NPM1 Is a Prognostic Biomarker Involved in Immune Infiltration of Lung Adenocarcinoma and Associated With m6A Modification and Glycolysis

BackgroundOverexpression of NPM1 can promote the growth and proliferation of various tumor cells. However, there are few studies on the comprehensive analysis of NPM1 in lung adenocarcinoma (LUAD).MethodsTCGA and GEO data sets were used to analyze the expression of NPM1 in LUAD and clinicopathological analysis. The GO/KEGG enrichment analysis of NPM1 co-expression and gene set enrichment analysis (GSEA) were performed using R software package. The relationship between NPM1 expression and LUAD immune infiltration was analyzed using TIMER, GEPIA database and TCGA data sets, and the relationship between NPM1 expression level and LUAD m6A modification and glycolysis was analyzed using TCGA and GEO data sets.ResultsNPM1 was overexpressed in a variety of tumors including LUAD, and the ROC curve showed that NPM1 had a certain accuracy in predicting the outcome of tumors and normal samples. The expression level of NPM1 in LUAD is significantly related to tumor stage and prognosis. The GO/KEGG enrichment analysis indicated that NPM1 was closely related to translational initiation, ribosome, structural constituent of ribosome, ribosome, Parkinson disease, and RNA transport. GSEA showed that the main enrichment pathway of NPM1-related differential genes was mainly related to mTORC1 mediated signaling, p53 hypoxia pathway, signaling by EGFR in cancer, antigen activates B cell receptor BCR leading to generation of second messengers, aerobic glycolysis and methylation pathways. The analysis of TIMER, GEPIA database and TCGA data sets showed that the expression level of NPM1 was negatively correlated with B cells and NK cells. The TCGA and GEO data sets analysis indicated that the NPM1 expression was significantly correlated with one m6A modifier related gene (YTHDF2) and five glycolysis related genes (ENO1, HK2, LDHA, LDHB and SLC2A1).ConclusionNPM1 is a prognostic biomarker involved in immune infiltration of LUAD and associated with m6A modification and glycolysis. NPM1 can be used as an effective target for diagnosis and treatment of LUAD.

Download Full-text

Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.681277 ◽

2021 ◽

Vol 12 ◽

Author(s):

Guomin Wu ◽

Qihao Wang ◽

Ting Zhu ◽

Linhai Fu ◽

Zhupeng Li ◽

...

Keyword(s):

Regression Analysis ◽

Lung Adenocarcinoma ◽

Clinical Features ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Immune Infiltration

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan–Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.

Download Full-text

CLDN6 and CLDN10 are Associated with Immune Infiltration of Ovarian Cancer: A Study of Claudin Family

10.21203/rs.3.rs-40048/v1 ◽

2020 ◽

Author(s):

Peipei Gao ◽

Ting Peng ◽

Canhui Cao ◽

Shitong Lin ◽

Ping Wu ◽

...

Keyword(s):

