Dataset Information

A novel prognostic signature of immune-related genes for patients with colorectal cancer.

ABSTRACT: Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with an estimated 1.8 million new cases worldwide and associated with high mortality rates of 881 000 CRC-related deaths in 2018. Screening programs and new therapies have only marginally improved the survival of CRC patients. Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets. The aim of this study was to identify an immune-related prognostic signature for CRC. To this end, we combined gene expression and clinical data from the CRC data sets of The Cancer Genome Atlas (TCGA) into an integrated immune landscape profile. We identified a total of 476 IRGs that were differentially expressed in CRC vs normal tissues, of which 18 were survival related according to univariate Cox analysis. Stepwise multivariate Cox proportional hazards analysis established an immune-related prognostic signature consisting of SLC10A2, FGF2, CCL28, NDRG1, ESM1, UCN, UTS2 and TRDC. The predictive ability of this signature for 3- and 5-year overall survival was determined using receiver operating characteristics (ROC), and the respective areas under the curve (AUC) were 79.2% and 76.6%. The signature showed moderate predictive accuracy in the validation and GSE38832 data sets as well. Furthermore, the 8-IRG signature correlated significantly with tumour stage, invasion, lymph node metastasis and distant metastasis by univariate Cox analysis, and was established an independent prognostic factor by multivariate Cox regression analysis for CRC. Gene set enrichment analysis (GSEA) revealed a relationship between the IRG prognostic signature and various biological pathways. Focal adhesions and ECM-receptor interactions were positively correlated with the risk scores, while cytosolic DNA sensing and metabolism-related pathways were negatively correlated. Finally, the bioinformatics results were validated by real-time RT-qPCR. In conclusion, we identified and validated a novel, immune-related prognostic signature for patients with CRC, and this signature reflects the dysregulated tumour immune microenvironment and has a potential for better CRC patient management.

SUBMITTER: Wang J

PROVIDER: S-EPMC7412433 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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A novel prognostic signature of immune-related genes for patients with colorectal cancer.

Wang Jun J Yu Shaojun S Chen Guofeng G Kang Muxing M Jin Xiaoli X Huang Yi Y Lin Lele L Wu Dan D Wang Lie L Chen Jian J

Journal of cellular and molecular medicine 20200621 15

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with an estimated 1.8 million new cases worldwide and associated with high mortality rates of 881 000 CRC-related deaths in 2018. Screening programs and new therapies have only marginally improved the survival of CRC patients. Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets. The aim of this study was to identify an immune-related prognostic signature for CRC. To this end, we combined ...[more]

PMID: 32564470

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Project description:Colorectal cancer (CRC) is second most commonly diagnosed cancer with high morbidity and mortality. The heterogeneity of CRC makes clinical treatment tremendously challenging. Here, we aimed to comprehensively analyze the prognosis of CRC patients based on ANOIKIS- and immune-related genes. ANOIKIS-related genes were identified by differentially analysis of high anoikis score group (ANOIKIS_high group) and low anoikis score group (ANOIKIS_low group) divided by the cutoff value of anoikis score. Immune-related genes were screened by differentially analysis of high immune score group (ImmuneScore_high group) and low immune score group (ImmuneScore_low group) classified by the cutoff value of ImmuneScore. Prognostic ANOIKIS- and immune-related genes were identified by univariate Cox regression analysis. Multivariate Cox regression analysis were used for prognostic model construction. Ferroptosis expression profiles, the infiltration of immune cells, and the somatic mutation status were analyzed and compared. Univariate and multivariate Cox-regression analyses were performed to identify independent prognostic factors for CRC patient. Nomogram that contained the independent prognostic factors was established to predict 1-, 3-, and 5-year OS probability of CRC patients. Three ANOIKIS- and immune-related signatures were applied to construct a prognostic model, which divided the CRC patients into high-risk and low-risk groups. The patients with high-risk scores had obviously shorter OSs than those with low-risk scores. The time dependent ROC curve indicated that the risk score model had a stable performance to predict survival rates. Notably, the age, pathologic T, and risk score could be used independent indicators for CRC prognosis prediction. A nomogram containing the independent prognostic factors showed that the nomogram accurately predicted 1-, 3-, and 5-year survival rates of CRC patients. In our research, a novel prognostic model was developed based on ANOIKIS- and immune-related genes in CRC, which could be used for prognostic prediction of CRC patients.

Project description:Background: Anoikis is a type of apoptosis associated with cell detachment. Resistance to anoikis is a focal point of tumor metastasis. This study aimed to explore the relationship among anoikis-related genes (ARGs), immune infiltration, and prognosis in colorectal cancer (CRC). Methods: The transcriptome profile and clinical data on patients with CRC were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Patients were divided into two clusters based on the expression of ARGs. Differences between the two ARG molecular subtypes were analyzed in terms of prognosis, functional enrichment, gene mutation frequency, and immune cell infiltration. An ARG-related prognostic signature for predicting overall survival in patients with CRC was developed and validated using absolute value convergence and selection operator (LASSO) regression analysis. The correlation between the signature risk score and clinicopathological features, immune cell infiltration, immune typing, and immunotherapy response was analyzed. The risk score combined with clinicopathological characteristics was used to construct a nomogram to assess CRC patients' prognosis. Results: Overall, 151 ARGs were differentially expressed in CRC. Two ARG subtypes, namely, ARG-high and ARG-low groups, were identified and correlated with CRC prognosis. The gene mutation frequency and immune, stromal, and ESTIMATE scores of the ARG-high group were higher than those of the ARG-low group. Moreover, CD8, natural killer cells, M1 macrophages, human leukocyte antigen (HLA), and immune checkpoint-related genes were significantly increased in the ARG-high group. An optimized 25-gene CRC prognostic signature was successfully constructed, and its prognostic predictive ability was validated. The high-risk score was correlated with T, N, M, and TNM stages. Risk scores were negatively correlated with dendritic cells, eosinophils, and CD4 cells, and significantly positively correlated with regulatory T cells. Patients in the high-risk group were more likely to exhibit immune unresponsiveness. Finally, the nomogram model was constructed and showed good prognostic predictive power. Conclusion: ARGs are associated with clinicopathological features and the prognosis of CRC, and play important roles in the immune microenvironment. Herein, we underpinned the usefulness of ARGs in CRC to develop more effective immunotherapy techniques.

Dataset Information

A novel prognostic signature of immune-related genes for patients with colorectal cancer.

Publications

A novel prognostic signature of immune-related genes for patients with colorectal cancer.

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