Distinct genomic and immune microenvironment between thymomas and thymic carcinomas.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13529-e13529
Author(s):  
Kaicheng Wang ◽  
Suxia Lin ◽  
Xue Hou ◽  
Yongdong Liu ◽  
Meichen Li ◽  
...  

e13529 Background: Thymomas and thymic carcinomas which uniformly known as thymic epithelial tumors (TETs) are rare intrathoracic malignancies and a limited studies have been reported addressing the molecular biology and immune discrepancy. The main purpose of this study was to depict the genomic and transcriptomic landscape of thymomas and thymic carcinomas, as well as elucidate the differentiated immune microenvironment. Methods: Totally 15 thymomas and 7 thymic carcinomas patients were enrolled from January 2014 to July 2018. Treatment-naïve tissue samples were collected, and we also obtained matched peripheral blood mononucleocytes as negative control. DNA and RNA were co-extracted and performed with whole exon and transcriptome sequencing. The immune cell infiltration scores were estimated using ssGSEA algorithm. Results: Exome sequencing revealed that GTF2I mutation occurred in all of type A thymomas but was absent in the aggressive subtypes. The median tumor mutation burden of thymomas was 0.12/Mb, significantly lower than thymic carcinomas (median: 1.02/Mb, p = 0.001). Copy number variation was more common in thymic carcinomas than thymomas (83.3% vs 9.1%, p = 0.005). Top mutational signatures enriched in both thymomas and thymic carcinomas included age and Aristolochic acid exposure, while the APOBEC signature was more common in thymomas than thymic carcinomas (81.8% vs 16.7%, p = 0.03). As a confirmed immune escape event, loss of heterozygosity of human leukocyte antigen was identified in 9.1% of thymomas and 50% of thymic carcinomas. Via unsupervised clustering of immune infiltration, all tissue samples were classified into high- and low-infiltration subgroups. Remarkably, up to 71.4% of samples from thymic carcinomas and only 6.7% of samples from thymomas were defined as low immune cell infiltration. In consideration of specific immune cell types, macrophage ( p = 0.01) and neutrophil ( p = 0.02) were enriched in thymic carcinomas while CD56+ NK cell ( p = 0.005) was enriched in thymomas, indicating the evidential discrepancy about immune cell infiltration between two subtypes of TETs. Conclusions: This study elucidated the molecular and immune microenvironment discrepancy between two subtypes of TETs. From molecular perspective, thymomas and thymic carcinomas are entirely different diseases with different etiology and characterized by distinct immune infiltration, and thus should be managed with disparate therapeutic strategies. Findings in this study may also be useful in future targets development and exploration of immunotherapies in TETs.

2013 ◽  
Vol 108 (4) ◽  
pp. 914-923 ◽  
Author(s):  
Y Ino ◽  
R Yamazaki-Itoh ◽  
K Shimada ◽  
M Iwasaki ◽  
T Kosuge ◽  
...  

2021 ◽  
Vol 8 ◽  
Author(s):  
Mingqin Ge ◽  
Jie Niu ◽  
Ping Hu ◽  
Aihua Tong ◽  
Yan Dai ◽  
...  

Objective: This study aimed to construct a prognostic ferroptosis-related signature for thyroid cancer and probe into the association with tumor immune microenvironment.Methods: Based on the expression profiles of ferroptosis-related genes, a LASSO cox regression model was established for thyroid cancer. Kaplan-Meier survival analysis was presented between high and low risk groups. The predictive performance was assessed by ROC. The predictive independency was validated via multivariate cox regression analysis and stratified analysis. A nomogram was established and verified by calibration curves. The enriched signaling pathways were predicted via GSEA. The association between the signature and immune cell infiltration was analyzed by CIBERSORT. The ferroptosis-related genes were validated in thyroid cancer tissues by immunohistochemistry and RT-qPCR.Results: A ferroptosis-related eight gene model was established for predicting the prognosis of thyroid cancer. Patients with high risk score indicated a poorer prognosis than those with low risk score (p = 1.186e-03). The AUCs for 1-, 2-, and 3-year survival were 0.887, 0.890, and 0.840, respectively. Following adjusting other prognostic factors, the model could independently predict the prognosis (p = 0.015, HR: 1.870, 95%CI: 1.132–3.090). A nomogram combining the signature and age was constructed. The nomogram-predicted probability of 1-, 3-, and 5-year survival approached the actual survival time. Several ferroptosis-related pathways were enriched in the high-risk group. The signature was distinctly associated with the immune cell infiltration. After validation, the eight genes were abnormally expressed between thyroid cancer and control tissues.Conclusion: Our findings established a prognostic ferroptosis-related signature that was associated with the immune microenvironment for thyroid cancer.


2020 ◽  
Author(s):  
Li Li ◽  
Shanshan Huang ◽  
Yangyang Yao ◽  
Jun Chen ◽  
Junhe Li ◽  
...  

