scholarly journals Exonuclease 1 (EXO1) is a Potential Prognostic Biomarker and Correlates with Immune Infiltrates in Lung Adenocarcinoma

2021 ◽  
Vol Volume 14 ◽  
pp. 1033-1048
Author(s):  
Chang-shuai Zhou ◽  
Ming-tao Feng ◽  
Xin Chen ◽  
Yang Gao ◽  
Lei Chen ◽  
...  
Oncogene ◽  
2021 ◽  
Vol 40 (13) ◽  
pp. 2463-2478
Author(s):  
Mohamad Moustafa Ali ◽  
Mirco Di Marco ◽  
Sagar Mahale ◽  
Daniel Jachimowicz ◽  
Subazini Thankaswamy Kosalai ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Lianxiang Luo ◽  
Yushi Zheng ◽  
Zhiping Lin ◽  
Xiaodi Li ◽  
Xiaoling Li ◽  
...  

It has attracted growing attention that the role of serine hydroxy methyl transferase 2 (SHMT2) in various types of cancers. However, the prognostic role of SHMT2 in lung adenocarcinoma (LUAD) and its relationship with immune cell infiltration is not clear. In this study, the information of mRNA expression and clinic data in LUAD were, respectively, downloaded from the GEO and TCGA database. We conducted a biological analysis to select the signature gene SHMT2. Online databases including Oncomine, GEPIA, TISIDB, TIMER, and HPA were applied to analyze the characterization of SHMT2 expression, prognosis, and the correlation with immune infiltration in LUAD. The mRNA expression and protein expression of SHMT2 in LUAD tissues were higher than in normal tissue. A Kaplan-Meier analysis showed that patients with lower expression level of SHMT2 had a better overall survival rate. Multivariate analysis and the Cox proportional hazard regression model revealed that SHMT2 expression was an independent prognostic factor in patients with LUAD. Meanwhile, the gene SHMT2 was highly associated with tumor-infiltrating lymphocytes in LUAD. These results suggest that the SHMT2 gene is a promising candidate as a potential prognostic biomarker and highly associated with different types of immune cell infiltration in LUAD.


2021 ◽  
Vol 12 ◽  
Author(s):  
Jianlin Chen ◽  
Junping Ding ◽  
Wenjie Huang ◽  
Lin Sun ◽  
Jinping Chen ◽  
...  

Previous researches have highlighted that low-expressing deoxyribonuclease1-like 3 (DNASE1L3) may play a role as a potential prognostic biomarker in several cancers. However, the diagnosis and prognosis roles of DNASE1L3 gene in lung adenocarcinoma (LUAD) remain largely unknown. This research aimed to explore the diagnosis value, prognostic value, and potential oncogenic roles of DNASE1L3 in LUAD. We performed bioinformatics analysis on LUAD datasets downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analyzed with various online databases. We found that both the mRNA and protein levels of DNASE1L3 in patients with LUAD were noticeably lower than that in normal tissues. Low DNASE1L3 expression was significantly associated with higher pathological stages, T stages, and poor prognosis in LUAD cohorts. Multivariate analysis revealed that DNASE1L3 was an independent factor affecting overall survival (HR = 0.680, p = 0.027). Moreover, decreased DNASE1L3 showed strong diagnostic efficiency for LUAD. Results indicated that the mRNA level of DNASE1L3 was positively correlated with the infiltration of various immune cells, immune checkpoints in LUAD, especially with some m6A methylation regulators. In addition, enrichment function analysis revealed that the co-expressed genes may participate in the process of intercellular signal transduction and transmission. GSEA indicated that DNASE1L3 was positively related to G protein-coupled receptor ligand biding (NES = 1.738; P adjust = 0.044; FDR = 0.033) and G alpha (i) signaling events (NES = 1.635; P adjust = 0.044; FDR = 0.033). Our results demonstrated that decreased DNASE1L3 may serve as a novel diagnostic and prognostic biomarker associating with immune infiltrates in lung adenocarcinoma.


2018 ◽  
Vol 99 ◽  
pp. 363-368 ◽  
Author(s):  
Jiabi Qin ◽  
Huacheng Ning ◽  
Yao Zhou ◽  
Yue Hu ◽  
Lina Yang ◽  
...  

2018 ◽  
Vol 9 (8) ◽  
pp. 924-930 ◽  
Author(s):  
Shicheng Li ◽  
Xiao Sun ◽  
Shuncheng Miao ◽  
Tong Lu ◽  
Yuanyong Wang ◽  
...  

2021 ◽  
Vol 16 (10) ◽  
pp. S1144
Author(s):  
X. Jin ◽  
N. Zhou ◽  
L. Zu ◽  
J. He ◽  
L. Yang ◽  
...  

2020 ◽  
Vol 10 ◽  
Author(s):  
Huan Zhao ◽  
Chunlei Zheng ◽  
Yizhe Wang ◽  
Kezuo Hou ◽  
Xianghong Yang ◽  
...  

2014 ◽  
Author(s):  
Ramdane Harouaka ◽  
Xin Liu ◽  
Waleed Khan ◽  
Tasleema Khan ◽  
Ayeh Asiaii ◽  
...  

2014 ◽  
Vol 105 (4) ◽  
pp. 490-497 ◽  
Author(s):  
Yoshihiko Murata ◽  
Yuko Minami ◽  
Reika Iwakawa ◽  
Jun Yokota ◽  
Shingo Usui ◽  
...  

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