scholarly journals Development and validation of a LRP1B mutation-associated prognostic model for hepatocellular carcinoma

2021 ◽  
Author(s):  
Jian Xu ◽  
Xiaomin Shen ◽  
Bo Zhang ◽  
Rui Su ◽  
Mingxuan Cui ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Gene Mutation ◽  
Prognostic Model ◽  
Immune Cell ◽  
Low Risk ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Significant Difference

Purpose: To develop a LRP1B gene mutation based prognostic model for hepatocellular carcinoma (HCC) patients risk prediction. Methods: The LRP1B gene mutation rate was calculated from HCC patient samples. Meanwhile, differentially expressed genes according to LRP1B mutant were screened out for prognostic model establishment. Based on this innovative model, HCC patients were categoried into high and low-risk group. The immune status including immune cell infiltration ratio and checkpoints have been explored in two groups. The functions of LRP1B and risk factors in the model were verified using both in vivo and in vitro experiments. Results: It could be demonstrated that LRP1B was a potential negative predictor for HCC patients prognosis with high mutation frequency. The functions of LRP1B was verified with ELISA assay and Quantitative Real-time PCR method based on clinical recruited HCC participants. 11 genes displayed significant differences according to LRP1B status, which could better predict HCC patient prognosis. The functions of these genes were examined using HCC cell line HCCLM3, suggesting they played a pivotal role in determining HCC cell proliferation and apoptosis. From the immune cell infiltration ratio analysis, there was a significant difference in the infiltration degree of 7 types of immune cells and 2 immune checkpoints between high and low-risk HCC patients. Conclusion: This study hypothesized a potential prognostic biomarker and developed a novel LRP1B mutation-associated prognostic model for hepatocellular carcinoma, which provided a systematic reference for future understanding of clinical research.

scholarly journals Development and validation of a LRP1B mutation-associated prognostic model for hepatocellular carcinoma

2021 ◽  
Author(s):  
Jian Xu ◽  
Xiaomin Shen ◽  
Bo Zhang ◽  
Rui Su ◽  
Mingxuan Cui ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Gene Mutation ◽  
Prognostic Model ◽  
Immune Cell ◽  
Low Risk ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Significant Difference ◽  
Patient Prognosis

Abstract Purpose: To develop a LRP1B gene mutation based prognostic model for hepatocellular carcinoma (HCC) patients risk prediction. Methods: The LRP1B gene mutation rate was calculated from HCC patient samples. Meanwhile, differentially expressed genes according to LRP1B mutant were screened out for prognostic model establishment. Based on this innovative model, HCC patients were categoried into high and low-risk group. The immune status including immune cell infiltration ratio and checkpoints have been explored in two groups. Results: It can be shown here 11 genes demonstrate significant differences according to LRP1B status, which can better predict HCC patient prognosis. The accuracy of the model prediction is evaluated and approved by the AUC value. From the immune cell infiltration ratio analysis, there is a significant difference in the infiltration degree of 7 types of immune cells and 2 immune checkpoints between high and low-risk HCC patients. Meanwhile, LRP1B was tested as a prognostic marker in clinic to predict different stages for HCC with satisfied accurancy. Conclusion: This study has explored a potential prognostic biomarker and developed a novel LRP1B mutation-associated prognostic model for hepatocellular carcinoma, which provides a systematic reference for future better understanding of clinical research.

scholarly journals Signatures Based On Tumor Microenvironment Genes Can Reliably Predict The Prognosis of Laryngeal Cancer Patients

2021 ◽  
Author(s):  
Haitang Ren ◽  
Zheng Luo ◽  
Min Wang ◽  
Lei Chen ◽  
Bo Zhang
Keyword(s):  
Tumor Microenvironment ◽  
Cancer Patients ◽  
Laryngeal Cancer ◽  
Prognostic Model ◽  
Immune Cell ◽  
Low Risk ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Significant Difference

Abstract Purpose: To develop a tumor microenvironment (TME) related genes based prognostic model for laryngeal cancer patients risk prediction. Methods: A innovative prognosic model was generated based on TME related genes (760 genes). Based on the model, laryngeal cancer patients were categoried into high and low-risk group. The immune status including immune cell infiltration ratio as well as checkpoints have been exploreds.Results: It can be shown here 15 genes demonstrate significant differences, which can better predict laryngeal cancer patient prognosis. The accuracy of the model prediction is evaluated and approved by the AUC value. From the immune cell infiltration ratio analysis, there is a significant difference in the infiltration degree of several types of immune cells and 6 immune checkpoints between high and low-risk laryngeal cancer patients. At the same time, the close related genes as well as TME pathways have been also investigated.Conclusion: This study has explored a potential prognostic biomarker and developed a novel TME-associated prognostic model for laryngeal cancer, which provides a valuable reference for future clinical research.