Abstract Background: Follistatin-like 1 (FSTL1) plays a central role in the progression of tumor and tumor immunity. However, the effect of FSTL1 on the prognosis and immune infiltration of gastric cancer (GC) remains to be elucidated.Method: The expression of FSTL1 data was analyzed in Oncomine and TIMER databases. Analyses of clinical parameters and survival data were conducted by Kaplan-Meier plotter and immunohistochemistry. Western blot assay and real‐time quantitative PCR (RT-qPCR) was using to analyzed protein and mRNA expression, respectively. The correlations between FSTL1 and cancer immune infiltrates was analyzed by Tumor Immune Estimation Resource (TIME), Gene Expression Profiling Interactive Analysis (GEPIA) and LinkedOmics database.Results: The expression of FSTL1 was significantly higher in GC tissues than in normal tissues, and bioinformatic analysis and Immunohistochemistry (IHC) indicated that high FSTL1 expression significantly correlated with poor prognosis in GC. Moreover, FSTL1 was predicted as an independent prognostic factor in GC patients. Bioinformatics analysis results suggested that FSTL1 mainly involved in tumor progression and tumor immunity. And significant correlations were found between FSTL1 expression and immune cell infiltration in GC.Conclusion: The study effectively revealed useful information about FSTL1 expression, prognostic values, potential functional networks and impact of tumor immune infiltration in GC. In summary, FSTL1 can be used as a biomarker for prognosis and evaluating immune cell infiltration in GC.


2019 ◽  
Vol 8 (11) ◽  
pp. 1993 ◽  
Author(s):  
Minchan Gil ◽  
Kyung Eun Kim

Interleukin-18 (IL-18) is a cytokine that enhances innate and adaptive immune responses. Although there are conflicting reports about the roles of IL-18 in melanoma progression, the clinical relevance of IL-18 expression has not been comprehensively studied. In this study, we investigated IL-18 expression and its correlation with patient survival and immune cell infiltration in melanoma using cancer gene expression data publicly available through various databases. IL18 mRNA expression was found to be significantly lower in melanoma tissues than normal tissues. Kaplan–Meier survival analysis showed that IL18 expression was positively correlated with patient survival. To investigate the possible mechanisms by which IL18 expression increased patient survival, we then assessed the correlation between IL18 expression and immune cell infiltration levels. Infiltration of various immune cells, especially CD8+ T and natural killer (NK) cells, which are cytolytic effector cells, was significantly increased by IL18 expression. Additionally, the expression levels of two cytolytic molecules including perforin and granzyme B were significantly positively correlated with IL18 expression. Collectively, this study provides the first evidence that IL18 expression has prognostic value for melanoma patient survival and is strongly correlated with CD8+ T and NK cell infiltration, suggesting the role of IL-18 as a biomarker for predicting melanoma prognosis.


Author(s):  
Nian Liu ◽  
Zijian Liu ◽  
Xinxin Liu ◽  
Xiaoru Duan ◽  
Yuqiong Huang ◽  
...  

Abstract Background: Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related genes (IRGs) signature for melanoma prognosis. Methods: Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. Results: With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. Conclusions: This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.


2021 ◽  
Vol 12 ◽  
Author(s):  
XiongHui Rao ◽  
JianLong Jiang ◽  
ZhiHao Liang ◽  
JianBao Zhang ◽  
ZheHong Zhuang ◽  
...  

Background: CLDN10, an important component of the tight junctions of epithelial cells, plays a crucial role in a variety of tumors. The effect of CLDN10 expression in gastric cancer, however, has yet to be elucidated.Methods: Differential expression of CLDN10 at the mRNA and protein levels was evaluated using Oncomine, ULCAN, HPA and TIMER2.0 databases. Real-time polymerase chain reaction (RT-PCR) was utilized to further verify the expression of CLDN10 in vitro. Correlations between CLDN10 expression and clinical outcomes of gastric cancer were explored by Kaplan-Meier Plotter. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) were performed via LinkedOmics and GeneMANIA. The correlations between CLDN10 expression and immune cell infiltration and somatic copy number alternations (SCNA) in gastric cancer were explored by TIMER2.0 and GEPIA2.0.Results: CLDN10 expression was lower in gastric cancer compared to adjacent normal tissues, and associated with better prognosis. CLDN10 also showed significant differences at different T stages, Lauren classification, treatments and HER2 status. PPI and GSEA analysis showed that CLDN10 might be involved in signal transmission, transmembrane transport and metabolism. In some major immune cells, low expression of CLDN10 was associated with increased levels of immune cell infiltration. In addition, it was found that different SCNA status in CLDN10 might affect the level of immune cell infiltration. Furthermore, the expression of CLDN10 was significantly associated with the expression of several immune cell markers, especially B cell markers, follicular helper T cell (Tfh) markers and T cell exhaustion markers.Conclusion: Down-regulated CLDN10 was associated with better overall survival (OS) in gastric cancer. And CLDN10 may serve as a potential prognostic biomarker and correlate to immune infiltration levels in gastric cancer.


Author(s):  
Wenshi Liu ◽  
Dongdong Zheng ◽  
Wenjing Lv ◽  
Ying Hua ◽  
Rong Huang ◽  
...  

