23P A comprehensive analysis of the mucosal melanoma immune microenvironment

Background: Breast cancer (BC) is a heterogeneous malignant tumor, leading to the second major cause of female mortality. This study aimed to establish an in-depth relationship between ferroptosis-related LncRNA (FRlncRNA) and the prognosis as well as immune microenvironment of the patients with BC.Methods: We downloaded and integrated the gene expression data and the clinical information of the patients with BC from The Cancer Genome Atlas (TCGA) database. The co-expression network analysis and univariate Cox regression analysis were performed to screen out the FRlncRNAs related to prognosis. A cluster analysis was adopted to explore the difference of immune microenvironment between the clusters. Furthermore, we determined the optimal survival-related FRLncRNAs for final signature by LASSO Cox regression analysis. Afterward, we constructed and validated the prediction models, which were further tested in different subgroups.Results: A total of 31 FRLncRNAs were filtrated as prognostic biomarkers. Two clusters were determined, and C1 showed better prognosis and higher infiltration level of immune cells, such as B cells naive, plasma cells, T cells CD8, and T cells CD4 memory activated. However, there were no significantly different clinical characters between the clusters. Gene Set Enrichment Analysis (GSEA) revealed that some metabolism-related pathways and immune-associated pathways were exposed. In addition, 12 FRLncRNAs were determined by LASSO analysis and used to construct a prognostic signature. In both the training and testing sets, patients in the high-risk group had a worse survival than the low-risk patients. The area under the curves (AUCs) of receiver operator characteristic (ROC) curves were about 0.700, showing positive prognostic capacity. More notably, through the comprehensive analysis of heatmap, we regarded LINC01871, LINC02384, LIPE-AS1, and HSD11B1-AS1 as protective LncRNAs, while LINC00393, AC121247.2, AC010655.2, LINC01419, PTPRD-AS1, AC099329.2, OTUD6B-AS1, and LINC02266 were classified as risk LncRNAs. At the same time, the patients in the low-risk groups were more likely to be assigned to C1 and had a higher immune score, which were consistent with a better prognosis.Conclusion: Our research indicated that the ferroptosis-related prognostic signature could be used as novel biomarkers for predicting the prognosis of BC. The differences in the immune microenvironment exhibited by BC patients with different risks and clusters suggested that there may be a complementary synergistic effect between ferroptosis and immunotherapy.

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CCL19 has potential to be a prognostic biomarker and a modulator of tumor immune microenvironment (TIME) of breast cancer: a comprehensive analysis based on TCGA database

10.21203/rs.3.rs-87457/v1 ◽

2020 ◽

Author(s):

Jinyan Wang ◽

Jinqiu Wang ◽

Quan Gu ◽

Yan Yang ◽

Yajun Ma ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Cells ◽

Immune Cells ◽

Prognostic Biomarker ◽

Comprehensive Analysis ◽

Ppi Network ◽

Intrinsic Properties ◽

Immune Microenvironment ◽

Stromal Component ◽

Tumor Immune Microenvironment

Abstract The development of cancer was determined by not only the intrinsic properties of cancer cells, but also the communication between cancer cells and tumor microenvironment (TME). We applied ESTIMATE and CIBERSORT algorithms to calculate the immune/stromal component and tumor-infiltrating immune cells (TICs) in TME of BC. The results showed that immune component in TME predicted patients’ survival and associated with progression of BC. Differentially expressed genes (DEGs) were primarily enriched in immune-related activities. Finally, CCL19 was acquired which shared the leading nodes in PPI network and was associated with patients’ survival. High expression of CCL19 predicted better prognosis and participated in progression of BC. Genes in CCL19 up-regulated group were enriched in immune-related activities and these functions might depend on the communications between CCL19 and multiple TICs in TIME. In conclusion, CCL19 functioned as a potential prognostic biomarker and a modulator of TIME in BC through communicating with various TICs.

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Abstract 4048: Comprehensive analysis of the suppressed tumor immune microenvironment of CIN gastro-esophageal adenocarcinomas

10.1158/1538-7445.am2018-4048 ◽

2018 ◽

Author(s):

Sarah Derks ◽

Xinsen Xu ◽

Leonie de Klerk ◽

Tania Fleitas ◽

Kevin Liu ◽

...