scholarly journals Signatures based on tumor microenvironment genes can reliably predict the prognosis of laryngeal cancer patients

2021 ◽  
Author(s):  
Haitang Ren ◽  
Zheng Luo ◽  
Min Wang ◽  
Lei Chen ◽  
Bo Zhang
Keyword(s):  
Tumor Microenvironment ◽  
Cancer Patients ◽  
Laryngeal Cancer ◽  
Prognostic Model ◽  
Immune Cell ◽  
Low Risk ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Significant Difference

Abstract Purpose: To develop a tumor microenvironment (TME) related genes based prognostic model for laryngeal cancer patients risk prediction. Methods: A innovative prognosic model was generated based on TME related genes (760 genes). Based on the model, laryngeal cancer patients were categoried into high and low-risk group. The immune status including immune cell infiltration ratio as well as checkpoints have been exploreds. Results: It can be shown here 15 genes demonstrate significant differences, which can better predict laryngeal cancer patient prognosis. The accuracy of the model prediction is evaluated and approved by the AUC value. From the immune cell infiltration ratio analysis, there is a significant difference in the infiltration degree of several types of immune cells and 6 immune checkpoints between high and low-risk laryngeal cancer patients. At the same time, the close related genes as well as TME pathways have been also investigated. Conclusion: This study has explored a potential prognostic biomarker and developed a novel TME-associated prognostic model for laryngeal cancer, which provides a valuable reference for future clinical research.

scholarly journals Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuomao Mo ◽  
Daiyuan Liu ◽  
Dade Rong ◽  
Shijun Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

scholarly journals Significant correlation between HSPA4 and prognosis and immune regulation in hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12315
Author(s):  
Bing-Bing Shang ◽  
Jun Chen ◽  
Zhi-Guo Wang ◽  
Hui Liu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dna Methylation ◽  
Roc Curve ◽  
Immune Regulation ◽  
Immune Cell ◽  
Genetic Alterations ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Cancer Stage

Background Hepatocellular carcinoma (HCC) is an inflammation-associated tumor involved in immune tolerance and evasion in the immune microenvironment. Heat shock proteins (HSPs) are involved in the occurrence, progression, and immune regulation of tumors. Therefore, HSPs have been considered potential therapeutic targets. Here, we aimed to elucidate the value of HSP family A (Hsp70) member 4 (HSPA4) in the diagnosis and predicting prognosis of HCC, and its relationship with immune cell infiltration, immune cell biomarkers, and immune checkpoints. Gene mutation, DNA methylation, and the pathway involved in HCC were also analyzed. Methods The gene expression omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were used to compare HSPA4 expression, and the results were confirmed by immunohistochemical staining of clinical samples. R package was used to analyze the correlation between HSPA4 and cancer stage, and to establish receiver operating characteristic (ROC) curve of diagnosis, time-dependent survival ROC curve, and a nomogram model. cBioPortal and MethSurv were used to identify genetic alterations and DNA methylation, and their effect on prognosis. The Tumor Immune Estimation Resource (TIMER) was used to analyze immune cell infiltration, immune cell biomarkers, and immune checkpoints. The STRING database was used to analyze protein–protein interaction network information. Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the functions of HSPA4 and its functional partner genes. Results Overexpression of HSPA4 was identified in 25 cancers. Overexpression of HSPA4 considerably correlated with cancer stage and alpha-fetoprotein (AFP) level in HCC. Patients with higher HSPA4 expression showed poorer prognosis. HSPA4 expression can accurately identify tumor from normal tissue (AUC = 0.957). The area under 1-, 3-, and 5-year survival ROCs were above 0.6. The HSPA4 genetic alteration rate was 1.3%. Among the 14 DNA methylation CpG sites, seven were related to the prognosis of HCC. HSPA4 was positively related to immune cell infiltration and immune checkpoints (PD-1 and CTLA-4) in HCC. The KEGG pathway enrichment analysis revealed HSPA4 enrichment in antigen processing and presentation together with HSPA8 and HSP90AA1. We verified the value of HSPA4 in the diagnosis and predicting prognosis of HCC. HSPA4 may not only participate in the occurrence and progression but also the immune regulation of HCC. Therefore, HSPA4 can be a potential diagnostic and prognostic biomarker and a therapeutic target for HCC.

