Identification of prognostic immune-related gene signature associated with tumor microenvironment of colorectal cancer.

The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC). Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database. Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717-0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates. In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.

Wang Y ，Li W ，Jin X ，Jiang X ，Guo S ，Xu F ，Su X ，Wang G ，Zhao Z ，Gu X ... -  《BMC CANCER》

Identification of prognostic genes in adrenocortical carcinoma microenvironment based on bioinformatic methods.

To identify prognostic genes which were associated with adrenocortical carcinoma (ACC) tumor microenvironment (TME). Transcriptome profiles and clinical data of ACC samples were collected from The Cancer Genome Atlas (TCGA) database. We use ESTIMATE (estimation of stromal and Immune cells in malignant tumor tissues using expression data) algorithm to calculate immune scores, stromal scores and estimate scores. Heatmap and volcano plots were applied for differential analysis. Venn plots were used for intersect genes selection. We used protein-protein interaction (PPI) networks and functional analysis to explore underlying pathways. After performing stepwise regression method and multivariate Cox analysis, we finally screened hub genes associated with ACC TME. We calculated risk scores (RS) for ACC cases based on multivariate Cox results and evaluated the prognostic value of RS shown by receiver operating characteristic curve (ROC). We investigated the association between hub genes with immune infiltrates supported by algorithm from online TIMER database. Gene expression profiles and clinical data were downloaded from TCGA. Lower immune scores were observed in disease with distant metastasis (DM) and locoregional recurrence (LR) than other cases (P = .0204). Kaplan-Meier analysis revealed that lower immune scores were significantly associated with poor overall survival (OS) (P = .0495). We screened 1649 differentially expressed genes (DEGs) and 1521 DEGs based on immune scores and stromal scores, respectively. Venn plots helped us find 1122 intersect genes. After analysing by cytoHubba from Cytoscape software, 18 hub genes were found. We calculated RS and ROC showed significantly predictive accuracy (area under curve (AUC) = 0.887). ACC patients with higher RS had worse survival outcomes (P < .0001). Results from TIMER (tumor immune estimation resource) database revealed that HLA-DOA was significantly related with immune cells infiltration. We screened a list of TME-related genes which predict poor survival outcomes in ACC patients from TCGA database.

Li X ，Gao Y ，Xu Z ，Zhang Z ，Zheng Y ，Qi F ... -  《Cancer Medicine》

A five-immune-related genes-based prognostic signature for colorectal cancer.

Colorectal cancer (CRC) is a common malignancy with high morbidity and mortality. Prognosis of CRC is highly heterogeneous which hinders the making of appropriate clinical decision tremendously. We here propose to comprehensively define prognosis of CRC patients in the context of mRNA levels of immune-related genes (IRGs). CRC samples were acquired from both the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). IRGs were obtained from ImmProt database. Univariate Cox-regression analysis was adopted to screen prognostically significant IRGs for CRC patients. LASSO Cox-regression analysis was used to identify the optimal prognostic IRGs and construct the prognostic model. Multivariate Cox-regression analysis was performed to determine the independence of associations of specific factors with CRC's OS. Nomogram that combines the independent prognostic factors was constructed to predict CRC patients' 1-year, 3-years, and 5-years OS probability. There were a total of 76 differentially expressed IRGs (DEGs) in CRC tumor compared with paracancerous samples. Five out of those DEGs were significantly associated with the CRC patients' OS probability and used for the construction of prognostic model. CRC samples were divided into high-risk and low-risk group based on prognostic model. Significant differences in OS probability were obtained between high-risk and low-risk CRC patients. Additionally, a nomogram containing risk score, age and stage could effectively predict long-term OS probability of CRC patients. In conclusion, we developed a robust IRGs-based prognostic signature which should be helpful for the understanding of heterogeneity of OS probability and the future clinical research.

Zhu L ，Wang H ，Wang Z 《-》

Identification and validation of an immune prognostic signature in colorectal cancer.

Colorectal cancer (CRC) is one of the most common malignant neoplasms worldwide. Although the significant efficacy of immunotherapy has been shown, only limited CRC patients benefit from it. Therefore, we aimed to establish a prognostic signature based on immune-related genes (IRGs) to predict overall survival (OS) and the potential response to immunotherapy in CRC patients. Gene expression profiles and clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The prognostic signature composed of IRGs was established using univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analysis. CIBERSORT was used to estimate the immune cell infiltration. A total of 24 survival-related IRGs were identified from 247 differentially expressed IRGs. Then, 16 IRGs were selected to establish the prognostic signature that stratified the patients into the high-risk and low-risk groups with statistically different survival outcomes. The AUCs of the time-dependent ROC curves indicated that the signature had a strong predictive accuracy in internal and external validation sets. Multivariate cox regression analysis suggested that the signature could also act as an independent prognostic factor for OS. The low-risk group had a higher proportion of immune cell infiltration than the high-risk group, such as CD4 memory resting T cells, activated dendritic cells, and resting dendritic cells. In addition, patients in the high-risk group exhibited higher tumor mutation burden and BRAF mutation. We developed an immune-related prognostic signature to predict the OS and immune status in CRC patients. We believed that our signature is conducive to better stratification and more precise immunotherapy for CRC patients.

Li M ，Wang H ，Li W ，Peng Y ，Xu F ，Shang J ，Dong S ，Bu L ，Wang H ，Wei W ，Hu Q ，Liu L ，Zhao Q ... -  《-》

Comprehensive analysis of prognostic immune-related genes in the tumor microenvironment of colorectal cancer.

Li W ，Jin X ，Guo S ，Xu F ，Su X ，Jiang X ，Wang G ... -  《Aging-US》