Evidence map›Paper›PMID 33034614›Full record

ArticleBioscience reports2020

A novel prognostic risk score model based on immune-related genes in patients with stage IV colorectal cancer.

Ke Xu, Jie He, Jie Zhang, Tao Liu, Fang Yang, Tao Ren

Abstract readValidation Study
In one paragraph

Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ke Xu *Department of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People's Republic of China.
Jie He *Department of Pulmonary and Critical Care Medicine, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People's Republic of China.
Jie ZhangDepartment of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People's Republic of China.
Tao LiuDepartment of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People's Republic of China.
Fang YangDepartment of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People's Republic of China.
Tao RenDepartment of Oncology, Clinical Medical College and The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aims of the present study were to explore immune-related genes (IRGs) in stage IV colorectal cancer (CRC) and construct a prognostic risk score model to predict patient overall survival (OS), providing a reference for individualized clinical treatment.

methodsHigh-throughput RNA-sequencing, phenotype, and survival data from patients with stage IV CRC were downloaded from TCGA. Candidate genes were identified by screening for differentially expressed IRGs (DE-IRGs). Univariate Cox regression, LASSO, and multivariate Cox regression analyses were used to determine the final variables for construction of the prognostic risk score model. GSE17536 from the GEO database was used as an external validation dataset to evaluate the predictive power of the model.

resultsA total of 770 candidate DE-IRGs were obtained, and a prognostic risk score model was constructed by variable screening using the following 12 genes: FGFR4, LGR6, TRBV12-3, NUDT6, MET, PDIA2, ORM1, IGKV3D-20, THRB, WNT5A, FGF18, and CCR8. In the external validation set, the survival prediction C-index was 0.685, and the AUC values were 0.583, 0.731, and 0.837 for 1-, 2- and 3-year OS, respectively. Univariate and multivariate Cox regression analyses demonstrated that the risk score model was an independent prognostic factor for patients with stage IV CRC. High- and low-risk patient groups had significant differences in the expression of checkpoint coding genes (ICGs).

conclusionThe prognostic risk score model for stage IV CRC developed in the present study based on immune-related genes has acceptable predictive power, and is closely related to the expression of ICGs.

Indexed as

Models, GeneticAgedBiomarkers, TumorColorectal NeoplasmsDatasets as TopicFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasm StagingPredictive Value of TestsPrognosisProtein Interaction MappingBiomarkers, Tumorimmune-related genesmetastatic colorectal canceroverall survivalprognostic modelrisk score

Identifiers

PMID33034614
PMCPMC7584813

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