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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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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