scholarly journals LACTB mRNA expression is increased in pancreatic adenocarcinoma and high expression indicates a poor prognosis

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245908
Author(s):  
Jian Xie ◽  
Yang Peng ◽  
Xiaoyu Chen ◽  
Qigang Li ◽  
Bin Jian ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Pancreatic Adenocarcinoma ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
Vital Status ◽  
Immune Marker ◽  
Kaplan Meier ◽  
Cancer Tissues

This study aimed to find the prognostic value of Beta-lactamase-like (LACTB) in pancreatic adenocarcinoma (PAAD) patients. The mRNA expression of LACTB was upregulated in PAAD and was correlated with vital status (P = 0.0199). The immunoreactive scores of LACTB protein in human PAAD tissues were significantly higher than those in adjacent noncancerous pancreatic tissues. Receiver operating characteristic (ROC) curve assessment showed that LACTB mRNA expression has high diagnostic value in PAAD. Kaplan-Meier curve and Cox analyses suggested that patients with high LACTB mRNA expression have a poor prognosis, indicating that LACTB mRNA is an independent prognostic factor for overall survival [hazard ratio (HR) = 1.72, P = 0.015, 95% confidence interval (CI) = 1.106–2.253] and disease-specific survival (HR = 1.97, P = 0.004, 95% CI = 1.238–3.152) of PAAD patients. Gene set enrichment analysis (GSEA) revealed that hallmark_g2m_checkpoint, hallmark_myc_targets_v1, hallmark_e2f_targets, and kegg_cell_cycle were differentially enriched in phenotypes with high LACTB expression. In addition, CDC20, CDK4, MCM6, MAD2L1, MCM2 and MCM5 were leading genes intersecting in these four pathways, and a positive correlation between mRNA expression and LACTB was observed in most normal and cancer tissues. Finally, elevated LACTB mRNA expression was significantly related to multiple immune marker sets. Our results elucidate that LACTB is involved in the development of cancer, and that high LACTB expression in patients with PAAD can predict a poor prognosis. High LACTB expression was significantly correlated with cell cycle-related genes and multiple immune marker sets.

scholarly journals Low UGP2 Expression Is Associated with Tumour Progression and Predicts Poor Prognosis in Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Qiuyue Hu ◽  
Shen Shen ◽  
Jianhao Li ◽  
Liwen Liu ◽  
Xin Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Tumour Progression ◽  
Enrichment Analysis ◽  
Malignant Tumour ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
Uridine Diphosphate ◽  
Roc Curve Analysis

Hepatocellular carcinoma (HCC) is a malignant tumour associated with a high mortality rate and poor prognosis worldwide. Uridine diphosphate-glucose pyrophosphorylase 2 (UGP2), a key enzyme in glycogen biosynthesis, has been reported to be associated with the occurrence and development of various cancer types. However, its diagnostic value and prognostic value in HCC remain unclear. The present study observed that UGP2 expression was significantly downregulated at both the mRNA and protein levels in HCC tissues. Receiver operating characteristic (ROC) curve analysis revealed that UGP2 may be an indicator for the diagnosis of HCC. In addition, Kaplan-Meier and Cox regression multivariate analyses indicated that UGP2 is an independent prognostic factor of overall survival (OS) in patients with HCC. Furthermore, gene set enrichment analysis (GSEA) suggested that gene sets negatively correlated with the survival of HCC patients were enriched in the group with low UGP2 expression levels. More importantly, a significant correlation was identified between low UGP2 expression and fatty acid metabolism. In summary, the present study demonstrates that UGP2 may contribute to the progression of HCC, indicating a potential therapeutic target for HCC patients.

scholarly journals CDCA8 as an independent predictor for a poor prognosis in liver cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yu Shuai ◽  
Erxi Fan ◽  
Qiuyue Zhong ◽  
Qiying Chen ◽  
Guangyong Feng ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Liver Cancer ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Gene Set Enrichment Analysis ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Wilcoxon Rank Sum Test ◽  
Cancer Tissues

