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Updated: Nov 2, 2025
Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts
Published on: April 29, 2014
Development and Validation of an Autophagy-Stroma-Based Microenvironment Gene Signature for Risk Stratification in
Lin Chen1, Kunzi Zhang1, Jian Sun1
1Department of gastrointestinal surgery of the First Hospital of China Medical University, Shenyang, 110001, People's Republic of China.
Background:
Colorectal cancer is the fourth most common cancer and the second leading cause of cancer-related death in the USA. The aim of this study was to establish a tumor gene signature based on tumor stromal cell and autophagy for predicting the risk of recurrence in patients with colorectal cancer.
Methods:
We used "Rtsne" and "xCell" R packages to estimate autophagy and stroma status, respectively. The discovery cohort used microarray gene expression data retrieved from the GSE39582 dataset. The Cox regression model and Least Absolute Shrinkage and Selection Operator (LASSO) were used to identify prognostic genes and to construct an autophagy-stroma-based gene signature. Moreover, external validation was conducted using GSE17538, GSE38832, TCGA database, and patient data obtained from the First Hospital of China Medical University (CMU).
Results:
The LASSO model identified three genes (TNS1, TAGLN, and SFRP4) which were used to develop a risk stratification gene signature. The autophagy-stroma-based gene signature was identified as an independent prognostic factor by multivariate analysis (p = 0.0023). The results were validated in GSE17538 (p=0.0062), GSE38832 (p=0.028), TCGA (p=0.046) database, and patient data obtained from the First Hospital of China Medical University (CMU) (p=0.027).
Conclusion:
We have established and verified a feasible prognostic model of colorectal cancer based on autophagy and stromal cell characteristics of patients. The model can be used to evaluate recurrence risk of cancer patients, and the hub genes in the model provide potential targets for targeted colorectal cancer treatment.
