scholarly journals Upregulated CCNE1 Correlates with Poor Prognosis, Tumor Immune Infiltration and Escape in Breast Cancer

2021 ◽  
Author(s):  
Jiaxi Feng ◽  
Yanan Hu ◽  
Dan Liu ◽  
Shanshan Wang ◽  
Mengci Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Cell ◽  
High Expression ◽  
Expression Level ◽  
Immune Cell Infiltration ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract BackgroundBreast cancer (BC) is the most common malignant tumor in women and widely known for its poor prognosis. More and more research has discovered that cyclin E1 (CCNE1) plays an important role in progression of various types of cancer. But its specific mechanism in BC progression still needs further research to explore.MethodsAt first, we determined the expression and prognostic value of CCNE1 through The Cancer Genome Atlas (TCGA) database and The Genotype-Tissue Expression (GTEx) data. Then, we predicted the upstream non-coding RNAs of CCNE1 through StarBase, GEPIA, and Kaplan-Meier plotter database. We further studied the correlation of CCNE1 expression with BC immune cell infiltration, biomarkers of immune cells and immune checkpoints expression through TIMER and GEPIA databases.ResultsThe results suggested that CCNE1 was significantly upregulated in BC and its high expression was correlated with poor prognosis in BC patients. Next, we identified long noncoding RNA (lncRNA) LINC00511 / microRNA-195-5p (miR-195-5p) / CCNE1 axis as the most potential pathway that could regulate CCNE1 expression in BC through StarBase, GEPIA, and Kaplan-Meier plotter database. Furthermore, our in-depth research discovered that CCNE1 expression level was significantly correlated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression in BC.ConclusionIn summary, high expression level of CCNE1 was significantly correlated with poor prognosis, tumor immune infiltration and escape in BC.

scholarly journals Upregulated CCNE1 Correlates with Poor Prognosis, Tumor Immune Infiltration and Escape in Breast Cancer

2021 ◽  
Author(s):  
Jiaxi Feng ◽  
Yanan Hu ◽  
Dan Liu ◽  
Shanshan Wang ◽  
Mengci Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Cell ◽  
High Expression ◽  
Expression Level ◽  
Immune Cell Infiltration ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Breast cancer (BC) is the most common malignant tumor in women and widely known for its poor prognosis. More and more research has discovered that cyclin E1 (CCNE1) plays an important role in progression of various types of cancer. But its specific mechanism in BC progression still needs further research to explore.Methods At first, we determined the expression and prognostic value of CCNE1 through The Cancer Genome Atlas (TCGA) database and The Genotype-Tissue Expression (GTEx) data. Then, we predicted the upstream non-coding RNAs of CCNE1 through StarBase, GEPIA, and Kaplan-Meier plotter database. We further studied the correlation of CCNE1 expression with BC immune cell infiltration, biomarkers of immune cells and immune checkpoints expression through TIMER and GEPIA databases.Results The results suggested that CCNE1 was significantly upregulated in BC and its high expression was correlated with poor prognosis in BC patients. Next, we identified long noncoding RNA (lncRNA) LINC00511 / microRNA-195-5p (miR-195-5p) / CCNE1 axis as the most potential pathway that could regulate CCNE1 expression in BC through StarBase, GEPIA, and Kaplan-Meier plotter database. Furthermore, our in-depth research discovered that CCNE1 expression level was significantly correlated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression in BC. conclusions In summary, high expression level of CCNE1 was significantly correlated with poor prognosis, tumor immune infiltration and escape in BC.

scholarly journals APOC1 is a Potential Prognostic Biomarker and Correlated With Immune Infiltration in ESCC

