Classification of gastric cancers based on immunogenomic profiling.

ABSTRACT:

Background

Extensive evidence showed that gastric cancer (GC) is heterogeneous, and many studies have been focused on identifying GC subtypes based on genomic profiles. However, few studies have specifically explored the GC classification and predicted the classification accuracy that may help facilitate the optimal stratification of GC patients responsive to immunotherapy.

Methods

Using two publicly available GC genomics datasets, we classified GC on the basis of 797 immune related genes. Unsupervised and supervised machine learning methods were used to predict the classification.

Results

We identified two GC subtypes that we named as Immunity-High (IM-H) and Immunity- Low (IM-L), and demonstrated that this classification was duplicable and predictable by analyzing o

SUBMITTER: Liu Z 

PROVIDER: S-EPMC7576512 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature