPI) network. Besides, MTOR was significantly associated with 5 prognostic markers (CDO1, NEURL4, SMAP1, NPEPPS, IQCK) identified by survival analysis based on machine learning. In total, MTOR hypermethylation may be related to the susceptibility of LUAD patients to SARS-CoV-2 and the prognosis of LUAD patients suffering from COVID-19.

KW - LUAD

KW - MTOR

KW - SARS-CoV-2

KW - machine learning

KW - multi-omics

UR - https://www.scopus.com/pages/publications/85146663139

U2 - 10.1109/BIBM55620.2022.9995080

DO - 10.1109/BIBM55620.2022.9995080

M3 - 会议稿件

AN - SCOPUS:85146663139

T3 - Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

SP - 2397

EP - 2402

BT - Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

A2 - Adjeroh, Donald

A2 - Long, Qi

A2 - Shi, Xinghua

A2 - Guo, Fei

A2 - Hu, Xiaohua

A2 - Aluru, Srinivas

A2 - Narasimhan, Giri

A2 - Wang, Jianxin

A2 - Kang, Mingon

A2 - Mondal, Ananda M.

A2 - Liu, Jin

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

Y2 - 6 December 2022 through 8 December 2022

ER -

Guo Y, Li M, Hu Y , Zang T. MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning. In Adjeroh D, Long Q, Shi X, Guo F, Hu X, Aluru S, Narasimhan G, Wang J, Kang M, Mondal AM, Liu J, editors, Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 2397-2402. (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022). doi: 10.1109/BIBM55620.2022.9995080

MTOR hypermethylation may associate with the susceptibility and survival of SARS-CoV-2 infections to lung adenocarcinoma patients based on multi-omics data and machine learning

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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