IntroductionThis study aimed to identify novel differentially co-expressed genes and to investigate the features of immune cell infiltration in PAH.Material and methodsThe GSE113439 and GSE117261 datasets were acquired from the Gene Expression Omnibus database. And the differentially expressed genes between PAH and control groups were identified based on the GSE117261 dataset. Weighted Gene Co-Expression Network Analysis (WGCNA) was adopted to analyze the pre-processed data. Functional enrichment analysis was then carried out to explore the biological functions of these genes modules. The differentially co-expressed key genes modules were in-depth verified by GEO2R analysis. The immune infiltration in PAH was investigated by Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT).ResultsWGCNA analysis found 15 differentially co-expressed genes modules, amongst which module blue indicated that it exhibited the strongest positive link to PAH, whereas module green presented the strongest negative association with PAH. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the genes in module blue were largely enriched in Lysosome, Complement, and coagulation cascades, and others, while the genes in module green were primarily enriched in the Chemokine signaling pathway, Platelet activation, etc. Integrin subunit alpha M (ITGAM) was identified as the differentially co-expressed key gene. Immune infiltration analysis by CIBERSORT showed that the differences between PAH and control groups or between PAH subgroups.ConclusionsITGAM was considered a promising biomarker to discriminate PAH from the control. Obvious differences were observed in immune infiltration between patients with PAH and normal groups.


2021 ◽  
Vol 12 ◽  
Author(s):  
Qianhui Xu ◽  
Shaohuai Chen ◽  
Yuanbo Hu ◽  
Wen Huang

BackgroundIncreasing evdence supports the suggestion that the immune cell infiltration (ICI) patterns play a pivotal role in tumor progression in breast cancer (BRCA). Nonetheless, there has been no comprehensive analysis of the ICI patterns effects on the clinical outcomes and immunotherapy.MethodsMultiomic data for BRCA samples were downloaded from TCGA. ESTIMATE algorithm, ssGSEA method, and CIBERSORT analysis were used to uncover the landscape of the tumor immune microenvironment (TIME). BRCA subtypes based on the ICI pattern were identified by consensus clustering and principal-component analysis was performed to obtain the ICI scores to quantify the ICI patterns in individual tumors. Their prognostic value was validated by the Kaplan-Meier survival curves. Gene set enrichment analysis (GSEA) was applied for functional annotation. Immunophenoscore (IPS) was employed to explore the immunotherapeutic role of the ICI scores. Finally, the mutation data was analyzed by using the “maftools” R package.ResultsThree different immune infiltration patterns with a distinct prognosis and biological signature were recognized among 1,198 BRCA samples. The characteristics of TIME under these three patterns were highly consistent with three known immune profiles: immune- excluded, immune-desert, and immune-inflamed phenotypes, respectively. The identification of the ICI patterns within individual tumors based on the ICI score, developed under the ICI-related signature genes, contributed into dissecting biological processes, clinical outcome, immune cells infiltration, immunotherapeutic effect, and genetic variation. High ICI score subtype, characterized with a suppression of immunity, suggested an immune-exhausted phenotype. Abundant effective immune cells were discovered in the low ICI score patients, which corresponded to an immune-activated phenotype and might present an immunotherapeutic advantage. Immunophenoscore was implemented as a surrogate of immunotherapeutic outcome, low-ICI scores samples obtained a significantly higher immunophenoscore. Enrichment of the JAK/STAT and VEGF signal pathways were activated in the ICI low-score subgroup. Finally, the synergistic effect between the ICI score and the tumor mutation burden (TMB) was confirmed.ConclusionThis work comprehensively elucidated that the ICI patterns served as an indispensable player in complexity and diversity of TIME. Quantitative identification of the ICI patterns in individual tumor will contribute into mapping the landscape of TIME further optimizing precision immunotherapy.


2021 ◽  
Vol 12 ◽  
Author(s):  
Yudong Cao ◽  
Hecheng Zhu ◽  
Jun Tan ◽  
Wen Yin ◽  
Quanwei Zhou ◽  
...  

IntroductionGlioma is the most common primary cancer of the central nervous system with dismal prognosis. Long noncoding RNAs (lncRNAs) have been discovered to play key roles in tumorigenesis in various cancers, including glioma. Because of the relevance between immune infiltrating and clinical outcome of glioma, identifying immune-related lncRNAs is urgent for better personalized management.Materials and methodsSingle-sample gene set enrichment analysis (ssGSEA) was applied to estimate immune infiltration, and glioma samples were divided into high immune cell infiltration group and low immune cell infiltration group. After screening differentially expressed lncRNAs in two immune groups, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune-related prognostic signature. Additionally, we explored the correlation between immune infiltration and the prognostic signature.ResultsA total of 653 samples were appropriate for further analyses, and 10 lncRNAs were identified as immune-related lncRNAs in glioma. After univariate Cox regression and LASSO Cox regression analysis, six lncRNAs were identified to construct a prognostic signature for glioma, which could be taken as independent prognostic factors in both univariate and multivariate Cox regression analyses. Moreover, risk score was significantly correlated with all the 29 immune-related checkpoint expression (p < 0.05) in ssGSEA except neutrophils (p = 0.43).ConclusionThe study constructed an immune-related prognostic signature for glioma, which contributed to improve clinical outcome prediction and guide immunotherapy.


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