Ovarian Cancer ◽

T Cell ◽

Tumor Microenvironment ◽

Immune Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Markers ◽

Immune Infiltration ◽

Kaplan Meier ◽

The Relationship

Abstract Background: Claudin family is a group of membrane proteins related to tight junction. There are many studies about them in cancer, but few studies pay attention to the relationship between them and the tumor microenvironment. In our research, we mainly focused on the genes related to the prognosis of ovarian cancer, and explored the relationship between them and the tumor microenvironment of ovarian cancer.Methods: The cBioProtal provided the genetic variation pattern of claudin gene family in ovarian cancer. The ONCOMINE database and Gene Expression Profiling Interactive Analysis (GEPIA) were used to exploring the mRNA expression of claudins in cancers. The prognostic potential of these genes was examined via Kaplan-Meier plotter. Immunologic signatures were enriched by gene set enrichment analysis (GSEA). The correlations between claudins and the tumor microenvironment of ovarian cancer were investigated via Tumor Immune Estimation Resource (TIMER).Results: In our research, claudin genes were altered in 363 (62%) of queried patients/samples. Abnormal expression levels of claudins were observed in various cancers. Among them, we found that CLDN3, CLDN4, CLDN6, CLDN10, CLDN15 and CLDN16 were significantly correlated with overall survival of patients with ovarian cancer. GSEA revealed that CLDN6 and CLDN10 were significantly enriched in immunologic signatures about B cell, CD4 T cell and CD8 T cell. What makes more sense is that CLDN6 and CLDN10 were found related to the tumor microenvironment. CLDN6 expression was negatively correlated with immune infiltration level in ovarian cancer, and CLDN10 expression was positively correlated with immune infiltration level in ovarian cancer. Further study revealed the CLDN6 expression level was negatively correlated with gene markers of various immune cells in ovarian cancer. And, the expression of CLDN10 was positive correlated with gene markers of immune cells in ovarian cancer.Conclusions: CLDN6 and CLDN10 were prognostic biomarkers, and correlated with immune infiltration in ovarian cancer. Our results revealed new roles for CLDN6 and CLDN10, and they were potential therapeutic targets in the treatment of ovarian cancer.

Download Full-text

Significance of CD47 and Its Association With Tumor Immune Microenvironment Heterogeneity in Ovarian Cancer

Frontiers in Immunology ◽

10.3389/fimmu.2021.768115 ◽

2021 ◽

Vol 12 ◽

Author(s):

Lan Yu ◽

Yi Ding ◽

Ting Wan ◽

Ting Deng ◽

He Huang ◽

...

Keyword(s):

Ovarian Cancer ◽

Tumor Microenvironment ◽

Single Cell ◽

Prognostic Biomarker ◽

Gene Set Enrichment Analysis ◽

Cancer Prognosis ◽

Expression Level ◽

Immune Microenvironment ◽

Immune Infiltration ◽

Tumor Immune Microenvironment

BackgroundIt was reported that tumor heterogeneity and the surrounding tumor microenvironment (TME) in ovarian cancer affects immunotherapy efficacy and patient outcomes. And the TME of ovarian cancer is intrinsically heterogeneous. CD47 plays vital roles in cell functional behavior and immune homeostasis relating to cancer prognosis. But how it affects TME and its contribution to heterogeneity in ovarian cancer has not been fully illustrated. Therefore, we aimed to identify a prognostic biomarker which may help explain tumor immune microenvironment heterogeneity of ovarian cancer.MethodsCancer single-cell state atlas (CancerSEA) was used to evaluate functional role of CD47. Several bioinformatics database including Oncomine, Gene Expression Profiling Interaction Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), The Human Protein Atlas (HPA), Ualcan and Kaplan-Meier plotter (KM plotter) were applied to illustrate correlation of CD47 with ovarian cancer prognosis and immune infiltration. Tumor Immune Single-cell Hub (TISCH) single cell database was employed to evaluate correlation of CD47 with tumor microenvironment. GeneMANIA was implemented to identify regulation networks of CD47. Differentially expressed genes (DEGs) between CD47 high and low expression groups were analyzed with R package DESeq2. Kyoto encyclopedia of genes and genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were utilized to explore how CD47 affect the immune related cell signaling pathway.ResultsCD47 expression was upregulated and connected to worse OS and PFS in ovarian cancer. Close relation was found between CD47 expression level and immune infiltration in ovarian cancer, especially with Treg cells, Monocytes, Macrophages and T cell exhaustion (P<0.05). The CD47 expression level was relatively low in plasma cells, dendritic cells and Mono/Macro cells of OV_GSE115007, in myofibroblasts, fibroblasts and endothelial cells of OV_GSE118828, compared to malignant cells of OV_GSE118828 dataset. The cell components and distribution in primary and metastatic ovarian cancer are quite distinct, which may lead to TME heterogeneity of ovarian cancer.ConclusionOur results indicated that CD47 is closely correlated to ovarian cancer immune microenvironment and might induce ovarian cancer heterogeneity. Therefore, CD47 may be used as a candidate prognostic biomarker and provide us with new insights into potential immunotherapy in ovarian cancer patients.