2020 ◽  
Author(s):  
Jia-yi XIE ◽  
Ming Liu ◽  
Yaxin Luo ◽  
Zhen Wang ◽  
Zhenghong Lu ◽  
...  
Keyword(s):  
T Cells ◽  
Transcription Factors ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Killer Cell ◽  
Gene Set Enrichment Analysis ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract PurposeEsophageal cancer (EC) is the sixth leading cause of cancer death worldwide. Esophageal squamous cell carcinoma (ESCC) is a predominant subtype of EC. Identifying diagnostic biomarkers for ESCC is necessary for cancer practice. Increasing evidence illustrates that apolipoprotein C-1 (APOC1) participates in the carcinogenesis. However, the biological function of APOC1 in ESCC remains unclear. Patients and methodsWe investigated the expression level of APOC1 using TIMER2.0 and GEO databases, the prognostic value of APOC1 in ESCC using Kaplan-Meier plotter and TCGA databases. We used LinkedOmics to identify co-expressed genes with APOC1 and perform GO and KEGG pathway analysis. The target networks of kinases, miRNAs and transcription factors were predicted by gene set enrichment analysis (GSEA). The correlations between APOC1 and immune infiltration were calculated using TIMER2.0 and CIBERSORT databases. We further performed the prognostic analysis based on APOC1 expression levels in related immune cells subgroups via Kaplan-Meier plotter database. ResultsAPOC1 was found overexpressed in tumor tissues in multiple ESCC cohorts and high APOC1 expression was related to a dismal prognosis. Multivariate analysis confirmed that APOC1 overexpression was an independent indicator of poor OS. Functional network analysis indicated that APOC1 might regulate the natural killer cell mediated cytotoxicity, phagosome, AMPK and hippo signaling through pathways involving some cancer-related kinases, miRNA and transcription factors. Immune infiltration analysis showed that APOC1 was significantly positively correlated with M0 macrophages cells, M1 macrophages cells and activated NK cells, negatively correlated with regulatory T cells, CD8 T cells, neutrophils and monocytes. High APOC1 expression had a poor prognosis in server immune cells subgroups in ESCC, including decreased CD8+ T cells subgroups. ConclusionThese findings suggest that increased expression of APOC1 is related to poor prognosis and immune infiltration in ESCC. APOC1 holds promise for serving as a valuable diagnostic and prognostic marker in ESCC.

scholarly journals Bromine domain protein 4 is an important marker for prognosis of ovarian cancer and tumor immune infiltration

2021 ◽  
Author(s):  
Chujia Chen ◽  
Zhiyong Yang ◽  
Qiuchan Zhao ◽  
Bangming Xu ◽  
Donglin Cao
Keyword(s):  
Ovarian Cancer ◽  
Immune Cell ◽  
Expression Level ◽  
Immune Markers ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Domain Protein ◽  
Kaplan Meier Plotter

Abstract Background Ovarian cancer (OC) is one of the most common malignant gynecological tumors, but its pathogenesis is unclear. Bromine domain protein 4 (BRD4) is involved in the malignant transformation of cells, as well as the invasion and metastasis of tumor cells. The biological role of BRD4 in ovarian cancer is yet to be determined. Methods The differential expression of BRD4 in OC and corresponding normal tissues was evaluated by exploring the Tumor Immune Assessment Resources (TIMER) and the Oncomine database. The correlation between the expression level of BRD4 and the prognosis of OC patients was evaluated using the Kaplan-Meier Plotter database. Using TIMER, we further studied the correlation between BRD4 and tumor immune cell infiltration. Results The expression of BRD4 was significantly higher in patients with OC, and high BRD4 expression was closely related to low overall survival rate. The BRD4 expression was associated with the levels of immune markers of macrophages, dendritic cells, neutrophils, and various effector T cells. Taken together, these findings show that BRD4 expression is significantly related to immune infiltration in OC and suggest that BRD4 might play an important role in the immune evasion of OC cells. Conclusion The expression level of BRD4 in OC tissues is significantly upregulated, and its high expression is significantly associated with poor prognosis of patients and is closely related to tumor immune infiltration. These results suggest that BRD4 can be used as a prognostic marker and a marker of immune infiltration in OC.

Gasdermin C as a potential prognostic biomarker and its correlation with immune infiltration in pancreatic ductal adenocarcinoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16256-e16256
Author(s):  
Xianghou Xia ◽  
Yang Yu ◽  
Hongjian Yang ◽  
Dehong Zou ◽  
Canming Wang ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Prognostic Value ◽  
Immune Cell ◽  
Prognostic Significance ◽  
High Expression ◽  
Ductal Adenocarcinoma ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