Abstract Background Human cell division cycle associated 8 (CDCA8) a key regulator of mitosis, has been described as a potential prognostic biomarker for a variety of cancers, such as breast, colon and lung cancers. We aimed to evaluate the potential role of CDCA8 expression in the prognosis of liver cancer by analysing data from The Cancer Genome Atlas (TCGA). Methods The Wilcoxon rank-sum test was used to compare the difference in CDCA8 expression between liver cancer tissues and matched normal tissues. Then, we applied logistic regression and the Wilcoxon rank-sum test to identify the association between CDCA8 expression and clinicopathologic characteristics. Cox regression and the Kaplan–Meier method were used to examine the clinicopathologic features correlated with overall survival (OS) in patients from the TCGA. Gene set enrichment analysis (GSEA) was performed to explore possible mechanisms of CDCA8 according to the TCGA dataset. Results CDCA8 expression was higher in liver cancer tissues than in matched normal tissues. Logistic regression and the Wilcoxon rank-sum test revealed that the increased level of CDCA8 expression in liver cancer tissues was notably related to T stage (OR = 1.64 for T1/2 vs. T3/4), clinical stage (OR = 1.66 for I/II vs. III/IV), histologic grade (OR = 6.71 for G1 vs. G4) and histological type (OR = 0.24 for cholangiocarcinoma [CHOL] vs. hepatocellular carcinoma [LIHC]) (all P-values < 0.05). Kaplan–Meier survival analysis indicated that high CDCA8 expression was related to a poor prognosis in liver cancer (P = 2.456 × 10−6). Univariate analysis showed that high CDCA8 expression was associated with poor OS in liver cancer patients, with a hazard ratio (HR) of 1.85 (95% confidence interval [CI]: 1.47–2.32; P = 1.16 × 10–7). Multivariate analysis showed that CDCA8 expression was independently correlated with OS (HR = 1.74; CI: 1.25–12.64; P = 1.27 × 10–5). GSEA revealed that the apoptosis, cell cycle, ErbB, MAPK, mTOR, Notch, p53 and TGF-β signaling pathways were differentially enriched in the CDCA8 high expression phenotype. Conclusions High CDCA8 expression is a potential molecular predictor of a poor prognosis in liver cancer.

scholarly journals CELSR3 mRNA expression is increased in hepatocellular carcinoma and indicates poor prognosis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7816 ◽  
Author(s):  
Xuefeng Gu ◽  
Hongbo Li ◽  
Ling Sha ◽  
Yuan Mao ◽  
Chuanbing Shi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mrna Expression ◽  
Cell Line ◽  
Roc Curve ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Dna Recombination ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier

Objective Hepatocellular carcinoma (HCC) is a disease that is associated with high mortality; currently, there is no curative and reliable treatment. Cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) is the key signaling molecule in the wingless and INT-1/planar cell polarity (WNT/PCP) pathway. This study aimed to elucidate the prognostic significance of CELSR3 in HCC patients. Methods The Cancer Genome Atlas (TCGA) database, the Cancer Cell Line Encyclopedia (CCLE) database and the Gene Expression Omnibus (GEO) database were used to analyze the expression of CELSR3 mRNA in HCC samples and cells. The relationship between CELSR3 mRNA and clinical features was assessed by the chi-square test. the diagnostic and predictive value of CELSR3 mRNA expression were analyzed using the receiver operating characteristic (ROC) curve. Kaplan–Meier curve and Cox regression analyses were performed to assess the prognostic value of CELSR3 mRNA in HCC patients. Finally, all three cohorts database was used for gene set enrichment analysis(GSEA) and the identification of CELSR3-related signal transduction pathways. Results The expression of CELSR3 mRNA was upregulated in HCC, and its expression was correlated with age (P = 0.025), tumor status (P = 0.022), clinical stage (P = 0.003), T classification (P = 0.010), vital status (P = 0.001), and relapse (P = 0.005). The ROC curve assessment indicated that CELSR3 mRNA expression has high diagnostic value in HCC and in the subgroup analysis of stage. In addition, the Kaplan-Meier curve and Cox analyses suggested that patients with high CELSR3 mRNA expression have a poor prognosis, indicating that CELSR3 mRNA is an independent prognostic factor for the overall survival of HCC patients. GSEA showed that GO somatic diversification of immune receptors, GO endonuclease activity, GO DNA repair complex and GO somatic cell DNA recombination, were differentially enriched in the meta-GEO cohort, the HCC cell line cohort and the TCGA cohort of the high CELSR3 mRNA expression phenotype. Conclusion Our results indicate that CELSR3 mRNA is involved in the progression of cancer and can be used as a biomarker for the prognosis of HCC patients.