Download Full-text

Significance of HMMR Overexpression in Hepatocellular Carcinoma

10.21203/rs.3.rs-1100876/v1 ◽

2022 ◽

Author(s):

Weidong Zhao ◽

Zhengxiang Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Progression ◽

Enrichment Analysis ◽

Progression Free Survival ◽

Expression Level ◽

Marker Genes ◽

Surface Binding ◽

Free Survival ◽

Immune Infiltration ◽

The Relationship

Abstract Background: Hyaluronan Mediated Motility Receptor (HMMR), as one of the key surface binding proteins of HA, is up-regulated in many tumors. What’s more, the expression level of HMMR is usually correlate with tumor progression and prognosis. However, the relationship between the expression of HMMR and the prognosis and immune infiltration of hepatocellular carcinoma (HCC) is still unclear.Methods: We analyzed the expression level of HMMR by TIMER database, GEO database and GEPIA database. The correlation between the HMMR expression and tumor prognosis was analyzed via the Kaplan-Meier plots. The TIMER database and GEPIA database were used to study the relationship between HMMR expression and immune infiltration. GO and KEGG enrichment analysis were used to explore the potential biological functions of HMMR.Results: HMMR expression was significantly higher in several human cancers, including HCC, than in corresponding normal tissues. High HMMR expression associated with poorer overall survival, disease-specific survival, progression-free survival and relapse-free survival in HCC patients. HMMR showed strong correlation with tumor-infiltrating B cells, CD4 + and CD8 + T cells, macrophages, neutrophils, and dendritic cells. Several immune marker genes expression, including CD86, IRF5, CD11b, KIRIDL4, CD11c, IFN-γ, STAT3, STAT5B, and CTLA4, have markedly positive correlations with HMMR expression. Enrichment analysis found that HMMR is mainly involved in cell cycle, DNA replication and repair, PLK1 pathway, E2F pathway, ATR pathway and AURORA B pathway.Conclusions: HMMR is a potential prognostic biomarker that influence tumor progression and correlated with tumor immune cells infiltration in HCC.

Download Full-text

Identification of HMMR as a prognostic biomarker for patients with lung adenocarcinoma via integrated bioinformatics analysis

PeerJ ◽

10.7717/peerj.12624 ◽

2021 ◽

Vol 9 ◽

pp. e12624

Author(s):

Zhaodong Li ◽

Hongtian Fei ◽

Siyu Lei ◽

Fengtong Hao ◽

Lijie Yang ◽

...

Keyword(s):

Cell Cycle ◽

Lung Adenocarcinoma ◽

Expression Analysis ◽

Prognostic Biomarker ◽

Enrichment Analysis ◽

Core Gene ◽

Potential Functions ◽

Gene Set Enrichment Analysis ◽

Cox Regression Analysis ◽

The Core

Background Lung adenocarcinoma (LUAD) is the most prevalent tumor in lung carcinoma cases and threatens human life seriously worldwide. Here we attempt to identify a prognostic biomarker and potential therapeutic target for LUAD patients. Methods Differentially expressed genes (DEGs) shared by GSE18842, GSE75037, GSE101929 and GSE19188 profiles were determined and used for protein-protein interaction analysis, enrichment analysis and clinical correlation analysis to search for the core gene, whose expression was further validated in multiple databases and LUAD cells (A549 and PC-9) by quantitative real-time PCR (qRT-PCR) and western blot analyses. Its prognostic value was estimated using the Kaplan-Meier method, meta-analysis and Cox regression analysis based on the Cancer Genome Atlas (TCGA) dataset and co-expression analysis was conducted using the Oncomine database. Gene Set Enrichment Analysis (GSEA) was performed to illuminate the potential functions of the core gene. Results A total of 115 shared DEGs were found, of which 24 DEGs were identified as candidate hub genes with potential functions associated with cell cycle and FOXM1 transcription factor network. Among these candidates, HMMR was identified as the core gene, which was highly expressed in LUAD as verified by multiple datasets and cell samples. Besides, high HMMR expression was found to independently predict poor survival in patients with LUAD. Co-expression analysis showed that HMMR was closely related to FOXM1 and was mainly involved in cell cycle as suggested by GSEA. Conclusion HMMR might be served as an independent prognostic biomarker for LUAD patients, which needs further validation in subsequent studies.

