scholarly journals Follistatin-like 1 (FSTL1) is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in Gastric 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.

2020 ◽  
Vol 18 (1) ◽  
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. Methods 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) were used to analyze protein and mRNA expression, respectively. The correlations between FSTL1 and cancer immune infiltrates were 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. Conclusions 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.


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. Methods: 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. Conclusions: 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.


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

Abstract 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 was evaluated using Oncomine, ULCAN, and TIMER2.0 databases. Correlations between CLDN10 expression and clinical outcomes of gastric cancer were explored by Kaplan-Meier Plotter. The correlations between CLDN10 expression and immune cell infiltration and somatic copy number mutation (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. Low expression of CLDN10 was associated with increased infiltration levels of certain immune cells in the tumor microenvironment. In addition, it was found that different somatic copy number changes (SCNA) 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: CLDN10 may act as a potential prognostic biomarker and correlate to immune infiltration levels in gastric cancer.


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.


2020 ◽  
Vol 40 (5) ◽  
Author(s):  
Ming Wu ◽  
Yadong Wang ◽  
Hang Liu ◽  
Jukun Song ◽  
Jie Ding

Abstract The immune infiltration of patients with gastric cancer (GC) is closely associated with clinical prognosis. However, previous studies failed to explain the different subsets of immune cells involved in immune responses and diverse functions. The present study aimed to uncover the differences in immunophenotypes in a tumor microenvironment (TME) between adjacent and tumor tissues and to explore their therapeutic targets. In our study, the relative proportion of immune cells in 229 GC tumor samples and 22 paired matched tissues was evaluated with a Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) algorithm. The correlation between immune cell infiltration and clinical information was analyzed. The proportion of 22 immune cell subsets was assessed to determine the correlation between each immune cell type and clinical features. Three molecular subtypes were identified with ‘CancerSubtypes’ R-package. Functional enrichment was analyzed in each subtype. The profiles of immune infiltration in the GC cohort from The Cancer Genome Atlas (TCGA) varied significantly between the 22 paired tissues. TNM stage was associated with M1 macrophages and eosinophils. Follicular helper T cells were activated at the late stage. Monocytes were associated with radiation therapy. Three clustering processes were obtained via the ‘CancerSubtypes’ R-package. Each cancer subtype had a specific molecular classification and subtype-specific characterization. These findings showed that the CIBERSOFT algorithm could be used to detect differences in the composition of immune-infiltrating cells in GC samples, and these differences might be an important driver of GC progression and treatment response.


2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 46-46
Author(s):  
Sophie Earle ◽  
Toru Aoyama ◽  
Alexander I. Wright ◽  
Darren Treanor ◽  
Yohei Miyagi ◽  
...  

46 Background: Since the ACTS-GC trial, Japanese patients with stage II/III gastric cancer (GC) receive adjuvant S1 chemotherapy. However, selection of patients (pts) by TNM stage does not predict benefit from adjuvant S1 with certainty. Thus, there is an urgent clinical need to identify predictive biomarkers. Increasing evidence suggests tumor immune cell infiltration may be related to GC pts prognosis. We tested the hypothesis that extent and type of immune cell infiltration in GC is related to benefit from adjuvant chemotherapy. Methods: Tissue microarrays from 252 GC resections (109 pts treated by surgery alone (S), 143 pts treated by surgery and adjuvant S1 chemotherapy (SC)) from the Kanagawa Cancer Center Hospital (Yokohama, Japan) were investigated by immunohistochemistry for common leucocytes antigen (CD45), neutrophils (CD66b), macrophages (CD68 and CD163), T-cell subtypes (CD45R0, CD8, CD3), B-cells (CD20) and Treg cells (FOXP3). Staining was quantified as percentage immunoreactivity/area by automated image analysis. Relationship with overall survival was analyzed. A Cox regression model was used to identify independent prognostic markers and treatment interaction effect. Results: The hazard ratio of S1 was 0.694 in this GC cohort which is similar to the results of the ACTS-GC trial. CD45 and CD45R0 were independent prognostic markers in the S group only (CD45 p=0.032, CD45R0 p=0.003). A treatment interaction effect was seen for CD45, CD45R0, and CD68 (p value for test of interaction: CD45 p=0.062, CD45R0 p=0.082, CD68 p=0.057). Survival in the SC group was significantly poorer compared to the S group for CD45>56% or CD68>7% (p<0.05). Conclusions: This is the first study to investigate the relationship between tumor immune cell infiltration at time of surgery and benefit from adjuvant chemotherapy. Our results indicate that GC patients with high intratumoral levels of CD68, CD45, or CD45R0 positive immune cells might not benefit from adjuvant S1 chemotherapy. These findings require validation in a second independent dataset before conducting a prospective study stratifying patients with stage II/III GC based upon extent of CD45, CD45R0, or CD68 immune cell infiltration for adjuvant treatment.


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.


2021 ◽  
Author(s):  
Qi Zhou ◽  
Xin Xiong ◽  
Min Tang ◽  
Yingqing Lei ◽  
Hongbin Lv

Abstract BackgroundDiabetic retinopathy (DR), a severe complication of diabetes mellitus (DM), is a global social and economic burden. However, the pathological mechanisms mediating DR are not well-understood. This study aimed to identify differentially methylated and differentially expressed hub genes (DMGs and DEGs, respectively) and associated signaling pathways, and to evaluate immune cell infiltration involved in DR. MethodsTwo publicly available datasets were downloaded from the Gene Expression Omnibus database. Transcriptome and epigenome microarray data and multi-component weighted gene coexpression network analysis (WGCNA) were utilized to determine hub genes within DR. One dataset was utilized to screen DEGs and to further explore their potential biological functions using functional annotation analysis. A protein-protein interaction network was constructed. Gene set enrichment and variation analyses (GSVA and GSEA, respectively) were utilized to identify the potential mechanisms mediating the function of hub genes in DR. Infiltrating immune cells were evaluated in one dataset using CIBERSORT. The Connectivity Map (CMap) database was used to predict potential therapeutic agents. ResultsIn total, 673 DEGs (151 upregulated and 522 downregulated genes) were detected. Gene expression was significantly enriched in the extracellular matrix and sensory organ development, extracellular matrix organization, and glial cell differentiation pathways. Through WGCNA, one module was found to be significantly related with DR (r=0.34, P =0.002), and 979 hub genes were identified. By comparing DMGs, DEGs, and genes in WGCNA, we identified eight hub genes in DR ( AKAP13, BOC, ACSS1, ARNT2, TGFB2, LHFPL2, GFPT2, TNFRSF1A ), which were significantly enriched in critical pathways involving coagulation, angiogenesis, TGF-β, and TNF-α-NF-κB signaling via GSVA and GSEA. Immune cell infiltration analysis revealed that activated natural killer cells, M0 macrophages, resting mast cells, and CD8 + T cells may be involved in DR. ARNT2, TGFB2, LHFPL2 , and AKAP13 expression were correlated with immune cell processes, and ZG-10, JNK-9L, chromomycin-a3, and calyculin were identified as potential drugs against DR. Finally, TNFRSF1A , GFPT2 , and LHFPL2 expression levels were consistent with the bioinformatic analysis. ConclusionsOur results are informative with respect to correlations between differentially methylated and expressed hub genes and immune cell infiltration in DR, providing new insight towards DR drug development and treatment.


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.


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