e16256 Background: Although pyroptosis is critical for macrophages against pathogen infection, its role in cancer cells remains elusive. GSDMC is a pyroptosis executioner newly identified in cancer cells and have been shown to facilitate inflammatory tumor death. However, the expression of GSDMC in Pancreatic Ductal Adenocarcinoma (PDAC), its prognostic significance and possible impact on reshaping tumor immune microenviroment in PDAC is still unknown. Methods: We investigated the expression level of GSDMC using TNM plotter with TCGA and GTEx databases, the prognostic value of GSDMC in PDAC using Kaplan-Meier plotter with TCGA, GTEx and TCGA databases. The correlations between GSDMC and immune infiltration in PDAC were calculated using TIMER2.0 and TIDE with TCGA database. We further validated the prognostic value of GSDMC with immunohistochemistry(IHC) staining on a tissue microarray of 172 cases of PDAC patients receiving treatment in our institution. Correlations between expression of GSDMC and tumor infiltration lymphacytes(TILs) cells were also analyzed on tissue samples of those 172 PDAC patients. Results: TNM plotter analysis shows that the expression of GSDMC in PDAC tumor tissue is 10.49 folds higher than it is in pancreatic normal tissues (p = 8.86*e-56). Results from Kaplan-Meier plotter analysis shows high expression of GSDMC is significantly correlated with poorer overall survival(OS), HR = 1.8(1.19−2.71) logrank P = 0.004 and shorter relapse free survival (RFS), HR = 4.6(1.94−10.88), Logrank P = 0.00014 in PDAC. Analysis with TIMER2.0 and TIDE platform shows that expression of GSDMC is positively correlated with immunosuppressive cells, Cancer Associated Fiberblast (CAF) and Meyloid Derived Tumor Suprresso Cells(MDTSC). IHC staining analysis results is also consistent with aformentioned bioinformatic analysis, showing that high GSDMC expression correlated with shorter OS and reduced Tils infiltration. Conclusions: Our findings suggest that high expression of GSDMC is related to poor prognosis and compromised immune cell infiltration in PDAC. GSDMC holds promise for serving as a valuable prognostic marker and therapeutic target in PDAC.

scholarly journals The ncRNA-Mediated Overexpression of Ferroptosis-Related Gene EMC2 Correlates With Poor Prognosis and Tumor Immune Infiltration in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Xing Liu ◽  
Pengshuo Yang ◽  
Lu Han ◽  
Qing Zhou ◽  
Qingsong Qu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Poor Prognosis ◽  
Invasive Carcinoma ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Death Process ◽  
Immune Cell Infiltration ◽  
Related Gene ◽  
Expression Levels ◽  
Immune Infiltration

Ferroptosis is an iron-dependent programmed cell death process. Although ferroptosis inducers hold promising potential in the treatment of breast cancer, the specific role and mechanism of the ferroptosis-related gene EMC2 in breast cancer have not been entirely determined. The potential roles of EMC2 in different tumors were explored based on The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Tumor Immune Estimation Resource (TIMER), Shiny Methylation Analysis Resource Tool (SMART), starBase, and cBioPortal for cancer genomics (cBioPortal) datasets. The expression difference, mutation, survival, pathological stage, DNA methylation, non-coding RNAs (ncRNAs), and immune cell infiltration related to EMC2 were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify the differences in biological processes and functions among different related genes. The expression levels of core prognostic genes were then verified in breast invasive carcinoma samples using immunohistochemistry and breast invasive carcinoma cell lines using real-time polymerase chain reaction. High expression levels of EMC2 were observed in most cancer types. EMC2 expression in breast cancer tissue samples correlated with poor overall survival. EMC2 was mutated and methylated in a variety of tumors and affected survival. The LINC00665-miR-410-3p axis was identified as the most potential upstream ncRNA-related pathway of EMC2 in breast cancer. EMC2 levels were significantly positively correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression. Our study offers a comprehensive understanding of the oncogenic roles of EMC2 across different tumors. The upregulation of EMC2 expression mediated by ncRNAs is related to poor prognosis and tumor immune infiltration in breast cancer.

scholarly journals CLEC10A is A Prognostic Biomarker and is Correlated with Immune Infiltrates in Breast Cancer

2021 ◽  
Author(s):  
Shasha Tang ◽  
Yi Zhang ◽  
Xiaoyan Lin ◽  
Chunmei Cen ◽  
Liyun Yong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Mrna Levels ◽  
Gene Markers ◽  
Normal Tissues ◽  
Potential Biomarker

Abstract Background To investigate the association between CLEC10A and prognosis in breast cancer (BC) patients. Methods We assessed the prognostic value of CLEC10A in BC using data from The Cancer Genome Atlas (TCGA) online database. We examined CLEC10A expression differences in BC and normal tissues via the TIMER and UALCAN databases. Then, we used the Kaplan-Meier plotter database to evaluate the correlation of CLEC10A mRNA levels with clinical outcomes. Subsequently, the TIMER platform and TISIDB website were used to assess the correlation of CLEC10A with the tumor immune cell infiltration level in BC. Results Our results showed that CLEC10A levels were significantly downregulated in BC tissues compared with normal tissues. CLEC10A expression was associated with histologic type, pathologic stage, T stage, Her2 status and a poor prognosis. Additionally, CLEC10A was positively related to the level of different tumor-infiltrating immune cells in BC, and CLEC10A was closely correlated with the gene markers of diverse immune cells. Additionally, low CLEC10A expression predicted a poor prognosis in BC patients grouped based on immune cell infiltration levels. Conclusion CLEC10A may be a potential biomarker and may efficiently predict prognosis in BC patients.