Download Full-text

Wnt pathway-related three-mRNA clinical outcome signature in bladder urothelial carcinoma: computational biology and experimental analyses

Journal of Translational Medicine ◽

10.1186/s12967-021-03061-4 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Siqing Sun ◽

Yutao Wang ◽

Jianfeng Wang ◽

Jianbin Bi

Keyword(s):

Wnt Signaling ◽

Signaling Pathway ◽

Wnt Pathway ◽

Cox Regression ◽

Wnt Signaling Pathway ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Immune Infiltration ◽

The Relationship

Abstract Background The Wnt signaling pathway is core to the growth of bladder tumors. Epithelial-to-mesenchymal transition (EMT) is significant for bladder tumor metastasis. Nevertheless, the relationship between the Wnt signaling pathway, outcomes of bladder cancer (BLCA), and the specific mechanisms driving immune infiltration have not been studied. Methods We obtained Wnt pathway-related gene mRNA and clinicopathological data from the Cancer Genome Atlas (TCGA). We obtained 34 genes that were greatly correlated with outcome using univariate Cox regression analysis and conducted a completely randomized data t-test to perform clinical staging. According to the single-sample gene set enrichment analysis (ssGSEA), the weighted correlation network analysis (WGCNA) was applied to identify relevant biological functions. Various subtypes were identified using consensus cluster analysis. Univariate Cox regression and least absolute shrinkage sum selection operator–Cox regression algorithm analysis were conducted on TCGA and Gene Expression Omnibus data to identify risk characteristics. The Kaplan–Meier method and receiver running feature curves were adopted to calculate overall survival. Single-sample gene set enrichment analysis (ssGSEA) was adopted for the assessment of the degree of immune infiltration. Then, we demonstrated the relationship between PPP2CB and EMT function in two cell lines. Results Thirty-four Wnt signaling pathway-related genes were risk factors for BLCA outcome, and their expression levels differed by clinical stage. The co-expression of WGCNA showed the relationship between the Wnt signaling pathway and biological functions and was closely associated with EMT. We divided BLCA patients into two subtypes using consensus clustering. Survival curves and clinical analysis showed that the Wnt pathway enriched group had worse outcomes. The Wnt signature showed the significance of the outcome for MAPK10, PPP2CB, and RAC3. Based on these genes, the degree of immune infiltration was evaluated. Cell function experiments suggested that PPP2CB drives the proliferation and migration of BLCA cells. Conclusion We found that Wnt signaling pathway-related genes can be used as prognostic risk factors for BLCA, and the Wnt signaling pathway is a cancer-promoting signaling pathway associated with EMT. We identified three critical genes: MAPK10, RAC3, and PPP2CB. The genes in these three Wnt signaling pathways are associated with tumor cell EMT and immune cell infiltration. The most important finding was that these three genes were independent prognostic factors for BLCA.

Download Full-text

GPR143 is a Prognostic Biomarker Associated with Immune Infiltration in Melanoma

10.21203/rs.3.rs-430494/v1 ◽

2021 ◽

Author(s):

Zixuan Xing ◽

Shaobo Wu ◽

Qijuan Zang ◽

Hao Lei ◽

Yi Wei ◽

...

