Gastric Cancer Tumor Microenvironment Characterization Reveals Stromal-Related Gene Signatures Associated With Macrophage Infiltration

Frontiers in Genetics
Shenyu WeiXiangdong Cheng

Abstract

The tumor microenvironment (TME) has attracted attention owing to its essential role in tumor initiation, progression, and metastasis. With the emergence of immunotherapies for various cancers, and their high efficacy, an understanding of the TME in gastric cancer (GC) is critical. The aim of this study was to investigate the effect of various components within the GC TME, and to identify mechanisms that exhibit potential as therapeutic targets. The ESTIMATE algorithm was used to quantify immune and stromal components in GC samples, whose clinicopathological significance and relationship with predicted outcomes were explored. Low tumor mutational burden and high M2 macrophage infiltration, which are considered immune suppressive characteristics and may be responsible for unfavorable prognoses in GC, were observed in the high stromal group (HR = 1.585; 95% CI, 1.112-2.259; P = 0.009). Furthermore, weighted correlation network, differential expression, and univariate Cox analyses were used, along with machine learning methods (LASSO and SVM-RFE), to reveal genome-wide immune phenotypic correlations. Eight stromal-relevant genes cluster (FSTL1, RAB31, FBN1, ANTXR1, LRRC32, CTSK, COL5A2, and ENG) were identified as adverse prognost...Continue Reading

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Datasets Mentioned

BETA
GSE54129
GSE79973
GSE13911

Methods Mentioned

BETA
flow cytometry

Software Mentioned

maftools R
clusterProfile
CIBERSORT
GSVA R
e1071
TCGAbiolinks R package
MutSigCV
CellMarker
R
Oncomine

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