scholarly journals Downregulated ZC3H13 by miR-362-3p/miR-425-5p is Associated with Poor Prognosis and Adverse Outcomes in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
shuang wu ◽  
Shihai Liu ◽  
Yongxian Cao ◽  
Chao Geng ◽  
Peng Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Human Cancer ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Adverse Outcomes ◽  
Gene Set Enrichment Analysis ◽  
Rna Modification ◽  
Kaplan Meier

Abstract Background: Hepatocellular carcinoma (HCC) is notorious for its poor prognosis. Increasing evidence has demonstrated that N6-methyladenosine (m6A) related genes plays key roles in initiation and progression of several types of human cancer. However, the specific role and mechanism of m6A RNA modification in HCC remains not fully determined. Previous studies identified that several m6A-related genes, especially ZC3H13, could be a high candidate as a novel biomarker and therapeutic target for hepatocellular carcinoma. In liver hepatocellular carcinoma (LIHC), the low expression of ZC3H13 was reported but the molecular reason is unclear.Methods: Oncomine and GEPIA databases were used to explore the differential expression of ZC3H13 in multiple cancers. Kaplan–Meier plotter was selected to explore the prognostic value of ZC3H13. The GSCALite database was used to analyze the genetic variation of the m6A-related genes. StarBase was selected to predict and analysis of upstream miRNAs of ZC3H13. MiR-362-3p/miR-425-5p mimics and inhibitors results detected by Quantitative Real-time PCR (qPCR) analysis and western blotting. Gene set enrichment analysis (GSEA) identified the potential regulatory mechanism of ZC3H13. In addition, we investigated the relationship between ZC3H13 and tumor infiltrating immune cells (TIICs). Finally, we determined the expression correlation of ZC3H13 with biomarkers of immune cells in HCC using GEPIA database.Results: In this study, we found that ZC3H13 expression was significantly correlated with both overall survival (OS) and progression-free survival (RFS) in LIHC patients based on a comprehensive analysis of the m6A family. Our experimental results indicate that inhibiting miR-362-3p/miR-425-5p expression in the LIHC cell line significantly restored the expression of ZC3H13, which is consistent with bioinformatic studies. Further, we noticed that there is a possible relationship between ZC3H13 high expression and tumor microenvironment infiltrating immune cells.Conclusions: In conclusion, this study demonstrates that ZC3H13 is a direct target of miR-362-3p/miR-425-5p in LIHC that regulates the immune modulations in the microenvironment of LIHC.

scholarly journals Overexpressed XRCC2 as an independent risk factor for poor prognosis in glioma patients

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Zhendong Liu ◽  
Wang Zhang ◽  
Xingbo Cheng ◽  
Hongbo Wang ◽  
Lu Bian ◽  
...  
Keyword(s):  
Risk Factor ◽  
Expression Pattern ◽  
Poor Prognosis ◽  
Independent Risk Factor ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cellular Mechanisms ◽  
Molecular Features ◽  
Meta Analyses