scholarly journals ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Yuanyuan Feng ◽  
Xinfang Tang ◽  
Changcheng Li ◽  
Ying Su ◽  
Xiaoyu Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Migration And Invasion ◽  
Risk Indicator ◽  
Immune Cell Infiltration

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

scholarly journals Identification of Glycolysis-Related lncRNAs and the Novel lncRNA WAC-AS1 Promotes Glycolysis and Tumor Progression in Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Xigang Xia ◽  
Hao Zhang ◽  
Peng Xia ◽  
Yimin Zhu ◽  
Jie Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Expression Analysis ◽  
Risk Score ◽  
Prognostic Model ◽  
Immune Cell ◽  
Differential Expression Analysis ◽  
Lactate Production ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Analysis

BackgroundHigh glycolysis efficiency in tumor cells can promote tumor growth. lncRNAs play an important role in the proliferation, metabolism and migration of cancer cells, but their regulation of tumor glycolysis is currently not well researched.MethodsWe analyzed the co-expression of glycolysis-related genes and lncRNAs in The Cancer Genome Atlas (TCGA) database to screen glycolysis-related lncRNAs. Further prognostic analysis and differential expression analysis were performed. We further analyzed the relationship between lncRNAs and tumor immune infiltration. Since WAC antisense RNA 1 (WAC-AS1) had the greatest effect on the prognosis among all screened lncRNAs and had a larger coefficient in the prognostic model, we chose WAC-AS1 for further verification experiments and investigated the function and mechanism of action of WAC-AS1 in hepatocellular carcinoma.ResultsWe screened 502 lncRNAs that have co-expression relationships with glycolytic genes based on co-expression analysis. Among them, 112 lncRNAs were abnormally expressed in liver cancer, and 40 lncRNAs were related to the prognosis of patients. Eight lncRNAs (WAC-AS1, SNHG3, SNHG12, MSC-AS1, MIR210HG, PTOV1-AS1, AC145207.5 and AL031985.3) were used to established a prognostic model. Independent prognostic analysis (P<0.001), survival analysis (P<0.001), receiver operating characteristic (ROC) curve analysis (AUC=0.779) and clinical correlation analysis (P<0.001) all indicated that the prognostic model has good predictive power and that the risk score can be used as an independent prognostic factor (P<0.001). The risk score and lncRNAs in the model were found to be related to a variety of immune cell infiltration and immune functions. WAC-AS1 was found to affect glycolysis and promote tumor proliferation (P<0.01). WAC-AS1 affected the expression of several glycolysis-related genes (cAMP regulated phosphoprotein 19 (ARPP19), CHST12, MED24 and KIF2A) (P<0.01). Under hypoxic conditions, WAC-AS1 regulated ARPP19 by sponging miR-320d to promote glucose uptake and lactate production (P<0.01).ConclusionWe constructed a model based on glycolysis-related lncRNAs to evaluate the prognostic risk of patients. The risk score and lncRNAs in the model were related to immune cell infiltration. WAC-AS1 can regulate ARPP19 to promote glycolysis and proliferation by sponging miR-320d.

scholarly journals Identification of an m6A Regulators-Mediated Prognosis Signature For Survival Prediction and Its Relevance to Immune Infiltration in Melanoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Liuxing Wu ◽  
Xin Hu ◽  
Hongji Dai ◽  
Kexin Chen ◽  
Ben Liu
Keyword(s):  
High Risk ◽  
Immune Cell ◽  
Risk Group ◽  
Low Risk ◽  
Cell Infiltration ◽  
Survival Prediction ◽  
Immune Cell Infiltration ◽  
Immune Infiltration ◽  
Related Risk ◽  
Significant Difference

Despite robust evidence for the role of m6A in cancer development and progression, its association with immune infiltration and survival outcomes in melanoma remains obscure. Here, we aimed to develop an m6A-related risk signature to improve prognostic and immunotherapy responder prediction performance in the context of melanoma. We comprehensively analyzed the m6A cluster and immune infiltration phenotypes of public datasets. The TCGA (n = 457) and eleven independent melanoma cohorts (n = 758) were used as the training and validation datasets, respectively. We identified two m6A clusters (m6A-clusterA and m6A-clusterB) based on the expression pattern of m6A regulators via unsupervised consensus clustering. IGF2BP1 (7.49%), KIAA1429 (7.06%), and YTHDC1 (4.28%) were the three most frequently mutated genes. There was a correlation between driver genes mutation statuses and the expression of m6A regulators. A significant difference in tumor-associated immune infiltration between two m6A clusters was detected. Compared with m6A-clusterA, the m6A-clusterB was characterized by a lower immune score and immune cell infiltration but higher mRNA expression-based stemness index (mRNAsi). An m6A-related risk signature consisting of 12 genes was determined via Cox regression analysis and divided the patients into low- and high-risk groups (IL6ST, MBNL1, NXT2, EIF2A, CSGALNACT1, C11orf58, CD14, SPI1, NCCRP1, BOK, CD74, PAEP). A nomogram was developed for the prediction of the survival rate. Compared with the high-risk group, the low-risk group was characterized by high expression of immune checkpoints and immunophenoscore (IPS), activation of immune-related pathways, and more enriched in immune cell infiltrations. The low-risk group had a favorable prognosis and contained the potential beneficiaries of the immune checkpoint blockade therapy and verified by the IMvigor210 cohort (n = 298). The m6A-related signature we have determined in melanoma highlights the relationships between m6A regulators and immune cell infiltration. The established risk signature was identified as a promising clinical biomarker of melanoma.

