Predicting the clinical outcome of melanoma using an immune-related gene pairs signature

Meng, Liangliang; He, Xiaoxi; Xiao, Zhang; Zhang, Xiaobo; Wei, Yingtian; Wu, Bin; Li, Wei; Li, Jing; Xiao, Yueyong

doi:10.1371/journal.pone.0240331

Cited by 11 publications

(9 citation statements)

References 40 publications

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“…Meng et al. established a signature consisted of 33 immune-related gene (IRG) pairs which associated with OS in malignant melanoma and analyzed the variations of the abundance of immune cells ( 21 ). Liu et al.…”

Section: Discussionmentioning

confidence: 99%

Development of an Immune-Related Gene Signature for Prognosis in Melanoma

et al. 2021

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Melanoma remains a potentially deadly malignant tumor. The incidence of melanoma continues to rise. Immunotherapy has become a new treatment method and is widely used in a variety of tumors. Original melanoma data were downloaded from TCGA. ssGSEA was performed to classify them. GSVA software and the "hclust" package were used to analyze the data. The ESTIMATE algorithm screened DEGs. The edgeR package and Venn diagram identified valid immune-related genes. Univariate, LASSO and multivariate analyses were used to explore the hub genes. The "rms" package established the nomogram and calibrated the curve. Immune infiltration data were obtained from the TIMER database. Compared with that of samples in the high immune cell infiltration cluster, we found that the tumor purity of samples in the low immune cell infiltration cluster was higher. The immune score, ESTIMATE score and stromal score in the low immune cell infiltration cluster were lower. In the high immune cell infiltration cluster, the immune components were more abundant, while the tumor purity was lower. The expression levels of TIGIT, PDCD1, LAG3, HAVCR2, CTLA4 and the HLA family were also higher in the high immune cell infiltration cluster. Survival analysis showed that patients in the high immune cell infiltration cluster had shorter OS than patients in the low immune cell infiltration cluster. IGHV1-18, CXCL11, LTF, and HLA-DQB1 were identified as immune cell infiltration-related DEGs. The prognosis of melanoma was significantly negatively correlated with the infiltration of CD4+ T cells, CD8+ T cells, dendritic cells, neutrophils and macrophages. In this study, we identified immune-related melanoma core genes and relevant immune cell subtypes, which may be used in targeted therapy and immunotherapy of melanoma.

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Section: Discussionmentioning

confidence: 99%

Development of an Immune-Related Gene Signature for Prognosis in Melanoma

et al. 2021

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“… Zhang et al (2019) developed a potent signature with 20 immune-related gene pairs to predict OS for serous ovarian carcinoma patients, shedding new light for postoperative treatment. Meng et al (2020) defined a reliable prognosis-related model for melanoma formed from immune gene pairs and proved its efficacy in other independent datasets). In this study, we managed to construct a reliable prognostic model consisting of 15 irlncRNA pairs to predict OS for CRC patients.…”

Section: Discussionmentioning

confidence: 96%

Predicting the Survival and Immune Landscape of Colorectal Cancer Patients Using an Immune-Related lncRNA Pair Model

Zhang

Zhao

et al. 2021

Front. Genet.

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BackgroundAccumulating evidence has demonstrated that immune-related long non-coding ribonucleic acids (irlncRNAs) can be used as prognostic indicators of overall survival (OS) in patients with colorectal cancer (CRC). Our aim in this research, therefore, was to construct a risk model using irlncRNA pairs with no requirement for a specific expression level, in hope of reliably predicting the prognosis and immune landscape of CRC patients.MethodsClinical and transcriptome profiling data of CRC patients downloaded from the Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed (DE) irlncRNAs. The irlncRNA pairs significantly correlated with the prognosis of patients were screened out by univariable Cox regression analysis and a prognostic model was constructed by Lasso and multivariate Cox regression analyses. A receiver operating characteristic (ROC) curve was then plotted, with the area under the curve calculated to confirm the reliability of the model. Based on the optimal cutoff value, CRC patients in the high- or low-risk groups were distinguished, laying the ground for evaluating the risk model from the following perspectives: survival, clinicopathological traits, tumor-infiltrating immune cells (TIICs), antitumor drug efficacy, kinase inhibitor efficacy, and molecules related to immune checkpoints.ResultsA prognostic model consisting of 15 irlncRNA pairs was constructed, which was found to have a high correlation with patient prognosis in a cohort from the TCGA (p < 0.001, HR = 1.089, 95% CI [1.067–1.112]). According to both univariate and multivariate Cox analyses, this model could be used as an independent prognostic indicator in the TCGA cohort (p < 0.001). Effective differentiation between high- and low-risk patients was also accomplished, on the basis of aggressive clinicopathological characteristics, sensitivity to antitumor drugs, and kinase inhibitors, the tumor immune infiltration status, and the expression levels of specific molecules related to immune checkpoints.ConclusionThe prognostic model established with irlncRNA pairs is a promising indicator for prognosis prediction in CRC patients.

