Identification of molecular subtypes and a novel prognostic model of diffuse large B-cell lymphoma based on a metabolism-associated gene signature

He, Jinbo; Chen, Ziwei; Xue, Qingfeng; Sun, Pingping; Wang, Yuan; Zhu, Cindy; Shi, Wenyu

doi:10.1186/s12967-022-03393-9

Cited by 32 publications

(30 citation statements)

References 72 publications

(59 reference statements)

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“…For the convenience of application, we have constructed a nomogram. Age, gender, TNM staging, stage, and risk score were utilized as predictive parameters to construct the nomogram ( 24 ), and we calculated the total points to obtain the 1-, 2-, and 3-year overall survival in LUAD ( Figure 6A ). Furthermore, for the accuracy of the model, we used the consistency index (C-index) and calibration curve to estimate.…”

Section: Resultsmentioning

confidence: 99%

Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma

Chen

Wang

et al. 2022

Front. Immunol.

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ObjectiveLung adenocarcinoma (LUAD) is a familiar lung cancer with a very poor prognosis. This study investigated the immune- and stemness-related genes to develop model related with cancer immunity and prognosis in LUAD.MethodThe Cancer Genome Atlas (TCGA) was utilized for obtaining original transcriptome data and clinical information. Differential expression, prognostic value, and correlation with clinic parameter of mRNA stemness index (mRNAsi) were conducted in LUAD. Significant mRNAsi-related module and hub genes were screened using weighted gene coexpression network analysis (WGCNA). Meanwhile, immune-related differential genes (IRGs) were screened in LUAD. Stem cell index and immune-related differential genes (SC-IRGs) were screened and further developed to construct prognosis-related model and nomogram. Comprehensive analysis of hub genes and subgroups, involving enrichment in the subgroup [gene set enrichment analysis (GSEA)], gene mutation, genetic correlation, gene expression, immune, tumor mutation burden (TMB), and drug sensitivity, used bioinformatics and reverse transcription polymerase chain reaction (RT-PCR) for verification. ResultsThrough difference analysis, mRNAsi of LUAD group was markedly higher than that of normal group. Clinical parameters (age, gender, and T staging) were ascertained to be highly relevant to mRNAsi. MEturquoise and MEblue were found to be the most significant modules (including positive and negative correlations) related to mRNAsi via WGCNA. The functions and pathways of the two mRNAsi-related modules were mainly enriched in tumorigenesis, development, and metastasis. Combining stem cell index–related differential genes and immune-related differential genes, 30 prognosis-related SC-IRGs were screened via Cox regression analysis. Then, 16 prognosis-related SC-IRGs were screened to construct a LASSO regression model at last. In addition, the model was successfully validated by using TCGA-LUAD and GSE68465, whereas c-index and the calibration curves were utilized to demonstrate the clinical value of our nomogram. Following the validation of the model, GSEA, immune cell correlation, TMB, clinical relevance, etc., have found significant difference in high- and low-risk groups, and 16-gene expression of the SC-IRG model also was tested by RT-PCR. ADRB2, ANGPTL4, BDNF, CBLC, CX3CR1, and IL3RA were found markedly different expression between the tumor and normal group.ConclusionThe SC-IRG model and the prognostic nomogram could accurately predict LUAD survival. Our study used mRNAsi combined with immunity that may lay a foundation for the future research studies in LUAD.

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Section: Resultsmentioning

confidence: 99%

Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma

Chen

Wang

et al. 2022

Front. Immunol.

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“…No. 13684, Cell Signaling Technology) were stained by IHC to detect the expression of IRF4 and PD-L1 (1 : 50 dilution) [ 16 ]. Briefly, 4 μ m of tissue array sections were blocked with dehydrated peroxidase.…”

Section: Methodsmentioning

confidence: 99%

Immunogenomic-Based Analysis of Hierarchical Clustering of Diffuse Large Cell Lymphoma