scholarly journals Correlation Between 18F-FDG Uptake and Immune Cell Infiltration in Metastatic Brain Lesions

2021 ◽  
Vol 11 ◽  
Author(s):  
Young-Sil An ◽  
Se-Hyuk Kim ◽  
Tae Hoon Roh ◽  
So Hyun Park ◽  
Tae-Gyu Kim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Standardized Uptake Value ◽  
Brain Lesions ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Ki 67 ◽  
Glucose Transporter 1 ◽  
Fdg Uptake

BackgroundThe purpose of this study was to investigate the correlation between 18F-fluorodeoxyglucose (FDG) uptake and infiltrating immune cells in metastatic brain lesions.MethodsThis retrospective study included 34 patients with metastatic brain lesions who underwent brain 18F-FDG positron emission tomography (PET)/computed tomography (CT) followed by surgery. 18F-FDG uptake ratio was calculated by dividing the standardized uptake value (SUV) of the metastatic brain lesion by the contralateral normal white matter uptake value. We investigated the clinicopathological characteristics of the patients and analyzed the correlation between 18F-FDG uptake and infiltration of various immune cells. In addition, we evaluated immune-expression levels of glucose transporter 1 (GLUT1), hexokinase 2 (HK2), and Ki-67 in metastatic brain lesions.ResultsThe degree of 18F-FDG uptake of metastatic brain lesions was not significantly correlated with clinical parameters. There was no significant relationship between the 18F-FDG uptake and degree of immune cell infiltration in brain metastasis. Furthermore, other markers, such as GLUT1, HK2, and Ki-67, were not correlated with degree of 18F-FDG uptake. In metastatic brain lesions that originated from breast cancer, a higher degree of 18F-FDG uptake was observed in those with high expression of CD68.ConclusionsIn metastatic brain lesions, the degree of 18F-FDG uptake was not significantly associated with infiltration of immune cells. The 18F-FDG uptake of metastatic brain lesions from breast cancer, however, might be associated with macrophage activity.

scholarly journals Expression and Prognostic Characteristics of m6 A RNA Methylation Regulators in Breast Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Bo Zhang ◽  
Yanlin Gu ◽  
Guoqin Jiang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Patients ◽  
High Expression ◽  
Cancer Gene ◽  
Breast Cancer Patients ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Her 2 ◽  
Kaplan Meier Plotter

PurposeN6-methyladenosine (m6A) is the most prevalent modification in mRNA methylation which has a wide effect on biological functions. This study aims to figure out the efficacy of m6A RNA methylation regulator-based biomarkers with prognostic significance in breast cancer.Patients and MethodsThe 23 RNA methylation regulators were firstly analyzed through ONCOMINE, then relative RNA-seq transcriptome and clinical data of 1,096 breast cancer samples and 112 normal tissue samples were acquired from The Cancer Gene Atlas (TCGA) database. The expressive distinction was also showed by the Gene Expression Omnibus (GEO) database. The gene expression data of m6A RNA regulators in human tissues were acquired from the Genotype-Tissue Expression (GTEx) database. The R v3.5.1 and other online tools such as STRING, bc-GeneExminer v4.5, Kaplan-Meier Plotter were applied for bioinformatics analysis.ResultsResults from ONCOMINE, TCGA, and GEO databases showed distinctive expression and clinical correlations of m6A RNA methylation regulators in breast cancer patients. The high expression of YTHDF3, ZC3H13, LRPPRC, and METTL16 indicated poor survival rate in patients with breast cancer, while high expression of RBM15B pointed to a better survival rate. Both univariate and multivariate Cox regression analyses revealed that age and risk scores were related to overall survival (OS). Univariate analysis also delineated that stage, tumor (T) status, lymph node (N) status, and metastasis (M) status were associated with OS. From another perspective, Kaplan-Meier Plotter platform showed that the relatively high expression of YTHDF3 and LRPPRC and the relatively low expression of RBM15B, ZC3H13, and METTL16 in breast cancer patients had worse Relapse-Free Survival (RFS). Breast Cancer Gene-Expression Miner v4.5 showed that LRPPRC level was negatively associated with ER and PR expression, while METTL16, RBM15B, ZC3H13 level was positively linked with ER and PR expression. In HER-2 (+) breast cancer patients, the expression of LRPPRC, METTL16, RBM15B, and ZC3H13 were all lower than the HER-2 (−) group.ConclusionThe significant difference in expression levels and prognostic value of m6A RNA methylation regulators were analyzed and validated in this study. This signature revealed the potential therapeutic value of m6A RNA methylation regulators in breast cancer.