Abstract Background XRCC2, a homologous recombination-related gene, has been reported to be associated with a variety of cancers. However, its role in glioma has not been reported. This study aimed to find out the role of XRCC2 in glioma and reveal in which glioma-specific biological processes is XRCC2 involved based on thousands of glioma samples, thereby, providing a new perspective in the treatment and prognostic evaluation of glioma. Methods The expression characteristics of XRCC2 in thousands of glioma samples from CGGA and TCGA databases were comprehensively analyzed. Wilcox or Kruskal test was used to analyze the expression pattern of XRCC2 in gliomas with different clinical and molecular features. The effect of XRCC2 on the prognosis of glioma patients was explored by Kaplan–Meier and Cox regression. Gene set enrichment analysis (GSEA) revealed the possible cellular mechanisms involved in XRCC2 in glioma. Connectivity map (CMap) was used to screen small molecule drugs targeting XRCC2 and the expression levels of XRCC2 were verified in glioma cells and tissues by RT-qPCR and immunohistochemical staining. Results We found the overexpression of XRCC2 in glioma. Moreover, the overexpressed XRCC2 was associated with a variety of clinical features related to prognosis. Cox and meta-analyses showed that XRCC2 is an independent risk factor for the poor prognosis of glioma. Furthermore, the results of GSEA indicated that overexpressed XRCC2 could promote malignant progression through involved signaling pathways, such as in the cell cycle. Finally, doxazosin, quinostatin, canavanine, and chrysin were identified to exert anti-glioma effects by targeting XRCC2. Conclusions This study analyzed the expression pattern of XRCC2 in gliomas and its relationship with prognosis using multiple datasets. This is the first study to show that XRCC2, a novel oncogene, is significantly overexpressed in glioma and can lead to poor prognosis in glioma patients. XRCC2 could serve as a new biomarker for glioma diagnosis, treatment, and prognosis evaluation, thus bringing new insight into the management of glioma.

Robust Metabolic Transcriptional Components in 34,494 Patient-Derived Samples and Cell Lines

2021 ◽  
Author(s):  
Vincent Christiaan Leeuwenburgh ◽  
Carlos G. Urzúa-Traslaviña ◽  
Arkajyoti Bhattacharya ◽  
Marthe T.C. Walvoort ◽  
Mathilde Jalving ◽  
...  
Keyword(s):  
Cell Lines ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Metabolic Processes ◽  
Gene Sets ◽  
Transcriptional Changes ◽  
Cancer Tissues ◽  
Tumor Biopsies ◽  
Transcriptional Landscape

Abstract Background: Patient-derived bulk expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These profiles represent the average expression pattern of all heterogeneous tumor and non-tumor cells present in biopsies of tumor lesions. Hence, subtle transcriptional footprints of metabolic processes can be concealed by other biological processes and experimental artifacts. However, consensus Independent Component Analyses (c-ICA) can capture statistically independent transcriptional footprints, of both subtle and more pronounced metabolic processes. Methods: We performed c-ICA with 34,494 bulk expression profiles of patient-derived tumor biopsies, non-cancer tissues, and cell lines. Gene set enrichment analysis with 608 gene sets that describe metabolic processes was performed to identify transcriptional components enriched for metabolic processes (mTCs). The activity of these mTCs were determined in all samples to create a metabolic transcriptional landscape. Results: A set of 555 mTCs were identified of which many were robust across different datasets, platforms, and patient-derived tissues and cell lines. We demonstrate how the metabolic transcriptional landscape defined by the activity of these mTCs in samples can be used to explore associations between the metabolic transcriptome and drug sensitivities, patient outcomes, and the composition of the immune tumor microenvironment. Conclusions: To facilitate the use of our transcriptional metabolic landscape, we have provided access to all data via a web portal ( www.themetaboliclandscapeofcancer.com ). We believe this resource will contribute to the formulation of new hypotheses on how to metabolically engage the tumor or its (immune) microenvironment.