Keyword(s):

Comprehensive Analysis ◽

Immune Microenvironment ◽

Tumor Immune Microenvironment

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Integrative Analysis of a Novel Eleven-Small Nucleolar RNA Prognostic Signature in Patients With Lower Grade Glioma

Frontiers in Oncology ◽

10.3389/fonc.2021.650828 ◽

2021 ◽

Vol 11 ◽

Author(s):

Teng Deng ◽

Yizhen Gong ◽

Xiwen Liao ◽

Xiangkun Wang ◽

Xin Zhou ◽

...

Keyword(s):

Enrichment Analysis ◽

Comprehensive Analysis ◽

Integrative Analysis ◽

Gene Set Enrichment Analysis ◽

Lower Grade ◽

Rna Seq ◽

Prognostic Signature ◽

Immune Microenvironment ◽

Immune Infiltration ◽

Lower Grade Glioma

ObjectiveThe present study used the RNA sequencing (RNA-seq) dataset to identify prognostic snoRNAs and construct a prognostic signature of The Cancer Genome Atla (TCGA) lower grade glioma (LGG) cohort, and comprehensive analysis of this signature.MethodsRNA-seq dataset of 488 patients from TCGA LGG cohort were included in this study. Comprehensive analysis including function enrichment, gene set enrichment analysis (GSEA), immune infiltration, cancer immune microenvironment, and connectivity map (CMap) were used to evaluate the snoRNAs prognostic signature.ResultsWe identified 21 LGG prognostic snoRNAs and constructed a novel eleven-snoRNA prognostic signature for LGG patients. Survival analysis suggests that this signature is an independent prognostic risk factor for LGG, and the prognosis of LGG patients with a high-risk phenotype is poor (adjusted P = 0.003, adjusted hazard ratio = 2.076, 95% confidence interval = 1.290–3.340). GSEA and functional enrichment analysis suggest that this signature may be involved in the following biological processes and signaling pathways: such as cell cycle, Wnt, mitogen-activated protein kinase, janus kinase/signal transducer and activator of tran-ions, T cell receptor, nuclear factor-kappa B signaling pathway. CMap analysis screened out ten targeted therapy drugs for this signature: 15-delta prostaglandin J2, MG-262, vorinostat, 5155877, puromycin, anisomycin, withaferin A, ciclopirox, chloropyrazine and megestrol. We also found that high- and low-risk score phenotypes of LGG patients have significant differences in immune infiltration and cancer immune microenvironment.ConclusionsThe present study identified a novel eleven-snoRNA prognostic signature of LGG and performed a integrative analysis of its molecular mechanisms and relationship with tumor immunity.

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Comprehensive Analysis Uncovers Prognostic and Immunogenic Characteristics of Cellular Senescence for Lung Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.780461 ◽

2021 ◽

Vol 9 ◽

Author(s):

Weihao Lin ◽

Xin Wang ◽

Zhen Wang ◽

Fei Shao ◽

Yannan Yang ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Clinical Outcomes ◽

Cellular Senescence ◽

Immune Modulation ◽

Expression Profiles ◽

Comprehensive Analysis ◽

Immune Microenvironment ◽

Prognostic Predictor ◽

Tumor Immune Microenvironment ◽

Secretory Phenotype

Cellular senescence plays a crucial role in tumorigenesis, development and immune modulation in cancers. However, to date, a robust and reliable cellular senescence-related signature and its value in clinical outcomes and immunotherapy response remain unexplored in lung adenocarcinoma (LUAD) patients. Through exploring the expression profiles of 278 cellular senescence-related genes in 936 LUAD patients, a cellular senescence-related signature (SRS) was constructed and validated as an independent prognostic predictor for LUAD patients. Notably, patients with high SRS scores exhibited upregulation of senescence-associated secretory phenotype (SASP) and an immunosuppressive phenotype. Further analysis showed that SRS combined with immune checkpoint expression or TMB served as a good predictor for patients’ clinical outcomes, and patients with low SRS scores might benefit from immunotherapy. Collectively, our findings demonstrated that SRS involved in the regulation of the tumor immune microenvironment through SASP was a robust biomarker for the immunotherapeutic response and prognosis in LUAD.