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“…The primary function of macrophages is phagocytosis and digestion of cellular debris and pathogens, and activation of other immune cells. M0 macrophages are non-activated macrophages without any inflammatory or tumor-associated function and can be transformed into classically activated M1 macrophages and alternatively activated M2 macrophages ( 37 , 38 ). M1 macrophages have a primary anti-tumor role, distinguishing tumor cells from healthy cells, recognizing and then killing tumor cells by mediating cytotoxic effects.…”

Section: Discussionmentioning

confidence: 99%

CCR4, CCR8, and P2RY14 as Prognostic Factors in Head and Neck Squamous Cell Carcinoma Are Involved in the Remodeling of the Tumor Microenvironment

Meng

Qin

et al. 2021

Front. Oncol.

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The tumor microenvironment (TME) plays a critical role in the initiation and progression of cancer. However, the specific mechanism of its regulation in head and neck squamous cell carcinoma (HNSCC) remains unclear. In this study, we first applied the ESTIMATE method to calculate the immune and stromal scores in patients’ tumor tissues from The Cancer Genome Atlas (TCGA) database. GSE41613, GSE30784, and GSE37991 data sets from the Gene Expression Omnibus (GEO) database were recruited for further validation. Differentially expressed genes (DEGs) were identified and then analyzed by Cox regression analysis and protein-protein interaction (PPI) network construction. DEGs significantly associated with prognosis and TME will be identified as hub genes. These genes were also validated at the protein level by immunohistochemical analysis of 10 pairs of primary tumor tissues and the adjacent normal tissues from our institution. The relationship between hub genes expression and immune cell fraction estimated by CIBERSORT software was also examined. 275 DEGs were significantly associated with TME. CCR4, CCR8, and P2RY14 have then identified as hub genes by intersection Cox and PPI analysis. Further investigation revealed that the expression of CCR4, CCR8, and P2RY14 was negatively correlated with clinicopathological characteristics (clinical stage, T stage) and positively associated with survival in HNSCC patients, especially in male patients. The expression of CCR8 and P2RY14 was lower in males than in females. CCR8 and P2RY14 were differentially expressed in tumor tissues than normal tissues, and the results were validated at the protein level by immunohistochemistry experiments. Gene set enrichment analysis (GSEA) showed that the high expression groups’ hub genes were mainly enriched for immune-related activities. In the low-expression groups, genes were primarily enriched in metabolic pathways. CIBERSORT results showed that the expression of these genes was all negatively correlated with the fraction of memory B cells and positively correlated with the fraction of the other four cells, including naive B cells, resting T cells CD4 memory, T cells follicular helper, and T cells regulatory (Tregs). The results suggest that CCR4, CCR8, and P2RY14 may be responsible for maintaining the immune dominance of TME, thus leading to a better prognosis.

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Predicting the clinical outcome of melanoma using an immune-related gene pairs signature

Cited by 11 publications

References 40 publications

Development of an Immune-Related Gene Signature for Prognosis in Melanoma

Development of an Immune-Related Gene Signature for Prognosis in Melanoma

Predicting the Survival and Immune Landscape of Colorectal Cancer Patients Using an Immune-Related lncRNA Pair Model

CCR4, CCR8, and P2RY14 as Prognostic Factors in Head and Neck Squamous Cell Carcinoma Are Involved in the Remodeling of the Tumor Microenvironment

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