Transmembrane p24 Trafficking Protein 2 Regulates Inflammation Through the TLR4/NF-κB Signaling Pathway in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Longhua Feng ◽  
Pengjiang Cheng ◽  
Zhengyun Feng ◽  
Xiaoyu Zhang
Keyword(s):  
Lung Adenocarcinoma ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Inflammatory Factors ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
New Strategy

Abstract Background: To investigate the role of transmembrane p24 trafficking protein 2 (TMED2) in lung adenocarcinoma (LUAD) and determine whether TMED2 knockdown could inhibit LUAD in vitro and in vivo.Methods: TIMER2.0, Kaplan-Meier plotter, gene set enrichment analysis (GSEA), Target Gene, and pan-cancer systems were used to predict the potential function of TMED2. Western blotting and immunohistochemistry were performed to analyze TMED2 expression in different tissues or cell lines. The proliferation, development, and apoptosis of LUAD were observed using a lentivirus-mediated TMED2 knockdown. Bioinformatics and western blot analysis of TMED2 against inflammation via the TLR4/NF-κB signaling pathway were conducted. Results: TMED2 expression in LUAD tumor tissues was higher than that in normal tissues and positively correlated with poor survival in lung cancer and negatively correlated with apoptosis in LUAD. The expression of TMED2 was higher in tumors or HCC827 cells. TMED2 knockdown inhibited LUAD development in vitro and in vivo and increased the levels of inflammatory factors via the TLR4/NF-κB signaling pathway. TMED2 was correlated with TME, immune score, TME-associated immune cells, their target markers, and some mechanisms and pathways, as determined using the TIMER2.0, GO, and KEGG assays.Conclusions: TMED2 may regulate inflammation in LUAD through the TLR4/NF-κB signaling pathway, and enhance the proliferation, development, and prognosis of LUAD by regulating inflammation, which provide a new strategy for treating LUAD by regulating inflammation.

scholarly journals High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiming Wang ◽  
Yan Cai ◽  
Xuewen Fu ◽  
Liang Chen
Keyword(s):  
Cervical Cancer ◽  
Poor Prognosis ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Cervical Cancer Cells ◽  
Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

scholarly journals A Prognostic Autophagy-Related Long Non-coding RNA (ARlncRNA) Signature in Acute Myeloid Leukemia (AML)

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunxia Zhao ◽  
Yulu Wang ◽  
Famei Tu ◽  
Shuai Zhao ◽  
Xiaoying Ye ◽  
...  
Keyword(s):  
Cox Regression ◽  
Survival Curve ◽  
Pearson Correlation ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Novel Biomarkers ◽  
Meier Survival Curve

BackgroundSome studies have proven that autophagy and lncRNA play important roles in AML. Several autophagy related lncRNA signatures have been shown to affect the survival of patients in some other cancers. However, the role of autophagy related lncRNA in AML has not been explored yet. Hence, this study aims to find an autophagy related lncRNA signature that can affect survival for AML patients.MethodA Pearson correlation analysis, a Kaplan–Meier survival curve, a univariate cox regression, and a multivariate cox regression were performed to establish an autophagy related lncRNA signature. A univariate cox regression, a multivariate cox regression, a Kaplan–Meier survival curve, and a ROC curve were applied to confirm if the signature is an independent prognosis for AML patients. The relationship between the signature and the clinical features was explored by using a T test. Gene Set Enrichment Analysis (GSEA) was used to investigate the potential tumor related pathways.ResultsA four-autophagy related lncRNA (MIR133A1HG, AL359715.1, MIRLET7BHG, and AL356752.1) signature was established. The high risk score based on signature was related to the short survival time of AML patients. The signature was an independent factor for the prognosis for AML patients (HR = 1.684, 95% CI = 1.324–2.142, P &lt; 0.001). The signature was correlated with age, leukocyte numbers, and FAB (M3 or non-M3). The P53, IL6/JAK/STAT3, TNF-α, INF-γ, and IL2/STAT5 pathways might contribute to the differences between the risk groups based on signature in AML.ConclusionThe four autophagy related lncRNAs and their signature might be novel biomarkers for predicting the survival of AML patients. Some biological pathways might be the potential mechanisms of the signature for the survival of AML patients.

scholarly journals DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang-Jie Wu ◽  
Ai-Tao Nai ◽  
Gui-Cheng He ◽  
Fei Xiao ◽  
Zhi-Min Li ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
List Type ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. Methods Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. Results In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. Conclusions In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. Highlights Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. DPYSL2 can independently predict the LUAD outcomes. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

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