Overall survival prediction of gastric cancer using the gene signature of CT-detected extramural venous invasion combined with M2 macrophages infiltration

Q: What is the main goal of this study on gastric cancer?

To investigate how CT-detected extramural venous invasion relates to M2 macrophages and to build a gene-signature model for prognosis prediction.

Q: How were EMVI and M2 macrophage signals combined to construct the gene signature?

EMVI-related genes were selected from gastric cancer samples by correlation with EMVI scores, overlapped with WGCNA modules and M2 macrophage–related genes from TCGA, yielding a set of genes used to train a hub-gene signature with COX and LASSO.

Q: How does the model evaluate outcomes and immunotherapy potential?

High- and low-risk groups were compared using Kaplan–Meier curves and COX analysis; tumor mutation burden was estimated with ESTIMATE, and sensitivity to immune checkpoint inhibitors was evaluated alongside hub-gene expression and experimental validation.

Sep 21, 2026

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CT-detected extramural venous invasion (EMVI) is an independent risk factor for distant metastasis in advanced gastric cancer, yet its molecular mechanism and prognostic basis remain unclear. This study links CT-detected EMVI to M2 macrophages and builds a radiogenomic model to predict survival. EMVI-related genes were integrated with WGCNA co-expression modules and M2 macrophage–related genes, then hub-gene signatures were trained, validated, and assessed for survival and immunotherapy relevance.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages15

Reading Time38 min

AccessFree to download

Abstract

Background

Methods

Results

Conclusion

Introduction

Yang et al. Journal of Translational Medicine (2024) 22:829 [https://doi.org/10.1186/s12967-024-05628-3](https://doi.org/10.1186/s12967-024-05628-3) Journal of Translational Medicine RESEARCH Open Access Overall survival prediction of gastric cancer using the gene signature of CT-detected extramural venous invasion combined with M2 macrophages infiltration Hao Yang 1†, Xinyi Gou2†, Caizhen Feng2, Yuanyuan Zhang3, Boshi Sun4, Peng Peng6, Yi Wang2, Nan Hong2, Yingjiang Ye5, Jin Cheng2* and Bo Gao6* Abstract Background CT-detected Extramural venous invasion (EMVI) is known as an independent risk factor for distant metastasis in patients with advanced gastric cancer (GC) . However, the molecular basis is not clear. In colorectal cancer, M2 macrophages plays a vital role in determining EMVI. This study aimed to investigate the relationship between CT-detected EMVI and the M2 macrophages as well as prognosis predictionusing a radiogenomic approach. Method We utilized EMVI-related genes (from mRNA sequencing of 13 GC samples correlated with EMVI score by spearman analysis, P < 0. 01) to overlap the co-expression genes of WGCNA module and M2 macrophages related genes (from mRNA data of 371 GC patients inTCGA database), generating a total of 136 genes. An EMVI-M2-prognosis-related hub gene signature was constructed by COX and least absolute shrinkage and selection operator (LASSO) analysis from a training cohort TCGA database (n = 371) and validated it in a validation cohort from GEO database (n = 357) . High-and low-risk groups were divided by hub gene (EGFLAM and GNG11) signature-derived risk scores. We assessed its predictive ability through Kaplan-Meier (K-M) curve and COX analysis. Furthermore, we utilized ESTIMATE to detect tumor mutation burden (TMB) and evaluate sensitivity to immune checkpoint inhibitors (ICIs) . Expression of hub genes was tested using western blotting and immunohistochemistry (IHC) analysis. Results The overall survival (OS) was significantly reduced in the high-risk group (Training/Validation: AUC = 0 . 701/0 . 620; P < 0. 001/0 . 003) . Furthermore, the risk score was identified as an independent predictor of OS in multivariate COX regression analyses (Training/Validation: HR = 1 . 909/1 . 928; 95% CI: 1.225–2. 974/1 .308–2. 844) . The low-risk group exhibited significantly higher TMB levels (P = 1 . 6e− 07) and greater sensitivity to ICIs. Significant higher expression of hub-genes was identified on multiple GC cell lines and original samples. Hub-genes knockdown in †Hao Yang and Xinyi Gou contributed equally to this work and share first authorship. *Correspondence: Jin Cheng [chengjinpkuph@outlook.com](chengjinpkuph@outlook.com)[ ](chengjinpkuph@outlook.com)Bo Gao [bo.gao@bjmu.edu.cn](bo.gao@bjmu.edu.cn) Full list of author information is available at the end of the article © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://](http://)[ ](http://)[creativecommons.org/l](creativecommons.org/l)icenses/by-nc-nd/4.0/. Yang et al. Journal of Tran

FAQs

What is the main goal of this study on gastric cancer?

To investigate how CT-detected extramural venous invasion relates to M2 macrophages and to build a gene-signature model for prognosis prediction.

How were EMVI and M2 macrophage signals combined to construct the gene signature?

EMVI-related genes were selected from gastric cancer samples by correlation with EMVI scores, overlapped with WGCNA modules and M2 macrophage–related genes from TCGA, yielding a set of genes used to train a hub-gene signature with COX and LASSO.

How does the model evaluate outcomes and immunotherapy potential?

High- and low-risk groups were compared using Kaplan–Meier curves and COX analysis; tumor mutation burden was estimated with ESTIMATE, and sensitivity to immune checkpoint inhibitors was evaluated alongside hub-gene expression and experimental validation.

Sep 21, 2026

Upload by Theodore