Dataset Information

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients.

ABSTRACT:

Background

Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient's prognosis.

Methods

IRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene signature, which was verified in another two CRC datasets from the Gene Expression Omnibus (GEO). Gene function enrichment analysis was conducted. A prognostic nomogram was built incorporating the IRG signature with clinical risk factors.

Results

The three datasets had 487, 579, and 224 patients, respectively. A prognostic six-gene-signature (CCL22, LIMK1, MAPKAPK3, FLOT1, GPRC5B, and IL20RB) was developed through feature selection that showed good differentiation between the low- and high-risk groups in the training set (p < 0.001), which was later confirmed in the two validation groups (log-rank p < 0.05). The signature outperformed tumor TNM staging for survival prediction. GO and KEGG functional annotation analysis suggested that the signature was significantly enriched in metabolic processes and regulation of immunity (p < 0.05). When combined with clinical risk factors, the model showed robust prediction capability.

Conclusion

The immune-related six-gene signature is a reliable prognostic indicator for CRC patients and could provide insight for personalized cancer management.

SUBMITTER: Dai S

PROVIDER: S-EPMC7746810 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients.

Dai Siqi S Xu Shuang S Ye Yao Y Ding Kefeng K

Frontiers in genetics 20201204

<h4>Background</h4>Despite recent advance in immune therapy, great heterogeneity exists in the outcomes of colorectal cancer (CRC) patients. In this study, we aimed to analyze the immune-related gene (IRG) expression profiles from three independent public databases and develop an effective signature to forecast patient's prognosis.<h4>Methods</h4>IRGs were collected from the ImmPort database. The CRC dataset from The Cancer Genome Atlas (TCGA) database was used to identify a prognostic gene sign ...[more]

PMID: 33343640

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Project description:Background: Immune checkpoint inhibitors have been successfully used in a variety of tumors, however, the efficacy of immune checkpoint blockade therapy for patients with glioma is limited. In this study, we tried to clarify gene expression signatures related to the prognosis of gliomas and construct a signature to predict the survival of patients with gliomas. Methods: Calcium-related differential expressed genes (DEGs) between gliomas and normal brain tissues were comprehensively analyzed in two independent databases. Univariate, multivariate Cox regression analysis and proportional hazards model were used to identify the prognostic of calcium-related risk score signature. The CIBERSORT algorithm and association analysis were carried out to evaluate the relationship between calcium-related signature and characteristic clinical features, tumor-infiltrating immune cell signatures as well as immune checkpoint molecules in glioma. A nomogram model was developed for predicting the overall survival for patients with gliomas. Results: We found the intersection of 415 DEGs between gliomas and normal brain tissues, and identified that an eighteen calcium-related gene panel was significantly enriched in these DEGs. A calcium-related signature derived risk score was developed to divide patients into high- and low-risk groups. Low levels of calcium-related gene expression in high-risk score cases were accompanied with worse outcomes of patients. Calcium-related risk scores were significantly associated with characteristic clinical features, immune infiltrating signatures of tumor microenvironment, and exhausted T cell markers including programmed cell death 1 (PD-1), lymphocyte activating 3 (LAG3), and T cell membrane protein 3 (TIM-3), which contribute to an adverse therapeutic effect of immunotherapy. Calcium-related signature risk score was considered as an independent prognostic parameter to predict the of overall survival of patients with gliomas in nomogram model. Conclusion: Our study demonstrated that calcium signaling pathway is highly associated with immunosuppression of gliomas and overall survival of patients. Targeting the calcium signaling pathway might be a new strategy to reverse the immunosuppressive microenvironment of gliomas and improve the efficacy of glioma immunotherapy.

Dataset Information

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients.

Background

Methods

Results

Conclusion

Publications

Identification of an Immune-Related Gene Signature to Improve Prognosis Prediction in Colorectal Cancer Patients.

Similar Datasets

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