Keyword(s):

G Protein ◽

Prognostic Biomarker ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Congenital Nystagmus ◽

Immune Infiltration ◽

Interactive Analysis ◽

Tcga Dataset ◽

Cox Analysis ◽

G Protein Coupled

Abstract Background: Skin cutaneous melanoma (SKCM) is considered one of the most aggressive and lethal cancers of the skin. G-protein coupled receptor 143 (GPR143), which has been reported to cause congenital nystagmus, belongs to the superfamily of G protein-coupled receptors. Methods and Results: We analyzed the expression of GPR143 and survival of SKCM patients in SKCM via Gene Expression Profiling Interactive Analysis (GEPIA). Then, logistic regression and multivariate cox analysis was used to analyze the influence of GPR143 expression on clinicopathological elements and survival. We explored the immune response of 22 TIICs in SKCM via CIBERSORT and used TIMER to assess the correlation of GPR143 expression and immune infiltration level. Finally, we used gene set enrichment analysis (GSEA) to assess the TCGA dataset. The outcomes suggest that GPR143 expression in tumor samples is remarkedly higher than in normal samples and high GPR143 expression is associated with poorer prognosis. The result of multivariate analysis indicated that increased GPR143 expression is an independent prognostic factor for prognosis. We found GPR143 expression level has prominent negative correlations with infiltrating levels of B cell, CD8+ T cells, etc. GSEA indicated that pigment metabolic process, pigment biosynthetic process and other pathways were identified as differentially enriched pathways in Gene Ontology (GO). Oxidative phosphorylation, Parkinson’s disease and other pathways were showed significantly differential enrichment in GPR143 high expression phenotype in Kyoto Encyclopedia of Genes and Genomes (KEGG).Conclusions: In conclusion, GPR143 may be a novel prognostic biomarker and associated with immune infiltrates in SKCM.

Download Full-text

NRAS Expression is Associated With Prognosis and Tumor Immune Microenvironment in Lung Adenocarcinoma

10.21203/rs.3.rs-862652/v1 ◽

2021 ◽

Author(s):

Yueren Yan ◽

Zhendong Gao ◽

Han Han ◽

Yue Zhao ◽

Yang Zhang ◽

...

Keyword(s):

T Cells ◽

Lung Adenocarcinoma ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Immune Microenvironment ◽

Kaplan Meier ◽

Tumor Immune Microenvironment ◽

Cox Analysis

Abstract Purpose: NRAS plays a pivotal role in progression of various kinds of somatic malignancies; however, the correlation between NRAS and lung adenocarcinoma is less known. We aim to analyze the prognostic value of NRAS expression in lung adenocarcinoma, and explore the relationship between NRAS and tumor immune microenvironment. Methods: We obtained the transcriptome pofiles and clinical data of LUAD from The Cancer Genome Atlas database and three Genome Expression Omnibus datasets. Specimens from 325 patients with completely resected lung adenocarcinoma were collected for immunohistochemical assays of NRAS, PD-L1, PD-1 and TIM-3. Then we performed gene set enrichment analysis to investigate cancer-related and immune-related signaling pathways. TIMER algorithms were performed to evaluate tumor immune infiltrating cells and immune-related biomarkers.Results: Compared with adjacent non-tumor tissue, NRAS expression was significantly upregulated in LUAD tissue. NRAS expression was significantly correlated with more advanced stage and positive lymph nodes. Kaplan-Meier curves and Cox analysis suggested that high NRAS expression led to a poor prognosis, and could be an independent prognostic factor in LUAD patients. Besides, NRAS expression was positively correlated with CD8+ T cells, macrophages, and neutrophils, and negatively correlated with B cells and CD4+ T cells. The expression level of NRAS was positively correlated with PD-L1, PD-1, and TIM-3 both at RNA and protein level. Conclusions: To conclude, we found NRAS a novel prognostic biomarker in LUAD. Besides, the expression level of NRAS may influence the prognosis of LUAD via various kinds of cancer-related pathways and remodeling TIM.