scholarly journals Indigo Pulverata Levis (Chung-Dae, Persicaria tinctoria) Alleviates Atopic Dermatitis-like Inflammatory Responses In Vivo and In Vitro

2022 ◽  
Vol 23 (1) ◽  
pp. 553
Author(s):  
Ga-Yul Min ◽  
Ji-Hye Kim ◽  
Tae-In Kim ◽  
Won-Kyung Cho ◽  
Ju-Hye Yang ◽  
...  
Keyword(s):  
Atopic Dermatitis ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Hacat Cells ◽  
Serum Ige ◽  
Tnf Α ◽  
Inflammatory Chemokines

Atopic dermatitis (AD) is a chronic inflammatory skin disease associated with a type 2 T helper cell (Th2) immune response. The IndigoPulverata Levis extract (CHD) is used in traditional Southeast Asian medicine; however, its beneficial effects on AD remain uninvestigated. Therefore, we investigated the therapeutic effects of CHD in 2,4-dinitrochlorobenzene (DNCB)-induced BALB/c mice and tumor necrosis factor (TNF)-α- and interferon gamma (IFN)-γ-stimulated HaCaT cells. We evaluated immune cell infiltration, skin thickness, and the serum IgE and TNF-α levels in DNCB-induced AD mice. Moreover, we measured the expression levels of pro-inflammatory cytokines, mitogen-activated protein kinase (MAPK), and the nuclear factor-kappa B (NF-κB) in the mice dorsal skin. We also studied the effect of CHD on the translocation of NF-κB p65 and inflammatory chemokines in HaCaT cells. Our in vivo results revealed that CHD reduced the dermis and epidermis thicknesses and inhibited immune cell infiltration. Furthermore, it suppressed the proinflammatory cytokine expression and MAPK and NF-κB phosphorylations in the skin tissue and decreased serum IgE and TNF-α levels. In vitro results indicated that CHD downregulated inflammatory chemokines and blocked NF-κB p65 translocation. Thus, we deduced that CHD is a potential drug candidate for AD treatment.

scholarly journals Glucose-6-Phosphate Dehydrogenase is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Author(s):  
Yang Bu ◽  
Kejun Liu ◽  
Yiming Niu ◽  
Ji Hao ◽  
Lei Cui ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Liver Cancer ◽  
Immune Cell ◽  
Cox Regression ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Potential Biomarker ◽  
Glucose 6 Phosphate Dehydrogenase

Abstract Background: Glucose-6-phosphate dehydrogenase (G6PD) plays an important role in the metabolic and immunological aspects of tumors. In hepatocellular carcinoma (HCC), the alteration of tumor microenvironment influences recurrence and metastasis. We extracted G6PD-related data from public databases of HCC tissues and used a bioinformatics approach to explore the correlation between G6PD expression and clinicopathological features and prognosis of immune cell infiltration in HCC.Methods: We extract G6PD expression information from TCGA and GEO databases in liver cancer tissues and normal tissues, validated by immunohistochemistry, and the correlation between G6PD expression and clinical features is analyzed, and the clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier, Cox regression and prognostic line graph models. Functional enrichment analysis is performed by protein-protein interaction (PPI) network, GO/KEGG, GSEA and G6PD-associated differentially expressed genes (DEGs). TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results: Our results show that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues (P < 0.001). G6PD expression is associated with histological grade, pathological stage, T-stage, vascular infiltration and AFP level (P < 0.05); HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group (P < 0.05). The level of G6PD expression also affects the levels of macrophages, unactivated dendritic cells, B cells, and follicular helper T cells in the tumor microenvironment.Conclusion: High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma, and G6PD may be a target for immunotherapy of HCC.

Sign in / Sign up

Export Citation Format

Share Document