Wang

Yuan

et al. 2022

Journal of Immunology Research

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Diffuse large B cell lymphoma (DLBCL) is one of the most usual types of adult lymphoma with heterogeneousness in histological morphology, prognosis, and clinical indications. Prior to this, several studies were carried out to determine the DLBCL subtype based on the analysis of the genome profile. However, classification based on assessment of genes related to the immune system has limited clinical significance for DLBCL. We systematically explored the DLBCL gene expression dataset and provided publicly available clinical information on patients with GEO. In this research, 928 DLBCL samples were applied, and we calculated 29 immune-related genomes’ enrichment levels in each sample and stratified them into high immunity (Immunity_H, n = 135 , 28.7%), moderate immunity (Immunity_M, n = 135 , 28.7%), and low immunity (Immunity_L, n = 12 , 2.6%) that was based on ssGSEA score. The ESTIMATE algorithm was used to calculate stromal scores (range 586.88 to 1982.43), immune scores, estimated scores (range 2,618.2 to 8,098.14), and tumor purity (range 0.216 to 0.976). All of them were significantly correlated with immune subtypes (Kruskal-Wallis test, p < 0.001 ). At the same time, the correlation of related genes was analyzed by immunohistochemistry staining. In addition, DLBCL cells were cultured in transfected and in vitro with siRNA to verify correlation analysis and gene expression. Finally, human peripheral blood lymphocytes were incubated with DLBCL cells and stained. Flow cytometry was applied to analyze genes’ influence on immune function. By analysis, immune checkpoint and HLA gene expression levels were higher in the Immunity_H group (Kruskal-Wallis test, p < 0.05 ). The levels of Tfhs (follicular helper T cells), monocytes, CD8+ T cells, M1 macrophages, M2 macrophages, and CD4+ memory-activated T cells were the most excellent in Immunity_H, and the total survival rate was higher in the Immunity_L. Through analysis, IRF4 (MUM1) was identified by us as immunotherapeutic target and a potential prognostic marker for DLBCL, which was made sure by using molecular biology experimentations. To conclude, immunosignature made a connection between DLBCL subtypes playing a position in DLBCL prognostic stratification. Immunocharacteristics-related DLBCL subtypes’ construction predicts expected patient results and supplies conceivable immunotherapy candida.

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“…ESTIMATE and ssGSEA algorithms were used to calculate the expression levels of immune microenvironment components in LUSC tissues ( 17 ). The association between IL18R1 expression and stromal, immune, and estimate scores and 24 immune cells was visualized by Pearson analysis and scatter plot.…”

Section: Methodsmentioning

confidence: 99%

Downregulation of T-cell cytotoxic marker IL18R1 promotes cancer proliferation and migration and is associated with dismal prognosis and immunity in lung squamous cell carcinoma

Guo

Jiang

et al. 2022

Front. Immunol.

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Immunotherapy can improve the survival of patients with advanced lung squamous cell carcinoma (LUSC). T cytotoxic cells are one of the main members of the immune microenvironment. Herein, we aimed to identify the roles of T-cell cytotoxic markers interleukin 18 (IL18) receptor 1 (IL18R1) in the LUSC progression using bioinformatics, clinical tissue specimen, and cell experiment. We assessed the association between the IL18R1 expression and immune infiltration and IL18R1-related competing RNA network. The IL18R1 expression was downregulated in the LUSC tissues. The IL18R1 expression downregulation was associated with diagnosis and short overall survival and disease-specific survival, and it was also an independent risk factor for dismal survival time in LUSC. IL18R1-related nomograms predicted the survival time of patients with LUSC. IL18R1 overexpression inhibited the proliferation, migration, and invasion of LUSC cells. The IL18R1 expression was significantly associated with the microenvironment (stromal, immune, and estimate scores), immune cells (such as the T cells, cytotoxic cells, CD8 T cells), and immune cell markers (such as the CD8A, PD-1, and CTLA4) in LUSC. AC091563.1 and RBPMS-AS1 downregulation was positively associated with the IL18R1 expression, negatively associated with the miR-128-3p expression, and associated with short disease-specific survival and progression in LUSC. In conclusion, IL18R1 was significantly downregulated and associated with the prognosis and immune microenvironment. IL18R1 overexpression inhibits the growth and migration of cancer cells in LUSC. Furthermore, AC091563.1 and RBPMS-AS1 might compete with IL18R1 to bind miR-128-3p for participating in LUSC progression. These results showed that IL18R1 is a biomarker for evaluating the prognosis of patients with LUSC.

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Identification of molecular subtypes and a novel prognostic model of diffuse large B-cell lymphoma based on a metabolism-associated gene signature

Cited by 32 publications

References 72 publications

Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma

Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma

Immunogenomic-Based Analysis of Hierarchical Clustering of Diffuse Large Cell Lymphoma

Downregulation of T-cell cytotoxic marker IL18R1 promotes cancer proliferation and migration and is associated with dismal prognosis and immunity in lung squamous cell carcinoma

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