Machine learning-based screening of the relationship between differential genes and immune infiltration in gastric cancer

Fengjin Shang; Yaxing Liu; Luyao Chen; Haoran Zhang; Changhong Lian

doi:10.1117/12.2674517

23 May 2023 Machine learning-based screening of the relationship between differential genes and immune infiltration in gastric cancer

Fengjin Shang, Yaxing Liu, Luyao Chen, Haoran Zhang, Changhong Lian

Author Affiliations +

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 126041Y (2023) https://doi.org/10.1117/12.2674517
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

Gastric cancer (GC) is the fifth most prevalent malignancy in humans and one of the common causes of cancer-related deaths. In 2020, there will be 1.8 million new cases of GC and 770,000 deaths worldwide, which is the fifth and fourth highest of all malignancies, respectively. The dataset GSE103236, GSE13911, and GSE79973 was downloaded from the GEO database to comparing differentially expressed genes (DEGs) in paired carcinoma tissue and paraneoplastic tissue clinical samples by LASSO and SVM-RFE machine learning methods. Finally, we analyzed the relationship between differential genes and 22 types of immune cells by using the CIBERSORT method, and then provided new ideas for immunotherapy of gastric cancer.

Citation Download Citation

Fengjin Shang, Yaxing Liu, Luyao Chen, Haoran Zhang, and Changhong Lian "Machine learning-based screening of the relationship between differential genes and immune infiltration in gastric cancer", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 126041Y (23 May 2023); https://doi.org/10.1117/12.2674517

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available