Dataset Information

Tumor-Derived Peptidoglycan Recognition Protein 2 Predicts Survival and Antitumor Immune Responses in Hepatocellular Carcinoma.

ABSTRACT: BACKGROUND AND AIMS:Hepatocellular carcinoma (HCC) is linked to immunosuppression. Relieving immunosuppression has been an attractive strategy to improve the efficacy of cancer immunotherapy. Peptidoglycan recognition protein 2 (PGLYRP2) is a pattern recognition receptor which is specifically expressed in liver and implicated in the regulation of innate immunity and immunosurveillance. However, the role of hepatic PGLYRP2 in modulating immune responses against HCC remains to be investigated. APPROACH AND RESULTS:In this study, we investigated whether PGLYRP2 is able to influence HCC progression through regulating host antitumor immune responses. We demonstrated that PGLYRP2 was down-regulated in HCC, which was linked with poor prognosis in patients (P < 0.001). PGLYRP2 overexpression in HCC cells significantly enhanced antitumor immune responses in immune-competent mice and elevated immune response rates of peripheral blood mononuclear cells against HCC. Mechanistically, DNA methyltransferase 3A-mediated promoter hypermethylation was responsible for the down-regulation of PGLYRP2 in HCC. PGLYRP2 promoted production of chemokine (C-C motif) ligand 5 (CCL5) in HCC through binding to the CCL5 promoter, which contributed to the enhanced antitumor immunity. CONCLUSIONS:We provide evidence that tumor-derived PGLYRP2 acts as a candidate biomarker for adequate immune response against HCC and improved patient outcomes, indicating the importance of hepatic PGLYRP2 in cancer immunosurveillance and in designing immunotherapeutic approaches.

SUBMITTER: Yang Z

PROVIDER: S-EPMC7318564 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Tumor-Derived Peptidoglycan Recognition Protein 2 Predicts Survival and Antitumor Immune Responses in Hepatocellular Carcinoma.

Yang Zongyi Z Feng Jia J Xiao Li L Chen Xi X Yao Yuanfei Y Li Yiqun Y Tang Yu Y Zhang Shuai S Lu Min M Qian Yu Y Wu Hongjin H Shi Ming M

Hepatology (Baltimore, Md.) 20200124 5

<h4>Background and aims</h4>Hepatocellular carcinoma (HCC) is linked to immunosuppression. Relieving immunosuppression has been an attractive strategy to improve the efficacy of cancer immunotherapy. Peptidoglycan recognition protein 2 (PGLYRP2) is a pattern recognition receptor which is specifically expressed in liver and implicated in the regulation of innate immunity and immunosurveillance. However, the role of hepatic PGLYRP2 in modulating immune responses against HCC remains to be investiga ...[more]

PMID: 31479523

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Project description:BackgroundHepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear.MethodsBased on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset.ResultsA total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours.ConclusionOur IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

Dataset Information

Tumor-Derived Peptidoglycan Recognition Protein 2 Predicts Survival and Antitumor Immune Responses in Hepatocellular Carcinoma.

Publications

Tumor-Derived Peptidoglycan Recognition Protein 2 Predicts Survival and Antitumor Immune Responses in Hepatocellular Carcinoma.

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