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Comprehensive analysis of tumour mutation burden and the immune microenvironment in hepatocellular carcinoma

International Immunopharmacology ◽

10.1016/j.intimp.2020.107135 ◽

2020 ◽

Vol 89 ◽

pp. 107135

Author(s):

Fucun Xie ◽

Yi Bai ◽

Xu Yang ◽

Junyu Long ◽

Jinzhu Mao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Comprehensive Analysis ◽

Immune Microenvironment ◽

Mutation Burden

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Comprehensive Analysis of Genome-instability Related lncRNAs and Tumor-immune Microenvironment to Discriminate the Prognosis, Immunotherapy and PARP Inhibitor Responses in Patients with Low-grade Glioma

10.21203/rs.3.rs-711385/v1 ◽

2021 ◽

Author(s):

Zijian Zhou ◽

Bin Lu ◽

JinHong Wei ◽

Lei Guo ◽

ZhongMing He ◽

...

Keyword(s):

Clinical Outcome ◽

Risk Model ◽

Genome Instability ◽

Parp Inhibitor ◽

Comprehensive Analysis ◽

Low Grade Glioma ◽

Therapeutic Effects ◽

Low Grade ◽

Immune Microenvironment ◽

Tumor Immune Microenvironment

Abstract Background: Previous study revealed that Genome-instability was correlated with tumor-immune microenvironment in cancer. We try to discriminate the prognosis, immunotherapy and poly (ADP)-ribose polymerase (PARP) inhibitor responses through comprehensive analysis of genome-instability related lncRNAs and the tumor-immune microenvironment in patients with low-grade glioma (LGG). Methods and Results: RNAseq data, genome variation profiling data and copy number variation (CNV) data were used to evaluate the genomic instability of LGG patients. Genomic unstable-like (GU-like) and genomic stable-like (GS-like) clusters were identified by hierarchical clustering analysis of 102 genome-instability related lncRNAs (GILncRNAs). GS-like cluster had a tendency to receive better clinical outcome. Patients in GU-like cluster were more likely to respond to immunotherapy, especially anti-PD-1/PD-L1 treatment. PARP inhibitors including Rucaparib and Olaparib will get better therapeutic effects for patients in GU-like cluster. Lasso and Cox regression analysis were utilized to construct the risk model based on GILncRNAs. As for the risk model constructed by 9 GILncRNAs, the overall survival, clinical outcome, immunotherapeutic response, and PARP inhibitor sensitivity were significantly different between patients of high and low-risk groups. Conclusions: The genome-instability related lncRNAs signature involved in our risk model had great advantages in predicting prognosis, immunotherapy and PARP inhibitor response.

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Identification of a novel snoRNA expression signature associated with overall survival in patients with lung adenocarcinoma: A comprehensive analysis based on RNA sequencing dataset

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021389 ◽

2021 ◽

Vol 18 (6) ◽

pp. 7837-7860

Author(s):

Linbo Zhang ◽

◽

Mei Xin ◽

Peng Wang

Keyword(s):

Overall Survival ◽

Lung Adenocarcinoma ◽

Rna Sequencing ◽

Risk Score ◽

Transforming Growth Factor ◽

Comprehensive Analysis ◽

The Cancer Genome Atlas ◽

Mitogen Activated Protein Kinase ◽

Immune Microenvironment ◽

Expression Signature

<abstract> <p>Since multiple studies have reported that small nucleolar RNAs (snoRNAs) can be serve as prognostic biomarkers for cancers, however, the prognostic values of snoRNAs in lung adenocarcinoma (LUAD) remain unclear. Therefore, the main work of this study is to identify the prognostic snoRNAs of LUAD and conduct a comprehensive analysis. The Cancer Genome Atlas LUAD cohort whole-genome RNA-sequencing dataset is included in this study, prognostic analysis and multiple bioinformatics approaches are used for comprehensive analysis and identification of prognostic snoRNAs. There were seven LUAD prognostic snoRNAs were screened in current study. We also constructed a novel expression signature containing five LUAD prognostic snoRNAs (snoU109, SNORA5A, SNORA70, SNORD104 and U3). Survival analysis of this expression signature reveals that LUAD patients with high risk score was significantly related to an unfavourable overall survival (adjusted P = 0.01, adjusted hazard ratio = 1.476, 95% confidence interval = 1.096-1.987). Functional analysis indicated that LUAD patients with different risk score phenotypes had significant differences in cell cycle, apoptosis, integrin, transforming growth factor beta, ErbB, nuclear factor kappa B, mitogen-activated protein kinase, phosphatidylinositol-3-kinase and toll like receptor signaling pathway. Immune microenvironment analysis also indicated that there were significant differences in immune microenvironment scores among LUAD patients with different risk score. In conclusion, this study identified an novel expression signature containing five LUAD prognostic snoRNAs, which may be serve as an independent prognostic indicator for LUAD patients.</p> </abstract>

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