scholarly journals Tumor infiltrating immune cells (TIICs) as a biomarker for prognosis benefits in patients with osteosarcoma

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ying Chen ◽  
Bo Zhao ◽  
Xiaohu Wang
Keyword(s):  
Risk Score ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Cell ◽  
Cell Types ◽  
Difficult Problem ◽  
Model Base ◽  
Model Based ◽  
Kaplan Meier ◽  
Score Model

Abstract Background Osteosarcoma is a rare malignant bone tumor in adolescents and children. Poor prognosis has always been a difficult problem for patients with osteosarcoma. Recent studies have shown that tumor infiltrating immune cells (TIICs) are associated with the clinical outcome of osteosarcoma patients. The aim of our research was to construct a risk score model based on TIICs to predict the prognosis of patients with osteosarcoma. Methods CIBERSORTX algorithm was used to calculate the proportion of 22 TIIC types in osteosarcoma samples. Kaplan-Meier curves were drawn to investigate the prognostic value of 22 TIIC types. Forward stepwise approach was used to screen a minimal set of immune cell types. Multivariate Cox PHR analysis was performed to construct an immune risk score model. Results Osteosarcoma samples with CIBERSORTX output p value less than 0.05 were selected for research. Kaplan-Meier curves indicated that naive B cells (p = 0.047) and Monocytes (p = 0.03) in osteosarcoma are associated with poor prognosis. An immune risk score model was constructed base on eight immune cell types, and the ROC curve showed that the immune risk score model is reliable in predicting the prognosis of patients with osteosarcoma (AUC = 0.724). Besides, a nomogram model base on eight immune cell types was constructed to predict the survival rate of patients with osteosarcoma. Conclusions TIICs are closely related to the prognosis of osteosarcoma. The immune risk score model based on TIICs is reliable in predicting the prognosis of osteosarcoma.

Low TWEAK expression indicates poor survival and is correlated with sparse TIICs in lung adenocarcinoma (LUAD).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21017-e21017
Author(s):  
Jinchun Wu ◽  
Xianyu Liu ◽  
Yanhua Mou ◽  
Shan Zeng ◽  
Jin Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Lung Adenocarcinoma ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Immune Escape ◽  
Underlying Mechanism ◽  
Memory Cd8 T Cells ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

e21017 Background: Lung adenocarcinoma (LUAD) occupies the most of non-small cell lung cancer (NSCLC) and shows promising response to PD-1 immunotherapy, but immune escape will cause treatment failure indicating poor prognosis. TWEAK (Tumor necrosis factor-related weak inducer of apoptosis, also known as TNFSF12) combining with its receptor FN14 (fibroblast growth factor–inducible 14) mediates crucial innate and adaptive immune pathways to promote the progression of multiple autoimmune diseases. So we assumed that TWEAK is a prognostic predictor and related with tumor-infiltrating immune cells (TIICs) in LUAD. Methods: TWEAK expression of LUAD was primarily investigated in The Cancer Immunome Atlas (TCIA) and then validated in Tumor Immune Estimation Resource (TIMER) databases. We assessed the effect of TWEAK on the survival via the Kaplan-Meier plotter, GEPIA2 (gene expression profiling interactive analysis) and PrognoScan databases. The relation between TWEAK and TIICs was explored in TIMER and TCIA, as well as the correlation of TWEAK and FN14 was analyzed in TIMER and GEPIA2. Results: Low TWEAK expression was significantly associated with poor relapse-free survival (RFS) (HR = 0.62, 95% CI = 0.4~0.97, logrank P = 0.035) and overall survival (OS) (HR = 0.61, 95% CI = 0.46~0.83, logrank P = 0.0012) in LUAD from Kaplan-Meier plotter. Similar impacts of TWEAK on the survival were validated in GEPIA2 and four independent cohorts from PrognoScan (jacob-00182-CANDF, GSE13213, jacob-00182-MSK and GSE31210). Moreover, reduced TWEAK expression was closely related with the paucity of TIICs which contributed to poor OS, including central memory CD8 T cells, plasmacytoid dendritic cells, activated CD8 T cells, monocytes, T follicular helper cells, immature B cells and eosinophils. In addition, TWEAK expression was positively related with the expression level of FN14 in both GEPIA2(R = 0.13, P= 0.0031) and TIMER (partial.cor = 0.212, P= 2.04e-06). Conclusions: Low TWEAK expression maybe indicate poor prognosis in LUAD, and correlated with the impaired infiltration of immune cells in the tumor region. The defective TWEAK/FN14 pathway possibly accounts for these observations, but the underlying mechanism needs to be further explored.

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