Expression of Four Autophagy-Related Genes Accurately Predicts the Prognosis of Gastrointestinal Cancer in Asian Patients

Abstract

Gastrointestinal (GI) cancers are among the most fatal diseases in the world. Numerous studies have demonstrated the relationship between autophagy and development of gastrointestinal cancers. However, whether autophagy-related genes can predict prognosis of GI cancers in individuals of Asian ancestry has not been defined. This study, evaluated the prognostic value of autophagy-related genes in gastrointestinal cancer. Expression profile of autophagy-related genes for 296 gastrointestinal cancer patients of Asian ancestry was downloaded from the TCGA database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL, and TCGA-READ). The prognostic value of the autophagy-related genes was evaluated using univariate Cox, LASSO, and multivariate Cox regression analyses. The risk score of the autophagy-related gene signature was calculated to assess its predictive prognostic value for GI cancers. Forty-seven differentially expressed autophagy-related genes, in Asian patients with gastrointestinal cancers, were identified. Of the 47 genes, 4 were associated with prognosis of GI cancer (SQSTM1, BIRC5, NRG3, and CXCR4). A prognostic model for GI cancer, based on the expression of the above 4 genes in the training set, showed that cancer patients were stratified into high-risk and low-risk groups ( P < 0.05 ). The utility of the model for overall survival (OS) of GI cancer patients was consistent across the entire set, training set, and test set (entire set: P = 4.568 × 10 − 4 ; train set: P = 5.718 × 10 − 3 ; test set: P = 3.516 × 10 − 2 ). The sensitivity and specificity of the ROC curve of the above prognostic model in predicting the 5-year prognosis of GI cancer was satisfactory (entire set: 0.728; train set: 0.727; test set: 0.733). Analysis of clinical samples validated the overexpression of the 4 genes (SQSTM1, BIRC5, NRG3, and CXCR4) in tumor tissues relative to paired normal tissues, consistent with bioinformatic findings. Expression of the 4 autophagy-related genes (SQSTM1, BIRC5, NRG3, and CXCR4) can accurately predict the prognosis of gastrointestinal tumors in Asian patients.

Novel Immune-Related Ferroptosis Signature in Esophageal Cancer: An Informatics Exploration of Biological Processes Related to the TMEM161B-AS1/hsa-miR-27a-3p/GCH1 Regulatory Network

“…The Kaplan–Meier survival plot also confirmed that our model with the lowest p -value has the best ability to distinguish prognosis ( Figures 4D–F ). In addition, through the comparison of the c-indexes, we also observed that our model performed better than the model of Tang et al (2021) ( Figure 4G ). And our model has also been marked to have the highest RMST curve in 3 models ( Figure 4H ).…”

“…After multiple analysis and verification of multiple internal and external datasets, our model has proven to meet this requirement. In addition, our model showed the best predictive value compared with other models in previous research (Song et al, 2021;Tang et al, 2021). Three PR-DE-IRFeGs have been reported to be closely related to ferroptosis and immunity, as well as the occurrence, development and prognosis of certain cancers.…”

“…IRFR model represents the model we built using three PR-DE-IRFeGs. Tang autophagy model represents a model constructed by Tang et al (2021) using 4 autophagy-related genes. The Song ferroptosis model represents a model constructed by Song et al (2021) using 7 ferroptosis-related genes.…”

“… Song et al (2021) and Tang et al (2021) , respectively, screened 7 ferroptosis-related genes and 4 autophagy-related genes to construct models to predict the prognosis of patients with ESCA. We extracted the mRNA expression data of the corresponding genes of each model from the TCGA ESCA dataset to construct a multiCox regression model and calculated the corresponding risk score for each sample.…”

“…Similarly, the Kaplan–Meier survival plot were used to compare the ability of the three models to distinguish prognosis. Thus, we tried to compare the prognostic performance of the 7-gene combination model, 4-gene combination model and our 3-gene combination model based on the concordance index (C-index) calculated based on the mRNA expression levels of the 7 genes (ALOX12, ALOX12B, ANGPTL7, DRD4, MAPK9, SLC38A1, and ZNF419) that Song et al (2021) introduced, the 4 genes (SQSTM1, BIRC5, NRG3, and CXCR4) that Tang et al (2021) introduced, and the 3 genes our study presented. Higher C-index implied better prognostic performance ( Schröder et al, 2011 ).…”