Download Full-text

HSF2 is a Promising Prognostic Biomarker and is Correlated With Immune Infiltration in Hepatocellular Carcinoma

10.21203/rs.3.rs-89953/v1 ◽

2020 ◽

Author(s):

Bihui Han ◽

Yanxiu Meng ◽

Yumei Fan ◽

Bing Liu ◽

Jiajie Hou ◽

...

Keyword(s):

Immune Cells ◽

Critical Role ◽

Enrichment Analysis ◽

Normal Liver ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Immune Infiltration ◽

Kaplan Meier ◽

The Relationship ◽

Kaplan Meier Plotter

Abstract BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies on the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. MethodsThe TCGA, Oncomine, UALCAN, HCCDB and HPA databases were used to investigate HSF2 expression in HCC. Kaplan-Meier plotter, GEPIA and HCCDB databases were used to evaluate the association of HSF2 with the prognosis of HCC patients. Genetic alteration of HSF2 was examined by the cBioPortal database. The mechanism was investigated with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GESA), and the relationship between HSF2 expression and immune infiltration was explored through the TIMER database and CIBERSORT algorithm.Results In the present study, we found that HSF2 expression was significantly upregulated in HCC compared with normal liver tissues. High HSF2 expression was associated with poor survival in HCC patients. GO, KEGG and GESA analyses demonstrated that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC. ConclusionsIn summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

Download Full-text

Diagnostic Biomarker KIF23 is Associated With Immune Infiltration in Gastric Cancer

10.21203/rs.3.rs-778412/v1 ◽

2021 ◽

Author(s):

Maoshu Bai ◽

Xin Liu

Keyword(s):

Gastric Cancer ◽

Area Under The Curve ◽

Enrichment Analysis ◽

Progression Free Survival ◽

Roc Curves ◽

Diagnostic Value ◽

Expression Level ◽

Diagnostic Biomarker ◽

Immune Infiltration ◽

The Relationship

Abstract Background: Kinesin family member 23 (KIF23), an index of tumor proliferation, can serve as a prognostic marker in numerous tumors. However, the relationship between KIF23 expression and immune infiltration and the diagnostic value of KIF23 remain unclear in GC (gastric cancer). This study aimed to explored the diagnostic value of KIF23 and its interactions with tumor-infiltrating immune cells in GC by bioinformatics analysis. Mothods: The relationship between clinicopathologic features and KIF23 expression was also analyzed using the Wilcoxon rank-sum test and logistic regression. And the expression level of KIF23 was validated by IHC and GEO databases, which was consistent with informatics results. Receiver operating characteristic (ROC) curves were generated to evaluate the value of KIF23 as a binary classifier using the area under the curve (AUC value).Results: High expression of KIF23 was significantly associated with longer overall survival and progression-free survival in GC. The mutations of KIF23 in GC were analyzed using cBioPortal and the Catalogue of Somatic Mutations in Cancer database. Enrichment analysis of co-expressed genes and KIF23 analysis was performed using LinkedOmics. By using STRING and GeneMANIA databases, we investigated the protein-coding genes related to KIF23 and its co-expression genes in GC tissues. Then, the relationship between KIF23 expression and immune infiltration in GC was investigated using Timer and GEPIA. We found that KIF23 might be used as a potential diagnostic biomarker in GC. Subsequently, KIF23 expression level was correlated with the infiltration levels of CD8 + T cells, macrophages, neutrophils, and more obviously with B cells and dendritic cells. In addition, KIF23 expression was significantly associated with T cell exhaustion (CTLA-4 and GZMB). KIF23 expression showed correlations with the infiltration of diverse immune markers in GC. Conclusions: Our findings suggest KIF23 can serve as a marker for immune infiltration and diagnostic in GC, making it a potential treatment of target.

Download Full-text